Emerging trends and challenges in information technology management 1-59904-019-0, 978-1-61692-128-6

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Em e rging Tre nds a nd Cha lle nge s in I nfor m at ion Te chnology M a na ge m e nt

2 0 0 6 I nform a t ion Re sourc e s M a na ge m e nt Assoc ia t ion I nt e rna t iona l Confe re nc e Wa shingt on, DC, U SA M a y 2 1 -2 4 , 2 0 0 6

M e hdi K hosrow -Pour I nform a t ion Re sourc e s M a na ge m e nt Assoc ia t ion, U SA

I DEA GROU P PU BLI SH I N G Hershey • London • Melbourne • Singapore Copyright © 2006, Idea Group Inc. Copying or distributing in print or electronic forms without written permission of Idea Group Inc. is prohibited.

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Published in the United States of America by Idea Group Publishing (an imprint of Idea Group Inc.) 701 E. Chocolate Avenue Hershey PA 17033 Tel: 717-533-8845 Fax: 717-533-8661 E-mail: [email protected] Web site: http://www.idea-group.com and in the United Kingdom by Idea Group Publishing (an imprint of Idea Group Inc.) 3 Henrietta Street Covent Garden London WC2E 8LU Tel: 44 20 7240 0856 Fax: 44 20 7379 0609 Web site: http://www.eurospanonline.com Copyright © 2006 by Idea Group Inc. All rights reserved. No part of this book may be reproduced in any form or by any means, electronic ro mechanical, including photocopying, without written permission from the publisher. ISBN 1-59904-019-0 (print version) ISBN 1-59904-020-4 (CD-ROM version)

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The manuscripts published in these proceedings were subject to a blind, peer review by at least three reviewers. Manuscripts are assigned to reviewers with specific expertise in the area of the paper. IRMA 2006 International Conference utilized 500+ expert reviewers, external to the conference organizing committee to complete the blind peer/expert review. Each manuscript is assigned to at least three expert reviewers adn is subject to a blind, peer review by these reviewers. A final decision is made based upon the recommendations of the reviewers.

Emerging Trends and Challenges in Information Technology Management (ISBN 1-59904-019-0) is printed in two volumes. Volume 1 covers pages 1-503. Volume 2 covers pages 504-1077.

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Table of Contents Accounting Information Systems A Risk-Based Approach to Auditing Relational Databases Wendy S. Walker and Jeffrey W. Merhout ................................ 9 3 2 Integrating Information Security and Assurance into MIS Curriculums Jeffrey W. Merhout and Douglas J. Havelka ............................. 8 8 3 Knowledge Dissemination Using a Hybrid of Teaching Techniques: Lessons Learned from the Case of The American University in Cairo Khaled Dahawy and Sherif Kamel .............................................. 1 0 4 5 The Design and Validation of a Knowledge-Based System for the Auditor’s Report Mohamed A. Wahdan, Pieter Spronck, Hamdi F. Ali, Eddy Vaassen, and H. Jaap van den Herik ............................................................. 3 6 2 The Effects of Contexts and Cognitive Characteristics on Accounting Information Processing: A Review of Behavioral Accounting and Cognitive Psychology Research Mohamed A. Elbannan ................................................................... 4 8 2 Agile Approaches to Systems Development Agile Practices, Promises of Rigor, and Information Systems Quality Sue Kong, Kenneth E. Kendall, and Julie E. Kendall ............... 9 9 4 Business Data Communications and Networking Expert Workshop: Mobile Business Outlook 2008-2010 Martin Steinert, Patrick Merten, and Stephanie Tuefel ......... 8 8 5 Modeling and Simulation of IEEE 802.11 WLANs: A Case Study of a Network Simulator Nurul I. Sarkar and Roger McHaney ............................................ 7 1 5 Performance Study of IEEE 802.11b Wireless LAN under High Traffic Conditions Nurul I. Sarkar .................................................................................. 1 0 1 Potential Weaknesses in Risk Assessment for Business Data Communications Philip Irving, Sonia Tindle, and John Tindle .......................... 1 0 4 9 Business Process Management A Framework for Situating Business Process Engineering Approaches: An Illustration with ARIS and EKD-CMM Selmin Nurcan and Zhichao Song ................................................ 2 8 5 Facilitating Successful Business Process Management Projects: Pitfalls and Success Factors Yvonne Lederer-Antonucci and Vijay Khatnani ...................... 8 2 5 Identify the Effective Factors to Select the Appropriate Form of Collaboration between One Company and Other Companies in Information Technology Industry in Iran Payam Hanafizadeh, Mina Rohani Tabatabai, and Seyed Ali Akbar Hosseini .............................................................................................. 8 8 8 Lean Order Management Hans-Henrik Hvolby ....................................................................... 5 8 6 OUML: A Language to Map Observed Usages to BPML Jean-Mathias Heraud, Laure France, and Joseph Heili ............ 6 8 3 Process Performance Measurement: Identifying KPI’s that Link Process Performance to Company Strategy P. Willaert, J. Willems, D. Deschoolmeester, and S. Viaene 7 4 0 QoS Driven Dynamic Task Assignment for BPM Systems Using Fuzzy Logic Cagil Tasdemir and Candemir Toklu ........................................... 7 6 7 Recent Trends in Innovation and Business Models in the New Digital Economy Soumaya Ben Letaifa and Yves Rabeau ...................................... 4 5 7

Relating Business Processes to the Elements of Underlying IT Application Joseph Barjis, Derek B. Weaver, and Isaac Barjis .................... 5 5 9 Resource Optimization on Flow Shop Scheduling for Industrial Case Using Simulation Ibrahim Al Kattan and Ahmed Al Nunu ..................................... 5 5 1 Service Oriented Investment Marc Rabaey, Eddy Vandijck, Koenraad Vandenborre, and Martin Timmerman ...................................................................................... 5 1 4 Supporting Interactions Between Organizations with Language-Action Models Peter Rittgen .................................................................................... 1 7 2 The Convergence Strategy in Small and Medium Sized Companies Exemplified by E-Business and T-Business Organisations Jerzy A. Kisielnicki ........................................................................... 7 8 Total Value Consideration for Outsourcing Vijay Vanarase, Marina Onken, Donna Maria Blancero, and William Anderson ............................................................................................ 6 4 4 Using Petri Nets to Represent Cross-Departmental Business Processes Joseph Barjis, Han Reichgelt, Paul Forté, and Chris Small .... 1 9 2 Customer Relationship Management Systems A Conceptual Framework for Electronic Customer Relationship Management (e-CRM): A Strategic Approach Forough Karimi and Reza Sarkhosh ............................................. 7 0 6 A Design Science Approach to Investigating the Piloting of Customer Relationship Management Carl Erik Wikström ........................................................................ 2 1 2 Measuring the Returns of Information Driven Customer Relationship Management Tools Ahern Brown, Timothy Shea, and D. Steven White ............... 5 8 4 Data Warehousing and Mining Classification and Rule Generation for Colon Tumor Gene Expression Data Shawkat Ali and Pramila Gupta .................................................... 2 8 1 Evidential Characterization of Uncertainty in Location-Based Prediction Iftikhar Sikder .................................................................................. 6 5 4 Hybrid Rough/Fuzzy Modeling of Advertising Effects on Consumer Preferences Ashwani Kumar ................................................................................ 1 6 4 Implementing Real Time OLAP with MDDC (Multi-Dimensional Dynamic Clustering) Michael W. Martin and Rada Chirkova ...................................... 6 6 6 Weakness of Association Rules: A Mechanism for Clustering Rajesh Natarajan and B. Shekar ................................................... 4 3 5 Database Management Technologies Architecting Personalized Information Retrieval and Access Services in Data Intensive Domains Nong Chen and Ajantha Dahanayake ......................................... 8 9 2 Research Information Management System: BioRio Yavuz Tor, Chaitanya Jasti, Zhixiang Chen, and Charles Harlow ............................................................................................................. 9 4 9 Decision Support Technologies Access Control for Auditors in Corporate Collaboration Timon C. Du, Vincent Lai, Charles Chou, and Richard Hwang3 8 6 Building HR Decision Support: Insights from Empirical Research Jochen Malinowski and Tobias Keim .......................................... 6 5 1

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Building HR Decision Support: Insights from Theory Jochen Malinowski and Tobias Keim .......................................... 8 2 9 Cognitive Reconstructive Remote Sensing for Decision Support in Environmental Resource Management Ivan E. Villalon-Turrubiates and Yuriy V. Shkvarko .............. 9 7 8 Exotic Options with Stochastic Volatilities Sanju Vaidya ...................................................................................... 9 9 7 Intelligent Processing for SAR Imagery for Environmental Management Ivan E. Villalon-Turrubiates ......................................................... 9 8 1 The Challenge of Global Supply Chain: Cross-Cultural Issues in Using an Expert System Model(QuickView) to Evaluate International Small Manufacturers Norita Ahmad and Gene R. Simons ............................................. 4 9 4 The Wireless Impact on the Legal System: A Case Study of a Law Firm Stan Lewis, Ernest W. King, and Eddy J. Burks ....................... 9 0 6 Distance Learning Technologies Design of an Assistance Tool to Support the Tutor in the Setting-Up of Learning Situations Elise Garrot, Sébastien George, and Patrick Prévôt ................ 4 2 4 Process Driven Knowledgebase for Managing Student Support H. Dexter and J. Petch ..................................................................... 8 6 Quality Issues in E-Learning: Differences in Eastern and Western Approaches Alan Murphy ..................................................................................... 8 1 1 Service-Oriented Architecture: Technology Selection and Strategic IT Management Brian R. Payne and A. James Baroody ....................................... 7 9 0 The Impact of Distance Learning on Graduation Rates for Information Systems Students Michael Mick and Susan E. Conners ........................................... 9 9 2 Using Educator Portals and Vignettes with Adult Online Learners Maria H.Z. Kish and Josephine Cocian Crame ......................... 5 6 7 Visual Representation of Computer Mediated Communication Patterns in Distance Learning Georgios A. Dafoulas ....................................................................... 6 2 7 E-Business Research A Descriptive Study of Online Privacy in the GCC Countries Zeinab Karake Shalhoub ................................................................. 5 8 9 Attitudes of Students Toward Electronic Cash Rosarito Sánchez-Morcilio ............................................................ 3 9 4 Business to Business E-Commerce and Inter-Firm Governance Qi Fei and Jim Q. Chen .................................................................... 3 8 Coping with Business Relationships: Use of Mobile Solutions to Improve Inter-Organizational Business Processes Jari Salo ................................................................................................ 9 7 Creating and Maintaining Privacy and Trust in an Online Trading Environment: A Case Study Seamus Hill and Denise Melia ....................................................... 3 0 4 E-Business in SMEs of Thailand: A Descriptive Survey Katherine Blashki and Suttisak Jantavongso ............................. 4 4 8 E-Marketplace: A Generic Electronic Catalogue Framework for SMEs Yin Leng Tan and Linda A. Macaulay ........................................ 9 5 4 E-Recruiting System Development In Lee ................................................................................................. 3 9 7 Evaluation of E-Commerce in Continental Native American Nations Yun-ke Chang, Miguel A. Morales Arroyo, Suliman Hawamdeh, and Jaime Jiménez ................................................................................. 1 0 2 1 Facilitators and Inhibitors of E-Commerce Adoption in an Irish SME: An Action Research Case Study Orla Kirwan and Kieran Conboy .................................................. 3 7 4 Hermeneutic Phenomenology: A Useful Tool for IS Educators? Steve Benson .................................................................................... 3 9 2 Money Laundering Using Electronic Payment Systems Juergen Seitz and Krzysztof Woda ............................................... 4 0 2 Predicting Online Customer Shopping Behavior Fan Zhao and Sagar S. Kulkarni ................................................... 8 4 6

The Benefits of an E-Business Performance Measurement System Matthew Hinton and David Barnes .............................................. 9 1 8 The Effect of Propensity to Trust on Customers’ Initial Trust in WebBased Online Stores Euijin Kim and Suresh Tadisina .................................................... 2 2 0 The Virtual User Shopping Experience: A Multi-Faceted Classification Ahmeyd Mahfouz ............................................................................. 4 6 8 Unattended Delivery for Online Shopping: An Exploratory Study From Consumers Perspectives Brett Ferrand, Mark Xu, and Martyn Roberts ............................ 3 0 Web Ontology as E-Business Information Exchange and Decision Support Tool Yefim Kats, James Geller, and Kuo-chuan Huang .................... 9 6 8 E-Collaboration Buying Stuff on the Web: Can Users Correctly Identify Deception in Purchasing Contracts? Ned Kock, Jacques Verville, Hafizul Islam, and Jesus Camona .... ............................................................................................................. 3 9 9 e-HR: A Custom Electronic Human Resources Management System M. Almanhali, M. Radaidah, and T. Shehabuddin .................... 6 7 2 Leadership and Organizational Citizenship Behavior in E-Collaborative Teams Richard R. Reilly, Karen Sobel Lojeski, and Michael R. Ryan ..... ............................................................................................................. 7 0 4 Leveraging Collaborative Technologies for Sharing Tacit Knowledge: An Integrative Model Vikas Sahasrabudhe and Subhasish Dasgupta .............................. 9 3 4 Reasoning about Functional and Non-Functional Concerns during Model Refinement: A Goal-Oriented and Knowledge-Based Approach Lawrence Chung and Sam Supakkul ............................................. 6 6 8 Stimulating Creativity and Innovation through People-Concepts Connectivity within On-Line Collaborative Workspaces Marc Pallot, Wolfgang Prinz, and Kulwant Pawar ................ 1 0 1 8 The Role of E-Collaboration Participative Budgeting Kevin E. Dow, Penelope Sue Greenberg, and Ralph H. Greenberg ............................................................................................................. 9 7 6 Towards Collaborative Worker-Centric Innovation Networks: A Conceptual Outline and Research Challenges Falk Graser, Jens Eschenbaecher, and Klaus-Dieter Thoben . 6 3 9 Unintended Consequences of Instant Messaging in the Workplace: An Empirical Study Jesus Carmona ................................................................................... 8 3 9 Electronic Commerce Technologies Management Cognitive Antecedents of Trust in Electronic Commerce Among Chinese Internet Users Yuan Gao and Dean Xu ................................................................... 8 3 6 Redundancy Reduction Utilizing XML, Web-Services and 2-D Bar Codes Greg Koniecek and Paul Darbyshire ............................................ 5 7 8 The Retaliatory Feedback Problem: Evidence from eBay and a Proposed Solution Ross A. Malaga ................................................................................. 8 2 2 Understanding the Impact of Innovation Characteristics and Individual Factors on Adoption of Online Channels Annette M. Mills, Lila Rao Graham, and Gunjan Mansingh .. 9 4 2 Electronic Government Research A Market-Based Information Resource Management Approach in Information Grid Yanli Hu, Liang Bai, Weiming Zhang, Weidong Xiao, Zhong Liu, and Yingchao Zhang ............................................................................... 2 3 9 A Study on the Information Quality Satisfaction of Communication Portals in the Hong Kong Government Shuk Ying Ho and Kevin K. W. Ho ............................................... 9 1 Developing Successful Strategies for ICT Initiatives in the Public Sector: The Case of Electronic Government Strategies in a U.S. City Bob Stea and G. Harindranath ....................................................... 8 7 6

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Performance Measurement for E-Government Scenarios: A Reference Process Model Based Approach Thomas Matheis, Christine Daun, and Peter Loos .................. 9 2 0 The Case of eReadiness on eGovernment in Developing Nations Case of Egypt Hany Abdelghaffar and Sherif Kamel .......................................... 7 2 8 The Use of Paralingual Web Pages to Improve Trust in E-Government Web Sites in Regions of Highly Bilingual Populations Roy Segovia and Murray E. Jennex ............................................. 9 8 4 Enterprise Information Systems A Systematic View of ERP Implementation Carin Chuang and Kuan-Chou Chen ............................................ 9 0 4 Frameworks for Building Enterprise Information Architectures Mahmood H. Shah and Zaigham Mahmood ............................... 5 4 1 Methodology Issues in Enterprise Systems Implementations Lambertus Verhage .......................................................................... 9 2 2 Toward a Quality Model for Enterprise Information Systems in Developing Countries: A Jamaican Case Study Evan W. Duggan and Charlette Donalds .................................... 8 5 0 Trends in the Delivery and Utilization of Enterprise ICT Jiri Vorisek and George Feuerlicht ............................................... 1 1 8 User’s Expectations and Reality of ERP System: Implementation Experience in Higher Education Adekunle Okunoye and Mark Frolick ......................................... 5 2 5 Geographic Information Systems A Conceptual Geospatial Data Warehouse Model for Forest Information Management Robert Magai and Wookey Lee .................................................... 7 5 3 A Proposed Software Architecture for Graphical Data Manipulation in the Context of a Mobile GIS for the Tourism Industry in Mauritius Geerish Suddul and Nawaz Mohamudally .................................... 9 2 5 Key Aspects in Community-Based Coastal Emergency Response GIS X. Mara Chen, Colleen Parrott, and Karin E. Johnson .......... 1 1 4 Global IT Management Transformational Leadership and Information Technology Management Integration Framework: A Normative Framework to Achieve Organizational Performance Effectiveness William S. Boddie ............................................................................. 5 4 5 Human Computer Interaction Achieving Implementation Success in Ubiquitous Computing Environments: Understanding the Role of Psychological Ownership Edward J. Garrity, Jonghoon Moon, and G. Lawrence Sanders .... ............................................................................................................... 3 4 Advanced Multi-Modal User Interfaces for Mobile Devices: Integration of Visualization, Speech Interaction and Task Modeling Norman Biehl, Antje Düsterhöft, Peter Forbrig, Georg Fuchs, Daniel Reichart, and Heidrun Schumann ................................................. 8 6 2 Feature Requirements in Educational Web Sites: A Q-Sort Analysis Sunil Hazari ....................................................................................... 6 9 4 Measuring Credibility Assessment Targets in Web-Based Information Jim D. Collins ..................................................................................... 1 1 Visualization in Multimodal User Interfaces of Mobile Applications Georg Fuchs and Heidrun Schumann ............................................ 3 4 5 Human Side of IT Research in Progress: A Field Study of Career Anchors and Women in the IT Force Jeria L. Quesenberry ........................................................................ 9 7 4 Being and Appearing: Human Interfaces in the Digital Age Lars-Erik Janlert .............................................................................. 2 3 2 Problematic Assimilation of ICTs in Radiology Practices: An Exploratory Investigation of the Four Dimensions of the Social Actor Framework Jeanette Lew ..................................................................................... 3 8 1 Small Business Experience and Governance of Employee Owned Personal Digital Devices W. Brett McKenzie ....................................................................... 1 0 0 4

Users as Subjects in and of Co-Design Peter Rittgen ..................................................................................... 4 5 9 Information Ethics Issues A Cross-Country Comparison of Software Piracy Determinants Among University Students: Demographics, Ethical Attitudes and SocioEconomic Factors Arsalan Butt ...................................................................................... 9 2 7 Avatars, Student Friend, Lecturer Foe? The Use of Avatars to Support Teaching and Learning Elaine Ferneley and A. Kamil Mahmood ................................... 4 1 5 Can Identity Theft Defense be Practically Effective? A TAM-Derived Survey of Software-Based Deterrence to Phishing and Pharming Charles McClain ............................................................................... 4 5 2 Crossing Privacy, Information, and Ethics Sabah S. Al-Fedaghi ........................................................................... 2 6 Cyberloafing: Vice or Virtue? Constant D. Beugré and Daeryong Kim ...................................... 8 3 4 Information Technology and the Ethics of Globalization Robert A. Schultz ............................................................................. 8 4 2 The Internet and Digital Imaging: A Recipe for Visual Deception Lucie Joshko and Jerome Moscicki ............................................. 5 9 1 Information Quality Management A Comparison of Quality Issues for Data, Information, and Knowledge Elizabeth Pierce, Beverly Kahn, and Helinä Melkas ................. 6 0 A Value-Driven Model for Data Manufacturing: An Application for Optimal Error-Correction Policy Adir Even and G. Shankaranarayanan ......................................... 7 4 9 Achieving Data Quality in Engineering Asset Management Jing Gao, Shien Lin, and Andy Koronios ................................... 6 0 7 Amount and Utility of Information Values: Two Cases of the Two Most Misunderstood Quality Attributes Zbigniew Gackowski .......................................................................... 6 3 Designing a Balanced Data Quality Scorecard John R. Talburt and Traci Campbell ........................................... 5 0 6 Information Mapping: A Case of Operating Theatre List Management Process Latif Al-Hakim ................................................................................. 7 9 9 Intrinsic and Internal vs External View of DQ/IQ (A Case of Relativity) Zbigniew Gackowski ........................................................................ 3 8 8 Theoretical Framework for Mapping Information of Social-Technical Processes: A Case of Operating Theatre Waiting List Management Process Gerhardine Foo and Latif Al-Hakim ........................................... 7 1 9 Information Security Management Service-Oriented Approach to Developing Security Policies for Trustworthy Systems Kassem Saleh, Abdulaziz Alkhaili, and Ibrahim Alkattan ...... 9 0 1 An Investigation of Information Security Policies, Procedures, and Perceptions within University Campuses Ramesh Subramanian, Robert Tordella, and Minnie Yen ....... 7 3 2 Building Career in Information Security Management Kuan-Chou Chen and Carin Chuang ............................................ 6 9 6 Consideration of Privacy Protection for Ubiquitous Applications through an Interdisciplinary Approach Kunihiko Kido and Satoshi Yasiro ............................................... 1 4 3 Development of a Weighted Network Security Measure Based on a Software Reliability Model Bong Gun Cho, Il-Yeol Song, Sung Y. Chin, and Charlie Y. Shim ............................................................................................................. 4 7 5 Increasing Governmental Regulations and Their Impact on IT: SOX and HIPAA Amita Goyal Chin and Sushma Mishra ....................................... 4 1 8 Information Security: Impacts of Leadership and Organizational Culture Gary Tarbet and Theodore Schlie ................................................ 4 6 2 Monitoring-Based Coordinated Defense through the Lens of the Coordination Theory Shuyuan Mary Ho and U. Yeliz Ereryel ...................................... 1 8 8

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Revealing Prospect Theory Bias in Information Security Decision Making Neil J. Schroeder and Michael R. Grimaila ................................. 1 7 6 Security by Integration, Correlation and Collaboration: Integrating Verification Reusable Agents into SOAP Messages Khalil A. Abuosba ............................................................................ 9 6 6 Security Status and Security Model for Mid-Size Accounting Firms in New Zealand Lech J. Janczewski and Vincent Tai ............................................ 2 6 9 Target, Shield and Weapon: A Taxonomy of IT Security Initiatives Laura Lally .......................................................................................... 2 3 The Architecture of Presence Investigation for Remote Control Hsieh-Hong Huang and Cheng-Yuan Ku ..................................... 9 5 1

Information Technology in Europe Factors that Influence the SMEs’ Adoption of Application Service Providers George Meletiou, Alemayehu Molla, and Adekunle Okunoye ............................................................................................................. 6 3 5 The Next Wave in IT Infrastructure Risk Management: A Causal Modeling Approach with Bayesian Belief Networks Daniel J. Hinz and Heiko Gewald ................................................. 1 4 8

Information Technology Education Everything We Wanted to Know About Our Course, but were Afraid to Ask: Views from the Student Perspective Anne Venables, Sarojini Devi Nagappan, and Asim Ghous .... 5 9 5 Application of a Collaborative Virtual Environment for Learning Molecular Biology Miguel A. Garcia-Ruiz, Ricardo Acosta Diaz, Maria Andrade-Arechiga, and Juan Contreras-Castillo ......................................................... 1 0 2 7 Computer-Based Edutainment for Children Aged 3 to 5 Years Old Man-Ying Cheung, Koon-Ying Raymond Li, and Tim Zapart ............................................................................................................. 2 9 3 Design Tools for Facilitating Qualitative Research Design in the Information Systems Environment Jakovljevic Maria ............................................................................. 2 7 3 E-Assessment in Information Technology Education Georgios A. Dafoulas ....................................................................... 5 1 6 Enabling Multidisciplinary Learning: A Descriptive Study Juha Kontio ....................................................................................... 5 0 9 Facilitating Group Learning in IT Higher Education Libby Hobson and Carmen Joham ................................................ 5 6 5 Implementing Educational Technology in K-12 Public Education: The Importance of Factors to Senior School Administrators in Pennsylvania Lawrence A. Tomei and David Carbonara ................................. 7 4 5 Implementing Educational Technology in K-12 Public Education: The Importance of Factors to Senior School Administrators in Pennsylvania David D. Carbonara and Lawrence A. Tomei ......................... 1 0 3 8 Pathways to Producing Digital Portfolios Eleanor J. Flanigan and Susan Amirian ....................................... 6 9 8 Role of Organizational Context on Digital Library’s Success Factor Noornina Dahlan, Noorliza Karia, Muhammad Hasmi Abu Hassan Asaari, T. Ramayah, and Goon Tuck Lee .................................. 7 1 2 Student Preferences for Reflective Learning Journals in a Studio Environment: A Survey Aleksander Sasha Talevski and Mark Szota .............................. 1 0 5 Teaching Information and Communication Technology in the Arab World: An Examination of Curriculum Anil Sharma, Khalifa Ali Alsuwaidi, and Stephen Boylan ...... 3 1 6 Teaching Java: Applications of Programmed Instruction and Collaborative Peer Tutoring Henry H. Emurian ........................................................................... 4 3 8 The Current State of the MIS Course: A Study of Business Program IS Curriculum Implementation Fred K. Augustine, Jr. and Theodore J. Surynt ......................... 9 7 2 The Dispositions of Professional Educators Contemplating The Use of The Readingpen® as a Motivational Factor to Increase Reading Fluency Heather Naleppa .............................................................................. 9 5 7 Towards a General Framework for the Study of ICT Skill Supply and Demand Krassie Petrova and B. Dawn Medlin .......................................... 2 5 5 Using Reflective Learning in an Introductory Programming Course Joo Eng Lee-Partridge ...................................................................... 9 4

Intelligent Information Technologies A Framework for Context-Aware Question Answering System of the Math Forum Digital Library Shanshan Ma and Il-Yeol Song ..................................................... 2 0 0 Cooperative and Dialog-Based Multi-Agents in Global Software Delivery Management Ravi Gorthi, Andie Kurniawan, and Nandan Parameswaran .. 3 7 7 The Safety Effect of the Red Light Running Cameras: Applying Data Mining Techniques Using ...................................................................... Fatality Analysis Reporting System (FARS) Data Scott Solomon, Jay Liebowitz, William Agresti, and Hang Nguyen ........................................................................................................... 1 0 5 1

Intellectual Property Issues Role-Based Approach to Intellectual Asset Management in Service Organizations S. Ramesh Babu, V.P. Kochikar, and M.P. Ravindra ............... 4 6 5

Interactive and Educational Technology Adaptive IT Education through IT Industry Participation MSD Fernando, ANW Dahanayake, and HG Sol ...................... 7 9 7 Introducing Computer-Supported Team-Based Learning: Preliminary Outcomes and Learning Impacts Elizabeth Avery Gomez, Deziu Wu, Katia Passerini, and Michael Bieber .................................................................................................. 6 0 3 Modeling of CHO Metabolism and Krebs Cycle Using Petri-Nets (PN) Isaac Barjis, Sidi Berri, Nwayigwe Okpa, Jennifer Tan, and Idline Agustin ............................................................................................... 8 5 4 Survey on IT Industry and University Collaboration for Adaptive Course Development MSD Fernando, ANW Dahanayake, and HG Sol ...................... 4 8 6 IRM in Government The Determinants of Information Resource Management: Substantiating a Construct Paul M. Chalekian ........................................................................... 8 3 2 IT and Supply Chain Management Analysis of Information Security in Supply Chain Management Systems Ibrahim Al Kattan, Ahmed Al Nunu, and Kassem Saleh ......... 6 8 0 ‘Herd’ Behavior and the BullWhip Effect: Information Access, or Risks and Rewards? Patrick I. Jeffers, Rhoda Joseph, and Francis A. Mendez ...... 6 8 8 IT Support for Managing Aircraft Spares in a Closed-Loop Supply Chain Track Michael MacDonnell and Benjamin T. Clegg ........................... 6 3 1 RFID: Risks to the Supply Chain Sanjay Goel and Jakov Crnkovic ................................................ 1 0 3 3 Strategic and Operational Benefits of B2B Data Exchange Technologies in Supply Chain Management Maria Madlberger ............................................................................. 9 1 3 Strategic IS Usage to Support Supply Chain Activities: A BP-ISP Integration Perspective Che-Chan Liao and Pu-Yuan Kuo ................................................ 5 3 8 IT Business Value E-Business Innovation and Firm Performance Namchul Shin .................................................................................. 1 0 1 3 Measuring the Business Value of IT: A Resource-Based View of Leading Indicators

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Penelope Sue Greenberg, Ralph H. Greenberg, Kevin E. Dow, and Jeffrey Wong .................................................................................... 7 0 2 The Impact of CEO/CIO Convergence on IT Strategic Alignment Alice Johnson and Albert L. Lederer ............................................ 5 0 The Impact of Information Technology on Productive Efficiency: An International Comparison Winston T. Lin and Page P. Tsai .............................................. 1 0 1 1 IT Evaluation Methods and Management A Formal Approach to Information Lifecycle Management Lars Arne Turczyk, Oliver Heckmann, Rainer Berbner, and Ralf Steinmetz ........................................................................................... 5 3 1 A Methodology for Educational Software Evaluation (ESE) Norelkys Espinoza, Bexi Perdomo, and Marco Flores ........... 9 3 9 Adoption of Pharmaceutical Sales Force Automation Systems: An Exploratory Study Sung J. Shim ...................................................................................... 9 9 9 An Analytical Model of Information Lifecycle Management Lars Arne Turczyk, Oliver Heckmann, Rainer Berbner, and Ralf Steinmetz ........................................................................................... 5 2 7 Developing Best Practice in Intranet Evaluation: A Comparison of Evaluation Models for Usability and Acceptance James Hill, Murray Scott, Thomas Acton, and Peter O’Boyle .... ............................................................................................................. 4 3 0 Examining the Value of Management Control in IT Organizations Sertaç Son, Tim Weitzel, and Wolfgang König ........................ 2 3 5 Leveraging the Balanced Scorecard to Measure and Manage Information Technology Governance Wim Van Grembergen and Steven De Haes ............................... 3 5 3 Selecting RFID Technology in the Manufacturing Industry Sector: A Decision Criteria Proposal Puja Sahni and Gerry Grant ........................................................... 3 6 7 The Evaluation of IT Investments through Real Options Maria Alice Frontini and Fernando José Barbin Laurindo ...... 4 7 9 IT Global Sourcing Contracts for Successful Outsourcing: Analyzing the Impact of Pricing Structures, Penalty & Reward Systems, and Liability Clauses on “Good” Sourcing Relationships Cornelia Gellings .............................................................................. 7 0 9 Decision Making Process of Information Systems Outsourcing Edward T. Chen, Jeffrey Hsu, and Kuoching Feng ................... 1 3 0 Managing Outsourced Support for ERP Systems N. Dayasindhu ................................................................................... 8 7 7 Outsourcing, Insourcing IT-Related Business: The Impact on the Organization James A. Sena ..................................................................................... 1 9 IT in Small Business A TPM Toolset for Small and Medium-Sized Businesses Axel C. Schwickert and Bernhard Ostheimer ............................ 2 5 1 Communities of Practice and Performance: Perceptions of IT Personnel in Small Organizations in the USA Loreen Marie Butcher-Powell and Brian Cameron .................. 3 1 3 Impact of Technology on the Legal System: A Study of a Law Firm’s Disaster Recovery Planning Stan Lewis, Ernest W. King, and Eddy J. Burks ....................... 1 2 7 The Use of Hard and Soft Technologies for Knowledge Management in Small Businesses Sathasivam Mathiyalakan .............................................................. 9 1 6 Variations in Adoption Factors and Use of E-Commerce Among Small Businesses: Are all SMEs the Same? Elizabeth Regan and Scott Wymer .............................................. 9 4 4 IT Management in Asia Pacific Countries Facilitators of IT-Business Alignment Between End-Users and IT Staff: A Framework Deb Sledgianowski ............................................................................ 4 7 0

The Challenge of E-Business in China: Exploring Competitive Advantage within the Electrical Appliance Industry Yan Tao, Matthew Hinton, and Stephen Little ........................ 6 9 1 IT Management in Developing Countries A Global Culture for E-Learning Alan Murphy ..................................................................................... 8 9 8 A Prototype Decision Support System for ERP Evaluation in Small and Medium Enterprises Leopoldo E. Colmenares G. ......................................................... 1 0 1 5 Information Systems in Developing Countries: Reasons for Failure – Jordan, Case Study Maha T. Al-Mahid and Evon M. Abu-Taieh ............................. 8 6 8 IT Management in Healthcare A Complex Data Warehouse for Personalized, Anticipative Medicine Jerôme Darmont and Emerson Olivier ....................................... 6 8 5 A Content-Based Approach to Image Retrieval in Medical Applications Thomas Lehmann, Thomas Deselaers, Henning Schubert, Mark Oliver Güld, Christian Thies, and Klaus Spitzer ....................... 9 1 1 Data Management Challenges for U.S. Healthcare Providers Steven B. Dolins and Robert E. Kero .......................................... 7 2 4 Health Community Portals: A Wish List Daniel Carbone and Stephen Burgess .......................................... 3 4 1 Improving Hospital Performance: A Framework for Designing Medical IT Systems Robert J. Mockler and Dorothy G. Dologite ............................. 4 4 1 Networkcentric Healthcare: Strategies, Structures and Technologies for Managing Knowledge Dag von Lubitz and Nilmini Wickramasinghe ............................... 5 Query Reformulation with Information-Based Query Expansion for Handling Medical Scenario Queries Yong Jun Choi .................................................................................. 3 2 5 IT Teaching Cases An Online Counseling Platform for a Mexican University Ricardo Acosta-Díaz, Arthur Edwards, Raúl Aquino Santos, Miguel A. Garcia-Ruiz, Jorge Rafael Gutiérrez-Pulido, and Juan ContrerasCastillo ............................................................................................... 3 3 7 Postgraduate Student Attendance: Face-to-Face vs. Online Stephen Burgess and Paul Darbyshire .......................................... 3 4 9 Knowledge Management A Knowledge Contribution Model to a Knowledge Management System George W. Stewart and Evan W. Duggan ................................... 2 1 6 Beyond Skill Management: Innovative Ways of Competency Catalogue Application Kai Reinhart and Ernst Biesalski .................................................. 4 2 7 Common Ground? Explaining the Willingness to Share Knowledge in Organizational Teams Pernill G.A. van der Rijt ................................................................ 4 0 6 Information and Knowledge Sharing by Undergraduate Students in Singapore Shaheen Majid and Ting Jer Yuen .............................................. 1 0 5 7 IS to Support Innovation: Weapons of Mass Discussion? Brian Donnellan, Kieran Conboy, and Seamus Hill ................. 6 2 3 Just-In-Context Clinical Knowledge Dissemination with Clinical Information Assistant Yong Jun Choi and Juman Byun ................................................... 3 2 9 Knowledge Leadership vs. Knowledge Management: The Malaysian Bankers’ View Muhamed Ali Haiazi and Zawiyah Mohammad Yusof ............ 3 5 7 Meta-Matrix Modeling for Knowledge Management: An Introduction Ronald Dattero and Jing Jim Quan ............................................... 1 9 6 Multi-Functional Stakeholder Information System for Strategic Knowledge Management: Theoretical Concept and Case Studies Kerstin Fink, Christian Ploder, and Friedrich Roithmayr ...... 1 5 2 Organisational Strategy, Structure and Culture: Influences on Organisational Knowledge Sharing Sharman Lichtenstein and Michael Edward Brain .................... 5 7 1

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Organizational Administrative Information Management: Issues Concerning Distribution, Retention, and Availability of WorkRelated Information David W. Miller, Paul J. Lazarony, and Donna A. Driscoll .. 9 7 0 Quantitative versus Qualitative Approaches to Tacit Knowledge Testing Peter Busch, Lee Flax, and Debbie Richards ............................. 4 9 0 Social Capital and Knowledge Sharing in Virtual Communities Teresa L. Ju, Hui-ching Chen, and Patricia H. Ju .................... 4 0 9 The Role of Social Networks in Tacit Knowledge Diffusion Peter Busch and Debbie Richards ................................................. 5 0 4 Transforming Universities from Teaching Organizations to Learning Organizations by Implementing eKM: A Pakistani Public Sector University Scenario Eram Abbasi, Nadeem A. Syed, Arshad Siddiqui ........................ 8 7 1 Validating the Indicators for the Knowledge-Based Economy: A Case Study of Economic Development Board of Singapore Abdus Sattar Chaudhry and Fong Pin Fen .................................. 8 0 4 Wanted: A Framework for IT-Supported KM Lena Aggestam ................................................................................... 4 6 Managing Electronic Communication Building a Tool for Expertise Discovery Sara Tedmori, Thomas Jackson, Dino Bouchlaghem, Holger Adelmann, and Rama Nagaraju ................................................... 1 0 5 3 Developing an Email Interception and Interpretation Information System to Reduce Employee Interruptions Thomas W. Jackson and Stephen Smith .................................... 6 1 1 Spim, Spam and Advertisement: Proposing a Model for Charging Privacy Intrusion and Harassment Dionysios Politis, Georgios John Fakas, and Konstantinos P. Theodoridis ....................................................................................... 6 7 7 Mobile Computing and Commerce A Practical X10 Protocol Implementation over a Cellular Network Using SMS Joffre Pesantez and Hernán Córdova .......................................... 8 5 7 A Scheme of Technology Acceptance for Mobile Computing Patricia H. Lapczynski and Linda Jo Calloway ........................ 2 0 8 Acceptance of the Mobile Internet as Distribution Channel for Paid Content Christian Kaspar, Lutz Seidenfaden, Björn Ortelbach, and Svenja Hagenhoff ............................................................................................ 6 8 Adaptive Web Browsing Using Web Mining Technologies for InternetEnabled Mobile Handheld Devices Wen-Chen Hu, Jyh-haw Hu, Hung-ju Chu, and Sheng-Chien Lee ............................................................................................................. 2 7 7 Determinants of 3G Mobile Video Adoption by the South African Mobile Consumer Faizel Richards and Jean-Paul Van Belle .................................... 7 7 2 Mobile Auctions: Will They Come? Will They Pay? Paul W. Forster and Ya Tang ....................................................... 7 7 9 Mobile Gaming: A Reference Model and Critical Success Factors Krassie Petrova and Haixia Qu ..................................................... 2 2 8 Multicultural Issues in IT Management Cross-Cultural Issues in Global Information Systems Development Haiyan Huang ................................................................................... 9 3 0 Cultural Issues in Information Systems Research: A Review of Current Literature and Directions for Future Research Subhasish Dasgupta and Li Xiao ................................................... 7 0 0 Gender Discrimination in IT Salary: A Preliminary Investigation Jing “Jim” Quan, Ronald Dattero, and Stuart D. Galup ............ 8 2 Multimedia Information Management Methodologies for Developing Multimedia Systems: A Survey Mark Szota and Kirsten Ellis ............................................................. 1 Modeling of DNA Transcription and Gene Regulation Using Petri Nets Isaac Barjis, Wallied Samarrai, Idline Augustine, and Joseph Barjis ............................................................................................................. 5 4 8

Speed Analysis of Camera Motion in Video Sequence Thitiporn Lertrusdachakul, Terumasa Aoki, and Hiroshi Yasuda ........................................................................................................... 1 0 0 1 Object Oriented Technologies Specifying Refactorings as Metamodel-Based Transformations Claudia Pereira and Lilianna Favre .............................................. 2 6 4 Open Source Software A Framework for Teaching Information Security Laboratory Projects with Open Source Software Mariana Hentea ................................................................................ 2 9 0 A Proposed Framework for Assessing the Factors Influencing the Adoption of Free and Open Source Application Software in Organizations Gerald G. Grant, Lila Rao Graham, and Gunjan Mansingh ..... 3 3 3 Philosophical Viewpoints in Information Management A Framework for Design Science Research Activities John Venable ..................................................................................... 1 8 4 Making Choices: Research Paradigms and Information Management: Practical Applications of Philosophy in Information Management Research M. E. Burke ......................................................................................... 1 5 Philosophical Foundations of Information Modeling John M. Artz .................................................................................... 4 4 3 Web Ontologies and Philosophical Aspects of Knowledge Management Yefin Kats ......................................................................................... 8 4 4 Project Management and IT Combat the Menace of Scope Creep of Development Projects through the Use of EUReqa Methodology: A Collaborative and Iterative Requirement Engineering Process Ravi Sankar, Rambabu Yeleti, and Addul Hakeem ................... 9 6 0 From Functional Structure to Project Structure: A Brazilian Clinical Research Company Case Marcos Antonio de Oliveira and Marly Monteiro de Cavalho .... ............................................................................................................. 5 1 2 Integrated Approach to Risk Management for Custom Software Development and Maintenance Initiatives N Dayasindhu, Sriram Padmanabhan, and Jamuna Ravi ......... 7 9 3 Modeling of Project Dynamics in IT Sector: A System Dynamics Approach for Resource Optimization from a Risk Perspective N. Dharmaraj, Lewlyn L.R. Rodrigues, and Shrinivasa Rao B. R. ............................................................................................................. 8 9 5 One Size Does Not Fit All: Modeling the Relationship between System Development Methodology and the Web-Based System Environment Theresa A. Steinbach and Linda V. Knight ................................ 9 3 7 Project Portfolio Management Daniel Brandon ................................................................................. 1 0 9 The Impact of Project Management Practices and Project Sponsorship on Project Performance David Bryde and David Petie ........................................................ 1 2 2 Virtual Project Risk April Reed and Linda Knight ...................................................... 1 0 0 9 Semantic Web Applications Utilising the PHOAF Prototype for Integrated ENUM and FOAF Queries Kurt Reichinger, Gerd Reichinger, and Robert Baumgartner . 1 3 3 Human-Centric Challenges in Ontology Engineering for the Semantic Web: A Perspective from Patterns Ontology Pankaj Kamthan and Hsueh-Ieng Pai ......................................... 8 7 9 Knowledge Extraction to Improve Information Retrieval in Scientific Documents Rocio Abascal and Béatrice Rumpler .......................................... 3 7 1 Research on Constructing Ontology for the Semantic Web Song Jun-feng, Zhang Wei-Ming, Tang Da-quan, and Tang Jin-yang ............................................................................................................... 5 5

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Social Responsibility in the Information Age A User Requirement Study on the Needs of Visual Artists with Upper Limb Disabilities Katherine Blashki, Dharani Priyahansika Perera, and Gang Li ............................................................................................................. 1 6 0 Making Good on Municipal Promises: Can Municipal Wireless Broadband Networks Reduce Information Inequality? Andrea Tapia, Julio Angel Ortiz, and Edgar Maldonado Rangel ............................................................................................................. 5 9 9 The Challenge of Telecommuting Implementation in Malaysian Government Offices Rafidah Abd Razak, Huda Ibrahim, Zahurin Mat Aji, Wan Rozaini Sheik Osman, Nafishah Othman, and Juliana Wahid ............... 8 1 3 The Influence of Educational, Social, and Economical Factors on the International Digital Divide, as Measured by IT Usage and Expenditure James Pick and Rasool Azari ...................................................... 1 0 0 6 Software Engineering Technologies A Method of Translating Business Use Cases into System Use Cases George Abraham and Il-Yeol Song ............................................... 6 5 7 Representing, Organizing and Reusing Knowledge About Functional and Non-Functional Concerns During Software Development Sam Supakkul and Lawrence Chung ............................................. 5 3 4 Systems Design for Requirements Expressed as a Map Naveen Prakash and Colette Rolland .......................................... 5 0 1 Software Process Improvement A Model for Measuring Team Size as a Surrogate for Software Development Effort James A. Rodger ............................................................................... 7 8 7 Building a Methodology for the Design of Reference Architectures that Integrates Legacy Systems Juan Muñoz López, Jaime Muñoz Arteaga, and Carlos Argelio ............................................................................................................. 6 4 8 CMMi for Small Business: Initial Tailoring of a Mexican organization Francisco Alvarez R, Jaime Muñoz, and Alfredo Weitzenfeld ............................................................................................................. 7 7 6 Cultural and Political Issues in Implementing Software Process Improvement Dana Edberg and Lisa A. Anderson ............................................. 1 6 8 Design Interactive Applications Using Object-Oriented Petri Nets in Software Components Jaime Muñoz Arteaga, Francisco Alvarez Rodríguez, Gustavo Rodríguez Gómez, and Héctor Perez González ......................... 2 2 4 Improving the Software Development Process by Improving the Process of Relationship Discovery Joseph T. Catanio and Michael Bieber ....................................... 4 2 1 Strategic IT Management E-Learning Acceptance Model (ELAM) Hassan M. Selim ................................................................................. 7 3 IT Strategies in Digital Economy: Selected Problems, Polish Experiences Tadeusz Krupa and Lech Gasiorkiewicz ...................................... 2 4 2 Organizational Slack in the Global Information Technology Industry Perry Sadorsky ................................................................................... 4 2 Telecommunications and Networking Technologies Estimating Signal Strengths in Indoor Wireless Systems in Order to Deliver a Cost-Effective Solution Optimizing the Performance of the Network Gabriel Astudillo, Lenny Garófalo, and Hernán Córdova ..... 1 0 2 4 Improving TCP/IP Performance Over Geosynchronous Satellite Links: A Comparative Analysis Joseph M. Lawson and Michael R. Grimaila .............................. 1 8 0 Interactive Television: A Study into the Diffusion of a New Technology in Britain and Ireland James Hill, Thomas Action, and Neil Farren ............................ 6 1 5

Text Database and Document Management A Digital Preservation Ingest Parsing Service for Complex Data Objects Don F. Flynn ..................................................................................... 9 4 7 Experiments in Information Extraction Soraya Abad-Mota and Eduardo Ruiz I. ...................................... 2 0 4 Managing Concurrent XML Structures: The Multi-Structured Document Building Process Noureddine Chatti, Sylvie Calabretto, and Jean-Marie Pinon ...... ............................................................................................................. 9 8 6 Unified Modeling Language and Unified Process Action Research and the Unified Process: Can They match? Christian Malus ................................................................................ 5 7 5 CSpec: Constraint Specification for Data Modeling Gillian S. Miller ................................................................................ 5 1 9 HERMES: A XML-Based Environment for Flexible Requirements Management Alberto Colombo, Ernesto Damiani, Mauro Madravio, Renato Macconi, and Karl Reed ................................................................. 4 1 2 MDA-Based Design Pattern Components Liliana Martinez and Liliana Favre ............................................. 2 5 9 Reasoning About Functional and Non-Functional Concerns During Model Refinement: A Goal-Oriented and Knowledge-Based Approach Lawrence Chung and Sam Supakkul ............................................. 8 1 6 Universities and Online Education A Taxonomy of Learning Technologies: Simplifying Online Learning for Learners, Professors, and Designers Richard Caladine .............................................................................. 2 4 7 Course Embedded Assessment of IT Competency: A Case Study Anil Aggarwal and Susan A. Lynn ................................................ 3 2 2 How to Integrate Public University Web Sites and Embed Learning Management Systems Axel C. Schwickert and Bernhard Ostheimer ............................ 7 5 8 Online Eduction as a Technology Innovation in Higher Education Steven F. Tello ................................................................................. 9 6 3 The Open Sources Education: A Real Time Education Tadeusz Krupa and Teresa Ostrowska ......................................... 6 6 1 The Seen Playfulness as Aspect of the Distance Education Mauricio Rosa and Marcus Vinicius Maltempi .......................... 5 5 4 Very Large Business Applications Distribution of ERP System Components and Security Considerations Nico Brehm and Jorge Marx Gómez ............................................ 4 9 4 SAP®/R3™ as Part of a Federated ERP System Environment Nico Brehm, Jorge Marx Gómez, and Claus Rautenstrauch ... 8 6 5 Virtual Organizations and Society Telework Implementation toward Virtual Organization in Malaysia Muhammad Hasmi Abu Hassan Asaari and Noorliza Karia .... 7 8 4 Virtual Universities A Virtual University Providing an Online Master Program in a PublicPrivate Partnership: Challenges and Solutions Karl Kurbel ........................................................................................ 1 5 6 Designing and Explaining the Trust Model of Students Applying to Virtual Universities Mohammad Ali Sarlak and Hassan Abedi Jafari ........................ 2 9 7 Web Engineering Technologies E-Learning Systems in the Bergen Region, Norway: An Overview Terje Kristensen, Yngve Lamo, and Khalid Mughal ............... 5 6 2 Hybrid Agent Web Service Engineering: A Case Study in Financial Application Domain Sujan Pradhan and Hongen Lu ...................................................... 7 6 2 Semantic Web-Enabled Web Engineering: The Case of Patterns Pankaj Kamthan and Hsueh-Ieng Pai ......................................... 8 8 1

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Web Services An Architectural Framework for Web Services Based SOA Realization in a Bank Jakakumar Venkataraman and Sriram Anand ............................. 1 3 7 ETMS-WEB: A Low-Cost Innovative Solution to Manage the Sale Staff Anna Bruno, Andrea Pandurino, and Nicola Fiore ................ 1 0 4 2 Ontology-Based Security Specification Tools for SOA Myong Kang, Anya Kim, Jim Lo, Bruce Montrose, and Amit Khashnobish ...................................................................................... 6 1 9 Software Risk Mitigation through Web Services Daniel J. Hinz ................................................................................... 8 2 0 Trends of Web Services Adoption: A Synthesis Vincent C. Yen ............................................................................... 1 0 3 0 Web Services Based Tools for Personal Financial Planning Oliver Braun and Günter Schmidt ................................................ 9 8 9 Web-Based Learning and Teaching Technologies A Rationale for Conceiving Adaptation in Educational Adaptive Hypermedia Systems José M. Parente de Oliveira and Clovis Torres Fernandes ..... 3 0 9 A User Needs Assessment of a Cultural Heritage Portal: The Singapore Infopedia Chu Keong Lee and Bonny Tan ................................................... 9 0 8 Course Management Systems: A Tool for International Student Collaboration Diane Boehm and Lilianna Aniola-Jedrzejek .......................... 1 0 3 6 Integrated Access to Learning Objects Repositories and Digital Libraries Geórgia R. R. Gomes, Sean W.M. Siqueira, Maria Helena L. B. Braz, and Rubens N. Melo ........................................................................ 7 3 6 Multimedia Influence on Learning Esperanza Huerta ............................................................................. 4 7 2 PMK: An Intelligent Environment for Project Management Education Paula Torreao, Patricia Tedesco, and Hermano Perrelli ........ 5 8 1 Roles in Learning Management Systems Development Ari Wahstedt .................................................................................... 5 2 2 Abstracts A Cross-Sectional Study on Internet Searching Skills by Health Facilities of a Latin-American University Belkys Chacín, Norelkys Espinoza, and Angel Rincón ......... 1 0 6 2 A Database-Oriented Approach to the Introductory MIS Course Effrem G. Mallach ......................................................................... 1 0 6 1 A Model for Educating the Transitional Technical Professional Gary Schmidt .................................................................................. 1 0 6 2 Cybercrime, Cyberwarfare, and Cyberterrorism in the New Millennium Shin-Ping Tucker ........................................................................... 1 0 6 3 Determinants of Information Systems Project Failures in Sub-Saharan Africa: A Review of the Critical Factors Mary Otieno .................................................................................... 1 0 6 2

E-Business Implementation Process in China Jing Zhao, Wilfred V. Huang, and Zhen Zhu ........................... 1 0 6 1 Enhancing the Accessibility of Information Assets Available on an ECommerce Platform through Data Mining Analytics Stephan Kudyba and Kenneth Lawrence .................................. 1 0 6 2 Evaluation of Multicarrier Modulation Technique Using Linear Devices Hernán Córdova ............................................................................. 1 0 6 4 IT Global Sourcing: What is its State of Maturity? Mehdi Ghods .................................................................................... 1 0 6 3 Outsourcing: An Innovative Delivery Model Vijayanand Vadervu ....................................................................... 1 0 6 4 Role of Information Exchange in Damping Supply Chain Oscillations Ken Dozier and David Chang ...................................................... 1 0 6 1 The Impact of Organizational Culture and Knowledge Management on Organizational Performance Zhang Li, Tian Yezhuang, and Qi Zhongying ......................... 1 0 6 4 The Value of Search Engine Optimization: A Case Study of a New ECommerce Web Site Ross A. Malaga ............................................................................... 1 0 6 1 Panels, Workshops and Tutorials Agile and/or Plan Driven Software Development Jacob Norbjerg and Wolfgang Zuser ........................................... 1 0 6 6 Assessing the Value of e-Learning Systems Yair Levy ........................................................................................ 1 0 6 5 International Tracking and Reporting Systems for Combating the HIV/ AIDS Pandemic Sue J. Griffey ................................................................................... 1 0 6 6 Listening to Learn: Educating Information Age Leaders Kathleen M. Schulin and Mary S. McCally .............................. 1 0 6 8 The Potential and Perils of Information Technology Portfolio Management John T. Christian ........................................................................... 1 0 6 5 Transforming Technologies: Organizational and Leadership Dimensions Gerry Gingrich ................................................................................ 1 0 6 7 Web-Based Systems for Distance Education and e-Learning: Towards eLearning Online Communities Georgios A. Dafoulas ..................................................................... 1 0 6 7 Doctoral Symposium Submission A Framework of Enterprise Resource Planning (ERP) Systems Implementation in Kenya: An Empirical Study Jim Otieno and Geetha Abeysinghe ........................................... 1 0 6 9 Attracting Female High School Students to the IT Industry Donna M. Grant ............................................................................. 1 0 7 2 B2B E-Commerce Adoption in the Financial Services Sector: A Strategic Perspective Moses Niwe .................................................................................... 1 0 7 5 The Information Cycle in the European Commission’s Policy-Making Process Evangelia Koundouraki ................................................................ 1 0 7 3

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Emerging Trends and Challenges in IT Management

1

Methodologies for Developing Multimedia Systems: A Survey Mark Szota & Kirsten Ellis Monash University, Berwick Campus, Clyde Road, Berwick, Victoria 3806, Australia {Telephone: +61 3 9904 7097, Fax: +61 3 9904 7169, Fax: +61 3 9904 7169, [email protected]} {Telephone: +61 3 9904 7132, Fax: +61 3 9904 7169, [email protected]}

ABSTRACT Many theoretical development practices exist for creating multimedia systems. Most of these development models are orientated towards building traditional information systems, where the requirements are usually well understood. Multimedia systems, like the industry itself, are evolving rapidly, therefore new tools and techniques are constantly being published. Such rapid change results in clients of such systems lacking full awareness of the capabilities of multimedia systems, thus making it difficult to define their requirements. Some of the current models are able to respond to scenarios such as this, but others cannot. This research surveyed multimedia developers within Australia in order to find the most widely used development model(s) within the industry, and the rationale for their use. The results indicate that there is no specific approach to creating multimedia systems. Developers tend to use a range of different methodologies. The motives for using a variety of approaches are also examined.

INTRODUCTION The development of any computer software system has a common characteristic: a software development life cycle. This life cycle is a period of time that commences at the proposal to develop a system, and usually terminates when the system is complete and handed over to the client. It involves analysing the requirements of the system; designing and implementing a solution; testing and installation. In many cases, an ongoing support stage occurs, where the system may be modified or updated should the need arise. These stages may be performed repeatedly, or overlap with each other. Developers of traditional Information Systems (IS) use a range of software engineering methodologies. With the progressive escalation of multimedia applications, it remains unclear if developers are applying these same methodologies. This paper investigates the most widely used methodologies to develop multimedia systems, and the reasons for their adoption.

DEVELOPMENT MODELS IN VOGUE Current methodologies used for traditional system development can be categorised into three different forms: structured, iterative and evolutionary. Structured models (also known as traditional models) are in a linear form. Phases are completed sequentially until the cycle has finished. Iterative models are based upon a cycle that is repeated until it is complete. Some of these models combine iterative and sequential stages. Evolutionary models are new hybrids that generally do not fit into either category. They may be structured, iterative, or a combination of both. Structured methodologies are one of the most commonly used software development techniques. A primary example of this is the Waterfall model. Several variants of this approach were uncovered, which suggests that there may be no fixed approach. Dennis and Wixom (2000), along

with Satzinger et al. (2004) suggest a linear, four-phased approach that involves pre-project planning, analysing, designing and then implementing a system. Pressman (2000) offers a similar interpretation with minor variations. The planning stage is removed, and a dedicated testing phase is inserted after the system has been built. Hoffer, George and Valcich (1999) propose a version that has extended planning and design phases. However, their model suggests a project can go back to a previous stage if required, which tends to violate the linear nature of the Waterfall approach. Vaughan (1998) promotes his own structured approach, which is oriented towards multimedia development. Each stage consists of several defined tasks, and the project can be aborted at any stage. Vaughan also supports the use of prototypes and Computer Aided Software Engineering (CASE) tools. Siegel (1997) presents a structured model that is focused upon web site development. Like traditional methodologies, it does not allow any backtracking, and has a similar four-phase approach. Iterative methods use a highly repetitive cycle of development. The most common forms of iterative development are Rapid Application Development (RAD) and Prototyping. Dennis and Wixom (2000) present several versions of RAD. The key feature of RAD is the use of CASE tools, which are used to hasten the analysis, design and implementation phases. Joint Application Design (JAD) sessions can also be used to assist in the analysis of system requirements. Plfeeger (1998) describes a Phased Development model that breaks the overall system into a series of ‘versions’ that are developed sequentially. This process is repeated until the system is complete or becomes redundant. Prototyping uses a similar repetitive formula, but the same example is continually enhanced until it is complete (Dennis and Wixom, 2000). Throwaway prototyping uses prototypes that are designed to explore and understand a particular aspect of the proposed system. Once these issues have been resolved, the prototype is ‘thrown away’, and a linear progression of system development continues. Several Evolutionary models of development exist. MacCormack (2001) presents an Evolutionary-Delivery model of software development that involves breaking down a project into several micro-projects. The objective of each micro-project is to deliver a portion of the functionality into the overall system. This method provides early feedback on how the development is progressing, and is highly flexible. Pressman (2000) presents an Incremental model that combines structured development with the iterative processes of prototyping. Sommerville (2001) discusses the Spiral model, which combines the iterative processes of Prototyping with the clinical and systematic approaches of structured methodologies. It has the potential to rapidly produce incremental versions of a given system. Boehm et al. (1998) proposes a WINWIN Spiral model that improves on the previous approach by allowing for negotiations between the client and the developer. The overall objective for these negotiations is to have a ‘win-win’ scenario for both parties. Hoffer et al. (1999) present an Object Orientated Design model that is heavily based on Object-Oriented (OO) theorems to develop a system that is based upon ‘objects’ rather than information or processes.

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2 2006 IRMA International Conference The research has shown that there are several methodologies in use for system development. Some of these are oriented towards multimedia system development, however most of them are focused on the construction of traditional IS. With so many alternatives available, developers of such systems must use a variety of approaches. This paper investigates if this phenomenon applies to multimedia system development.

INVESTIGATING THE ISSUE In order to discover the most widely used methodologies for creating multimedia systems, a survey was conducted that investigated the approaches used by multimedia developers within Australia. The questionnaire was distributed via electronic mail, and comprised of eleven questions that were designed to elicit both qualitative and quantitative data from organisations. These questions covered topics such as the size of each organisation, and the various platforms they develop multimedia applications for, such as the World Wide Web (WWW), CD-ROM, DVD, standalone multimedia systems (e.g. interactive kiosks), and standalone audio/video productions (e.g. DVD-Video). Other topics discussed on the questionnaire included current and previous methodologies used by developers for a given platform, and their justification for using or discontinuing a chosen model. From the information ascertained, various trends relating to the use of traditional methodologies for multimedia products were uncovered. From the 254 surveys sent out to multimedia developers, 50 were confirmed to have read the survey, and 18 responded, which translates to a 36 percent response rate.

METHODOLOGIES USED TO CREATE MULTIMEDIA SYSTEMS Ninety-four percent of respondents indicated which development models they used to create multimedia systems. A summary of the range of methodologies used by developers is shown in Table 1. A majority of developers used more than one methodology to create multimedia products. Eighteen percent use five different development models, which may indicate that some developers feel a multiplicity of approaches is required. Thirty-five percent use only one, and six percent used no methodology at all.

METHODOLOGIES USED FOR VARIOUS PLATFORMS Specific methodologies are defined as development processes that are always applied for a given platform. For example, a developer may only use the Waterfall model for developing web sites: therefore, that is deemed as a ‘specific’ approach. Alternatively, developers may have several suitable models that could be deployed for a given platform. Each one of these is defined as an ‘in-specific’ approach. Tables 2 and 3 show the utilisation rate (on a specific and in-specific basis) of a development model for a given platform. The clear majority of developers (66 percent) tend not to use a specific model when developing web-based multimedia. Twenty-one percent specifically use their own customised development process. Phased Development is seldom used, and there are some organisations that do not employ any methodology. The results indicate that almost all of the methodologies detailed in previous discussion are used on a sporadic

Table 1. Range of methodologies used by developers Number of Methodologies Zero

Total (%) 6

One

35

Two

24

Three

6

Four

6

Five

18

Six

6

basis. Developers used their own customised processes thirty-three percent of the time. Other methodologies are used less frequently. There were no developers found that employed the Spiral or WINWIN Spiral models. Methodologies used for creating CD-ROM applications show that a clear majority of developers do not use any specific approach. Only a quarter of developers specifically use their own customised approach. Like Web development, a range of approaches was used on an in-specific basis. Customised development models are again the most likely to be used, with theoretical methodologies less favoured. The majority of developers do not use a set approach for creating DVD applications. This reinforces the same trend that was prevalent for both WWW and CD-ROM based multimedia. Twenty-nine percent specifically use their own customised approach. For organisations that do not apply a specific model, several methodologies may be applied, although the majority still choose to apply their own proprietary model. Again, developers tend to use no specific approach when developing standalone multimedia systems, with fifty-seven percent preferring to use a range of different methodologies. However, twenty-nine percent of organisations still prefer to use their own custom development methods. If they do not use a specific model, alternative methodologies are used less frequently. The current trend for specific approaches remains when creating standalone audio / video productions. The majority of developers tend to use a variety of approaches. A more diverse range of approaches are employed by developers who choose not to implement a specific methodology, with ten alternative models identified. Customised methodologies remain most favourable approach. For multimedia that is developed for mobile computing platforms, all the respondents indicated that they did not use any specific approach. Instead, a range of approaches are used. Developers used their own customised approach forty percent of the time. Waterfall, RAD or Prototyping models were used less often.

MOTIVES FOR UTILISING CHOSEN METHODOLOGIES Seventy-two percent of organisations provided some insight into the motives behind using a given development model. Interestingly, cost seemed to be an irrelevant issue, with only four organisations citing this as a reason for using their chosen models. One developer mentioned ‘budget constraints’ as a reason for using either RAD or the Waterfall model for developing multimedia systems. Conversely, another organisation (who did not indicate the processes that they used) noted

Table. Utilisation rate of methodologies (specific and in-specific) for creating WWW, CD-ROM and DVD multimedia WWW Model

CD-ROM

DVD

Specific In-specific Specific In-specific Specific In-specific (%) (%) (%) (%) (%) (%)

Waterfall / Structured

0

3

0

5

0

0

RAD

0

10

0

14

0

11

Phased Development

7

13

6

11

14

11

Prototyping

0

10

6

11

0

11

Throwaway Prototyping

0

3

0

3

0

0

Incremental

0

6

0

5

0

0

Evolutionary-Delivery

0

6

0

8

0

11

Spiral

0

0

0

0

0

0

WINWIN Spiral

0

0

0

0

0

0

Object-Oriented

0

13

0

14

0

0

Custom

21

33

25

26

29

56

None

7

3

6

3

0

0

Other

0

0

0

0

0

0

Don't Use A Specific Model

65

N/A

57

N/A

57

N/A

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Emerging Trends and Challenges in IT Management Table 3. Utilisation rate of methodologies (specific and in-specific) for creating standalone multimedia, audio / visual and mobile computing systems Standalone MM Model

Standalone AV

Mobile Computing

Specific In-specific Specific In-specific Specific In-specific (%) (%) (%) (%) (%) (%)

Waterfall / Structured

0

8

0

9

0

20

RAD

0

15

0

9

0

20

Phased Development

14

15

9

9

0

0

Prototyping

0

15

0

9

0

20

Throwaway Prototyping

0

0

0

5

0

0

Incremental

0

0

0

9

0

0

Evolutionary-Delivery

0

0

0

9

0

0

Spiral

0

0

0

0

0

0

WINWIN Spiral

0

0

0

0

0

0

Object-Oriented

0

8

0

9

0

0

Custom

29

39

18

27

0

40

None

0

0

9

5

0

0

Other

0

0

0

0

0

0

N/A

64

N/A

100

N/A

Don't Use A Specific Model 57

that the Waterfall model became ‘incredibly expensive’ if modifications to a system were required. This same developer also concluded that ‘$$$ [sic] almost always make the final decision” when deciding upon a given development model. Deadlines also received little attention amongst developers, with only four indicating this influenced their decision. One developer noted that the Waterfall model was a good choice if they knew precisely what was required. Another organisation customised their development process to fit within the client’s preferred timeline of development. A developer who used a range of methodologies also indicated that deadlines prejudiced their decision to implement either a traditional model, or their own customised approach. A lack of experience in using other development models was cited by only one developer as a reason for adhering to their chosen methodologies, which were the Waterfall Model and RAD. Project requirements were the main reason for using a diverse range of approaches, which was cited by forty-six percent of organisations. One developer used a customised approach, based upon many traditional models, in order to meet the client’s needs. They felt that this process has been beneficial because their clients had generally been satisfied with the outcome of their project. An alternative approach, used by the same developer, was to have a list of pre-defined prototypes from which a client can pick and choose. Another developer noted that they used Prototyping for all platforms, particularly when user requirements were imprecise. In addition, one organisation felt that no two projects are ever the same, so they need to use a range of approaches for the various platforms for which they develop. A solitary organisation also mentioned their reasons behind use their own proprietary method. They believe that their process covers all aspects of software development, and can be used for creating any form of multimedia, as well as other varieties of software. This company also believed that this process was highly flexible and was able to meet a various range of project requirements. A developer who did not use any methodology claims they do not see a purpose for deploying any kind of model. Instead, their employees are encouraged to work using whatever process they deem applicable, and by any guidelines that are specific to a given project. Few developers (16 percent) acknowledged that they had previously used other development methodologies. One developer, who did not specify which approach they used, suggested that none of the development models could apply to all types of development. Another had tried to utilise Object-Oriented methodologies, but found the design aspect too difficult and awkward.

3

CONCLUSION The findings show that there are many and varied methodologies used to create multimedia systems, but there is no solitary approach that is more suitable than others. Developers tend to use a wide range of approaches when developing multimedia systems. From this range of approaches, it appears most likely that they will use their own proprietary methods. Developers also use established development methods, but not as frequently as they will use a customised approach. Most developers do not rely upon one specific approach when creating multimedia, instead utilising a range of methodologies. This would indicate that one specific model cannot cater for the various platforms that do exist. Obviously, there are many physical differences between each platform, so this may indicate that their approaches must also change. Project requirements are the main influence behind a developer’s decision to select a given methodology. Other factors, such as cost and timelines also play some part in the choice of development model, but are not as important as the requirements of a project. It also appears that developers will stick to the models they know, as few indicated they had discontinued the use of other development methodologies. Customised approaches are the most likely to be used by developers for creating any kind of multimedia system. This may indicate that established methodologies are inappropriate for creating multimedia. As the origins of many established methodologies come from traditional IS development, this provides some foundation to such an argument. However, considering that there are several developers who do utilise such theoretical approaches, such a statement tends to be unfounded. Perhaps not all multimedia developers have the same education or training as more traditional computing employees. This could reflect the lack of formal models used in multimedia systems development. A more troubling statistic is that there are developers who do not employ any methodology for creating multimedia. Any kind of methodology will bring structure and control to the development process, so there are obvious benefits available. Another angle that could be adopted is that there is a need for more methodologies to be created specifically for multimedia. Developers could have difficulty trying to adopt traditional IS methodologies for multimedia, therefore there is a trend to use their own methods which are easier to understand. It is clear there are models that have been successfully applied for multimedia development, but their origins appear to lie in the IS arena. Whilst the trend for proprietary approaches remains apparent, further research into such models could reveal more details about how those models are put to work. It is possible that there are certain qualities within these customised models that reflect those found in traditional methods. This would then indicate that there is an underlying theoretical influence within these approaches. A wider international study with a larger response rate may ratify the current indicators of methodology usage, or perhaps provide new answers. A study that measured the levels of overall project success and client satisfaction with a given methodology may offer a more credible insight into what are the most suitable methodologies for creating multimedia systems. Overall, the majority of developers use some form of methodology. However, it appears that traditional methods are not well accepted amongst multimedia developers, so there is a tendency to use customised approaches. Many possibilities have been discussed as to the cause of this finding. Until more multimedia-specific development methodologies are conceived and promoted, it would appear that this current trend is likely to continue.

REFERENCES Boehm, B., Egyed, A., Kwan, J., Port, D., Shah, A. and Madachy, R. (ed) (1998) “Using the WinWin Spiral Model: A Case Study”, Computer, IEEE Computer Society, New York, Vol 31, Issue 7, pp. 33-44

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4 2006 IRMA International Conference Dennis, A. and Wixom, B.H. (2000) Systems Analysis and Design: An Applied Approach, John Wiley & Sons, New York, pp 9-16, 7274, 120-124. Hoffer, J.A., George, J.F. And Valacich, J.S. (1999) Modern Systems Analysis and Design (2nd Ed.), Addison-Wesley, Reading, pp 2434, 486-498. MacCormack, A. (ed.) (2001) “Product-development Practices That Work: How Internet Companies Build Software”, MIT Sloan Management Review, MIT Sloan School of Management, Cambridge, Vol 42, Issue 2, pp. 75-84 Pfleeger, S.L. (1998) Software Engineering: Theory and Practice, Prentice Hall, New Jersey, p. 126

Pressman, R. (2000) Software Engineering: A Practitioner’s Approach, McGraw-Hill, New York, pp 29-47 Satzinger, J.W., Jackson, R.B., Burd, S.D. (2004) Systems Analysis and Design in a Changing World (3 rd Edition), Course Technology, Boston, p. 42 Siegel, D. (1997) Secrets of Successful Web Sites: Project Management for the World Wide Web, Hayden Books, Indianapolis, pp 160-168, 206282. Sommerville, I. (2001) Software Engineering (6 th Edition), Addison Wesley, Essex, pp. 53-55 Vaughan, T. (1998) Multimedia: Making it Work (4th Edition), Osborne/ McGraw-Hill, Berkeley, pp 428-434

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Emerging Trends and Challenges in IT Management

5

Networkcentric Healthcare: Strategies, Structures and Technologies for Managing Knowledge Dag von Lubitz, MedSMART, Inc., Ann Arbor, MI 48904 & HH & GA Dow Coll. of Health Professions, Central Michigan University, Mt. Pleasant, MI 48804, T 734-527-7120, [email protected] Nilmini Wickramasinghe, Center Management Medical Technology, Stuart Graduate School of Business, Illinois Institute of Technology, Chicago, IL 60661, T 312-906-6578, [email protected]

ABSTRACT The proliferation of IC 2T (information computer and communication technologies ) throughout the business environment has lead to exponentially increasing amounts of data and information generation. Although these technologies were implemented to enhance and facilitate superior decision making what we see is information chaos and information overload; the productivity paradox [1-4]. Knowledge management is a recent management technique designed to make sense of this information chaos by applying strategies, structures and techniques to apparently unrelated and seemingly, what appears at times irrelevant data elements and pieces of information so that germane knowledge can be extracted[5-6]. The latter then serve in support of decision making, effective and efficient operations as well as enable an organisation to reach a state of information superiority. Critical to knowledge management is the application of IC2T [ibid]. However it is the configuration of these technologies that is important to support the techniques of knowledge management. This paper discusses how effective and efficient healthcare operations can ensue through the adoption of a networkcentric healthcare perspective that is grounded in the process oriented knowledge generation framework of Boyd and enabled through WHIG (world healthcare information grid) a totally integrated set of sophisticated IC 2T[7-9].

INTRODUCTION Healthcare is an information rich, knowledge intensive environment. In order to treat and diagnose even a simple condition a physician must combine many varied data elements and information. Such multispectral data must be carefully integrated and synthesized to allow medically appropriate management of the disease. Given the need to combine data and information into a coherent whole and then disseminate these findings to decision makers in a timely fashion, the benefits of IC 2T to support decision making of the physician and other actors throughout the healthcare system are clear [10]. In fact, we see the proliferation of many technologies such as HER (health electronic records), PACS (picture archive computerized systems) systems, CDSS (clinical decision support systems) etc. However and paradoxically, the more investment in IC2T by healthcare the more global healthcare appears to be hampered by information chaos which in turn leads to inferior decision making, ineffective and inefficient operations, exponentially increasing costs and even loss of life [10-11]. We believe the reason for this lies in the essentially platform centric application of IC2T to date within healthcare, which at the micro level do indeed bring some benefits but at the macro level only add to the problem by creating islands of automation and information silos that hinder rather than enable and facilitate the smooth and seamless flow of relevant information to any decision maker when and where such information is required.

To remedy this problem and maximize the potential afforded by IC2T and consequently alleviate the current problems faced by healthcare, we suggest the adoption of a networkcentric approach to healthcare operations. Such a networkcentric approach is grounded in a process oriented view of knowledge generation and the pioneering work of Boyd [7-9,12].

PROCESS ORIENTED KNOWLEDGE GENERATION Within knowledge management, the two predominant approaches to knowledge generation are people centric and technology centric [5,13]. A people oriented perspective draws from the work of Nonaka as well as Blacker and Spender [13-16]. Essential to this perspective of knowledge creation is that knowledge is created by people and that new knowledge or the increasing of the extant knowledge base occurs as a result of human cognitive activities and the effecting of specific knowledge transformations [ibid, fig 1a]. A technology driven perspective to knowledge creation is centred around the computerized technique of data mining and the many mathematical and statistical methods available to transform data into information and then meaningful knowledge [13, 17-27, fig 1b]. In contrast to both of these approaches, a process centric approach to knowledge creation not only combines the essentials of both the people centric and technology centric perspectives but also emphasises the dynamic and on going nature of the process. Process centred knowledge generation is grounded in the pioneering work of Boyd and his OODA Loop, a conceptual framework that maps out the critical process required to support rapid decision making and extraction of critical and germane knowledge [12-13]. The Loop is based on a cycle of four interrelated stages essential to support critical analysis and rapid decision making that revolve in both time and space: Observation followed by Orientation, then by Decision, and finally Action (OODA). At the Observation and Orientation stages, implicit and explicit inputs are gathered or extracted from the environment (Observation) and converted into coherent information (Orientation). The latter determines the sequential Determination (knowledge generation) and Action (practical implementation of knowledge) steps [ibid, fig1c]. The outcome of the Action stage then affects, in turn, the character of the starting point (Observation) of the next revolution in the forward progression of the rolling loop. Given that healthcare is such a knowledge rich environment that requires rapid decision making to take place that has far reaching consequences, a process centred approach to knowledge generation is most relevant and forms the conceptual framework for networkcentric healthcare operations.

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6 2006 IRMA International Conference Figure 1a.

NETWORKCENTRIC HEALTHCARE OPERATIONS Healthcare, like all activities conducted in complex operational space, both affects and requires the functioning of three distinct entities, i.e. people process and technology. To capture this dynamic triad that continually impacts all healthcare operations, the doctrine of healthcare network-centric operations is built around three entities that form mutually interconnected and functionally related domains. Specifically these domains include[7-9]:

PEOPLE PERSPECTIVE OF KNOWLEDGE GENERATION

Nonaka’s/Spender’s/Blackler’s K-Types Tacit/ Implicit/ Embrained

KNOWLEDGE

other K Types (embodied, encultured, embedded )

Social

Explicit

1) a. b.

The Knowledge Spiral

1. SOCIALIZATION

2. EXTERNALIZATION

Spender’s Actors

c. 4. COMBINATION

3. INTERNALIZATION

d.

Individual

2) a.

Figure 1b. TECHNICAL PERSPECTIVE OF KNOWEDGE GENERATION

b. c.

Steps in knowledge discovery

Selection

Preprocessing

Transformation

Data mining

Interpretation/ Evaluation

d. e. DATA

TARGET DATA

PREPROCESSED DATA

TRANSFORMED DATA

PATTERNS

KNOWLEDGE

3) a. b. Figure 1c. c. PROCESS PERSPECTIVE TO KNOWELDGE GENERATION

Observation Data/information collection

Orientation

Action

Boyd’s Loop

Competitive thrust

Determination Germane knowledge development

Data transformation /analysis/ Generation of germane information

Storage of nongermane data/information

a physical domain that: represents the current state of healthcare reality encompasses the structure of the entire environment healthcare operations intend to influence directly or indirectly, e.g., elimination of disease, fiscal operations, political environment, patient and personnel education, etc. has data within it that are the easiest to collect and analyze, especially that they relate to the present rather than future state. is also the territory where all physical assets (platforms) such as hospitals, clinics, administrative entities, data management facilities, and all other physical subcomponents (including people) reside. an information domain that: contains all elements required for generation, storage, manipulation, dissemination/sharing of information, and its transformation and dissemination/sharing as knowledge in all its forms. within the information domain, all aspects of command and control are communicated and all sensory inputs gathered. while the information existing within this domain may or may not adequately represent the current state of reality, all our knowledge about that state emerges, nonetheless, from and through the interaction with the information domain. all communications about the state of healthcare take place through interactions within this domain. the information domain is particularly sensitive and must be protected against intrusions that may affect the quality of information contained within domain. A cognitive domain that: constitutes all human factors that affect operations. is within the cognitive domain that deep situational awareness is created, judgments made, and decisions and their alternatives are formulated. also contains elements of social attributes (e.g., behaviours, peer interactions, etc.) that further affect and complicate interaction with and among other actors within the operational sphere.

In essence, these domains cumulatively serve to capture and then process all data and information from the environment and given the dynamic nature of the environment new information and data must always be uploaded. Thus, the process is continuous in time and space captured by the ‘rolling nature’ of Boyd’s OODA Loop; ie is grounded in the process oriented perspective of knowledge generation. IC 2 T Use in Healthcare Network Centric Operations The critical technologies for supporting healthcare networkcentric operations are not new, rather they are reconfigurations of existing technologies including web and Internet technologies. The backbone of the network is provided by WHIG (world healthcare information grid) [7-9]. WHIG consists of three distinct domains that are each made up of multiple grids all interconnecting to enable complete and seamless information and data exchange throughout the system. Figure 2 depicts the WHIG with its distinct yet interconnected domains each made up of interconnecting grids. The three essential elements of the grid architecture are the smart portal which provides the entry point to the network, the analytic node and the intelligent sensors [7-9]. Taken together these elements make up the knowledge enabling technologies to support and effect critical data,

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Emerging Trends and Challenges in IT Management Figure 2.

7

Figure 3.

THE NODE AND ITS ASSOCIATED SMART PORTAL - ENTRY POINT TO WHIG

Security & standards/ protocols

Network interactions:

Input from grid

Output to grid

Boyd’s Loop

Network elements: SENSOR ANALYTIC NODE

information and knowledge exchanges that in turn serve to ensure effective and efficient healthcare operations. In networkcentric healthcare operations the entry point or smart portal must provide the decision maker with pertinent information and germane knowledge constructed through the synthesis and integration of a multiplicity of data points; i.e. support and enable OODA thinking. Unlike current web pages in general and especially current medical webportals and on-line databases such as MedLine, that provide the decision maker with large amounts of information that he/she must then synthesise and determine relative and general relevance; i.e. they are passive in nature, the smart portal enables the possibility to access the critical information required to formulate the Action (practical implementation) stage of Boyd’s Loop. In addition, the smart portal includes the ability to navigate well through the grid system; i.e. the smart portal must have a well structured grid map to identify what information is coming from where (or what information is being uploaded to where). In order to support the ability of the smart portal to bring all relevant information and knowledge located throughout the grid system to the decision maker there must be universal standards and protocols that ensure the free flowing and seamless transfer of information and data throughout WHIG; the ultimate in shared services. Finally, given the total access to WHIG provided by the smart portal to the decision maker it is vital that the highest level of security protocols are maintained at all times; thereby ensuring the integrity of WHIG. Figure 3 captures all these key elements of the smart portal. The analytic nodes of the WHIG perform all the major intelligence and analysis functions and must incorporate the many tools and technologies of artificial intelligence and business analytics including OLAP (online analytic processing), genetic algorithms, neural networks and intelligent agents in order to continually assimilate and analyze critical data and information throughout the grid system and/or within a particular domain. The primary role of these analytic nodes is to enable the systematic and objective process of integrating and sorting information or support the Orientation stage of Boyd’s Loop. Although we discuss the functional elements of the analytic node separately, it is important to stress that the analytic node is in fact part of the smart portal. In fact, the presence of the analytic node is one of the primary reasons that the smart portal is indeed “smart” or active rather than its more passive distant cousin the integrated e-portal that dominates many intranet and extranet sites of e-businesses today. The final important technology element of WHIG is the intelligent sensor. These sensors are essentially expert systems or other intelligent detectors programmed to identify changes to WHIG and data and/or

information within a narrow and well defined spectrum, such as for example, an unusually high outbreak of anthrax in a localized geographic region, which would send a message of a possible bio-terrorism attack warning to the analytic node, or perhaps the possibility of spurious or corrupt data entering the WHIG system. The sensors are not necessarily part of the smart portal and can be located throughout WHIG independent of the analytic nodes and smart portals Figure 3 depicts the three essential technical components of WHIG. Knowledge Development, Support, and Dissemination In our earlier paper [8] we have pointed out that healthcare information quality depends inversely on its range, i.e., the shorter the distance between the source and recipient, and the lesser degree of information content manipulation, the higher the quality. Similar observations have been made by other authors in the context of military activities whose complexity closely matches that of healthcare [28]. At the moment, and even more so in the future, the highest quality of healthcare information reposes within medical libraries associated with major medical centers around the globe. However, despite over a twenty year long history of IAIMS (Integrated Advanced Information Management System) initiative [29] and increasing need for a drastic change of operational philosophy [30-31], the majority of medical libraries continue to function as the repositories for print-based knowledge (or its electronically disseminated substitute) whose participation in healthcare operations is driven by customer demand (essentially passive) rather than operate as dynamic, knowledge developing and disseminating entities capable of actively shaping the healthcare world. As pointed out by several authors [31-33] future medical libraries must “filter, focus, and interpret information” [34] and “distribution of information, not control, is key to establishing, and maintaining power” [35]. In the context of networkcentric healthcare operations the role of medical libraries transforms even further – the library becomes a node. Presently, major strides are made toward practical incorporation of the IAIMS concept in reality [36-37]. However, global scale networkcentricity demands capabilities extending beyond “reliable, secure access to information that is filtered, organized, and highly relevant to specific tasks and needs…” [36]. In addition to these essential requirements, networkcentric operations demand merging of multispectral information streams into coherent, operation-centered knowledge bases, development of real-time or near real time operational space awareness, and predictive capabilities that are beyond the current scope of medical library operational profiles. Thus, contrary to the technologically advanced library of today, the library-node of tomorrow

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8 2006 IRMA International Conference must adopt Boyd’s Loop principles of interaction with the environment as the principal philosophy of its interaction with the information world within which it functions [8]. Adaptation of such philosophy is also the critical step in transforming operational profile of the existing medical libraries from essentially passive repositories which, with varying degree of efficiency and reliability, transform the reposited information into coherent knowledge-base blocks, into active information seeking entities (nodes) that conduct their exploratory work not only within their pre-determined domain of healthcare, but also within all other domains whose content may be potentially relevant to healthcare itself. There is no doubt that the proposed change is fundamental. On the other hand, it is the change that moves the medical library beyond its current notion of the institutional “networked biomedical enterprise” [34] into a global-level knowledge development, -management and -dissemination center. Most significantly, aligning such centers within the WHIG structure will lead to a massive enhancement of their overall operational power which [7], accordingly to Metcalf’s law, increases in proportion to the square of the nodes connected to the network. The proposed transformation of the medical library into a fully capable healthcare knowledge management and dissemination node will require major changes in the profile of the employed personnel. Today’s librarian, exquisitely skilled in client-mandated database searches and information retrieval will become a powerful knowledge worker intimately familiar with the processes of active seeking new information, converting often unrelated information into coherent knowledge streams, and, ultimately, unifying individual streams and fusing them into the body of general healthcare knowledge base. The new breed of healthcare knowledge workers will be essential in development of CDSS, identification of new disease patterns, creation of new administrative tools, and positioning of global healthcare systems toward “just-in-time” responses to crises. Thus, the currently subordinate role of a librarian presently operating as a support element in healthcare delivery will shift to that of an equal partner of a physician and administrator. In some situations, particularly those involving large area events, healthcare knowledge workers may even assume the subordinate role of countermeasure effort coordinators and leaders. The widened scope of their importance in global healthcare operations imposes the need for rapid change in education of the new generation of “librarians” who, particularly in the context of networkcentric healthcare operations, will need to function as integral members of large, multidisciplinary management teams and be intimately familiar with several disciplines stretching beyond the classical realm of medicine and its affiliates. The rapidly approaching need for new skills is evidenced by increasing number of papers devoted to this subject and the introduction of new training programs aimed at the creation of “new generation” specialists [38-42]. There is thus no doubt that, in similarity to military activities (from which the concept of networkcentricity also evolves), healthcare operations will need to adopt the philosophy of “jointness’ where many currently independent disciplines will need to combine and interact in order to attain the stated overall goal – maintenance of global health.

of effort. Highly useful information generated within individual systems is, for all practical purposes, lost since it is inaccessible to others either because of its incompatibility with different operational platforms or simply because others are not even aware of its existence! The latter issue becomes particularly significant when relevant information exists within healthcare-unrelated domains. Particularly apt and very recent example of such failure were the recovery efforts after the tsunami disaster of 2004, where the world dispatched badly needed medical supplies to the affected regions but failed to relate the transport to on site distribution. The supplies piled up at major airports while healthcare workers in the field were short of the most basic commodities. The currently practiced approach to healthcare informatics supports reoccurrence of similar events: for all practical purposes healthcare informatics limits its sphere of activity only to subjects strictly related to medicine, its practice, and administration at the healthcare organization level. Yet, healthcare relates to a number of other elements of life – political structure of the region, its stability, its economy, even its weather. Failure to incorporate these seemingly irrelevant domains of information results in the emergence of medical “earthquakes” such as the discovery that, contrary to the assumptions of the West, cardiovascular disease is the predominant killer in among the populations of the underdeveloped World [43]. We believe that adoption of the networkcentric approach that is integrally connected to the process perspective of knowledge management may provide at least part of the solution, especially at the worldwide level of healthcare. The concept is not new. In 1994, DA Lindberg described a vision of global information infrastructure based on extensive implementation and exploitation of US-leadership in high performance computing, networking, and communications in developing a large-scale, technology-based approach to healthcare. During the same decade, the US Department of Defense followed by military establishments around the world adopted the notion of networkcentric operations as the most viable solution to the ever increasing complexity of military operations [28]. Similar concepts are brought to life in multilayered, dynamic business activities [44]. Healthcare operations are equally complex, if not more so, than either business or military ones. Their information/knowledge needs are equally multispectral and intense. And while healthcare is, indeed, about providing an individual with easy access to healthcare provider, and providing the provider with tools to provide adequate healthcare, it all takes place in a vastly more complicated environment of economies, policies and politics, and, far too frequently – conflicts. We believe, therefore, that in similarity to the two other fields of human activity to which healthcare is (maybe unfortunately) also related – business and war – healthcare needs to expands its incursion into the world of IC 2 T to the concept of networkcentricity and pursue it with utmost vigour. As already demonstrated in practice [44], networkcentric operations increase efficiency, reduce cost, and increase chance of success. All of these are of critical importance in the conduct of a single, most expensive and yet significantly inefficient activity known to humankind – the conduct of global healthcare operations.

DISCUSSION AND CONCLUSION

REFERENCES

At its most fundamental (and maybe also the most naïve) healthcare is about assuring and maintaining individual’s adequate level of health necessary to function as a fully capable member of the society. In reality, healthcare, particularly in its global context, became a business growing at an unprecedented rate, where global disparities in healthcare delivery become increasingly more apparent, where technology emphasizes them rather than assists in their obliteration, and where the current expenditure of trillions of dollars yearly appears to have no impact at all. Part of the problem rests with the fact that the majority (if not all) solutions to the healthcare crisis are, essentially, platformcentric, i.e., concentrate on the highly specific needs of a specialty (e.g., molecukar biology), an organization (e.g., hospital) or a politically defined region (e.g., US or EU). Hence, most of the technology-based solutions, while highly functional and of unquestionable benefit to their users, fail to act as collaborative tools assisting in the unification rather than subdivision

1. 2. 3. 4.

5. 6.

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Emerging Trends and Challenges in IT Management 7.

8.

9.

10.

11.

12.

13.

14. 15. 16. 17. 18.

19.

20.

21.

22.

23.

24.

25.

26. 27. 28.

von Lubitz, D. and Wickramasinghe, N., 2005. in press Healthcare and Technology: The Doctrine of Networkcentric Healthcare, Health Care Management Science von Lubitz, D. and Wickramasinghe, N., 2005. in press Networkcentric Healthcare and Bioinformatics: unified operations within three domains of knowledge Intl J. Expert Systems von Lubitz and Wickramasinghe, N., 2005 in press Networkcentric Healthcare: outline of the entry portal concept Intl J. Electronic Business Management Wickramasinghe, N., Geisler, E., and Schaffer, J., 2005. Realizing The value Proposition for Healthcare By Incorporating KM strategies and Data Mining Techniques with the use of information communication technologies, in press Int. J. Healthcare Technology and Management Wickramasinghe, N., Bloomendal, H., de Bruin, A., and Krabbendam, K., 2005. Enabling Innovative Healthcare Delivery Through the Use of the Focused Factory Model: The Case of the Spine Clinic of the Future. International Journal of Innovation and Learning (IJIL). no. 1 p.90-110 Boyd JR, COL USAF, 1987. in Patterns of Conflict, unpubl Briefing (accessible as “Essence of Winning and Losing”, http:/ /www.d-n-i.net ) von Lubitz, D., and Wickramasinghe N. 2005. Creating germane knowledge in dynamic environments, Intl. J. Innovation Learning, in press. Nonaka, I and Nishiguchi, T., 2001. Knowledge Emergence, Oxford University Press, Oxford. Nonaka, I 1994. A dynamic theory of organizational knowledge creation Organizational Science no.5 p.14-37. Newell, S., Robertson, M., Scarbrough, H., and Swan. J., 2002. Managing Knowledge Work Palgrave, New York. Adriaans, P. and Zantinge, D., 1996. Data Mining, AddisonWesley, Boston. Cabena, P., Hadjinian, P., Stadler, R., Verhees, J., and Zanasi, A., 1998. Discovering Data Mining from Concept to Implementation, Prentice Hall, Upper Saddle River. Bendoly, E. 2003. Theory And Support For Process Frameworks Of Knowledge Discovery And Data Mining From ERP Systems, Information & Management, 40 p.639-647. Fayyad, Piatetsky-Shapiro, and Smyth, 1996. From Data Mining to Knowledge Discovery: An Overview, in Fayyad, PiatetskyShapiro, Smyth, Uthurusamy, Advances in Knowledge Discovery and Data Mining, AAAI Press / The MIT Press, Menlo Park, CA. Holsapple,C., and Joshi, K., 2002. Knowledge Manipulation Activities: results of a Delphi Study. Information & Management, 39 p.477-419 Choi, B., and Lee, H., 2003. An empirical Investigation of KM styles and Their effect on Corporate Performance. Information & Management, 40 p.403-417 Chung, M and Gray, P. 1999. Special Section: Data Mining. Journal of Management Information Systems No. 1, Summer p. 11 - 16 Becerra-Fernandez, I. and Sabherwal, R., 2001. Organizational Knowledge Management: A contingency Perspective No. 1, Summer p. 23-55. Yen, D., Chou, D. and Cao, J. 2004 Innovation in Information Technology: integration of web and database technologies Intl J. of Innovation and Learning p. 143-157 Award,E. and Ghaziri, H. 2004 Knowledge Management Prentice Hall, Upper Saddle River. Wickramasinghe, N. and S. Sharma in press Fundamentals of Knowledge Management , Prentice Hall, Upper Saddle River. Alberts, D.S., Garstka, J.J., & Stein, F.P. 2000. Network centric warfare: developing and leveraging information superiority, CCRP Publication Series (Dept. of Defense), Washington, DC, (1-284). (available at http://www.dodccrp.org/publications/pdf/ Alberts_NCW.pdf

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Matheson, N.W., 1995, Things to come: postmodern digital knowledge management and medical informatics, J. Am. Med. Informatics Assoc. 2, 73-78 Kronenfeld, M.R., 1995 Trends in academic health sciences libraries and their emergence as the “knowledge nexus” for their academic health centers, J. Med. Libr. Assoc. 93, 32-9 Blansit, B.D., Connor, E., 1999. Making sense of the electronic resource marketplace: trends in health related electronic resources, Bull. Med. Libr. Assoc. 87, 243-250 DuVal, M.K., 1967. “The changing role of the library” Public address given at “The Emerging Role of Medical Libraries” Session of the 66 Annual Meeting of the Medical Library Association, Miami, FL, June 14 Fuller, S.S., Ketchell, M.L., Tarczy-Hornoch, Masuda, D. 1999. Integrating knowledge resources at the point of care: opportunities for the librarians, Bull. Med. Libr. Assoc. 87, 393-403 Stead, W.W., 1998. Positioning the library at the epicenter of the networked biomedical enterprise, Bull. Med. Libr. Assoc. 86, 26-30 Martin, C., 1997. Digital estate: strategies for competing, surviving, and thriving in an Internetworked world, McGraw Hill (New York) McGowan, J.J., Overhage, J.M., Barnes, M., and McDonald, C.J., 2004. Indianapolis I3: the third generation Integrated Advanced Information Management Systems, J. Med. Libr. Assoc. 92, 179187 Guard, J.R., Brueggeman, R., Hutton, J.J., Kues, J.R., Marine, S.A., Rouan, W., and Schick, L., 2004. Integrated Advanced Information Management System: a twenty-year history at the University of Cincinnati, J. Med. Libr. Assoc. 92, 171-78 Moore, M.E., Vaughan, K.T., and Hayes, B.E., 2004. Building a bioinformatics community of practice through library education programs, Med. Ref. Serv. Q. 23, 71-9 Florance, V., Giuss, N.B., and Ketchell, D.S., 2002. Information in context: integrating information specialists into practice settings, J. Med. Libr. Assoc. 90, 49-58 Keeling, C., and Lambert, S., 2000. Knowledge management in the NHS: positioning the healthcare librarian at the knowledge intersection, Health Libr. Rev. 17, 136-43 NHS Regional Librarian Group evidence to the Functions and Manpower Review 1993-94. Manpower of library services in the proposed new structure. Health Libr. Rev. 13, 187-92 Aronow, D.B., Payne, T.H., and Pincetl, S.P., 1991. Postdoctoral training in medical informatics: a survey of National Library of Medicine-supported fellows, Med. Decis. Making 11, 29-32 Leeder, S., Raymond, S., Greenberg, H., Liu, H., and Esson, K. (Eds), 2004. A Race Against Time: The Challenge of Cardiovascular Disease in Developing Countries, The Earth Institute at Columbia University http://www.earth.columbia.edu/news/2004/ images/raceagainsttime_FINAL_0410404.pdf Cebrowski, A.K., and Garstka, J.J., 1998. Network-centric warfare: its origin and future, US Nav. Inst. Proc. 1, 28-35

LEGENDS TO FIGURES FIG. 1 The processes of creating and capturing knowledge, irrespective of the specific philosophical orientation (i.e. Lockean/Leibnitzian versus Hegelian/Kantian), is the central focus of both the psycho-social (people) and algorithmic (technology) theories of knowledge creation. However, to date knowledge creation has tended to be approached from one or the other perspective, rather than an holistic, combined perspective [5]. Fig. 1a highlights the essential aspects of the three well known psycho-social knowledge creation theories; namely, Nonaka’s Knowledge Spiral, Spender’s and Blackler’s respective frameworks into one integrative framework by showing that it is possible to change the form of knowledge; i.e., transform existing tacit knowledge into new explicit knowledge and existing explicit knowledge into new tacit knowledge or

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10 2006 IRMA International Conference to transform the subjective form of knowledge into the objective form of knowledge [5-6,13-16, 27]. In effecting such transformations the extant knowledge base as well as the amount and utilization of the knowledge within the organization increases. According to Nonaka [14]: 1) Tacit to tacit (socialization) knowledge transformation usually occurs through apprenticeship type relations where the teacher or master passes on the skill to the apprentice. 2) Explicit to explicit (transformation) knowledge transformation usually occurs via formal learning of facts. 3) Tacit to explicit (externalization) knowledge transformation usually occurs when there is an articulation of nuances; for example, as in healthcare if a renowned surgeon is questioned as to why he does a particular procedure in a certain manner, by his articulation of the steps the tacit knowledge becomes explicit and 4) Explicit to tacit (internalization) knowledge transformation usually occurs as new explicit knowledge is internalized it can then be used to broaden, reframe and extend one’s tacit knowledge. The two other primarily people driven theories that focus on knowledge creation as a central theme are Spender’s and Blackler’s respective frameworks [5, 13, 16, 27]. Spender draws a distinction between individual knowledge and social knowledge, each of which he claims can be implicit or explicit [ibid]. Spender’s definition of implicit knowledge corresponds to Nonaka’s tacit knowledge. However, unlike Spender, Nonaka doesn’t differentiate between individual and social dimensions of knowledge; rather he just focuses on the nature and types of the knowledge itself. In contrast, Blackler [ibid] views knowledge creation from an organizational perspective, noting that knowledge can exist as encoded, embedded, embodied, encultured and/or embrained. In addition, Blackler emphasized that for different organizational types, different types of knowledge predominate and highlighted the connection between knowledge and organizational processes [ibid]. In contrast to the above primarily people oriented frameworks pertaining to knowledge creation, knowledge discovery in databases (KDD), and more specifically data mining, approaches knowledge creation from a primarily technology driven perspective. In particular, the KDD process focuses on how data is transformed into knowledge by identifying valid, novel, potentially useful, and ultimately understandable patterns in data [17-27]. KDD is primarily used on data sets for creating knowledge through model building, or by finding patterns and relationships in data using various techniques drawn from computer science, statistics and mathematics. From an application perspective, data mining and KDD are often used interchangeably. Fig 1b presents a generic representation of a typical knowledge discovery process. Knowledge creation in a KDD project usually starts with data collection or data selection, covering almost all steps in the KDD process; the first three steps of the KDD process (i.e., selection, preprocessing and transformation) are considered exploratory data mining, whereas the last two steps (i.e., data mining and interpretation/evaluation) in the KDD process are considered predictive data mining. A process centric perspective view of knowledge creation is found in Boyd’s OODA Loop model (Fig 1c). The Loop (Fig 1c) is based on a cycle of four interrelated stages essential to the extraction of germane knowledge necessary to support critical analysis, rapid decision making: Observation followed by Orientation, then by Decision, and finally Action (OODA). At the Observation and Orientation stages, implicit and explicit inputs are gathered or extracted from the environment (Observation) and converted into coherent information (Orientation). The latter determines the sequential Determination (knowledge generation) and Action (practical implementation of knowledge) steps [13]. The outcome of the Action stage then affects, in turn, the character of the starting point (Observation) of the next revolution in the forward progression of the rolling loop. In Fig 1c, this is represented with the removal of non germane data/information/knowledge from continuing to the next step. It is important to note that at all stages within the OODA loop both people and technology perspectives are supported and required to enable and facilitate germane knowledge extraction.

FIG. 2 Although ultimately directed at the individual patient, delivery of modern healthcare is an exceedingly complex operation involving several layers, many of which are not directly related to healthcare itself. In most extreme cases (e.g., smallpox) treatment of a single patient may trigger a cascade of events affecting several countries that may be separated by very large distances. Rapid containment of the consequences of such events may require highly specialized knowledge, high degree of dynamic and environment-sensitive multispectral information/ knowledge coordination, analysis, and transformation into a multidimensional picture of the “operational space” characterizing the event. Presently, due to the mutual incompatibility of the existing information/knowledge resources (platformcentricity),, inefficiency of knowledge management organizations, and lack of coordination among national and international bodies either directly or indirectly involved in healthcare delivery, efficiency of the “operators,” i.e., healthcare delivery personnel and their parent organizations (ambulance units, ambulatory clinics, hospitals, etc.) is significantly reduced, particularly during cataclysmic events when the need reaches its peak. The concept of networkcentricity in healthcare operations reduces the current deficiencies by assuring continuous, unimpeded and polydirectional flow of information among the nodes (depicted as cylinders) populating the WHIG (World Healthcare Information Grid). At the level of the “Operators” each node constitutes of an efficient knowledge management organization (e.g., medical library attached to a major medical centre – see ref. XX (HICS paper). Operator layer nodes interact with the nodes within other networks such as Organizations’ Network (national and international governmental organizations, NGOs, insurers, etc.), Politics Network (such as ministerial level organizations, judicial or parliamentary elements), Infrastructure Network (communication facilities, transportation, power grids, etc.) that, at times may also be linked to law enforcement/military nodes (particularly during humanitarian/disaster relief healthcare operations). Commonality and compatibility of standards determining extraction, analysis, storage, and dissemination of the information/knowledge within WHIG are mandatory in networkcentric operations. The power of WHIG is directly proportional to the square of the number of the populating nodes, while adherence to the ASP (Application Software Provider concept) and the development of intelligent WHIG access portals will assure accessibility even to those entities whose technology-base is less than optimal. FIG 3. The entry point to WHIG is a “smart” portal (Fig 3). Unlike a traditional portal the smart portal is active or dynamic. It provides the decision maker or effector access to relevant data, pertinent information and germane knowledge required for a specific query [9]. This is achieved by the interaction of the decision maker via the smart portal in conjunction with the analytic nodes. It is in fact the intelligence capabilities and knowledge management technologies of the analytic nodes throughout WHIG which support process centric knowledge management, that make the smart portal “smart”. The analytic nodes obtain and process all multispectral data throughout and process it into pertinent information and germane knowledge that is assimilated and synthesized at the smart portal and then made available to the decision maker. Other design elements unique to the smart portal include the ability to navigate well through the grid system, sophisticated security protocols and the existence of sensors in the network that detect erroneous or critical data.

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Emerging Trends and Challenges in IT Management

11

Measuring Credibility Assessment Targets in Web-Based Information James D. Collins, Missouri Southern State University, 3950 East Newman Road, Joplin MO {Phone: (417) 625-9661, Fax: (417) 6594450, E-mail: [email protected]}

PROBLEM STATEMENT AND GOAL This research consisted of two separate, but inter-related studies. In Study 1, a rating scale, called the Web Credibility Scale, was created to measure the credibility of a Web page. This scale improves the precision of measuring the credibility of Web pages by offering a replacement to the unvalidated scales currently in use [3]. Study 2 included the goal of learning more about credibility assessment targets [6]. This refers to the precise focus of user attention when evaluating the credibility of a Web page. Fogg and Tseng have postulated four targets of credibility assessment: on-screen characters, computer qua computer (the computer itself), brand (a corporation), and expert creator. However, their work does not address comparative magnitudes of influence between these four targets. The research in Study 2 compared two of the targets, brand and expert creator, in an experiment to discover which makes a greater contribution to credibility. Both studies used 100 to 200 participants, which should provide ample sample size [18]. Fogg and Tseng [6] provide little information on the characteristics of the credibility assessment targets postulated and they have not been investigated in later research [4, 5]. Consequently, the precise details on their definition are lacking other than brand refers to a corporation as the source of a Web page and expert creator refers to an individual as the source of a Web page. The difference between brand and expert creator seems to hinge on the fact that one is an institution and the other an individual. In order to experimentally determine which of the two credibility assessment targets makes a greater contribution to credibility, it seemed reasonable to include a means of accounting for preexisting differences in participants’ disposition to trust—differences in participants’ general expectation of another’s trustworthiness. Disposition to trust affects how much a person is willing to trust [10] and is especially important when one is unfamiliar with the situation or individuals involved. Several researchers have included disposition to trust when investigating the perception of trustworthiness in others [16, 17]. Together, Study 1 and Study 2 accomplished the following three goals: 1. 2.

3.

Developed a reliable and valid instrument to measure the credibility of Web-based information. Collected data on preexisting differences in participants’ disposition to trust and incorporated it into the experiment in Study 2. Conducted an experiment to determine if credibility perception differs when the source is manipulated.

2. 3.

4. 5. 6.

Credibility Assessment Targets — precise focus of user attention when evaluating the credibility of a Web page. Disposition to trust — a tendency, consisting of the subconstructs benevolence, integrity, competence, and trusting stance, to treat others as trustworthy in a variety of situations [10]. Expertise — the amount a communicator is seen as a valid source of assertions [7]. Trust — the willingness to become vulnerable to another due to some expectation, but independent of any external controls [9]. Trustworthiness — the perceptions of the probability that a source is providing information that the source considers to be correct [7].

SOLUTION PROCESS AND DETAILS Item generation for the Web Credibility Scale began with adoption of a definition of credibility as the perception of expertise and trustworthiness of the source of a message, which was first given by [7]. Existing literature was used to construct questions to measure expertise and

Table 1. Web credibility scale with 31 items Question 1. I believe the source would act in my best interest. 2. If I required help, the source would do its best to help me. 3. The source is interested in my well-being, not just its own. 4. I trust the source. 5. The source is truthful in its dealings with me. 6. The source presents information that is reliable. 7. The source is fair. 8. The source is impartial in the presentation of information. 9. The source is well-intentioned. 10. The source presents information that is unbiased. 11. I would characterize the source as honest. 12. The source is sincere in the presentation of information. 13. I believe the source. 14. The source presents information that is convincing. 15. The source treats others with decency.

In addition to the three goals given above, two research questions were investigated. 1. 2.

Will disposition to trust significantly influence the perception of credibility? If one credibility target makes a greater influence on credibility than the other, are the differences statistically significant?

16. I believe the source is honorable in dealing with others. 17. The source has a great amount of knowledge. 18. The source is intelligent. 19. I believe the source is very capable. 20. The source has a great amount of experience. 21. The source has a great amount of competence.

BACKGROUND (DEFINITION OF TERMS)

22. I would characterize the source as powerful.

1.

23. Overall, the source is very capable.

Credibility — the perception of expertise and trustworthiness of the source of a message [7].

24. I believe the source is skillful in what it does. (table continues)

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12 2006 IRMA International Conference Table 1. cont.

Table 3. Factor analysis with all items

Question

Question

Factor 1 Factor 2 Factor 3

1. The source is very accurate in the presentation of information.

16. I believe the source is skillful in what it does.

.83

.23

2. I would characterize the source as factual when dealing with others.

15. Overall, the source is capable.

.77

.40

.16

3. The source is well-trained.

18. I believe the source is a leader in their field.

.73

.19

.36

4. I believe the source is well-informed.

20. The source performs their role well.

.72

.38

.21

5. I believe the source is a leader in their field.

14. The source is competent.

.70

.42

.17

6. The source could be characterized as an authority.

19. The source could be characterized as an authority.

.69

.17

.16

21. The source has an excellent past performance.

.58

.44

.20

10. The source treats others with decency.

.29

.81

.17

11. I believe the source is honorable in dealing with others.

.34

.79

.27

7. The source performs their role very well.

trustworthiness by subdividing each one into smaller components. In addition, two existing instruments, the Trusting Beliefs Scale [11] and the Perceived Corporate Credibility Scale [13] were used to provide additional initial items in the Web Credibility Scale. The resulting 31item scale, shown in Table 1, included 16 items intended to represent the trustworthiness dimension and 15 items designed to represent the expertise dimension.

.21

9. I would characterize the source as honest.

.33

.71

.41

4. The source is interested in my well-being, not just its own.

.32

.68

.35

6. The source is fair.

.27

.65

.42

3. If I required help, the source would do its best to help me.

.34

.63

.35

To strengthen the evidence for content validity, a panel of five experts reviewed the initial items in the Web Credibility Scale. Reviewers were asked to evaluate the 31 initial items for sampling adequacy—the extent to which the items effectively reflect the domain of credibility. Feedback from the panel resulted in rewording three items, eliminating twelve items, and adding two items. The resulting 21-item scale, shown in Table 2, was then formatted as a 7-point Likert-type instrument. Pilot testing of the format with 20 university student participants revealed no areas of concern in usability of the instrument; all 20 participants responded that the instrument was easy to understand and use.

2. I believe the source would act in my best interest.

.40

.60

.34

12. The source discloses full information, good and bad.

.13

.17

.79

Full administration of the Web Credibility Scale was conducted at Missouri Southern State University and the data collected was used to investigate the construct dimension of credibility and select items for deletion. One hundred seventy-two completed surveys were collected in

Table 2. Web credibility scale with 21 items Question 1. The source presents information that is reliable. 2. I believe the source would act in my best interest. 3. If I required help, the source would do its best to help me. 4. The source is interested in my well-being, not just its own. 5. The source is truthful in its dealings with me. 6. The source is fair. 7. The source is impartial in the presentation of information. 8. The source presents information that is unbiased. 9. I would characterize the source as honest. 10. The source treats others with decency. 11. I believe the source is honorable in dealing with others. 12. The source discloses full information, good and bad. 13. I would characterize the source as factual when dealing with others. 14. The source is competent. 15. Overall, the source is capable. 16. I believe the source is skillful in what it does. 17. The source is accurate in the presentation of information. 18. I believe the source is a leader in their field. 19. The source could be characterized as an authority. 20. The source performs their role well. 21. The source has an excellent past performance.

8. The source presents information that is unbiased.

.20

.31

.77

7. The source is impartial in the presentation of information.

.18

.31

.72

17. The source is accurate in the presentation of information.

.51

.29

.65

5. The source is truthful in his dealings with me.

.29

.53

.57

13. I would characterize the source as factual when dealing with others.

.46

.47

.57

1. The source presents information that is reliable.

.47

.36

.49

Study 1. An exploratory factor analysis of the 21 items was conducted to eliminate items that did not load on the appropriate high-level construct, as recommended by McKnight et al. [11]. When no factors were specified for the exploratory factor analysis, a three-factor solution was generated with eigenvalues greater than one. The threefactor solution, shown in Table 3, consisted of one factor made up entirely of items designed to measure source expertise; a second factor consisted entirely of items designed to measure source trustworthiness, and a third factor consisted of a mix of items designed to measure either expertise or trustworthiness. Although the third factor contained items written to measure either the expertise or trustworthiness of a source, a common theme could be identified—the source’s ability to convey correct information. Scree plot analysis suggested a two-factor solution consisting of expertise and trustworthiness. Consequently, the third factor was removed. After removal of the third factor, which consisted of seven items, two factors remained with seven items in each. Together the two factors explained 69% of the variance. The Web Credibility Scale was shortened to reduce participant fatigue and decrease semantic overlap [1] and make it more comparable to other trust-like scales [20, 18, 15]. Reducing the number of items in the Web Credibility Scale to eight resulted in decreasing reliability for the expertise factor from .92 to .88 and decreasing reliability for the trustworthiness factor from .93 to .90. Overall reliability of the Web Credibility Scale with eight items was .92, which is characterized as high according to Ohanian [14] and very good according to DeVellis [2]. The final version of the Web Credibility Scale is presented in Table 4. Items were designed so that the generic term “the source” would be replaced with the specific source of a Web page; in this study, “the source” was replaced with the name of a person (an expert creator) or the name of a company (a brand) and the sentence slightly reworded as appropriate for the type of source.

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Emerging Trends and Challenges in IT Management Table 4. Item analysis for the Web credibility scale Question

Item-Total Correlation

Alpha if Item Deleted

11. I believe the source is honorable in dealing with others.

.80

.90

15. Overall, the source is capable.

.80

.90

9. I would characterize the source as honest.

.78

.91

10. The source treats others with decency.

.73

.91

16. I believe the source is skillful in what it does.

.73

.91

4. The source is interested in my well-being, not just its own.

.70

.91

18. I believe the source is a leader in their field.

.69

.91

21. The source has an excellent past performance. Note. Coefficient alpha for both factors together is .92.

.66

.91

The Web Credibility Scale was evaluated for convergent and discriminant validity using two other scales that were administered along with the Web Credibility Scale: the Trusting Beliefs Scale [11] and the Perceived Complexity of Computer Use [8]. The 11-item Trusting Beliefs Scale was designed to measure the perceived benevolence, integrity, and competence of the source of a Web site offering legal advice. The Perceived Complexity of Computer Use Scale was developed to measure the amount of difficultly participants perceived in using a computer. The Pearson product-moment correlation coefficient was utilized to measure the relationships between the continuous scales. A strong correlation (r = .91, p < .05) between the Web Credibility Scale and the Trusting Beliefs Scale and no correlation (r = .02) between the Web Credibility Scale and the Perceived Complexity of Computer Use Scale were found. As with any scale development, further studies in a more generalized population will be required for greater generalizability. Since initial support for validity and reliability was found, the Web Credibility Scale was deemed ready for use in Study 2, where the remaining goals and research questions were investigated. The experiment using the Web Credibility Scale in Study 2 addressed disposition to trust by use of a blocking design through the following steps. First, 200 participants were measured on disposition to trust using the scale developed by McKnight et al. [11]; this was a separate sample from the one used in scale development. After this, participants were grouped according to their scores into one of three groups: low, medium, or high, as suggested by Yamagishi and Kikuchi [21]. Three groups of participants are sufficient to capture curvilinear relationships between CV and DV [19]. Lastly, participants from each of the three groups were randomly assigned to one of the two manipulated IV levels so as to place an equal number of low, medium, and high disposition to trust scoring participants in both levels. An independent-samples t-test indicted that the two participant groups did not differ significantly in disposition to trust. Study 2 compared the two assessment targets, brand and expert creator, proposed by Fogg and Tseng [6] to discover which makes a greater contribution to credibility. One group of participants viewed a Web page that appeared to be authored by a corporation (brand version), while a different experimental group of participants viewed the same Web page, but from a different source—a person (expert creator version). Both Web pages represent modifications of the original Web pages at http:/ /sir.jrc.it/abi/ [12].

thiness and expertise, which make up the Web Credibility Scale, also revealed no significant difference between the two participant groups. Thus, Study 2 lends support to the conclusion that, in some situations, neither of the two credibility assessment targets is more important than the other in fostering the perception of credibility. A correlation between perceived credibility and disposition to trust was found (r = .55, p < .01, n = 189). As participants’ disposition to trust scores increased, so did their perception of credibility. Thus, the research question investigating whether disposition to trust significantly influences the perception of credibility can be answered; there is a correlation between disposition to trust and perception of credibility. Since there is a correlation between disposition to trust and perception of credibility, an even distribution of participants into the two participant groups based on their disposition to trust scores helps to assure that measurement of credibility perception between the two groups is not biased by disposition to trust. It is unknown if disposition to trust would have been evenly distributed by relying on random assignment alone. Correlations between disposition to trust and credibility subconstructs were also conducted. The correlation between disposition to trust and the factors of credibility, expertise (r = .52, p < .01) and trustworthiness (r = .51, p < .01), was almost even. The correlation between the factors of disposition to trust, benevolence, integrity, competence, and trusting stance, revealed the highest correlations between expertise and integrity (r = .52, p < .01) and trustworthiness and integrity (r = .51, p < .01). The lowest correlations between the factors were between expertise and trusting stance (r = .36, p < .01) and trustworthiness and trusting stance (r = .36, p < .01). Consequently, participants with the highest disposition to perceive integrity in others tend to also perceive more credibility in Web pages. The correlation between credibility and disposition to trust provided further evidence of convergent validity support for the Web Credibility Scale. Several authors have postulated a relationship between trustworthiness and disposition to trust [13, 6, 16, 17]. Similarly, this study postulated a relationship between credibility and disposition to trust and a correlation between data collected from the Web Credibility Scale and the Disposition to Trust Scale [11] was found. Consequently, the Web Credibility Scale behaved as expected, which [2] indicates is crucial to construct validity support. Given the results of the present study indicating beginning evidence of reliability and validity, the Web Credibility Scale can be recommended for use in studies on credibility and Web page design. In this way, the Web Credibility Scale has the potential to aid in understanding credibility— how it differs from other trust-like constructs and how it is assessed by users.

REFERENCES 1.

2. 3. 4.

5.

SOLUTION RESULTS An independent-samples t-test indicated that the two groups did not significantly differ (p = .01); those that viewed the brand version of the Web page perceived the same amount of credibility as those that viewed the expert creator version. Scores from the Web Credibility Scale could range from –24 to +24; the average score reported between the two participant groups was 8.45. Comparisons of the two subscales, trustwor-

13

6.

7.

Bhattacherjee, A. (2002). Individual trust in online firms: Scale development and initial test. Journal of Management Information Systems, 19(1), 211–241. DeVillis, R.F. (1991). Scale Development. Newbury Park, CA: Sage Publications. B.J. Fogg, personal communication, April 16, 2002 Fogg, B.J., Marshall, J., Kameda, T., Solomon, J., Rangnekar, A., Boyd, J., et al. (2001). Web credibility research: A method for online experiments and some early study results. Proceedings of ACM CHI Conference on Human Factors in Computing Systems, Vol. 2. New York: ACM Press. Fogg, B.J., Marshall, J., Laraki, O., Osipovich, A., Varma, C., Fang, N., et al. (2001). What makes a Web site credible? A report on a large quantitative study Proceedings of the CHI01 Conference of the ACM/SIGCHI, pp. 61–68. Seattle, WA: ACM Press. Fogg, B.J., & Tseng, H. (1999). The elements of computer credibility. Proceedings of the CHI01 Conference of the ACM/ SIGCHI, pp. 80–87. Pittsburgh, PA: ACM Press. Hovland, C.I., Janis, I.L., & Kelly, H.H. (1953). Communication and persuasion. New Haven, CT: Yale University Press.

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14 2006 IRMA International Conference 8.

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Emerging Trends and Challenges in IT Management

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Making Choices: Research Paradigms and Information Management: Practical Applications of Philosophy in Information Management Research M.E.Burke, Information Systems Institute, Maxwell Building, University of Salford, Salford, Greater Manchester, M5 4WT, {Phone: 0161 295 5657, Fax: 0161 295 4695, E-Mail: [email protected]}

ABSTRACT This paper examines questions regarding the choices of research paradigms and the practical application of philosophy to the life of professional information managers. The purpose of this paper is to examine a variety of research approaches which information managers may find useful to meet the needs of working in the networked, digitized age. This is achieved by a discussion of the research paradigms inherent within both information theory and social theory. These approaches are considered and the reasons for acceptance and rejection detailed together with the final justification for an interpretist approach as the most appropriate context in which to work, in order to meet the emerging trends and current challenges of information technology management.

INTRODUCTION Philosophy can be defined as the questioning of basic fundamental concepts and the need to embrace a meaningful understanding of a particular field. The discipline of philosophy can be used to allow research to be viewed in a certain way, by using particular “accepted” approaches e.g. positivism, interpretism. These “accepted” approaches are useful to the information professional for three reasons. First, the approach clearly communicates the stance of the research, second, it allows others to quickly understand context and third it provides a means for clearly articulating the results of that research. The purpose of this paper is to examine a variety of research approaches which information managers may find useful to meet the needs of working in the networked, digitized age. This is achieved by a discussion of the research paradigms inherent within both information theory and social theory. These approaches are considered and the reasons for acceptance and rejection detailed together with the final justification for an interpretist approach as the most appropriate context in which to work, in order to meet the emerging trends and current challenges of information technology management.

THE THREE C’S: COMMUNICATIONS, COMPETITION AND CHANGE The way in which information professionals undertake research is of paramount importance as we need to react to what can be termed the three “C’s” i.e. Communications, Competition and Change. Communications have radically altered since the impact of technology, e.g. the immediacy of communication and the accessibility of all time zones mean that business can thrive 24/7 in an international arena. This in turn has led to increase in competition as markets expand and borders disappear, allowing and encouraging trade in many countries. Inevitably, the need to react quickly and efficiently to competition causes the need to change whether it is small scale administrative changes or major

restructures and mergers. Change is all around us, as much in the private sector as the public sector. Change is now rapid and continuous, management texts no longer refer to how to manage change, but simply to how to manage in times of change, the change in wording although small has huge significance. What is important in information management research is an ability to undertake research within the world created by the three “C’s” and the suggestion in this paper is that research which involves the study of people and cultures, should, unless there is good proven reason, be undertaken from an interpretive viewpoint. This is because an interpretive approach allows the context of the research, in particular during the data collection to be taken into account. When dealing with people and information this is a vital factor in establishing information needs in order to ensure that systems (for example) provide information satisfaction and information fulfillment. Paradigms which assist with dealing with subjectivity are considered in the following section.

RESEARCH PARADIGMS Subjectivity can be seen to be a fundamental aspect of research which deals primarily with people and information. This subjectivity must be addressed in some way so as to ensure that research is conducted with rigour and fairness. This is achieved by setting a research methodology within a suitable research paradigm and clearly communicating the assumptions pertinent to that research paradigm. Ideas around paradigms were considered by Kuhn (1962) in his revolutionary treatise “The Structure of Scientific Revolutions”. He identified a paradigm as a “disciplinary matrix”, as a means of identifying and therefore sharing assumptions about core beliefs and values. Others, such as McArthur, (1992) defined a research paradigm in more general terms as: an overriding viewpoint that shapes ideas and action. A paradigm shift occurs when ideas and practices taken more or less for granted under the old paradigm are reassessed under the new. Such a shift occurred in the sixteenth century when Copernicus claimed that the Earth went round the Sun and in the nineteenth century with Darwin’s theory of natural selection. The research paradigm, once chosen, acts as a “set of lenses” for the researcher – it allows the researcher to view the fieldwork within a particular set of established assumptions, thus merging the abstract usefulness of the paradigm with the practical application of conducting rigorous research.

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16 2006 IRMA International Conference INFORMATION THEORY FRAMEWORKS

SOCIAL THEORY FRAMEWORKS

Within the discipline of information management, the term information science is used when discussing theoretical and philosophical ideas of the area. Information science is simply the “science and theory” which underpins the whole arena of information management and is thus the term used in this section.

The Information Systems discipline is in a better position. It has “borrowed” frameworks from the sociology discipline and one of the most important papers was written towards the end of the 1970’s when sociology was a growing and thriving field. This view has now been widely accepted and forms the social theory framework which sets out the major viewpoints.

Information science does not hold to one particular paradigm. Rather, as a relatively young discipline, it is still searching for its roots and thus discussion about what constitutes the philosophical dimension of information science is an ongoing debate. At its most basic level, information science both as a profession and as a discipline is concerned with gaining and maintaining “respectability” in terms of the sciences and the need to establish itself as a real “profession”. Hjorland‘s work (1992; 1995; 1997; 1998) in the area of theories in information science is well documented and thought provoking. His work in 1992 on the concept of the subject in information science attempted to set out a philosophical framework which categorised boundaries of what constitutes a subject, a field and a discipline in order that information science is established, and accepted, as a “robust” science. His later works deal, for example, with the growth of information science theories (1997), and “discourse communities” i.e. the fact that different “documents have different meanings in different domains and therefore must be considered differently by different information systems” (2000). Whilst Hjorland favours the “Socio- Cognitive” view of information science, work undertaken by Basden and Burke (2004) dealt with the question of defining documents by application of the fifteen Modal Aspects created by the philosopher Dooyerweerd. These include such aspects as juridical aspect, the lingual aspect and social aspects. Within this framework, the areas of diversity, responsibility, roles, identity and change were analysed and discussed. Budd’s (2001) work also addresses the question as to whether information science can be called a “science “in the true sense. Budd posits that Bacon was the true “father” of sciences who postulated that the scientific method was about collecting factual data through a method of observation agreed by a specific set of rules, resulting in new knowledge which then added to existing knowledge which in turn built up a complete body of knowledge. If this is so, then all who work within the information profession are quite justifiably scientists. However, other philosophers – from Aristotle and Plato to Kant and Locke, Hume and Berkley have argued that the discussion should not be about what is a science, but about what is knowledge and only when this question is answered can the question of what constitutes a science be satisfactorily concluded. Hjorland (1998) attempted to define the discipline of information science in a different way by considering the basic epistemological assumptions on which information science is based. He does this by considering four areas, that of empiricism, rationalism and historicism and pragmatism. He does concede that this is inevitably a “narrow” look at a very wide field, but he provides pegs on which to hook ideas and frameworks. He reviews ideas in retrieval, in subject classification, ideas concerning the typology of documents and information selection. He concludes that empiricism, rationalism and pragmatism are not satisfactory as frameworks for information science as they do not cater for the lack of boundaries in aspects of information science. Instead he suggest that historicism is the way forward as this allows for all facets of the discipline to be considered equally thus providing a stable epistemological assumption for information science. Burke (2003) builds on this view that other variables should be considered which in the past have been overlooked, or brought into an area of concern at a later stage, such as organisation structures and the impact of information processing systems on both the people and the organisation. However, all these approaches are broad and do not address specific fundamental questions such as which approach to consider when undertaking research. The views about what constitutes the underlying assumptions of information science are still unclear, although there are a several schools of diverse thought resulting in a rich tapestry of interwoven ideas.

From a sociological viewpoint, Burrell and Morgan writing in 1979 endeavoured to present the pertinent issues of the 60’s and 70’s into a single model. They created the framework for four sociological paradigms which are now widely accepted and used to convey a standpoint on a particular issue. The four paradigms are Radical Humanist; Radical Structuralist; Functionalist and Interpretive views. They contain “fundamentally different perspectives for the analysis of social phenomena”. (Burrell & Morgan, 1979) The functionalist paradigm refers to the search for explanations of social phenomena, from the view of a realist – what can be described as a positivist perspective. It is a logical, rational view which is often “problem orientated in approach”. It has its roots in the pure sciences where issues could be measured, evaluated and monitored. The radical structuralist paradigm however espouses an objective view. This view is concerned with structure, with structural relationships and with the certainty that as all things have a structural relationship within society, then all things can be explained in a logical way. This view is closely aligned with that of the functionalist. The radical humanist paradigm views the world as one in which everyone has potential that we are able to “do better” and “be better” than society at any given time, permits. This view of “endless possibilities” is closely allied to the interpretive viewpoint as it is a view which allows and encourages subjectivity. The perspective of the “critical social researcher” is formed from within this paradigm. The fourth paradigm, the interpretive view is concerned with understanding, with interpreting the world and each situation, dependent on the tangible and intangible variables that were present at the time. This seeks a view “within the frame of reference of the participant as opposed to the observer of action”. This frame of reference is vital in order to undertake research based within information management which deals primarily with people, information and cultural contexts. Now that the research paradigms have been introduced, the research lens becomes more focused and the research paradigm which, it is suggested, best suits this information management and people based research is sought.

RESEARCH PARADIGMS: ACCEPTANCE AND REJECTION As the information science discipline does not offer an easily “accepted” paradigm, a decision was made to explore and accept one of the paradigms offered by the social theorists. Within the information systems field the two major opposing research paradigms are that of the positivist, (Burrell and Morgan’s functionalist paradigm) and the interpretist. Within these spectrums lie the other schools of thought. Each of these paradigms has their own merits and limitations. Within the information systems research arena writers such as Walsham (1993; 1995) and Galliers (1985) take a strong stance on the interpretive view as the most useful. However, although the interpretive style is being proposed as the most appropriate paradigm for information management research which deals with people and culture, the reasons why the other paradigms were rejected are equally important to consider and this task is undertaken in the following sections:

THE FUNCTIONALIST / POSITIVIST APPROACH Within the functionalist paradigm, the positivist approach to research can be defined as an approach where facts are clearly defined and results are measurable. According to Myers, (1997) “Positivist studies generally attempt to test theory, in an attempt to increase the predictive

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Emerging Trends and Challenges in IT Management understanding of phenomena.” The researcher is seen as an objective instrument. Positivists aim to forecast the general patterns of human activity regardless of historical or cultural contexts. Adopting this perspective in people and information based research would not allowed context – which can be critical to a study - to be taken into account. Whilst this perspective which searches for explanations for social phenomenon could have allowed for standard, structured, “reasonable” conclusions about behaviour, it could have missed, for example, a rich array of history, a range of social conventions, and the reasons behind the different types of behaviour. On these grounds, a positivist approach is rejected.

THE RADICAL STRUCTURALIST / POST MODERNIST APPROACH The radical structuralist paradigm provided a framework for other views such as the post modernists whose research approach is based on a deep mistrust of the other methods as they all take place by systematic empirical observation. A post modernism (Dorst 1989: Rose1989) would take issue with the fact that results are presented in a detached way and would want the researcher’s experience to be part of the final results. This is in direct contradiction to the more “usual” research view where the researcher must identify his or her role in the process and attempt to separate that from the research participants. However, this approach does have possibilities for UK based research, but could be rejected, for example, on the grounds of the difficulty of placing the researcher as a “participant” in the field due to the language and conversational difficulties that would have been encountered. These problems could of course be overcome if the language skills are available. On the whole, however, the radical structuralist / post modernist approach can be rejected due to practical considerations. 9. THE RADICAL HUMANIST / CRITICAL SOCIAL APPROACH The criticism of the positivist is that positivists ignore social context. To counteract this, the radical humanist approach is centred on dynamic action, is zealous in approach to needing and demanding a solution or improvement in the situation. This view has developed into a flourishing approach to research known as “critical social research”. The goal is to return or give the power to those who need it most. The critical research approach can be defined as looking beyond what is present –to the past of the people, including the cultural past, to the issues that have formed strong influences in the past and the history and form of politics prevalent within the field. The critical approach can assist with helping people recognise reality in an objective way – it aims to help them understand and cast off false beliefs and myths that may have prevented them from achieving their goals in the past. This standpoint would be useful in an intervention type of study in a research setting where the aim was to assist people and to help them transcend imposed limitations. The zealousness inherent in this approach would form a strong starting point for the rejection of the “accepted norm” and would present an idealistic alternative. However, if the researcher needed to collect data without interruption to daily lives, was present for a short time span and did not have the power to radically change established structures this could not considered a suitable approach. On these grounds a radical humanist / critical research approach was rejected.

THE INTERPRETIVE APPROACH. At its most basic level the interpretive approach allows for discussion and questioning of assumptions. According to Clarke ((2000) interpretism: Confronts the difficulties presented by the nature of the research domain such as the intangibility of many of the factors and relationships; the inherent involvement of the researcher within the research domain; the

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dependence of outcomes on the researcher’s perspective such as the definition of the research question, the design of the research question and the measurement of variables. Clarke’s concern with the measurement of variables is particularly pertinent to information and people based research. As the goal of the interpretive researcher is about sharing the perspective of the groups, it is considered the most appropriate means of undertaking research based on people and information needs. This is the method which allows the most natural behaviour of those seeking information and thus helps researchers to make key decisions about information needs, information satisfaction and information fulfillment .

JUSTIFICATION FOR THE INTERPRETIVE APPROACH: AN EXAMPLE The justification for the use of the interpretive approach can be summarised by examining Myers (1997) epistemological assumptions of interpretivism together with a consideration of how the assumption fits a particular research study. This example - the Information Fulfilment Project (IFL) was took place over a number of years and was conducted in three countries by ethnographic means using participant observation and Blumer’s (1954) symbolic interactionist approach. The study examined the relationship between the design of an organization’s structure and information fulfillment. Information fulfillment was defined as a final stage of information seeking behaviour which ensures that the user has gained all the information needed to fully complete a task, beyond initial satisfaction. The research was conducted in higher education institutions in Poland, Russia, and the UK. It was thus important to choose a research lens which allowed the different cultures of the countries to be carefully considered. Hence the interpretive research stance was the one which appeared most appropriate. The following table was used in the study to explores the epistemological assumptions which underlie the interpretive approach (stated in the left hand column) whilst the right hand column contains comments on the usefulness and relevance of the research study to each of the assumptions in the IFL project. The deconstruction of the five assumptions that make up the interpretavist view show that this stance is justified as it provides the best methodological approach of collecting social phenomena in natural settings, which is so important in the field of information management and which was vital to the success of the IFL research project. Whilst the application of the interpretavist view to the information field is well documented, it is still relatively unusual to apply these principles to the field of information management and thus demonstrate the usefulness of this lens to the information fulfilment research project.

CONCLUSION The purpose of this paper was to provide an insight into making research choices in information management and to suggest a way of applying one aspect of philosophy to information management research. This was achieved by an examination of research approaches which may be useful in information management research and as background to this discussion the importance of communication, competition and change were highlighted. Each of the research paradigms were examined for relevance and although there were possibilities of usefulness in different contexts, it was generally considered that interpretism is the most useful and the one that will give the richest results. The decision was justified by taking an example of information management research – the IFL project and deconstructing decisions against Myers (1997) epistemological assumptions of interpretivism. The central theme of this paper is that research which deals primarily with people and information in a world of change, competition and fluid communications technology, should take into account and allow for an understanding of human behaviour. This understanding helps to highlight different contexts, backgrounds and cultures and therefore provides assistance in making appropriate choices concerning research

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18 2006 IRMA International Conference Figure 1. Justification for the use of the interpretive approach Epistemological Assumptions Epistemological Assumption 1 “Data are not detachable from theory, for what counts as data is determined in the light of some theoretical interpretation, and the facts themselves have to be reconstructed in the light of interpretation”.

Relevance to the IFL Project

All the data collected from the time spent in the field needed careful analysis and to be interpreted in the context of each of the field settings. This was a critical element for the success of the study.

Epistemological Assumption 2 “In the human sciences theories are mimetic reconstructions of the facts themselves, and the criterion of a good theory is understandings of meanings and intentions rather than deductive explanation”

As the fieldwork was undertaken in three very differently constructed societies, two of which were rich in folklore and historical traditions it was essential that the research paradigm allowed for meaning in a particular instance rather than gave a full overall explanation for all actions

Epistemological Assumption 3 “The generalisations derived from experience are dependent upon the researcher, his/her methods and the interactions with the subjects of the study. The validity of the generalisations does not depend upon statistical inference ‘but on the plausibility and cogency of the logical reasoning used in describing the results from the cases, and in drawing conclusions from them ‘ (Walsham, 1993)

Epistemological Assumption 4 “The languages of human sciences are irreducibly equivocal (because of multiple emergent meanings) and continually adapt themselves to changing circumstances”.

Epistemological Assumption 5 “Meanings in the human sciences are what constitute the facts, for data consists of documents, intentional behaviour, social rules, human artefacts etc. and these are inseparable from their meanings for agents”.

paradigms and information management, which in turn will ensure thoughtful methodology and justifiable research results.

The research was not a statistical study based on quantative data, but a “snapshot”, a “photo album” of three societies at a particular point in time. This was a study of qualitative data, and whilst there were some informal interviews, these were of a conversational nature, and the results put into loose groupings. It was more important to let the participant decide what they regarded as informal or formal information as this varied from person to person (depending on their job) and from society to society. (depending on the country) Each of the societies chosen for the field work was quite different in nature. Two of the three societies have also undergone a major shift in government patterns in the last ten to fifteen years. Inevitably this meant that the field was undertaken in an intensely “fluid” environment where the participants had to “continually adapt themselves to changing circumstances” This needed to be reflected in the chosen paradigm and interpretism offers the flexibility to allow for this Much of what happened in the field was observed – although there was some informal data collection a considerable proportion of finding out whether a participant felt they had ”information fulfilment” was gained from observation. This fifth assumption emphasises the nature of interpretism as a vehicle for the importance of behaviour and the way in which people follow – or disregard rules. This was essential for the success of this research.

REFERENCES Basden, A & Burke, M.(2004) Towards a philosophical understanding of documentation: a Dooyeweerdian framework. Journal of Documentation. 60 (4) Blumer H.(1954) What is wrong with social theory? American Sociological Review 19 pp3-10 Budd, J (2001) Knowledge and Knowing in Library and Information Science Maryland, Scarecrow Press Burke, M. (2003) Philosophical and theoretical perspectives of organisational structures as information processing systems. Journal of Documentation. 59 (2) Burrell & Morgan (1979) Sociological Paradigms and Organisational Analysis. London Gower Clarke R (2000) appropriate research methods for electronic commerce http://www.anu.edu.au/people/Roger.Clarke/EC/ Dorst, J.D. (1989) The written suburb : an ethnographic dilemma. Philadelphia Univ of Pennsylvania Galliers, R.D. (1985) In search of a paradigm for information systems research in Mumford et. al. (eds) Research Methods in Information Systems, (Proceedings: IFIP WG 8.2 Colloquium, Manchester 1 -3 September, 1984) Amsterdam, North Holland. Hjorland, B (1992) The concept of “subject” in information science. Journal of Documentation 48 172-200 Hjorland, B (1997) Information seeking and subject representation: an activity-theoretical approach to information science. Wesport Connecticut, Greenwood Hjorland, B. (1998) Theory and meta theory of information science: a new interpretation. Journal of Documentation 54 pp606-621. Hjorland, B. (2000)Library and information science: practice, theory and philosophical basis. Information Processing and Management. 36 pp 501-531 Klein H. & Myers, M (1999) A set of principles for conducting and evaluating interpretive field studies in information systems, MIS Quarterly, Vol 23, (1) March pp67-93 Kuhn,T., (1962) The Structure of scientific revolutions. Chicago, University of Chicago Press. McArthur,T., (1992) The Oxford companion to the English language, Oxford, Oxford University Press Myers, M.D., (1997) Qualitative Research in Information Systems MIS Quarterly (21) 2 June 1997 pp241-242 Rose, D., (1989). Patterns of American culture: ethnography and estrangement. Philadelphia: University of Pennsylvania Press Walsham, G (1993) Interpreting Information Systems in Organizations. Wiley, Chichester. Walsham,G. (1995) Interpretative case studies in IS research: nature and method, European Journal of Information Systems, 4, 74-81

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Outsourcing, Insourcing IT-Related Business: The Impact on the Organization James A. Sena, California Polytechnic State University, San Luis Obispo, California 93407 {Phone: 1 805 756 2680; E-mail: [email protected]}

ABSTRACT Outsourcing by American companies has become a way of doing business. Various forms of strategic sourcing are means for firms to compete strategically in the global marketplace. This paper defines outsourcing and describes its evolution over the in terms of job migration and its economic pros and cons. The deployment of IT sourcing is discussed as well – indicating that there are many variations of what we think to be outsourcing and insourcing.

INTRODUCTION With the growth and diversity in information and computer-based technology firms are pressured to control and manage increasing costs. Many strategies have been employed to control their computing cost. Often it is not just cost but the conviction that a firm needs to focus on its core competencies. Information Technology [IT] is often considered to be a support function. During the 1970’s in the era of the mainframe companies farmed out their specialty operations to timesharing. By the 1980’s the growth of service bureaus and facilities management were common place. At one point Electronic Data Systems assumed the complete computing operation of General Motors., then largest company in the world. Even as early as the late 1960’s firms frequently relegated their Payroll systems to banks and service bureaus to insure better control — checks and balances. This trend continued with the transfer of other bank-related transaction processing systems such as credit card processing. For the programmers and other computer systems professionals the period from the 1960s into the 1990s were golden times – high demand and good salaries. A harbinger of things to come was marked by Yourdon’s seminal work, “The Decline and Fall of the American Programmer” (Yourdon 1992) – American software is developed at a higher cost, less productively and with less quality. He went on to suggest the deployment of software technologies and innovations such as software reusability and reengineering technologies. Herein was the beginning of true outsourcing – we began to see programming sent overseas to Ireland, India and other technologically astute countries. By 1996 Yourdon published a sequel to his earlier book – “The Rise and Resurrection of the American Programmer.” (Yourdon 1996) He noted that in a four year period from 1992 to 1996 the world of computing went through two generations of hardware technology and witnessed the explosion of the internet, multimedia and other technologies especially the introduction of the World Wide Web. Software was becoming a commodity. This could also be extended to business applications. Customers began to realize that there are multiple vendors and that they can virtually get software anywhere. Remarkably sophisticated accounting systems could be purchased for not much more than the cost of Microsoft Office. More elaborate business and enterprise software could be purchased at much higher prices. If the requirements were unique a firm might turn to consultants or specialists – they did not have to rely

on their in-house staff. Development work could be outsourced to a local consulting firm or an offshore programming shops. Buchholz, in his book, “Bringing the Jobs Home”(Buchholz 2004) relates how four years ago, while lecturing to technology executives, about the preponderance of the outsourcing wave. The executives explained that they might not be firing Americans but they were not looking to hire more. Instead India, Ireland, Israel and China seemed to be nabbing the new jobs. Irish and Israeli programmers earned half as much as Americans while Indians and Chinese worked for one-fourth the salary. Forester Research states that more than 800,000 white-collar jobs have traveled overseas in 2005 and 3.4 million by 2015. This figure doesn’t state how many of these white-collar jobs are IT. Regardless Researchers at UC Berkley believe that Forester is too conservative and that 14 million job holders should be “trembling” (Buchholz 2004) The counter measure to outsourcing is “insourcing” where foreign firms are hiring Americans. More than six million Americans already work for foreign firms, and the number is climbing. The meaning of IS outsourcing has evolved over time (Fink 1994). Traditionally, it referred to the conditions under which the organization’s data were processed at an external computer service bureau. Now, however, it can mean much more and the concept has become somewhat blurred. A 1991 American survey of chief information officers concluded “There is little precision in the term outsourcing. Some respondents use the term to mean ‘farming out any task, service or function,’ while others use it to refer exclusively to the data center utility”(Analyzer 1993). Martinson provides a generalized definition, namely that “Information systems outsourcing is the act of subcontracting all or parts of the IS function to an external vendor as an alternative to relying solely on in house resources and capabilities”(Martinson 1993). In some cases, outsourcing means selling the existing assets of a company to an outside service provider and then working with their experts to improve those assets.(Associates 2001). The result: better use of capital and potential gains in quality, productivity, and throughput. In other cases, outsourcing is a way to take an existing fixed cost structure and turn it into a variable one in which expenses can move up or down as the business climate dictates.

SOME BACKGROUND ABOUT OUTSOURCING Outsourcing is not a recent occurrence. American companies have been manufacturing goods abroad in countries such as China and India for decades. Outsourcing has had a significant impact on information technology over the past 30 years. In the 1970’s many U.S. companies exported their payrolls processing to outside service providers. This practice continued into the 1980’s, where accounting services, payroll, billing, and word-processing were outsourced as well (eds.com 2005). Most often these early outsourcing tasks were only “outsourced” as far away as another state within the U.S., not India or China. By the late 1980’s this had changed. Firms were realizing the threat outsourcing

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20 2006 IRMA International Conference posed for American workers. The growing need for software developers and technical support personnel, combined with the ever-expanding network of telecommunications became a catalyst for the intensification of outsourcing. Early outsourcing to overseas providers by corporations such as Kodak and American Standard captured the public’s attention. “Kathleen Hudson, then Kodak’s CIO, said, her goal was to ‘plug into the wall and have data come out.’ That type of thinking helped put outsourcing on the map’. (News.com 2005) Outsourcing is more prevalent now than ever before. It is estimated that by 2015, $136 billion in wages will move to India, China, Russia, Pakistan, and Vietnam. Europe also has become a Mecca for outsourcing. They expect to reach 25 percent of total global outsource spending. Although media attention has tended to focus on India as the world’s most recent outsourcing hotspot, China has three to four times as many outsourced jobs as India over the past 15 years. While the current concentrations of outsourcing are information technology and manufacturing, product research and development as well as healthcare may soon be just as heavily outsourced as technical support centers. Outsourcing and Corporations International Business Machines (IBM) has been the dominant provider of mainframe computing for over fifty years. They also were the leader in the personal computing industry, introducing their first PC in 1981. Since then, IBM has encountered intense competition from Dell, Hewlett-Packard, Toshiba, and other companies. In response to this competition, IBM shifted their focus from PC manufacturing to what it calls “business transformation services,” or, what is more commonly known as outsourcing. (ibm.com 2005) Companies are increasingly outsourcing the development and management of information technology to IBM to gain access to specialized skills, costs, staff utilization, reduced recruitment and training, high standards of control and security, and specialized information services. (Downing 2003) There are reasons though to retain the development of IT applications in-house – subject matter expertise, confidentiality of business data, reduced vendor risk, ease of development and acceptance of internal adaptation, and the desire to develop internal leading-edge competence.

failures, outages, and/or security breaches are lessened. IBM’s business transformation services have also helped companies become more productive by outsourcing technical support centers. As an example, the employees of a financial investment firm can call the company’s overseas technical support desk for assistance related to departmental computer problems eliminating the need for in-house IT tech support. Outsourcing is nothing if not versatile. IBM obviously exploited this when successfully transforming itself into a consultancy and service provider within the IT sector. But as strategic repositioning is notoriously difficult, it would clearly have been folly on IBM’s part to put all of its eggs into this new basket – even though the company already had prior experience of providing service for its own products. On the other hand, expansion obviously increases demand on resources. So how did IBM manage to pull it off? The company decided to outsource production of its computers, servers and workstations, thus freeing up resources for its own transformation into provider for others (Leavy 2004; Group 2005) . Initially the Internet served as a communication platform connecting end users and computers. Today, the internet facilitates a broad range of business functions, including marketing, sales and transactions, customer service and other business applications. As a result, the process of building and maintaining e-business infrastructure has become more complex, time-consuming and expensive. Current e-business implementations involve integration and management of numerous components, including server hardware, networking elements, software, storage, security and system monitoring. Furthermore such a structure needs to be operational 24x7x365. The U.S. hosting service market continues to expand despite current macroeconomic conditions and technology sector turmoil (Posey 2004). The internet boom era is over, but companies continue to leverage the internet as a communications and transaction-oriented business medium. According to IDC the U.S. market for outsourced hosting services will grow from $5.5 billion in 2003 to $10.4 billion by 2008.

The overseas movement has become commonplace within the corporate industry. From HP, to Motorola, to Bank of America, companies continue to send jobs abroad through business process outsourcing (BPO). Offshore companies provide lower labor costs than their domestic counterparts. The lower wage-restrictions of many Asian and Middle Eastern countries allow offshore companies to hire more middle managers, who are then able to “devote more time to building the skills of their employees and to improving their processes than would be economical for most Western companies” (ibm.com 2005). By developing and producing goods less expensively using offshore manufacturers, companies are able to sell products to consumers at reduced prices.

Outsourcing Destinations US companies outsource to almost anywhere in the world. The two major United States outsourcing countries are India and China. (Naughton 1997; Bauer 2002; Gallagher 2004; Nanda 2004; Rahagopalan 2005) They offer the highest amount of laborers at the most competitive wages. Other countries like Pakistan, Ireland, Russia, and Philippine are also candidates for outsourcing services. Pakistan recently launched efforts to attract corporations by claiming to be a better place for outsourcing than India. Even though the scale of Pakistan’s IT industry is far smaller than India’s, Pakistan is marketing their country as having lower operation costs and a more neutral English accent than India. For Pakistan to become a major player in IT outsourcing industry, it will need to improve in physical infrastructure and education base.

IBM — Its not all Outsourcing IBM Global Services provides services to make corporations more proficient through what it calls “business transformation services.” By partnering these large corporations with strategic partners, IBM can “streamline business processes, business applications, and IT infrastructures” (ibm.com 2005). IBM primarily helps companies reduce costs as well as risks by managing their IT business core. In terms of costs, IBM’s Global Services has significantly reduced costs for numerous corporations by assuming the majority of the firm’s IT operations. According to a 2003 Deloitte Research study surveying 27 global financial institutions, 33 percent of respondents are using IT outsourcing with IBM, and 75 percent said they planned to outsource within the next 24 months. Financial institutions outsourcing their IT functions reported an average savings of 39 to 50 percent when compared to in-house IT function (eds.com 2005).

Outsourcing Failures and Risks The unique and distinct characteristics of IT can put clients at a disadvantage with respect to IS outsourcing providers for the following reasons: IT evolves so fast that there is a high degree of uncertainty involved in any decision related to outsourcing; IT is present in all business functions — knowing the idiosyncrasy of the organization becomes necessary to carry out many IT activities; the costs involved in changing from one IT provider to another are very high— making it complicated to encourage competition; and, clients often lack experience in signing outsourcing contracts — this is not the case for the provider. As a result of this information dissymmetry, providers are in a much better position in order to favor their own interests.(Claver 2002)

IBM’s IT outsourcing capabilities have helped corporations reduce the risks involved with conducting business. When information technology departments are not centrally located, the threats of in-house system

Outsourcing IT and software services can have benefits of cost savings to a company. Provider’s services can be expensive and may not meet customer’s expectations. Sometime the customer assumes that offshoring will result in comparable person-to-person saving without considering

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Emerging Trends and Challenges in IT Management costs such as travel, systems compatibility, infrastructure maintenance, or additional equipment. Most IT companies save about 15% to 25% during the first year of implementation, and can reach 40% by the third year when expectations align and reach maturity. The main cause of failure seems to be the differences between customer’s expectations and the perceived results to be provided by the service provider. Failures in outsourcing of customer service such as call centers can have adverse effects and potentially damage a company’s brand and reputation. The main perception customers have when they hear a foreign accent is to anticipate or expect a bad experience. For example, two years ago Dell computers had to restructure and rescale its technical support call centers in Bangalore, India due to overwhelming complaints. Many loyal customers were frustrated by the poor customer service when their calls were routed from one support agent to another and nothing is done. Currently Dell continues to route their customer service calls offshore — over half of their employees are located abroad. Another concern outsourcers have is the protection of intellectual property (IP) and security. Companies often are more focused on cost savings and gaining productivity without taking into account security issues. Although countries such as India have patent, copyright and IP protection laws, these laws are often difficult to enforce. For example, when Jolly Technologies discovered source codes and design documents were allegedly uploaded and emailed by an outsourced employee in India, the company tried but failed to get local authorities to investigate (Rebecca 2004) To avoid potential disappointments in outsourcing services, the customer and service provider need to have a strategic alignment between each other and set a standard that can be measured. Mechanisms need to be established to manage problems and insure ongoing management of relationships.

CONCLUSION The impact that outsourcing on the global economy will only continues to grow. (Pierlott 2004) As telecommunications become increasingly efficient into the 21st century, the outsourcing of information technology will become a normative practice. As China continues its development into a world power, its workers are becoming more educated and skilled, providing an increasingly attractive option for U.S. companies wishing to outsource. It is impossible for a company to be expert in every aspect of their business (Overell 2004). It is not only too expensive but a recipe for incompetence. Core competence is the goal. Technology has cut sharply the costs of communication to the extent that outsourcing of many information technology activities is becoming increasingly standard. So strong is this trend that outsourcing specialists themselves also tend to outsource several further specialized aspects of a task to others. The result, in practical terms, is that organizations are maintaining many more relationships than previously. These firms are now in the age of the “middleman.” The challenge to outsourcing is determining when to outsource a particular business function. While it is not a good idea to outsource mission-critical areas, administrative and support tasks that are not part of the business’ core competencies would be acceptable for outsourcing. In general, if the activities are those that do not add direct value to the firm’s customers, they can be considered (Papp 2004). For years, “sourcing” has been just another word for procurement (Gottfredson 2005) – a financially material, but strategically peripheral, corporate function. Globalization, aided by rapid technology innovation, is changing the basis for competition. According to Gottfried and his associates it is no longer a company’s ownership of capabilities that matters but rather its ability to control and make the most of critical capabilities – whether they do or do not reside on the firm’s balance sheet. Outsourcing has become so sophisticated that even core functions like engineering as well as manufacturing can and often should be moved outside. This will change the way firms think about their organization, their value chains, and their competitive positions.

21

Bossidy and Charon in their book, “Confronting Reality”(Bossidy 2004) present the practicality that we now face – virtually every business is now a player on the global stage. The new rule is that almost any business activity is ever more likely to have a worldwide dimension. Any one, anywhere can make a firm’s life difficult. The firm needs to recognize that they can become the new player that blindsides the complacent player. IT employees need to become chameleons. They must learn and change – adapting a dynamic global business and economy. The development of information technology has reached a stage where IT knowledge workers are no longer up-to-date but are instead experiencing various degrees of technological obsolescence . Outsourcing is one of many challenges presented by the continued growth of technology. Although its effects may now seem detrimental, one should probably not bet against the long-term domestic growth which may eventually come as a result of outsourcing. To flourish over the long run, most companies need to maintain a variety of innovation efforts.(O’Reilly 2004) They must constantly pursue incremental innovation – small improvements in their existing products and operations that let them operate more efficiently and deliver ever greater value to customers. Companies also have to make architectural innovations – applying technological or process advances to fundamentally change components of their business. Capitalizing on the capabilities of the Internet and perhaps taking advantage of low-labor-cost alternatives, such as call centers, where the impact does not affect the customer value.

REFERENCES Analyzer, I. (1993). New Wrinkles in IS OUtsourcing. I/S Analyzer 31(9): 1-19. Associates, C. (2001). Best Practices for Deciding what should be outsourced. Bauer, E. E. (2002). China Takes Off. University of Washington Press: 45. Bossidy, L. a. C., Ram (2004). Confronting Reality. New York, Crown Business. Buchholz, T. (2004). Bringing the Jobs Home. New York, Sentinel. Claver, E., Gonzalez, R., Gasco, J. and llopis, J. (2002). “Information ssytems, outsourcing: reasons, reservations and success factors.” Logistics Information Management 15(4): 294-308. Downing, C., Field, Joy, and Ritzman, Larry, (2003). “The Value of Outsourcing: A Field Study.”Information Systems Management,(Winter 2003). eds.com (2005). History. Fink, D. (1994). “A Security Framework for Information Systems Outsourcing.” Information Management & Computer Security 2(4): 3-8. Friedman, T. L. (2005). The World is Flat: A Brief History of the 21st Century. New York, Farrar, Straus, and Giroux. Gallagher, J. (2004). “Going Offshore for IT Help. Supermarket News,. Garten, J. (2004,). Offshoring: You Ain’t Seen Northin’ Yet. Business Week. Gottfredson, M., Puryear, Rudy and Phillips, Stephen (2005). “Strategic Sourcing,.” Harvard Business Review. Group, E. (2005). “Nikea, IKEA and IBM’s outsourcing and business strategies: Profits and Perils.” Human Resources International Digest 13(3): 15-17. ibm.com (2005). “IBM to Sell PC Business, Focus on Outsourcing.” ibm.com (2005). A New Paradigm in IT: Outsourcing. Leavy, B. (2004). “Outsourcing: Opportunities and Risks.” Strategy & Leadership 32(6): 20-25. Martinson, M. G. (1993). “Outsourcing Information Systems: A Strategic Partnership with Risks.” Long Range Planning 26(3): 18025. Nanda, H. S. (2004). 2005: India’s outsource industry poised to grow. World Media Digest. Naughton, B. (1997). The China Circle. Washington, Brookings Institution Press.

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22 2006 IRMA International Conference News.com (2005). Why Outsourcing is Suddenly in. O’Reilly, C. a. T., Michael (2004). “he Ambidextrous Organization.” Harvard Business Review. Overell, S. (2004). Knowledge that gets to the business cor. Financial Times Management. Papp, R. (2004). Outsourcing Systems Management. Annals of Cases in Information Technology. M. Khosrow-Pour, Idea Group Publishing. Six. Pierlott, M. (2004). “Moral Considerations in Outsourcing to Foreign Labor.” International Journal of Social Economics 31(5/6): 582-592.

Posey, M. (2004). The Increasing Business Case for Outsourced Hosting. IDC Whitepaper. Rahagopalan, S. (2005). China way behind India in IT services: McKinsey. Rebecca (2004). Offshore Outsourcing Country Focus: China. Yourdon, E. (1992). Decline and Fall of the American Programmer,. New Jersey, Prentice-Hall,. Yourdon, E. (1996). Rise and Resurrection of the American Programmer. New Jersey, Prentice-Hall.

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Emerging Trends and Challenges in IT Management

23

Target, Shield and Weapon: A Taxonomy of IT Security Initiatives Laura Lally, Hofstra University, BCIS/QM Department, Hempstead, NY 11549-134 {Phone: 516 463-5351, E-mail: [email protected]}

ABSTRACT With IT Security becoming an issue of growing importance, many new IT based technologies and applications are emerging to confront this challenge. This paper presents a theoretically based model for classifying these emerging technologies, the “Target, Shield and Weapon” model. The goal of this research is to create a meaningful taxonomy for emerging initiatives that will: 1) ensure interoperability with existing, and other emerging systems, 2) identify areas of basic research needed to support the full operability of these initiatives and 3) identify applications, developed for military scenarios that can be modified for use in civilian environment .Two case studies will be outlined for the application of the model: 1) the London terrorist bombings, and 2) the New Orleans flood.

A THEORY BASED MODEL FOR CLASSIFYING NEW INITIATIVES IN IT SECURITY IT Security has become an issue of great importance. The increase in malicious computer based attacks, the Y2K crisis, the events of 9/11, and the growing dependence on networked computer systems have made the security of IT based systems a top priority. Even though computer budgets are being cut, spending of security has increased. An increasing number of entrepreneurs are developing solutions for these problems. New government regulations require that organizations keep their systems more secure and keep better track of their documents. MIT’s Magazine of Innovation: Technology Review reports that the budget for the 2005 Department of Homeland Security for 2005 was $30 billion dollars (MIT’s Magazine of Innovation, 2005). For Customs, Immigration, and Border Protection it included $2.9 billion for container security and $340 for US-VISIT, an automated entry and exit system for frequent international travelers For the Coast Guard, it included $724 million to upgrade the technology and communications division. For the Transportation Security Administration $475 million for explosives detection systems, baggage screening equipment and their installation. For State and Local Assistance programs it included $150 in port security grants, $150 million in rail/ transit security grants and $715 million in grants to fire departments. For the Emergency Preparedness and Response Directorate, it included $2 billion for an emergency relief fund. For the Science and Technology Directorate, it included $593 million to develop technologies that counter threats from chemical, biological, nuclear and radiological weapons and high explosives and $61 million to continue the development of innovative countermeasures to protect commercial aircraft against possible missile systems. For Information Analysis and Infrastucture Protection Directorate, it included $2 billion to assess and protect critical infrastructures including cyberspace. “Pasadena, CAbased Cogent, which developed automated fingerprint recognition systems used by law enforcement and the Department of Homeland Security, went public in September and raised $216 million, then saw its stock price nearly triple by the end of the year (MIT Magazine of Innovation, p.42). As a result of this new emphasis, many new IT based initiatives have evolved. This paper proposed a theoretically based model for under-

standing three functions security based initiatives can serve. First, since IT based systems are often a target of malicious attacks, security initiatives can intercept intrusions before they can do damage. If attacks do occur, other IT based systems can mitigate the damage that is done, both to computer systems and to the real world systems that depend on them. Secondly, IT based initiatives can suggest best organizational practices to shield against further attacks. Finally, IT based initiatives can be used to proactively seek out potential attackers and prevent them from launching first attacks. This taxonomy will be used to categorize the functionality of initiatives as they emerge and address several key challenges and opportunities faced by the developers of new security initiatives. First, the challenge of making new initiatives interoperable with existing systems will become more apparent. Secondly, with venture capitalists putting an increased emphasis on the development of systems that can be made operational within a short time frame, the need for basic research that must be explored to make the initiatives fully operable will be more easily identified. This basic research can then be fast tracked and its cost allocated between all the applications that depend on it. Finally, opportunities for additional applications of emerging technology, such as military applications being used to help first responders will be more apparent as well. This paper will draw on Lally’s “Target and Shield” model (Lally, 2005) a theoretically based model for examining the potential threats to IT based systems, the propagation of these threats, and the potential for their mitigation. The paper will then extend the model to encompass the use of IT as a weapon against potential attackers. Finally, a taxonomy of emerging initiatives will be created to illustrate the appropriateness of the model in categorizing these initiatives. Lally’s “Target and Shield” model is based on Normal Accident Theory, originally conceived by Charles Perrow (Perrow, 1984) as a model for how small errors can propagate into large disasters. The model is also informed by the Theory of High Reliability Organizations, that emphasizes methodologies by which organizations can minimize the likelihood for disaster in tightly coupled complex organizations (Grabowski and Roberts, 1997), (Klein, Bigley, and Roberts, 1995), (LaPorte and Consolini, 1991), (Sagan, 1993), (Turner, 1976), and (Weick, 1993). Lally (1996) argued that Normal Accident Theory was a sound theoretical perspective for understanding the risks of Information Technology, because IT is complex, and tightly coupled and often poorly controlled. She also argued (Lally, 1996), (Lally, 1997) that IT based systems do not operate in isolation but in organizational settings where failures in IT can lead to more widespread secondary failures in organizations. Additionally, she argued (Lally, 2002) that the frequent rapid change in both IT based systems and the work processes they support can further exacerbate the potential for disaster. Lally (2005) further extended her model and argued that IT based systems are not only a target used as a weapon of destruction to cause serious accidents, but that IT based systems can be a shield used to prevent damage from future incidents, whether they be IT based or physical. This “Target and Shield” conceptual model drew on insights from the Theory of High Reliability Organizations and suggests that IT designers and managers, as well as

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24 2006 IRMA International Conference Figure 1. The target and shield model

Figure 2. IT as a weapon against potential threats

Target Control:Intercept Potential Incidents

Control:Mitigation Complexity (+)

Complexity (+)

Tight Coupling (+)

Tight Coupling (+)

Change (+)

Change (+) Real World Impacts

A

B

Shield Prevent future incidents

Secondary Impacts

C Prevent propagation of incidents

D Mitigate Impacts of Disasters Loop #3

Loop #2

Loop #1

government and law enforcement agencies learn from past experiences and embody this knowledge in the design and implementation of future IT based systems. The resulting systems should not only be more secure and resilient, they should aid in preventing future IT based or physical attacks, or mitigating their impact should they occur. Figure 1 illustrates the Target and Shield conceptual model for analyzing the source, propagation and impacts of IT based threats, as well as ways in which IT can be used to identify, and mitigate the impact of, future threats. The Target and Shield model incorporates Lally’s extensions to Normal Accident Theory. The model also contains three significant feedback loops, which allow IT to play a positive role in preventing future incidents from materializing, having real world impacts, and mitigating their impacts when they do occur. In the Feedback Loop #1, Prevent future incidents, controls can be built into the system to prevent future incidents from materializing. In Feedback Loop #2, Prevent Propagation of Incidents, controls can be built into the system to prevent future incidents that have materialized from turning into accidents. In the Feedback Loop #3, Mitigate Impact of Disasters, IT based systems can be dev eloped to prevent accidents resulting from IT based or physical attacks from propagating even further. Lally and Nolan (2005) applied the Target and Shield model to map Wireless Technologies. Their analysis indicated that Wireless Technologies are a Target because of their vulnerabilities to Air Interface denial of service attacks, snooping attacks that threaten data integrity and the limitations of standards in applications that use unlicensed spectrum. Their analysis also indicated that Wireless Technology could be used as a shield because the distributed architecture of these networks can provide robustness and redundancy to prevent catastrophic failures. Finally, they indicated that location aware devices could be used for tracking suspected cyber attackers.

EXTENDING THE MODEL: IT AS A WEAPON In the Target and Shield Model, Feedback Loop #1 addresses the challenge of preventing future incidents. In a learning environment, once incidents occur, knowledge should be gained about the nature of the incident to prevent future incidents from occurring. The proactive prevention of future incidents involves more than waiting for new incidents to occur and developing defensive techniques when they do. IT Based tools are emerging for tracing incidents to their source and eliminating them. When IT is used as a weapon to fight back against potential attackers, the dynamics of the “Target and Shield” model is reversed. Instead of responding to a single negative event and its propagation through a large and complex system, the emphasis is on identifying potential threats in a complex technological and social environment, gathering intelligence on those threats, and if the threats

Step #1 Identify potential threats in complex social and technological environment.

Step #2 Gather Intelligence if threat is significant

Step #3: Plan logistics to eliminate threat and minimize damage

are confirmed, planning the logistics to eliminate the threat with a minimum of damage to innocent people and their property. With use, the model should also provide insight into which threats are the most serious and need to be eliminated. In Step #1, IT can be used to identify anomalous behavior, such as a group of people who have never contacted one another suddenly being in frequent contact. Artificial Intelligence based systems for identifying anomalous patterns in telecommunication behavior can identify unusual patterns. The challenge in Step #1 is identifying potential threats in an environment that consists primarily of innocent people, whether corporate employees or civilians. In Step #2, IT based intelligence gathering can then reveal whether the members of the new group are on a “watch list”—indicating that they may be a terrorist cell becoming active, or, perhaps members of a new computer class, corporate subcomittee or scout troop. In Step #3, if the threat is real, IT can then be used to monitor the activities of the group and eliminate the threat in a manner that will cause the least collateral damage. Many new IT based tools are being developed for military applications that can be mapped into the model. These applications can be modified for use in non-combat situations. In “Network Centric Warfare” the U.S. military uses Information Technology as a force multiplier with the hope that it will lead to shorter conflicts with limited casualties to armed forces and civilians. The three crucial elements of the strategy are to provide troops with additional strategic advantages in terms of: 1) knowledge of both enemy and allied troop movements, 2) speed to respond rapidly, and 3) precision, leading to more surgical strikes. Applications include highly detailed surveillance and GPS data to provide soldiers in the field with up to date information about local terrain and the presence of enemy tanks. Frontline soldiers in sophisticated Stryker vehicles and command centers are kept in constant contact. Military strikes can be more surgical so that innocent civilians and their property, as well a cultural landmarks can be protected. Step #3, therefore, appears to be well suited for enhancement with IT support. The emphasis by the military on using Commerical-Off-TheShelf technologies makes the possibility of trickle down effects for civilian applications more likely. The emphasis by the military on convergence at the client server or at the TCP/IP level, where information is shared via the Internet, even to users who may use different technologies to access the information. Similar technologies can be used to help first responders create more co-ordinated responses to threats. The interoperability of the technology, and its reliability, are of primary importance. GPS enabled systems used by the military can also be used by first responders as well as by businesses to provide a wide range of location based services. Although surveillance technology can identify enemy tanks, Step #1, identifying potential threats in civilian populations provides a far greater challenge. Simulation games are being developed (NPR, 2005)

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Emerging Trends and Challenges in IT Management to help soldiers to interact with civilian populations who have different languages and culture to facilitate the process of interaction and minimize the potential for misunderstandings. First responders in multicultural urban areas could also use these games to familiarize themselves with the cultures, languages, and social conventions of different ethnic groups that could help construct a more appropriate means of interacting with the public. Step #2, the identification of actual, versus potential threats can also be supported with database technology, if correct information is gathered and shared about potential threats. The minimization of false positives here is key for the civilian population to retain confidence in the system. The degree to which technology can support these two stages, obviously varies widely. As other initiatives emerge and are analyzed, the model should indicate to military commanders, chiefs of first responder units and organizational leaders, the degree to which technology can support a given phase of threat elimination.

TWO MAJOR DISASTERS: THE LONDON TERRORIST BOMBINGS AND THE NEW ORLEANS FLOOD Two major disasters occurred in the summer of 2005. The London terrorist bombing and the New Orleans flood. Case studies of both disasters will be developed in terms of the Target, Shield, and Weapon (TSW) model. The London terrorist bombing, like 9/11, was the result of a terrorist plot. The TSW model will provide insight into: •

•

•

What existing Information Technologies exist that could have prevented the bombings? Could the use of databases and surveillance technologies (widely used in London) uncovered the plot before it occurred? What emerging technologies can enhance the likelihood that future attacks can be prevented? How was Information Technology used to mitigate the damage of the attack? How was communication technology used to coordinate rescue efforts? What existing and emerging technologies can further improve rescue efforts after a terrorist attack? How was Information Technology used to track down the bombers? How did London’s elaborate surveillance system trace the bombers back to their supporting organizations? What existing and emerging technologies can enhance the ability to track down and eliminate future threats?

The New Orleans flood was a disaster of natural origins. The TSW model, however, can still provide insights. •

•

What Information Technologies could have predicted the problem and designed solutions? Preliminary evidence suggests that simulation models had already predicted the vulnerability of New Orleans’ levees to Class 4 hurricanes and that designs for solutions were in the blueprint stage. How can existing and emerging technologies identify future disasters from occurring? Furthermore, how can information resulting from these analyses be conveyed and acted upon before predicted disasters occur? Given the advances in first responder technologies and methodologies since 9/11, what went wrong in New Orleans? What

•

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existing and emerging technologies can enhance the ability of first responders to conduct well co-ordinated and effective rescue and evacuation efforts? Since a hurricane is a natural disaster, it is unlikely that IT can prevent future storms from materializing.

In both cases the taxonomy provided by the TSW model will provide insights into which Information Technologies are already available, which are emerging, and what further basic research needs to be done. Insights into which Information Technologies developed to counter terrorism can be applied to predict and to mitigate the impact of natural disasters should also emerge.

REFERENCES Grabowski, M. and Roberts, K. (1997). Risk mitigation in large scale systems: Lessons from high reliability organizations. California Management Review, Summer, 152-162. Klein, R.L., Bigley, G.A., Roberts, K.H. (1995). Organizational culture in High Reliability Organizations. Human Relations, 48:7. 771792. Lally, L. (1996). Enumerating the risks of reengineered processes. Proceedings of 1996 ACM Computer Science Conference, 1823. Lally, L. (1997). Are reengineered organizations disaster prone?” Proceedings of the National Decision Sciences Conference, 178182. Lally, L. (2002). Complexity, coupling, control and change: An IT based extension to Normal Accident Theory. Proceedings of the International Information Resources Management Conference, 1089-1095. Lally, L. (2005) Information Technology as a Target and Shield in the Post 9/11 Environment. Information Resources Management Journal, Jan-Mar, Volume 18, No. 1. Lally, L. (2005). Applying the Target and Shield Model to Wireless Technology, Proceedings of the International Information Resources Conference, upcoming. LaPorte, T. R. & Consolini. P. (1991). Working in practice but not in theory: Theoretical challenges of High Reliability Organizations. Journal of Public Administration, 1, 19-47. Perrow, Charles. (1984). Normal Accidents: Living with High Risk Technologies. New York: Basic Books. Sagan, Scott. (1993). The Limits of Safety. Princeton New Jersey: Princeton University Press. Turner, B.M. (1976). The organizational and interorganizational development of disasters. Administrative Science Quarterly, 21, 378397. Weick, K.E.and Roberts, K. (1993). Collective mind in organizations: Heedful interrelating on flight decks. Administrative Science Quarterly, 38, 357-381.

ENDNOTE *

This research was funded by a Summer Research Grant from the Frank G. Zarb School of Business at Hofstra University.

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26 2006 IRMA International Conference

Crossing Privacy, Information, and Ethics Sabah S. Al-Fedaghi, Computer Engineering Department, Kuwait University, PO Box 5969 Safat, 13050, Kuwait, [email protected]

ABSTRACT This paper introduces a theoretical exploration of an interdisciplinary field that that integrates principles of ethics, privacy and information. Ethics has already been interwoven with information in the field of information ethics. We show that information ethics does not provide sufficient notions to handle ethical analysis that involves private information. Private information ethics gives moral consideration to the well-being of private information based on moral considerations regarding the welfare of its proprietor (the ‘owner’ of the information).

INTRODUCTION “Information Ethics” (IE) can provide an important conceptual framework within which to understand a multitude of ethical issues that are emerging as a result of new information technologies (Mathiesen, 2004). According to Floridi (1998), IE refers to the philosophical foundation that provides the basis for the moral principles that will then guide the problem-solving procedures in computer ethics. In IE, all objects are “information objects” and all information objects have inherent moral value. A human being as a private information entity has an intrinsic value that should regulate a moral action affecting it. “[A] person, a free and responsible agent, is after all a packet of information... We are our information and when an information entity is a human being at the receiving end of an action, we can speak of a mehood. ... What kind of moral rights does a me-hood enjoy? Privacy is certainly one of them, for personal information is a constitutive part of a me-hood” (Floridi, 1998). Mathiesen (2004) criticized such a theory of IE since “a theory of information ethics will need to specify the relation between persons and information such that information can be of ethical import.” Why does IE lack the specification of “the relation between persons and information such that information can be of ethical import?” We claim the reason is that IE does not provide sufficient definition of the types of information necessary for ethical analysis. Simply put, “private information,” not just “information,” is the “centre of ethical worth” of our information sphere because it is based on the highest possible characterization of intrinsic volubility, a human person, while the worth of abstract information is built on the lowest possible common attribute of such a worth.

THE PROBLEM Consider the difference between the idea of a human being as an information entity and as a private information entity. Suppose that a husband, “John,” reads the diary of his wife, “Alice,” without her permission. What is wrong with such an act? (Floridi, 1998). According to IE, the source of the wrongness is “a lack of care and respect for the individual, who is also her information” (Floridi, 1998). We should ask agents “to realise that when they treat personal and private information, they are treating human beings themselves, and should therefore exercise the same care and show the same ethical respect they would exercise and show when dealing with other people, living bodies or environmental elements” (Floridi, 1998). Nevertheless, in this example, the “ethical consideration” conferred on the patient (the recipient of the consequences, i.e., the wife) is not because she is an

information entity, but rather because she is a “private information entity.” Suppose that the diary does not include any private information, but contains nothing other than comparisons between scientific materials related to the wife’s profession. It is not clear whether IE considers such materials “private” (since they are privately owned) and thereby considers treating it as treating human beings themselves. If IE considers the materials to be private information, then this seems to mix possession of non-private information with information about a person. We show later that non-informational privacy intrusion is different than informational privacy intrusion. If IE does not consider such material to be private information, then the given ethical justification (treating it as treating human beings themselves) needs examination. It seems that the assumption here is that since the information is in a diary, it is personal information. We can raise the question, what if the diary contains other people’s personal information that is in the wife’s possession? In this case, does “treating human beings themselves” refer to the wife, the other people or both? Suppose the diary includes only private information regarding the wife’s friend, “Jane.” For simplicity, assume it includes only the information, “Jane is broke,” and that this is Jane’s private information that is in Alice’s possession. An IE justification may lead to the interpretation that the husband’s intrusion is wrong because it is an intrusion on Jane as an information entity (since it is difficult to think of this information as a constitutive part of the wife). The wife’s position as a patient in this ethical discourse is unclear. She is an information entity that possesses the personal information of another information entity. Also, suppose that, in the last case, the husband read the diary with the permission of his wife. Does IE consider his act (or his wife’s act of granting permission) to be wrong? Suppose that what the husband found in his wife’s diary is information about himself, for instance that his mother confidentially told his wife that he once had a psychological disturbance when he was a boy and that – according to his doctor’s advice – he should not be reminded of it. Where are the agent and the patient in such a scenario? Do we consider the husband an agent who stumbled on “a constitute part” of his-hood (the patient). In the alternative, is the wife the agent who has no right to hide a constitutive part of her husband’s informational “ontology” while, at the same time, she is the patient who is affected by the husband’s violation of her diary. Assume that the husband found a plan to kill a person, “Jane,” in his wife’s diary. Is the plan Alice’s private information? Does Jane have any claim to this information? We observe that ethical analysis related to private information needs a well-defined notion of what private information really is. What is needed here is a theory of private information that provides a framework for organizing private (personal) information issues. Utilizing the definition of private information proposed by Al-Fedaghi (2005a) and the basic premise of IE that information has intrinsic moral value, we will construct a foundation for private information ethics.

PRIVATE INFORMATION Private information theory includes a universal set of private information agents, Z = V ∪ N, of two fundamental types: Individual and

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Emerging Trends and Challenges in IT Management Nonindividual. Individual represents the set of natural persons V; Nonindividual represents the set of non-persons N in Z. Definition: Private information is any linguistic expression that has referent(s) of type Individual. Assume that p(X) is a sentence such that X is the set of its referents. There are two types of private information: (1)

(2)

p(X) is atomic private information if X ∩ V is the singleton set {x} , i.e., atomic private information is an expression that has a single human referent. p(X) is compound private information if | X ∩ V | > 1 , i.e., compound private information is an expression that has more than one human referent.

In Al-Fedaghi (2005a), the relationship between individuals and their own atomic private information is called proprietorship. If p is a piece of atomic private information of v ∈ V, then v is its proprietor. A possessor refers to any agent in Z that knows stores or owns the information. Any compound private assertion is privacy-reducible to a set of atomic private assertions. The familiar notation “.” is used to define the informational entity Individual such as Individual.Proprietary.Known, as shown in Figure 1. Figure 1 includes the following sets: 1. (a) (b) 2.

Proprietary is the set of pieces of atomic private information of an individual. Proprietary has two components: Known: The set of pieces of atomic private information that is in possession of others. Notknown: The set of pieces of atomic private information that is only known by the proprietor. NProprietary is the set of pieces of private information of the other individuals that is in the possession of a different individual; however, the individual in possession is not the proprietor.

PRIVATE INFORMATION ETHICS In Al-Fedaghi (2005a), it is proposed to adopt Floridi’s notion of moral value of information to private information such that private information ethics (PIE) recognizes private information itself has an intrinsic moral value. Recognition of the intrinsic ethical value of private information does not imply prohibiting acting upon the information. Rather, it means that, while others may have a right to utilize private information for legitimate needs and purposes, it should not be done in such a way that devalues private information as an object of respect. Private information consists of “human parts” with intrinsic value that precludes misuse. “Human parts,” as used here, does not imply a kind of sacredness; rather, it expresses relationship to humaneness that may be as valuable as a brain or as insignificant as some parts of the hair or nails. For example, the ontology of the person’s genome is on the border between material and informational forms being. A person can collect pieces of hairs to know the sequences the DNA; hence, in this case, private information is literally, in Floridi’s words, “part of me-hood”. The human-centered significance aspect of private information also derives from its value to a human being as something that hides his/her secrets, feelings, embarrassing facts, etc., and something that gives him/ her a sense of identity, security and, of course, privacy. There are many conceptualizations of human beings as information processors, information seekers, information consumers, information designers, and as “packets of information.” On the other hand, privacy has always been Figure 1. Proprietary information and non-proprietary information

27

promoted as a human trait and hence, information and privacy in combination result in a unique human notion that is vital and valued: private information. Floridi introduced the notion of infosphere: “The task is to formulate an information ethics that can treat the world of data, information, knowledge and communication as a new environment: the infosphere” (Floridi, 2001). Similarly, we propose the private information infosphere as a new environment for private information, as defined previously. Private information infosphere conceptualizes human beings as information referents. PIE is concerned with the “moral consideration” of private information because private information’s “well-being” is a manifestation of the proprietor’s welfare. The moral aspect of being a piece of private assertion means that, before acting on such information, thought should be given to its “being private,” in addition to other considerations (e.g., its significance/insignificance). This extension of ethical concern is a kind of infosphere/biosphere mixture since the patient is an informational “beingness” of a person. The private information infosphere includes entities in Z = V ∪ N that deal with private information. Individuals (humans) in V and nonindividuals (non-humans) in N act as agents. Also, in PIE, the informational ontology of a human being is limited to his/her proprietary private information, i.e., private information that refers to him/ herself. A human being may possess non-private information or private information about others, but these types of private information are not “a constitutive part” of that human being. Private information is considered to have a higher intrinsic moral value than non-private information. From the privacy side, the moral worth of private information is based on the assumption that the proper “beneficiary” of the moral action is the proprietor of the private information. Thus, the intrinsic moral status of private information comes from the intrinsic moral status of its proprietor. To phrase it more accurately, the “moral considerability” of private information by agents stems from the proprietor’s right to “privacy”. The individual’s role as patient comes indirectly through having his/her proprietary private information affected by the agents’ activities on that private information. Consider the act of possessing private information that is not one’s own, against the proprietor’s will, whose consent is not unreasonably withheld. What is wrong with such an act is not the possession of information, hardly valued in itself as an anonymized piece of information, but the possession of information with a particular quality - namely, that of being not the proprietary information of the possessor. Thus, the proprietor of the possessed information is the patient toward whom the act is aimed, and it is the patient who is affected. The sensitivity of the private information is incidental; whether it is information of minor significance or vital health information does not affect the fundamental character of the act as morally wrong. Thus, possession of private information - against the proprietor’s will - amounts, morally, to theft, where the wrong is not acting on the stolen thing, but taking the thing which is not one’s own. According to PIE, a human being, as a private information entity, has an intrinsic value that should regulate a moral action affecting him/her. Information about the human-information entity (proprietary private information) has an intrinsic value because it is a constitutive part of that entity. Privacy is assumed to be property of human beings. Thus, “Book DS559.46.H35 is out of print,” is not private information; consequently, it has no PIE intrinsic value. Also, if the person under consideration is Einstein, then E=mc² is not a constitutive part of Einstein, while, “I am convinced that He does not play dice,” is because it contains the identification, “I,” that refers uniquely to Einstein. A fundamental premise in PIE is that proprietary private information about individuals is a constitutive part of the individuals. The implication here is that private information has a value because a person values it in the same way he/she values aspects or parts of his/herself.

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28 2006 IRMA International Conference We claim that the very nature of atomic private information gives it more significance than comparable non-private information. Suppose that we have the two assertions: 1. 2.

p (non-private assertion): Students in this class threatened one of their teachers. q (atomic private assertion): Students in this class threatened their teacher, Mrs. Jones.

We claim that q deserves more ethical consideration (e.g., is more bad) than p. The reason is that the assertion p has many possibilities of actions by the principal of the school. Ethical judgment motivates acts. The significance of the assertion is reflected in terms of its specificity in regard to performing an act. We can notice this in all aspects of life. A salesman immediately serves the customer who knows what he/she wants because this conserves the salesman’s energy. Courts have recognized the significance of this; thus, they specifically require professionals to act (e.g., warning victims) only when there is an overt threat of violence toward a specifically-identifiable victim. To put it simply, q deserves more ethical consideration than p because it deserves more acting consideration. Alternatively (and according to IE), we can observe that p has “less information” than q and hence, it is less valuable. The general objective in IE is to minimize any kind of decay in the information system, or information entropy. In information theory, entropy is usually viewed as a measure of the level of disorganization in any part of the universe. In this sense, information counteracts decay. In PIE, a condition in which there is no private information refers to complete “publicness” (decay) of informational privacy where every possessor has all private information in the environment, assuming |Z| > 1 and |V| > 0. The other extreme state occurs when there is no possession of non-proprietary private information. We can assume a model of a finite and closed system with ideal state of distribution of private information where “good” acts are those acts that bring the system closer to this ideal state. PIE is unique in terms of its entropy-related properties. For example, randomization increases the information entropy of the system. Nevertheless, the techniques of randomization and anonymization are used to protect private information. Both techniques increase the information entropy. A hospital that k-anonymizes its health records makes every k records indistinguishable from each other, thus increasing the level of entropy. The opposite is true in PIE, where randomization and anonymization halt the “spread” of private information, thus increasing informational privacy and the “privacy order” of the environment. PIE’s evaluating moral criteria is that “publicness of private information” is, in general, evil because it causes the degradation of privacy. “Publicness” of private information refers to any transaction that results in moving private information: (a) from Proprietary.Notknown to Proprietary.Known, (b) to more possessors in Proprietary.Known. “Publicness” is “dis-privatizing” the individual and can be viewed as the disorder (entropy) of the structure of private information; consequently, minimizing it benefits the privacy environment and allows the proprietors of private information to flourish.

PRIVACY INTRUSION Returning to the example of a husband who reads his wife’s diary without her permission, the husband’s act is wrong because he then possessed private information without the consent of its proprietor. There are several types of interference or intrusion in PIE. Also, there is a difference between the act of intruding on a person and intruding on that person’s private information. Non-informational privacy intrusion: In this situation, the wife’s diary includes no information or non-private information. Notice that the “patient” in PIE is private information. Informational privacy intrusion: In this case, the agent’s intrusion is on the private information of a proprietor, i.e., the diary includes private information. Figure 2 shows possible categories of this type of private information that can be found by the husband. Accordingly, informational privacy intrusion on each type of these pieces of private information caries different ethical weight: Intrusion on Proprietary.Known: As in (1): This piece of atomic private information is a shared secret between Alice and her mother, Mary. The intrusion in this case is an intrusion on Alice’s right to control the sharing of her private information with others. Intrusion on Proprietary.Notknown: As in (2): Only Alice knows this piece of atomic private information. She has not even mentioned it to her mother. This intrusion is a violation of Alice’s right to have her private information remain in her mind. Intrusion on NProprietary.Notknown: As in (3): Alice knows this piece of atomic private information about John and she does not tell anyone about it. This intrusion is an intrusion on Alice’s right to generate private information about others in her mind. Intrusion on NProprietary.Known: As in (4): This piece of atomic private information about Mary is known by Alice and others. We assume that John is not among the people who know this about Mary. This intrusion is an intrusion on the confidentiality of private information in possession of a person. As we see here, the husband’s act is an informational privacy related act if it involves private information. If it does not, its moral status is equivalent to intrusion on things that the wife owns, such as logging onto her computer without consent. Such an act may have privacy-significance but it is not an intrusion on “me-hood.” It is analogous to stealing my pencil, in contrast to stealing, for instance, pieces of my hair for whatever purpose. If the act does involve private information, then the moral seriousness of such an act depends on the type of private information involved.

Figure 2. Possible categories of informational privacy intrusion

The ethical principles regarding private information regulate the behavior of any agent. Individuals have proprietary rights to their private information. Agents have the duty to treat private information, when it is put in the role of patient, as an informational manifestation of its proprietor. Generally, any action on a piece of private information is evaluated in terms of its contribution to the welfare of the privacy information sphere, which implies the welfare of proprietors. This focus on welfare seems to have some universality, as suggested by the development of agreed-upon principles of private-information protection and other privacy-protection rules.

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Emerging Trends and Challenges in IT Management

29

CONCLUSION

REFERENCES

The intertwining of privacy, ethics and information generates many new ways to revisit theories and issues from these three realms of inquiry. An example is developing moral justification for lying about private information. Privacy provides a universal requirement that supports lying about private information in order to avoid harm (Al-Fedaghi, 2005b). PIE is also applied to study the dilemma whether to breach confidentiality in the case of the risk of harming identifiable individuals (Al-Fedaghi, 2005c). It is argued that the right of the third-party person to his/her private information outweighs maintaining patient confidentiality. The argument is that the private information involved is “compound” information that identifies several individuals and hence it is “owned” by all of its proprietors. Further work in this direction includes applying PIE to rules of fair information practices, personal defamation, personal misinformation, etc.

Al-Fedaghi, S. (2005a). “How to Calculate the Information Privacy.” Proceedings of the Third Annual Conference on Privacy, Security and Trust. October 12-14, St. Andrews, New Brunswick, Canada. —. (2005b). “Lying about Private Information: an Ethical Justification.” Communications of the International Information Management Association,, Volume 5, Issue 3, 47-56. —. (2005c). “Privacy as a Base for Confidentiality.” The Fourth Workshop on the Economics of Information Security (Rump session). Harvard University, Cambridge, MA. . Floridi, L. (1998). “Information Ethics: On the Philosophical Foundation of Computer Ethics.” ETHICOMP98 The Fourth International Conference on Ethical Issues of Information Technology. —. (2001). “Ethics in the infosphere.” The UNESCO Executive Board 161st Session Thematic debate “The New Information and Communication Technologies for the Development of Education.” UNESCO, Paris. Mathiesen, K. (2004). “What is Information Ethics?” Computers and Society Magazine Volume 32 - Issue 8 (June).

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30 2006 IRMA International Conference

Unattended Delivery for Online Shopping: An Exploratory Study from Consumers Perspectives Brett Ferrand, Mark Xu, Martyn Roberts, Portsmouth Business School, University of Portsmouth, Portsmouth, UK, PO1 3DE

ABSTRACT

SCOPE OF THE STUDY

Waiting for items to be delivered and the failure of scheduled delivery can offset the time-saving and convenience benefits of online shopping. This paper reports on part of a survey-based study that examines consumers’ perception of current delivery options when shopping online in the UK. It found that the delivery options currently offered by eTailers were limited and the level of negative attitude towards the current delivery processes was high. UK consumers do not perceive unattended delivery as a particularly favourable choice as widely reported in US and Europe, but see online tracking and local collection points as more convenient delivery options.

Delivery requests vary according to the type of products purchased online. The delivery of letter-box sized items is not a concern for both the eTailer and eShopper, as the item can be securely delivered to the consumer’s property without the need for the person to present. Delivery of larger items is often linked to installation and commissioning of the product purchased, making unattended delivery difficult and consumers accept that their pre-arranged presence is necessary. This study concentrates on the delivery of small packages, parcels and groceries (except perishable items that have special delivery requirements). Delivery of these items tends to cause most inconvenience to the consumer and is an area where has potential for eTailers to improve.

INTRODUCTION Product delivery for online shopping is considered to be an important part of order fulfilment that is becoming more salient to consumers (Cooke, 2004). One of the notable benefits of online shopping is the convenience and time saving when compared to traditional shopping (Alreck and Settle, 2002; Roberts, et al. 2003). However, recent studies have shown that the convenience and time saving benefits have not always materialised (Morganosky and Cude, 2002; Annon, 2004). Some online shoppers even feel online shopping takes longer than traditional shopping mainly because of delays in delivery or the problems of failed delivery. Morganosky and Cude (2002) report that although the majority of the respondents cited convenience as the most important motivational driver for using online shopping service, over 20% of respondents felt the time was the same or even more than traditional shopping. Annon (2001) reports that 42% of home shoppers had to collect missed delivered items from a post office or other depot in the year 2000. In their later study (Annon, 2004), 64% of respondents said they would buy more online if they had more delivery options, with unattended options coming out the top of their wish list. It is apparent that the logistics infrastructure and the delivery model effects the adoption of online shopping. Frazer (2000) identifies time constraint issues, the quality of home delivery services, and the variety of delivery services on offer as some of the reasons why home delivery is the weakest link in the Internet chain. He argues that businesses are increasingly finding it difficult to find delivery options that are both affordable and satisfy consumers. This notion is reinforced by Newton (2001) who states the central challenge for B2C companies is to deliver products to the home of individual consumers in a way that is cost effective and meets customers’ expectations. Compared with a large body of literature on Internet adoption (Gary, 2003; Fillis, et al. 2004); online shopper profile (Kau, et al. 2003), effective delivery models for online shopping are under-researched. The common order-fulfilment models (i.e. distribution centre vs. existing store pick up) has attracted the attention of some researchers (Seybold, 2002; Punakivi and Tanskanen, 2002), and the concept of unattended delivery has emerged from US and EU based studies (Ring and Tigert, 2001; Tanskanen, et al. 2002; McKinnon and Tallam; 2003). However, the concept of unattended delivery has not been tested in the UK from both consumer and eTailers perspectives.

A REVIEW OF DELIVERY OPTIONS Many traditional and innovative delivery options are currently available for uses by online retailers (eTailers), but the situation today is that there is not yet a proven operations model for the home delivery service (Tinnila and Jarvela, 2000). Three main types of delivery methods/ models are reviewed as follows: Traditional Delivery The traditional delivery options that are currently used by parcel handlers are: same-day, next-day and multi-day delivery. Dimaria (2002) suggests that same day deliveries that ensure products magically appear on the doorstep of consumers within hours of placing the order are unlikely to ever happen. This is because companies must have a full inventory located in nearly every local market throughout the country. This tends to be expensive and will not be cost effective for the online retailer. Next day service is currently the most popular option. Some customers may associate next day delivery with first-thing-in-themorning, which is what it typically used to be. The final option is multiday delivery. It may be the most economic method, but delivery can take anything from two days or more. Time Slot Delivery Grocery retailers offer different delivery time slots to their consumers. ISOTrack (2003) analysed the use of timed delivery options and identified some problems with its use. The main problem is the uneven time slots required, that is the majority of consumers who order groceries, want goods to be delivered between 6 p.m. and 8 p.m. with Thursday to Sunday being favourites. This places large demands on the delivery fleet during busy period, that is vans running at low capacity for 80% of the day then at full capacity for the rest. The uneven demand for time slots is also supported by a DTI (2001) survey of 317 Internet shoppers where 34% of them indicated that the best delivery time slots for them would be between 6 p.m. and 8 p.m. ISOTrack (2003) proposes that companies may need to offer customers on the Internet only the slots which are profitable, for example, hiding the Friday slots or, giving different charges, for example, charge more for Friday slots than that for Monday and Wednesday.

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Emerging Trends and Challenges in IT Management Figure 1. Cluster model for unattended delivery Online shopping

Table 1. Participant demographic profile Frequency

%

Male

%

Female

%

Under 15

Age Range

7

5.6

4

3.2

3

2.4

15 – 29

42

33.6

25

20

17

13.6

5.0

30 – 44

34

27.2

17

13.6

17

13.6

4.2

45 – 59

38

30.4

22

17.6

16

12.8

4.2

Customer

Internet Storefront

Collect

Over 60

Picking Up Centre (DC)

Delivery

Reception Box / Clusters near home/work

31

Total

Average Shopping Frequency* 4.7

4

3.2

0

0.0

4

3.2

6.5

125

100

67

54.4

58

45.6

4.9

*Scale 1 = Never, 7=Regularly

Unattended Delivery Delivery for packets and parcels is only beneficial if customers are there to receive them. Punakivi and Tanskanen (2002) suggest that the most expensive service model among the ones generally used is attended delivery on the following day in one-hour delivery windows. The least expensive service model, unattended weekly delivery on a defined weekday, will reduce home delivery costs to less than a half. Originally, unattended delivery was simply leaving an item on someone’s doorstep, or in their garden shed, but this brings many security concerns and implications for those items. McKinnon and Tallam (2003) analysed secure unattended delivery options including home security access systems, fitted integrated box, fitted external box, mobile reception box, workplace collection, use of existing outlets and mechanised storage and retrieval devices. These options are believed to improve home delivery to match the busy lifestyle of consumers whilst still being profitable for the company. Unattended reception is the optimal service concept from the perspective of cost efficiency in home delivery transportation. It allows for greater operating efficiency without sacrificing the service level, but requires investment in reception solutions at the consumer end. Unattended reception of goods can be achieved with a refrigerated reception box at the consumer’s location or a delivery box, or a shared reception box cluster, which is similar to garbage collection from a block of flats or an office building. The clusters can also be placed in dense residential areas to ensure sufficient households have access to the boxes. Tanskanen, etal. (2002) suggest a “Clusters Model” for unattended delivery, which is depicted in Figure 1. The concept is to build a refrigerated reception box at the customer’s home or located in an office building, or a shared reception box clusters for unattended delivery. Ring and Tigert (2001) suggests that the objective of delivering to a collection point could increase the number of deliveries per hour and reduce significantly the delivery time. They use GIB (Brussels) as an example to show that the number of orders “delivered” (to the collection point) would be 9 per hour, this fulfilment ratio is about 2.5 times higher than deliveries made per hour by delivering directly to the home (4-5 orders per hour). Delivery models need not only to be convenient to customers but also financially viable for the company. Ring and Tigert (2001) argue that the two killer costs facing the pure Internet grocer are the picking costs and the delivery costs. The objective to select which delivery model is to significantly reduce the delivery time or increase the number of deliveries per hour. Another concern is whether consumers would like to pay extra for secured unattended delivery, or pay more for extra services (Cooke, 2004).

between 15-59 years old. This is the typical UK e-consumer group as suggested by Consumer Knowledge (2004). The questionnaires were initially piloted on 10 consumers and appropriate changes made in the light of feedback. The final response rate for the consumer questionnaire was 71%. The questionnaire was split into three sections: the consumer profile, the online experience with the current delivery process, and the views/ perceptions on online delivery options. Both quantitative and qualitative data were collected and tabulated for data analysis. The next section reports the main findings from the questionnaire.

RESULTS AND DISCUSSION The characteristics of participants involved in the survey are important contextual information for understanding the findings. Table 1 shows the demographic profile of the respondents. The table shows that participants are primarily in the age group between 15-59 years old, which confirms the e-consumer category identified by Consumer Knowledge (2004). The sample consists of a good mix of male and female respondents. Consumer Experience With Delivery Of Online Shopping This section examines consumers’ online shopping experience with regard to the delivery location and problems with the current delivery methods. Table 2 shows the frequency of participants using which delivery locations to have their online purchases delivered. The table shows that most participants frequently have their online purchases delivered to their home. Other locations are rarely used including local collection points, safe box, and other locations. Deliver to work place is rather limited to very few consumers. Consumers’ negative experiences of home delivery process are explored through the question and the findings are presented Table 3. The results shows that 64% people frequently collected items from distributors’ depots and over half of the respondents often reorganize their day in order to wait for delivery to arrive. This shows that many purchases online resulted in inconvenience for online shoppers.

Table 2. Delivery location Delivery Options

METHODOLOGY This study uses questionnaires to gauge the current delivery processes offered by eTailers in the UK and the perceptions and attitudes towards unattended delivery from e-consumer’s point of view. Questionnaires were distributed to 150 selected e-consumers electronically via email with a follow up call to non-respondents after 5 days. A sample of 125 e-consumers was framed. Consideration was taken to achieve a balance of male/female participants and to gain a balance of age distribution—

Mean*

Deliver to home

4.18

Deliver to work Place

2.07

Deliver to other locations

1.58

Local collection point

1.51

A safe box

1.26

* 1- Never, 5-Very Frequently

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32 2006 IRMA International Conference Table 3. Negative experiences with home delivery Experience With Delivery

Table 4. Consumers’ attitudes towards delivery process

(Very) Frequently 64%

Often 26%

Rarely/ Never 13%

Mean* n=125 3.5

Reorganise your day to stay at home for a delivery

27%

26%

47%

2.8

I prefer to have an expected delivery date before I purchase.

4.10

Re-arrange home or work place delivery time slots

16%

27%

57%

2.4

I would be willing to collect the item from a local convenient collection point within a

3.57

Collect an item from distributor’s depot

Items

Mean

I believe there is the need for online delivery tracking, with hourly accurate delivery

4.20

information.

reasonable distance of my house.

Wait for a delivery that did not arrive

13%

17%

70%

2.2

I am more likely to buy a product from a store that offers more delivery options than that of

3.54

just one standard delivery.

* 1- Never, 5-Very Frequently

The data also showed that participants rarely waited for a delivery that failed to happen. This shows a positive aspect to eTailers’ current delivery processes. This is in contrast to the argument (ISOTrack, 2003) that in the early e-commerce days, delivery successes rate was low with many deliveries not taking place on the day as scheduled.

I would pay more for a delivery that was more convenient

3.29

Offering different delivery options makes me think that a store is different from others

3.16

I would pay more for a faster delivery

2.92

I would like the item to be delivered for the lowest charge regardless of how long it took or

2.70

when it would be delivered. The speed of a delivery is more important than convenience.

2.43

Current delivery processes are satisfactory to me

2.42

I would like to be offered the chance to leave a safe box on my premises that the goods

2.34

could be delivered to.

Perceptions On Delivery Processes Participant’s attitudes and opinions regarding delivery options and related issues are shown in Table 4. The results show that there is a need for online delivery tracking. Most participants prefer to have an expected delivery date before purchase. This uncovers two potential areas for improvement by eTailers regarding their delivery processes. Positive responses (mean > 3.0) generated from this question suggest that consumer are willing to collect purchased items from local convenience stores, corner shops and are willing to pay more for convenience and faster delivery. Offering more delivery choices are also needed, which can differentiate the eTailer from other e-shops for competitive advantage. It was also shown that disagreement (mean < 2.5) was posed towards the offering of a safe box that could be left on the consumer’s premises. Participants don’t like the idea of having a safe box on their premises for items to be delivered to. There may be safety, cost, space and planning permission concerns with installing a safe box in the customer home in the UK. Overall, consumers don’t perceive the current delivery processes are satisfactory (mean = 2.42). Consumers’ Preference On Delivery Options Consumers’ preferences on delivery were sought through two open questions. The data generated is qualitative in nature, thus, is treated as such in data analysis. The main method used is to categorise the data according to thematic topics. Table 5 shows the results of consumers’ preferences on delivery choices. The results show that a variety of issues were generated from the participants of the study. 37 respondents expressed the strong desire for delivery tracking, and the need to be informed prior to the delivery arrival. This supports Dimaria’s (2002) argument that many consumers don’t necessarily mind the wait, provided that they are properly

N= 125, Scale, 1- Strongly Disagree, 2- Disagree, 3-Undecided, 4-Agree, 5-Strongly Agree

informed about how much they’re saving and given an accurate and reliable delivery window. This identifies a potential area for future eTailer to improve their delivery services. 34 respondents referred cost of delivery as an influential factor that affects their choice of delivery and e-shopping. Although no general consensus was achieved, consumers who are willing to pay extra want a faster speedy delivery service, whilst most consumers prefer no or low delivery charges. It suggests that delivery costs are a sensitive matter for consumers, and also a challenge confronted by eTailers. The result reinforces Charton’s (2001) finding that 52% of participates were dissatisfied with delivery cost issues of home shopping. Using collection points appears an attractive option, but the concern is with the distance between the collection point and the customer’s home, and the time available for the collection. Petrol station and 24 hours convenience stores were suggested as the possible collection points. To enable effective and efficient home delivery, delivery outside office hours are strongly suggested by some respondents, presumably they have a busy lifestyle. The benefit is obvious, i.e. it can increase the delivery quantity per hour, due to reduced road traffic and delivery is more likely to be attended by the customer. The result reaffirm our earlier suggestion that UK consumers are not inclined to using safety boxes, or reception boxes at customer’s homes for better delivery. Only two respondents agree with this unattended delivery method. Instead, UK consumers are used to and prefer to have items delivered to neighbouring houses. Not all eTailers currently adopt this method, but it can be considered as an option for unattended delivery.

CONCLUSION Table 5.

Preferred delivery methods

Category of preferred method Delivery Tracking Cost of delivery

Percent % (n = 117) 31.6 % 29 %

Work place delivery

18 %

Collection point delivery

16 %

Non Office Hour Deliveries

16%

Convenient delivery options

13.6 %

Neighbour

10 %

Speedy delivery

7.7 %

Standard delivery

6.8 %

Safe box

1.7 %

N = 117

The findings reveal that most UK consumers want a flexible delivery window prior to e-shopping and want to be able to track the delivery process and to be informed instantly. Although most UK consumers prefer no or low delivery charges, paying extra for better service (more convenient or faster) is not seen as a financial burden for those consumers. The preferred main delivery location is the consumer’s home. Most consumers are against unattended safe boxes; instead, they are in favour of using a neighbouring house or collection points like petrol stations or corner shops, so long as these collection points are within short distance and is time convenient. Most busy working families welcome weekend delivery and off-office hour delivery, but this poses challenges to eTailers because of uneven demand for delivery. The implication of the findings is as follows: firstly, eTailers need to be aware that delivery is becoming a significant factor affecting e-shopping

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Emerging Trends and Challenges in IT Management expansion. The convenience, time saving benefits of online shopping can be offset by increased time in waiting for delivery. Delivery problems could become a bottleneck for the further adoption of e-shopping. Secondly, an appropriate delivery model (or a mix of various delivery methods) needs to be developed to satisfy consumers’ different needs. Thirdly, factors that affect eTailers to choose which delivery options need to be considered in conjunction with increasing consumer convenience, for example, delivery cost, cost of device for unattended delivery.

LIMITATIONS A further paper will report on the second part of the study, which examined 15 eTailers on the views and concerns of the aforementioned delivery options and the challenges for implementing new delivery methods. Due to space limitations, the results are not reported. The reasons of consumers’ preference of a particular delivery method should have been explored. Both of the results would help interpret, for example, why UK consumers are not inclined to unattended delivery (delivery box) that appears to be widely accepted in US and Europe.

REFERENCES Alreck, P. L. and Settle, R. B., (2002), The hurried consumer: timesaving perceptions of Internet and catalogue shopping The Journal of Database Marketing, (UK), September, Vol.10, No. 1, pp.25-35. Annon (2001), Survey puts figures on failed deliveries. e.logistics magazine, February, pp.9 Annon (2004), What people want from home shopping. e.logistics magazine June/July, pp.14, 17. Charton, (2001), Get delivery right, then worry about price survey, e.logistics magazine March, pp.9. Consumer Knowledge, (2004), Consumer Knowledge - Buying online a report online a report by the general consumer council for Northern Ireland. GCCNI. Available: URL http:// www.gccni.org.uk/online_documents/Buying_online_final.pdf. Cooke, J., (2004), Shippers are paying more for “last mile” deliveries, Logistics Management, September, Vol. 43, Issue 9, pp.19. Dimaria, F., (2002), Wrap Session. IE Solutions . May, pp.34 – 38 DTI (2001), Survey results RAC Available: URL http://www.dti.org.uk/ survey/asp/ 2001/results_final. Fillis, I., Johannson, U., and Wagner, B., (2004), Factors impacting on adoption and development in the smaller firm. International

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Journal of Enterpreneurial Behaviour & Research, 10(3), 178191. Frazer, B., (2000), Home delivery is the weakest link in Internet chain. Marketing Week . 23 (16), pp.22. Gary, C., (2003), A stage model of ICT adoption in small firms, Workshop in Rimini – Firms and Consumers Facing E-Commerce: Strategies to Increase Its Adoption and Usage”,Open University Business School, UK. ISOTrack, (2003), The uses of timed delivery slots. In: ISOTrack 2003, London: ISOTrack 1-34. Kau, A. K., Tang, Y. E., and Ghose, S., (2003), Typology of online shoppers, Journal of Consumer Marketing, 20 (2), pp. 139-156. McKinnon, A., & Tallam, D., (2003), Unattended delivery to the home: an assessment of the security implications. International Journal of Retail & Distribution management, Vol. 31 (1), pp.30 – 41. Morganosky, M. A., and Cude, B. F., (2002), Consumer demand for online food retailing: is it really a supply side issue? International Journal of Retail & Distribution Management, Vol. 30, No.10, pp. 451-458. Punakivi, M. & Tanskanen, K., (2002), Increasing the cost efficiently of e-fulfillment using shared reception boxes, International journal of retail & distribution management, 30 (10), pp.498 – 507. Ring, L. F., and Tigert, D. F., (2001), Viewpoint: the decline and fall of Internet grocery retailers International Journal of Retail & Distribution Management, (UK), Vol. 29, No. 6, pp. 264-271. Roberts, M., Xu, M., and Mettos, N., (2003), Internet Shopping: the supermarket model and customer perceptions, Journal of Electronic Commerce in Organisations, 1 (2), pp. 33-44, April-June. Saunders, M., Lewis, P., & Thornhill, A., (1997), Collecting primary data using questionnaires. In: Research methods for business studies. London: Pitman Publishing. 243 – 286. Seybold, P., (2002), Shopping online at Tesco, Online source: Business Line, Financial Daily from the Hindu Group Publications. http:/ /www.blonnet.com/catalyst/2002/03/07/stories Tanskanen, K., YrjÖla, H., HolmstrÖm, F., (2002), The way to profitable Internet grocery retailing – six lessons learned, International Journal of Retail & Distribution Management, (UK), Vol. 30, No. 4, pp.169-178. Tinnila, M., and Jarvela, P., (2000), “First steps – second thoughts – third parties” Digital Media Report, Tekes, Helsinik.

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34 2006 IRMA International Conference

Achieving Implementation Success in Ubiquitous Computing Environments: Understanding the Role of Psychological Ownership Edward J. Garrity, Information Systems Department, Canisius College, Buffalo, New York 14208 USA, {E-mail: [email protected]} Junghoon Moon, {E-mail: [email protected]} G. Lawrence Sanders, Management Science and Systems, State University of New York at Buffalo, Amherst, New York 14216, {[email protected]}

ABSTRACT This paper proposes the use of general systems theory and systems diagramming techniques to identify pervasive computing opportunities. The Garrity and Sanders’ model of information systems success is used to provide a framework to view implementation and the variable psychological ownership is identified as a potential major factor for pervasive computing implementation success.

INTRODUCTION The rapid development of and diffusion of new information technologies such as wireless and mobile communication technology, the Internet, hand-held computing devices, and cellular telephones is beginning to have a dramatic impact on business and organizational computing environments. New computing applications are quickly emerging and are changing how work is performed and the way organizations are structured. In general, the use of these technologies enables a new distribution of work within and between organizations and is leading to a new set of computing capabilities termed – Ubiquitous, Pervasive or Nomadic Computing (Note: We will use the term Pervasive computing to denote those applications which allow computing and communication from virtually any location.) Lyytinen and Yoo (2001) define Nomadic computing as a heterogeneous assemblage of interconnected technological and organizational elements, which enables physical and social mobility of computing and communication services between organizational actors both within and across organizational borders (p.1). In order to better understand how organizations can best apply these technologies for competitive advantage and to better understand how to systematically study these emerging applications, this paper proposes (1) a practical way of identifying pervasive computing opportunities along with a research framework based on systems theory, and (2) the use of Psychological Ownership as an important dimension to advance our understanding of information system implementation success. This paper is organized as follows. Section 2 reviews characteristics of pervasive computing environments and discusses how general systems theory may be used as a tool to examine these areas and as a way to identify potential areas of application for pervasive computing. Section 3 discusses the dimensions of information systems success and how they are pertinent to pervasive computing. Section 4 discusses the concept of Psychological Ownership and how it relates to achieving success in the implementation of pervasive computing applications. Section 5 is the summary and conclusions.

CHARACTERISTICS OF PERVASIVE COMPUTING ENVIRONMENTS Technological developments and business needs and trends have both been responsible for the emergence of pervasive computing. Technology such as wireless and mobile communication technology, the Internet, hand-held computing devices, and cellular telephones have all been key factors enabling computation and communication from virtually any location. In addition, the term digital convergence denotes the increasing use of embedded microprocessors in numerous products thus providing computing capabilities in hand-held devices or embedded within traditional products or environments. Wireless transmission in combination with embedded or miniature devices means that information can be transferred relatively easily; thus allowing transaction processing, workflow, customer service and management decision making all to be performed at alternative locations and times. While computing technology has enabled pervasive computing, the needs of businesses have also provided a strong impetus for corporations to seek pervasive computing. The globalization of business has meant an increasing need to connect various organizational units and members and to share information to enable faster decision making. In addition, increasing global competition has forced companies to stay closer to customers and provide better and more responsive customer service. Because of these business and technology trends, pervasive computing has emerged as an important area of study for researchers and IT professionals. The Essence of Pervasive Computing The essence of pervasive computing, in a physical sense, is the embedded nature of the technology. In other words, due to the technological advances referred to earlier, computing power and digital communication or information transfer can take place from virtually any location. Because of the location independence of computation and information transfer, the conduct of business can be fundamentally altered. In essence, these sets of communication technologies allow for virtual teams within organizations, location independence, or what Lyytinen and Yoo (2001) call virtualization. Many of the previous assumptions regarding where and how work must be performed can now be questioned and altered. This paper proposes the use of two models or viewpoints to address how best to manage these impacts: (1) the use of systems theory and (2) the use of a socio-technical viewpoint that gives greater attention to the human, social and psychological aspects of the interaction of humans and technology within work systems.

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Emerging Trends and Challenges in IT Management Organizational-based Pervasive Computing and General Systems Theory Pervasive computing has the potential to greatly impact the nature of work within companies. In the case of intra-organizational computing, numerous examples exist of how companies have incorporated the use of information technology to improve productivity or decision making. Sipior and Garrity (1990) describe a case where the early adoption of laptop computers and expert system software helped salesmen provide expert, technical product advice to customers. Prior to the adoption of this technology there were long delays in finding expert advice, and long delays mean lower levels of customer service and lost sales. Essentially, this use of pervasive computing meant that an expert could be available, or virtually available, on demand.

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Figure 1. MNP’s system Customers

Prescription

Physical product

Subsystem, Store 1 Technology Pharmacists Prescription

Information

Currently, a major, national Pharmacy (MNP) is in the process of using Internet and communications technology to balance the work load of retail pharmacy stores. Specifically, some MNP outlets experience low volume prescription sales while others are heavy volume. MNP is in the process of sending basic customer profile information from heavy load stores to lighter load stores. The low volume stores can then utilize their pharmacy work force to do data entry and basic prescription checking – without causing inconvenience to customers (i.e., customers still have their prescriptions actually, physically filled at their normal location). This example illustrates the tremendous flexibility afforded by pervasive computing – work can be performed where it is more convenient for company productivity, not necessarily limited to the traditional or historical physical location. Meanwhile customer service is actually improved as heavy volume stores do not overburden the pharmacy workforce. These examples beg the question – “How does one go about identifying potential areas for the application of pervasive computing?” We recommend the use of general systems theory because by examining work systems abstractly we can remove various forms of bias or preconceived notions regarding technology application or traditional business thinking and business rules. Specifically, in the MNP example above, we can diagram the situation abstractly using systems theory and focusing on the sub-systems, information flow, components (computer technology and human components) and boundaries (See Figure 1). In Figure 1 above, the fast and easy transfer of digital information from store 1 to store 2 made this particular pervasive computing example possible. Similarly, the OpBright expert system example above is another example of pervasive computing because information (and knowledge) was easily transmitted to the location where it was needed most – at the sales site, where expert advice could be rendered to provide customer service, support, and aid in the process of selling products. In both of these cases, the key ingredient was the rapid availability of information and computing power and the ability to have work performed or transferred to the location where it most matters. The use of a general systems theory approach with the aid of a diagramming technique as shown above (or using data flow diagramming or similar systems analysis and design tools), allows the business analyst a degree of objectivity and open mindedness because such tools allow one to abstract the essential features of the situation without being constrained by current technology considerations. In other words, we are suggesting that traditional systems analysis and design techniques can and should be applied to the study of potential pervasive computing applications. In a similar fashion, one may still use the same analysis and design techniques for the design of the entire work system, regardless of whether the work is performed within the organization, externally along the supply chain, or externally by a more efficient system or company (i.e., outsourcing work to another firm). Again this is accomplished through the ability to quickly transfer digital information to a different physical location. Similarly, one may diagram or abstractly represent this work and information transfer using various system diagramming techniques (based on systems theory). The power of this technique is that less is represented – only the essential features need to be modeled – data flow, data storage, and data transformation

Subsystem, Store 2, (low Volume) Pharmacists

Technology

(i.e., processes or transformations). Whether a human or a computerbased system does the data transformation is unimportant in identifying opportunities for the use of pervasive computing. These details, or implementation concerns, are best handled after the initial design of “where” work should best be performed. Once opportunities have been identified and a fundamental redesign of work has been accomplished, one must still implement the new work design within an organizational setting. In order to better understand the issues involved in achieving implementation success the next section discusses the dimensions of information systems success.

DIMENSIONS OF INFORMATION SYSTEM SUCCESS Garrity and Sanders (1998) extended the DeLone & McLean (1992) model of information systems success and proposed an alternative model in the context of organizational and socio-technical systems (Figure 2). The model identifies four sub-dimensions of User Satisfaction: Interface Satisfaction, Decision Support Satisfaction, Task Support Satisfaction, and Quality of Work Life Satisfaction. These factors were derived from an extensive review of IS success research and reasoning from basic principles of systems and general systems theory. The four factors correspond with three viewpoints of information systems: the organizational viewpoint (that IS as a component of the larger organization system), the human-machine viewpoint (which focuses on the computer interface and the user as components of a work system), and the socio-technical viewpoint (that considers humans as also having goals that are separate from the organization and whereby the IT or technical artifact impacts the human component in this realm). Both Task Support Satisfaction and Decision Support Satisfaction attempt to assess the effectiveness of an IS within the context of the organizational viewpoint of systems. The Task Support Satisfaction dimension captures the overall set of tasks associated with job activities while Decision Support Satisfaction is more focused on decision support (i.e. structuring, analyzing, and implementing a decision). Interface Satisfaction assesses IS success from the human-machine viewpoint. Interface Satisfaction measures the quality of the interface in terms of presentation, format, and processing efficiency. The quality of the interface is related to both Task Support and Decision Support Satisfaction. An improperly designed interface can cause users difficulty with task completion or it can impair their ability to make decisions. The fourth dimension of the Garrity and Sanders’ model is Quality of Work-life Satisfaction. This dimension addresses the fit between an IS and the socio-technical work world of the respective users. Specifically, Quality of work-life satisfaction is concerned with the user’s physiological, psychological and higher order needs as they relate to intrinsic

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36 2006 IRMA International Conference Figure 2. Garrity and Sanders model of IS success (1998)

System Use

User Satisfaction Task Support Satisfaction Decision Support Satisfaction

Individual Impact

Organizational Impact

Quality of Work life Satisfaction Interface Satisfaction

rewards, job satisfaction, pleasure, feelings of worth and importance. Items for this dimension include assessments of the worker’s span of control, autonomy, how well the system supports the individual’s psychological well-being and is thus closely related to the technology’s impact on the user’s job satisfaction. Quality of work-life satisfaction is an important dimension of success in organizational settings. The last dimension of IS success, Quality of work-life satisfaction is especially relevant for pervasive computing environments since pervasive computing often demands that computer technology be embedded within our existing products and services and therefore it must work in a seamless, transparent fashion for technology to effectively act as a tool while not negatively impacting our personal lives and our general well-being.

PSYCHOLOGICAL OWNERSHIP AND ACHIEVING SUCCESS IN THE IMPLEMENTATION OF PERVASIVE COMPUTING Pervasive computing offers a number of challenges for developers and designers trying to achieve implementation success along the four dimensions discussed in section 3. In order to understand why, we first develop a broad, working definition of pervasive computing: Pervasive computing involves the set of technologies that allow for location transparency in the performance of organizational tasks, transactions, and or decision making. The key elements of the above definition are: (1) Tasks can be performed in many different locations – location independence (corresponding with task support satisfaction), (2) Decisions can be performed in many different locations – location independence (corresponding with decision support satisfaction). We have purposely not included the types of technology involved in pervasive computing in our definition because the sets of technologies are ever evolving. However, at present these technologies all involve getting information and knowledge from one location to another in a fast and effective fashion in order to provide support for task accomplishment, (documented and transferred as transaction processing) and decision making. Because of the nature of the technologies involved (e.g., wireless communications, RFID), pervasive computing tends to be embedded more tightly within the social system (both inside organizations and externally). Thus, we have a much tighter coupling with the socio-technical system and a greater potential impact on the human element of systems – with a corresponding greater need to assess impacts of pervasive computing technology on users’ Quality of Worklife satisfaction. As businesses increasingly seek to use pervasive computing technologies there will also be a greater demand on designing proper user interfaces to support users’ Task support, Decision Support and Quality of Worklife satisfaction.

Central to the discussion of implementation success of pervasive computing will be finding ways to incorporate technology into the user’s work-world, life-world, or socio-technical world so that they will find it both helpful in meeting their work, task or decision needs but also acceptable in meeting their personal or quality of life needs. A major factor that influences one’s job satisfaction and that has received much research attention lately is the factor – Psychological Ownership. The next section explores this variable in greater detail and examines its likely impact on pervasive computing implementation success. Psychological Ownership Psychological ownership is defined as the state in which an individual feels as though the target of ownership belongs to them (Pierce et al., 1992). Enhancing workers feelings of possession or ownership may be important considerations for organizations. For example, Brown (1989) stated that psychological ownership will be the key to organizational competitiveness during the 21st century and others have noted that Harley Davidson was able to make its successful turnaround largely due to creating feelings of ownership among its employees (Peters, 1988). Pierce et al. (1991) and others (Peters, 1988; Stayer, 1990) have proposed that psychological ownership is associated with positive behavioral and social-psychological consequences. Pierce et al. (2004) note that there are clinically based observations suggesting that responsibility, caring, stewardship, and acts of citizenship are enhanced when individuals experience feelings of ownership toward the target object. Further, Vandewalle et al. (1995) provided empirical support to demonstrate that psychological ownership was positively related to extra-role behavior and in positive social psychological states including organizational commitment and satisfaction. Determinants of Psychological Ownership Pierce et al. (1991) have suggested that control is an important structural component contributing to the experienced state of ownership. Researchers in the area of human development have proposed that as young children begin to explore their environment, they discover things that can and things that cannot be controlled. This initiates the beginning of a distinction between self and not-self. Objects for which there appears to the child to be a near-perfect correlation between their motor command and the visual feedback of their movement are experienced as parts of (i.e., one with) the self (cf. Seligman, 1975). Those objects that cannot be controlled fall within the domain of not-self. Similarly, through socialization practices, other people (e.g., parents) start to draw the line between what can and cannot be touched, moved, and controlled. Fearing for the safety of the child and passing along their own possession or ownership values, adults send strong messages..... It is through such direct experiences and socialization practices that a boundary gets constructed around possessions, along with the beliefs and feelings associated with the control of possession (p. 512, Pierce, et al., 2004). Prelinger (1959) provided empirical support for the link between object control and possession or psychological ownership. He found that the more an individual feels he has control over and can manipulate an object, the more likely that the object will be perceived as part of the self. Implications of Psychological Ownership for Implementation Success Pervasive computing applications demand a closer linkage between users in their social and socio-technical work worlds and computer technology. For example, when computer applications require close links with consumers, as is the case with radio-frequency identification technology for products (RFID), issues of control and privacy (a personal or social concern) become important. As eloquently stated by Weiser (1991),

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Emerging Trends and Challenges in IT Management “The social problem associated with ubiquitous computing, while often couched in terms of privacy, is really one of control.” The recent empirical study by Gunther and Spiekermann (2005) attests to the fact that consumers feel helpless and lack control over the RFID technology. Subjects in their study felt little control over their ability to control the RFID equipment, and the feelings of loss of control were even greater for the more highly educated consumers. Whether the pervasive computing technology is used within, or between organizations or to outside stakeholders, a key issue for implementation success will be to develop mechanisms that allow users (or consumers) the ability to control the technology and thus ultimately to develop a sense of psychological ownership. Within organizations one strategy is to involve users in a participative development process since participation in systems development and participative decision making are related to increased feelings of control. When the pervasive technology involves the consumer or other stakeholders outside the organization, careful development of interfaces will be a critical success factor since the interface is essentially the information technology artifact (object) and since the interface exerts such a strong influence on the other dimensions of information systems success.

SUMMARY AND CONCLUSIONS This paper has proposed a system approach to help identify pervasive computing opportunities and has demonstrated how systems diagramming may be used to provide an abstract and objective view to enable the discovery of these opportunities. Secondly, this paper has noted that as organizations implement more pervasive computing applications, it will become increasingly important to be especially cognizant of the impact of these systems on users’ socio-technical work world. This is because pervasive computing is inherently closely tied to users’ work environments, products, and social lives. A key factor that must be managed is the user’s feelings of psychological ownership, since this is likely to have a tremendous impact on the effective use of pervasive computing applications. The Garrity and Sanders’ (1998) model was used as a way to view implementation success of these applications.

37

REFERENCES Brown, T.L. (1989). What will it take to win? Industry Week, p. 15. DeLone W.H. and McLean, E.R. (1992). Information system success: The quest for the dependent variable. Information Systems Research, 3, 1, 60-95. Dwyer, D.J. and Ganster, D.C. (1991). The effects of job demands and control on employee attendance and satisfaction. Journal of Organizational Behavior, 12, 7, 595-608. Garrity, E.J., and G.L. Sanders, Dimensions of Information Systems Success, in: E.J. Garrity,G.L. Sanders (Eds.), Information Systems Success Measurement, Idea Group Publishing, Hershey, PA, 1998, pp. 13-45. Gunther, O., and Spiekermann, S. (2005). RFID and the perception of control: The consumer’s view. Communications of the ACM, 48, 9, 73-76. Lyytinen, K. and Yoo, Y. (2001). The next wave of nomadic computing: A research agenda for information systems research. Sprouts, Working paper, http://weatherhead.cwru.edu/sprouts/2001/ 010301.pdf, 20p. Peters, T. (1988). The leadership alliance. Schaumburg, Il: Video Publishing House. Pierce, J.L., O’Driscoll, M.P., and Coghlan, A. (2004). Work environment structure and psychological ownership: The mediating effects of control. The Journal of Social Psychology, 144(5), 507-534. Pierce, J.L., Van Dyne, L., and Cummings, L.L. (1992). Psychological ownership: A construct validation study. In M. Schnake (Ed.) Proceedings of the Southern Management Association, Valdosta, GA: Valdosta State University, 203-211. Prelinger, E. (1959). Extension and structure of the self. The Journal of Psychology, 47, 13-23. Sipior, J.C. and E.J. Garrity. Using expert systems for competitive advantage: A case study of the OpBright expert system. (1990). DSS-90 Transactions, Cambridge, MA, May. Stayer, R. (1990). How I learned to let my workers lead. Harvard Business Review, 68, 66-75. Vandewalle, D., Van Dyne, L., and Kostova, T. (1995). Psychological ownership: An empirical examination of its consequences. Group and Organization Management, 20, 2, 210-226.

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38 2006 IRMA International Conference

Business to Business E-Commerce and Inter-Firm Governance Qi Fei, Dept. of Mgmt, University Of Nebraska, Lincoln, NE 68588, P: (402) 472 4676, [email protected] Jim Q. Chen, Dept. of BCIS, St. Cloud State University, St. Cloud, MN 56301, P (320) 308 4882, [email protected]}

INTRODUCTION Electronic data interchange (EDI) and Internet based Business to business (B2B) e-commerce technology are two important inter-organization systems (IOS). Many studies have been done about their significant impact on business operations but little attention has been paid to their effect on the inter-firm governance. Inter-firm relationship has been the research focus in business management and information systems field for a long time. From the perspective of marketing, inter-firm governance is the mechanism which eventually determines inter-firm relationships. This study draws the conclusion that information technology has significant impact on inter-firm governance. Thus, understanding of IT impact on inter-firm governance will provide important insight for understanding the evolution of inter-firm relationship in the future. This study focuses on the transformation of inter-firm governance after business organizations adopt EDI and Internet based e-commerce technology. In the next section, a brief literature review on the interfirm governance is conducted. Then, the impact of information technology on inter-firm governance is analyzed. A conceptual model is proposed to show the transformation process. At last, transaction cost theory is adopted to explain the transformation. The article concludes with a summary and future research directions.

INTER-FIRM GOVERNANCES Governance is a mode of organizing transactions (Williamson and Ouchi, 1981). Palay (1984) defined it as shorthand expression for the institutional framework in which contracts are initiated, negotiated, monitored, adapted and terminated. Heide (1994) classified the governance of inter-firm relationship into three categories. Market Governance This concept is identified by transaction cost theory and could be viewed as a synonymous concept of discrete exchange (Goldberg, 1976 and Macneil, 1978) or arm’s length inter-firm relationship (Watts et al., 1995). For contracting parties in market governance, individual transactions are independent of past and future relations and constitute nothing more than the transfer of ownership to a product or service (Goldberg, 1976). When a transaction is finished, the partnership would be over. New relationship will be set up through new bargaining and negotiation. In this type of relationship, transaction parties have equal bargaining positions. No party is subject to the other’s control or dominant influence, and the transaction is treated with fairness, integrity and legality. Grover and Malhotra (2003) describe it as “coordinating materials and service flow between firms through the demand and supply forces, where in true competitive environments the buyer has choices of products and suppliers.”

Hierarchy Governance This category is also identified by transaction cost theory. It is corresponding to vertical integration (Williams’, 2002). To reduce operational cost and avoid supply uncertainty, some powerful companies set up stable relationship and business process integration with their upstream or downstream partners by acquiring their ownership. The possession of ownership engenders an authority structure which provides one contracting party (the core company) with the ability to develop rules, gives instructions and imposes decisions on the other one (Hart, 1990; Simon, 1991). Grover and Malhotra (2003) describe it as: “vertically integrated entities control and direct (product or service) flow at a higher level in the management hierarchy.” Compared with businesses in market governance, contracting parties of vertical integration have completely different relations: their cooperation is based on long term relationship instead of individual transactions; their positions within the relationship are not determined by demand and supply forces but by the ownership structure; their business processes are integrated with each other. Bilateral Governance This is a relative new notion. Transaction cost theory fails to identify it. Contracting parties within a bilateral relation jointly develop policies directed toward the achievement of certain goals. The nucleus of bilateral governance includes the following requirements (Bonoma 1976): individual units’ utility functions constitute global utility of a system; individual goals are reached in the system through joint achievements; individual units adopt a “unit action” orientation but the system serves as a restraint on individual tendencies; units concern about long term benefit of the system; members use self-control based on their internalized values (Ouchi’s, 1979). For companies in market governance, their relationship is based on individual transaction and their business processes are not integrated with each other. The basis of market governance is price mechanism (Bradach and Eccles, 1989; Maitland, Bryson and Van de Ven, 1985). On the contrary, the basis of both hierarchical and bilateral governance is long term cooperation and business process integration. However, they differ in integration mechanism.

EDI, INTERNET BASED E-COMMERCE SYSTEM, AND THEIR IMPACTS EDI has been widely adopted both in public and private sectors. Its users could be classified into two distinct types: initiators and adopters. The term “initiators” refers to EDI-initiating organizations. Initiators invest heavy resources to develop EDI applications and promote it to their trading partners. The term “followers” refers to those organizations which adopt and join the initiator’s EDI network. EDI provides an integration approach to shorten lead-time and reduce management cost. It enables trading partners to rationalize their operations. Combined with business process reengineering (BPR), it

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Emerging Trends and Challenges in IT Management enables adopters to reduce both inventory levels and stock-outs (Lee et al., 1999). At the same time, the basis of EDI-based integration is no longer ownership but information sharing. Thus, compared with authority parties involved in hierarchical governance, adoption initiators of EDI could avoid heavy ownership burden without sacrificing the operation efficiency. The relationship between initiators and followers is essentially different from that within vertical integration. Within vertical integration, all activities of peripheral units should encircle the benefit of the core unit. They are not independent and their own interest is in the secondary position. On the contrary, although EDI adoption followers’ positions are weak compared with their initiators, they are independent and their primary concerns are their own interests. The reason they decide to enter initiators’ EDI system is that they believed that they can achieve the business goals through the cooperation with initiators. The utility of whole EDI system is based on independent utilities of both initiators and followers. From the definition of bilateral governance, it is easy to say that the relationship governance between EDI adoption initiators and followers is bilateral rather than hierarchy compared with the relationship within vertical integration. Internet-Based B2B E-Commerce Technology The Internet-based E-commerce systems offer many benefits that EDI can not deliver. Two major ones are low construction cost and wide coverage. Internet technology urges the birth of e-marketplace. Emarketplace is an Internet-based virtual marketplace where organizations sell and buy products and services. For inter-firm governance, emarket is a relationship mechanism rather than just a virtual space. It has wide influences on different inter-firm governance. Businesses with traditional market inter-firm governance suffer from high searching cost and lack of information transparence. They also bear relative high transaction cost. E-marketplace provides them with a good opportunity to overcome this problem. E-marketplace is an efficient communication platform. Because of the apparent advantages of Internet, customers are capable to obtain any information and finish simple transaction at low cost. It would become much easier for companies to find their best business partners. For companies with hierarchical inter-firm relationship or those adopting EDI system, e-marketplace also provides all benefits EDI could offer and at the same time avoids EDI’s disadvantages. E-marketplace lowers the doorsill of technology adoption. It helps to increase market liquidity. Thus, both preponderant party and weak party would have more choices. The potential commitment aroused by heavy investment on system infrastructure would be released. It means that transaction parties become more independent than before. At the same time, facing keener competition, weak parties will be more motivated to raise system implementation level and thus improve cooperation quality. On the other hand, Internet also brings changes to supply chain system. Adopters do not need to construct or use VAN any more. Information and business documents could be transferred through Internet. There is no heavy investment for system adoption and upgrade. IT Impact at Micro Levels Heide (1994) proposed several evaluation standards for inter-firm governance based on three dimensions: relationship initiation, relationship maintenance and relationship termination. Relationship initiation is about the evaluation of potential business partners, initial negotiations, and preliminary adaptation attempts (Dwyer, Schurr, and Oh 1987). Relationship maintenance involves role specification, planning, adjustments, monitoring procedures, incentive system and means of enforcement. In the following section, these standards are used to show how information system influences inter-firm governance. Relationship Initiation Market governance does not require an initiation process (Butler, 1983). Hierarchical and bilateral relationships need initiation but the

39

processes are different. Bilateral governance involves more stringent initiation process. Both EDI adopters and Internet based e-commerce technology users need relationship initiation. In both situations, the transaction parties are independent to each other. Their relationship is based on cooperation rather than coerce from one party to the other party. Thus, besides skill and qualifications, subjective attitude and value orientation are also important for the future relationship. Role Specification Role specification describes the manner in which decisions and functions are assigned to the parties in a relationship (Gill and Stern, 1969). In market governance, roles are related to discrete transactions (Kaufmann and Stern, 1988). In hierarchical governance, roles are specified by one party to others through an authority. In bilateral governance, role specification is more complex and more integrated with the exchange partners (Heide, 1994). For EDI adopters, roles need to be specified for a long-term relationship. Initiators take advantage of their dominating positions and control the role specification. Thus, at this index, EDI adopters are more likely in hierarchical governance. Internet technology users’ role specification is also for long-term. Compared with EDI adopters, they own more independence to each other. The role specification is done mainly through negotiation and cooperation. Planning Inter-firm planning is the process by which future contingencies and consequential duties and responsibilities in a relationship have been made explicitly (Macaulay, 1963). Under market governance, over time planning is implicitly deemed not to exist. The planning process in a hierarchical relationship is centralized and formalized contingency plans are developed (Cyert and March, 1963). Planning with bilateral governance is a decentralized activity and exhibits significantly lower levels of specificity and completeness. It is more like aids or frames of reference rather than strict specifications of duties. EDI initiators’ positions in planning are very strong. They make the plan. The followers usually have no choice but to accept it. For the EDI adopters, the planning process is centralized. EDI adopters are more likely in hierarchical governance at this index. For Internet technology users, no party has the capability to determine the planning process of the others. The planning process is relatively decentralized. Adjustment processes For market governance, the need for making ongoing adjustment is somewhat limited by default. Changes could easily incur transaction cancellation. Hierarchical governance explicitly provides the ability to make changes by designing specific devices through which changes are to be made. Adjustments under bilateral governance are mutual processes (Thompson, 1967). Both sides are prepared to show flexibility and negotiate adjustment when the environment changes. Basically, almost all EDI followers are strictly limited by the initiators to make any adjustment to the transaction. Thus, EDI adopters are more likely in hierarchical governance at this index. Internet technology users attempt to preserve a long-term relationship through changing environment. Thus, they usually need to experience significant adjustment. Because there is no relation dominator, adjustment can only be made through a mutual adaptive process. Without good cooperation and negotiation, no adjustment will be successful with them. Monitoring Procedures Monitoring could be accomplished either externally by measuring output and behavior or internally by aligning the incentives of decision

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40 2006 IRMA International Conference makers to lower the necessity of performance measurement (Eisenhardt, 1985). Market and hierarchical governance are based on external measurement but their focuses are respectively on measuring output and behavior (Anderson and Oliver, 1987). Bilateral governance finishes measurement through socialization processes that promote internal self-control. For EDI adopters, dominators mainly depend on the external index to measure the followers’ performance. Sometime, especially when followers can not meet the requirements, dominators need to watch the working status of EDI system, which is the carrier of the relationship with EDI, before they make the final evaluation of the followers. How to improve the cooperation is an important concern for EDI initiators. Among Internet technology users, there is no relationship dominator. Transaction parties depend more on socialization process to improve cooperation efficiency. Temporary performance fluctuation is not their primary concern. Incentive System For market governance, incentives are inherently short term in nature and are tied directly to the completion of a transaction (John and Weitz, 1989). For hierarchical governance, incentives are long term and based on observed behavior (Anderson and Oliver, 1987). For bilateral governance, incentives are less contingent on specific performance but more dependent on system-relevant attitudes and overt behavior (Ouchi, 1979). It is based on the displayed commitment and overt compliance to the system. EDI adopters and Internet technology users share some characteristics here. The first reason for both to enter a relationship is the pursuit for a series of transactions in a long term. Their decision to stay in or leave the relationship also depends on its long term performance and transaction parties’ attitudes. Means of Enforcement For market governance, enforcement is external to a given relationship through maintenance of competition (Walker and Weber, 1984) or offsetting investments in other relationships (Heide and John, 1988). Hierarchical enforcement is through legitimate authority based on employment relations or contractual arrangements. Bilateral governance focuses on the ongoing relationship itself: having established common values and taking the expectation of future interaction as incentives. Enforcement of hierarchical governance is by means of direct control. Those of market and bilateral governances rely on different incentive structure. The primary adoption reason for EDI followers is initiators’ pressure. Heide and John (1988) found that business parties having made specific investment tended to combine themselves closely to their partners to safeguard their investments. There is little common value between initiators and followers. Even now, the followers still have the right to withdraw from the relationship when they do not see any interests from it. Thus, at this index, EDI adopters are somewhere between hierarchical point and bilateral point. Internet technology users depend on incentives but not legitimate authority or external enforcement. Actually, there is not authority on e-marketplace. Transaction parties’ relationships are mainly based on common values and future benefit. There is almost no relationship enforcement on the transaction parties. Relationship Termination For market governance, when a transaction is over, the inter-firm relationship based on that transaction is over. For hierarchical governance, relationship commencement and termination usually are included into the inter-firm contract (Dwyer, Schurr and Oh, 1987) or, relationship duration need not be clarified but one party is capable of renegotiating or terminating the relationship (Brickley and Dark,

Table 1. Impact of EDI and B2B e-commerce Marketing No initiation process.

Hierarchy Based on selective entry processes.

Bilateral Based on selective entry processes. Even more stringent than hierarchy governance. EDI and E-commerce adopter

Role specification

Related discrete transactions and are defined only in terms of minimum level of duties required to complete the exchange.

Roles are specified by one party to others through an authority. EDI adopter

not only complex or multidimensional but also more integrated with the exchange partners. E-commerce adopter

Planning

Focuses on discrete transactions. No over time planning.

Centralized and formalized contingency plans, specifying categories of environmental events and corresponding procedures and contractual. EDI adopter

Decentralized and significantly lower levels of specificity and completeness. Be more like aids or frames of reference rather than strict specifications of duties. E-commerce adopter

Adjustment processes

Limited need for making ongoing adjustment. Changes could easily incur transaction cancellation.

Designing specific devices through which changes are to be made.

Mutual adjustment. Both sides are prepared to show flexibility and negotiate adjustment when the environment changes. E-commerce adopter

Monitoring Procedures

Based on the use of external measurement procedures

Based on the use of external measurement procedures.

Incentive System

Incentives are short term in nature and are tied directly to the completion of a transaction.

Incentives are long term and based on observed behavior.

Enforcement

External to a given relationship. Through the use of legal system, maintenance of competition or offsetting investments in other relationships.

Through legitimate authority based on employment relations or contractual arrangements.

Relationship Termination

Every transaction constitutes a completed event. When a transaction is over, it means that the inter-firm relationship based on that transaction is over.

Included in the inter-firm contract or, relationship duration need not be clarified but one party is capable of renegotiating or terminating the relationship. EDI adopter

Relationship Initiation

EDI adopter

EDI adopter

Through socialization processes that promote internal selfcontrol. EDI adoption, E-commerce adopter Incentives depend on systemrelevant attitudes and overt behavior. EDI adopter, E-commerce adopter Having established common values and taking the expectation of future interaction as incentives. E-commerce adopter Entirely open-ended relationships with infinite or foreseeable termination points.

E-commerce adopter

1987). Bilateral governance has entirely open-ended relationships with infinite or foreseeable termination points (Macneil, 1978). EDI initiators have the capability to renegotiate or terminate the relationship when they need while some time followers can not renegotiate at their will. For Internet technology users, there is infinite terminations point. Duration of a relationship is decided by business partners’ evaluation on their relationships and future benefit expectation. In summary, EDI adopters are more likely in the mode of bilateral governance in the areas of initiation and incentive. However, they tend to be in hierarchical governance in the areas of role specification, planning, adjustment, monitoring, enforcement, and termination. Internet based e-commerce users exhibit more characteristics of bilateral governance in almost all aspects. It means that Internet based ecommerce technology is more powerful than EDI in transforming interfirm relationship from market governance or hierarchical governance to bilateral governance (see Table 1).

A MODEL FOR INTER-FIRM RELATIONSHIPS TRANSFORMATION A model to illustrate and predict the inter-firm governance transformation is proposed below (Figure 1). Several observations can be made based on the above analyses: 1. 2.

3.

4.

Information technologies are changing inter-firm relationships. The general transformation trend is that the traditional hierarchical or market governances are converging into bilateral governance due to the adoption of EDI and Internet based B2B e-commerce technology. Different initial inter-firm relationships experience different transformation path. For example, some market relationships are being transformed by B2B e-commerce into bilateral relationships, while some bilateral relationships remain unchanged after the e-commerce adoption. Internet based B2B e-commerce technology plays a more significant role than EDI does in the transformation process.

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Emerging Trends and Challenges in IT Management Figure 1. A Model for inter-firm governance transformation Relationship before IT adoption

Relationship after IT adoption Hierarchical governance

Hierarchica governance

Sys adopter Bilateral governance

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For traditional inter-firm relationship, it is difficult to find out which specific conditions favor bilateral governance (Grover & Malhotra, 2003). That is why traditional transaction cost theory doesn’t identify bilateral governance. However, with B2B e-commerce, bilateral governance becomes popular. The primary advantage of bilateral governance is the concurrence of high integration and business parties’ independence. It means less coordination cost, less transaction risk, and less alternative cost.

Bilateral governance

Compared with EDI, Internet based B2B e-commerce technology has brought down both infrastructure cost and coordination cost for business to business transactions. This is why B2B e-commerce technology favors bilateral governance more than EDI does.

Market governance

CONCLUSION

Non-sys adopter Market governance

Non-IS

EDI

B2B E-commerce

The transaction cost theory can be extended to explain the transformation process. Clemons et al., (1993) defined transaction cost as the sum of coordination costs and transactions risk. Usually, low transaction costs favor market relationship. High transaction costs favor hierarchical relationship (Grover & Malhotra, 2003). Within this study, Clemons’ transaction cost is taken as direct transaction cost. Correspondingly, total transaction cost is the sum of direct transaction cost (as defined above) and alternative cost. Alternative cost refers to the cost for the reduction of direct transaction cost. It is assumed that all firms seek to reduce total transaction cost. For example, the reason why some firms choose vertical integration is that their potential direct transaction costs are over the sum of ownership burden (alternative cost) and actual direct transaction cost. For firms running in arm lengths’ relationship, the situation is opposite.

The adoption of EDI and Internet based B2B e-commerce technology is transforming inter-firm relationships — from traditional market governance and hierarchical governance to bilateral relationships. A model is proposed to show the transformation process. The impact of the technologies is examined in terms of relationship initiation, role specification, planning, monitoring, and incentive systems. The implications of the changing inter-firm relationships include adjustments in a firm’s planning and management processes. In some cases, business process re-engineering may be required to accommodate the changing inter-firm relationships. Future research in this area includes case studies and surveys to validate above theoretical analysis. This research presentation is partially supported by a grant from Wells Fargo. References are available upon request.

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42 2006 IRMA International Conference

Organizational Slack in the Global Information Technology Industry Perry Sadorsky, Schulich School of Business, York University, 4700 Keele Street, Toronto, Ontario, Canada M3J 1P3 T 416 736 5067, F 416 736 5687, [email protected]

ABSTRACT

THEORY AND HYPOTHESES

Non-deployed resources (like cash and marketable securities), or in some cases, deployed but easily recoverable, resources (like sales and administration expenses) are termed slack resources and become the basis for managerial discretion. This study examines the relationship between organizational slack and firm performance in the global information technology industry. Results from a structural equation model show that organizational slack has a negative and significant impact on growth and profit performance which supports the predictions of agency theory. Market performance, however, has no impact on organizational slack.

Greenley and Oktemgil (1998), page 378, present a nice intuitive definition of slack.

INTRODUCTION All viable businesses go through periods of time when profits are rising. Broadly speaking, increases in profits can be used to invest in resources to grow the business, paid out as dividends to the shareholders, or retained as financial capital available to the firm but not yet deployed. These nondeployed resources (like cash and marketable securities), or in some cases, deployed but easily recoverable, resources (like sales and administration expenses) are termed slack resources and become the basis for managerial discretion. On one hand, slack resources are desirable because they provide a financial cushion to buffer the company against unexpected changes in the business environment. In accumulating slack, firms forego short term business opportunities in favor of gaining competitive advantage in the future. This view of how organizational slack impacts firm business performance is grounded in organizational theory which argues that a firm is similar to a living entity and needs slack resources to grow and prosper in the face of dynamic and uncertain environments (March and Simon, 1958). On the other hand, these slack resources represent a source of inefficiency because these resources are not being put to their most productive use. Agency theory argues that slack resources create inefficiencies, reduce risk taking and lower overall business performance (Jensen and Meckling, 1976). Behavioral accounting researchers find support for agency theory in that managers often build slack into their budgets (Dunk and Nouri, 1998). This study examines the relationship between organizational slack and firm performance in the global information technology industry (defined broadly as large firms engaged in computer hardware, software and communications equipment with an international focus). An industry study is important because industry structure along with sustainable competitive advantage, are the two fundamental factors that determine business profitability (Porter, 1980, 2001). The global information technology industry provides an interesting back drop from which to study the impact of slack resources on firm performance because this is an industry that is often perceived as being short term focused, has gone through a recent period of enormous turmoil and the dominant companies in the industry have varying amounts of slack resources. Microsoft, for example, had over $49 billion dollars in cash and short term money market investments at the end of 2003 which was up from $38 billion the year before. By comparison, Cisco Systems had slightly over $8 billion dollars in cash and short term money market investments at the end of 2003 which was down from over $12 billion the year before.

Slack is that cushion of actual or potential resources that allows an organization to successfully adapt to change, by providing the means for adapting strategies to the external environment. The theory behind organizational slack is grounded in two competing schools of thought. Organizational theory posits the firm as a living organism interested in survival (Cyert and March, 1963, Thompson, 1967). In organizational theory slack is necessary for the long term survival of the firm (March and Simon, 1958). According to organizational theory slack performs four main functions (Tan and Peng, 2003). First, slack provides an inducement to organizational members (payments in excess of organizational costs). Second, slack provides resources for conflict resolution (every problems has a solution). Third, slack provides a buffer to protect the organization from a fast changing and volatile business environment. Fourth, slack allows the firm necessary resources to experience changes in strategy. Organizational theory recognizes that holding valuable resources idle does constitute a cost to a business but advocates the idea the benefits from slack outweigh the costs. Organizational theory suggests the following two hypotheses. • •

Hypothesis 1a: The relationship between organizational slack and growth performance is positive. Hypothesis 2a: The relationship between organizational slack and profit performance is positive.

In comparison, agency theory advances the idea that organizational slack is wasteful. In agency theory, the firm is a collection of contracts between principles and agents (Fama, 1980). Slack may be good for agents to pursue their own selfish goals, but slack is not good for the organization as a whole (Jensen and Meckling, 1976). Under agency theory, slack leads to inefficiencies, restricts risk taking and inhibits growth. Agency theory suggests the following two hypotheses. • •

Hypothesis 1b: The relationship between organizational slack and growth performance is negative. Hypothesis 2b: The relationship between organizational slack and profit performance is negative.

As is often the case in the strategic management literature, growth and profitability are often used either in isolation or in combination with one and other to measure firm performance (Varaiya, Kerin, and Weeks, 1987, Woo, Willard, and Daillenbach, 1992). More recently, Cho and Pucik (2005) have investigated the direct and indirect relationship between growth, profitability and shareholder value and found that both growth and profitability have mediating effects on market value. There results suggest the following hypotheses.

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Emerging Trends and Challenges in IT Management • •

Hypothesis 3: The relationship between growth performance and profit performance is positive. Hypothesis 4: The relationship between profit performance and market value is positive.

In addition to the relationships between slack and business performance, it is also useful to propose a feedback relationship between business performance and slack. In other words, where do the resources to create slack come from? Appealing to organizational theory, companies with strong business performance are more likely to have monies available to devote to organizational slack. Hence, the following hypothesis is put forward. •

Hypothesis 5: The relationship between market value and organizational slack is positive.

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Table 1. Correlations and descriptive statistics Correlations (N=75) 1 2 3 4 5 6 7 8 9 10

Absorbed slack Unabsorbed slack Immediate slack ROA ROE ROI Market to Book Sales Assets Market value mean St dev max min

1 1.00 0.56** 0.82** -0.34** -0.29* -0.28* -0.05 -0.12 -0.21 0.05 0.42 0.29 2.31 0.05

2

3

4

5

6

7

8

9

10

1.00 0.81** -0.15 -0.09 -0.06 0.01 -0.13 -0.07 -0.17 2.66 2.55 17.29 0.65

1.00 -0.31** -0.26* -0.23* -0.04 -0.22 -0.19 -0.05 1.43 1.07 8.74 0.41

1.00 0.88** 0.88** 0.26* 0.53** 0.73** 0.34** -0.07 0.36 0.21 -2.64

1.00 0.75** 0.20 0.50** 0.66** 0.29* -0.11 0.52 0.46 -3.11

1.00 0.34** 0.56** 0.73** 0.38** -0.11 0.52 0.34 -3.11

1.00 0.31** 0.29* 0.15 3.90 2.40 13.83 -0.30

1.00 0.69** 0.52** -2.10 15.08 27.26 -57.79

1.00 0.54** 1.29 13.41 30.45 -58.18

1.00 21726 47098 320755 4

** Correlation is significant at the 0.01 level (2-tailed). * Correlation is significant at the 0.05 level (2-tailed).

Figure 1 shows the hypothesized model of organizational slack, growth performance, profit performance, and market performance. The empirical evidence on the relationship between slack and firm performance is mixed. Singh (1986) studies 64 large Canadian and U.S. companies and finds that a high level of absorbed and unabsorbed slack is related to good financial performance. Bromiley (1991) studies 288 U.S. companies and finds that available and potential slack increase business performance. Miller and Leiblein (1996) U.S. firms in four different sample periods and find that slack increases firm performance. Greenley and Oktemgil (1998) study 134 U.K. firms and find a positive relationship between slack and firm performance for large firms but no relationship between slack and firm performance for small firms. In a sample of Chinese companies, Tan and Peng (2002) find that absorbed slack has little impact on firm performance while unabsorbed slack has a positive impact on firm performance.

DATA AND METHODS The list of companies used in this study comes from the iShares S&P Global Information Technology Sector which consists of large capitalization information technology companies and trades on the AMEX under the ticker symbol, IXN. Firms like Apple Computer, Cisco Systems, Corning, Dell Computers, EMC, Hewlett Packard, IBM, Intel, Lucent, Microsoft, Nortel Networks, Qualcomm, Sun Microsystems, Xerox and Yahoo are included in the list. Firm specific data measured in millions of dollars for the years 2001 – 2003 come from COMPUSTAT. Three year averages and growth rates were used in constructing the variables discussed below in order to avoid spurious effects from taking just one year of data. In total, 75 firms were included in the analysis. Many of the included companies were American, but some were European and Asian. Organizational slack was measured as a construct using the three year average value (2001 – 2003) of absorbed slack, unabsorbed slack and immediate slack (Cronbach’s alpha = 0.64). Constructs are useful when several different indicators correlate highly with each other and each proxies the same underlying concept. Absorbed slack refers to excess costs in organizations that are not easy to redistribute (Sharfman et al., 1988). Absorbed slack was measured as the ratio of selling, general, and administrative expenses to sales (Greve, 2003). Unabsorbed slack refers to current underemployed resources that could be redistributed elsewhere. Unabsorbed slack was measured by the ratio of quick assets (cash and marketable securities) to liabilities (Greve, 2003). Immediate slack was measured by the ratio of working capital to sales (Finkelstein and Hambrick, 1990). Initially, an additional organizational slack variable was included using the three year average value of absorbed slack squared, unabsorbed slack squared and immediate slack squared (Cronbach’s alpha = 0.45). This variable was meant to capture the curvilinear properties of slack that some author’s find (Tan and Peng, 2003) but later dropped from the analysis due to the low alpha value and poor construct validity. Growth performance was measured as a construct using annualized continuously compounded growth rates over the years 2001 - 2003 on

sales, assets and market value (market capitalization) (Cronbach’s alpha = 0.80) (Cho and Pucik, 2005). Following Cho and Pucik (2005), profit performance was measured as a construct using the three year average (2001 – 2003) value of return on assets (ROA), return on invested capital (ROI) and return on equity (ROE) (Cronbach’s alpha = 0.92). ROA and ROI have both been previously used to study profitability in the telecommunications industry (Bae and Gargiulo, 2004). Market performance was measured using the three year average value (2001 – 2003) of market to book ratio. The market to book ratio tends to be widely excepted and easily accessible measure to compute (Cho and Pucik, 2005). There are, of course, many other measures of market performance including Tobin’s Q and economic value added, but these measures were not tried in this study. A correlation matrix of the variables used in this study shows that a number of the variables within each construct are significantly correlated (Table 1). Also notice the wide variation (as measured by the mean, standard deviation, maximum and minimum) in slack measures illustrating the differences in slack resources even for firms in the same industry. A structural equation model (SEM) was used to test the hypotheses. An SEM is a particularly useful modeling technique to use with latent variables because SEM accounts for correlation among the latent variables and tests for convergent and discriminant validity. An SEM allows for measurement errors, residual errors, as well as reciprocal causality and simultaneity (Segars, 1997, Byrne, 2001). All estimation was performed using maximum likelihood estimation in the software package AMOS 5. A two step approach to structural equation modeling was used where in the first step the measurement model was estimated and tested and in the second step the structural equation was estimated and hypotheses tested (Anderson and Gerbing, 1988).

RESULTS The estimated measurement model was evaluated for convergent validity and discriminant validity. Each of the factor loadings was highly significant (Table 2). All of the standardized factor loadings were greater than 0.57 and two thirds of them were larger than 0.80. Composite factor reliability can be evaluated using internal consistency measures and average variance extracted (Fornell and Larcker 1981, Segars, 1997). Internal consistency values greater than 0.70 and average variance extracted larger than 0.50 are considered to be adequate to establish individual indicators and constructs. The lower panel of Table 2 shows that composite factor reliability is established for each construct. Discriminant validity is verified if a construct shares more variance with its own measures than with other constructs. For discriminant validity to be established, the correlation between two constructs must be less than the square root of the average variance extracted. Each construct demonstrated discriminant validity because the diagonal of the correlation matrix (right side of second panel in Table 2) has elements that are

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44 2006 IRMA International Conference Table 2. Results of the measurement model

Table 3. Structural equation model goodness of fit statistics

Measurement paths

Factor loadings

Slack Absorbed slack Unabsorbed slack Immediate slack

0.917*** 0.604*** 0.896***

Growth Sales Assets Market value

0.723*** 0.962*** 0.569***

CMIN(df) CMIN (p) IFI TLI CFI RMSEA (low, high) a 43.03(30) 0.06 0.98 0.96 0.98 0.08 (0.00, 0.12) a For RMSEA, low and high denote the lower and upper bound for a 90% confidence interval.

Profits ROA 0.995*** ROE 0.882*** ROI 0.888*** Standardized loadings shown *** p < 0.001

Latent variables

Internal consistency

Average variance extracted

Correlations between latent variables

Slack Growth Profits Slack 0.855 0.670 0.818 -0.234 0.769 Growth 0.805 0.591 Profits 0.945 0.852 -0.372 0.756 0.923 Diagonal elements in the correlation matrix are square roots of average variance extracted.

greater than the off diagonal elements in the corresponding rows and columns. Having established the measurement model satisfies both convergent and discriminant validity, the next step was to estimate and test the structural equation model. Model fit was assessed using CMIN (minimum discrepancy) to test the equality between the unrestricted sample covariance matrix and the restricted covariance matrix. Higher probability values are indicative of a closer fit between the hypothesized model and the perfect fit model. Because CMIN is very sensitive to sample size, it was assessed in combination with other statistics (Byrne, 2001). The Incremental Fit Index (IFI), Tucker-Lewis Index (TLI) and Comparative Fit Index (CFI) range between 0 and 1, with values greater than 0.90 indicating an acceptable fitting model (Bentler and Bonett, 1980; Hu and Bentler, 1998). Smaller values of the root mean squared error of approximation (RMSEA) indicate a better fit to the data (Byrne, 2001). More specifically, RMSEA values below 0.08 indicate a reasonable fit, whereas values below 0.05 suggest a good data fit. The results reported in Table 3 show that the estimated SEM fits well. In addition the stability index for the recursive model was 0.061 which is less than the 1.0 for an admissible solution. As a further check on model missspecification, the standardized residuals were examined. None of the standardized residuals were larger then 1.96 in absolute value whereby indicating no evidence of model miss-specification. Turning now to the results from the structural equation model hypotheses tests (Table 4), the relationship between slack and growth performance is negative and significant which supports Hypothesis 1b. It is also the case that the relationship between slack and profit performance is

negative and significant which supports Hypothesis 2b. Hypotheses 1b and 2b are each supported at a high level of significance which points to the usefulness of agency theory in understanding the relationship between organizational slack and firm performance. Hypotheses 1a and 2a which pertain to the organizational theory of slack are rejected. As expected, growth performance is positively related to profit performance and Hypothesis 3 is supported at a high level of significance. The relationship between profit performance and market performance is positive and significant, confirming support of Hypothesis 4. No support was found for Hypothesis 5 which posits a positive relationship between market performance and slack. A possible explanation for this is that companies with strong business performance are more likely to be operating efficiently and thus less likely to have funds to devote to accumulating slack resources.

DISCUSSION AND CONCLUSIONS The major contribution of this paper is to propose a theoretical model of the firm linking organizational slack with overall business performance (incorporating growth, profits and stock market valuation) and estimating such a model using data from the global information technology industry. Results from a structural equation model reveal that organizational slack has a negative and significant impact on growth and profit performance which supports the predictions from agency theory. Market performance, however, has no impact on organizational slack. One important managerial implication is that global information technology companies should avoid accumulating slack because slack correlates negatively with both growth performance and profit performance. Investors looking for investment opportunities or managers looking to form joint ventures should be wary of companies with too much slack as it dampens business performance. There is still concern by some technology and innovation management observers that too much money is being spent on IT related projects (Gianforte, 2005). Reducing slack resources would pressure IT suppliers and IT customers to become more effective and efficient in their use of IT. Increased efficiency and the resulting positive impact on productivity could only lead to increased business performance. This paper does have a number of limitations that need to be pointed out. One important limitation is that the data set consists of 75 firms which is a relatively small number of observations for the structural equation modeling technique which is a large sample methodology. Conceptually, the global information technology industry tends to be dominated by a small number of very large companies. Empirically, every attempt was made to check for model miss-specification and none

Figure 1. The hypothesized model of organizational slack, growth performance, profit performance, and market performance Table 4. Results of structural equation model hypotheses tests Structural paths

Slack to growth

Slack to profits

Hypothesis

H1a,b

Structural estimates

-0.245

slack

Outcome p value

0.064

H2a,b

-0.212

0.016

Growth to profits

H3

0.713



Use MDOISW Approach to Integrate Two Example Domain Ontologies Suppose the animal domain ontology ando_a defined in section 5.1 can be identified by uri_a, another animal domain ontology ando_b can be identified by uri_b. In ando_b, RobertAdam is MalePerson, MalePerson is Human, encode ando_b in OWL Lite & SWRL:

< MalePerson rdf:ID=”RobertAdam”/>









< owl:Class rdf:resource=”#Person”/> < owl:Class rdf:resource=”#Female”/>







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58 2006 IRMA International Conference

5.



Encode ando_b in description logic: MalePerson(RobertAdam) MalePerson(x)’!Human(x) Now we have two domain ontologies, suppose the reality is: RobertAdam in ando_b is Adam in ando_a, MalePerson in ando_b is Man in ando_a, and Human in ando_b is Person in ando_a. We can’t know “uri_a#Adam is man” if we only use ando_a to reason; we can’t know “uri_b#RobertAdam is 13 years old” if we only use ando_b to reason. So we need to integrate ando_a and ando_b, then we can solve problems that need the support of integration of ando_a and ando_b. In the next, MDOISW approach is used to integrate ando_a and ando_b. 1 Construct IBK Create uri_IBK to locate IBK for the integration of ando_a and ando_b; in IBK, uri_a#Man, uri_a#Adam, uri_a#Person, uri_b#MalePerson, uri_b#RobertAdam, uri_b#Human are quoted and defined, and we can encode IBK in OWL Lite:

Minimal ontological commitment: An ontology should require the minimal ontological commitment sufficient to support the intended knowledge sharing activities.

Ontology integration is introduced detailedly in [13]. The definitions of ontology mapping, ontology alignment, ontology articulation, ontology merging, ontology translation and ontology integration are distinguished. Though the name of the paper is “ontology mapping…”, ontology integration is the main focus of that paper based on the definition of ontology integration given in that paper. Present research works about ontology integration don’t fit for using on the Semantic Web, such a large distributed environment. The essential reason is that inference efficiency is unsatisfiable in those works, as those works don’t choose a suitable formal ontology language; so we have no effective way to check consistency after ontology integration. In [14], based on experience of using ontology-editing environments such as Protégé-2000, Ontolingua and Chimaera, an ontology-development methodology for declarative frame-based systems is described. The steps in the ontology-development process are listed; the complex issues of defining class hierarchies and properties of classes and instances are addressed. In [15], Mike Uschold and Michael Gruninger propose an informal approach to developing ontology, which includes the following steps: identify purpose and scope, ontology capture, ontology coding, integrating existing ontologies, evaluation, documentation. Then a more rigorous approach to the development of ontologies is considered, and the role of formal languages in the specification, implementation, and evaluation of ontologies is discussed. These works are valuable references for the research in our paper.





Encode IBK in description logic: Mana”MalePerson Persona”Human Adam=RobertAdam 2 Check consistency By using Vampire, check consistency for integration of ando_a and ando_b; the result shows that the integration is consistent. 3 Call suitable reasoners to reason for solving problem According to the integration of ando_a and ando_b, we can use Vampire to make inference for solving problem. For example, we can inquire of the reasoner about a question, such as “is Man(Adam) true?” The reasoner will give a positive answer. This solves problem that can’t answered by using ando_a only.

CONCLUSION To make the web contents understandable to machine and suitable for inference, we need to establish ontology and use terms defined in ontology as metadata to annotate the web contents. In practical application, domain ontology or the integration of several domain ontologies is needed. In this paper, we propose DORRSW approach and MDOISW approach to represent domain ontology, integrate multiple domain ontologies and make inference for consistency check and problem solving. The application examples prove the effectiveness of these two approaches. From these discussions, the basic situations of domain ontology representation, reasoning and integration for the Semantic Web are clarified, so the basic knowledge of developing ontology for the Semantic Web is provided.

ACKNOWLEDGEMENT Supported by the National Natural Science Foundation of China under Grant No.60172012 and the Natural Science Foundation of HuNan Province under Grant No.03JJY3110.

REFERENCES [1] [2]

RELATED WORKS In [6], five design criteria for ontologies are proposed to guide and evaluate the design. We present them as follows:

[3]

1.

[4]

2. 3. 4.

Clarity: An ontology should effectively communicate the intended meaning of defined terms. Coherence: An ontology should be coherent: that is, it should sanction inferences that are consistent with the definitions. Extendibility: An ontology should be designed to anticipate the uses of the shared vocabulary. Minimal encoding bias: The conceptualization should be specified at the knowledge level without depending on a particular symbol-level encoding.

[5] [6]

Tim Berners-Lee. Weaving the Web. Harper, San Francisco, 1999. Tim Berners-Lee, James Hendler, Ora Lassila. The Semantic Web. Scientific American, May 2001. Nils J.Nilsson. Artificial Intelligence: A New Synthesis. China Machine Press & Morgan Kaufmann Publishers, Beijing, 1999, 215-316. Stuart Russell and Peter Norvig. Artificial Intelligence: A Modern Approach. Pearson0Education North Asia Limited and People’s Posts & Telecommunications Press, Beijing, 2002, 221-226. T. R. Gruber. A translation approach to portable ontologies. Knowledge Acquisition, 1993, 5(2), 199-220. T. R. Gruber. Towards principles for the design of ontologies used for knowledge sharing. International Journal of Human-Computer Studies, 1995, 907-928.

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Emerging Trends and Challenges in IT Management [7]

[8] [9]

[10]

[11]

Ian Horrocks, Peter F. Patel-Schneider, and Frank van Harmelen. From SHIQ and RDF to OWL: The making of a web ontology language. Journal of Web Semantics, 2003, 1(1), 7-26. Mike Dean and Guus Schreiber. OWL Web Ontology Language Reference. http://www.w3.org/TR/owl-ref/, 2004. Franz Baader, etc. The Description Logic Handbook: Theory, Implementation and Applications. Cambridge Univ. Press, Cambridge, UK, 2003, 1-100, 436-459. Ian Horrocks and Peter F. Patel-Schneider. Reducing OWL entailment to description logic satisfiability. Proceedings of the 2003 International Semantic Web Conference, Springer, Florida, USA, 2003, 17-29. Ian Horrocks, etc. SWRL: A Semantic Web Rule Language Combining OWL and RuleML, http://www.w3.org/Submission/ 2004/SUBM-SWRL-20040521/.

[12]

[13]

[14]

[15]

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Dmitry Tsarkov, etc. Using Vampire to Reason with OWL. Proc. of the 2004 International Semantic Web Conference, Springer, 2004, 471-485. Yannis Kalfoglou, Marco Schorlemmer. Ontology mapping: the state of the art. The Knowledge Engineering Review, 18(1), 2003, 1-31. N. Noy and D. L. McGuinness. Ontology development 101: A guide to creating your first ontology. Technical Report KSL-0105 and SMI-2001-0880, Stanford Knowledge Systems Laboratory and Stanford Medical Informatics, March 2001. Mike Uschold and Michael Gruninger. Ontologies: Principles, methods, and applications. Knowledge Engineering Review 11, (2), 1996, 93-155.

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60 2006 IRMA International Conference

A Comparison of Quality Issues for Data, Information, and Knowledge Elizabeth Pierce, Dept of MIS & Decision Sciences, The Eberly College of Business and Information Technology, Indiana University of Pennsylvania, 664 Pratt Dr, Rm 203, Indiana, PA 15705-1087, P (724) 357-5773, F (724) 357-4831, [email protected] Beverly Kahn, Information Systems & Operations Management Department, Sawyer School of Management, Suffolk University, 8 Ashburton Place, Boston, MA 02108, P (617) 573-8642, F (617) 994-4228, [email protected] Helinä Melkas, Helsinki University of Technology, Lahti Centre, Saimaankatu 11, FI-15140 Lahti, Finland P +358 3 525 0285, F +358 3 525 0204, [email protected]}

ABSTRACT Most agree that although related, data, information and knowledge differ from each other. Given this distinction, it is logical to ask if there is also variation in how quality is defined, measured, and improved for these three concepts. In this paper, the definitions for data, information, and knowledge are compared and their quality characteristics are explored.

INTRODUCTION Ask a manager whether he would like an additional data set, another report, or more knowledge about his business; it is safe to say that most managers would choose more knowledge. Even if the data set or report were of excellent quality and the knowledge less so, one might imagine that most managers would still choose knowledge. There is an implied hierarchy between data, information, and knowledge with knowledge being perceived by many as the most desirable. If indeed knowledge is the ultimate product produced by an organization’s systems then it is important to understand the relationship between these three concepts and how the quality of one affects the others. To begin, consider the differences in how people describe data, information, and knowledge.

BACKGROUND Most scholars ([1], [2], [3], [4], [7], [8], [12], [13]) refer to a datum as the most basic descriptive element. Whether it is symbolized as a number, text, or figure, a datum essentially represents a perception or measurement about some object of interest. By itself, a datum’s value typically lacks content, meaning, or intent. Data is the plural of datum and its usage is more common because for the most part, organizations work with collections of datum. For example, consider the kinds of datum that are used to describe a customer sales order. Individual datum like the customer’s name, the item’s description, the quantity sold, and the price are grouped together to form data. Data are often organized as a record, i.e., a set of attributes whose values describe some entity or event. Each attribute’s value can be considered a datum that describes some observation to be retained about the sale to that customer. Although some use the term data interchangeably with information, others consider information to be more than just data. They view information as the output of some process that interprets and manipulates data into some prescribed format ([1], [2], [3], [4], [7], [8], [12], [13]). Some authors prefer to use the phrase, information product, which is identified in terms of the raw, source data and semi-processed component data items required to manufacture it [17]. The expression, information product, emphasizes the idea that this item is determined by more than just its input data, but also by the procedures used to

construct it. Examples of information products include sales orders, packing lists, shipping labels, and customer invoices. Unfortunately not all information products are characterized by as much stability or simplicity in form or content as a shipping label. Some information products are more ad-hoc in nature. For instance, the results of queries are typically based on an assortment of data, presented in a variety of formats, generated on demand, and are typically used by only a few consumers. This type of information product is similar in nature to a one-of-a-kind manufactured product. Other information products are characterized by their complexity. Consider information products like data warehouses, hypertext documents, catalogs, and reference materials which may contain text, images, and audio objects. Such complex information products are often custom-made by a few people and then disseminated to a large audience. These complicated information products are particularly vulnerable to quality issues regarding their reliability, organization, content, accessibility, and presentation. Finally, while some view knowledge as information that has been further enriched so its value, context, and meaning are enhanced; others consider knowledge as being intrinsically different from either data or information products ([1], [2], [3], [4], [7], [8], [12], [13]). The idea that knowledge is more than information stems from the notion that knowledge is more process than product. The knowledge process occurs when an individual mentally synthesizes together an assortment of inputs: information, experiences, beliefs, relationships, and techniques to determine what a specific situation means and how to handle it [1]. For example, if the Marketing Vice President wants to devise next year’s sales strategy, he cannot solely rely on viewing information products like the end of year sales report or consumer market survey to acquire this understanding. Using his own internal reasoning, he must combine his assessment of these information products with his other accumulated experiences to come up with a plan for how to act. To make better use of the knowledge that will benefit their employees, processes, products, and performance, many companies are seeking to improve their Knowledge Management Systems (KMS). A KMS is not a computer system; rather it is a way of doing business that promotes knowledge management. Firms interested in improving their ability to discover, capture, share and apply knowledge must implement a variety of organizational means and technologies. Organizational means include such practices as collaborative creation of documents, face-toface meetings, on-the-job training, rotation of employees across departments, and corporate retreats. Technologies that enhance knowledge management include database management systems, video-conferencing, e-mail, groupware, and web portals. To be successful in knowledge discovery, capturing, sharing, and application, both the organizational means and the technologies employed must be compatible with the

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Emerging Trends and Challenges in IT Management underlying organization’s culture, structure, information technology (IT) infrastructure, common knowledge base, and physical environment. In particular, it is through the IT infrastructure which includes data processing, storage, communication technologies, and computer systems that data and information products are linked to the people and their actions for creating, storing, distributing, and exploiting knowledge of all types within an organization. Failure to understand this connection between the IT architecture’s information systems and a company’s ability to manage knowledge can lead to practical difficulties in organizations such as poor information sharing between different functional areas [14]. To avoid these problems, companies should identify as part of their system’s requirements, the kinds of knowledge needed to conduct day-to-day operations and to make decisions. Because some aspect of this knowledge must be conveyed and stored in a physical format, this necessitates the design and development of information products. Only when the design criteria for information products are well understood can an organization proceed to make sound decision about how to model, represent, and process the raw data upon which the information products will be based. Once the IT infrastructure’s systems are constructed and operational, data from the transactional processing systems are funneled into the management information systems which in turn help to support the organization’s KMS. Thus, while the design of systems and processes seem to be knowledge-driven, the operations of the systems appear to be data-driven. Given this interrelationship, the main thrust of the remainder of this paper will be to compare how quality dimensions, measurements, and methods for improvement compare between data, information products, and knowledge.

COMPARING DATA, INFORMATION, AND KNOWLEDGE QUALITY Quality Dimensions Most scholars agree that data quality is multidimensional in nature (Table 1: [10], [15], [16]). Although not always explicitly stated in the literature, it seems reasonable that one can apply these dimensions to data, information products or knowledge and their general meanings continue to apply. Quality Measurement Although the meanings of the quality dimensions are similar for data, information products, and knowledge, they differ in their measurability. Consider the quality dimension of completeness. Completeness refers to the extent to which something is not missing and is of sufficient breadth and depth for the task at hand. Completeness can be measured using subjective perceptions supplied by the consumer or by using quantifiable, objective measures which may either be task dependent or independent. Table 2 illustrates that it is relatively easy to derive objective, task independent completeness measures for data. Even if domain experts are needed to help ascertain whether the data’s schema or population is sufficiently complete to satisfy the requirements of a particular application, it is still fairly straight forward to derive objective, task dependent completeness measures. This occurs because data records are structured and well defined. The same data record is also Table 1. Summary of quality dimensions for data, information products, and knowledge Quality Category Quality of Values Collected (Also known as Intrinsic Quality) Quality of Application (Also known as Contextual Quality) Quality of Presentation and Storage (Also known as Representational Quality – Deals with Format and Definition) Quality of Accessibility via System Quality of System Support Services

Dimensions Associated with this Category Accuracy, Objectivity, Believability, Source Reputation, Completeness, Unambiguous, Meaningfulness, Currency Value-added, Relevancy, Timeliness, Comprehensiveness, Appropriate Amount, Appropriate Use, Proficiency in Use Ease of Interpretation, Ease of Understanding, Representational Consistency, Concise Representation, Appropriate Precision/Granularity, Good Organization/Structure/Definition Availability, Diffusion, Ease and Speed of Retrieval, Ease of Manipulation, Security, Privacy Feedback, Measurement, Improvement Track Record, Help Services, Ability to Handle Special Requests, Architecture, Portability, Commitment to Quality Policy

61

Table 2. Completeness measures for data, information product, and knowledge Metric Types Objective, Task Independent Measure

Objective, Task Dependent Measure

Examples of Quality Metrics for Completeness Dimension Data Record Information Product Knowledge -knowledge area – - Single Record -Single IP – Codification: How complete is Within a record, how many Within an IP, the proportion the definition and structure of of values which are present attributes contain values. the knowledge be it explicit, and accounted for. tacit, or some other type such as - Group of Records - Group of IP’s self-transcending. Proportion of records that Proportion of IP’s that contain all their values. contain all their values. Proportion of records that contains a value for a given attribute. Of the total cells contained in a table, the proportion that contains values. - Single Record Number of attributes missing from the record. - Group of Records Number of records that are missing from the data set. Number of attributes whose domain of values are incomplete.

-Single IP – Within an IP, are there any values that are partially incomplete? (e.g. missing items from a list or an incomplete sum) An IP’s design lacks certain pieces of information required by the task. - Group of IP’s Number of IP’s missing from a group.

Subjective Measure

Is this data record sufficiently complete for the task at hand?

Is this information product sufficiently complete for your needs?

- knowledge area Proficiency: How complete is the depth and comprehension of knowledge. Diffusion: How complete is the distribution and networking of knowledge capabilities across relevant stakeholders Value: How complete is the impact associated with the knowledge’s contribution to employees, processes, products, and performance. Do you have the knowledge you need to analyze this situation?

probably used by many different functional areas (sales, shipping, billing, etc.) so that certain quality characteristics of the data record such as its completeness, consistency, accuracy, and currency can be measured consistently across applications that require it. Objective quality measurements can also be developed for information products. Their quality metrics tend to be more context specific than those of data. This is reasonable since many information products are developed specifically for use by a particular business functional area. Thus one might examine a group of information products like a stack of sales orders for the purpose of determining if any sales orders were omitted or if the sales order design itself addresses all the information needs of the marketing group. Information products also tend to have more processing associated with their creation than data. This occurs because an information product builds upon the prior processing used to collect and store the raw data by adding additional steps that convert the raw data into a specified form. Hence, one might also wish to develop quality metrics that examine how complete were the data inputs and activities employed during each stage of an information product’s construction. Because knowledge is essentially the result of a process by which a variety of inputs are combined together by someone who wishes to determine what a specific situation means and how to handle it, it can be a challenge to find objective, application independent quality metrics for knowledge. One possible measure in this area is to identify the degree to which the knowledge can be made explicit or codified. This could be recorded on a scale ranging from gut feelings and mind models on the low end, then onto discussions, presentations, reports, followed by best practices and standards on the high end [5]. For certain types of knowledge, it is possible to obtain objective, task dependent quality measures, especially in the case of explicit know-how or know-why knowledge. For example, completeness for explicit knowhow knowledge can be defined as whether all the steps in the process are described. In addition for an individual step, one can ask if all the necessary details were included. Note that the completeness of the “step knowledge” is dependent not only on the nature of the task but on the level of the user’s expertise. A novice may require more explicit knowledge than a journeyman who needs only a subset of this knowledge. Explicit knowledge plus the individual’s tacit knowledge form the complete set of knowledge proficiencies used to accomplish the step. Completeness of knowledge can also be evaluated from the perspective of its diffusion across the enterprise or in its impact on the work accomplished by the firm. These last points demonstrate that of the three concepts: data quality, information product quality, and knowledge quality that it is knowledge

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62 2006 IRMA International Conference quality that is most defined by both its context and by the individuals who must apply the knowledge within that context. This sentiment is echoed by the Knowledge Management Professional Society who state that the criteria used to evaluate knowledge should be based upon the standards and conditions unique to the individual or group seeking to validate the knowledge [6]. Thus knowledge quality needs to be measured and investigated from a more personal and task oriented point of view than either data quality or information product quality. As a consequence, subjective measures that inquire as to which parts of the knowledge process were sufficiently present may be the principle means by which to judge the different quality aspects of one’s knowledge for a given purpose. Quality Improvement Most researchers agree that improvement of data, information products, and knowledge depends on applying quality principles and practices to the processes that create, store, manage, and present them ([4], [9], [17], [18]). The manufacturing literature provides many examples of using a total quality management philosophy to raise the satisfaction levels for many different types of products and services. Within the data quality field, it has been demonstrated that these quality improvement tools and techniques can be successfully adapted to the special characteristics of data, information products, and knowledge which possess atypical quality dimensions like “believability” and exhibit a simultaneous, non-depleting, multi-use nature [18]. In terms of how the quality improvement effort differs between data, information products, and knowledge, several observations can be noted. Although the creation and management of data, information products, and knowledge all involve processes, the complexity of those processes increases as one moves from the production of data through the production of information products to the production of knowledge. As the complexity of the processes increases, so does the difficulty associated with the definition, measurement, analysis, and improvement of quality. In part, the growing complexity of the processes stems from the need for a greater number of “manufacturing” steps over a longer length of time. Another complicating factor is that data, information products, and knowledge follow a life cycle which can be characterized by four major stages: Creation, Growth, Maturity, and Decline [17]. In practice, the distinctions between these four stages may not be clear cut. For example in healthcare, an information product such as a patient’s medical file tends to change continuously during its different phases of utilization and it is not necessarily complete even at the very end of the process. This raises the concern that the quality measured at only one stage of the process may give an incomplete picture that does not guide improvement efforts sufficiently.

• • • •

While it is apparent that this paper asks more questions that it gives answers, it nonetheless serves the purpose of highlighting further research that must be done if organizations are to fully integrate their data, information products, and knowledge systems. What is needed now is a more comprehensive literature review, comparison, and framework of quality issues related to data, information products, and knowledge.

REFERENCES [1]

[2] [3]

[4] [5]

[6] [7] [8]

[9] [10] [11]

SUMMARY AND RECOMMENDATIONS FOR FUTURE RESEARCH Whether it is a routine task such as recording a sales order or a complex activity such as devising next year’s marketing campaign, organizations must ensure their employees have the knowledge they need to complete tasks and make appropriate decisions. Making sure this knowledge is adequately developed, captured, shared, and used is the goal of the KMS which among its many facets includes the IT infrastructure where one finds the systems used to collect, manipulate, and store data records and information products. Improving the quality of knowledge requires a holistic approach to the entire knowledge management process which includes an understanding of the role that quality improvements in data records and information products can play. To better this understanding, more research is needed to address the following questions. •

•

Should organizations concentrate on measuring quality separately within the various systems that manage data, information products, and knowledge or should organizations concentrate on obtaining quality measurements at the boundary points where these systems interact? How best to define and capture quality measures for data, information products, and knowledge?

How do quality assurance costs for the data, information products, and knowledge compare? How do legal issues between data quality, information product quality, and knowledge quality compare? How do quality policy and personnel issues compare between data, information product, and knowledge quality? Sarbanes-Oxley and Health Insurance Portability and Accountability Act have legal requirements for the privacy and security of data. This has also been applied to some information products. Can these be extended to knowledge as well?

[12] [13] [14]

[15]

[16]

[17]

[18]

Becerra-Fernandez, I.; Gonzalez A.; and Sabherwal, R. Knowledge Management: Challenges, Solutions, and Technologies. Prentice Hall, Upper Saddle River, NJ, 2004. Davenport, T. Information Ecology: Mastering the Information and Knowledge Environment. Oxford University Press, New York, NY, 1997. Earl, J.J. “Knowledge as Strategy: Reflections on Skandia International and Shorko Films.” In C. Ciborra and T. Jelassi (Eds.), Strategic Information Systems: A European Perspective,. John Wiley & Sons, Chichester, UK, 1994, pp. 53-69. English, L. P. Improving Data Warehouse and Business Information Quality. John Wiley & Sons, New York, NY, 1999. Hofer-Alfeis, J. http://www.i-know.at/previous/i-know04/presentations/Hofer-Alfeis_authorized. pdf. Published in 2004, Accessed on June 28, 2005. Knowledge Management Profession al Society. http:// kmpro.org,, Accessed on June 28, 2005. Lillrank, P. “The Quality of Information.” International Journal of Quality & Reliability Management, 20 (6), 2003, pp.691-703. Miller, B.; Malloy, M. A.; Masek, E.; and Wild, C. “Towards a framework for managing the information environment.” Information and Knowledge Systems Management, 2, 2001, 359–384. Redman, T. Data Quality for the Information Age. Artech House, Boston, MA, 1996. Redman, T. Data Quality: The Field Guide. ButterworthHeinemann, Boston, MA, 2001. p. 74. Scharmer, C. O. “Self-transcending knowledge: Organizing around emerging realities.” in Nonaka, I., Teece, D. (eds.), Managing industrial knowledge: Creation, transfer and utilization, Sage Publications, London, 2001, pp. 68–90. Spek, R.v.d., and Spijkervet, A. Knowledge Management: Dealing Intelligently with Knowledge. Ultrecht: Kenniscentrum CIBIT, 1997. Tuomi, I., “Data is More than Knowledge.” Journal of Management Information Systems, 16 (3) , Winter 1999-2000, pp. 103-117. Uotila, T.; Melkas, H. “Book review – Ikujiro Nonaka and David Teece (eds.): Managing industrial knowledge. Creation, transfer and utilization.” Knowledge and Process Management, 10(4), 2003, pp. 277-281. Wand, Y., and Wang, R. Y. “Anchoring Data Quality Dimensions in Ontological Foundations.” Communications of the ACM, 39 (11), 1996, pp. 86-95. Wang, R. Y. and Strong, D. M. “Beyond Accuracy: What Data Quality Means to Data Consumers.” Journal of Management Information Systems, 12 (4), 1996, pp. 5-34. Wang, R. Y., Lee, Y., Pipino, L. and Strong, D. “Manage Your Information as a Product.” Sloan Management Review, 39(4), Summer 1998, pp. 95-105. Wang, R. Y. “A Product Perspective on Total Data Quality Management,” Communications of the ACM, 41 (2), 1998, pp. 58-65.

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Emerging Trends and Challenges in IT Management

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Amount and Utility of Information Values: Two Cases of the Most Misunderstood Quality Attributes Zbigniew J. Gackowski, California State University Stanislaus, College of Business Administration, Dept of Computer Information Systems, 801 W Monte Vista Avenue, Turlock, CA 95382, P 209-667-3275, F 209-667-3237, [email protected]

ABSTRACT This is a comparative technology-independent case approach to theorybased views of operations quality requirements for data and information values. Two contrasting cases illustrate the intricate relationship between the amount of information as defined by Shannon and Weaver and the utility value of information as defined by Kofler. Simple examples illustrate the role of quantity and utility value of information in decision-making within business environments. They are discussed by referring to the ontological, evolutional, and teleological frameworks proposed for assessing operations quality of data/information values.

INTRODUCTION This is a contribution to the discussions on different approaches to quality of data and information values. Liu and Chi (2005) categorized different approaches as intuitive, empirical, and theoretical. Initially, the intuitive, and the empirical approaches dominated, but they lack theoretical foundations on how DQ/IQ attributes are defined and grouped. This is a comparative technology-independent case approach to theory-based views of the quality of data and information values. The presented cases stay exclusively within the theoretical approaches that yield results of a more lasting validity. They derive attributes of information quality from established theories. Two cases illustrate and discuss the controversial amount of information as defined by Shannon and Weaver (1949) and the utility value of information as defined by Kofler (1968). Other dimensions of data/information quality are discussed as needed by the context by referring to three proposed theoretical frameworks: the ontological approach limited to the some intrinsic quality dimensions defined by Wand and Wang (1996), the evolutional theory-specific approach defined by Liu and Chie (2002), and the teleological operations research-based and content-focused approach as proposed by Gackowski (2005b).

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The main contributions of this paper are: •

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A demonstration of the advantages of the theoretical approaches to identifying the major data/information quality requirements Presentation of theory-specific approaches to quality by using two contrasting cases when: • The amount of information is important in defining its utility or payoff, and when • A huge utility value or payoff hinges upon only one bit of the amount of information A comparative discussion of other related quality dimensions as needed.

OVERVIEW OF SOME THEORY-BASED VIEWS OF QUALITY 1.

In 1949, within the mathematical theory of communications1, Shannon and Weaver (1947) defined the amount of

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information AI transmitted as a function of its probability pI that is: A I = -log 2 p I. The formula yields a number that indicates the rarity or the surprise effect associated with an object, event, or state represented by the received signal or value. Other attributes of information encoding can be derived from this one such as encoding capacity of communication channels or data fields, absolute and relative information encoding efficiency, absolute and relative redundancy, etc. It enables calculation of cost effectiveness of storing and processing of data and information. Two decades later, Mazur (1970) developed a generalized qualitative communication theory that does not require the assumption of probabilities and yields the same results, thus providing the ultimate proof of its validity. (In science, use of probabilities indicates that the internal mechanics of the phenomenon is not yet fully known.) How abstract the definition of the amount of information may sound, it plays a direct role in news services and news media2 such as press, radio, and TV. In 1968, in information economics, Kofler (1968) defined the utility of an information value as the difference between the utility value of results of operations while acting with and without it. The assumption is that decision-makers, while making decisions and acting accordingly, use some data D known to them. An incoming piece of information I may change the decision situation from what they know. The change is represented by the transition from state D to state D + I. Then, the utility value of an information value V(I)3 or its impact on business results is the difference between the utility value of results VR of business operations while acting with VR(D + I) and without it V R(D). It can be calculated only under the assumption that the results of business operations can be assessed, not necessarily in monetary units. The same formula covers the utility value of a lost piece of previously available data value that significantly impacts the outcomes. From this definition, other related attributes can be derived such as its procurement cost, net utility value, and its simple and expected cost effectiveness. Most authors of MIS textbooks do not pay attention to these attributes or pay lip service only. It amazes that Alter (2002, p. 162) ironically describes this pragmatic definition of utility of information value as “more elegant than practical.” Utility value of any data or information value should be considered from either side of the supply chain – the providers and the consumer. The benefits for both sides are equally important for lasting business relations. One should not overlook, however, that the provider of information is always in a stronger position than the consumers, hence, the latter may deserve more protection, although their perspective are not necessarily more important or critical. In 1996, based on ontological foundations, Wand and Wang (1996) defined four data quality dimensions (complete, unambiguous, meaningful, and correct) intrinsic to the design and

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operations of information systems. They were derived by analyzing the requirements for faithful mapping of states of the real world into the states of information systems. Within the confines of the assumptions used4, “those attributes have crystal-clear definitions and theoretically sound justification, but they constitute only a small subset of known attributes leaving the rest unspecified” (Liu and Chie, 2002). They are preconditions of accurate representation of reality, hence preconditions of accuracy and precision of data values, which again are contributing factors of credibility of data or information values. The defined quality dimensions were clearly explained as derived from deficiencies in the design and operations of information systems. There is, however a problem associated with this excellent contributions. They were clearly defined as intrinsic to the design and operations of information systems, but later mislabeled as intrinsic data quality dimensions. They are continuously cited and accepted as such. In 2002, in an evolutional and theory-specific approach to data quality, Liu and Chi (2002) try to overcome the weaknesses of the product analogy used in empirical studies of DQ/IQ and the narrowness of the ontological approach limited only to a few quality dimensions intrinsic to system design and operations. The authors claim that data have meaning only through a theory. As data evolve through the stages of the data evolution life cycle (DELC), they undergo a sequence of transformations and exist independently as different morphons (captured data; organized data, presented data, and utilized data). Each transformation introduces independent errors such as measurement errors during data collection, data entry errors during data organization, interpretation biases in data presentation. Different theories apply to different stages of the DELC; hence, different definitions to measure the quality of those morphons are needed. Instead of a single universal concept of data quality, four hierarchical quality views are used for data collection, organization, presentation, and application. In 2005, anchoring the concept of data/information quality in operations research, management science, and decision science, Gackowski (2005b) proposed a theoretical technology-independent teleological operations-based and contentfocused framework of operations quality of data and information values. This approach makes possible the definition of: A universal taxonomy of the entire universe of quality requirements for data and information values by the type of their impact on operations into direct and indirect ones, the direct into primary and secondary ones, and the primary into universal ones and task-specific ones Sufficient conditions for defining task-specific usability of single data/information values and for task-specific effective operational completeness of sets of usable data and information values with a clear distinction of only effective and four additional mandatory requirements for also economically effective completeness An economical examination sequence of the direct primary universal quality requirements Presently seven universal principles governing all operations quality requirements.

CASES WITH SELECTED THEORY-BASED ATTRIBUTES OF QUALITY Some Basic Terminology In discussing the theory-based attributes of data/information values, one must make a rigorous distinction between data and information values that in other situations might not be required. Here, this distinction is made within the context of decision situations. Decision makers and acting agents already know some aspects of the situation, but other may yet remain unknown to them. Within this paper, data5 values represent aspects of reality that are known, given, or assumed true. Reality

encompasses business organizations and their environments. Within reality, one distinguishes entities, which are objects or events represented symbolically by their identifiers and values of their attributes. Information values represent things, events, and unknown states that are yet to be acquired, which change the decision situations per se, and/ or the actions that implement the decisions, and/or the results of operations. From the viewpoint of the theory of communications, any representation of something known contains or conveys zero (0) bits of the amount of information – the low extreme of Shannon’s equation. Shannon’s formula of the amount of information AI = -log2 p I associates AI bits of information with any symbolic representation of reality that is yet unknown as a function of its probability p I. The amount of information measures the rarity or the surprise effect associated with the object, event, or state. Thus, at the other extreme, symbolic representations of objects, events, or states, which are very unlikely, with probability pI close to zero, is associated with nearly an infinite amount of information for their recipients. (AI = -log2 0 = - log2 (1/”) = log 2 •H•” [bits] – the high extreme of Shannon’s equation). Some in the field prefer “known information” vs. “unknown information” instead of data values and information values. In the light of the communications theory “known information” is a contradiction in adjective such as a solid liquid and as such unacceptable in rigorous parlance. In operations, explicit vs. tacit is considered universally only when testing interpretability of data and information values during their acquisition. In indirect informing, it is also a factor of presentation interpretability of values by their users. To them it may or may not be. Encoding does not imply explicit information. It may be encrypted. Under no circumstances, any amount of information should be considered useful; it may be or not. Within the model of operations quality, usability6 and usefulness7 of any data/information value are clearly defined. This approach to quality is simple, devoid of any lofty fuzzy considerations alien to decisively acting decision-makers in massive business, public administration, and military operations (Gackowski, 2005b). It is easier to grasp abstract concepts when examined within a broader context of their use. In operations: • • • • •

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Data values represent aspects of reality that are given, known, or assumed true. Information values represent aspects of reality that are unknown and must yet be obtained. Data and information values are disjoint sets of values (with no overlapping elements). Available data values never change operations; their usefulness has been already discounted. Any obtained information value, if of significant impact or relevance, always changes the operations situation qualitatively and quantitatively, and/or the necessary actions, and/or the results. All values of quality attributes of data and information values share the same multidimensional space, but differ substantially; usually they are at the opposing ends of their respective spectra. Data values are an important part of operations completeness, but they never increase it. An incoming information value, if only of significant impact and useable, always increases taskspecific operations completeness of data/information values.

MIS textbooks are confusing student minds with scientifically untenable definitions such, as “information is processed data.” No amount of highspeed data processing will yield information out of known values; it may derive another data value from available data values. This is a deterministic process, with no room for any uncertainty; hence no amount of corresponding information that always changes the corresponding decision situation. Data mining may yield information. Data mining, however, is not data processing but a one-time knowledge acquisition process of discovering new patterns in large data collections - a research result that to be interpreted by researchers not users. Discussions of operations quality of data and information values require a corresponding quality of the vocabulary used.

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Emerging Trends and Challenges in IT Management The following cases illustrate the theoretical aspects of the amount and the utility value associated with information values obtained from the outside world.

CASE 1 - AMOUNT OF INFORMATION AND OTHER IQ DIMENSIONS IN NEWS MEDIA This is a business case when a large amount of information translates into high utility value of an information value. Within communications theory, the amount of information is used mainly for calculating the capacity of communication channels and efficiency of encoding. However, it also measures an important aspect of news for news media. Generally, nothing known makes good news. It has to be extraordinary, rare, and unlikely for being considered interesting news. For the news media, the more unlikely an event is the more useful it is for the publisher. Reporting of rare events increases ratings, circulation, and visibility. It attracts high-paying advertisers. In addition, to rarity of events, the higher the general appeal of the subject for media consumers, the higher its utility value is. Its impact on business results of media may be very high. When information acquisition processes yield only values already known no one feels informed. They do not change the outcomes of business operations. Users received zero amount of information of zero utility value. There must be at least some amount of information to carry the utility value. Between the two, there is only a qualitative relationship, but no direct quantitative relationship. No trade-offs are possible either. The formulas that define the amount of information and the utility value of information are completely independent and derived from different sets of assumptions. No direct or intrinsic relationship between the two dimensions exists. The teleological view emphasizes the impact an information value makes on business results. In a news service, however, there are also other important universal direct primary quality requirements associated with a tangible utility value for publishers. Information values must also be operationally timely available with the exclusion of other competing actors; otherwise, they lose or substantially diminishes their utility value. Everybody agrees that availability of data or information is a serious issue. When economy matters, it must also be economically timely available. Inconsistent with the terminology of certified public accountants, several authors interpret timeliness as timely updated, as an aspect of information aging. “Currency” better conveys this meaning. Nevertheless, timely availability has at least three aspects. Therefore, one needs to qualify these terms too. In this case, the information value must be timely and exclusively available. In other words, it has to be of restricted availability. This indicates that at least some quality dimensions currently considered simple attributes, are in reality multifaceted attributes. The labels assigned to quality dimensions should reflect such facts. More examples follow. In news media, there is an unending race for exclusively operationally timely available information values. The most frequent casualty of this race is its credibility and completeness. Even worse, credibility of news is frequently compromised by a strong dose of political bias by media owners, editors, and the journalists themselves. Under the pressure of sensationalism8 or political expediency, e.g. to be the very first to report something unusual, there is not much time and interest in checking for its veracity and other mitigating circumstances, when mudslinging pays off. Even worse, the pressure to sensationalize the news literally leads to inventing news, thus to disinformation. Many journalists succumbed to the pressure to attain the highest utility value for them personally and for the editors at any cost, even when later it becomes detrimental to their personal and company’s reputation9. Neither credibility nor completeness is fully attainable. Both are measured by a continuum of degrees [0-100%]. If 100% is not attainable, there has to be at least an acceptable minimal level of credibility that triggers action. Any level of credibility that is equal or above this minimal level is the actionable level of credibility. Thus, one needs

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again qualified terms such as actionably credible and effectively operationally complete. Both are universal requirements not only in news services. From the external view, they are well defined, but from the decision-makers’ view, they are highly subjective, for they will be different for decision-makers of different personalities and in different situations. Alas, the evolutional theory-based approach (Liu and Chie, 2002) omits completely the issue of the amount of information an information value conveys as defined in the communications theory and the issue of its utility value as defined in information economics. This case illustrates the first principle or the law of relativity of all operations quality requirements, which in its full extent is recognized only in the teleological approach to quality (Gackowski, 2005b). There is no room for intrinsic quality requirements. Only under specific circumstances, a large amount of information as defined by Shannon and Weaver (see the last formula in previous section) translates into a high utility value for the publisher due to its attractiveness to the mass media audience. To this effect, however, it must be also operationally timely available (the third direct primary universal requirement) to a single publisher. Restricted availability is a situation-specific mandatory requirement otherwise, competition reaps profits. Disinformation violates credibility (the fourth direct primary universal requirement). It may yield a one-time gain, but it may ruin the publisher in the end as a failed or biased audit of ENRON ruined Arthur Anderson.

CASE 2 – AMOUNT AND UTILITY VALUE OF AN INFORMATION VALUE IN BUSINESS This case represents the other extreme in the relation between the amount and the utility value of an information value. This is a historical business case when enormous business opportunities hinged on a single variable of only two or possibly three values that represent the outcome of an event. It demonstrates also, how limited the present ways of thinking about quality requirements are. In 1815, in one of the 20 most decisive battles in world history, the British in alliance with Prussia faced Napoleon’s last-ditch effort to change the course of history, not only in Europe. Innumerable business opportunities, among them the pricing of assets (deposits, stocks, bonds, real estate, etc.) of the Rothschild’s bank in London, hinged on any decisive outcome of the Battle of Waterloo, Belgium. The outcome may be represented by a binary variable, which cannot yield more than one bit of information - the maximum amount of information possible in this situation. If one takes into account three options: an outright victory, outright defeat, or an inconclusive outcome, the maximum amount of information cannot exceed 1.6 bits according to Shannon. The actual amount of information was less, for by historical experience the outcome of battles waged by Napoleon was not 50/50. Most people still favored Napoleon. At that time, a decisive outcome would change the pricing of most assets in Britain. Rothschild decided to find the outcome as the first businessman in London. He sent observers to Waterloo equipped with carrier pigeons to be dispatched with the encoded result10. The informational model of the situation consists of one variable of unknown value that has to be acquired. In this case, however, the amount of less than 1.6 bit of information is associated with an enormous utility value. Rothschild was a shrewd businessman, too. Once he received the valuable information about the victorious outcome of the battle, he started selling assets. It sent all prices into a tailspin. Later he started buying everything at depressed prices by concealed representatives, thus multiplied his fortune. This is a classic case when utility value of enormous magnitude is associated with about one bit of the amount of information. This information, however, had to be of proper quality with many requirements attached to fit its use. The outcome of the battle must be accurately interpreted, encoded, transmitted, received, properly interpreted by the receiver, and finally shrewdly acted upon. All this was uncertain, as it usually is when stakes are high. Even redundancy had to

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66 2006 IRMA International Conference be added, e.g. many observers deployed, many encoding schemas used, many carrier pigeons dispatched for some might perish. The information might have arrived in a not interpretable form. Many things might have gone wrong. The requirement of exclusivity applies here, as well; hence, all types of security precautions had to be taken. The first conclusion from this case is that the teleological approach (Gackowski, 2005b) illuminates immediately the potentially most important quality requirements that must be considered for a successful acquisition. This research, even in its incomplete form, without the map of mutual interdependencies among all quality dimensions, provides a quality analyst with an insight what is important and mandatory versus what is secondary without resorting to survey-based research. The latter is practically infeasible with high-stake business opportunities. The teleological view does not exclude brainstorming sessions with experts. Similarly, the recommended sequence of examination of the universal direct primary quality dimensions within the teleological view turns out to be helpful, too. •

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First, whatever information arrives, whether from the battlefield or anywhere else, it must be acquisition interpretable. It is the first universal direct primary quality requirement. Second, it must be of significant impact on the desired business results. For instance, an indecisive outcome of the battle would probably be of no practical use. It is the second universal direct primary quality requirement. Third, the information must be not only available, but also exclusively and operationally timely available, e.g. sufficiently in advance so that any required action can be triggered successfully before anybody else becomes aware of the same opportunity. It is the third universal direct primary quality requirement. It also suggests that pertinent security measures for preventing information sharing must be taken as prudent precautions. Here, exclusivity is also mandatory; otherwise, its impact would be nullified or unacceptably diminished. It is not, however, an example of a universal but a situation-specific quality requirement. Fourth, it must be presentation interpretable, since here, the use of information is separated from its acquisition, and indirect informing takes place as defined in (Gackowski, 2005a). This one, however, is also not a universal requirement for it applies only to indirect informing. Fifth, it is desirable that the information is not simply credible but actionably credible; otherwise, it would be foolish to act upon it. Of course, what constitutes actionable credibility must be operationally defined within the context of a specific situation, for instance, when received from two independent sources that are experienced enough to correctly interpret the outcome of the battle, and sufficiently trustworthy to rely on them. It is the fourth universal direct primary quality requirement. Sixth and last, it also must be task-specifically effectively operationally complete that in this simple case is not a problem. The latter requirement within the teleological approach to quality represents the fifth and last universal direct primary quality requirement for a set of usable data or information values.

If any one of the five (here six) direct primary mandatory dimensions of information quality could not be met, the potential business opportunity is lost. This precludes considering the remaining quality requirements. When it comes to the direct secondary quality dimensions, they usually affect only the economy of effective use of information. In a case of high stakes, cost considerations are rather tertiary. The teleological view facilitates examining data/information quality derived from various theories and used in different situations. It helps to focus the examiner’s attention on only 5 – 9 direct quality requirements out of the seemingly unmanageable plethora of 179+ quality dimensions11 initially identified in the empirical study by Wang and Strong (1996). In stark contrast, like the evolutionary approach by Liu and Chie

(2002), they encompass neither the amount nor the utility value of an information value derived from the corresponding theories. It demonstrates again how unreliable can become otherwise useful empirical studies. By ignoring these important factors, both approaches do not provide any hints as to how much attention to pay to different information values, while collecting, storing, presenting and using them.

CONCLUSIONS This paper shows in two contrasting cases of data and information quality (viewed from theory-specific perspectives) the intricate relationship of the amount of information conveyed by and its utility value in operations – the two most misunderstood theory-derived quality attributes of information. Information systems do much more than only represent the real world as pure data processing systems do. If well designed, information systems assist in changing business results for the better. In business environments, the teleological perspective should be the dominant one. Once the only 5 - 9 direct operations quality requirements have been identified, the next important step is to map their functional dependencies on the remaining plethora of the 170 + the not yet identified indirect quality attributes, develop an examination algorithm and construct an intelligent operations quality analyzer of data and information values within their context-specific use in operations in business, public administration, and military. The internal view is restricted to the design and operations of data and information delivery and distribution systems, never to data and information values per se. This is obvious, but still it is very far from being generally accepted. Some ask how to measure quality within the context of operations. This question alone implies three things that: (a) such a measure can be developed, (b) may have any useful application, and (c) the more of it the better. One could say a detail answer to this question exceeds the boundaries of this paper; however it is simple and shocking. Shocking when one takes into consideration how much effort, time, and resources have been spent on developing and applying different metrics of quality. Here is the answer with the corresponding arguments. 1.

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First, by the law of relativity, operations quality requirements are determined by the purpose and circumstances of operations they are used for. It pertains to all representations of the states of the real-world (data, information, and rules of reasoning). This implies an absolute individuality of quality requirements for each data or information value as a function of task-specific purposes and circumstances. This alone precludes any composite measure of operations quality requirements. Within the realm of operations quality, attempts of developing such metrics are futile. Second, the quality of data and information values is a vector in a multidimensional space of 179+ potential quality attributes. One should define each of them in a manner that facilitates measurability. Nevertheless, they are interdependent, and we do not possess reliable exchange or trade-off rates for these attributes. It is unlikely we ever will. Hence, quality viewed this way cannot be reduced to a common scalar value12; it cannot be summarily measured. Third, the operations quality knows only five to nine direct quality requirements. As mandatory, they make trade-offs impossible. They must be met, hence no quantification is possible. Fourth, one may ask what purpose such a composite measure may serve. To reduce the problem ad absurdum, let’s assume tradeoffs among quality dimensions are possible and a composite measure calculated. Results of operations, especially their cost effectiveness, are certainly a function of specific quality dimensions, but not of quality in general. Most people intuitively tend to think that improved quality of data and information value improves the results of operations. It may, but not necessarily. Not even a single attribute of quality monotonically increases operations results, then the same holds true of their composite

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Emerging Trends and Challenges in IT Management measure. All quality attributes must be applied at their optimum levels to obtain the best results of operations. An unchecked effort to deviate from the optimum level of any quality aspect is counter-productive - see more detail discussion in Gackowski (2006). The economic law of diminishing returns applies here fully. In other words, no aspect of quality should become an end on its own merit. Each one should be fine-tuned from the perspective of maximized cost effectiveness of products, services, and operations. Operations are a granular network (graph) of elementary activities use resources (among them data and information values). It does not preclude optimization of aspects of operations quality, but it does preclude the development of any composite measure of operations quality of data and information values that would make sense and be applicable.

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REFERENCES Alter, S., (2002). Information systems—Foundation of e-business. Upper Saddle River, NJ: Prentice Hall. Gackowski, Z. J. (2005a). Informing systems in business environment: A purpose-focused view. Informing Science Journal, 8, 101– 122. Retrieved June 26, 2005, from http://inform.nu/Articles/ Vol8/v8p101-122Gack.pdf Gackowski, Z. J. (2005b). Operations quality of data and information: Teleological operations research-based approach, call for discussion. Proceedings of the 10th Anniversary International Conference on Information Quality—ICIQ-05 at Massachusetts Institute of Technology (MIT), Cambridge, MA. Gackowski, Z. J. (to appear). “Purpose-focused view on information quality: teleological operations research-based approach” in Information Quality Management: Theory and Applications, Al-Hakim, L., Chief Editor, The Idea Group, Hershey, PA. Kofler, E. (1968). O wartosci informacji (On value of information), Panstwowe Wydawnictwa Naukowe (PWN), Warsaw, Poland. Liu, L., & Chi, L. N. (2002). Evolutional data quality: A theory-specific view, Proceedings of the Seventh International Conference on Information Quality (ICIQ-02), Cambridge, MA, 292–304. Retrieved June 26, 2005, from http://www.iqconference.org/ iciq/iqdownload.aspx?ICIQYear=2002&File=Evolutiona lDataQualityATheorySpecificView.pdf Mazur, M. (1970). Jakosciowa teoria informacji (Qualitative theory of information), Panstwowe Wydawnictwa Techniczne (PWT), Warsaw, Poland. Shannon, C. E., & Weaver, W. (1949). The mathematical theory of communication. Urbana, IL: University of Illinois Press. Wand, Y., & Wang, R. Y. (1996). Anchoring data quality dimensions in ontological foundations. Communications of the ACM, 39(11), 86–95. Wang, R. Y., and Strong, D. M. (1996). “Beyond Accuracy: What Data Quality Means to Data Consumers”, Journal of Management Information Systems (JMIS), 12(4), 5-34.

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The theory deals with the quantity of information and problems arising in transmission of messages, which usually consist of one or more values. This measure is important not only in analyzing the efficiency of information transmission, but also carries a practical and monetary weight in news media. The anecdotal saying: “dog bites man does not make news, but man bites dog makes news” illustrates the above statement. For instance, the utility value of special information service on road conditions. “The Internal View assumptions: Issues related to the external view such as why the data are needed and how they are used is not part of the model. We confine our model to system design and data production aspects by excluding issues related to use and value of the data” (Wand and Wang, 1996) (emphasis added). From datum – facts considered to be given, true or propositions used to draw conclusions or make decisions A data or information value becomes usable when it jointly meets all its universal and situation specific mandatory quality requirements. Usability does not imply effective usability; it is a necessary requirement only (Gackowski, 2005b). A usable data or information value can become operationally useful only as a member of an operationally effectively complete activity-specific cluster of required usable data or information values (Gackowski, 2005b). May not be liked, but it is a driving concept of many media outlets, and it is of high utility value to publishers Note: CBS’s far reaching debacle with the credibility of their reporting during the last presidential election campaign. As historical reports show, at those times one could watch a battle without being unduly harassed as a non-combatant and non-participating observer. No other approach, model, or framework does it. None of the known approaches to quality defined a universal taxonomy, identified universal quality requirements with an economic sequence of their examination, and defined at least seven universal principles, which govern all aspects of operations quality of data and information values. As for instance, the value of products and services rendered are reduced to one value of the GNP (gross national product)

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Acceptance of the Mobile Internet as Distribution Channel for Paid Content Christian Kaspar, Lutz Seidenfaden, Björn Ortelbach, & Svenja Hagenhoff Institute of Information Systems, Dep. 2, Georg-August-University of Goettingen, Platz der Göttinger Sieben 5, 37073 Göttingen, Germany, P: +49 551 39-444, {ckaspar|lseiden|bortelb2|shagenh}@uni-goettingen.de

ABSTRACT The mobile Internet is perceived as a chance for media industry to generate additional revenues from paid contents. Successful business models for the mobile Internet will only be possible if mobile content formats generate added consumer value. In this context, media companies planning to establish mobile services for content distribution are facing the problem that acceptance of mobile services has not yet been researched thoroughly. We conducted a survey of mobile content usage that is based on 7183 valid responses in May 2005. Our paper outlines first results from this survey. Key findings are that paid mobile contents will not be a mass market in the medium term. Nevertheless, we found that respondents that are familiar with mobile radio and handset technology and read specialized printed media on a regular basis showed the highest acceptance of mobile paid contents.

INTRODUCTION The publishing industry is characterized by oligopolistic structures, differentiated products and fierce competition. The growing range of contents available in digital distribution channels like the Internet has led to decreasing circulations, revenues and earnings in the publishing industry. Despite concentrated efforts to generate direct revenues from online recipients the traditional freebie-mentality of Internet users seems to be overwhelming compared to the small online revenues. This development may lead to a strategical threat of the publishers’ core business if not to an enduring threat to their existence.

research. Section 2 gives an overview of the related work and the status of acceptance research related to the mobile Internet and describes the underlying methodology of the survey in detail. In section 3 the results of the survey are described. Section 4 analyses the results of the survey and points out the major findings. The paper closes with a conclusion in section 5.

RELATED WORK AND CONCEPT OF THE RESEARCH APPROACH Generally, the mobile Internet consists of data services built upon mobile radio technologies. In this area, it is important to distinguish between carrier technologies for LANs (e.g. 802.11, 802.16 and 802.20) and WANs (e.g. GSM, UMTS and CDMA2000) on the one hand and protocols for data communication on the other hand (e.g. WAP, SMS and MMS) [5]. Acceptance represents a form of consenting behavior or consenting attitude towards an innovation [6]. Acceptance research in business administration can be understood as an approach that tries to identify reasons on the customer side that lead to either acceptance or rejection of an innovation [7], [8]. Acceptance of an innovation depends on three factors: the (cognitive) knowledge of potential users, interest and a positive (affective) attitude and a specific (conative) decision to buy [9].

To find a way out of this situation, publishers can pursue two strategies in order to generate additional revenues [1]: They can enforce the diversification into new business areas such as Internet service providing or embrace measures to increase the customers’ willingness to pay for online content [2]. The willingness to pay does not only depend on the quality of the content but also on its usefulness and the quality of its format [3]. Examples for such value added services are mobile Internet services which provide location-independent access to contents [4]. In order to generate revenues from the utilization of content in the mobile Internet it is necessary that the content provided addresses existing customer requirements.

Two groups of studies which contribute to research of acceptance of the mobile Internet can be identified: expert groups [11], [12], [13], and customer surveys [14], [15], [16], [17]. It can be stated that no shared argumentation can be found in the studies mentioned above. Therefore, they do not enable the reliable deduction of promising mobile services. Instead it appears that the acceptance of mobile services needs to be examined empirically and experimentally for each individual case. Furthermore, the present status of acceptance research in the mobile Internet concerning mobile service provision by companies from different market segments, e.g. publishers or financial service providers, is rather unfocussed or has only little significance due to small samples. Therefore a lack of research can be identified in this field. The paper on hand is a first step to address this issue from the viewpoint of the mass media industry.

In practice, it is difficult for media businesses to identify relevant areas of application for mobile services, because their acceptance is only poorly understood. Therefore the decision problem of a publishing house in the mobile services area can be divided into three parts:

The main goal of the following acceptance analysis is to determine a decision map which can be used by media companies to identify promising distribution forms for their content in the mobile Internet. In order to achieve this, three central questions are examined:

•

1.

• •

Firstly, the customers who are likely to use the service have to be identified. Secondly, the content which is supposed to satisfy the requirements of the potential customers needs to be determined. Thirdly, the service formats which promise to be successful given the preferences of the potential customers need to be identified.

2.

3. The paper on hand answers the three questions based on a representative survey of German Internet users from the viewpoint of acceptance

With regards to the diversity of distribution formats in the mobile Internet (MMS, SMS, WAP, etc.), it seems necessary to identify those with the highest user acceptance. The question which content is used by which type of customer and to which extent in an mobile setting is at the core of the examination. Furthermore, the necessity to examine affective acceptance criteria suggests finding out which motives lead to the usage of mobile services and which do not.

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Emerging Trends and Challenges in IT Management Figure 1. Distribution of print titles relative to the survey population 100%

Figure 2. Distribution of mobile services relative to survey population

78%

80%

54%

60% 40%

38% 11%

20%

4%

3%

12%

2%

9%

17%

22% 28% 9%

0%

20%

19,02%

16,93%

15%

ew sp ap er ew sM Pr ag og . ra m W M om ag . en 's M ag Fa . m ily M ag M . us ic M ag Li . vi ng M ag A . du lt M Li ag fe . sty le M ag M ot . or M ag Sp Sc . or ie t nc e/T s M ag ra . ve l/C ul tu re IT M ag .

9,04%

8,02%

10%

3,57%

5%

1,21%

0,93%

2,12%

0%

N

N

69

SMS

MMS

WAP

Music

Clips

Classifieds Guidebook

LBS

which state that the circulation and the revenues of the newspaper segment significantly exceed those of the magazine market (cf. figure 1). These three questions address problem areas which require validation through field research. Since the underlying central questions of the analysis characterize quantifiable product/market combinations, the following survey was conducted as a standardized written survey. The primary goal is the detection and description of the verifiable usage of mobile services by the costumers of magazine publishers. The reason for the suggestion of actions for publishers who want to provide mobile value added service to their customers is an assumed logical connection between media specific customer segmentation (e.g. using format and content type as segmentation criteria) and the usage of mobile services. The verification of this hypothesis is not matter of this survey but a matter of our further research.

ACCEPTANCE OF MOBILE CONTENT FORMATS AMONG USERS OF PRINTED MEDIA The survey was aimed at identifying significant correlations between the regular use of popular printed media and mobile content formats. On this basis, we try to determine promising content/service combinations and their respective users as an additional source of revenue for newspaper and magazine publishers. For this purpose, we created a standardized online questionnaire which was advertised on the homepages of 16 popular German consumer magazines in order to achieve a high degree of representativeness. Out of the 13,402 viewers of the questionnaire, 7,178 completed the survey. Approximately 75% of the participants were male. On the whole, they were evenly distributed among the ageand income brackets. The survey was divided into four sections: first, participants were asked about their usage of 13 common types of printed media (newspapers, news magazines, (tv)program magazines, women’s magazines, family magazines, music and youth magazines, living magazines, adult magazines, lifestyle magazines, motor magazines, sports magazines, science/ travel/culture magazines, and IT magazines). The answers were used to create a typology of users of mobile content. The central question of the second section was the degree to which the acceptance of mobile radio technology influences the usage of mobile Internet applications. Questions included the mobile devices owned by the interviewee and the preferred mode of Internet access. The third section, which was the main focus of the survey, was centered around the use of contents on the mobile Internet. We examined potential combinations of content and different formats, including SMS, MMS and WAP. Besides, mobile music and video services as well as specialized contents such as guidebooks, classifieds and location-based services (LBS) were surveyed. The questionnaire was concluded by questions related to the motivation leading to the use or non-use of the various formats.

Stationary PCs are most widely distributed (87% of the participants), followed by mobile phones (79%) and notebook PCs (54%). Mobile phones are most widely distributed among the women’s, youth, music, and lifestyle segments. Only 4% of the interviewees use “Smartphones”, which combine the features of mobile phones and PDAs. These devices are considered to be a sign of a high acceptance of mobile services. Smartphones have an above average diffusion among readers of motor and adult press. Only paid mobile Internet services were examined. The most widely used services are the WAP-pages supplied by the mobile service provider’s portals. Contents supplied by SMS, MMS and LBS were popular as well. Mobile music and video services, guidebooks and classifieds are of little significance (cf. figure 2). The mass market segments such as daily newspapers, news- and program magazines show above average usage rates of all service categories compared to the population. The evaluation of service usage related to the size of the segment gives a different impression. Figure 3 shows the usage rates of the five most widely spread mobile service formats in relation to the size of each reader segment (the value in brackets indicates the number of respondents of each reader segment). Particularly readers of niche media with lower circulation, such as music, adult, lifestyle, motor, and travel magazines, display an above average willingness to use paid mobile content. For example, 28% of the readers of sports press use paid SMS services at least occasionally and 35% of the readers of adult press use paid WAP services. Music services display above average popularity among readers of youth and music press (11.9%) and adult press (13.8%). Usage Frequencies of Mobile Content Services per Reader Segment In the following, we will examine the usage frequencies of different services offered via SMS (1), MMS (2), WAP (3) and LBS (4) in detail in order to achieve a deeper understanding of their acceptance among different user groups. Video services, classifieds and guidebooks will be neglected due to their sparse usage as well as music services which were not examined in detail.

Figure 3. Mobile service usage by reader segments (in %) 40 30 20 10

ew

N

N

ew

sp ap er (

n= 55 sM 97 ag ) Pr . og (n =3 ra m 85 M 9 ) ag W .( om n= en 27 's 0 3) M ag .( Fa n= m 79 ily 4) M ag M .(n us = 28 ic 8) M ag .( Li n= vi 24 ng 4) M ag .( A n du =8 lt 62 M ) ag Li .( fe n= sty 15 le 2 M ) ag M .( ot n= or 66 M 7) ag .( Sp n= or 12 ts 09 M ) Sc ag ie .( nc n= e/T 64 9) ra ve l( n= IT 15 98 M ) ag .( n= 20 14 )

0

Usage Frequencies of Mobile Service Formats per Reader Segment In order to segment the respondents, we tested the regular use of 13 different types of printed media. Daily newspapers were used most frequently followed by news, program and IT magazines. These results correspond to present statistics of the German mass media market,

SMS

MMS

WAP

Music

Mean SMS

Mean MMS/LBS

Mean WAP

Mean Music

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LBS

70 2006 IRMA International Conference On average, SMS services are used by 17% of the interviewees. Readers of adult magazines display the most noticeable usage (30%). Readers of sports magazines (28.3%) as well as music titles (25%) are also frequent users. Seven specific versions of paid SMS services were examined, including both entertainment and information. On average, the most popular services are sports news (8.6%) and general news (6.4%). Financial news and horoscopes are of minor importance (2.5% and 2.4%). Aside of the significant use of SMS sports news by readers of sports press (21%), readers of music and youth magazines display a noticeable willingness to use entertainment content (12%). Readers of adult and lifestyle magazines are frequent users of sports news (14% and 8.5%). The usage of paid MMS services is similar to the case of SMS, albeit on a lower average level (8%) of the respondents. Again, sports news and general news have the highest average usage rates. Readers of adult magazines (23%), music und youth magazines (14%) and motor/sports magazines display an above average acceptance of MMS services in general. MMS-based sports news are consumed by readers of sports and adult magazines (8% and 7.8%). Readers of adult magazines (6%), music and youth magazines (3.6%) and sports press (3.1%) frequently consume general news. As stated above, WAP based portal services see the strongest demand among the target group. 12 typical WAP offerings were surveyed. Aside of media-specific information and entertainment offerings such as general news (9.1%), sports news (8.9%), leisure (3.1%) and travel information (3.2%), device-specific products such as ring tones (9.4%), email (7.1%) and games (6.7%) were purchased most frequently by the population. Entertainment contents such as ring tones and games are used above average by the readers of youth and music magazines (8.2%). Again, information content such as general news and sports are purchased most frequently by readers of adult (15.8% and 14.5%), lifestyle (12.6% and 10.3%) and sports press (8.5% and 20.2%). Respondents were able to choose among four kinds of LBS which have already been realized by the mobile service providers: location-based directories and yellow pages, so called “community services”, navigation services and location-based mobile payment. The usage level was generally low, with directories and navigation being the most popular services (3.6% and 3.4%). Community and payment services are of minor importance (1.6% and 0.4%). There is a noticeably high usage frequency of these services among readers of family magazines (e.g. 6.3% using directory services) and living magazines (e.g. 5% using navigation). Further segments displaying above average demand for LBS are music and youth, and adult publications. Motivation for the Usage of the Mobile Internet If the specific variants of mobile services were indicated to be not used, respondents were asked on which conditions they would consider using the services in the future. The survey contained items testing the expected utility (price and added value), the perceived quality of the content and aspects of technical usability (speed, display quality and device usability). There were no significant differences between the reasons stated by different segments and concerning different services. As displayed in Table 1, price and added value were dominant. For each service that a respondent indicated to use at least casually criterions were available that allow conclusions about the respondent’s

Table 1. Conditions for future usage of the mobile Internet

Figure 4. Purpose-neutral interest and content-oriented gratifications (in %) 25

25

20

20

15

15

10

10

5

5

0

0

SMS

MMS

WAP

LBS

Curiosity

Fascination

Mean Curiosity

Pract. Value

Habit

Mean Pract. Value/ Fascination

SMS

Music Mean Habit

MMS

WAP

Entertainm. Interacivity

Mobility Inform.

Figure 4 shows that the attraction of the mobile Internet is mainly determined by the respondents’ curiosity and general fascination of technology. Thereby, services based on WAP and SMS show highest practical value leading to higher habitual usage of these service formats. Furthermore, the figure shows that mobile services serve needs that are connected to the reason of mobility. While SMS-based services as well as surprisingly music-services serve information needs best, MMS, WAP and LBS are meant to interact with other users.

FINDINGS FROM THE SURVEY Against the background of the research questions listed in section 2 we will analyze the survey’s results in order to identify significant coherences of indicated behavior and to conclude from this behavior upon the respondents’ acceptance of contents in the mobile Internet. According to the first question we will examine the survey’s results for systematic dependencies between the consumption of printed contents and the usage of mobile content formats (1). Afterwards, we will study the motives indicated for the usage of mobile contents to identify differences of consumers’ needs (2). (1) Figure 3 leads to the assumption that respondents reading different print titles will show different usage patterns of mobile Internet content beyond the differences explained by their choice of mobile devices. In particular, readers of music, adult, lifestyle, motor and sport magazines show an above average willingness to use mobile services. Table 2 shows confidence coefficients resulting from (Chi-Square) tests of statistical independence between the reading habits and the willingness to use mobile contents. The test results prove that there is a significant dependency. However, the interrelation is very low for all reader groups,

Table 2. Confidence coefficients for magazine readership and mobile services use Program

Women's

SMS

Newspaper 0,028

News Mag. 0,037*

0,08**

0,051**

Family 0,03

Music 0,053**

0,036

MMS

0,018

0,04*

0,03

0,028

0,034*

0,044**

0,027

WAP

0,031

0,033

0,073**

0,015

0,03

0,07**

0,029

LBS

0,04*

0,041**

0,026

0,033

0,024

0,02

0,055**

Music

0,026*

0,046**

0,037*

0,064*

0,008

0,077**

0,019

Motor

SMS

0,068**

0,046**

0,056**

0,1**

0,027

0,068**

MMS

0,082**

0,045**

0,072**

0,072**

0,033*

0,063**

7,0

WAP

0,065**

0,086**

0,061**

0,091**

0,028

0,071**

10,8%

6,5

LBS

0,018

0,052**

0,035*

0,043**

0,053**

0,051**

Higher display quality

8,2%

4,8

Music

0,058**

0,054**

0,038**

0,052**

0,002

0,009

Better device usability

7,0%

3,4

13,4

Added value

18,5%

6,4

Content quality

18,1%

Higher bitrate

Living

* significant on 95%-level ** significant on 99%-level Lifestyle

Deviation

41,6%

Music

Mean Entert.

motive of using the certain service. In detail, eight criterions have been made available. Thereof four criterions indicate the respondent’s purpose-neutral interest (practical value of the service, curiosity about the service, fascination from mobile technology in general and habitual usage) and four criterions indicate the respondent’s earmarked interest (mobility, information, entertainment and interactivity).

Adult

Mean Lower prize

LBS

Mean Mobility Mean Inform./ Interacivity

Sports

Science /Travel

IT

* significant on 95%-level ** significant on 99%-level

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Emerging Trends and Challenges in IT Management Figure 5. Coefficients for magazine readership and mobile services use

Table 3. Confidence coefficients for magazine readership and mobile content use

0,15

Music Magazines

0,1 SMS

0,05 0 SMS Sports Mag. Music Mag.

MMS Adult Mag. Lifestyle Mag.

WAP Motor Mag. News Mag.

MMS

WAP

To answer the second research question, the interrelations identified on the level of service formats need to be verified on the level of different contents distributed in these formats. As we have detailed before, news, sports and entertainment contents are consumed most frequently using SMS-, MMS- and WAP-based services. Therefore, the results of independence tests for these contents in the four reader groups with highest willingness to use mobile services are shown in Table 3. The figure reveals that reading music, adult, and sports magazines is significantly interrelated with using mobile contents. However, besides the interrelations between usage of mobile sports contents by readers of sports magazines, the values of these interrelations are rather small. (2) In section 4 we described that the attractiveness of the mobile Internet is determined by curiosity and fascination of technology as well as the need for ubiquitous information. Examining the respondents’ motives in relation to their reading behavior reveals only marginal differences between different reader groups. E.g. SMS- and MMS-based contents tend to be perceived as entertainment by readers of music and adult magazines whereas readers of lifestyle magazines use them in order to satisfy information needs (cf. Figure 6). Only readers of adult magazines show a balance between habitual mobile content reception and satisfaction of spontaneous information needs. We did not find any significant differences either between the motives of mobility and ubiquity, dominating interactivity within all reader groups, and between technology fascination and practical value.

Entert.

Inform.

Entert.

Inform.

MMS

Music

Entert.

WAP

Adult

Lifestyle

Entert.

[1]

[5]

[6]

40%

[7]

20% 0% Curiosity SMS

Habit

Curiosity MMS

Habit

Curiosity WAP

Habit

Curiosity

Habit

0,034*

0,04**

Entertainment

0,085**

0,057**

0,058**

0,029*

Sports

0,038*

0,061**

0,02

0,124**

News

0,018

0,037*

0,031

0,026*

Entertainment

0,042**

0,059**

0,025*

0,026*

Sports

0,033*

0,061**

0,059**

0,183**

0,012

0,04**

0,071**

0,016

0,087**

0,059**

0,058**

0,017

REFERENCES

LBS

Sports

0,039**

Respondents reading special interest magazines such as adult or sports press show a higher willingness to use mobile contents. In contrast, consumers of mass market segments such as newspapers and news magazines did not show significant demand for mobile contents. This result is disillusioning for three reasons: Firstly, readers of music, adult, lifestyle or sports magazines are naturally limited in number. Secondly, there is only a small degree of interrelation within these groups. This leads to the conclusion that even those readers are not willing to use mobile services to a large degree. Thirdly, our examination of motives revealed that using mobile contents is mainly driven by curiosity and fascination. This leads to the assumption that content providers can not expect stable demand in the near future.

[3]

Inform.

0,051** 0,053**

The survey at hand addresses the acceptance of mobile services from a behavioral perspective. There are a number of key findings: mobile contents are used mainly in order to satisfy curiosity and locationindependent information needs. In contrast to e.g. [18], who assume that special interest contents such as guidebooks will dominate users’ demand of mobile services, we found that only contents of general interest such as news and sports are being used frequently. Furthermore we were able to disprove statements indicating a lack of acceptance of WAP-based contents.

[4]

SMS

0,205**

0,026* 0,038**

SUMMARY

0%

Inform.

Sports Magazine

* significant on 95%-level ** significant on 99%-level

40% 20%

Lifestyle Magazine

News

Entertainment

[2]

Figure 6. Relation of curiosity and habitual usage

Adult Magazines

Sports

News

as indicated by the coefficients which are very small. This leads to the conclusion that on the one hand reader segments showing significant dependencies will allow potential earnings from mobile content offerings. On the other hand, mobile content services will only reach small market sizes. It is unlikely that they will become a mass market in medium term. In Figure 5, we compare the values of the contingency coefficients of the five reader groups with the highest significance and the three most popular mobile service formats (SMS, MMS and WAP). Readers of sports magazines have the strongest interrelation with SMS- and WAP-based services while readers of adult magazines prefer MMS-based services.

71

Seidenfaden, L., Kahnwald, N., Kaspar, C., Ortelbach, B., Mediennutzung im digitalen Leben: Active Content Interfaces, Paid Content und integrierte Geschäftsmodelle, Business Village, Goettingen 2005. Gregg, S., Die Konvergenz: Telekommunikationsanbieter und Medienunternehmen – Wettbewerber oder Partner?, in: Vizjak, A., Ringlstetter, M., (Eds.) Medienmanagement: Content gewinnbringend nutzen. Gabler, Wiesbaden, 2001, p. 37-44. Fink, L., Economies of Aggregation, University of Cologne, 2002. Zobel, J., Mobile Business and M-Commerce, Hanser, Munich, 2001. Kaspar, C., Hagenhoff, S., An overview of mobile radio technologies, in: Pagani, M. (Ed.): Encyclopedia of Multimedia Technology and Networking, Hershey, 2005. Anstadt, U., Determinanten der individuellen Akzeptanz bei Einführung neuer Technologien, Europäischer Verlag der Wissenschaften, Frankfurt a. M., 1994. Venkatesh, V., Davis, F., A theoretical extension of the technology acceptance model. Four longitudinal field studies, in: Management Science, (46) 2, 186-203.

LBS

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72 2006 IRMA International Conference [8]

[9] [10] [11]

[12] [13]

Govindarajulu, C., Reithel, B., Sethi, V., A model of end user attutudes and in-tentions toward alternative sources of support, in: Information & Management, (37) 3, 77-86. Müller-Böling, D., Müller, M., Akzeptanzfaktoren der Bürokommunikation, Oldenbourg, Munich, 1986. Lehner, F., Mobile and wireless information systems, Springer, Berlin, 2003. Müller-Verse, F. Mobile Commerce Report, Durlacher Research Report, URL: http://www.durlacher.com/downloads/ mcomreport.pdf. Ovum, Mobile E-Commerce: Market Strategies – An Ovum Report, London, 2000. TIMElabs, Winning in Mobile eMarkets , URL: http:// www.timelabs.de/pdf/TIMElabs_C_mB2B_d.pdf

[14]

[15]

[16]

[17] [18]

Nokia (1999): The demand for mobile Value-Added Services. URL: http://www.telecomsportal.com/Assets_papers/Wireless/ Nokia_mobile_vas.pdf. Sirkin, H., Dean, D., Mobile Commerce – Winning the on-air consumer, URL: http://www.bcg.com/publications/files/MCommerce_Nov_2000_Summary.pdf. A.T. Kearney, Mobinet 5: The New Mobile Mindset, URL: http:/ /www.atkearney.com/shared_res/pdf/Mobinet_ Monograph_S.pdf Wohlfahrt, J., Akzeptanz und Wirkung von Mobile-BusinessAnwendungen, Dr. Kova Hamburg, 2004. Ziegler, M., Adam, B., Mastering Mobile Media Markets, Diebold Consulting, Eschborn, 2001.

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Emerging Trends and Challenges in IT Management

73

E-Learning Acceptance Model (ELAM) Hassan M. Selim, College of Business & Economics, Department of Business Administration, United Arab Emirates University, Al Ain, PO Box 17555, United Arab Emirates, F (9713) 763-2383, [email protected]

ABSTRACT This study develops an E-Learning Acceptance Model (ELAM) to investigate the relationships among the factors affecting students’ acceptance of e-learning. In line with the literature, three critical success factors were used, namely instructor characteristics, information technology infrastructure, and support. ELAM was analyzed and validated using data collected from 538 university students through structural equation modeling (LISREL 8.54). The influence of the three factors on students’ decision of accepting e-learning was empirically examined. The results showed that all three factors significantly and directly impacted the students’ decision of accepting e-learning-based university program. Information technology infrastructure and the institution support were proven to be key determinants of the instructor characteristics as a critical success factor of e-learning acceptance by students. Implications of this work are very important for higher education institutions, researchers, and instructors.

support, faculty support, and evaluation and assessment. Selim (2004, 2006) specified eight e-learning critical success factors that can assist universities and instructors to efficiently and effectively adopt elearning technologies: instructor characteristics (attitude towards and control of the technology, and teaching style), student characteristics (computer competency, interactive collaboration, and e-learning course content and design), technology (ease of access and infrastructure), and support. This study builds on the previous studies of factors identification by developing a causal structural equation model (LISREL) that includes 3 constructs (instructor characteristics, information technology, and institution support). The objective of the causal research model was to study the effects of the three factors on student e-learning acceptance which was represented as a fourth construct in the research model.

RESEARCH MODEL AND METHOD INTRODUCTION E-learning has become a main tool of enhancing education and training activities. Many higher education schools are integrating e-learning components into their courses in order to either offer degrees at a distance or enhance the delivery of traditional courses. E-learning can be viewed as the delivery of course content via electronic media, such as Internet, Intranets, Extranets, satellite broadcast, audio/video tape, interactive TV, and CD-ROM (Engelbrecht, 2005; Urdan & Weggen, 2000). Students use computers and telecommunications in e-learning to access online course materials via course management systems such as Blackboard (Rovai, 2002). Many e-learning initiatives fail to achieve desired learning and teaching outcomes because of the selection of the appropriate technology, the instructor characteristics, not enough attention and support by the organization (Engelbrecht, 2005; Selim, 2004, 2006). Despite the potential of e-learning as a tool to enhance education and training, its value will not be realized if instructors, students, and organizations do not accept it as a learning tool. Students are reluctant to enroll in elearning based courses or training programs if they are not confident that they will benefit more that traditional methods. Thus there is a need to develop a student e-learning acceptance model (ELAM). Studying the acceptance and usage of information technologies has been the focus of many studies in the literature (Davis, 1986, 1993; Katz, 2002; Selim, 2003, 2005; Venkatesh & Davis, 2000; Ward et al., 2002). There is a large number of research articles on e-learning, however few of them address the factors contributing to its acceptance. Volery & Lord (2000) identified three factors affecting the success of online education: technology (ease of access and navigation, interface design and level of interaction); instructor (attitudes towards students, instructor technical competence and classroom interaction); and previous use of technology from a student’s perspective. Soong, Chan, Chua, & Loh, (2001) identified human factors, technical competency of both instructor and student, e-learning mindset of both instructor and student, level of collaboration, and perceived information technology infrastructure as success factors of online courses. Dillon & Guawardena (1995) and Leidner & Jarvenpaa (1993) identified three main factors affect the effectiveness of e-learning environments: technology, instructor characteristics, and student characteristics. Govindasamy (2002) discussed seven e-learning quality benchmarks namely, institutional support, course development, teaching and learning, course structure, student

Research Model and Hypothesis The proposed student e-learning acceptance model (ELAM) is shown in Figure 1. As illustrated, four constructs were proposed. The instructor characteristics (INS), information technology (TECH), and organization support (SUP) were measured by five indicators. Student acceptance and usage (STD) was measured by four indicators. Students will accept e-learning if they perceive that it would help them to improve their learning effectiveness and efficiency. The INS construct assessed the elearning related instructors’ characteristics such as attitude towards elearning and students, ability to explain the e-learning course components, and the computing skills. The information technology infrastructure construct measured on campus ease if Internet access, availability of computer labs, reliability of computer networks, and the online services. The support construct included library online services reliability, the attitude towards the technical support team, the e-learning initiative support, and the computer labs technical support. According to the ELAM (shown in Figure 1), the instructor characteristics, the organization support, and the organization’s information technology infrastructure are predicting the students’ acceptance of elearning. Accordingly, the following hypotheses were proposed:

Figure 1. ELAM research model INS1

INS2

TECH1

INS4

INS

H2

INS5

STD1

H4

TECH2 TECH3

INS3

TECH

STD2

H1 H5

TECH1

TECH4

STD

SUP

TECH5

SUP1

SUP2

STD3

H6

SUP3

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H3

SUP4

STD4

SUP5

74 2006 IRMA International Conference Table 1. Demographic profile of surveyed students Item Gender

H1:

H2:

H3:

Male Female

Frequency 204 334

Table 2. Reliability and descriptive statistics of ELAM’s indicators

Percentage 37.9 62.1

Age

17-19 20-22 23-25 26-28

210 313 12 3

39.0 58.2 02.2 00.6

Years at UAEU

1-2 3-4 5-6

381 153 4

70.82 28.44 00.74

Years of e-learning

1 2 3

208 197 133

38.7 36.6 24.7

PC ownership

Yes No

474 64

88.1 11.9

The organization’s information technology will strongly affect students’ acceptance of e-learning. This means that there is a positive relationship between TECH and STD. The instructor’s characteristics will have a significant impact in determining the students’ acceptance of e-learning. This postulates that there is a positive relationship between INS and STD. The organization’s support will have a significant impact on student perception about accepting e-learning. This postulates that there is a positive relationship between SUP and STD.

The organization’s information technology infrastructure affects the instructor’s characteristics and the organization’s support. Organization’s support to e-learning initiatives affects the instructor’s characteristics. Therefore the following hypotheses were proposed: H4:

H5:

H6:

The instructor’s characteristics are affected by the organization’s information technology infrastructure. Hence, there is a positive relationship between INS and TECH. The organization’s support to e-learning is a function of the information technology infrastructure. This means that, there is a positive relationship between SUP and TECH. The instructor’s characteristics are affected by the organization’s support. This hypothesis postulates that there is a positive relationship between INS and SUP.

Participants The courses selected for the study combine both e-learning and traditional learning tools and all of them are laptop-based courses and use active and student centered learning methods. Traditional learning tools used in the selected courses are required attendance, regular textbook, and presence of instructor during the scheduled class time. E-learning tools used are electronic student-student and student-instructor communication, asynchronous course material delivered through a Blackboard (adopted course management information system) course web, in-class active and collaborating learning activities, and student self-pacing pattern. Data were collected through an anonymous survey instrument administered to 900 undergraduate university students during the Fall semester of 2002. Respondents for this study consisted of 538 (334 females and 204 males) – a response rate of 60% - undergraduate students enrolled in five 100-level laptop-based courses distributed over 37 class sections. All the selected courses were offered by the AACSB accredited college of Business and Economics at the United Arab Emirates University (UAEU). UAEU has 5 campuses located in 4 different geographical sites. Table 1 summarizes the demographic profile and descriptive statistics of the respondents. Student ages ranged from 17 to 28 years, with a mean age of 19.98 years (S.D. =1.256). Students came from 18 different middle eastern countries with different cultural backgrounds. They have an average GPA of 2.6 with a standard deviation of 0.54. Participants had 8 majors, namely accounting, economics, finance and banking, general business, management, management information systems, marketing,

Mean

S.D.

α

INS

INS1 INS2 INS3 INS4 INS5

4.00 3.92 3.94 3.86 3.89

0.99 0.97 1.00 1.02 0.98

0.91

Extracted Variance 0.68

TECH

TECH1 TECH2 TECH3 TECH4 TECH5

4.18 3.99 3.95 3.91 4.13

0.99 1.05 0.97 1.04 0.91

0.83

0.53

SUP

SUP1 SUP2 SUP3 SUP4 SUP5

4.04 3.86 3.85 3.69 3.73

0.96 0.94 0.93 1.00 0.97

0.90

0.62

STD

STD1 STD2 STD3 STD4

3.87 3.73 3.86 3.88

1.04 0.99 1.15 1.14

0.86

0.65

Construct

Item

and statistics. The exposure to e-learning technologies of the participating students varied from 1 to 3 years, 38.7% had 1 year exposure, 36.6% had 2 years, and 24.7% had 3 years of exposure. All students participated voluntarily in the study. Instrument Indicators selected for the 4 constructs were adopted from previous research. The instrument consisted of 5 sections, a section for each construct and a demographic section. The instructor characteristics construct section included 5 indicators (INS1-INS5) which assessed the characteristics of instructors (see Appendix A for the indicator details). The five indicators were adopted from (Volery & Lord, 2000). The information technology infrastructure construct was measured by 5 indicators (TECH1-TECH5). The first indicator was adopted from (Volery & Lord, 2000) and measured the ease of Internet access at the university. The other 4 indicators were developed to capture the effectiveness of the university IT infrastructure and services. The university support construct was measured by 5 indicators (SUP1SUP5). The 5 indicators were developed to measure the effectiveness and efficiency of the university technical support, library services, and computer labs reliability. The student acceptance was measured by 4 indicators (STD1-STD4). The first indicator was adopted from (Soong et al., 2001) to measure the student motivation to use e-learning. The second indicator used to measure the student’s attitude towards active learning activities that are facilitated using e-learning and adopted from (Soong et al., 2001). The last two indicators are standard information technology usage indicators and adopted from the standard TAM instrument (Davis, 1986, 1989). Some of the items were negatively worded. All items used a five-point Likert-type scale of potential responses: strongly agree, agree, neutral, disagree, and strongly disagree. The instrument was pre-tested by a random sample of 70 students. Minor changes to the order and wording of the items resulted from the pre-testers opinions. The survey instruments were distributed during lectures and were left to the students to be filled and returned later. Around 900 instruments were distributed, 538 usable responses were used giving a 60% response rate. The students were informed that all data were anonymous and were to be used in assessing the acceptance of e-learning technology at the university instruction environment. Table 2 shows the mean and variance of each item in the e-learning assessment instrument. Instrument Reliability and Validity Exploratory factor analysis (EFA) was used to detect and assess sources of variation and covariation in observed measurements (Joreskog, Sorbom, du Toit, & du Toit, 2000). The EFA was carried out using the four factors INS, TECH, SUP, and STD. Table 3 shows LISREL version

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Emerging Trends and Challenges in IT Management Table 3. Exploratory factor analysis for the survey instrument validity Item INS1 INS2 INS3 INS4 INS5 TECH1 TECH2 TECH3 TECH4 TECH5 SUP1 SUP2 SUP3 SUP4 SUP5 STD1 STD2 STD3 STD4

INS 0.810 0.818 0.858 0.829 0.820 0.032 0.035 0.052 -0.026 -0.048 -0.013 0.108 -0.001 -0.052 0.010 0.061 0.051 -0.022 -0.029

TECH 0.059 -0.010 -0.059 0.025 0.053 0.581 0.728 0.863 0.816 0.602 0.020 -0.054 0.088 0.131 -0.003 0.043 -0.001 -0.002 -0.016

SUP 0.010 0.021 0.022 0.002 0.002 0.181 -0.021 -0.062 0.082 0.081 0.790 0.844 0.721 0.798 0.776 -0.054 -0.026 0.063 0.040

STD -0.057 -0.022 0.043 -0.008 0.004 0.033 0.007 -0.040 -0.045 0.152 0.076 -0.055 0.130 -0.091 0.056 0.702 0.754 0.862 0.900

8.54 output results for the Promax-rotated factor loadings. Items intended to measure the same construct demonstrated markedly higher factor loadings (>0.50) and are shown in bold in Table 3. This testifies to the validity of the survey instrument for further analysis. Research instrument reliability is often estimated by Chronbach’s alpha (α). Table 2 shows the α values for the four constructs of ELAM. (Hair, Anderson, Tatham, & Black, 1998) suggested that the acceptable value of α is at least 0.70. As shown in Table 2, all constructs exhibit a high degree of internal consistency as the α values of the constructs are greater than 0.80. It was concluded that the indicators could be applied for the analysis with acceptable reliability. The average variance extracted, reflects the overall amount of variance in the indicators accounted for by the latent construct. The average variance extracted is more conservative than Chronbach’s alpha (α) as a composite reliability measure and its accepted value is 0.50 or above for a construct (Fornell & Larcker, 1981). As shown in the last column of Table 2, all the extracted variances are greater than 0.50. Average variance extracted can be used to evaluate discriminant validity. The square root of average variance extracted for each construct should be greater than the correlations between that construct and all other constructs (Fornell & Larcker, 1981). Table 4 shows the correlation matrix of the constructs and the square root of average variance extracted. The discriminant validity assessment does not reveal any problems.

75

Table 4. Correlation matrix of the constructs Construct INS TECH 0.825* INS 0.730* 0.423 TECH 0.384 0.607 SUP 0.389 0.495 STD * Square roots of the average variance extracted

SUP

STD

0.790* 0.468

0.810*

As suggested by (A. H. Segars & Grover, 1993), before fitting ELAM, confirmatory factor analysis (CFA) was used to examine the four measurement models associated with the four constructs. Testing of Measurement Models The measurement model of INS construct is shown in Figure 2. This measurement model yielded a chi-square statistic (χ2) of 6.33 and a pvalue of 0.18, which suggested good model fit. The observed fit measures are given in Table 5 and all of them were within acceptable levels. Figure 2 shows the estimated path coefficients or standardized factor loading, as well as the associated t-values of the INS measurement model. The t-values on significant paths are shown in bold. All coefficients were significant at p value of 0.00. The measurement model of construct TECH was examined and shown in Figure 3. A summary of the model fit measures observed for the TECH model is given in Table 5. As compared to the recommended values, all fit measures surpassed the acceptable levels suggesting a good fit. All standardized factor loadings were significant at p=0.00. The latent variable SUP measurement model was examined and yielded a good model fit. Figure 4 shows the estimated standardized factor loadings that were significant at p=0.00 and showed high validity of the measurement model. The STD measurement model is shown in Figure 5 and its fit measurements are given in Table 5 indicating good model fit. The confirmatory factor models test results confirmed the proposed 4 factors and can be used in testing ELAM with high validity and fit measures as shown in Table 5.

As illustrated in Figure 1, ELAM is a four-factor structure. INS, TECH, and SUP constructs were measured by five indicators and STD construct was measured by four indicators. All indicators are in the reflective mode.

ELAM Structural Equation Model ELAM research model (illustrated in Figure 1) was tested using LISREL version 8.54. The objective was to test the list of hypotheses and ELAM research model fit. ELAM model was evaluated for its validity using the asymptotic covariance matrix. The asymptotic covariance matrix and the weighted least squares method were used because all the indicator variables were ordinal (Jaakkola, 1996; Joreskog & Sorbom, 1996; Joreskog et al., 2000). The modification indices suggested by LISREL were taken into consideration and the standardized residuals were checked. A summary of the model fit measures is given in the last column of Table 5 in bold. The χ2 statistic indicates that the model fits the data (χ 2 = 150.37; p = 0.144 > 0.05). The ratio (χ 2 / DF) is around 1.13, which

Figure 2. Measurement model of INS

Figure 3. Measurement model of TECH

TESTING ELAM

0.42 (7.13) INS1

0.40 (6.61) INS2 0.22 (3.95)

0.25 (4.60)

0.24 (4.39)

0.41 (6.16)

0.76 (28.22)

0.58 (7.90)

0.78 (28.83)

TECH2 0.41 (5.43)

0.89 (47.15) 0.87 (46.75)

INS5

0.65 (14.09)

0.77 (19.40) 0.88 (32.26)

0.23 (3.63) TECH4

INS4 0.87 (43.44)

0.77 (22.79)

TECH3

INS

INS3

TECH2

0.70 (16.14) 0.51 (6.89) TECH2

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TECH

76 2006 IRMA International Conference Figure 4. Measurement model of SUP 0.36 (5.73)

0.37 (5.67)

SUP1

SUP2

0.28 (4.77) SUP3

Figure 5. Measurement model of STD 0.58 (9.01)

0.80 (27.25)

STD1 0.51 (7.80)

0.80 (28.09) 0.85 (36.25)

0.91 (48.11)

0.17 (3.09)

SUP

STD

STD3 0.12 (2.28)

SUP4 0.31 (5.16)

0.70 (19.56) STD2

0.83 (36.28 )

0.30 (5.27)

0.65 (17.79)

0.94 (53.10) STD4

0.83 (32.89)

SUP5

Figure 6. ELAM structural equation model Table 5. Fit measures for INS, TECH, SUP, and STD measurement models and ELAM INS

TECH

SUP

STD

ELAM

Recommended Values

6.33

6.15

4.23

0.07

150.37

-

4

3

4

1

133

-

p-value

0.176

0.105

0.375

0.793

0.144

≥ 0.05

χ2 /Degree of freedom (DF)

1.58

2.05

1.06

0.07

1.13

≤ 3.0

Root Mean Square Residual (RMR)

0.0169

0.0194

0.0144

0.0014

0.0934

≤ 0.10

Goodness-of-Fit Index (GFI)

0.9985

0.9982

0.9988

1.00

0.9929

≥ 0.90

Adjusted Goodness-of-Fit Index (AGFI)

0.9945

0.9912

0.9957

0.9998

0.9898

≥ 0.80

Normed Fit Index (NFI)

0.9961

0.9923

0.9957

1.00

0.9862

≥ 0.90

Nonormed Fit Index (NNFI)

0.9964

0.9867

0.9994

1.00

0.9979

≥ 0.90

Comparative Fit Index (CFI)

0.9985

0.9960

0.9998

1.00

0.9984

≥ 0.90

Root Mean Square Error of Approximation (RMSEA)

0.0329

0.044

0.010

0.00

0.016

≤ 0.10

Fit Measure 2

Chi-square (χ ) Degree of freedom

is below the desired value of 3.0 as recommended by the research literature (Chau, 1997; Albert H. Segars & Grover, 1998). The GFI and AGFI values are 0.9929 and 0.9898 respectively indicating a good fit. Further, RMR (0.0934), NFI (0.9862), NNFI (0.9979), CFI (0.9984), and RMSEA (0.016) are all within the acceptable levels. The estimated parameters and the corresponding t-values of the final research model appear in Table 5 and Figure 6. The results indicate that the explained variance of ELAM instructor characteristics (INS) is 0.32 and of university support (SUP) is 0.51. ELAM research model as a whole explains 0.45 of the variance in e-learning acceptance by students. As illustrated in Figure 6 and Table 6, all the direct paths between the construct pairs are significant. The university information technology infrastructure (TECH) had a significant direct and indirect impacts on students’ decision to accept e-learning (STD). As shown in Table 6, the direct effect of IT infrastructure on students’ acceptance of e-learning was 65% of the total effect with a regression coefficient (β) is 0.416 and a t-value of 5.77 with p< 0.0004. The indirect effect of TECH on STD, which is mediated through SUP and INS, is also significant at β=0.223 with t-value of 4.33 and p< 0.0004. Both direct and indirect effects generated a significant total effect of 0.639 with t-value of 13.73 and p= 0.0000. Therefore, the hypothesis H1 is supported, which means that students’ acceptance of e-learning (STD) is significantly affected by the university information technology infrastructure (TECH). The second hypothesis H2 is also accepted because the direct path INSèSTD is significant with β is 0.164 with t-value of 3.39 and p< 0.0004 (as indicated in Table 6 and Figure 6). This result indicated that the students’ decision of accepting e-learning is positively related to the instructor’s characteristics (INS). The total effect of the university support (SUP) on students’ acceptance is significant at β=0.223 with t-

INS (R2=0.32)

0.39** (6.40)

0.22* (3.45)

0.42** (5.77)

TECH

0.71** (19.71) * significant at p < 0.0004 ** significant at p = 0.00000

0.16* (3.39)

STD (R2=0.45)

0.19* (2.65)

SUP (R2=0.51)

value of 3.12 and p-value< 0.0004 which satisfies H3. The direct effect is 84% of the total effect whereas the indirect effect contributes 16% to the total effect. This clearly shows that the e-learning acceptance is significantly dependent on the instructor’s characteristics. The direct path (which represents 72% of the total effect) TECHèINS is significant since its β is 0.392, t-value of 6.40 and a p-value < 0.0004. The indirect effect of TECH on INS, which is mediated through SUP, represented 28% of the total effect and is significant at p 900 P erson s

2002

2003

O rg an izatio n a l in n ov ation s: 1 99 7 : first b ig p ro ject 2 00 1 : stra teg y con vergenc e 2 00 3 : com pan y reco g nised o n the m ark et a s realizin g th e b ig p rojects

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Emerging Trends and Challenges in IT Management competences of Transsystem by the company’s customers in 2003, respectively. Switching from traditional development strategy to the convergence strategy allowed the company to apply project-oriented management. The new strategy is visible in Transsystem’s present organization (now, there is a controlling committee and a project management office with the board of directors’ plenipotentiary for the projects issues), new methods of projects’ realization, new standards of directorship’s and project teams’ work. Figure 4 presents an organizational schedule of Transsystem S.A. after the transformation (project management office’s tasks included). Worth noticing is the fact that the traditional and ebusiness tasks are not separated in the organizational structure. The traditional and the IT using cells are integrated completely. Very important is the role of IT which uses the Intranet and the Internet. In the Intranet’s structure there is the management informing system – MIS. In Transsystem, the MIS was installed on the base of data warehouse and is the infrastructure for the convergence strategy. Apart from presenting complete data concerning the company and allowing communication in the network neighborhood, the MIS can also present information about different projects and processes. It is a vital instrument, as it supports the firm’s directorship in such projects as: analyses comparing the accounting periods, economic value added – EVA, portfolio analyses, trends’ analyses, evaluating projects by scaling, resources planning, costs’ account analyses, ROI or cash flow. At the level of individual project, the MIS allows analysis of profitability, deadlines, costs and budget variance. In addition, the Internet allows communication between the clients and the firm, both sides being involved in the firms’ projects and business processes. Not only did the convergence strategy improve the company’s economic measures but also turned it into a project orientated one. In consequence of the convergence strategy’s introduction, the company’s structure became more flexible, the workers’ entrepreneurship and self-reliance and the money claims’ management all improved. Moreover, the company’s growth barrier was defeated, as it acquired tools, which helped to manage numerous tasks at the same time. Both suppliers and clients could from then on join the projects’ realization processes. Realizing a strategic goal which was strengthening the firm’s competitive position effected in: • •

The firm becoming a leader in the field of provided services on the Polish domestic market (more than 40% of market share). Almost 30% of shareholders being key foreign clients.

Figure 4. Organizational chart of Transsystem Inc company CONTROLL COMMITTEE

THIS IS BOARD AND LINEAR DIRECTORS

BOARD Subordination to Project Manager: TIME LIMITS -BUDGETS, - SCOPE PROJECT OFFICE

CLOSING COMMENTS As we intended to prove, the convergence strategy is an effective one according to small e-business and t-business companies’ workers and directors. Nevertheless, it may not be beneficial for many traditional companies which have stable positions on some local markets. The most expected effects of this strategy are: gaining new clients and improving the economic rates. The costs connected with adopting the convergence strategy and starting e-business activity in particular are the main small firms’ apprehensions. As far as the convergence strategy’s results for medium companies are concerned, it is unambiguous that they should adopt it, if plan to compete and develop. The example of Transsystem S.A. proves it. As the experience and the theoretical analyses have showed, only successful introduction of the IT allows the introduction of the convergence strategy, therefore, competitiveness growth and debut on world markets.

REFERENCES J.A. Champy: (2002), X-Engineering the Corporation. Reinventening Your Business in the Digital Age. Warner Books Inc. N-Y Data Monitor. (2003): eBanking Strategies in Europe; www.datamonitor.com J.A. Kisielnicki, ., ed. (2002); Modern Organizations in Virtual Communities, IRM Press, Hershey, London J. A. Kisielnicki, S. Sroka (2005): Company Transformation as a Precondition for Becoming a Player on the Global Market, The Application of Re-engineering and X-engineering approaches in Transsystem S.A. Co in: Managing Modern Organization with Information Technology, Idea Group Pub. San Diego F.Pigini; P.Faverio; J.Moro; G. Buonamno;( 2004) Information and Communication Technologies and Small – Medium Enterprise in Innovations Through Information Technology, Idea Group Pub., New Orleans P. Sutherland; F.B. Tan ,(2004): The Nature of Consumer, Trust in B2C Electronic Commerce: A Multi Dimensional Conceptualism in Innovations Through Information Technology, Idea Group Pub., New Orleans A. J. Strickland, John E. Gamble, Arthur A. Thompson; ( 2005); Strategy: Winning in the Market place:, 2nd Edition , Irwin Professional Pub , 2005 H.Timmons (2000): Online Banks Can’t Go It Alone, Business Week, 31st July

ORDER

Advises

Total subordination to Project Manager. - disciplinary, - functional -professional -time limits -budgets

It is important for the organization to preserve the adopted transformations without loosing the flexibility needed for other crucial changes. On the one hand, the new organizational structure has got appropriate formal standards which include the TQM. On the other, however, the company needs to maintain the entrepreneurship favoring organizational culture. The IT infrastructure based on the Internet, the Intranet and the MIS is an inevitable tool of the convergence strategy’s use and monitoring.

LINEAR MANAGEMENT

PROJECT DEPUTY

Order

Documentation, Administration. Correspondence Accounting Project Management Norms Standards Formulars Employer for Project Managers

DESIGNING

PROJECT NR 1 MANAGER PROJECT TEAM

PROJECT A PROJECT PROJEKT NR 12 KIEROWNIK MANAGER PROJECT ZESPÓ£ TEAM

PRODUCTION

MATRIX ORGANISATION

81

PROJECT B MATRIX ORGANISATION

ASSAMBLIES

Advise

Subordination to Linear Manager: - discipline, - professionalism - functional

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82 2006 IRMA International Conference

Gender Discrimination in IT Salary: A Preliminary Investigation Jing ‘Jim’ Quan, Dept of Information & Decision Sciences, Perdue School of Business, Salisbury University, 1101 Camden Avenue, Salisbury, MD 21801, P (410) 543-6514, [email protected] Ronald Dattero, Dept of Computer Information Systems, Southwest Missouri State University, 901 South National Ave., Springfield, MO 65804, [email protected] Stuart D. Galup, Dept of Information Technology & Operations Management, Florida Atlantic University, Reubin O’D. Askew Tower, 220 SE 2nd Avenue, Fort Lauderdale, FL 33301, [email protected]

ABSTRACT Although over the past 25 years the gender pay gap for full-time workers has been dramatically narrowing, the gap remains wide in the IT industry. Why does such a gap persist and is the gap really gender related? A set of major factors for determining salary differentials has been identified by previous studies. Incorporating these variables in an integrated model that include a gender variable and various interaction terms, we examine whether wage discrimination based on gender for System Administrators exists. Our results indicate that after all major factors that may affect salary differentials are considered, gender is still a major significant factor in explaining such differentials.

INTRODUCTION Over the past 25 years the gender pay gap for full-time workers has been dramatically narrowing, Blau and Kahn (2000). A recent survey on IT professionals by InformationWeek (2005), however, finds that the gender gap remains wide in the IT industry. The survey reveals that women, on average, receive about $9 for every $10 men earn in wages and bonuses. Why does such a gap persist? Is gender a significant contributing factor for explaining the gap? Or the gap can be explained by differences in other factors than gender such as education, experience, industry type and geographic locations alone? The answers to these questions are of great interest to not only academic researchers but companies’ global competitiveness in the wake of the current labor shortage in the IT industry, Ahuja (2002). Various studies have attempted to identify the drivers behind salary differentials between females and males in the IT field. Truman and Baroudi (1994) focused on senior Information Technology (IT) managers. They found that factors such as job level, age, education, and work experience were important in explaining the differentials. In a study conducted by Bertrand and Hallock (2001), the top 5 executives in 1,500 of the largest publicly traded firms tracked by Standard and Poor’s were surveyed. Their analysis revealed that company size, age and seniority were the critical factors. In addition to the factors identified by the previous studies, human capital theory (Mincer (1957, 1958, 1962), Schultz (1960, 1961), and Becker (1962, 1964) emphasizes two other factors: experience and education. It is obvious that a more experienced person would earn more than a less experienced one. For example, pay increases consistently with seniority. The human capital implications of education are a wellknown and straightforward extension of Smith’s idea of equalizing differences (Berndt 1991, p. 154). Educated workers are more produc-

tive than their less educated counterparts and thus are more likely to command higher wages. This also provides an economic explanation as to why a person will forego earnings and incur additional expenses to undertake an education, since their efforts will result in substantially more compensation in the long run. Two other well known variables, although not well documented in academic research, are geographic location and industry type. In general, wages are vastly different across regions and industries. For example, the same InformationWeek (2005) survey reveals that IT wages increased in San Francisco, Portland (in Oregon), and Philadelphia while they fell in Houston, Washington, D.C., and Atlanta. Bernard et al. (2004) finds that relative wages vary considerably across regions of the United Kingdom and increases in the employment share of skillintensive industries are greater in regions with lower initial skill premium. In summary, a set of variables are identified by various studies as determinants for wages. As a natural extension, these variables can be used to study IT wages. The question remains whether the gender variable still plays a role after all factors are taken into consideration. If it does not, this would suggest that wage differentials between males and females can be explained by other factors than gender. If the gender variable is found significant, this would suggest the existence of discrimination by gender. This paper aims to answer this question by proposing an integrated model that includes all important wage determinants identified by previous research and a gender variable. We select one segment of the IT workforce: network and system administrators. The rational behind such a narrow focus is threefold. First, it is the most prevalent segment of the IT workforce. Second, the segment represents middle levels of IT management professionals. By focusing on a segment other than top IT management, we can contrast our results with those of the other research. Third, by selecting a sole occupation in the study minimizes the compounding factor of the crowding by occupation, Solberg (2005). The remainder of this paper is organized as follows. First, the research model and hypotheses are presented. This is followed by the description of the data set and discussion of the estimation results. Finally, managerial implications and conclusion remarks are provided.

RESEARCH BACKGROUND AND FRAMEWORK From the human capital theory point of view, the wage differences among workers are due to their differences in levels of education and experience. Human capital theorists believe that education represents

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Emerging Trends and Challenges in IT Management an investment. By going to school, one has to incur both direct costs in the form of tuition and opportunity costs in the form of forgone earnings. In order to make up for the losses, workers that have attained additional education must be compensated, by the market, by sufficiently higher life-time earnings, Mincer (1957, 1958, 1962), Schultz (1960, 1961). This is validated by a 2004 census report released by the US Census Bureau stating that workers of 18 year old or older and with bachelors degrees earn an average of $51,206 a year, while those with a high school diploma earn $27,915. Workers with an advanced degree make an average of $74,602, and those without a high school diploma average $18,734, Census Bureau (2004).

Figure 1. Research framework HCM Factors: EDU EXP

In another study, Truman and Baroudi (1994) focused on the senior managerial ranks of the information systems (IS) occupation. Using data gathered by the Society for Information Management (SIM), they found that the average salary for women IT managers was considerably lower than males even when controlling for job level, age, education, and work experience. They concluded that IS may not be immune to the problems of gender discrimination. In addition to the aforementioned factors, geographic locations of firms and industry types are found to play important roles in determining diversity in salaries by Bernard et al. (2004). In general, the divergence in price levels across different parts of the country determines the salary differentials. For example, an IT professional would make much more money in Silicon Valley than in Florida. According to a government estimate USDOL (2004), the average annual wages in 2004 for Computer and Mathematical Science Occupations were $57,960 in Florida and $74,060 in California. Industry types are also an important factor. For example, the average wage for computer programmers was $69,000 in Internet Services industry while $47,000 in Distributor/Wholesale industry according to a survey done by an online job site dice.com. In summary, previous theories, studies, and surveys have indicated that education, experience, firm size, seniority, age, job rank, geographic location, and industry type are important wage differentiators. We propose our research question: After taking into consideration all these variables, do a gender variable and its interaction with the other variables still have significant explanation power in determining wages? An affirmative answer to the above question confirms existence of gender discrimination. If none of the gender related variables is significant, however, one can conclude that all the wage divergence is explained by variables other than gender. Therefore, wage differences cannot be attributed to gender. Based on the discussion above, we present our research framework in Figure 1. In the framework above, we include not only a gender variable but interaction terms between gender and location, industry type, firm size, employee’s age, seniority and rank. The rational for the inclusion of the interaction terms is to discern any location- and industry-related gender discrimination. Specifically, even if the gender variable is found insignificant overall, wage discrimination based on gender can still be found in different regions and/or industries. In addition, such an inclusion helps

Gender

Bertrand & Hallock: Size Seniority Truman & Baroudi: Age Job level (rank)

Salary Differentials

Geographic Location South/NE/West/ Mid-West Industry Classification FIN/GOV/etc.

Another human capital factor is experience. Experience from the general on-the-job training enables a worker to acquire extremely versatile skills that are equally usable or salable across firms and industries. This skill acquisition, in turn, increases the worker’s productivity at any task. The competitive market dictates that she/he will be paid at a higher rate accordingly, Mincer (1957, 1958, 1962), Schultz (1960, 1961). Of previous studies on gender discrimination, two are relatively significant. Using a survey on the top 5 executives in 1,500 of the largest publicly traded firms tracked by Standard and Poor’s, Bertrand and Hallock (2001) showed that the fact that women managed smaller companies and were less likely to be CEO, Chair, or President of a large corporation can explain as much as 75% of the gender gap in salary for top corporate jobs. Adding other variables, such as age and seniority, to their model, the unexplained 25% gap fell further to only 5%.

83

answer questions such as whether older or higher ranked female workers are discriminated and whether female employees are better off working for large firms or small ones.

DATASET The dataset we use in our analysis is from a voluntary web-based survey on salary and skills of IT workers that was conducted by Dice Incorporated, one of the largest on-line job placement companies. The time period is from June 7, 2000 to April 13, 2001. Among the 38 different job titles, we selected Network Manager and Systems Administrator to test our model. After any problematic data was removed (see appendix for data treatment), our sample size is 2,103. Since technical experience is reported in levels rather than in years, it is scaled as follows: (1) 0.5 for less than 1 year, (2) 1.5 for 1-2 years, (3) 3.5 for 3-5 years, (4) 7.5 for 6-10 years, (5) 12.5 for 11-14 years, and (6) 17.5 for more than 15 years. By the same principal, the highest education level attained is scaled into education in years as follows: (1) 12 for High School, (2) 14 for Military, (3) 14 for Vocational/Tech School, (4) 14 for Some College, (5) 16 for College Grad, (6) 18 for Master’s Degree, (7) 20 for Doctoral Degree, and (8) 20 for Professional Degree (MD, JD).

MODEL Human capital theory suggests that the earning function is concave in experience with earnings peaking somewhere in midlife. It is also suggested that instead of using annual salaries, the hourly salary rate should be employed, Berndt (1991). We calculate the hourly salary based on the reported annual salary and average number of hours worked per week. Hence, we propose our model as follows: log Y = α + β1(edu) + β2(exp) + β2(exp)2 + Σπ(dummy) + Σρ(interactions) + ε (1) where dummy variables include: • • • • • •

Gender: female; Industry: Finance, IT, Government, Manufacturing, Medical, Retail/Wholesale, Transportation. Others are used as the base; Age: younger than 40; Size: small (1-99) and medium (100-999). Large (>1000) is used as the base; Seniority: less than 5 years in the current position; Geographic locations: West, Mid-West and Northeast. South is used as the base.

Interaction terms are between gender and all other indicative variables.

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84 2006 IRMA International Conference RESULTS

DISCUSSION AND CONCLUSIONS

Table 1 reports the estimation results. The model fits well with the human capital theory. As expected, the signs for Edu and Exp are positive and the sign for Exp2 is negative. The estimated coefficients for these three variables are 0.036, 0.047 and -0.002, respectively, and all are significant at the 1% level. Of the estimates coefficients for industries, the ones for Manufacturing, Medical, Retail/Wholesale and Transportation are not significant. The ones for IT and Finance are significant at the 1% level while the one for Government is at the 5% level. When compared to other industries, Network and System administrators are paid the most in IT (0.140), next in Finance (0.106) while making less in Government (-0.076). Firm size is also important in determining Network and System administrators’ pay. They are better off working for large organizations. They are paid less (-0.065) in medium companies and even worse (-0.128) in small ones. Both estimates are significant at the 1% level. For those who are in their current positions for 5 years or less, they are paid less (-0.088) than those who have more seniority. This estimate is significant at the 1% level. Our findings in terms of size and seniority are consistent with those by Bertrand and Hallock (2001). In terms of geographical locations, the West (0.115) and Northeast (0.105) regions are better places for Network and System administrators than the South. Both estimates are significant at the 1% level. Meanwhile, the Mid-West region is not significantly different from the South. None of the interaction terms are found significant.

This paper aims to develop a generalized model that can be used to determine whether salary differentials are based on gender. This model includes all possible variables identified by previous research as contributing factors to the wage gap. We estimate the model using data on one of the most predominant jobs in the IT field: Network and System administrators, obtained from an internet job placement website. Our results reveal that that after all major factors that may affect salary differentials are considered, gender is still likely a contributing factor.

After all the possible causes for explaining salary differentials are considered, the gender variable is still found negative (-0.142) and significant at the 10% level (p=0.0887). This suggests that gender itself is responsible for explaining some of the wage gender gap when controlling the other factors. Hence we conclude that it is likely that gender discrimination exists. That is, all things being equal female Network and System administrators are paid less than their male counterparts.

Table 1.

Estimation results

Coefficient Intercept Edu Exp 2 Exp Female Industry Indicators Finance IT Government Manufacturing Medical Retail/Wholesale Transportation/Utilities Age: Under 40 Years Old Firm Size Indicators Small (1-99) Medium (100-999) Tenure: Less than 5 Years in Current Position Region Indicators West Midwest Northeast Industry Interaction Terms with Female Finance IT Government Manufacturing Medical Retail/Wholesale Transportation/Utilities Age Interaction Term with Female Firm Size Interaction Terms with Female Small Medium Tenure Interaction Term with Female Region Interaction Terms with Female West Midwest Northeast Overall model p-value < .0001 2 Adj. R = 0.174 Notes: a Significant at the 1% level b Significant at the 5% level c Significant at the 10% level

Estimate a 2.350 a 0.036 a 0.047 a -0.002 c -0.142

Pr > |t|

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Emerging Trends and Challenges in IT Management Figure 2. Entity/Object interaction diagram

C us tom er

C loakroom Attendant

H ead Waiter

Waiter

659

Step-4. Identify the business entities and interactions with the business workers/actors. In this example, by looking at the story board Fig.1 we can identify the explicit business entities. The object interaction diagram (refer Fig. 2) displays the entities that are manipulated or created. Song et al [Son04b] present a detailed method for identifying objects in the use case descriptions and process summaries.

Kitchen Staff

Business entities identified: Token, Seating plan, Menu, Order, bill, transaction register Step-5. Aim for process innovation by categorizing task and information flow: Token

Seating Plan

Menu

Or der

Bil l

R egis ter

Step-2. Identify internal processes that would support the externally visible business process: a) Generate a process flow for the business process (order food); b) Document this process using a business use case template. For our example problem [Jac94] we choose the “order food” business use case for detailed analysis. The illustration (Fig.1) is optional and can be substituted with a process summary. Other visualizations like process flow diagrams can also be used. We chose story boards because they are simpler to illustrate and does not require much training. A detailed business process description is captured using a business use case template shown in Table 2, which has been derived from a system use case template. “BUC#” field would help in linking a business use case template to a system use case template at a later stage (Step 7) for addressing the traceability issue. The BUC template helps in separating business actor actions from business system actions. The new tags shown in the business template is to show how the business use case template differs from a system use case template [Son04a]. Step-3. Assign roles to the tasks identified in Step-2: Develop a sequence diagram to show assignment of tasks. Step-2 helped in identifying business workers who are internal to the business use case. In Step-3 we map the activity (in Table 2) to the roles as follows: Head waiter: Assign Table, Assign table waiter; Cloak room attendant: Check in coat, Check out coat; Table Waiter: Present Menu, Take order, Place order, Compute bill, Process payment; Kitchen Staff: Notify waiter, prepare order.

a) Task flow categorizations involves making decisions about tasks that could be automated, computer-supported, or manual, b) Generate a system sequence diagram [Lar05]. This step has a degree of subjectivity involved because the choice to automate something has to be justified from a business stand-point, and a technical/systems stand-point. The new design should aim to make the business process more efficient and effective. The systems sequence diagram shows which activities can now be displaced/delegated to the external computer system. This would help in visualizing the system input and also in identifying system actors in the system use case diagram. Step-6. Develop a system use case diagram: a) The system actors can be identified from the system sequence diagram, b) The actor goals are represented by the system use cases in the use case diagram. The system sequence diagram reveals candidate actors for the system being designed. The tasks being accomplished by the system become system use cases in the use case diagram. System actors –and actor goals Head waiter- Assign waiter, Assign table, Customer- Process coats, Kitchen Staff -Fulfill orders, Waiter- Process order. Step-7. Develop a system use case description for the use cases identified from the business use case: a) Use the system use case template for documentation. b) Do not name the system till other business use cases have been translated. It might yield additional system use cases. A system use case template is used to document the system functionality. An additional field (Row 3, Table 3) is included to link this system use case to the source business use case. This helps in ensuring traceability.

Figure 3. System sequence diagram for new business process

Customer

Cloakroom attendant

Head waiter

Waiter

Possible system

Kitchen staff

Check in coat Assign table Assign waiter

Place order

Fulfill order

Process payment

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660 2006 IRMA International Conference Figure 4. Partial System use case model based on one business use case System boundary

Fulfill order Assign Waiter

Update availibility Head Waiter

Kitchen Staff

Assign table

Process order Process Coats

Waiter Customer

Table 3. System use case template [Son04a] USE CASE #

SUC 1.0

USE CASE Name

Process order

Derived from Business use

BUC 1.0

case

New New

ACTOR Purpose (1 phrase) ……………..

……………….

…………………

……………………

Creation Date Other comments

4. CONCLUSION In this paper we presented a method for translating a business use case into system use cases. This approach helps traceability of requirements. We presented a technique for documenting the business use case using a business use case template derived from the system use case template. UML 2.0 diagrams were used to represent the operationalization of the steps. Future research would involve testing the 7-step method in terms of perception and performance [Moo03] in multiple domains, by analysts with varying levels of expertise to validate its effectiveness. We would like to mention that some amount of subjectivity exists in what is automated and what is not. This can at times significantly change the final output of the method.

REFERENCES [Cur92] Curtis, W., Kellner, M. I., and Over, J., (1992) Process Modeling. Communications of the ACM, Vol. 35, No. 9, pp. 75– 90. [Fow97] Fowler, M. (1997) UML distilled, Addison-Wesley [Gia01] Giaglis, G.M. (2001) A taxonomy of business process modeling and information systems modeling techniques. International Journal of Flexible Manufacturing Systems, 13(2): 209-228. [ Jac92] Jacobson, I., et al.(1992). Object oriented software engineering: a use case driven approach. Wokingham UK: AddisonWesley. [Jac94] Jacobson, I., Ericsson, M., Jacobson, A. (1994). The Object Advantage, Business Process Reengineering with Object Technology, Addison-Wesley Publishing Company. [Kru03] Krutchen, P (2003) The rational unified process an introductions. Addison-Wesley [Kav04] Kavakli, E. (2004) Modeling organization goals: Analysis of current methods, ACM Symposium on applied computing. [Lam01] van Lamsweerde, A. (2001) Goal oriented requirements engineering: A guided tour in the 5th IEEE international symposium on requirements engineering. RE’01. Toronto: Springer [Lar05] Larman, Craig. (2005). Applying UML and Patterns: An introduction to object oriented analysis and design, Upper saddle River, Prentice Hall [Ng 02] Ng,Pan-Wei (2002) Effective Business Modeling with UML: Describing Business use Cases and Realizations from http://www128.ibm.com/developerworks/rational/library/905.html [Oul 95] Ould M.A,(1995) Business processes- Modeling analysis for re-engineering and improvement. John Wiley and Sons. [RUP] Jacobson,I et. al (1999) The unified software development process, Reading MA: Addison Wesley. [San02] Santander, V. and Castro, J. (2002). Deriving use cases from organizational modeling. In Proceedings of the IEEE Joint International Conference on Requirements Engineering, pp.32– 39, Essen, Germany. [Son04a] Song, I. (2004). Object oriented analysis and design using UML: A practical guide. Lecture notebook, Pearson Custom Publishing. [Son04b] Song, I. et al (2004). A taxonomic class modeling methodology for object oriented analysis. In J. Krogstie et al (Eds.), Information modeling methods and methodologies , Idea group publishing. [Vas01] Vasconcelos, A., et al. (2001). A framework for modeling strategy, business processes and information systems from http:/ /ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=950424 [Yu93] Yu, E. (1993) Modeling organization for information systems requirements engineering., Proc Re’93, IEEE, pp. 34-41 [Yu97] Yu, E. (1997) Towards modeling and reasoning support for early phase requirements engineering. Proc. RE’97 3 rd international symposium in requirements engineering, Annapolis, pp. 226235

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Emerging Trends and Challenges in IT Management

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The Open Sources Education: A Real Time Education Tadeusz Krupa & Teresa Ostrowska Warsaw University of Technology, Narbutta 85, 02-524 Warsaw, Poland, T: +48 022 8499443, F: +48 022 8499798, {tkrupa, tmostrowska}@op.pl

ABSTRACT The Open Sources Education (OSE) is both an idea and a platform which entirely originates from Poland and is an unique method of succoring the didactic process by a network of academic Virtual Education Centers (VEC) using the Internet. The OSE is an initiative which has arisen while applying the e-learning techniques on daytime, evening and extramural studies of the Management and Marketing course at Faculty of Production Engineering, Warsaw University of Technology. The OSE, with the aid of Internet, can support the didactic process: the traditional course mode classes and the real time led teamwork classes. The article presents: the Open Sources Education idea, institutions, universities and platforms involved in e-learning, eStudent platform, VEC network, VEC development perspectives, VEC users’ instructions and some license restrictions.

system enables succoring the didactic process to all groups of users - the students, the lecturers and the administrators - in simple and friendly way, without any restrictions connected with the subjects, specifications and content. OSE platform creates IT technical environment called eStudent, compiled by PMP IT Consulting Co., available on the web site: www.eStudent.edu.pl The mission of the Open Sources Education is to create the international education platform using new IT technologies which enables: •

•

INTRODUCTION The persistent teaching and the distance teaching have become stigmata of modern societies’ education. The e-learning, that is teaching with the use of computer medium, is a challenge for the higher education and the world economy, which business necessities are: the working profile change and the workers’ training. 1 It can be realized in various ways: from presenting the course materials on optic discs, through advanced training courses in computer workrooms and under professional supervision, to student’s remote work via Internet. How can the Internet be used more effectively in the field of academic education? While, on the one hand, we can imagine a number of elearning’s limitations, on the other, we know that currently there is no better medium to be used for distance teaching. 2 Let us try to look at the new approach and the possibilities that are offered by the simple idea of The Open Sources Education realized in the academic environment.3 The Open Sources Education is intended to be the solution for the complexness and poor availability of educational platforms and high costs of traditional didactic classes organization. What is more, according to the experts, preparing a multimedia version of 1 hour of traditional course requires from 30 up to 100 hours of work. However, the OSE’s main matters of concern are students and lecturers’ efficiency and dynamics, and not the issues of the informational interface’s ergonomics.

THE IDEA OF THE OPEN SOURCES EDUCATION OSE is a new concept of breaching the barriers between lecturers and students. Therefore, it aims not at replacing the didactic cadre with sophisticated internet technologies, but, on the contrary, at strengthening lecturer’s position by providing him with simple and intuitive tool for communication with the student. The Open Sources Education (OSE) is both an idea and a platform which entirely originates from Poland and is a unique method of succoring the didactic process by a network of academic Virtual Education Centers (VEC) using the Internet. The OSE is an initiative which has arisen while applying the e-learning techniques on the daytime, evening and extramural studies of the Management and Marketing course at the Faculty of Production Engineering, Warsaw University of Technology. OSE

•

developing the traditional form of education and trainings by unlimited access to education content for everyone who wants to self-educate or complete the knowledge, equalization of the educational chances for people from different environments and regions including disabled people through the easy communication with the high schools and universities’ scientific personnel, unlimited access to the technical knowledge and to the regional and companies’ occupational improvement systems.

Development of the Open Sources Education (OSE) - follows on non profit conditions, because of its social, culture and civilization range. OSE system and its eStudent platform are available for free mainly for those who proclaim their education services also for free. About 1/3 costs of designing of the OSE system is covered by the didactic activity with the commerce characteristic (paid studies and courses) and by international private and state universities programs, and by the training services and also by postgraduate studies conducted for big companies and finance institutions, which are using in their educational process the eStudent platform. The other costs on development and exploitation of the eStudent platform are received from sponsoring organizations - the list of them you can find below4,5,6 - and from the work of enthusiasts of Open Sources Education idea: the students, doctor’s studies students and universities employees.

UNIVERSITIES, INSTITUTIONS AND PLATFORMS SUPPORTING THE E-LEARNING Nowadays, the e-learning and real time led studies issues are important matters of concern for: universities, international organizations and producers of technological platforms. To illustrate this tendency, chosen examples, Polish mostly, are presented below. Universities: •

•

•

AGH University of Science and Technology - Distance Education Study Centre (DESC). E-address: www.oen. agh.edu.pl National Technological University – NTU Network – a virtual university awarding master’s degrees in key management, technical, and engineering disciplines. The NTU arose in 1984 as a network of 7 universities supported by: IBM, Motorola and Hewlett-Packard. At present, it is a consortium of 52 American universities. E-address: www.ntu.edu/index.asp NETTUNO – Network Del L’Universita Ovunque - a consortium of 32 universities, RAI and TELECOM Italia, created in

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662 2006 IRMA International Conference

•

•

• •

1990 for distance education at academic level. The universities, which form the consortium, create inner centers that test, consult, lead diplomas and produce didactic materials for the use of the educational portal. E-address: www.nettuno.stm.it Warsaw University of Technology – Distance Education Centre. Since academic year 2001/2002 it coordinates the recruitment and the realization of the Extramural Distance Engineering Studies. There are faculties of: Electronics, Electronics and the Information Technology and Mechatronics, and specialties in: Industrial Informatics, Computer Enginery, Multimedia Techniques and Mechatronics. E-address: www.okno.pw.edu.pl Warsaw University of Technology – Institute of Production Systems Organization – The Open Sources Education – eStudent Platform. Since October 2003 the network of Virtual Education Centers was built. At present it consists of 12 establishment groups from public and private, technical and economic universities. E-addresses: www.estudent.edu.pl, [email protected] Warsaw School of Economics – www.e-sgh.pl platform. Mailto: [email protected]. Warsaw University – Open Multimedia Education Centre. E-address: www.come.uw.edu.pl

Institutions: •

•

•

•

AACE – Association for the Advancement of Computing in Education is an international organization, premises in Norfolk, USA, which was established in 1981. AACE distributes information about the possible IT uses in the educational process. E-address: www.aace.org EADL – European Association for Distance Learning. Offering more then 4000 different courses, it associates: EU countries, Iceland, Russia, Switzerland and Turkey. E-address: www.eadl.org EDEN – The European Distance Education Network. It is a non-governmental association of European universities, corporations and individuals that operate in the field of distance education. E-address: www.eden.bme.hu Virtual Polytechnic. Established in 2003, VP is an organization that associates 7 Polish Universities of Technology: AGH University of Science and Technology and polytechnics from: Bialystok, Gdansk, Cracow, Poznan, Wroclaw and Warsaw. The Virtual Polytechnic aims at equalizing the traditionally passed subjects with the ones passed via Internet. 7

eSTUDENT PLATFORM - VIRTUAL EDUCATION CENTRES NETWORK The Open Sources Education platform is formed by an IT environment named eStudent, developed by the PMP IT Consulting Co., available at the page: www.estudent.edu.pl The eStudent internet platform enables opening and maintaining a Virtual Education Centre (VEC) at any academic organization. VEC can be established within two licenses: •

•

The Virtual Education Centers network (VEC network) is formed by each and every VEC registered on the eStudent platform, within public or commercial license, by didactic workgroups members or administrative units which represent them (Fig. 1). A single VEC structure consists of: • • • • •

•

•

•

WTB platform of Digital Spirit co. The platform contains 2 programs: WBTExpress 3.0 and WBTServer 3.1. E-address: www.digital-spirit.pl ReadyGo! platform of Mindworx co. is a specialist application meant to prepare trainings for e-learning systems. Eaddress: www.readygo.com Lotus Learning Space platform. It is a scalable software and hardware unit securing backup for complex training projects. Learning Space Core and Learning Space Collaboration modules operate both asynchronous and group teaching mode. E-address: www.pugh.co.uk/products/lotus eStudent platform. This platform arose as a result of PMP IT Consulting Co. and Institute’s of Production Systems Organization collaboration. It enables: defining the lecture’s structure and content (texts, formulae etc.), inserting graphics (schedules, maps, schemes, plans) or video animations, inserting audio commentaries (lecturer’s remarks concerning the teaching material), defining questions and answers for tests and examinations, browsing the students’ activity reports. E-address: www.estudent.edu.pl

VEC coordinator (one or more persons, depending on the needs), VEC lecturers (approximately from 10 to 75), VEC students (no limits), Subjects (1-5 subject units for single lecturer), Technological sources of the eStudent platform, available for educational purposes and for VEC structure remote managing.

One can candidate for the position of VEC lecturer by filling a registration form in agreement with the coordinator of the proper VEC. Furthermore, the registration process is realized automatically. Applying for the position of VEC coordinator looks analogically. Below is the list of exemplary existing VEC, which are well developed or being extended. Current VEC list: • • • • •

Platforms: •

public license - for universities and high schools units, and for the charitable organizations conducting the honorary educational activity, commerce license - for high schools and universities units conducting paid educational activity and for the trainings destination in the big and medium companies and also in the financial institutions.

• •

Center for Industrial Ergonomics - University of Louiseville, USA, Faculty of Economics and Management - R. Lazarski Higher School of Commerce and Law Faculty of Electronics - Koszalin University of Technology, Institute of Manufacturing Technology - Warsaw University of Technology, Institute of Production Engineering - Opole University of Technology, Institute of Production Systems Organization - Warsaw University of Technology, IT Division - Radom University of Technology, Logistic of Marketing Division - Faculty of Management and Production Engineering - Opole University of Technology.

Figure 1. The idea of Virtual Education Center network – students and lecturers

VEC

VEC

VEC

VEC

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VEC

Emerging Trends and Challenges in IT Management DEVELOPMENT OF THE ESTUDENT PLATFORM FUNCTIONAL ABILITIES

•

What determines the efficiency of the eStudent platform, is its tight relation with the academic environment, in which it has arisen and developed being observed and constantly upgraded. Development of the eStudent platform functional abilities follows 5 perspectives:

• •

•

• • • •

• • • •

organizational perspective (division of competences in the Open Sources Education system), operational perspective (operating the eStudent platform’s informational interface – Fig. 2, Fig. 3), editorial perspective (content processing and input managing), didactic perspective (subject, lecture, test, exam, knowledge base and paraphernalia base structure), communicational perspective (individual and team work, student ⇔ lecturer ⇔ coordinator ⇔ administrator communication).

Organizational perspective: • • • •

• • •

in the system there are students, lecturers, coordinators and administrators, student executes lecturer’s tasks within the subjects he has enrolled on, coordinator has an electronic register of students, lecturers and subjects, coordinator registers: students into student groups, lecturers into particular subject lecturers workgroups, student groups of particular subject and lecturer, there is an electronic index of each student, where subjects, lecturers and received marks are stored, there is an electronic datasheet with each student group’s marks from given subjects and where final marks are stored, an electronic register of student groups’ activity is maintained, where current marks and worktime are stored.

Operational perspective: • • • • •

studies and didactic materials are prepared in three languages: Polish, English and German, lecturer specifies options of subject available for students, administrator specifies options for coordinator and lecturers, informational interface contains only options which are vital for particular tasks and moments, lecturer has the possibility to build his subject in stages: from presenting its whole content, through dividing it into lectures and topics, inputting tests, literature, knowledge and paraphernalia bases (there are no restrictions for procedural methodology),

663

lecturer can switch from subjects he leads to students groups as well as take on the student’s role, coordinator can become any lecturer, administrator can take on each and every role.

Editorial perspective: texts can be easily processed even on advanced level, mathematic formulae and symbols can be inserted, html and xml commands can be operated, movies, animations and voice recordings can be used.

Didactic perspective: • • • • • • • • •

subject consists of lectures, lecture consists of topics, topic includes texts, formulae, illustrations, literature links, each topic includes a thematic test, which verifies gained knowledge, an exam containing questions drawn from thematic tests is attached to each subject, particular lectures have literature of the subject attached to them, connected to the subject is a base of knowledge (keywords index), containing related concepts, illustrations and literature links, there are several types of tests and methods of combining them, there is a paraphernalia base (base of elementary bits of knowledge), based on which, lecturer constructs his topics, lectures, tests and base of knowledge.

Communicational perspective: • • • • • • • •

lecturer’s message board (for his students), administrator’s message board (for lecturers), message boards for students, who attend particular subjects, chatroom: lecturer and his students, chatroom: lecturers and coordinators with administrator, chatroom: lecturers with coordinator videoconference: lecturer and his students, videoconference: lecturers and coordinator.

eSTUDENT PLATFORM’S WORKING REGULATIONS eStudent platform’s working regulations are contained in public and commercial license projects. The public and the commercial license specify the rules of safe work of the eStudent platform’s users. Also, the public license’s description does not differ much from the commercial

Figure 3. The coordinator page of eStudent platform

Figure 2. The main page of eStudent platform

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664 2006 IRMA International Conference license (it does not contain the financial part). Therefore, as it is more universal, the commercial license is presented. Commerce License The student’s rights under commerce license: 1. 2. 3.

The remote access to the didactic materials published in VEC appropriate to each student. The remote registration to the subjects’ groups reported by new lecturers in VEC appropriate to each student. The possibility of participating in all of the e-learning forms conducted by VEC lecturers appropriate to each student.

EXAMPLES OF INSTRUCTIONS FOR VEC USERS VEC student instruction: • • • • • •

VEC lecturer instruction: •

The student’s restrictions under the commerce license: 1.

Coping of the didactic materials published under each VEC subject, only under permission of the lecturer who conduct the subject and only for the private education without the permission to copy or disseminate it in any form.

The lecturer’s rights under the commerce license: 1. 2. 3. 4. 5. 6. 7.

All students’ rights of each VEC. Publishing of the didactic materials for one or more your own subjects. The remote access to the didactic materials of every subject conducted in each VEC appropriate to each lecturer. Defining the time and the form of the access to the didactic materials of your own subjects. Off-line or on-line (e-board, e-mail, chat) communication with the VEC students in the range of conducted subjects. The remote designing of the subject’s structure and contents (subject’s unit, tests, requisites, passwords’ index, FAQ). The remote access to the VEC coordinator and to the technical reports of the educational platform.

• • • • • • • • •

• •

•

2.

Putting the materials from the foreign sources only if you get the permission of the owner, with the obligation to quote the source’s name and the owner’s name, and the feature of the document which confirm the permission for quotation. Coping of the didactic materials of other lecturers who belong to the appropriate VEC, only for your own necessities without the permission to copy or dessiminate it in any form.

• • • • • • • •

The coordinator’s rights under the commerce license: 1. 2. 3. 4. 5. 6.

All lecturers’ rights of each VEC. Registration of the VEC lecturers and subjects including finance conditions of commerce license. The remote management of all VEC supplies without the lecturers’ home folders. Off-line and on-line (e-board, e-mail, chat) communication with the VEC lecturers and students. The remote access to the VEC network administrator and to the technical reports of the educational platform. The supervision on obeying the conditions of the commerce license by the VEC students and lecturers.

go on to the address 1: www.eStudent.edu.pl or on to the address 2: www.eStudent.edu.pl/admin, (address 1.) write in your VEC name tag, for example: trainings, (address 1.) accept the license conditions /once/, (address 1.) choose the lecturer option, (address 1./2.) write in your name tag as a user, for example: aabacki, write in your password: ########, choose the login option, choose one of the possible options: edit | subjects | home folder | my subjects, (under the edit option) change your personal data, (under the subject option) publish the files for subscribed subjects using the home folder resources or workstation resources; you can listed new subjects by VEC coordinator; who has the access to all VEC subjects, (under the home folder option) you can collect all necessary resources to conduct your subjects, (under my subjects option) you get a fast access to all your subjects.

VEC coordinator instruction:

The lecturer’s restrictions under the commerce license: 1.

go on to the address: www.eStudent.edu.pl, write in the VEC name tag, for example: trainings, accept the license conditions (once), choose the student option, choose the login option, choose the subject, that you are interested in, for example: VEC trainings.

• • •

• • •

go on to the address 1.: www.eStudent.edu.pl or on to the address 2.: www.eStudent.edu.pl/admin, (address 1.) write in your VEC name tag, for example: trainings, (address 1.) accept the license conditions (once), (address 1.) choose the lecturer option, (address 1.) choose the login option, (address 1./2.) write in your name tag as a user, for example: aabacki, write in your password: ########, choose the login option, choose one of the possible option: edit | application list | subjects | lecturers | home folder | my subjects, (under the edit option) change your personal data, (under the application list option) accept the candidacies of new VEC lecturers, (under the subjects option register) new lecturers’ subjects or publish files for your subjects using the home folder resources or workstation resources; who has the access to all VEC subjects, (under the lecturers option) operate personal data of all VEC lecturers, (under the home folder option) you can collect all necessary resources to conduct your subjects, (under my subjects option) you get a fast access to all your subjects.

The coordinator’s restrictions under the commerce license: 1. 2. 3.

Conducting the trainings by new VEC lecturers. Informing all VEC users about rules of working and studying in VEC and also about any changes in eStudent platform operation. Informing the VEC network administrator about any problems in functioning of VEC.

NOMENCLATURE AND SAFETY Safety subject backups. It is advisory that the lecturer, who runs a subject on the eStudent platform, should always keep backup copies of files connected with his subject which are on the platform. Furthermore, the files ought to be stored in special folders, named the same as the subject, on his personal computer or one of network drives. Identical recommendation concerns files stored in the home catalogue.

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Emerging Trends and Challenges in IT Management Names of subjects. Names of subjects (didactic units) contain small letters only, words are separated by single spaces and no abbreviations are used (e.g. production management information systems). When subject is divided between lectures and practical classes lead by different persons, the subject’s name should be extended, by adding words like: lecture, practical class, conversations, laboratory, workshop (e.g. mathematics – practical class). In case if the subjects’ names repeat themselves, what should differentiate them is the teachers surname. Names of files. Names of files which belong to different didactic units are created using small letters, no Polish diacritic marks or abbreviations, and linked by underscore, for instance: examples_of_management_systems. If not generated automatically, file should be given proper extension which indicates which application should open it, e.g.: testing_tasks.pdf.

SUMMARY Development of the Open Sources Education can only be pursued at non profit conditions, as it has an unique cultural, civilization and social role. Therefore, the OSE and its eStudent platform are, in the first place, accessible for those who provide their educational services free of charge. Approximately 1/3 of costs of projecting the OSE system are covered by commercial didactic activity income (paid studies and courses), universities’ research programs, training services and postgraduate studies run for large enterprises and financial institutions. Rest of expenses on eStudent platform development and exploitation come from sponsors – whose list was presented – and OSE enthusiasts’ (students, candidates for doctor’s degree academic workers) own work.

665

gies management on global scale is the development of education, which brakes through political, economic, cultural and religious barriers. Surely, the Open Sources Education conception aids this idea and, as practice shows, gains the acclaim of numerous academic environments.

ENDNOTES 1

2

3

4

5

6

7

Learning for the 21st Century. Report and Mile Guide for 21st Century Skills www.21stcenturyskills.org Piech K. - The idea of life-time-learning in relation to e-learning system. “e-Mentor”, WSE Publishing, Warsaw, nr 1, X 2003. Krupa T. - eStudent education platform as an e-learning tool for practical use. “Innovations”, Nr 22, 2004. Warsaw University of Technology - the Institute of Production Systems Organization - is the author of Open Sources Education idea, the designer of eStudent IT educational platform, the administrator of the network of Virtual IT Studies Centres. PMP IT Consulting Co. - is the executor of the eStudent educational platform and eLearning, the supplier of IT services on eStudent platform, the IT sponsor of Opera Narodowa i Filharmonia Narodowa in Warsaw, the owner of Polish portal eBilet.pl Polish Society of Production Management - the main organizer of the trainings in eStudent educational platform, the promoter of the idea of management education in technical nad economic universities, the publisher of the “Enterprise Management” magazine about application of the business IT technology. ChybiDska E. - 7 e-academies. „Warsaw University of Technology Magazine”, Nr 4 (63) 2003, p. 2-3.

The authors believe that the role of sources and information technolo-

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666 2006 IRMA International Conference

Implementing Real Time OLAP with MDDC (Multi-Dimensional Dynamic Clustering) Michael W. Martin & Rada Chirkova North Carolina State University, Raleigh, N.C. 27695, {mwmartin, chirkova}@csc.ncsu.edu

ABSTRACT Data warehouse applications increasingly must update and maintain data in real time while simultaneously executing efficient OLAP (Online Analytical Processing) queries. The size and corresponding performance challenges of these data warehouses are growing at a staggering rate. This paper introduces, MDDC, a new technique that supports efficient OLAP queries without the extensive use of materialized views or secondary indexes. This technique is dynamic and does not require data reorganization. This is especially important for real-time data warehouses that must continually update data without downtime to reorganize data structures. This technique is similar to MHC (Multidimensional Hierarchical Clustering) but provides better symmetry and is completely dynamic. MDDC could utilize any number of host data structures including B-trees.

INTRODUCTION Multidimensional data structures are very important for data warehouse and OLAP applications [kimball:98].

MHC MHC (Multidimensional Hierarchical Clustering) combines Z-ordering and hierarchical clustering. In this section we review these concepts. Z-ordering MHC is partially based on the concept of bit interleaving from Z-ordering [orenstein:84,orenstein_:86]. This technique maps multidimensional spaces to one-dimensional spaces. When the Z-ordering curve is mapped in two dimensions it has a distinctive Z shape, hence the name. The Z-ordering technique shuffles or interleaves the bits from multiple keys together to form one contiguous key. Consider a composite multidimensional key made up of the keys or dimensions A, B, and C. Assume that each key is 3 bits long. Given a set of values for A, B, and C of {101, 110, 001}, a new interleaved key or Z-address takes the first bit from each of the three keys, then the second bit, and finally the third bit from each key so that the resulting single key in interleaved bit format is 110010101. Formally, a Z-address Z(k) is the ordinal number of a multidimensional composite key k from a tuple or record on the Z-curve and is calculated as follows:

Z(k) =

s-1

d

ΣΣ

k

i,j

•2(j•d+i-1)

j=0 i=0 The problem with Z-ordering relates to its requirement for a predetermined number of bits in each key coupled with differences in entropy among participating dimensions. A dimension has maximum entropy

when it enumerates the maximum number of dimension key values with the minimum number of bits. The maximum entropy E or minimum number of bits for a dimension D with K keys is: E = ceiling(log 2(K)) Consider data with two dimensions D1 and D2. If dimension D1 has 32 key values and a corresponding entropy of 5 bits while D2 has 100 key values and a corresponding entropy of 32 bits, then dimension D 1 probably will dominate the collating sequence of the B-tree. Accordingly, queries restricting only D 1 will be efficient while those only restricting D 2 will not be efficient. This problem prevents balanced query performance and renders Z-ordering ineffective in producing symmetric access to OLAP data. The Z-ordering technique could use 7 bits for D 2 to improve symmetry but would limit the number of keys in this dimension to 128 without a complete reorganization of the data. Hierarchical Clustering MHC is also partially based on hierarchical clustering. Hierarchical clustering is a method that controls key values and structures these key values specifically for queries. Hierarchical clustering capitalizes on the fact that data is often composed of hierarchies. As an example, a customer dimension might contain customers each of which are related to one city. The customer dimension might further assign each city to a state and each state to a region. Hierarchical clustering incorporates these hierarchies into keys and their corresponding indexes. MHC extends this concept to multidimensional data. To accomplish hierarchical clustering, MHC uses compound surrogate keys. These keys reserve a fixed number of bits for each level in a dimensional hierarchy. The fixed number of bits at each level depends on the number of unique values for all keys or parent keys of that level in the dimension hierarchy. For instance if the customer dimension has 6 regions overall, the maximum number of states in any of the 6 regions is 20, the maximum number of cities in any state is 150, and the maximum number of customers in any city is 17, then the compound surrogate would require 3 bits for the region level, 5 bits for the state level, 8 bits for the city level, and 5 bits for the customer level. Therefore the customer dimension would require a total of 21 bits for each of its primary keys. MHC also makes provision for variable length compound surrogate keys in the event that different keys have different numbers of hierarchical levels or unbalanced hierarchies but, MHC does not make provision for variable length bit strings for each hierarchical level individually. If MHC requires 8 bits for the city level in the customer dimension, then any primary key from the customer dimension that includes the city level must include all 8 bits and no state can contain more than 256 cities [markl:99]. The primary key structure for this customer dimension is shown in Table 1. As just demonstrated, if MHC designates too few bits for a given hierarchy level, then the data might exceed this threshold and require full reorganization of all data structures that include the affected

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Table 1: MHC Compound Surrogate for Customer Dimension

Table 2: MDDC Compound Surrogate for Customer Dimension

REGION STATE CITY CUSTOMER 001 10101 00100001 00011

REGION STATE CITY CUSTOMER 10000000 10101000 10000100 11000000

dimension before MHC can process any further updates. If MHC designates too many bits for a given hierarchy level, then some bits of the hierarchy level might remain empty for all data and therefore cause symmetry problems. Similarly, if one parent in a dimensional hierarchy contains 50 children when another parent on the same level in the dimension contains 3 children, then queries searching for children of the parent with 3 children or other parents with less than 50 children might experience symmetry and efficiency problems.

distinct key values from any hierarchy level. completely dynamic unlike MHC.

MDDC

Point Queries Point queries are very simple in MDDC. When the query specifies the full key for each dimension, MDDC simply computes the single address for the complete search key with dynamic bit interleaving as it makes comparisons with other keys in the data structure to locate the record or records with the specified key values.

MDDC removes the trade-off between symmetry and dynamic updates in MHC with a simple but powerful modification to the MHC key structure and bit interleaving technique. With hierarchical clustering, MHC imposes a partial ordering on data. Since hierarchical clustering already forces a partial ordering that orders data according to the dimensional hierarchies, MDDC further takes advantage of this partial ordering. Research related to MHC has shown that mirroring the bits of each level in compound surrogates improves symmetry in some cases [markl:00]. In addition to mirroring bits, MDDC uses a mechanism for variable length bit strings for each hierarchical level in the compound surrogate. This allows MDDC to be completely dynamic while maintaining the same or better symmetry than MHC. Variable Length Bit Strings MDDC allocates the last bit of each byte as a continuation bit so that 7 bits of each byte are usable. Each level in a variable length compound surrogate requires at least one byte and also uses a whole number of bytes for each level. This affects the length of keys that MDDC must store in key fields but does not affect symmetry since MDDC does not use the continuation or filler bits when interleaving bits. It is also important to point out that MDDC might also have an overall variable length byte for compound surrogates just as MHC does to accommodate unbalanced hierarchies. Dynamic Bit Interleaving If order preserving bit strings are used, the relative position of these bits in a Z-address must shift. This alters the overall Z-ordering and requires the data to be completely reorganized as bit string lengths change. Using mirrored bits in conjunction with variable length bit strings overcomes this problem. No matter how long the bit strings grow, the relative position of bits in the interleaving does not change. MDDC simply adds the additional bits for larger level values to the end of the bit string for that level in the compound surrogate. This does not alter the relative position of previous keys at any level in the overall bit interleaving and therefore does not require data reorganization. Mirrored bits have one more important advantage. Except for the value of 0, each mirrored bit string ends with a 1 by definition. This allows MDDC to trim the remaining filler bits, which are all zeros, when interleaving bits. With this technique, MDDC always exhibits symmetry as good as MHC and better in some cases. If MHC specifies 8 bits for a given level in a compound surrogate but only uses one, then MHC wastes 7 bits in the Z-ordering. In such cases, some dimensions that are using all bits in their compound surrogates might dominate the dimensions that have unused bits in the collating sequence of the data structure. For the previously listed reasons, MDDC does not include these unused bits in its dynamic bit interleaving process. The customer example presented in the MHC section has the MDDC format depicted in Table 2. Variable length, mirrored bit strings in conjunction with dynamic bit interleaving provide as good or better symmetry as compared to MHC. In addition, MDDC does not impose any preset limits on the number of

Thus, MDDC is also

Queries MDDC is like MHC in that it only alters the content of dimension keys and the collating sequence in host data structures and does not alter any of its other properties.

Range Queries MDDC uses wild card or “don’t care” bits in the dynamic bit interleaving for dimension key values or parts of dimension key values that the query does not specify and then proceeds to query the resulting key values. Maintenance MDDC inserts, deletes, and updates records with standard data structure methods with the caveat that MDDC dynamically interleaves the bits for all keys involved in comparisons in the data structure. The interleaved bits determine the placement and organization of records within the data structure. In doing so, MDDC does not in any way alter the properties of the host data structure. MDDC and B-trees Like MHC, MDDC works especially well with B-trees. Therefore, Btrees containing keys that the MDDC algorithm organizes retain all maintenance advantages of B-trees including the perfect balance, shallow depth, granular concurrency control, and recoverability. Unlike MHC, MDDC does not require data reorganization. Therefore, it is completely dynamic and can readily accommodate real-time updates.

CONCLUSIONS AND FUTURE WORK MDDC provides dynamic, real-time updates and efficient symmetry for OLAP queries. MDDC does not require data reorganizations, demonstrates suitability for the most common OLAP queries, and has the capability to reduce the size and number of secondary indexes and materialized views. This paper outlines the basic concepts of MDDC. In the near future we hope to complete experiments and demonstrate the effectiveness of MDDC.

REFERENCES Kimball, R., Reeves, L., Margy Ross, M. &Thornthwaith,W. The Data Warehouse Lifecycle Toolkit,John Wiley & Sons Inc.,New York, Chichester, Weinheim, Brisbane, Singapore, Toronto, 1998. Markl, V., Ramsak, F., & Bayer, R. (1999). Improving OLAP performance by multidimensional hierarchical clustering, proceedings of ideas’99 in Montreal Canada, IEEE. Orenstein, J.A. & Merritt,T.H. (1984, April). A Class of Data Structures for Associative Searching, ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems,pp. 181—190. Orenstein, J.A. (1986). Spatial Query Processing in an Object-Oriented Database System, Communications of the ACM, pp. 326—333. Mistral, V. M. (2000). Processing Relational Queries using a Multidimensional Access Technique, Datenbank Rundbrief, 26, pp. 24-25.

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668 2006 IRMA International Conference

Reasoning about Functional and Non-Functional Concerns during Model Refinement: A Goal-Oriented and Knowledge-Based Approach Lawrence Chung, The University of Texas at Dallas, [email protected] Sam Supakkul, Titat Software LLC, [email protected]

system largely depends on how good, or bad, these decisions are. For example, Fig. 1 shows three alternatives for refining the “send-alarm” message on a UML sequence diagram from analysis to the design level. Option (a), DeviceInterface makes a synchronous method invocation call and is blocked until the AlarmManager is done handling the message. Option (b) uses Producer-Consumer-Queue (PCQ) pattern [21] to deposit the new alarm into a synchronized buffer to be picked up by AlarmManager running in a separate thread/process, and option (c) uses Message-Oriented Middleware (MOM) [23] to asynchronously send the new alarm. Exploring and evaluating design decisions are usually carried out only informally without records of the knowledge and rationale used during the process [20]. This makes it difficult for others to understand why certain decisions were made and also to reuse the knowledge. These problems are the main focus of the design rationale research that produces a number of methods. However, these methods are generic for general design that is not tailored for software. The NFR Framework [4,5] provides a framework that is more specific and suitable for software development, especially for non-functional requirements (NFRs) modeling and architectural design. This paper adopts and extends the NFR Framework [4,5] to present a goal-oriented and knowledge-based framework for representing and organizing knowledge used for exploring design alternatives and evaluating trade-offs. We illustrate the application of the method using the refinement of the sequence diagram message shown in Fig. 1 as running examples throughout the paper.

ABSTRACT Traditional model driven development follows the stepwise refinement approach where early phase models are gradually refined with more details from one version to another and from one phase to another successively until they are expressed in the terms of the underlying programming language. Every refinement step implies some design decisions. The quality of a software system largely depends on how good, or bad, these decisions are. The quality of decisions in turn would depend on what kind of alternatives are explored, what kind of trade-offs are analyzed, and how a particular selection is made. However, the process of decision making is carried out only informally, where the knowledge and rationale that led to the decision are not explicitly documented. This makes it difficult for others to understand why certain decisions were made and to reuse the knowledge. This paper presents a goal-oriented and knowledge-based approach for explicitly representing, organizing, and reusing software development knowledge. In this framework, nonfunctional characteristics, such as performance and security, are treated as (soft) goals to be achieved and act as the criteria for selecting the alternatives. The application of this framework is illustrated using the refinement of a UML sequence diagram message.

I. INTRODUCTION Traditional model driven development such as in UML-based [8] development follows the stepwise refinement approach. Every refinement step implies some design decisions [14]. The quality of a software

The rest of the paper is organized as follows. Section II gives a brief overview of the NFR Framework. Section III describes the knowledge

Figure 1. Examples of alternatives for refining a message in a sequence diagram Analysis Model

DeviceInterface

AlarmManager

send-alarm

Design Model AlarmManager

DeviceInterface

sendAlarm

DeviceInterface

PCQ

AlarmManager

deposit

DeviceInterface

MOM

send remove

(a)

AlarmManager

(b)

push

(c)

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Emerging Trends and Challenges in IT Management

669

Figure 2. A softgoal interdependency graph representing NFRs related concepts (a) that are captured as methods (b) ResponseTime [Account]

ResponseTime [GoldAccount]

ResponseTime [RegularAccount]

+

...

PerformFirst [GoldAccount]

NFR DecompositionMethod ResponseTimeViaSubclass parent: ResponseTime[Account] offspring: {ResponseTime[RegularAccount], ResponseTime[GoldAccount]} contribution: AND OperationalizationMethod HelpResponseTimeWithPerformFirst parent ResponseTime[GoldAccount] offspring: PerformFirst[GoldAccount] contribution: HELP ArgumentationMethod PerformFirstRationale parent PerformFirst[GoldAccount] offspring: Claim[“Priority actions can be performed first”] contribution: MAKE

++ Claim [“Priority actions can be performed first”]

(b)

(a)

Legend non-functional softgoal

AND-decomposition

operationalizing softgoal

OR-decomposition

claim softgoal

satisficed softgoal X

denied softgoal

positive contribution negative contribution

representation in design model and how to capture it as Method. Section IV describes how to organize Methods. Section V describes how the Methods are reused. Finally, Sec. VI offers some conclusion remarks.

II. OVERVIEW OF THE NFR FRAMEWORK The NFR Framework [4,5] is a goal-oriented method for dealing with NFRs, which are represented as softgoals to be satisficed. The framework employs “goal-refinement, exploration of alternatives, and evaluation” analysis pattern. Using this pattern, first, high level goals are identified and refined using AND/OR decomposition. Then, design decisions for operationalizing the NFR softgoals are identified, refined, or further operationalized by lower level operationalizations. Last, the design decisions are evaluated based on how they contribute (positively or negatively) to the NFR softgoals. This entire process is recorded in a diagram called Softgoal Interdependency Graph (SIG). In the SIG, all softgoals are named with “Type[Topic]” nomenclature. In the case of NFR softgoal, “Type” indicates the NFR concern and “Topic” the context for the NFR. In the case of operationalizing softgoal, “Type” indicates the operationalization concept and “Topic” the context for which the solution is applicable. Finally, in the case of argumentation softgoal, “Type” indicates either FormalClaim or (informal) Claim [4] and “Topic” the corresponding argument description. Figure 2.a shows an example of the SIG. The individual pieces knowledge used to build each piece of the SIG can be captured as Methods as shown in Fig. 2.b.

III. REPRESENTING AND CAPTURING DEVELOPMENT KNOWLEDGE A. Representing Development Knowledge Figure 3 shows a design decision process for refining the “send-alarm” sequence diagram message. In this paper, “goal” refers to a functional goal and “softgoal” refers to a non-functional goal. First, we identify and refine functional goals (i.e. “Design[Message]”). Second, design decisions (“Synchronous[Message]” and “Asynchronous[Message]”) are identified. We repeat the refinement and operationalization of operationalizing goals until they are low-level enough for implementation. Last, the design decisions are evaluated based on their positive or

negative contributions toward the highest criticality NFR softgoals (Reponsiveness). B. Capturing Development Knowledge We adopt and extend the Method mechanism from the NFR Framework to capture individual pieces of FRs-related knowledge with three additional types of Methods: Model Refinement, Functional Operationalization, and Model Mapping Methods. Attributes of the Methods (e.g. parent, contribution, and applicabilityCondition) are used as the selection criteria for selecting applicable Methods to apply. When a Method is applied against a parent goal, the goals described by the offspring attribute would be generated and linked to the parent goal. Model Refinement Method Using Fig. 3 as an example, refining the send-alarm message to design level messages is represented by the root goal “Design[Message]”. An example of Model Refinement Method definition based on Fig. 3 is given below. RefinementMethod DesignMessage parent: UML.Message /* a UML metaclass */ offspring: Design[Message] contribution: DesignRefinement applicabilityCondition: /* user defined */ Functional Operationalization Method This method captures the knowledge that creates and links an operationalizing goal to a parent functional or operationalizing goal. An example is given below. FnOperationalizationMethod OperationalizeMessage_Sync parent: Design[Message] offspring: Synchronous[Message] contribution: SOME+ !!Responsiveness applicabilityCondition: /* user defined */

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670 2006 IRMA International Conference Figure 3. Representation of functional and non-functional knowledge for refining a sequence diagram message

DeviceInterface

A. Aggregation/Decomposition Dimension In Fig. 4.a, following the composite design pattern [16], Methods may be combined to form a CompositeMethod. Because CompositeMethod is also a Method, it can be contained in other CompositeMethods. An example of the CompositeMethod definition is given as follows. When the OperationalizeMessage is applied, the two contained Methods are applied against the parent goal.

Design[Message]

!!

SOME-

Responsiveness Time Performance

SOME+

Synchronous [Message]

Claim[“Caller blocked until recipient is done processing the message”]

It is not only important that we can represent knowledge, but also how we structure and organize it [10]. This section discusses the organization of Methods along the three organizational dimensions [11].

AlarmManager

send-alarm

X

IV. ORGANIZING DEVELOPMENT KNOWLEDGE

!

Asynchronous [Message] _

++ ProducerCons umerQueue [Message]

X

MessageOriented Middleware Message] Claim[“MOM is more heavy-weight with more features and usually requires a server”]

SOME-

M

CompositeMethod OperationalizeMessage parent: Design[Message] applicabilityCondition:/* user defined */ methods: OperationalizeMessage_Synchronous, Operationalize Mes sage_Asynchronous

Sequence Diagram

Model Mapping Method Model Mapping Method captures the knowledge for mapping the parent of the root goal to a target model. An example of Model Mapping Method is given below. The mappingMeans attribute indicates the mechanism or technique used for the mapping. The mappingSpec attribute specifies the detailed mapping based on the mappingMeans.

B. Generalization/Specialization Dimension Figure 4.b shows that a Method may be specialized by another Method. The specialized Method inherits all of the attributes from the generalized Method, optionally adds or re-defines one or more attributes. An example of a specialized Method is given below. FnOperationalizationMethod OperationalizeMessage_PCQHurt extends OperationalizeMessage_PCQ parent: Asynchronous[Message] offspring: ProducerConsumerQueue[Message] contribution: MAKE !TimePerformance, HURT !!Reliability applicabilityCondition:/* specific condition */ C. Classification/Instantiation Dimension Figure 4.c shows the classification/instantiation relationship of MetaMethod, Method, and MethodInstance.

MappingMethod AnalysisMessageToDesignMessage_PCQ parent: ProducerConsumerQueue[Message] offspring: SequenceDiagram applicabilityCondition: /* user defined */ mappingMeans: TemplateMOF mappingSpec: … deposit = factory.create(Message) deposit.sendEvent = factory.create(MessageEnd) deposit.receiveEvent = factory.create(MessageEnd) deposit.sendEvent.covered = deposit.receiveEvent.covered = remove = factory.create(Message) remove.sendEvent = factory.create(MessageEnd) remove.receiveEvent = factory.create(MessageEnd) remove.sendEvent.covered = remove.receiveEvent.covered = … }

V. REUSING DEVELOPMENT KNOWLEDGE When sufficient Methods are defined and stored in a knowledge base, they may be selected and applied successively to generate or update a goal graph to record the design decision process (i.e. Process) and also the target model elements (i.e. Product). Figure 5 depicts the Method application process.

VI. CONCLUSIONS We have presented a goal-oriented and knowledge-based framework for representing, organizing, and reusing development knowledge. The framework extends the NFR Framework with the following extensions: 1) the “goal-refinement, exploration of alternatives, and evaluation” pattern is now made applicable to functional concerns; 2) three additional types of Methods have been proposed to capture individual pieces

Figure 4. Methods organization along aggregation (a), generalization (b), and classification dimensions Method

Meta Method

*

Instantiate Simple Method

Composite Method

Generalized Method

Method Instantiate

Model Refinement Method

Functional Operationalization Method

Model Mapping Method

(a)

Refinement Method

Operationalization Method

Argumentation Method

Specialized Method

(b)

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Method Instance

(c)

Emerging Trends and Challenges in IT Management

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Figure 5. Methods application that generates a goal graph and the target model DeviceInterface

AlarmManager

send-alarm

Methods

Design[Message] SOME -

DeviceInterface

Method Knowledge Base

AlarmManager

Source Model

Process

send-alarm

NFRs

X

Method Application

Synchronous [Message]

Claim[“Caller blocked until recipient is done processing the message”]

++ ProducerCo nsumerQue ue [Message]

Product M

!!

Responsiveness

!

Time Performance

DeviceInterface

PCQ

!!

Responsiveness

SOME + Asynchronou s [Message]

!

Time Performan ce

_

X

SOME Sequence Diagram

MessageOriente dMiddleware Message] Claim[“MOM is more heavy-weight with more features and usually requires a server”]

AlarmManager

deposit remove

of FRs-related knowledge; 3) CompositeMethod is introduced to combine and reuse previously defined simple Methods and Correlation Rules. With these extensions, both functional and non-functional concerns can be analyzed together with NFRs as the criteria guiding the design decisions. Knowledge of such analysis can be captured, cataloged, tailored, improved, and reused. Future work of this research includes developing a metamodel to semi-formally describe the framework to extend the UML profile we previously defined for integrating the NFR Framework with UML [15], to also support functional goal analysis.

[12]

[13] [14] [15]

REFERENCES [1]

[2]

[3]

[4]

[5] [6]

[7]

[8] [9] [10]

[11]

A. Dardenne, A. van Lamsweerde, and S. Fickas, “Goal-Directed Requirements Acquisition,” Science of Computer Programming, Vol. 20, 1993, pp. 3-50 J. Mylopoulos, L. Chung, and E. Yu, “From Object-Oriented to Goal-Oriented Requirements Analysis,” Comm. ACM, vol. 42, no. 1, Jan. 1999, pp. 31-37 J. Mylopoulos, L. Chung, S. Liao, and H. Wang, “Exploring Alternatives During Requirements Analysis,” IEEE Software, Jan./Feb.2001,pp. 2-6 J. Mylopoulos, L. Chung, and B. Nixon, “Representing and Using Nonfunctional Requirements,” IEEE Trans. Software Engineering, Vol. 18, No. 6, June 1992,pp. 483-497 L. Chung, B. Nixon, E. Yu, and J. Mylopoulos, Non-Functional Requirements in Software Engineering, Kluwer Publishing, 2000 Y. Yu, J. C. S. do Prado Leite, and J. Mylopoulos, “From Goals to Aspects: Discovering Aspects from Requirements Goal Models,” In Proc. 12th IEEE Int. Requirements Engineering Conference, 2004, pp. 38-47 G. Caplat, J. Sourouille, “Considerations about Model Mapping,” Workshop in Software Model Engineering, Oct. 2003, San Francisco, USA, http://www.metamodel.com/wisme-2003/18.pdf OMG, “UML 2.0 Superstructure Specification,” http:// www.omg.org/cgi-bin/apps/doc?ptc/04-10-02.zip, Oct. 2004 OMG, “MDA Guide Version 1.0.1,” http://www.omg.org/cgi-bin/ apps/doc?omg/03-06-01.pdf, June 2003 S. Greenspan, J. Mylopoulos, and A. Borgida, “Capturing More World Knowledge in the Requirements Specification,” In Proc. 6th Intl. Conf. on Software Engineering, Tokyo, Japan, 1982. R. Hull, and R. King, “Semantic database modeling: Survey,

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[23]

[24]

application and research issues,” ACM Comp. Surv. Vol. 19, No. 3, 1987, pp.201-260 W. Regli, X. Hu, M. Atwood, and W. Sun, “A Survey of Design Rationale Systems: Approaches, Representation, Capture, and Retrival,” Engineering with Computers, Vol. 16, SpringerVerlag, pp.209-235 K. Arnold, J. Gosling, and D. Homes, The Java Programming Language, Third Edition, Addison-Wesley, 2000 N. Wirth, “Program Development by Stepwise Refinement,” Comm. ACM, Vol. 14, 1971, pp.221-227 S. Supakkul and L. Chung, “A UML Profile for Goal-Oriented and Use Case-Driven Representation of NFRs and FRs”, In Proc. SERA’05, IEEE Computer Society. pp. 112-119 E. Gamma, R. Helm, R. Johnson, and J. Vlissides, Design Patterns: Elements of Reusable Object-Oriented Software, Addison-Wesley, 1995 OMG, “Meta Object Facility (MOF) 2.0 Core Specification,” http://www.omg.org/cgi-bin/apps/doc?ptc/03-10-04.pdf, Oct. 2003 E. Kavakli, “Goal-Oriented Requirements Engineering: A Unifying Framework,” Requirements Eng., vol. 6, no.4, 2002, pp. 237-251 A.I. Anton, “Goal-based Requirements Analysis,” In Proc. 2nd IEEE Intl. Conf. Requirements Engineering, 1996, pp.136-144 S. Shum, and N. Hammond, “Argumentation-Based Design Rationale: What Use at What Cost?” International Journal of Human-Computer Studies, Vol. 40, No. 4, 1994 K. Jeffay, “The Real-Time Producer/Consumer Paradigm: A paradigm for the construction of efficient, predictable real-time systems,” In Proc. ACM/SIGAPP Symposium on Applied Computing, Indianapolis, IN, February, 1993, pp.796-804 M. Wahler, “Formalizing Relational Model Transformation Approaches”, Research Plan, Swiss Federal Institute of Technology Zurich, 2004, http://www.zurich.ibm.com/~wah/doc/ research_plan_wahler.pdf W. Emmerich. “Software Engineering and Middleware: A Roadmap” The Future of Software Engineering, ACM Press 2000 S. Supakkul and L. Chung, “Representing, Organizing and Reusing Knowledge about both Functional and Non-Functional Concerns during Software Development,” Submitted

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672 2006 IRMA International Conference

e-HR: A Custom Electronic Human Resources Management System M. Almanhali, M. Radaideh, & T. Shehabuddin Human Resources General Directorate, Abu Dhabi Police GHQ, Ministry of Interior, UAE, [email protected]

ABSTRACT The Human Resources General Directorate (hereinafter HRGD) of Abu Dhabi Police GHQ (hereinafter ADP) endeavored a project to become an electronic work environment. The targeted system will be a total electronic Human Resources Management System (hereinafter e-HR) that supports all six departments in the HRGD. These departments are the Personnel Affairs, Recruitment, Training, HR Planning, Performance Appraisals, and Police Institutes and Schools. The e-HR system has two interfaces, the first is to be used internally (intranet) and the second is to be used by externals (internet). Our concern was concentrated in two directions. First, to automate data acquisition, transfer and processing. Second, to integrate all departments and functions across HRGD into a single solution that can serve different departments’ needs and requirements. This paper is to furnish a high-level of details of the e-Recruitment sub-system that is being tested and evaluated before it is made public.

Why is the Proposed e-HR System Better than Existing ERPs? It is important to mention that we have chosen to develop the e-HR system completely in-house as the existing ERP solutions from Oracle, SAP and others require much customization to fit the current HR environment at ADP. We estimated that the cost of developing this system in-house will be much less than the cost of adopting and customizing one of the existing ERP solutions. Besides that, the estimated time it would take us to customize such solutions would be longer than the time it takes us to develop the e-HR system completely in-house. The following table summarizes the three main factors that lead us to chose the in-house development of the intended system as opposed to adopting one of the many existing HR/ERP solutions/systems:

Factor

Cost

Timeline

According to the Enterprise Resource Planning Research Center the implementation of ERP usually runs between one and three years [6], on average depending on the enterprise size and the stability of the requirements. In our project we are applying the system in phases. In one year we have been able to fully serve three departments out of six.

Dynamic requirement

Due to the nature of the police department, requirements change frequently. In ERP system, once a requirement is set, it is very hard and expensive to adjust it. It is important to figure out requirements before the beginning of implementation. Any change in the requirement later will delay the project because some complex processes need to be rewritten and it might lead to the failing of ERP [2]. In our system, due to the simple design, it is easy to change the system to meet the upcoming requirements as well as adding additional processes to perform additional tasks.

BACKGROUND The Human Resources General Directorate (hereinafter HRGD) of Abu Dhabi Police GHQ (hereinafter ADP) endeavored a project to become an electronic work environment. The project started around the end of year 2004 and still carrying on. The targeted system will be a total electronic Human Resources Management System (hereinafter e-HR) that supports the HRGD six departments. These departments are the Personnel Affairs, Recruitment, Training, HR Planning, Performance Appraisals, and Police Institutes and Schools. The e-HR system has two interfaces, the first is to be used internally and the second is to be used through the internet. The following table summarizes some of the currently implemented HR strategies and solutions in different agencies and enterprises:

Solution

Description

Manual HR system

Some agencies still manage their HR systems as separated procedures where everything is done manually including recruitment, employees’ leaves, employee raise and bonuses … etc. A candidate or an employee should fill paper-based form that is submitted to the concerned party where it goes through many steps before a decision is made. Not only is it inconvenient but also it places a great overhead on HR department. Due the lack of efficiency and scalability this system doesn’t work even for a middle size business not to mention a government agency.

HR Solutions

Many outsourcing companies provide solutions for e-Recruitment such as StaffCV, Eclipse and many others [1]. Although these solutions are considered cost efficient they have very limited functionality that do not meet the requirements of a government agency. Moreover, these solutions assume one workflow of the recruitment process where the candidate applies and his/her application is been revised by the HR department. This is not the case in military agencies where many parties are concerned as will be explained later.

Enterprise resource planning software (ERP)

ERP system is a single software program that serves and combines all different departments together into a single, integrated software program that runs off a single database so that the various departments can more easily share information and communicate with each other. The goal of ERP is “to gain include standardization, better inventory management, improved profit margins and increased competitiveness” [4]. Some companies provide ERP systems such as Oracle and SAP [3].

Description The total cost of ownership (TCO) of ERP includes hardware, software and professional services. The average TCO was $15 million (the highest was $300 million and lowest was $400,000) [6]. The cost increases as the number of users increase because of acquiring licenses. In addition, over 31% of companies which applied ERP said that it was over budget while 18% said it was not applicable [4]. In our project the solution is developed in house and open-source technologies are used which cut down the overall cost.

At the time of writing this paper, three of the e-HR sub-systems have been completely developed. These are the e-Recruitment, e-Training, and e-Education ones, which are being internally tested and will be released to public in the near future.

•

The e-Recruitment sub-system handles the entire recruiting cycle that can be summarized as follows: o Concerned ADP departments post their staffing needs. o HR Planning department double checks these needs and approve/disapprove them. o Recruiting department advertises the approved jobs openings on the website. o Receiving applications from applicants for particular job openings. o Concerned ADP departments review and evaluate applications and shortlist candidates for each of their advertised jobs.

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Emerging Trends and Challenges in IT Management o

•

•

Recruiting department arranges for interviews, medical tests, appointments, etc.

The e-Training sub-system enables the Training department to: o Receive training requirements electronically from the different ADP departments. o Receive the details of available training programs from internal and external training providers. o Produce a training plan and communicate that with the concerned ADP departments as well as with the concerned training providers. o Follow up on carrying on training programs. The e-Education sub-system enables the Education section of the Training department to maintain ongoing communications with ADP undergraduate and graduate students who are studying inside the country as well as with those who are studying abroad. Also,

673

this facilitates communications with their universities. Overall, this sub-system helps the Education section to monitor all ADPsponsored students. At a later stage of the e-HR project, the following sub-systems will be developed and implemented: e-Personnel, e-Institutes, e-Schools, ePlanning, and e-Performance. This paper is intended to present a high-level details of the e-Recruitment sub-system.

E-RECRUITMENT All ADP departments will be using this sub-system besides applicants seeking employment at ADP. The ADP entire recruitment process is incorporated into this sub-system. Some modifications were introduced

Figure 1. E-Recruitment Sub-System’s Logical Foundation

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674 2006 IRMA International Conference in the process in order to decentralize the existing current recruitment process by enabling the concerned departments to review the applications first such that the Recruiting department just takes care of the overall all coordination of the recruiting process.

•

At anytime, the status of any application can be viewed by the applicant himself/herself, the ADP concerned departments, etc. and therefore there would be no need for an applicant to visit any of the ADP employment offices around the country.

•

E-Recruitment Workflow As shown in Figures 1 and 2, the e-Recruitment sub-system can be viewed of three basic stages:

•

The process of advertising jobs by the concerned departments at ADP. The process of filling the application for job by the applicants through the internet. The process of evaluating applications by the concerned departments and the Recruiting department.

Advertising Jobs • User 1 - All ADP Departments: These departments request advertising their vacancies online through the e-Recruitment sub-system in a secured manner.

•

User 2 - HR Planning Department: This department reviews all requests for advertising vacancies for budgetary, job description and responsibilities purposes. HR Planning department can adjust the number of required staff and any other details in the

Figure 2. E-Recruitment Sub-System Workflow

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Emerging Trends and Challenges in IT Management

•

requested advertisement. Once an advertisement request is approved by the HR Planning department, the e-Recruitment subsystem passes it to the Recruitment department for further processing. User 3 - Recruitment Department: This department reviews the requests for vacancies advertising passed by the HR Planning department and approve/disapprove them. Once a request is approved by the Recruitment department, it gets automatically published on the e-HR website and becomes available for public review.

675

Apply for jobs • User – External and Internal Applicants: The user reviews the vacant jobs and their requirements then fills an application form for a particular job. The system generates an application number for the applicant to use later on to check on the status of his/ her application. Evaluation of Applications • User 1 – all ADP Departments: Each department evaluates all applications submitted against its own job vacancies. The system

Figure 3. The e-Recruitment Sub-system’s main page

Figure 4. The listing of available jobs

Figure 5. The first part of the application form

Figure 6. The second part of the application form

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676 2006 IRMA International Conference

•

passes to the Recruitment department only those applications that have been passed by the departments of concern for further processing. User 2 - Recruitment Department: This department reviews all applications that have been passed by the concerned ADP departments and then arrange for interviews, medical tests, security check, etc. Once this process is completed, the system transfers all passing applications to the Personnel Affairs department for appointments.

ACKNOWLEDGMENTS The authors would like to express their sincere appreciation to His Highness Sheikh Saif Bin Zayed Al-Nahayan, UAE Minister of Interior, for his personal and unlimited support to the project team. Abu Dhabi Police GHQ deserves a big ‘thank you’ for supporting this project. Special thanks go to the team members; M. Abdelhameed, F. Hamad, and Amera Al-Ashaal for their dedication and valuable contributions.

REFERENCES E-Recruitment Implementation This subsection presents some snapshots of the many screens that we developed as part of the e-Recruitment sub-system interface. As can be predicated from these snapshots, the current version of the e-Recruitment sub-system supports the Arabic language. The English version will follow in the near future.

[1]

CONCLUSION

[4]

In this paper, the e-Recruitment sub-system of the intended ADP e-HR system has been presented at a high-level of details. This system is being tested and evaluated for public deployment in the near future. The initial observations lead us to believe that this system will save ADP too much effort and cost in their recruitment process.

[5]

[2]

[3]

[6]

Corporate Recruiting. Retrieved November 29, 2005. http:// www.staffcv.com/solutions/corporate_recruiting.asp Christopher Koch. (n.d.). The ABC s of ERP. Retrieved November 29, 2005, from http://www.cio.com/research/erp/edit/ erpbasics.html#erp_fail Human Resources Management. Retrieved November 29, 2005, from http://www.oracle.com/applications/human_resources/ intro.html Oct 07, 2001. ERP Progress Report. Retrieved November 29, 2005, from http://www2.cio.com/research/surveyreport. cfm?ID=31 Susan M. Heathfield. (n.d.). Outsourcing: A Strategic Solution. Retrieved November 29, 2005, from http:// humanresources.about.com/cs/strategichr/a/outsourcing.htm What is Enterprise Resource Planning?. Retrieved November 29, 2005, from http://www2.bc.edu/~oreillyv/definitions/ EnterpriseResourcePlanning.htm

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Emerging Trends and Challenges in IT Management

677

Spim, Spam and Advertisement: Proposing a Model for Charging Privacy Intrusion and Harassment Dionysios Politis, Dept of Informatics, Aristotle University of Thessaloniki, Thessaloniki, GR-541 24, GREECE, T: +30 2310 998412, F: +49 2310 998419, [email protected] Georgios John Fakas, Dept of Computing & Mathematics, Manchester Metropolitan University, Chester Str, Manchester, M1 5GD, UK, T: +44 161-2473537, F: +44 161-2471483, [email protected] Konstantinos P. Theodoridis, Centre of International & European Economic Law, Ikaron 1, Thessaloniki, GR-541 02, GREECE, T: +30 2310 486900, F: +30 2310 476 366, [email protected]

ABSTRACT An issue factually challenging the peer-to-peer nature of the Internet is the increase of spam trafficking. Having reached record levels at the beginning of this year, it raised consciousness that Internet communication was endangered by an erosive threat similar to the uncontrollable, massive free circulation of MP3s that devastated the musical industry. Recent combined advances in the software industry and in the legal front have reduced the phenomenon. The technical, social, financial and legal parameters of this campaign are examined in this paper under the prism of a networked economy.

INTRODUCTION A significant problem of our times, accelerated by the advances in technology, is the plethora of commercial Internet messages usually defined as spam, while the equivalent in classic television emission is the frequent and uncontrollable advertisement. Advertisement, perceived as an expression and factor of the economy, is legitimate and desirable. However, abusive advertising practices cause multipledamage: invasion in our private communication space, homogenisation of morals and customs leading to globalized overconsumption. Variations and cloning of spam and advertisement include spim, distributed instant messaging using bulk SMS’s over mobile telephone networks or the web, wireless attacks and penetration, targeted unsolicited online harassment and others.

Spam as a social phenomenon arises from an on-line social situation that technology created. First, it costs no more to send a million e-mail messages than to send one. Second, hits are percentage of transmissions, so sending more spam means expecting more profit (Whitworth, 2004). So, from the advertising point of view, the important characteristic of spam is that it is practically with no charge. It is not the best e-mail communication technique, it is not the most efficient but it attracts people because of its free ride.

LEGAL ASPECTS OF SPAM USA Since 1996 many cases1 between Internet Service Providers (ISPs) and spammers found their way to the court; however the problem has always remained the same: lack of specific legal regulation, which led to objectionable decisions (Frank, 2003, Kasprzycki, 2004). The need for an ad hoc federal law was obvious and after many rejected drafts, on 01.01.2004, the “CAN SPAM Act 2003 2”was finally put into force. This Act includes a variety of measures for the prevention and the restriction of the problem and provides serious penalties for the spammers. More specifically, among others: • •

PROBLEM FORMULATION Spam is usually defined as “unsolicited bulk e-mail”. This is generally done for financial reasons, but the motive for spamming may be social or political. Unsolicited means that the recipient has not granted verifiable permission for the message to be sent. Bulk means that the message is sent as part of a larger collection of messages, all having substantively identical content (Cheng, 2004). Rough estimates conclude that e-mails like “Buy this product” or “Participate in this campaign” are more than 60% of what is the normal daily load (Doyle, 2004). Generally, the longer an email address has been in use, the more spam it will receive. Moreover, any email address listed on a website or mentioned in newsgroups postings will be spammed disproportionally. Mailing lists are also a good target. A variation of spam is spim. It is defined as unsolicited commercial messaging produced via an instant messaging (IM) system. It disperses messages to a pre-determined set of screen names, which are generated randomly or are harvested off the Internet.

• • •

spammers face penalties of imprisonment up to 5 years and/or high fines. the falsification of the sender identity or header information, the harvesting of electronic addresses and the unauthorized manipulation of computers and servers is penalized (Sec. 4). advertisers are obliged to include an “Opt-out” option in each advertising e-mail (Sec. 5). e-mail advertisements must be labelled as such, with the addition of the abbreviation “ADV” in the line of subject (Sec. 11). the formation of a “Do-Not-E-Mail registry” is foreseen (Sec. 9) 3, where the internet users can register themselves in order to avoid receiving advertising e-mails. Advertisers owe, theoretically, to consult this list before launching a mass electronic advertising campaign.

EU European Union has demonstrated its prompt reflex as far as the protection of European consumers is concerned, by publishing the Directive 1997/7/EC “on the protection of consumers in respect of distance” and preventing the use of certain means of distance communication (telephone, fax), without the prior consent of the consumer

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678 2006 IRMA International Conference (Art. 10). Later on, the Directive 2000/31/EC “on electronic commerce” focused further on the unsolicited commercial electronic communication prescribing the formation of opt-out registers (Art. 7). Finally the Directive 2002/58/EC “on privacy and electronic communication”, replacing the Directive 1997/66/EC, is providing a powerful legal tool against spamming. According to article 13 of the new Directive: •

•

•

the communication for the purpose of direct marketing via telephone, fax or e-mail requires the prior consent of the consumer-user (opt-in) or is acceptable in the context of the sale of a product or a service (soft opt-in). each advertising e-mail must incorporate an easy and costless “opt-out” opportunity for the recipient in order to object to such use of electronic contact details. disguising or concealing the sender identity and providing an invalid reply address for the opt-out, shall be prohibited

not in communication terms, since the present Gigabit Ethernet does not seem to congest from text messages, but from user dysphoria, caused by imponderable and excessive spam. Consumers gain utility by communicating via the net, with e-mails, and gain disutility most of their communication is spam, i.e. noise, intrusion or harassment. In this case, there is a price p per transmitted packet, whether this is charged a-priori, as a preventive measure, or afterwards, as and ad-hoc fine 7 . Therefore, the utility function of each consumer is defined as follows (Shy, 2001):

n def

Ui

Q

qi

pqi

_

j 1

qi

CHARGING SPAM Estimations and Projection In order to propose a model for charging spam, the authors of this article conducted a survey on spam. The graphical outputs of the survey can be seen in Fig. 1.6 For 8 months 16.478 active e-mail accounts where monitored, not of course on their content, but on their reaction to spam as far as an anti-spam filter was concerned, applied at the e-mail server’s level. For legal reasons having to do with the protection of personal data, it was not possible to estimate the filtering strength of the software devices that end users deploy themselves at their e-mail clients. Charging Spam: A Calculus Analysis Suppose that there are n potential spammers, indexed by i = 1, …, n. Each of them transmits q i packets to the Internet, so the aggregate number def

of transmitted packets in a given period is Q

n i 1 _

Figure 1. Spam trafficking at AUTh (Aristotle University of Thessaloniki). Blue line: the e-mail messages that AUTh’s 16.478 active users received. Green line: the number of e-mails diagnosed as spam by the Spamassasin® software. Red line: the percentage of active users deploying the Spamassasin filtering mechanism.

pqi

(1)

The where δ > 0 measures the intensity of disutility caused by spamming. _ “latency” caused by the spam effect is measured by Q / Q which is the ratio of_ actual, non infected by spam, e-mail communication capacity. _ If Q Q the network is not congested by spam. If, however, Q Q the network bristles with spam and user discontent increases. Since each consumer participates as a peer in this communication, (s)he takes the network usage by other consumers

j 1

q and chooses his/her j

usage qi that solves

qi max U i

j 1

qi

qi

q

j

_

(2)

pqi

Q

yielding that the first and second order derivatives, regarding the transmitted packets q i for maximum conditions are given by

q i . The network is

supposed to have a limited capacity, denoted by Q , which is measured

j

Q

Q Nearly all member states have already adjusted the national legislation and have established regulatory authorities like OPTA 4, that has issued its first fines5.

q

_

0

Ui qi

1 2 qi

2 _

p

Q

and

Ui (qi ) 2

1 4 (qi )3

0

(3)

Hence, the individual and aggregate packet transmission levels are _

Q2

qi

_

4(

2

_

(4)

p 2 Q 2 2 p Q)

100

% Users utilising

80

60

40

20 7,18

0

anti-Spam Software

Example: Suppose that a spammer sends spam messages to the 16.478 active email users of the Aristotle University of Thessaloniki (AUTh). – a message per day, for one month. It has been estimated for theses users that they accept on average 1.064.573,286 messages per month (see Fig. 1), therefore the distribution of messages per user for one month interval is 1.064.573,286 / 16.478 H” 65 messages. The e-mail capacity of the server is not limited however to only 1.000.000 e-mail messages per month. AUTh hosts about 50.000 students, researchers and employees. The average world user is considered to send and receive about 200 messages per month. So, the system would be saturated if all 50.000 users were sending and receiving e-mails, i.e.

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Emerging Trends and Challenges in IT Management _

Q = 200 x 50.000 = 10.000.000

(7)

Hence, solving equation (5) we have that _

Q 2 qi

10.000.000 = 622.042,6 2 64,61

(8)

Solving equation (4) for p yields p= 0,001 • per every spam message sent. Accordingly, we deduce that if detected and litigated, the spammer should be charged with p = 0,001 • per spam message, that he would be charged for 16.478 x 30=494.340 illegally sent messages. These sum up for 494. 340 x 0,001 = 494,34 •. This amount is roughly equivalent with the cost of advertising for a month to the campus with any other method, like say, distributing leaflets, having in mind of course that statistically only 1‰ of the spam recipients correspond to the advertiser, i.e. 1‰ x 16.478 = 16 individuals!

EPILOGUE AND CONCLUSIONS The combined action of substantial legal countermeasures and advanced techniques of content filtering have limited the exaltation of spam.

REFERENCES Cheng, T. (2004): Recent international attempts to can spam, Computer Law & Security Report, Vol. 20, no. 6, pp. 472-479. Doyle, E. (2004): Spam rules - and there’s nothing you can do, Elsevier Infosecurity Today, November/December, pp.24-28. Frank, T. (2003): Zur strafrechtlichen Bewältigung des Spamming, p. 177. Funk, A., Zeifang G., Johnson D. T., Spessard R. W. (2003): Unsolicited Commercial E-mails in the Jurisdictions of Germany and the USA, CRi 5, p. 141. Kasprzycki, D. (2004): Trends in regulating Unsolicited Commercial Communication, CRi 3, p. 77. LeClaire, J. (2004): Netherland issues its first fines against spammers, e-Commerce Times, 29.12.2004. Shy, O. (2001): The Economics of Network Industries, Cambridge University Press. Whitworth, B., Whitworth, E. (2004) :Spam and the Social-Technical Gap, IEEE Computer, Vol. 37, No. 10, pp. 38-45.

ENDNOTES 1

2

3 4

The spam issue is part of a more complex phenomenon concerning the governance of the Internet, the economics of networked industries, technological advances and software development. The spam issue does not merely threaten the future of a self governed Internet; it tests the tolerances of many factors for the networked economies. Therefore, justified legal action should be enforced.

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5

6

7

E.g. America Online Inc. v. Cyber Promotions Inc. (E.D. Pa. 1996), CompuServe Inc. v. Cyber Promotions Inc. (S.D. Ohio 1997), Hotmail Corp. v. Van$ Money Pie Inc. (N.D. Cal. 1998), America Online Inc. v. LCGM Inc. (E.D. Va. 1998). Controlling the Assault of Non-Solicited Pornography and Marketing Act of 2003, 15 U.S.C.A. § 7701-7713. See further analysis by Funk, 2003. OPTA, Netherland’s Independent Post and Telecommunications Authority. http://www.opta.nl. E.g. US$ 61.000 against an individual, who was involved in four spam campaigns, US$ 34.000 against a company spamming about financial software, $27.000 against a company sending spam text messages on mobile phones (LeClaire, 2004). Statistical data from a survey conducted at the Network Operations Center (NOC) of the Aristotle University of Thessaloniki (AUTh) from 1.10.2004 till 30.4.2005. See supra note no. 4.

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680 2006 IRMA International Conference

Analysis of Information Security in Supply Chain Management Systems Ibrahim Al Kattan, Ahmed Al Nunu, & Kassem Saleh Engineering Systems Management, American University of Sharjah, [email protected]

ABSTRACT This paper presents a quantitative information security model using measurable values to describe the security of information systems in supply chain management (SCM) systems, [1]. There are four main drivers in a SCM system: 1) suppliers, 2) manufacturers and inventories, 3) distributors and retailers, and 4) the customers [2]. The security of supply chain management concerns the security of various interactions among these drivers. Each driver requires a different security level relevant to the services it contributes to the overall SCM system. A transition matrix representing the semi-Markov chain model of each driver is developed. Then, a system-wide security for SCM is produced using the transition matrices of each driver to reach a steady state of SCM information security. The model includes nine different levels of attacks presenting several scenarios for an intruder. Comparison of the steadystate security for multi driver model with different levels of attacks is presented. An analysis of the results is then presented and discussed.

1. INTRODUCTION Information security management has become an integral part of supply chain management. The importance of security is more evident as the value of system assets to protect increases. The supply chain management drivers often face the challenge of integrating security into their systems development from suppliers to customers. The main goals of security are: Confidentiality; Integrity; Availability and Accountability, (CIAA). The security involves three system elements; software; hardware; and information. The main focus of this research is on the performance analysis of information security (PAIS) through supply chain management (SCM) drivers. The security functions should be integrated and well communicated through all supply chain drivers with regular test warnings and feedback for recovery from any attack. This research will focus on the development of a quantitative model to provide a measurable description of security. In addition, we will analyze and compare the security among the supply chain drivers for different levels of attacks. A semi-Markov chain model will be developed to present several scenarios with different levels of attacks [1]. Improving the performance of information among the supply chain drivers has a valuable effect on customer satisfaction. But due to the existence of competitors, hackers, and intruders information should be secured at the supply chain parties while being shared. The process starts

Figure 1. Flow of information and the physical parts through the SCM drivers

INFORMATION SECURITY CONFIDENTIALITY, INTEGRITY, AND AVAILABILITY

Supplier Raw Material

Manufacturer Inventory

Distributor Retailer

Customer

THIRD PARTY LOGISTIC AND TRANSPORTATION “3PLT”

with an order of raw materials and/or semi finished parts from the supplier. Then they are used for the manufacturing or assembling processes, transported to the distributor, then to the retailer, and to the final users-the customers. Usually, the supply chain parties could come from different countries, or regions, with different levels of technologies and levels of securities. In fact, most supply chain management systems are global in nature. For these reasons, sharing information among them will be truly vulnerable to the individual party and to the supply chain security [3, 4]. One example is e-commerce: the customer has to insert a credit card number, address, and other information which should be secured during transaction processing. Figure 1 shows the flow of information, the goal of security, and the physical flow of parts through the SCM drivers.

2. LITERATURE REVIEW The overall performance of information security of SCM system could be improved drastically by adopting suitable security standards. Security standards could be used to develop measurable values for CIA and to assess these values when collected. These values can de used for building a quantitative model for security. Jonsson et al [3] are the pioneers in using a quantitative analysis approach of attacker behavior based on empirical data collected from intrusion experiments. They divided the attacker’s behavior into three different phases: the learning phase, the standard attack phase, and the innovation phase. The probability for successful attacks is shown to be considerably higher in the standard attack phase. Lambrinoudakis et al [5] presented a probabilistic structure, in the form of a Markov model. The model provides detailed information about all possible transitions of the system in the course of time. Lambrinoudakis, stated that the probabilistic structure enables both the estimation of the insurance premium and the evaluation of the security investment. Madan et al [6] initiated security attributes for intrusion by applying a quantitative model. The model is run for steadystate behavior leading to measures like mean time to security failure, (MTSF). Madan, used the steady-state to find the probabilities for confidentiality, integrity, availability and the value of absorbing states representing the MTSF. Ortalo et al [7] introduced a stochastic model by using Markov chain to obtain a steady state. The model allows obtaining the mean time to security failure by evaluating the proposed measure of operating security. Trivedi [8] considers that the attacker could arrive at a random time, just as a failure may occur randomly. Also, he used a Markov process to estimate the amount of time or effort that an attacker has to spend in injecting an attack. This could be modeled as a random variable that can be described by choosing Poisson distribution functions. Wang, C. et al [9] developed a quantitative security model by using a semi-Markov model for an intrusion tolerant system.

3. SECURITY MODEL An attacker’s behavior is unpredictable and random in nature which represents a stochastic process. The security model developed in this research is based on stochastic processes. A stochastic process is an evolution model where the systems are either exhibiting inherent randomness, or operating in an unpredictable environment. This unpredictable behavior of attackers might be in more than one form. The semi-Markov chain process is considered to be an appropriate

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Emerging Trends and Challenges in IT Management Figure 2. Security state diagram of a Driver under attack

681

Table 1. Proposed CIAA for SCM Multi driver Driver1 Driver2 Driver3 Driver4

0

pC 0.25 0.10 0.05 0.40

pI 0.25 0.40 0.05 0.05

p Acc 0.05 0.05 0.10 0.10

pA 0.05 0.05 0.40 0.05

pCIAA 0.60 0.60 0.60 0.60

1

these scenarios of attacks. These levels of attacks are (15%, very low; 25% low, 35% - 45% more or less low, 50%, medium, 55% - 65%, more or less medium, 75%, high 85% very high ) are tested to present different security responses. So, repeating the same process on the GTM for each attack level, we obtain nine steady state matrices.

2 3

The following steps are used to develop the study state security for SCM drivers:

4

5

1. 2. 3. 4.

6 7

5. 0 1 2 3

N or m a l s tate V u ln er ab ility fou n d A tta ck s tar t A ttack C o n fid e n tiality

4 5 6 7

A ttack I n te g r ity A ttack A v a ila b ility A ttack A cc ou n ta b ility F a ilu re

modeling tool to illustrate the behavior of attackers. Markov chains have a special property that, the probability of any event moving to future state depends only on the present state; hence it is independent of past events. Attacker’s process fits well this description, so Markov chains provide an important kind of probabilistic model for attackers. The structure of a generic model for the security of any driver in the SCM is shown Figure 2 [6]. The eight states of the security system and their links (probabilities) are indicated in Figure 3. From all the states, the system can return back to state 0, the normal state, with different level of probabilities and with different degrees of losses. Below, is a general transition matrix (GTM) formulation of the relation among the states and their probability.

4. PERFORMANCE ANALYSIS The security of supply chain management is a state-wide application which concerns a variety of decisions about the interactions and security of several drivers. The steady state probabilities of supply chain management could be developed by generating an individual Markov chain for each driver. The proposed values of pC, p I, pA, pAcc for each driver (depending on its mission) is shown in Table 1. However, the reader can use this model for many drivers and use corresponding CIAA data. Next step to develop a generic transition matrix GTM for each driver (i) created by substituting the parameters of pC, pI, p A, p Acc from Table 1. The model proposed nine different levels of attacks to present

0 0  1  p1  2  p2 3  p3 P=  4  p4 5 p  5 6  p6 7   1

1

2

3

4

5

6

1

0

0

0

0

0

0

p12

0

0

0

0

7

0

0

p23

p24

p25

p26

0

0

p33

p34

p35

p36

0

0

0

p44

p45

p46

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

p66 0

0   0  0   p37   p47  , where,  p57  0   0 

The steady states of SCM for system wide can be achieved by multiplying the matrices of all drivers as presented in Table 2. The steady states probability for system wide and CIAA could be found using the following relationships:

π S = π 0 + π 1 ; and π C = 1 − π 3 ; π I = 1 − π 4 ; π A = 1 − (π 5 + π 7 ) ; π Acc = 1 − π 6 The state wide system security for SCM has less vulnerability leading to better security due to the sharing of information about attacks. Once an attack on a Driver occurs, the information about this attack could be shared among the remaining drivers. Therefore, an individual driver is more vulnerable than a SCM. Figure 4 illustrates 5 curves one represents SW for a SCM as an integral system and the other 4 curves represent 4 drivers as individual security unit. In Figure 4, the curve for system wide (SW) security shows improvements for all levels of attack (15% - 85%). Curves D1, D2, D3 and D4 are representing the security for Driver1, Driver2, Driver3, and Driver4, respectively. These curves show a much lower security level than the overall SCM security. On the other hand, when each driver represents individual business where their security information are not shared, each of them will be more vulnerable to an attack as shown in Figure 4.

5. CONCLUSIONS AND REMARKS This research developed a quantitative model using measurable values to describe the information system security of four drivers in statewide application of SCM. A semi-Markov chain model was used to describe different security levels. This model is used to present several scenarios with different levels of attacks. The model has been tested for SCM with Table 2. System wide security for SCM when it reaches a steady state

Figure 3. Generic Transition Matrices (GTM)

0

Develop 4 matrices of GTM for each driver. Use GTM for each driver at nine attack levels (36 GTM). Solve for the steady state matrix (SSM) for individual drivers. Find the system wide SW security by multiply each driver GTM to get the SW transition Matrix. Run the SW transition matrix to get the study state for the SCM system as a security unit.

p12 + p1 = 1 p23 + p24 + p25 + p26 + p 2 = 1 p33 + p34 + p35 + p36 + p37 + p 3 = 1 p44 + p45 + p46 + p47 + p 4 = 1 p57 + p5 = 1

Attacker Normal π0 level 0.15 0.5529 0.25 0.5203 0.35 0.4946 0.45 0.4747 0.50 0.4668 0.55 0.4602 0.65 0.4510 0.75 0.4473 0.85 0.4498

V π1 0.3302 0.3029 0.2800 0.2610 0.2528 0.2454 0.2332 0.2247 0.2207

Att π2 0.0783 0.1172 0.1477 0.1709 0.1800 0.1874 0.1973 0.2003 0.1955

C π3 0.0219 0.0337 0.0439 0.0527 0.0565 0.0601 0.0663 0.0709 0.0733

I π4 0.0031 0.0047 0.0062 0.0074 0.0079 0.0085 0.0094 0.0101 0.0105

A π5 0.0031 0.0047 0.0062 0.0074 0.0079 0.0085 0.0094 0.0101 0.0105

p66 + p 6 = 1

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Acc π6 0.0075 0.0115 0.0151 0.0181 0.0195 0.0208 0.0232 0.0251 0.0266

F π7 0.0032 0.0049 0.0065 0.0079 0.0085 0.0092 0.0104 0.0117 0.0131

Security πS 0.8831 0.8232 0.7746 0.7357 0.7196 0.7056 0.6842 0.6720 0.6705

682 2006 IRMA International Conference Figure 4. Comparing SCM versus individual driver

6. REFERENCES [1]

0.90

0.85

[2]

0.80

[3]

Security

0.75 SW

0.70

0.65

[4]

D3 D1

0.60

D2

D4

0.55

[5] 0.50 0.15

0.25

0.35

0.45

0.55

0.65

0.75

0.85

Attack Level Driver 1

Driver 2

Driver 3

Driver 4

System wide Security

four drivers where each driver provides different services within SCM. The model runs for steady-state using MATLAB for all combinations. The analysis of the model and graphical representation show that the SCM sharing security and information has been improved at all level of attacks. Individual driver exposed to higher risk of attack which could lead to a higher vulnerability of the SCM, if the information about its own vulnerability and risk level are not shared with other drivers. In the future, we would like to generalize our quantitative model to analyze the security of multi-agent based systems and then apply it to electronic commerce systems. Moreover, we would like to carefully study the problem of assigning probabilities for different security goals and drivers, and the correlation between the elements of the CIAA security model.

[6]

[7]

[8]

[9]

AL Nunu, A. M., “Information Security in Supply Chain Management – A Quantitative Approach”, MS Thesis in Engineering Systems Management, American University of Sharjah, UAE, 2005. Sunil Chopra and Peter Meindl, Supply Chain Management, 2nd ed Prentice Hall, 2004. E. Jonsson and T. Olovsson, “A Quantitative Model of the security Intrusion process Based on Attacker Behavior,” IEEE Transaction on Software Engineering, vol. 23, no. 4, pp. 235245, 1997. Konstantin Knorr and Susanne Rohrig, “Security requirements of e-business processes,” in Proceedings of the First IFIP Conference on E-Commerce, E-Business, and E-Government (I3E) 2001, pp. 73-86. Costas Lambrinoudakis, Stefanos Gritzalis, and Petros Hatzopoulos, “A formal model for pricing information systems insurance contracts,” Computer Standards & Interfaces, vol. 27, pp. 521-532, 2005. Baharat B. Madan, Katerina Goseva-Popstojanova, Kalyanaraman Vaidyanathan, and Kishor S.Trivedi, “A method for modeling and quantifying the security attributes of intrusion tolerant systems,” Performance Evaluation, vol. 56, pp. 167-186, 2004. R. Ortalo and et al., “Experiments with quantitative evaluation tools for monitoring operational security,” IEEE Transaction on Software Engineering, vol. 25, no. 5, pp. 633-650, 1999. K. S. Trivedi, Probability and Statistics with Reliability, Queuing, and Computer Science Applications, 2nd ed. New York: Wiley, 2001. Chenxi Wang and William A. Wulf, “Towards A framework for security measurement,” Logistics Information Management, vol. 15, no. 5/6, pp. 414-422, 2002.

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Emerging Trends and Challenges in IT Management

683

OUML: A Language to Map Observed Usages to BPML Jean-Mathias Heraud, Laure France, & Joseph Heili Graduate School of Chambery, 12 avenue d’Annecy, 73181 LeBourget du Lac, France, {jm_heraud, l_france, j_heili}@esc-chambery.fr

INTRODUCTION Business Process Management (BPM) has widely spread out recently. More and more companies use systems based on BPM [7]. One of the main reasons of this enthusiasm for the BPM is the possibility to improve a process [6] by recording the process progress in order to perform optimizations in the process definition/implementation [8]. However, the process progress recording is unfortunately an approach too limited to help the process reengineering. We thus propose an approach that consists of separating the usage collect and the process progress first, and then, of linking these elements thanks to a description language of usages: OUML (Observed Usage Modeling Language). This approach, coupled to a matching system, allows us to go beyond these limits. The paper is organized as follows: We show in section 2 the limits of the process progress recording to help the process reengineering. Then, we propose in section 3 our approach of the collect, and then, in section 4, we present OUML (Observed Usage Modeling Language), our description language of usages. In section 5, we discuss this approach. Finally, we show in the discussion the potentialities of our approach for the process reengineering.

research framework, we use this type of software to trace during experiments the user activities by recording all these keystrokes, the list of the computer processes that are executed, the titles of the dialog boxes displayed on the screen and their content. In order to lead experiments, we developed a software agent capable of logging the user activity, and of exchanging the collected information with other agents of the same kind (observer agents) or agents specialized in the collect and the processing of this information type (collector agents). However, we can note that this multi-agent architecture is justified by the work we undertake on the collaborative issues, beyond the scope of this paper (see [2] for more details). The use of keyloggers may be opposed to anonymity which constitutes one of the aspects of privacy. This assertion has to be moderated according to the legislations of the various countries where such systems are used. Within the framework of our experiments, we retained the four following principles inspired of the Information and Telecommunication Access Principles Position Statement [11]: • • •

BPMS: LIMITED POSSIBILITIES FOR PROCESS REENGINEERING “BPM refers to a set of activities which organizations can perform to either optimize their business processes or adapt them to new organizational needs” [11] and BPMS refers to the software systems which support BPM. Usually, BPM is described by three phases: design, execution and monitoring. Currently, most of the BPM Systems enable the observation of the activated process progress [4] for the monitoring phase. This observation is performed by recording the different states of the activities composing these processes. The transitions and duration are then deduced from the previous observations on a common timeline. These possibilities of observation help to determine which processes have been performed totally or partially, which ones have been successful or failed. Indeed, this type of observation permits a comparative analysis between recommended process and performed process. This comparison allows us to check whether the foreseen sequences are fulfilled or some activities are omitted or permuted. However, this type of observation is limited due to the fact that we can observe only what was recommended. Any activity not foreseen in the process will not be observed and thus will not be detected. Consequently, the reengineering help possibilities are restricted to adjustment, suppressions or permutations of process activities. Indeed, the process quality manager will not be able to rely on this observation to determine which activity must be added to the process to meet a need. To raise this type of limits, we thus propose another type of observation that we present in the next section.

OBSERVING THE CLIENT COMPUTERS Keyloggers are small applications that are executed on a computer client. These programs are usually executed without the knowledge of the computer users, since their purpose is to spy the users. The basic functioning principle is to record every keystrokes in a text file. In our

•

No data should be collected from people not aware Individuals should have the choice to decide how their information is used and distributed Individuals should have the right to view any data files about them and the right to contest the completeness and accuracy of those files Organizations must ensure that the data are secure from unauthorized access

The data logged by the observer agents are stored in a generic log format (GLF) [9]. Indeed, to be able to obtain the log sources that store the information in other formats such as apache logs, we defined rewriting rules enabling the transformation of the main log formats into GLF. The collector agent uses these rules to be interfaced with multiple log sources active on the computer (other than the user activity, for instance, the logs Apache on a web server). The agents can communicate to each other via messages in GLF format, but these messages are at a low level of abstraction. Therefore, we need a higher level, namely the trace described in OUML format. We introduce OUML in the following section.

DESCRIPTION OF USAGES: OUML We defined a language that allows us to represent the performed usages in a more abstract way than just a set of raw logs. The idea is to define an intermediate level between logs and the process modeled by BPML [1], by using a vocabulary close to BPML, but with the own logic of the logs. Indeed, there is a gap between raw logs and the process while considering two major “things”, activities and roles. Therefore, we need to make individual activities emerge from raw logs. For instance, we use the notions of activity and sequence defined in BPML; however, we did not take into account the choice operator, since only one user path is observed in the logs. Nevertheless, this operator could be reintroduced later on at another level, when we will need to combine several traces or define a trace query language. We present here the general lines of the OUML language.

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684 2006 IRMA International Conference BASIC STRUCTURE OF AN OBSERVED USAGE

Figure 1. Mapping between logs, OUML and BPM

Any sequence of observed log can be expressed by an object “trace”. A trace can be composed of complex activities in ways described in the next subsection. These activities are constituted by combining simple or complex activities, where simple activities can be split into two categories: the user activities and the system activities. The user activities are: •

•

“User’s action”: Represents the task of the user (name, role, resource, etc.). This activity can have the status “started”, “completed” or “aborted”. “User’s inactivity”: Expresses a lap of time with no user’s activity observed. This activity can have the status “started” or “completed”.

The five other types of simple activities rely on the System activity: • • • • •

“System Assign”: Assigns a new value to a property. “System Call”: Instantiates a process and waits for it to complete. “System Delay”: Expresses the passage of time. “System Spawn”: Instantiates a process without waiting for it to complete. “System Synch”: Synchronizes on a signal.

COMPOSITION OF ACTIVITIES Several activities can be performed at the same time. In order to better understand the logical sequencing of the activities, we propose the following operators: • •

All(A,B) : the operator tells that the complex activities A and B are executed in parallel. Sequence(A,B) : the operator tells that the complex activities A and B are executed sequentially (B after A).

MAPPING BETWEEN LOGS, OUML AND BPM Our objective is to define the four mappings shown in Figure 1. To reach this goal, we chose to follow an incremental approach based on an experiment that we done in 2004 [5]. We are currently concerned with the first step (1) and we plan to follow the three others in the order used in the figure. •

•

•

•

Generate OUML traces from raw logs: In a first stage, we try to generate OUML traces from the logs of this experiment. This stage allows us to define a mapping (1) between raw logs and an OUML trace. The method we retain to generate OUML traces is based on a set of rules and patterns. OUML as a raw log query language: In a second stage, we use the obtained OUML traces to test a mapping (2) towards other sources of logs observed during the same experiment. This stage allows us to test OUML as a raw log query language, since several sets of raw logs correspond to one OUML trace. Mapping between OUML and BPML: With the same set of OUML traces, we then test the mapping (3) between OUML and the BPML definition of the process recommended during the experiment. BPML as an OUML query language: When this stage of modeling all the usages observed during the experiment is completed, we can work on mapping (4) OUML traces with the recommended process. This last stage allows us to define a query language for OUML trace.

CONCLUSION In this paper, we proposed a language to represent observed usages. This language is particularly useful when observations are captured from numerous sources. This work is still in progress, and thus mapping definitions between raw logs, OUML and BPML, lead to an evolution of the OUML language. The prospects at the end of this experiment are numerous. By creating a relationship between raw logs and a process modeling language such as BPML, OUML makes it possible to envisage the detection of the process execution in the observed usages. This detection may be handled a posteriori but also in real time. The applications of such a system could be, for instance, fraud detection, awareness, or knowledge management. In a more general way, increasing the richness of the observation level and clarifying the sequencing of a process are paramount stages. We already proposed some visualization tools to represent the traces in [3]. All this work will make it possible to improve the quality of the process implemented and, thereafter, to allow us to improve their level of maturity.

REFERENCES [1]

[2]

[3]

[4]

[5]

[6]

[7] [8] [9]

[10] [11]

Arkin A. (2002) “Business Process Modeling Language” From Business Process Management Initiative (BPMI). Contributions by: Blondeau D., Ghalimi I., Jekeli W., Pogliani S., Pryor M., Riemer K., Smith H., Trickovic I., White S.A., 98 pages. Carron T., Heraud J.-M., (2005) “A SMA architecture based on usages observation to support collaborative tasks”, Working Paper, Syscom, university of Savoie. France L., Heraud J.-M., Marty J.-C., Carron T. (2005) “Help through visualization to compare learners’ activities to recommended learning scenarios.”, The Vth IEEE International Conference on Advanced Learning Technologies, Taipei, Taiwan. Grigoria D., Casatib F., Castellanosb M., Dayalb U., Sayalb M., (2004), “Business Process Intelligence”, Computer in industry, Volume 53, pp.321-343. Heraud J.-M., Marty J.-C., France L., Carron T. (2005) “Helping the Interpretation of Web Logs: Application to Learning Scenario Improvement.” Workshop Usage analysis in learning systems, AIED2005: XIIth International Conference on Artificial Intelligence in Education, Amsterdam, Netherland Marty J.-C., Heraud J.-M., Carron T., France L., (2004) “A quality approach for collaborative learning scenarios”, Learning Technology Newsletter, publication of IEEE Computer Society Technical Committee on Learning Technology, Volume 6, Issue 4, pp 46-48. MacVittie L. (2005) “IT Detours On the Road to BPM”, Intelligent Enterprise Magazine, August 2005. Paulk M.C., Curtis B., Chrissis M.B., Weber C.V., “Capability Maturity Model - Version 1.1.” IEEE Software, pp. 18-27, 1993. Rambaud S., Armanet L., Jost C., (2005) “Generic Log Format (GLF) : un langage pivot pour combiner plusieurs sources de logs”, Master thesis, university of Savoie, in french. http://en.wikipedia.org/wiki/Business_Process_Management http://www.cla.ca/about/access.htm

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Emerging Trends and Challenges in IT Management

685

A Complex Data Warehouse for Personalized, Anticipative Medicine Jérôme Darmont & Emerson Olivier, ERIC, University of Lyon 2, 5 avenue Pierre Mendès-France, 69676 Bron Cedex, FRANCE, T: +33 478 774 403, F: +33 478 772 378, [email protected]

INTRODUCTION

Figure 1. Data warehouse global architecture

With the growing use of new technologies, healthcare is nowadays undergoing significant changes. The development of electronic health records shall indeed help enforcing personalized, lifetime healthcare and pre-symptomatic treatment, as well as various analyses over a given population of patients. Such an information-based medicine has to exploit medical decision-support systems and requires the analysis of various, heterogeneous data, such as patient records, medical images, biological analysis results, etc. (Saad, 2004). In this context, we work with a physician on large amounts of data relating to high-level athletes. His aim is to make the analyzed subjects the managers of their own health capital, by issuing recommendations regarding, e.g., life style, nutrition, or physical activity. This is meant to support personalized, anticipative medicine. To achieve this goal, a decision-support system must allow transverse analyses of a given population and the storage of global medical data such as biometrical, biological, cardio-vascular, clinical, and psychological data. Data warehousing technologies are now considered mature and can form the base of such a decision-support system. Though they primarily allow the analysis of numerical data, the concepts of data warehousing remain valid for what we term complex data. In this context, the warehouse measures, though not necessarily numerical, remain the indicators for analysis, and analysis is still performed following different perspectives represented by dimensions. Large data volumes and their dating are other arguments in favor of this approach. Data warehousing can also support various types of analysis, such as statistical reporting, on-line analysis (OLAP) and data mining. In this paper, we present the design of the complex data warehouse relating to high-level athletes. It is original in two ways. First, it is aimed at storing complex medical data. Second, it is designed to allow innovative and quite different kinds of analyses to support: 1. 2.

personalized and anticipative medicine (in opposition to curative medicine) for well-identified patients; broad-band statistical studies over a given population of patients. Furthermore, the system includes data relating to several medical fields.

It is also designed to be evolutionary to take into account future advances in medical research.

WAREHOUSE MODEL Global Architecture To make our solution evolutionary, we adopted a bus architecture (Kimball and Ross, 2002). It is composed of a set of conformed dimensions and standardized definitions of facts. In this framework, the warehoused data related to every medical field we need to take into account represent datamarts that are plugged into the data warehouse bus and receive the dimension and fact tables they need. The union of these datamarts may be viewed as the whole data warehouse. Figure 1 represents the global architecture of our data warehouse. Straight squares symbolize fact tables, round squares symbolize dimen-

sions, dotted lines embed the different datamarts, and the data warehouse bus is a rounded rectangle. It is constituted by dimensions that are common to several datamarts. The main dimensions that are common to all our datamarts are patient, data provider, time, and medical analysis (that regroups several kinds of analyses). Of course, some datamarts (such as the cardio-vascular datamart) do have specific dimensions that are not shared. Our data warehouse also includes a medical background datamart (not depicted), and more datamarts are currently being developed. Simple Datamarts: the Biological and Biometrical Datamarts Input biological data are the results of various biological examinations (biochemistry, protein checkup, hematology, immunology, toxicology…), which are themselves subdivided into actual analyses (e.g., an hematology examination consists in reticulocyte numbering and an hemogram). These data are available under the form of unnormalized spreadsheet files from different sources. They are thus heterogeneous and often refer to the same examination using different terms or abbreviations, use different units for the same numerical values, etc. This heterogeneity is dealt with during the ETL (Extract, Transform, Load) process. Biometrical data are measured during medical examinations. They include weight, height, pulse rate, fat percentage, and blood pressure. Though their structure is simpler than that of the biological data, they require a fine granularity. For example, the weight of an athlete may be measured twice a day, before and after training. This has an impact on data warehouse modeling. More precisely, it helps defining the granularity of the time dimension hierarchy (see below). Figure 2 represents the architecture of our biological and biometrical datamarts. The biological fact table stores an exam result under the form of a numerical value (e.g., a reticulocyte numbering). It is described by

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686 2006 IRMA International Conference Figure 2. Biological and biometrical datamarts’ architecture

component of our “complex fact” may be individually linked to the dimensions. Cardio-vascular documents and results are indeed not descriptors of the would-be fact: report, they are part of a fuzzier fact that is composed of several entities. Finally, note that cardio-vascular documents cannot currently be exploited by OLAP technologies. However, we need to store them and have them accessible for medico-legal reasons. Furthermore, extensions to the usual OLAP operators should make this exploitation possible in the near future (Ben Messaoud et al., 2004).

RELATED WORK The first family of medical data warehouses we identify are repositories tailored for later data mining treatments. Since data mining techniques take “attribute-value” tables as input, some of these warehouses do not bear a multidimensional architecture (Prather et al., 1997; Sun et al., 2004), and might prove less evolutionary than the solution we selected.

four dimensions: patient, time of the examination, data provider (typically the laboratory performing the analysis), and the analysis itself. The biometrical fact table stores numerical biometrical values (e.g., weight). It is described by the same dimensions than the biological datamart, the “analysis” actually representing a measurement. The patient, data provider, time, and medical examination dimensions are thus all shared, conformed dimensions. Attributes in dimension tables are not detailed due to confidentiality constraints.

A second family is constituted of biological data warehouses that focus on molecular biology and genetics (Schönbach et al., 2000; Eriksson and Tsuritani 2003; Sun et al., 2004), which bear interesting characteristics. For instance, some of them include metadata and ontologies from various public sources such as RefSeq or Medline (Engström and Asthorsso, 2003; Shah et al., 2005). The incremental maintenance and evolution of the warehouse is also addressed (Engström and Asthorsso, 2003). However, the particular focus of these approaches makes them inappropriate to our current needs, which are both different and much more diversified. The future developments of our data warehouse will probably exploit this existing work, though.

Note that the medical analysis and time dimensions are further organized into hierarchies, to take into account the particularities identified into the source data. Here, biological and biometrical data are distinguished: the simple biometrical data are not normalized nor organized in a hierarchy, while the biological data are. Hence, the description of biometrical facts only appear in the medical analysis dimension table, while biological facts are further described by a hierarchy of biological examinations and categories.

To sum up, the existing medical warehouse that is closest to our own is a cardiology data warehouse (Tchounikine et al., 2001; Miquel and Tchounikine 2002). Its aim is to ease medical data mining by integrating data and processes into a single warehouse. However, raw sensor data (e.g., electrocardiograms) are stored separately from multidimensional data (e.g., patient identity, therapeutic data), while we seek to integrate them all in our cardio-vascular datamart.

Each datamart is thus modeled as a snowflake schema rather than as a simpler, classical star schema. Since the biological and biometrical fact tables share their dimensions, our overall data warehouse follows a constellation schema. In such an architecture, it is easy to add in new fact tables described by existing dimensions.

RESEARCH PERSPECTIVES

Finally, our data warehouse also includes metadata that help managing both the integration of source data into the warehouse (e.g., correspondence between different labels or numerical units, the French SLBC biomedical nomenclature, etc.) and their exploitation during analysis (e.g., the interval between which an examination result is considered normal).

This work opens up two kinds of perspectives. The first one concerns the actual contents and significance of the data warehouse. It involves

Figure 3. Cardio-vascular datamart’s architecture

Complex Datamart: The Cardio-Vascular Datamart Figure 3 represents the architecture of our cardio-vascular datamart. Here, the complex nature of source data, which are constituted of raw measurements (e.g., ventricle size), multimedia documents (e.g., echocardiograms) and a conclusion by a physician, cannot be embedded in a single, standard fact table. Hence, we exploit a set of interrelated tables that together represent the facts. They are represented as dotted, straight squares. The report mainly contains the physician’s conclusion. It is the central element in our “complex fact”. It is linked to several numerical analysis results that help building the physician’s conclusion. It is also related to multimedia documents such as medical images that also help devising the diagnosis. Note that this relationship, which is represented as a bold line, is a many-to-many relationship. Some documents may indeed be referred to by several reports, for instance to take into account a patient’s evolution over time, through distinct series of echocardiograms. Each

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Emerging Trends and Challenges in IT Management modeling and adding in new datamarts. The cardio-vascular and psychology datamarts are already implemented and more are currently being developed (such as the medical background datamart) or scheduled. This helps broadening the scopes of analyses. Other output than statistical reports are also envisaged. Since we adopted a dimensional modeling, OLAP navigation is also definitely possible, and “attribute-value” views could easily be extracted from the data warehouse to allow data mining explorations. The second kind of perspectives is more technical and aim at improving our prototype. This includes automating and generalizing the ETL process on all the datamarts, which is currently an ongoing task. We also follow other leads to improve the user-friendliness of our interfaces and the security of the whole system, which is particularly primordial when dealing with medical, personal data.

ACKNOWLEDGMENTS The authors thank Dr Jean-Marcel Ferret, the promoter of the personalized and anticipative medicine project. This work has been co-funded by the Rhône-Alpes Region.

REFERENCES Ben Messaoud, R., Rabaseda, S., Boussaïd, O., & Bentayeb, F. (2004). OpAC: A New OLAP Operator Based on a Data Mining Method. Sixth International Baltic Conference on Databases and Information Systems (DB&IS 04), Riga, Latvia. Engström, H., & Asthorsso, K. (2003). A Data Warehouse Approach to Maintenance of Integrated Biological Data. Workshop on Bioinformatics, 19th International Conference on Data Engineering (ICDE 03), Bangalore, India.

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Eriksson, T., & Tsuritani, K. A dimensional data warehouse for biological data. (2003). 11th International Conference on Intelligent Systems for Molecular Biology (ISMB 03), Brisbane, Australia. Kimball, R., & Ross, M. (2002). The Data Warehouse Toolkit. John Wiley & Sons. Miquel, M., & Tchounikine, A. (2002). Software Components Integration in Medical Data Warehouses: a Proposal. 15th IEEE Symposium on Computer-Based Medical Systems (CBMS 02), Maribor, Slovenia. 361-364. Prather, C., Lobach, D.F., Goodwin, L.K., Hales, J.W., Hage, M.L., & Hammond, W.E. (1997). Medical Data Mining: Knowledge Discovery in a Clinical Data Warehouse. 1997 AMIA Annual Fall Symposium, Nashville, USA. Saad, K. (2004). Information-based Medicine: A New Era in Patient Care. (2004). ACM 7th International Workshop on Data Warehousing and OLAP (DOLAP 04), Washington, USA. 58. Schönbach, C., Kowalski-Saunders, P., & Brusic, V. (2000). Data Warehousing in Molecular Biology. Briefings in Bioinformatics. 1(2), 190-198. Shah, S.P., Huang, Y., Xu, T., Yuen, M.M., Ling, J., & Ouellette, B.F. (2005). Atlas – a data warehouse for integrative bioinformatics. BMC Bioinformatics. 6(1), 34. Sun, Y.M., Huang, H.D., Horng, J.T., Huang, S.L., & Tsou, A.P. (2004). RgS-Miner: A Biological Data Warehousing, Analyzing and Mining System for Identifying Transcriptional Regulatory Sites in Human Genome. 15th International Database and Expert Systems Applications Conference (DEXA 04), Zaragoza, Spain. LNCS. 3180, 751-760. Tchounikine, A., Miquel, M., & Flory, A. (2001). Information Warehouse for Medical Research. 3rd International Conference on Data Warehousing and Knowledge Discovery (DaWaK 01), München, Germany. LNCS. 2114, 208-218.

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688 2006 IRMA International Conference

‘Herd’ Behavior and the Bull Whip Effect: Information Access, or Risks and Rewards? Patrick I. Jeffers, Iowa State University, Department of Logistics, Operations and MIS, College of Business, Rm. 4320, Gerdin Bldg., Ames, IA 50011, [email protected] Rhoda Joseph, Pennsylvania State University, Harrisburg, School of Business Administration, 777 W. Harrisburg Pike, Middletown, PA 17057, [email protected] Francis A. Mendez, Texas State University, School of Business Administration, Department of CIS and Quantitative Methods, 601 University Drive, San Marcos, TX 78666, [email protected]

ABSTRACT “Information cascades” occur in sequential decision-making process, where the second person who ignores their own information in favor of going along with the decision of the first person could induce others to follow, sometimes even when those earlier decision-makers are misinformed. Suppliers and retailers have observed in recent years that minor variations in customer demand may cause widespread gyrations – the bullwhip effect - in inventory levels and back-orders, which increase in magnitude as the (mis)information is transmitted across the supply chain. Traditionally, the problem has been defined as information-based and has been addressed by providing increased visibility across the supply chain, at best a partial remedy. Given that for most firms the sales and marketing department is the nexus of the organization, one possible explanation for the bullwhip effect could lie in the risk-sharing and payoff policies of supply chain players. This paper presents the theoretical basis for an experiment that tests the effect of the prevailing reward system on the frequency information cascades. Proof of the main hypothesis would imply that more equitable sharing of risks and payoff in supply chain alliances can actually reduce the impact of the bullwhip effect, a new perspective on the phenomenon.

1. THE BULLWHIP EFFECT In a sequential supply chain decision-making process, small variations in consumer demand have been observed to cause increasingly larger gyrations in inventory and back-order levels as the information is relayed backwards across the supply chain, away from the retailer. This phenomenon, the “bullwhip effect” is believed to be the result of one of four supply chain related causes (Lee, Padmanabhan and Whang, 1997): (i)

(ii)

(iii)

(iv)

Demand signal processing: where a retailer incorrectly interprets a temporary surge in one period as a signal of an increase in future demand; Response to rationing: where in the case of rationed supplies, the retail may pad orders to ensure additional safety stock as a buffer against possibility stock-outs; Order batching: demand distortion that can result either from the periodic review process, or the processing cost of a purchase transaction, where the retailer could order an amount up to the volume of the previous cycle’s demand; and Price fluctuations: in instances where a retailer faces independent and identically distributed demand in each period, this could generate the bullwhip effect.

Mitigation measures focus on greater visibility for supply chain members, calling for more transparent data sharing (Lee, Padmanabhan and Whang, 1997; Eleni and Ilias, 2005; Wang, Jai and Takahashi, 2005). Some researchers are not as optimistic re this solution (Dejonckheere, Disney, Lambrecht and Towill, 2004). Firstly, most supply chain success stories are at best anecdotal (Bechtel and Jayaram, 1997), and given the predominance of the sales and marketing functions of the firm and the preponderant concern with sales maximization, firms may be easily enticed into abandon common supply-chain efficiency objectives in favor of more selfish gains. Supply chain management entails three distinct component processes: first, planning involves sophisticated demand forecasting that guide sourcing, manufacturing and operations. Next, these high level strategic plans are translated into tactical level action plans at the execution and transactional levels of the organizations, allowing for some degree of interpretation and modification which could initiate the “cascades” identified in supply chains as “the bullwhip effect.” The lure of the possibility of increased sales may lead to defection by any supply chain member, choosing instead to pursue individual goals that bear the prospect of higher rewards (Reddy 2001). As information regarding this act of defection travels further up the supply chain amended forecasts become more and more exaggerated and the bullwhip effect takes shape. Banerjee’s “herd-behavior” model (1992) refers to the associated decision-action of following the majority, where subjects choose to ignore their own information even when it may be correct, in favor of following others’ lead, sometimes even when those others are misinformed. In a sequential decision-making process, the decision of the second person to ignore their own information in favor of going along with the decision of the first could induce the rest of the chain to go along with the popular decision, resulting in an “information cascade.” Subsequent researchers (Anderson and Holt, 1997) have claimed that their laboratory findings supported Banerjee’s conclusions, while yet others have proposed alternate explanations. This paper proposes yet another possible explanation: given that both “herd-member” and firstmover strategies are valid and rational strategies, one possible explanation could lie in the reward policies used in these laboratory experiments. Subjects may be simply reacting according to the underlying system of risk and rewards of the options they face. Next follows a brief explanation of Bayesian rule and how they relate to the concept of information cascades. Then we examine some laboratory and other experiments that are believed to either support or refute the argument that information cascades are at the root of the issue and outline a methodology to test the influence of the reward structure used in the experiment.

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Emerging Trends and Challenges in IT Management 2. INFORMATION CASCADES AND ‘HERD’ THEORY The basic decision-making principle involved here is an inference technique that provides for reasoning under uncertainty, called Bayesian belief networks, which in turn is based on Bayes’ theorem. Bayesian reasoning infers that statements can be represented by variables which may take on many probabilistic values rather than simply true or false. Bayesian inference requires an initial estimate of the belief value of each variable, called prior probabilities which is then updated to represent a revised belief value as new information is received, using the Bayes’ inversion formula: P(χe) = aλ e(c) × P(χ). This rule allows computation of the revised probability of a variable χ given the occurrence of some event e, believed to be a signal of the event χ (Morawski, 1989). The likelihood ratio λ e(χ) is one of a vector of possibilities and gives the level of certainty with which each possible state of c is indicated given the occurrence of an event e. The symbol a is a normalization constant that ensures that the probabilities sum to one. The term “herd externality” conveys the potentially negative impact of this phenomenon (Banerjee, 1992). The very act of trying to use information contained in others’ decision makes each person’s decision less reflective of their own information, and in turn less informative to others (possibly an explanation for the amplification observed in the bullwhip effect. In equilibrium this “reduced informativeness” may be so severe that it may be more beneficial to constrain some decision-makers to using only their own information. The outcome of this herd behavior may be inefficient even when the individuals themselves earn the anticipated reward for their decisions. Bikhchandani, et al, (1992) used a similar concept to model the dynamics of imitative decision processes, but defines its presence as an optimizing behavior by a decision-maker who chooses to disregard his own information and follow the action of those preceding him; thus cascades could explain uniform behavior as well as fads, although the phenomenon can often be mistaken. The outcome may not always be socially desirable, but a reasoning process that takes into account the decision of others is seen as totally rational, even when the individual places no value on conformity in itself. In that sense, their paper serves as an extension of Banerjee’s line of argument.

3. PROPOSED ALTERNATIVE EXPERIMENT There are several possible alternative arguments for explaining the development of cascades. One argument (Anderson and Holt, 1996, 1997) holds that human subjects frequently deviate from rational Bayesian inferences in controlled experiments, especially when they are provided with simple heuristic rules-of-thumb. Alternatively, several non-Bayesian-based explanations for conformity can be offered. For example, psychologists and decision theorists have discovered a tendency among subjects to prefer an alternative that maintains the “status quo.” This would be evident of an irrational bias if the decision-maker’s private information is at least as reliable as the information available to the people responsible for establish the existing condition. However, in the case where it is reasonable to believe that this status quo was established on the basis of good information or bad experiences with alternatives, it should be viewed as a rational selection. Yet other researchers contend that contrary to Bayes’ rule, individuals may simply ignore prior and base-rate information in revising beliefs, thereby reducing their options to a heuristic choice between “following the majority” and “follow your own signal” (Grether, 1980; Huck and Oechssler, 2000). The question of what determines the final heuristic choice is addressed in this research. In past experiments subjects were rewarded for simply providing what is determined as the correct response by the experimenters. Could it be that the incidence of information cascades as observed is a figment of the reward system itself?

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Methodology of Proposed Experiment The proposed experiment runs as follows: an individual observes a private signal, a, or b, that reveals information about which of two equally likely events, A or B, has occurred. Each signal is informative in that there is a probability of 2 /3 that it matches the corresponding event. This setup can be physically replicated by placing balls of two distinct colors, perhaps, in opaque cups labeled A or B, as shown in the following Andersen and Holt (1996): Cup A: Dark, Dark, Light Cup B: Light, Light, Dark Note that since two of the three balls in Cup A are dark-color this means that there is a posterior probability of 2/3 that a chosen ball came from Cup A if it is dark-color, and 1/ 3 , if it is light-color, and similarly for Cup B. Individuals are then approached in a random order to receive a signal (draw a ball) and make a decision as to the event (cup) with which the signal is associated. The decision is announced publicly when it is made, while ensuring that the actual signal (the color of the ball) is not revealed. Each individual earns a fixed, cash reward for choosing the correct event, so a person wishing to maximize expected utility will always choose the event with the higher posterior probability. For the first decision-maker, the only private information would be that provided by the draw; but subsequent decision-makers would have not only their private information, but the announced decision of those that preceded them. We propose a 2×2 factorial analysis experiment (Figure 1) with the two treatments of interest being “knowledge of Bayes’ rule” and “system of rewards.” We expect to employ a total of 72 subjects comprising two main groups. One group will represent those familiar with Bayes’ rule. As an additional measure, this group then will be re-familiarized with the topic and reminded that they should consider it as a relevant option - although not required to be utilize. A second group of 36 students will represent those who have never been exposed to the concept of Bayes’ rule. These major groups will be further subdivided: in one segment all correct responses will be rewarded; in the other, only a subset of the correct decisions will be rewarded. All four segments will run concurrently. The actual experiment will be comprised of a number of sessions each involving groups of 6 subjects. This means that ultimately there will be 3 separate sequential groups assigned to each of the four categories of subjects (Figure 1). Each subject will receive a fixed nominal fee for

Figure 1. Proposed 2× 2 experimental design – information cascades Knowledge of Bayes’ rule

Bayesian-familiar subjects

Non-Bayesianfamiliar subjects

Only a subset rewarded

Only a subset rewarded

Reward System Bayesian-familiar subjects

Non-Bayesianfamiliar subjects

All correct responses rewarded

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All correct responses rewarded

690 2006 IRMA International Conference participation at beginning of the experiment. In addition, and as an incentive for maintaining high levels of interest during the experiment, winners will be rewarded with a chip after each session, which they would then cash in at the end. An information cascade can occur whenever the first two decisionmakers choose the same event, which makes it an attractive optimizing option for all subsequent decision-makers to follow suit. A cascade can also form if the first two decisions differ but the next two match. In sum, an imbalance of two decisions favoring any one of the events could muddle the informational content of any subsequent individual signal, causing that subject to ignore their own signal and go along with those preceding. In those segments where only a subset of the correct answers are rewarded, potential information cascades will be limited in size to either 3 or 4 subjects at most, whereas in those segments where all correct decisions are reward, information cascades can potentially involve all 6 participants of a session. But we are interested in a comparison of the frequency with which identifiable incidents of information cascades occur between the segments, rather than the size of the cascade. We do not expect that information cascades would be significantly influenced by a lack of understanding of Bayes’ rule although our experiment includes this possibility as a control. On the other hand if, as we expect, information cascades are more reflective of heuristic decision making based on maximizing rewards, then we would see a more distinct variation in the level of frequency, based on the reward system, being higher in the case where all correct decisions are rewarded. This would indicate that the decision space is being reduced to a simpler landscape in which decisions are based on perceived risk and reward. The question of potential reward would determine whether the subject’s motivation is gaining early mover advantage or is willing to settle for being a “member of the herd.” Each subject will be asked to complete an exit questionnaire in which, among other things they would be asked to identify the decision process they used, and to approximate the frequency with which this method was used.

Supply chain arrangements are based extensively on contracts, but to what extent these contracts proactively aim to address the issue of the bullwhip effect is questionable, given the accepted definition for this issue. The results of this experiment could be an important initial step in guiding more effective contractual arrangements in supply chains.

REFERENCES Andersen, Lisa R., Holt, Charles A., “Information Cascades in the Laboratory,” The American Economic Review, 87, 5, (1997), 847-862. Andersen, Lisa R., Holt, Charles A., “Classroom Games: Information Cascades,” The Journal of Economic Perspectives, 10, 4, (1996), 187-193. Banergee, Abhijit V., “A Simple Model of Herd Behavior,” Quarterly Journal of Economics, 107, 3, (1992), 797-817. Bechtel, C. and Jayaram, J., (1997), “Supply Chain Management: A Strategic Perspective,” International Journal of Logistics Management, 8 (1), 15 – 33. Bikhchandani, Sushil, Hirschleifer, David and Welch, Ivo, “A Theory of Fads, Fashions, Customs, and Cultural Change as Information Cascades,” The Journal of Political Economy, 100, 5, (1992), 992-1026. Grether, David M., “Bayes Rule as a Descriptive Model: The Representativeness Heuristic,” Quarterly Journal of Economics, 95, 3, (1980), 537-557. Huck, S. and Oechssler, J., “Information cascades in the laboratory: Do they occur for the right reasons?” Journal of Economic Psychology, 21, (2000), 661-671. Morawski, Paul, “Understanding Bayesian Belief Networks,” AI Expert, (May, 1989), 44-48. Reddy, Ram, Intelligent Enterprise, 15243621, 6/13/2001, Vol. 4, Issue 9.

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Emerging Trends and Challenges in IT Management

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The Challenge of E-Business in China: Exploring Competitive Advantage within the Electrical Appliance Industry Yan Tao, Matthew Hinton, & Stephen Little Open University Business School, Walton Hall, Milton Keynes, MK7 6AA, UK, T: +44 1908 655888, F: +44 1908 655898, {y.tao, c.m.hinton, S.E.Little}@open.ac.uk

ABSTRACT This paper explores the sources of competitive advantage gained from e-business applications within the context of the Chinese electrical appliance industry. Findings from two case studies are described. The case companies are leading players within this sector. Specific attention has been paid towards using the value chain framework to analyse the main sources of competitive advantage.

INTRODUCTION This paper provides empirical evidence, from two ongoing case studies, of how established organisations gain competitive advantage through their e-business applications in the electrical appliance industry. Furthermore, it offers insight into how value chain theory helps to explain this phenomenon within the Chinese economy. E-business is defined as ‘the sharing of business information, maintaining of business relationships, and conducting of business transactions by means of telecommunications networks’ (Zwass, 1996).

LITERATURE One of the key issues in e-business research is how established companies can gain competitive advantage. Despite the interest in e-business applications by traditional firms, few empirical studies have been carried out to look at how ‘clicks-and-mortar’ approaches offer competitive advantages, especially from a specific industry perspective (Steinfield et al., 2002; Kauffman & Walden, 2001). Moreover, the Chinese government has identified e-business as a critical technology for closing the economic gap between China and the USA, Japan and European Union. China has 94 million Internet users, the world’s second-largest online population. Although the Internet population has grown rapidly, e-business has not been accepted on a large scale due to the relative underdevelopment of the financial infrastructure and a lack of trust among potential customers with respect to electronic transactions (CINIC, 2005). However, progress has been made with respect to: 1) 2) 3)

Growing acceptance of online payment; Consumer acceptance of the Internet and e-commerce; More categories of products and services exploiting e-commerce channels.

Consequently, it is critical to investigate how to gain competitive advantage from e-business applications in the context of Mainland China. This paper investigates the key sources of competitive advantages gained from e-business applications made by Chinese electrical appliance companies and whether the value chain theory and its related theories can explain this phenomenon. Research conducted by the authors over the last two years has shown that the value chain framework is useful to identify and categorize possible e-business application areas in Chinese real estate industry. Moreover, this categorization makes identification of key sources of competitive advantage explicit. How-

ever, this framework cannot fully explain the success of e-business applications nor the realization of intended motivations (Tao and Hinton, 2004).

METHODOLOGY The key aims of this research are to identify the main e-business applications and sources of competitive advantage, as well as any common patterns. Given the nature of the research this study adopts a qualitative case study approach as an appropriate choice of methodology for developing theory (Eisenhardt, 1989). As part of a set of cases, two companies were chosen in the Chinese electrical appliance industry. The interviews were conducted in two stages: 1) in the period from July to August 2004; 2) in the period from May to June 2005. In these two stages, similar case study protocol has been followed to facilitate both longitudinal and cross-case comparison.

RESULTS Alpha Inc is a multinational corporation manufacturing a wide range of household electrical appliances. The Company has a leadership position in the Chinese electrical appliance industry. Its adoption of e-business applications was promoted by its CEO in 2000 following a business process re-engineering program. It has a B2C website which sells its products directly to end consumers. However, 90% of payments are made via cash-on-delivery. It utilizes a range of B2B applications. Through e-procurement it purchases 95% of all raw materials online, creating new value by selling the raw materials purchased online to other manufacturers. In addition, both CRM and ERP applications are used to manage large dealers and high volume customers as well as inventory and production management. Beta Inc is a subsidiary of China’s leading maker of mobile phones and televisions and Beta Inc focuses on the electrical accessories industry. Its use of B2C is limited to the provision of online customer order forms and company promotion. Its B2B applications are used to manage its dealer network, and has trialled the adoption of a dealers’ inventory management system. However, this has met resistance from dealers. Beta Inc has also moved into e-procurement. Table 1 summarises the development of the case companies’ use of e-business: The results have identified several common themes. These center on: i.

ii. iii.

Approaches to improving supply chain management: This includes sharing data, integration and collaboration with upstream and downstream companies. A pragmatic approach to what is achievable through e-business within the Chinese context. The importance of integrating business process through ebusiness applications. This is coupled with a focus on group perspective rather than from an individual company perspective with the aim of saving resources of the whole enterprise.

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692 2006 IRMA International Conference Table 1. The key features of the case companies’ use of e-business

Company E-business (EB) strategy

Main EB applications

Benefits of EB adoption

Impacts on OS & culture, industry

Obstructions of EB adoption

1) Adopt B2B & B2C on the whole Alpha Inc corporation (2004) scale; 2) Use EB to create value; 3) Become an e-shopping mall (Aim 3).

1) B2C; 2) B2B: eprocurement; customer relationship management (CRM) to dealers and key customers; ERP; 3) Internal mngt: HRM, KM.

1) Optimize supplier’s network leading to improved collaboration; 2) Better supply chain management and shorten product life cycle; 3) Save cost on raw materials; 4) Increase customer base; 5) Provide timely and accurate information.

1) Redefine organizational structure. 2) Innovation culture contributes to EB adoption. 3) A national role model. 4) B2C has little influence on the industry.

1) The low volume of B2C sales turnover; 2) Conflicts between online and offline channels; 3) Information transparency leads to changes on leaders’ power.

1) Improve information flow; 2) Improve enterprise IS; 3) Improve the growth rate of online sale; 4) Cancel Aim 3.

1) Cancel the provision of personalized made-on-order in B2C; 2) Build online customer centre.

1) EB causes polarization of companies in the industry through shortening product life cycle, improving company’s brand name and customer services.

1) Organizational structure was often readjusted to accommodate the rapid growth of the enterprise.

1) B2C sales turnover improved by methods of charging delivery fee, marketing promotion and setting assessing benchmark.

1) Apply enterprise information portal (EIP); 2) Apply IT in the whole corporation; 3) EB strategy integrated into business strategy.

1) B2C website only for marketing function; 2) B2B: channel mngt to dealers; manage dealer’s inventory (Application 2); 3) Internal mngt: channel mngt to subsidiaries;HRM; financial mngt.

1) Improve working efficiency; 2) Change employees’ concept on IT; 3) Contribute to company’s brand name.

1) Established an independent IT department and a commercial department; 2) Competitors feel the pressure of adopting EB.

1) Cooperation from dealers: channel conflicts; 2) The employees’ concepts and working habits.

1) Standardize IS and integrate systems to fit rapid company growth; 2) Enforce the implementation of the systems; 3) Add new systems such as product development management.

1) Adopted EIP and eprocurement; 2) Realized integration of functional systems through EIP. 3) Improved in B2C; 4) Adjust Application 2.

1) Further improve on efficiency and order handling time; 2) Cost saving on procurement and IS updating; 3) Optimize supplier’s network; 4) Realize information integration and real time information sharing.

1) Have minor impacts on organizational structure although organizational structure is subtly adjusted continuously.

1) To maintain the security of EIP; 2) To contribute to implementing of mngt concepts.

Changes In 2005

Beta Inc (2004)

Changes In 2005

iv.

v.

vi.

The importance of implementing information systems or ebusiness from a whole enterprise perspective rather than from an individual subsidiary company perspective with the aim of saving resources of the whole enterprise. Both companies cite brand as one of their main sources of competitive advantage and see their e-business applications as key contributors to building and maintaining their brand name. Both companies lack formal evaluation systems although they have evaluation indices for each small project.

Differences of e-business application exist between these two companies. Beta Inc has adopted enterprise information portal, e-procurement, CRM, and online channel management to manage its value chain. These applications have improved the efficiency of the value chain. Accompanying the adoption of enterprise information portal, the information within different systems has been integrated. Alpha Inc has taken this a stage further by concentrating on e-business applications facing end consumers along its value chain. Whilst the adoption of e-business applications has influenced organizational structure within both companies, the extent of this varies. In

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Emerging Trends and Challenges in IT Management Alpha Inc, the whole business process and organizational structure have been re-defined, whereas in Beta Inc organizational structure has not been redefined thoroughly. Only some adjustments have been made to establish two new departments. Equally, the two companies are at different stages of e-business strategy. For Beta Inc the main aim of ebusiness application is to support business operation. Hence, the key is to let its supply chain run smoothly. So, they have no strong interest in B2C. By contrast Alpha Inc aims to support its entire business operation through e-business approaches and explores every opportunity of using e-business to create business value

CONCLUSIONS Thus far, the research has begun to investigate the main e-business applications within the Chinese electrical appliance industry and their impact on competitive advantages. In general, the value chain framework is useful to identify and categorize possible e-business applications in the industry. In this industry, e-business adoption is necessary for leading companies to improve operational efficiency. They firmly believe that e-business applications are contributing to their gaining competitive advantage. Furthermore, they realize that the key to understanding the e-business concept is the realization that e-business is only a method to solve problems arising within the company. Hence,

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they need to take a pragmatic approach and focus on the fundamentals of the business. Further work is planned to explore the disparity between anticipated and realized competitive advantages derived from e-business adoption.

REFERENCES CINIC

(2005) http://www.cnnic.net.cn/resource/develst/ cnnic200107rep-3.shtml accessed on 20 April 2005. Eisenhardt K. M., (1989) “Building theories from case study research”, Academy of Management Review, Vol.14, pp 532-550. Kauffman R. J. and Walden E. A., (2001) “Economics and electronic commerce: survey and directions for research”, International Journal of Electronic Commerce, Vol.5, No.4, pp 5-116. Steinfield C. et al, (2002) “The dynamics of click-and mortar electronic commerce: opportunities and management strategies”, International Journal of Electronic Commerce, Vol.7, No. 1, pp 93-119. Tao Y. and Hinton M., (2004) “Exploring sources of competitive advantage in e-business application in Mainland Chinese Real Estate Industry”, Proceedings of International Conference on Electronic Business, Beijing, China, pp 655-660. Zwass V., (1996) “Electronic commerce: structure and issues”, International Journal of Electronic Commerce, Vol.1, No. 1, pp 3-23.

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694 2006 IRMA International Conference

Feature Requirements in Educational Web Sites: A Q-Sort Analysis Sunil Hazari, Richards College of Business, University of West Virginia, Carrollton, GA 30118, Tel: (678)839-4842, [email protected]

INTRODUCTION

LEARNABILITY

There is relative paucity of original research that explains phenomena related to usability of educational websites. Educational websites can be used to provide web-based instruction, which itself is a relatively recent phenomenon and research in this area is in its infancy. Educational websites are built with a different set of criteria as compared to other sites, such as those having an e-commerce or marketing focus. More research is needed to build a theoretical foundation for feature requirements in educational web sites. The online environment has become a powerful interactive medium for promoting higher order thinking skills in students. This environment uses a web based interface in which students interact with course materials, other students and the instructor. Usability of the web site plays an important part in meeting learning objectives specified in course material being delivered online (Hazari, 2005). As in any new approach to teaching and learning, critical issues need to be examined before Web-based instruction is fully integrated into teaching processes. When developing educational web sites, features that support pedagogy should be given primary consideration. It is therefore important to identify key elements that will have maximum impact on learning. Using Q-sort analysis (which is a type of Factor Analysis), this study will investigate feature requirements of educational websites. Based on the analysis of user requirements in relation to several variables that were identified from review of literature, group characteristics should emerge. Similarities and differences between groups will be investigated and implications of these results for development of educational web sites will be presented in this study.

4. 5. 6.

REVIEW OF LITERATURE Although there exists much literature on traditional teaching and learning, the use of web for education is a relatively recent phenomenon and research in this area is in its infancy. Bonk & Dennen (n.d.) call most web materials to be “pedagogically negligent”. Janicki & Liegle (2001) reported that web-based educational material are generally poor in educational content as authors of web based material have never had a course in learning theory and the web content they develop lacks foundations of learning theory. On the other hand, professionals such as teachers who may have knowledge of learning theories lack the technical skills to develop educational materials for the web (Murray, 1996). Educational web site development is not an exact science and these sites are built with a different set of criteria as compared to other sites, such as those having an e-commerce or marketing focus. More research is needed to build a theoretical foundation for educational web site design and web-based instruction. The review of literature has been used to extract following statement variables (under 3 major criteria) relating to usability of educational websites: Operational definitions of these variables as it relates to the study are provided below: USABILITY 1. 2. 3.

Ease of navigation through website [NAVI] Visual appeal of web pages [VISU] Consistency of design between webpages [CONS]

Clearly stated objectives and instructions [OBJT] Quality of instructional content [CONT] Good Interactivity (such as Quizzes, simulations) [INTR]

TECHNICAL FUNCTIONALITY 7. 8. 9.

Multimedia elements (such as audio/video) [MULT] Web page download/refresh time [REFR] Cross browser (such as IE, Netscape) functionality [COMP]

Usability can be defined as how a user can use the functionality of a system in relation to 1) how easy it is to learn, 2) how efficient it is to use, 3) how easy it is to remember, 4) how it can be used with few errors, and 5) how pleasant it is to use (Lu & Yeung, 1998). Research on usability exists (Palmer, 2002) but many websites do not apply these principles thereby making them difficult to use. When developing websites, one of the first questions an organization should answer is what is the purpose in creating this site? To an educational institution, the overall goal may be to determine how the site can be used to enhance the quality of learning in students. Whatever the motivation, it is essential to keep these goals at the forefront when planning, developing and maintaining the websites (Warlick, 2005). Educational websites in particular can benefit from learnability features. Key factors in evaluating a site’s learnability include clearly stated objectives and instructions, quality instructional content, and good interactivity throughout the site (Conner, n.d). Technical features of websites such as download times, image refresh rate, use of audio, video, ability to work with different browsers often determine success rate of websites in attracting repeat visitors (previously also referred to as sticky sites). For development of educational websites, these elements become especially important because equipment used in educational institutions is not state-of-the-art, and may not be able to support cutting edge technologies such as high bandwidth Java applets that may be embedded in Web pages for purpose of interactivity. Use of multimedia elements including audio and video, web page download time, and cross browser functionality are key considerations when evaluating the technical functionality of an educational site.

METHODOLOGY The sample in this study consisted of graduate business students. Students were given instructions to visit a web site that explained the nature of the study and provided information on how the Q-sort statements should be sorted. This was important since students are more used to completing questionnaires in survey format that use Likert scale, open-ended, or close-ended questions (such as those used during end of term class evaluation of instruction), but may not be familiar with the peculiarities of the Q-sort procedure. Q-sort methodology relies on using theories for item development. It is useful in exploratory research and a well-developed theoretical literature guides and supports its users (Thomas and Watson, 2002). Q sort uses ipsative (self-referenced) technique of sorting participant’s statements about subjective conditions. It is a variation of factor

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Emerging Trends and Challenges in IT Management Table 1. Participant Ranked scores Statement Ease of Navigation Visual Appeal Consistency of design Clear Objectives/Instructions Quality of instructional content Good Interactivity Multimedia Element Web page download time Compatibility across browsers

Mean 3.84 3.00 2.36 3.49 3.72 3.21 1.98 3.00 2.38

SD 0.98 1.03 1.06 1.01 0.96 0.88 0.85 1.01 1.08

analysis technique that uses Q -methodology theory to analyze correlation measure (Brown, 1980).

PRELIMINARY RESULTS Prior to conducting Q-sort analysis, ranked scores of all participants (before identifying factor groups) on each statement variable have been calculated for preliminary descriptive statistics. These are shown in Table 1. (Mean Score normalized as: 5= Most important , 1= Least important) Next, a Q-Sort analysis will be conducted (research is in progress). The goal is to look a correlation between variables, correlation between factor groups, and identification of factor groups by rotation to extract similar patterns of response, the statement variables in each factor group which are statistically significant, and a comparison between factor groups to identify consensus or disagreement of statement variables.

DISCUSSIONS AND APPLICATIONS FOR PRACTICE In this study, Q-methodology will be used to define participant viewpoint and perceptions, empirically place participant in groups, provide sharper insight into participant preferred directions, identify criteria

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that are important to participants, explicitly outline areas of consensus and conflicts, and investigate a contemporary problem relating to educational web site usability by quantifying subjectivity. Results will be useful to web developers, administrators, and users in evaluating criteria that make an effective educational website. For further research, similar studies will be useful in other areas such as development and evaluation of e-commerce sites from a user perspective.

REFERENCES Bonk, C. & Dennen, V. (n.d). Frameworks for research, design, benchmarks, training, and pedagogy in web-based distance education. Retrieved January 05, 2006 from http://www.uab.edu/ it/instructional/technology/docs/frameworks.pdf Brown, S. R. (1980). Political subjectivity: Applications of Q methodology in political science. CT: Yale. Conner, M. (n.d.). Usability, user-centered design, & learnability. Retrieved Dec. 12, 2005, from Ageless Leaner Website: http:/ /agelesslearner.com/intros/usability.html Hazari, S. I. (2005). Strategy for assessment of online course discussions Journal of Information Systems Education, 15 (4), 349-355. Janicki, T & Liegle. J . (2001). Development and evaluation of a framework for creating web-based learning modules: a pedagogical and systems perspective. Journal of Asynchronous Learning Networks, 5(1), 58-84. Lu, M., & Yeung, W. (1998). A framework for effective commercial web application development. Internet Research, 8(2). Murray, T. (1996). From story boards to knowledge bases, the first step in making CAI ‘Intelligent’. In Proceedings, Carlson & Makedon (Eds.) Educational Multimedia and Hypermedia Conference. (pp.509-514). Charlottesville, VA: AACE. Palmer, J.W. (2002). Web site usability, design, and performance metrics. Information Systems Research, 13(2), p. 151-167. Thomas, D. & Watson, R. (2002). Q-sorting and MIS research: A primer. Communications of the AIS, 8, 141-156. Warlick, D. (2005). Building Web sites that work for your media center. Knowledge Quest, 33(3), 13-15.

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696 2006 IRMA International Conference

Building Career in Information Security Management Kuan-Chou Chen, Department of Information Systems, Purdue University of Calumet, Hammond, IN 46323, Tel: (219)989-2336, [email protected] Carin Chuang, Department of Computer & Information Technology, Purdue University North Central, Westville, IN 46391, Tel: (219)785-5723, [email protected]

ABSTRACT The issue of information security and the need to protect the company’s information systems, networks, and infrastructures could be more prevalent. Information systems security managers are responsible for ensuring that information systems assets are secure. The information security manager becomes a new administrative position within a company. In this paper, the need of information security management and the role and qualification of information security manager will be discussed. In general, the main goal of this paper is to stress the importance of information security management and how to get into this professional area through the education and discipline.

INTRODUCTION Nowadays, there are many different threats that cause much concern to information technology users, from viruses to unauthorized access of a database, and many more. Because of these threats, information security is an important field of study that offers skilled professionals an opportunity to make a more than adequate salary. In the paragraphs to come, we will discuss in a little more detail, the different information crimes that can take place, along with the importance of data integrity. Afterwards, we will discuss information security management as an occupation. In this section of the paper, we will begin by discussing the educational requirements of obtaining a degree in an information security field as well as the different certifications that are available and mandatory to work at certain companies. Afterwards, we will delve into the industry of Information Security, dealing with the growth of the industry, the value of information security as a whole, and the demand of information security managers and personnel. The last part of this section details information security management as an occupation; more specifically what types of jobs are available in this particular field of study, what requirements those jobs place on their information security managers and few of the benefits that come with having experience. In conclusion, we will summarize the main points and provide an overview of how the information security industry will fair in the near to distant future.

EDUCATION AND CERTIFICATION There are a wide variety of computer disciplines that one can study in order to work in the information security industry. This industry takes people from all backgrounds in the computer field. Whether your degree is in computer programming, web development, or networking, jobs look at more than just the degree you are holding. However, your degree must be in Computer Science or some related field. One of the main things that jobs look at has to do with the knowledge you have obtained in school and on the job. Knowledge of security issues are mandatory to work in this industry. Internet/Web security, networking and network security, and security audit techniques are some of the classes that one can take in college to further his or her understanding of the industry of information security.

Other computer classes that one can take that do not necessarily have to do with security deal with the developmental aspect of information systems. These the topics of these classes include C++, JAVA, database programming and administration, web-server management, and systems analysis and design methods. Keep in mind, that these are not the only courses one can take. There are a plethora of courses that can prepare you for the industry of information security. Along with the computer courses that are necessary for this occupation, one must be well able to manage a group of people in general and know how business works from a management point of view. A course in ecommerce is very helpful in this regard, along with other management courses. While companies view degrees as an important qualification to be considered for an opening, they also look at certain certifications. There are number of certifications that one can receive that make him or her even more marketable to organizations. Some of these certifications include the Global Information Assurance Certification (GIAC), Certified Information Security Professional (CISSP), and Casting Industry Suppliers Association (CISA). As you will see later on, while they are not always required, companies look for these certifications.

INFORMATION SECURITY AS AN OCCUPATION Companies require an assortment of different skills from their information security managers. In general, the skills that one must obtain to have such a title include, but are definitely not limited to, a variety of programming languages and a certain amount of professional knowledge dealing with information security, such as the knowledge of certain perimeter security applications and security audit tools and methodologies. In addition to the technological background, information security managers must also display practical management capabilities, such as strong analytical skills, excellent oral and written communication skills, and the ability to interact with personnel at all levels within the organization. In the few paragraphs that follow, three different job opportunities will be analyzed and compare to show some of the requirements and preferences that different companies have of their information security managers. Here is an analysis of another job opening in the information security management field from Lending Tree, which is an online loan marketplace. The title of this position is Information Security Engineer. Educationally this position also requires a Bachelor’s degree in Computer Science or related degree along with at least six years of experience. These six are broken down into three two-year segments with experience in each of the following: 1) perimeter security in large scale/high bandwidth networks with a preference on the financial services industry, 3) experience in system administration in a heterogeneous networked environment, and 3) development experience with an emphasis on creating interfaces to back end databases. Regardless of the degree, the

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Emerging Trends and Challenges in IT Management Table 1. Professional Knowledge Table for Lending Tree Networking

Development

System Administration

Internet Applications

Database

General

• • • • • • • • • • • • • • • • • • • • • • •

Knowledge of TCP/IP, CIDR, switched networking, sniffing, protocol analysis Experience in a high volume production environment Experience in large scale Internet and WAN connected networks Web Development User Interface Design Programming languages: C, C++, Java Scripting languages: PERL, Java, Bash, sed, awk Web: HTML, XML, PHP, ASP Debugging: gdb, lint GNU/ Linux (Gentoo) Solaris Microsoft (Windows/NT/2000/XP) PC / Server / Networking / RAID hardware maintenance RAID array configuration and management Web servers: Apache, IIS Proxies: Squid, Netscape DNS (multiple domain experience including split DNS experience) Miscellaneous: SSH, Mail, NTP Application / Database interface SQL, ODBC Data normalization Expert at root cause analysis Proficient in multiple medium report generation (real-time, adhoc, batch)

professional knowledge that this position requires is broken down into different subcategories that are stated and defined in the table 1. Along with the responsibilities of this job are the specific requirements that its applicants must have to even be considered to fill this position. First, as with any management position, the applicant must have great analytical and communication skills and he or she must be able to work well with other members of the IT department. Concerning the technical requirements, this person must have at least ten years of experience in computing and security, including experience with Internet technologies. The applicant must be proficient in “firewall, router, intrusion detection, compliance monitoring and switching technologies” (monster.com). The applicant must also have knowledge of the following: Firewall systems (Checkpoint FW1), remote access / virtual private networks, strong authentication software and procedures, security architectures, security audit procedures, web access control systems, mainframe architectures, Internet / Web services and communications security. Also, this position requires knowledge of mainframe architectures, database management systems (Oracle, DB2, etc.), client/server platforms (Sun Solaris, Intel / Windows, etc.), distributed message-based architectures (J2EE), storage architectures including SANS, word processing software and spreadsheets, project planning and management tools, and Internet security services (Iplanet, Websphere). The education required for this position includes a Bachelors degree in Computer Science or some related field of study. Various certifications are mentioned, however, this job does not necessarily require one to have them to be considered. These certifications include GIAC, CISSP, CISA, MCSE, and CCNP. In order to be considered for a position as an information security manager, much is required of the applicant. To summarize the jobs, a minimum of a Bachelors degree in some computer related field is a must. On top of that, the better, higher paying jobs require you to have at least eight to ten years of experience along with a very in-depth knowledge of quite a few topics regarding security. Not only is security an issue with these jobs, but also different platforms, development environments, and various kinds of architectures are just as important and necessary.

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CONCLUSION Security as a whole is by far one of the most important topics when you talk about information and the passing of data from one place to another. Whether it is computerized or otherwise, safeguarding the information is one very important key to effective communication and business transactions. You have just read about some of the various actions and crimes that can threaten any type of information system. A few examples of these would be virus and worms, hackers and crackers, and back doors and Trojan horses. Each threat presents a somewhat unique way of viewing information security. Along with the different crimes that are present to an information system, there are also certain natural occurrences that can have a detrimental effect on an information system’s ability to safeguard data. An example of this would be echoes, or noise, on a communication line if one decides to pass information along a network. This is an innocent occurrence that can either cause your data to be received with things added onto the messages or cause your messages to not be received at all. Either way, businesses suffer when unadulterated information is not relayed in a timely fashion, thus creating information security as an occupation. Since we have currently entered the Information Age, the exchanging of different types of information is vital for most businesses to stay alive. Also, since these businesses rely on sending and receiving unadulterated information in a timely fashion, there will always be a need for an information security specialist. So, to wrap up my analysis concerning the future of information security as an occupation, it looks very bright. Much is required of this field, but with dedication and hard work, one can easily have a very rewarding and lucrative career as an information security manager.

REFERENCES 1. 2.

3.

4. 5. 6. 7. 8. 9. 10.

11. 12. 13. 14.

Campbell, P., Calvert, B. and Bosewell, S. (2003). Network security fundamental. Boston: Course Technology. Carlson, Tom. (2001). Information Security Management: Understanding ISO 17799. White paper, Lucent Technologies Worldwide Services. Clarke, R. (1998). Message Transmission Security (or ‘Cryptography in Plain Text’). Retrieved April 02, 2002, from the Australian National University, Engineering and Information Technology site: http://www.anu.edu.au/people/Roger.Clarke/ II/CryptoSecy.html Davis, P. & Lewis, B. (1996). Computer security for dummies. Foster city: IDG Books. Hall, James A. (2002) .Information Systems Auditing and Assurance. South-Western College Publishing. Larson, E. and Stephens, B. (2000). Web servers, security, & maintenance. Upper Saddel River: Prentice Hall PTR. Leinwand, A. and Conroy, K. F. (1996). Network management: A practical perspective. Reading: Addison-Wesley. Maiwald, Eric (2001). Network security: a beginner’s guide. New York: Osborne. Mackey, D. (2003). Web security for network and system administrators. Boston: Course Technology. National Science Foundation Report. (2002). Protecting information: The role of community college in cybersecurity education. Washington, D.C. Protocols.com. (2002) Retrieved April 05, 2002 from http:// www.protocols.com/ Schneider, Gary P. & Perry, James T. (2001). Electronic Commerce (2nd ed). Canada: Course Technology. SecurityWatch.com. (2002). Retrieved April 7, 2002 from http://www.securitywatch.com/ Stein, L. (1998). Web security: A step-by-step reference guide. Boston: Addison-Wesley.

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698 2006 IRMA International Conference

Pathways to Producing Digital Portfolios Eleanor J. Flanigan, Ed.D., Management & Information Systems, Montclair State University, 1 Normal Avenue-PA-347, Upper Montclair, NJ 07043, Phone: 973-822-9231, [email protected], Fax: 973-822-0345 Susan Amirian, Ed.D., Media Communications & Technology, E. Stroudsburg University, School of Professional Studies, E. Stroudsburg, PA 18301, 570-424-1588

BACKGROUND Within the past decade the concept of portfolio development in the arts has expanded into other academic and professional areas. The original design of a portfolio as carried over from artists or graphic design professionals was traditionally on paper or cardboard as well as exhibited through photographs or pieces of sculpture. A contemporary approach is to assemble these artifacts and preserve their images by digital technology. The use of portfolios as a method of preservation of special work and as a method of presentation of technical skill is helpful for many groups, including instructors, students, and those beyond the classroom environment. Portfolios serve as tracks or pathways showing initial work and then progressing along with the creator’s development of a tangible product showing advancement in the learning process. This ongoing process has taken hold in education with teachers aware that helping students to build the skills necessary to create digital portfolios should be the start of lifelong professional development tool (Barrett, 2005). Not only do students strengthen their self-reflection but they also learn or hone technical skills needed to create the portfolio

INSTRUCTIONAL USE OF DIGITAL PORTFOLIOS Designing portfolios using technology has been introduced in classrooms for both professional and instructional purposes. Teacher education has responded to national accreditation criteria for methods of assessment for aspiring teachers. Many school districts continue with this technique, requiring the staff to exhibit concrete evidence of their own development within the classroom. Teachers, having perfected their own skills in developing their professional portfolios, pass on concepts of portfolio creation to their students. Thus there is a ripple effect through all academic levels. Students on all levels use components for portfolios which different names, depending on the goals the creator has for the final product. Some developers call their portfolios digital story-telling. Some use the final portfolio as a way of learning how to use technology to digitize their precious materials. Others use portfolios for professional career building or for employment interviews. Some use portfolios to summarize and preserve snapshots of course projects. What these portfolios are called may differ and why they are created varies from case to case. Basically the contents can be whatever the creator wishes to preserve. The type of storage and distribution is also one of the differences between traditional or paper-based portfolios and digital portfolios. Archiving artifacts with production of a CD or DVD or storage on a Web site is basically the final distribution choice for digital portfolios. Content and sophistication of the final product depends on its purpose as well as the expertise and/or creativity of the designer. Artifacts can be more diverse with digital portfolios than with paper portfolios since digital technology can include multimedia as well as text. Digitizing artifacts also allows for creative connections as artifacts can hyperlink and provide broader branching. Recently collegiate business schools have begun to recognize and develop programs for portfolio creation. These schools as well as university teacher education programs and local school districts are sometimes driven by the need for accreditation. Curriculum assessment

by clients of the program is a key ingredient for original accreditation and ongoing validation. Business schools in particular use portfolios as a measure of assessment along with using students’ projects to support their claims of relevancy. In turn, the students use these projects to enhance their fledgling resumes.

WHY CREATE PORTFOLIOS? Copious data are available to support why portfolios should be developed and to show the importance of the final product. Defining a purpose for the portfolio is the first step in development. The “why” must precede the “how” particularly for students who are unaccustomed to analyzing what steps they have already taken on the academic road to success. Students usually follow prescribed courses of study, depending on their mentors to move them ahead on a knowledge continuum. Portfolio creation requires self-reflection, a good reason in itself for portfolio creation. There are several basic types or categories into which portfolios are placed: to support ongoing learning or professional development, to support assessment by either students or administrators, or to support marketing and employment. By developing portfolios for assessment of learning, students are engaged in connecting their academic dots. According to Davies (2000), this requires “deep involvement on the part of the learner in clarifying outcomes, monitoring ongoing learning, collecting evidence, and presenting evidence of learning to others.” The term “evidence” is synonymous with the artifacts students collect to populate their portfolios along with representing their reasoning in choosing one artifact over another. Barrett (2003) encourages students to recognize why this evidence or artifact “constitutes … achieving specific goals, outcomes, or standards.”

PROCESS OF CREATING PORTFOLIOS Digital portfolios were implemented in the courses of the two authors at two state universities: Montclair State University in New Jersey and East Stroudsburg University in Pennsylvania. The courses in which portfolios were created were in the department of Management and Information Systems in the School of Business and the department of Media Communication & Technology in the School of Professional Studies. The authors collaborated on portfolio creation strategies, sharing ideas on classroom methods and processes. Their collaboration also resulted in a full text/workbook not only describing the portfolio creation process but actually giving step-by-step directions on how to work through each area of portfolio creation. (Amirian and Flanigan, 2006) One type of portfolio mentioned above was one supporting ongoing learning or professional development. This type, a course portfolio, was developed by graduate students for a course on imaging technology. The other portfolio, a career portfolio, was developed by business students to support marketing themselves and gaining employment. In each course students created digital portfolios as an integral part of their learning experience in addition to contributing to their preparation for internships, cooperative work experience, or job searches. Students

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Emerging Trends and Challenges in IT Management in the graduate course created course portfolios as part of learning design, collecting an artifact of each assignment to display in their course portfolio. Students were required to include a short reflective text with each assignment. The business students created career portfolios as ancillary projects to strengthen job searches and interviews with prospective employers. They were required to keep a journal of their progress and submit this weekly along with the portfolio segment assigned. These types of activities aided both teacher and student assessment of course work. The following are the steps taken in both courses, depending on the purpose and design of the portfolios. 1.

2.

3.

4.

5.

6.

7.

Introducing portfolios and the development process: Students were introduced to the reasons why portfolios would benefit them both professionally and personally. They were given general procedures and calendars as procedural guides with benchmark dates. Samples of past student portfolios were shown to provide inspiration as well as to allow discussion and questions. Brainstorming and Discussion: Students developed the concept of their portfolio designs and presented them in teams to the other students. This served as a valuable step as students quizzed each other and helped to clarify their thoughts. Designing the Theme: These concepts included defining the visual metaphor the portfolio would follow graphically and describing the structure of the portfolio. For example, some students chose to use the metaphor of steps for their theme with each step representing an artifact. Another theme was a file cabinet with open drawers and file folders. Visualizing a graphic metaphor aided students in creating the organization, storyboard, behavior, look, and graphic feel of their portfolio pages. Navigating the Portfolio: Linear portfolios would be viewed in a sequential way, one page at a time. The book metaphor, for example, would have a cover, table of contents, chapters, and page numbers. Portfolios using a Web structure could be viewed in any order the user chose, having the navigational ability to jump from one content area to another. Designing Pages: Students created pages in the software of their choice, such as Microsoft PowerPoint, Adobe Photoshop, or Microsoft Word. These pages were used to hold the text, video, images, and links to documents that comprised their portfolio content. Special attention was given to using color creatively, particularly by using sharply contrasting colors. Students were aided by using the commercially available templates in PowerPoint for examples of color contrast. These pages also contained intuitive navigation, such as hyperlinks. Students learned the benefits of using symbols as well as text for their hyperlink navigation. Teammates and instructors provided constant monitoring to ensure that the portfolios had a professional appearance. Since the portfolios were designed as primary digital documents to be viewed on the computer, screen design, resolution, and legibility issues were introduced. Web-safe colors and system fonts were selected as universal design elements for consistent viewing across platforms. Selecting Artifacts: Students chose documents, projects, and video that they felt represented their best works and abilities as artifacts for the portfolios. The artifacts were then digitized and stored. Paper artifacts were digitized by scanning, and all digital files were optimized so that two files for each artifact were saved. Optimization included sizing and using image compression to create files that would view efficiently on screen in the portfolio presentation. The instructor reviewed students’ selections periodically, and students were guided in their selection or creation of effective artifacts. Storage of Artifacts: Students stored their digitized artifacts on their own computers and portable flash memory sticks as well as on university servers. Some professional software and servers

8.

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are available as described in the next section on portfolio creation. Distribution: When completed, students created a final CD or DVD for distribution. Students designed CD labels, jewel case inserts, and collateral paper pieces. Commercial software, such as Roxio, contains features to allow file transfer and label creation and case inserts.

PORTFOLIO CREATION WITH CORPORATE AND ACADEMIC COLLABORATION Several programs demonstrate how diverse groups with a single focus are supporting portfolio development. These programs are collaborative, not limited to one population or one academic focus. Some of the solutions involve specific software vendors and dedicated course management systems. Some enjoy the benefits of working with off-campus servers hosted by the vendors while others are campus-based. The following is a short listing of some of these programs: Epsilen Portfolio Management System by Indiana University Purdue University Indianapolis (UPUI) CyberLab: A comprehensive electronic portfolio management system, offering a Web environment for students, faculty, alumni, and professionals wishing to build personal portfolios. Provides free membership throughout 2006 for students, faculty, or staff within a post secondary educational institution. Provides a personal lifelong cyber identity allowing ePortfolios and social networking, academic collaboration, and a course management system. •

•

• •

•

Nuventive: TracDat supports assessment documentation and iWebfolio supports electronic portfolios. Is used by Western Michigan University Center of Excellence for Portfolios and Assessment. Chalk & Wire: Provides access to creation of ePortfolios with RubricMarker hosted on their server. Templates are provided for easy portfolio creation. FolioLive by McGraw-Hill: Online portfolio tool for students to create an electronic portfolio. Hosted on company server. BlackBoard: Added an ePortfolio feature to its Content Management System, allowing students to use professionally designed templates to store artifacts. Taskstream: Provides several tools for collaboration and portfolio management, particularly useful for teacher education. Assessment is through their Web Folio and Web Page Builders. Rubric wizards and other instructional design tools are available.

REFERENCES Amirian, S. and Flanigan, E. (2006) Creating Your Digital Portfolio. Indianapolis, IN: JIST Publishing Company. Barrett, H. (2003) Presentation at First International Conference on the e-Portfolio, Poiters, France, October 9, 2003. [Retrieved January 8, 2006 from http://electronicportfolios.org/portfolios/eifel.pdf] Barrett, H. (2005) Researching Electronic Portfolios and Learner Engagement. [Retrieved January 6, 2006 from http:// www.taskstream.com/reflect/whitepaper.pdf] Davies, A. (2000) Making Classroom Assessment Work. Merville, BC: Connections Publishing. RESOURCES BlackBoard ePortfolios: http://www.blackboard.com/products/as/ contentsys/ Epsilen: http://www.epsilen.com McGraw-Hill FolioLive: http://www.foliolive.com Nuventive: iWebfolio and TracDat software http://www.nuventive.com/ Taskstream: http://www.taskstream.com/pub/default.asp

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700 2006 IRMA International Conference

Cultural Issues in Information Systems Research: A Review of Current Literature and Directions for Future Research (Research-in-Progress) Subhasish Dasgupta & Li Xiao Information Systems & Technology Management Dept, The George Washington University, {dasgupta, lilyxiao}@gwu.edu

INTRODUCTION Cultural factors influence information systems in a variety of ways. At the national level, for example, culture influences IS management practices in different countries (Harris and Davison 1999; Ford, Connelly and Meister 2003). At the organizational level, several studies propose that organizational culture directly relates to success of IT implementation (Zammuto and O’Connor 1992; Fedrick 2001; Harper and Utley 2001; Doherty and Doig 2003; Harrington and Guimaraes 2005). Despite the potential importance of culture in IS field, very little discussion has been conducted on the topic. Culture has been studied on a limited number of occasions in IS literature, yet there has been no effort to comprehensively evaluate current state of culture research. The purpose of this meta-analytic study is to explore and critically evaluate research on cultural issues in information systems field. Based on the evaluation, we will synthesize research findings of existing literature and present areas for further research. In short, the purpose of this study is to initiate a discussion of culture within the conversation of information systems research. In this article, we provide an overview of the topic field, discuss about the need for a metaanalysis on the area, and report on the current status of this research. Defining Culture Culture is commonly regarded as difficult to define (Davison and Martinsons 2003). Different authors use a variety of categories to describe culture, such as observed behavioral regularities, group norms, values, philosophy, climate, shared meanings, formal rituals and celebrations (Schein 2004). Although a precise definition for culture is always controversial, most scholars commonly agree on a few general principles: 1. Culture is shared among a group of people; 2. Culture is defined by a pattern of values, beliefs, and behaviors; 3. Culture is socially acquired through the group’s development over a period of time (Davison and Martinsons 2003; Schein 2004). In this article, we define culture as “a pattern of shared basic assumptions that was learned by a group as it solved its problems of external adaptation and internal integration, that has worked well enough to be considered valid and, therefore, to be taught to new members as the correct way to perceive, think, and feel in relation to those problems” (Schein 2004).

As culture is drawing increasing attention from IS researchers and more studies are conducted on the topic, it is valuable to pause and reflect on the state of the research area. The benefits of undertaking such a study are numerous. First, we will be able to synthesize research findings from a number of studies that have looked at culture and information systems. Second, we will be able to evaluate whether certain research findings are consistent across studies, and identify the areas where additional research is necessary.

PRELIMINARY ANALYSIS A preliminary analysis showed that research in the area of culture and information systems can be divided into two types: research on organizational culture, and research on national culture. These two categories of research are based on the units of analysis used in the evaluation of culture: organizational or national. Research that considered national culture can again be divided into studies that considered cultural issues related to one nation or country and those that compared information systems in cross-cultural settings. Our initial work in the area has identified studies that either investigate the effect of culture on information systems or vice versa. Culture in these studies is considered to be the independent or dependent variable. There are other studies that control for culture or compare a phenomenon across nations; these studies are primarily cross-cultural in nature. We report on some preliminary observations in the present status

CURRENT PROGRESS AND PRELIMINARY RESULTS We have collected literature on the topic area and we are in the process of reviewing the literature and developing our research model. Here are some preliminary observations from the qualitative classification phase of this study:

Figure 1. Number of academic publications on culture and information systems Number of Academic Publications on Culture and Information Systems

OVERVIEW OF THE AREA AND NEED FOR A METAANALYTIC STUDY Number of Articles

In recent years the issue of culture is drawing more and more attention from IS researchers. A search of keywords “culture” and “information systems” for peer-reviewed publications in ABI/INFORM database resulted in 194 peer-reviewed articles1. The development of research is very promising in that more studies are being carried out on the topic area. As indicated in figure 1, the number of academic publications has been on the increase over the past years.

92

100 80

66

60 40 20

27 9

0 -1990

1991-1995

1996-2000

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2001-2005

Emerging Trends and Challenges in IT Management •

•

•

Most studies admit that culture is an important factor in the implementation of information systems, at both national level and organizational level. Some studies conclude that culture will affect information systems implementation and information systems, in turn, will change culture and behavior. Measurement of culture is controversial. Different scholars hold divergent opinions on whether culture can be measured and how to measurement culture.

REFERENCES Davison, R. and Martinsons, M. G. (2003). “Guest editorial cultural issues and it management: past and present.” IEEE Transactions on Engineering Management 50(1): 3-7. Doherty, N. F. and Doig, G. (2003). “An analysis of the anticipated cultural impacts of the implementation of data warehouses.” IEEE Transactions on Engineering Management 50(1): 78. Fedrick, M. A. C. (2001). The relationship between organizational culture and the processes for implementing technology at selected private liberal arts colleges, The Pennsylvania State University. Ford, D. P., Connelly, C. E. and Meister, D. B. (2003). “Information systems research and Hofstede’s culture’s consequences: an

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uneasy and incomplete partnership.” IEEE Transactions on Engineering Management 50(1): 8-25. Harper, G. R. and Utley, D. R. (2001). “Organizational culture and successful information technology implementation.” Engineering Management Journal 13(2): 11. Harrington, S. J. and Guimaraes, T. (2005). “Corporate culture, absorptive capacity and IT success.” Information and Organization 15: 39-63. Harris, R. and Davison, R. (1999). “Anxiety and involvement: Cultural dimensions of attitudes toward computers in developing societies.” Journal of Global Information Management 7(1): 26. Schein, E. H. (2004). Organizational culture and leadership, San Francisco: Jossey-Bass. Zammuto, R. F. and O’Connor, E. J. (1992). “Gaining Advanced Manufacturing Technologies’ Benefits: The Roles of Organization Design and Culture.” Academy of Management. The Academy of Management Review 17(4): 701-728.

ENDNOTE 1

Search conducted on October 1, 2005.

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702 2006 IRMA International Conference

Measuring the Business Value of IT: A Resource-Based View of Leading Indicators Penelope Sue Greenberg, Department of Penelope Sue Greenberg, Department of MIS/DS, School of Business Administration, Widener University, Chester, PA 19013, Tel: (610) 499-4475, Fax: (610) 499-4614, [email protected] Ralph H. Greenberg, Department of Accounting, Fox School of Business & Management, Temple University, Philadelphia, PA 19122, Tel: (215) 204-6830, Fax: (215) 204-5587, [email protected] Kevin E. Dow, Department of Accounting, College of Business Administration, Kent State University, Kent, Ohio 44242, Tel: (330) 672-1109, Fax: (330) 672-2548, [email protected] Jeffrey Wong, Department of Accounting, College of Business, Oregon State University, Corvallis, Oregon 97331, Tel: (541) 737-4890, Fax: (541) 737-6044, [email protected]

ABSTRACT The business value of IT is a topic of importance to both IT and business sides of the organization. However, despite the growing body of research on assessing the value of IT, there are still issues and debates concerning the appropriate approach. Most of the research has focused on ex post measurements, which are dependent on factors that influence the measurements in innumerable identified and unidentified ways. This paper contributes to this literature by proposing a set of metrics that focus on leading indicators of value as opposed to ex post measurements. To develop these leading indicators, we use the resource-based theory of the firm and resource dependency theory to adapt and extend two previously identified sets of metrics. The first is the balanced scorecard, which is widely used by business managers to align internal performance measures with strategic goals. The second is DeLone and McLean’s measures of IS success. The extension focuses on two additional areas. The first is measuring system and business flexibility, which critical in today’s fast-changing environment. The second addresses inter-organization and network IT measurement issues.

OVERVIEW

Klein 2004). The value of IT can be seriously underestimated if complementarities between IT infrastructure and e-commerce capabilities are ignored (Zhu 2004). The objective of this research is to develop a more comprehensive set of measures that address the problems identified above. To accomplish this, we build upon two widely-accepted sets of measurement variables, one from systems, DeLone and McLean’s (1992) six-factor taxonomy of IS success (system quality, information quality, IS use, user satisfactions, individual impact and organization impact) and one from business, Kaplan and Norton’s (2001, 2004) balanced scorecard (efficiency of the internal business process, quality to the customer, and financial, and continuous improvement measures). But what is missing from these is the measurement and evaluation of flexibility. Flexibility is necessary because of the hyper-competitive nature of e-commerce and the short life cycles of products and services, which require firms to adapt their products and services rapidly. Also missing from these sets of variables is any measurement of valuechain or network level performance metrics. Straub, Rai and Klein (2004) indicate that “There is a pressing need to move forward with measuring performance at a networked organizational level, …” (p. 85).

The business value of IT is a topic of importance to both IT and business sides of the organization, as evidenced by the number of professional seminars, workshops and conferences offered by professional organizations and consulting companies, the recent research interest by economics, organizational behavior and IT scholars, and the number of articles published in both academic and professional journals. While various conceptualizations of IT and the appropriate related metrics exist, recent literature reviews (Melville, Kraemer and Gurbaxani 2004; Kohli and Devaraj 2003) indicate that IT value research has focused on efficiency (productivity) and effectiveness (profitability) measures. The measurements are usually taken ex post to test hypothesized models of the IT value. Here, we propose that for both investment and evaluation purposes, leading indicators would be useful additions to the previously identified set of metrics.

To accomplish the development of a more comprehensive set of measures, we will rely on the resource-based theory of the firm (Penrose 1959, Wernerfelt 1984) and resource-dependency (Scott 1987). The resource-based view of the firm emphasizes heterogeneous resource endowments as the basis for competitive advantage to the firm. The conditions necessary for a sustainable competitive advantage are value, rareness, inimitability, and non-substitutability (Barney 1991).

In addition, much of the IT value research has been at the firm level. On one hand, this approach uses aggregate measures which limit the ability to differentiate among types of IT investments and outcomes (Kumar 2004). On the other hand, this approach ignores the value chain relationships pervasive in the networked economy (Straub, Rai and

Ambrosio, Johanna. 2001. What to count? Computerworld: ROI Framingham: Jul/Aug Vol. 1, Iss. 3, p. 16-22. Barney, J. B. 1991. Firm Resources and Sustained Competitive Advantage. Journal of Management Vol. 17, Issue 1 pp. 99-120.

Resource-dependency theory argues that organizations must engage in exchanges with their environment to obtain resources. This need creates dependencies that need to be addressed in developing network and value chain performance measures.

REFERENCES

Copyright © 2006, Idea Group Inc. Copying or distributing in print or electronic forms without written permission of Idea Group Inc. is prohibited.

Emerging Trends and Challenges in IT Management Barringer, Bruce R., and Jeffrey S. Harrison. 2000. Walking a Tightrope” Creating Value through Interorganizational Relationships. Journal of Management. Vol. 26 Issue 3, pp. 367-403. DeLone, W. H., and E. R. McLean. 1992. Information Systems Success: The Quest for the Dependent Variable. Information Systems Research Vol 3. Issue 1, pp. 60-95. Kaplan, Robert S., and David P. Norton. 2004. Strategy Maps: Converting Intangible Assets into Tangible Outcomes. Harvard Business Publishing Corporation. Boston, MA. Kaplan, Robert S., and David P. Norton. 2001. The Strategy-focused Organization: How Balanced Scorecard Companies Thrive in the New Business Environment. Harvard Business Publishing Corporation. Boston, MA. Kohli, Rajiv, and Sarv Devaraj. 2003. Measuring Information Technology Payoff: A Meta-Analysis of Structural Variables In FirmLevel Empirical Research. Information Systems Research Linthicum: June Vol. 14, Iss. 2, p. 127. Kumar, Ram L. 2004. A Framework for Assessing the Business Value of Information Technology Infrastructures Journal of Management Information Systems Armonk:Fall 2004. Vol. 21, Iss. 2, p. 11-32 Melville, Nigel, Kenneth Kraemer and Vijay Gurbaxani. 2004. Review: Information Technology And Organizational Performance: An Integrative Model Of It Business Value. MIS Quarterly Minneapolis:June Vol. 28, Iss. 2, p. 283-322.

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Penrose, E. 1959. The Theory of the Growth of the Firm. London: Basil Blackwell. Rai, Arun, Sandra S. Lang, and Robert B. Welker. 2002. Assessing the Validity of IS Success Models: An Empirical Test and Theoretical Analysis. Information System Research Vol. 13, Issue 1, pp. 5069. Scott, E., 1987. Organizations. Englewood cliffs, NJ: Simon and Schuster. Straub, Detmar, Arun Rai, and Richard Klein. 2004. Measuring Firm Performance at the Network Level: A Nomology of the Business Impact of Digital Supply Networks Journal of Management Information Systems Armonk: Summer Vol. 21, Iss. 1, p. 83-114. Wade, and Hulland, 2004. Management Information Systems Quarterly Vol. Wernerfelt, B. 1984. A Resource-Based View of the Firm. Strategic Management Journal Vol. 5 Issue 2, pp. 171-180. Zhu, Kevin, and Kenneth L Kraemer. 2005. Post-Adoption Variations in Usage and Value of E-Business by Organizations: CrossCountry Evidence from the Retail Industry. Information Systems Research Linthicum: March Vol. 16, Iss. 1, p. 61-84. Zhu, Kevin. 2004. The Complementarity of Information Technology Infrastructure and E-Commerce Capability: A Resource-Based Assessment of Their Business Value. Journal of Management Information Systems Armonk:Summer 2004. Vol. 21, Iss. 1, p. 167-202.

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704 2006 IRMA International Conference

Leadership and Organizational Citizenship Behavior in E-Collaborative Teams Richard R. Reilly, Karen Sobel Lojeski, & Michael R. Ryan Stevens Institute of Technology, Hoboken, NJ 07030, T: (201)216-5383, [email protected]

INTRODUCTION The rapid evolution of networked organizations has led to a rise in global and virtual teams. An organization’s success is highly dependent on the use of such teams in projects focused on new product development, application software development, supply chain integration, and many other activities. Further, globalizing the innovation process using virtual resources has become an important way to access diverse sets of knowledge and has become an imperative for companies seeking to succeed in a global market (Santos, Doz & Williamson, 2004). Advances in communication technology have reshaped the manner and frequency of daily interactions between coworkers and customers. Telephones, videoconferencing, e-mail, and groupware have made it possible for people to collaborate without meeting face-to face (FTF) (Zaccaro & Bader, 2002). Research on virtual teams has identified three basic characteristics: members are geographically and/or organizationally dispersed, collaboration and communication occur through the use of information technologies, and interactions are more likely to be temporally displaced or asynchronous (e.g. Townsend, deMarie, & Hendrickson, 1998; Zigurs, 2002). Much of the literature assumes that teams are either virtual or FTF. Although some (e.g., Arnison, 2002), contend that it is virtually impossible to distinguish a virtual team from a traditional team due to the pervasive nature of technology and communications. We have taken an expanded perspective in our research. First, “virtualness” is not necessarily a dichotomous phenomenon (Pauleen, 2003). Most teams today, whether global, virtual or co-located, can be described by a mix of virtual and FTF interactions. The key characteristics used to define a “virtual team” are best thought of as contributing to a continuum (Zigurs, 2002, Griffith, Sawyer & Neale, 2003) of virtualness. For example, many co-located teams use e-mail or webbased collaboration or design tools. Second, the commonly cited characteristics of virtual teams are not the only factors influencing the attitudes, behavior, and innovativeness of team members. For example, global virtual teams engaged in new product development and other innovative activities are challenged by a number of different issues including building trust and motivating one another, cultural diversity and lack of goal clarity (Barczak & McDonough, 2003). Collaboration, whether FTF or computer mediated, occurs within a much broader context or climate, which includes interpersonal, social, organizational and technical factors, all of which have important implications for the attitudes and behavior of team members and their ability to succeed and innovate (O’Leary & Cummings, 2005). To be effective, leaders must promote a climate that supports innovation and business success (Harborne, 2003). This can only be accomplished when managers understand the issues that virtual team members face in the globalized workplace. Although there are clearly new sets of issues that present themselves to the 21st century networked workforce, the virtual team research to date has reported relatively few outcome differences between virtual teams and FTF teams (Powell, Piccoli and Blake, 2004). In most cases, these studies have treated virtualness as a dichotomous phenomenon, with FTF or “traditional” teams as a control group or comparator (e.g. Arnison, 2003; Aubert & Kelsey,

2003). Moreover, they have looked at the defining constructs of temporal, technological and geographic displacement in isolation from other potentially important variables (e.g. Montoya-Weiss, Massey & Song, 2001; Jarvenpaa & Leidner, 1998). We sought to examine the role of leadership in e-collaborative teams that differed in their “virtualness”. In previous research (Reilly, Sobel Lojeski, Dominick, 2005) we operationalized a broad set of variables that might more fully explain behavior, success, and innovation in workplace teams. We drew from both the recent virtual team research, which stresses computer-mediated interaction along with temporal and geographic displacement as well as more general concepts related to group dynamics and social interaction. We tried to understand how these variables, considered together, impacted trust, goal clarity and organizational citizenship behavior (OCB); all of which should be predictors of project success and innovation performance. Most global virtual team research considers geographic distance as a fundamental characteristic. But distance can also be used to describe the emotional or psychological gap between team members who work in the same building and regularly meet FTF. For a team working primarily in virtual space the socio-emotional “distance” may be a function of other factors, in addition to the obvious ones of geography and computer mediation. Our work will address two relatively unexplored issues in virtual team research: organizational citizenship behavior and leadership. Specifically, we sought to better understand the extent to which OCB occurs as teams become more virtual and how leadership influences OCB under differing conditions of virtual distance. We hypothesized that virtual distance would have a negative influence on OCB and that leadership would have a positive relationship to OCB. We also hypothesized that the influence of leadership on OCB would be stronger on collaborative teams with lower virtual distance.

METHOD Procedure All respondents completed a web-based questionnaire describing their organization, current position and their experiences with a recently completed project. Scales measuring each of the hypothesized distance components were included in the questionnaire as were scales assessing OCB and leadership. Sample The sample included data from 147 respondents. We had additional data from over 100 respondents that did not contain the leadership scale and consequently these cases could not be included. Most of the respondents worked in technology-related fields in a variety of organizations with headquarters in the Northeastern corridor and held positions ranging from Vice-president to programmer. Seventeen different organizations were represented and included financial services, manufacturing, healthcare, government, software, and outsourcing industries. The largest functional areas included Information Technology (33%) and

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Emerging Trends and Challenges in IT Management Table 1. Means, Standard Deviations and Intercorrelations Variable

Mean

SD

VDM Index

0.00

0.53

Leadership

3.69

0.68

OCB

3.50

0.48

VDM Index Leadership (.89)

OCB

-.34**

-.49**

(.87)

.49** (.82)

Notes: all coefficients were significant at p

98589025 intc market buy 1000



Listing 2:

STA SOAP response for a stock trade



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Listing 4:

STA SOAP response for position indicator

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Vulnerabilities Check



VRFs agents is to provide a more secured computing environment for parties involved in web services transaction. These agents act as a trust conveyer by performing benchmarking tests on services end-points.

VRF-AGENT DESIGN REQUIREMENTS GUIDELINES In order for the web services to be functional and operational; design requirements call for management simplicity of the services. We obtain simplicity by securing hybrid specifications within the service. For assurances purposes, Vulnerabilities-agents must exchange a security token to a vulnerabilities coordination server and request a current list of vulnerabilities definitions. This token is considered to be a hash function value which may be computed based on pre-defined attributes of the requesters computing environment variables, based on this value; the server will pass strictly the vulnerabilities definitions that are of interest to the requesting agent. These variables may be architecture specifications, API specifications, Operating system footprint, ..etc. This methodology will narrow down the list of vulnerabilities of interest resulting reduction of computing resources overheads as only vulnerabilities that effects the environment computing variables (Environment Profile) will be scanned and analyzed.

CONCLUSION AND CURRENT/FUTURE WORK In order to maximize vulnerability assessment capabilities, integration of a VRF module is a must in any deployments of Web Services. This module may addresses most known possible vulnerabilities in web servers for the purpose of problems abstraction and as a compliance auditing tool of computing environments. The proposal is considered to be a new approach in software engineering where integration, collaboration, and correlation are its semantics. Future work is directed towards addressing possible architectures of implementations methods of retrieval, and environment variables computing. Most of related work is based on methods of scanning and none are directed towards an integration approach for all SOAP-based Web Services.

REFERENCES [1] [2] [3] [4] [5] [6]

The World Wide Web Consortium, Web Service Architecture, http://www.w3.org/TR/ws-arch/ US-Computer Emergency Readiness Team (US-CERT)’s database; http://search.us-cert.gov/ [7] Common Vulnerabilities and Exposures (CVE) http:// www.cve.mitre.org/cve/ Distributed Info. Systems, Errol Simon, McGraw-Hills National Infrastructure Advisory Council, http://www.dhs.gov/ Vulnerability Disclosure Framework, http://www.dhs.gov/ interweb/assetlibrary/vdwgreport.pdf

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968 2006 IRMA International Conference

Web Ontology as E-Business Information Exchange and Decision Support Tool Yefim Kats, Computer Science Dept, Southwestern Oklahoma State University, 100 Campus Dr, Weatherford, OK 73096, [email protected] James Geller & Kuo-chuan Huang Computer Science Dept, New Jersey Institute of Technology, University Heights, Newark, NJ 07002, {geller, kh8}@njit.edu

ABSTRACT This paper is based on the ongoing research grant from the National Research Council and partly funded by the National Science Foundation. This study is also linked to our foreign partner’s project for the Ukrainian Government - Development of Knowledge Base Architecture and Knowledge Discovery Methods for Intelligent Information Systems in Economics. The study can serve as a practical testing ground for the development of generic as well as domain specific business oriented Web based knowledge resources, using ontology languages such as OWL. The overall objectives of the study include development of the standard consensual terminology, conceptual framework, and the required mappings for a cluster of business-oriented ontologies to facilitate information exchange and e-commerce transactions between Ukraine and USA.

INTRODUCTION Ontologies are often defined as conceptualizations that “provide a shared and common understanding of a domain that can be communicated between people and heterogeneous and widely spread application systems” (Fensel, 2003). Thus, by definition, the study of ontologies requires cooperation between the parties belonging to the different social, economic, and linguistic environments. The use of Web Ontologies as well as ontology languages such as OWL should contribute to our ability to improve both the data exchange and the decision-making processes (including, crucial for certain businesses, the ability to make decisions dynamically) involving users communicating in a multicultural environment. The Web Ontologies are being developed as an integral part of the Semantic Web project aimed at reshaping the Web into the complex semantic infrastructure. The essential elements of this infrastructure include: • • •

Web Ontologies explicitly representing the semantics of typical knowledge domains. Agent enabled new markup languages, capable to work with the Web Ontologies. Ontology enabled security and trust infrastructure.

cultural environments with possible semantic diversions within the class of related domains.

ONTOLOGY IMPLEMENTATION At the current phase of the project we developed a Multilingual Ontology Based E-commerce search engine implemented in JAVA and in the currently de facto standard ontology design language OWL. OWL is categorized into three sub-languages: OWL-Lite, OWL-DL and OWLFull. OWL-Lite is the syntactically simplest sub-language; OWL-DL is much more expressive than OWL-Lite and is based on Description Logics; OWL-Full is the most expressive OWL sub-language. OWL-DL is a better choice than OWL-Lite for our project because of its automated reasoning capability. As a convenient software tool to implement the bulk of the project, we chose Protégé (Protégé) – free software developed at Stanford University. It has useful plug-ins, such as the Protégé-OWL plug-in, which can save the Ontology in OWL format. Another useful tool is Racer (Racer) - a stand-alone semantic reasoning tool for RDF/OWL to be used to check for possible ontology inconsistencies. The sample graph below (fig. 1) represents the first design step in identifying typical E-commerce vocabulary: This graph is based largely on the XML Common Business Library version 4.0 modules and can be treated as a rudimentary E-R type model to be refined iteratively as the project progresses (XCBL). The iterative nature of this process is due to the fact that the overall structure, the entities with their attributes and the relationships between entities have to be adjusted to the diverse business practices in different countries (in our case – Ukraine and USA). Accordingly, as we continue to accumulate more vocabulary, we are forced to readjust the semantics of our model.

Fig. 1. E-Business terminology Structure

The overall objectives of this project are being implemented in several steps: •

• • •

Identifying the standard ontology vocabulary covering generic terms for the major e-commerce models involved in economic exchange. Identifying domain models, including classes, relations and attributes with the corresponding semantic constraints. Identifying specific ontological commitments for (intelligent) agent based automatic processing. Development of metrics to measure and assess the degree of similarity between related ontologies developed in different

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Emerging Trends and Challenges in IT Management Fig. 2. Flowchart for Web Search Interface

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input term is combined with an appropriate default string from the ‘central’ English language ontology. The final combined string – input term AND ‘ontology context string’ – is submitted to the Google API. The output consists of the translated input string as well as a list of relevant Web links. In case of the advanced search, the user will be presented with an ontology pop-up window offering him to place his input term into the context of the available (in his native input language) E-Commerce ontology. Then the input term and the ‘ontology context string’ will be translated into the chosen output language and submitted to Google. The following figure presents the Russian version of the ‘ontology choice window’ presented when the user chooses the advanced search option. In many cases, ontology based search in the E-commerce domain proved to be more efficient than the straightforward Google search. As an example, the string ‘international money order’ submitted to Google returns over 900 hits, while our search engine, still using Google, returns just over 100 hits.

CONCLUSION Essentially, the international nature of the project makes it difficult (or impossible) to apply any straightforward modeling technique. At this phase of project implementation we first created the ‘central’ English language ontology. The English terms were directly translated into several languages and, consequently, the three ontologies of ebusiness terms – in English, Russina, and German - have also been created as a first draft; the users may append those terms (in the correct language) to their own search terms. The conceptual problem with this approach is that all ontologies have the same semantic structure. However, this structure depends upon the business practice in a particular country. Thus, not only the vocabulary for each ontology needs to be refined and expanded, but also, as the project progresses, we may need to modify some (or all) of non-English ontologies.

INTERFACE DESIGN The functionality chart for the JAVA-based Multilingual, OntologyBased E-Commerce Browser is shown on figure 2 (M.O.R.E). The logic of search process is as follows. The search interface allows the user to input e-business terminology in his native language and to request the output in several languages such as Russian or German. If the user makes a ‘simple’ search choice, the input term is directly translated into the output language using the built-in ontologies. Then the translated

Our study showed that ontology based search provides a considerable enhancement to e-business. Sellers should be able to present information in their language of choice, while customers will be able to search for information in their language of choice. Thus, not only ontology based interface engine enhances search efficiency but it also brings to the next level international or/and multilingual seller-buyer interaction. The use of ontology driven menus can be also expanded to benefit online sellers. In particular, customers may be presented with ontology based pop-up windows to help them both navigate their current Web site and direct them to related sites in order to enhance their shopping experience. Finally, the goal of searching transparently in different languages would require a large amount of computing power, which is currently not practical. However, we are planning to include heuristics that connect a variety of languages with particular subject areas. Then the browser will be enabled to use such heuristics to locate the country and language most likely to result in a successful purchase. It will then, transparently to the user, search the Web pages of that country for pages that contain both the translated search terms and the e-commerce terms appended to them by choice of the user (and also translated transparently). Currently our implementation already makes use of the Google API, and considering that Google supplies an approximate translation capability, we can make use of it to further enhance our cross-country translation facilities.

REFERENCES Figure 3. Russian Ontology Pop-up Window

Spinning the Semantic Web (2003), ed. by D. Fensel et. al. Cambridge, MA: MIT Press. Protégé, available at: http://protege.stanford.edu Racer, available at: http://www.sts.tu-harburg.de/~r.f.moeller/racer M.O.R.E., available at: http://web.njit.edu/~kh8/ ecommerceOntology.jsp XCBL, available at: http://www.xcbl.org

SELECTED BIBLIOGRAPHY Kats Y. Enabling Intelligent Agents and the Semantic Web for ECommerce. Computing, (2, 3), 2003, pp. 153-159, ISSN: 17276209. Ontology Learning for the Semantic Web by A. Maedche, Kluwer AcademicPublishers, 2002, ISBN: 0792376560. The Semantic Web: A Guide to the Future of XML, Web Services, and Knowledge Management, by Michael C. Daconta et al, John & Sons, 2003, ISBN: 0471432571. Towards the Semantic Web: Ontology-driven Knowledge Management, ed. by John Davies, Dieter Fensel, Frank Van Hamelen, John Wiley & Sons, 2003, ISBN: 0470858060.

Copyright © 2006, Idea Group Inc. Copying or distributing in print or electronic forms without written permission of Idea Group Inc. is prohibited.

970 2006 IRMA International Conference

Organizational Administrative Information Mangement: Issues Concerning Distribution, Retention, and Availability of Work-Related Information David W. Miller, Paul J. Lazarony, & Donna A. Driscoll California State University, Northridge, College of Business & Economics, Dept of Accounting & Information Systems, 18111 Nordhoff St., Northridge, CA 91311-8372, (818) 677-2451, {david.w.miller, paul.lazarony, donna.driscoll}@csun.edu

INTRODUCTION Electronic mail (email) has been seen as a valuable tool within organizations as a means of distributing information (Motiwalla, 1995; Zhao, Kumar and Stohr, 2001), particularly organizational administrative information (Merrier, Duff and Patterson, 1999). Organizational administrative information (OAI) includes policy statements and other administrative information, notices of upcoming events, job opportunity messages and other news items related to an organization. Because email makes it possible to disseminate information quickly and easily, it has become one of the most accepted and frequently used communication methods in today’s office environment (Merrier, Duff and Patterson, 1999). Unfortunately, the features that have made email a popular means for distributing OAI have also created a problem for its users: information overload (Zhao, Kumar and Stohr, 2001). Emails come to members of an organization by the thousands and reside in individual mailboxes that may not have any coherent organizational scheme in which users prioritize, retain and can retrieve relevant OAI. Content management systems (CMS) have been developed to address problems of unstructured information management and are being increasingly implemented in the workplace. The subject of the drawbacks of using email as an OAI distribution system has been discussed in trade and business publications as well as has the use of CMS. However, there has been little discussion, or academic research conducted, in the use of the posting capabilities of CMS to correct many of the perceived shortcomings of the email OAI distribution, retention and availability. The purpose of this study is to conduct assessments of: (1) an existing email-based system of OAI management and (2) a new OAI CMS implementation.

HYPOTHESES Regarding hypotheses, we believe that: (1) OAI recipients (users) are not certain that they receive or know how to access all pertinent OAI, (2) OAI distributors are uncertain that all OAI recipients receive distributions or know how to access pertinent OAI, (3) OAI users are not certain that they retain and can retrieve all pertinent OAI and (4) OAI distributors are uncertain that all OAI recipients retain and can retrieve the OAI. We further hypothesize that the CMS will reduce these problems.

RESEARCH METHODS An online, self-report anonymous survey instrument has been issued to employees of the Business School of a large university in the western United States to capture respondents’ perceptions on the existing distribution, retention and availability of OAI within the Business School. A similar survey instrument will be issued after a reasonable “shake out” period following the implementation of a CMS. Completion of the survey questionnaire is voluntary and takes approximately twenty

(20) minutes to complete. The only personal information requested of subjects is the type of position held and level of use of OAI. Modified versions of validated survey instruments are used. Part of the survey is drawn from the Chang and King (2005) instrument developed to measure information systems performance. Since the CMS that is the subject of this study is a subsystem, questionnaire items have been removed that are applicable only at a systems level. The remainder of the questionnaire is an adaptation of the Davis (Davis, Bagozzi and Warshaw, 1989) Technology Acceptance Model (TAM) (cf. Salisbury, Chin, Gopal Newsted, 2002 and Venkatesh, 2000). TAM provides measures for the ease of use and usefulness of the technology. All items in the survey use a Likert-style five point scale soliciting respondents’ agreement with the question.

PRELIMINARY FINDINGS There were thirty-eight respondents of approximately 150 employees of the Business School (see Table 1 for details). Five respondents abandoned the survey before completion while another four replied “N/ A” to forty percent or more of the survey questions. Thus, twenty-nine respondents substantially completed the survey. Table 2 shows the level of usage of OAI by respondents. Approximately 88 percent of those responding indicate that they are at least moderate users of OAI. Moving on to the responses themselves, the average standard deviation for all items is slightly greater than one unit (1.06). The minimum standard deviation is 0.84 while the maximum standard deviation is 1.27. The median of the standard deviations is just 0.0045 greater than the mean of the standard deviations. These values show that the items have reasonable variability in that it is close to one, but that there is reasonable agreement as the range in standard deviations is less than one. The closeness of the mean and median values indicates that the variation in the standard deviations is well distributed around the mean. This preliminary examination lends some credibility of the survey instrument for data analysis.

Table 1. Respondent characteristics Position Faculty – Assistant Professor Faculty – Associate Professor Faculty – Professor Faculty – Full-time Lecturer Faculty – Part-time Lecturer Faculty – FERP Professor Staff Administrator Responses Skipped this item

Response Total 3 4 16 0 2 1 6 1 33 5

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Percent 9.1% 12.1% 48.5% 0.0% 6.1% 3.0% 18.2% 3.0%

Emerging Trends and Challenges in IT Management Table 2.Level of usage of OAI Level of Usage Very Heavy User Heavy User Moderate User Light User I make no (or almost no) use of this information Responses Skipped this item

Response Total 2 12 15 4 0 33 5

Percent 6.1% 36.4% 45.5% 12.1% 0.0%

The responses are separated into four broad categories. These categories are a post hoc decision on how the data may be represented. One category relates to the quality of the information itself. Survey items in this category seek to measure users’ confidence in the quality of the OAI that is the focus of this study. The other three categories relate to the distribution, retention and availability of the information. Survey items in this category seek to measure users’ belief that they receive important OAI and that important OAI that they have distributed is received by appropriate recipients and that it is not distributed to those who should not receive the OAI. The mean score in each category is shown in Table 3.

DISCUSSION The first item for discussion is the survey instrument itself. In the case of the four respondents providing a substantial number of “N/A” item responses, those responses began at a point in the survey with the subject, “finishing out” the survey with the “N/A” responses. This is, therefore, seen as another means of abandoning the survey making for nine of thirtyeight respondents (24%) abandoned the survey before completion. The researchers also received casual comments from individuals who had taken the survey that they found the instrument to be difficult to complete. One member of the population even replied to the email message that, upon examination of the survey, refused to respond to the survey because he could not see how the instrument could possibly be relevant to the topic of interest. The most prevalent feedback received is that they found it difficult to determine which information we were asking about with this survey. The introduction to the survey described OAI as: The focus of this study is information that is distributed among employees of the college, primarily through email. Examples of such information include, but are not limited to: (a) distribution of policy statements, (b) notices of upcoming events, (c) meeting agendas/minutes, (d) discussions of issues, (e) student job opportunity messages, and (f) other news items related to [the Business School]. It was also made clear that the information that is the focus of this study is limited to information distributed within the Business School and does not include information distributed by the University or available in the campus-wide information system. These observations indicate that the adaptation of the survey instrument may have been less than successful. Since the original survey is designed to measure the performance of information systems at the system level, the information in question is all information that one could access through the system. In the case within this study, the focus is on a subset of information. In this way, the researchers placed respondents in the position of having to differentiate School level from University level information, and to separate out different sources of School level information. Therefore, questions asked about “the Table 3. Statistics by category Category Quality of Information Distribution Retention Availability

Mean 2.96 3.09 3.10 2.96

St. Dev. 0.41 0.33 0.35 0.20

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information” can seem vague and uncertain. Clearly, the researchers need to consider revising the survey instrument for measures of subsystem level performance and specify the particular information of interest for a particular survey question. Validating the survey items has not been accomplished as of this writing. Contributing to this is the concern with the structure of the survey instrument itself and the possibility that it may not be appropriate for subsystem performance measures. It is not possible at this time to perform factor analysis on the items to validate the instrument as there are not enough responses to satisfy the statistical examination. The preliminary statistics presented in Table 3 indicate that respondents, in general are somewhat confident in the means of distribution, retention and availability of OAI and the quality of that information. These measures represent what may be considered “middle-of-the-road” values. This impression is also reflected in the relatively small variation in mean values. It may be that the uncertainty of some of the respondents expressed towards the survey instrument resulted in the values and may not reflect their true impression of the OAI that is the focus of the study. What is also yet to be known is if these values improve with the implementation of the CMS.

SIGNIFICANCE OF PROJECT Through articles in trade and business publications, the information systems professional community has repeatedly expressed concern about problems encountered with distribution, retention, and availability of organizational administrative information via email. However, little rigorous academic research has been conducted to support (or refute) the anecdotal evidence. Affirmative results from this study will aid the professional community in justifying the development and implementation of CMS and other information management systems within organizations. The academic disciplines of information systems and of management will benefit from greater knowledge of the problems associated with OAI management and the effectiveness of CMS and similar technologies in reducing those problems.

STATUS OF THE RESEARCH The researchers will undertake an analysis of the survey instrument and redesign and re-issue the survey if deemed necessary. The second survey will be issued following the implementation of the CMS and a reasonable “shake out” period. All of this will occur before the conclusion of the Spring 2006 term so a full report will be presented at the conference.

REFERENCES Chang, C.J. and King, W.R. (2005). Measuring performance of information systems: A functional scorecard, Journal of Management Information Systems, Summer 2005, 1, 85-115. Davis, F.D., Bagozzi, R.P. and Warshaw, P.R. (1989). User acceptance of computer technology: A comparison of two theoretical models, Management Science, 35, 982-1003. Merrier, P.A., Duff, T.B., and Patterson, D. (1999). Form and function of messages sent through a university’s email distribution list, Office Systems Research Journal, 17(1), 19-27. Motiwalla, L.F. (2001). An intelligent agent for prioritizing e-mail messages, Information Resources Management Journal, Spring 1995, 8(2), 16-24. Salisbury, W.D., Chin, W.W., Gopal, A. and Newsted, P.R. (2002). Research Note: Better theory through measurement—developing a scale to capture consensus on appropriation, Information Systems Research, 13, 2002, 91-103. Venkatesh, V. (2000). Determinants of perceived ease of use: Integrating control, intrinsic motivation, and emotion into the technology acceptance model, Information Systems Research, December 2000, 11, 342-365. Zhao, J.L., Kumar, A., and Stohr, E.A. (2001). Workflow-centric information distribution through e-mail, Journal of Management Information Systems, Winter 2000-2001, 17(3), 45-72.

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972 2006 IRMA International Conference

The Current State of the MIS Course: A Study of Business Program IS Curriculum Implementation Fred K. Augustine, Jr. & Theodore J. Surynt Department of Decision and Information Sciences, School of Business Administration, Stetson University, DeLand, FL 32720

INTRODUCTION In December of 2002, an article was published in the Communications of the Association for Information Systems entitled “What Every Business Student Needs to Know About Information Systems” (Ives, Valacich, Watson, and Zmud, 2002). This article was the result of work by a task force of 40 prominent information systems educators and was written in response to draft accreditation guidelines prepared by AACSB International (AACSB International, 2002). These draft guidelines, in the opinion of Ives, Valacich, Watson, Zmud, et al. did not address or reflect the “essential and growing role of information systems and technology in the future careers of business school graduates”. The article goes on to propose a set of “core information systems requirements for all business school graduates”. This extensive list of key information systems concepts and associated learning objectives provide the conceptual basis for essential information systems education in the context of business schools and programs. In terms of the delivery of these key concepts the task force recommended that “in most cases, these concepts and principles are best delivered in an integrated and comprehensive course” (Ives, Valacich, Watson, and Zmud, 2002). It is this “integrated and comprehensive” course that is the focus of this research. Implicit in the work of the AIS Task Force is the fact that this method of implementation of a “information systems knowledge requirement” is not universally used or (more importantly to the task force) mandated by the AACSB. Thus, this paper specifically addresses the issue of how Business schools and program have chosen to implement the concept of a “information systems knowledge requirement” by either using a course (or courses) based on these key concepts or via the more traditional “tools or applications” course. This research will examine business school degree programs to determine the degree to which the “MIS” course or other information systems courses are used to satisfy the requirement of providing an information systems body of knowledge that is essential for all business school students. A survey research plan was developed for the purposes of discovering the current state of the art with respect to the degree to which each category of information systems proficiency courses was used to provide this core knowledge. Also of interest in this study are the names used and the content of various curricular implementations.

DISCUSSION In general, Business degree programs require one or more courses in order for students to satisfy what is often referred to as the “information systems knowledge requirement”. These courses typically fall into one of two broad categories: (1) computer applications or “tools” courses, and (2) information systems concepts or the “MIS” course. The Tools Approach Historically, the most common means of curricular implementation for the “information systems knowledge requirement” for business pro-

grams has been to require students to complete computer applications or “tools” courses. At an earlier point in time (late 1980’s through the 1990’s) this was the most reasonable approach. During this period the microcomputer was in the process of replacing larger computer systems as the platform of choice for infusing information systems knowledge into business degree programs. Student populations during this era were not uniformly aware of or competent in the use of basic computer technologies since the cost of these technologies had not yet reached the point where they were universally available to individuals as well as primary and secondary level educational institutions (It is recognized that a “digital divide” does exist and that this statement is primarily accurate with respect to the experience of institutions in the United States). Thus the computer applications or “tools” course was the easiest and most cost effective way of implementing a requirement for “technology proficiency” in a business degree program. It is, however, the nature of the information systems discipline to evolve. According to Landry, et.al: “Such IT innovativeness comes from an attempt to move beyond the confines of traditional academic and disciplinary boundaries to meet the breadth of knowledge needed …” (Landry, et.al. 2003) For business programs attempting to include a relevant “information systems knowledge requirement”, this evolution took the form of the recognition that students were entering university level degree programs with a knowledge of many of the skills and applications included in the “tools” course. As such, it has become increasingly popular to allow students to demonstrate proficiency via an examination or to simply to assume or require technology proficiency. It is this evolution (among other trends and issues) that motivated the AIS Task Force report (Ives, Blake, and Zmud, 2002). The “MIS” Course The “core information systems requirements for all business school graduates” described above have been included in Business School curricula, in most instances, in the form of a course or courses. The names given to these courses and their content vary widely in spite of the fact that they all reside in business school/program curricula and are based on curriculum standards established by academic and professional organizations devoted to the promotion of information systems education (for example the IS 2002 Model Curriculum which was developed jointly by the Association for Information Systems, Association for Computing Machinery, and the Association for Information Technology Professionals). The course used to fulfill this requirement is often (and most commonly) referred to as the Management Information Systems (MIS) course. Of the 185 universities surveyed in this research (that chose this approach) the course title “Management Information Systems” was used by 80. Of these two approaches, only the “MIS” course implementation satisfies the “core IS requirements” described earlier. It stands to reason,

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Emerging Trends and Challenges in IT Management Figure 1 – Survey Research Results

CONCLUSION

Curricular Implementation

Only

Used By Both

MIS

183

72

45

%

61%

24%

15%

Applications

158

%

52%

973

Neither

therefore, that the way in which business programs implement the “technology requirement” in their curricula, would produce insight about how well business schools and programs are satisfying the “core IS requirements” proposed by the AIS task force. The Research Question This question posed by this paper is, to what extent have business schools and programs chosen to use the “tools course” or the “MIS course” to implement their “information systems knowledge requirement” and thus to what extent have these programs used the “core IS requirements” approach proposed by the AIS task force. As a means of measuring this level of acceptance, the number of business schools and programs which have chosen each method should provide an accurate indication.

RESEARCH METHOD The research method used was survey of the curricula of business schools and programs throughout the United States. The survey was accomplished via the examination of curricular documents provided by the universities housing the business schools and programs, either through the university web site or catalog. The schools surveyed were chosen from the listing of U.S. Universities by State found on the University of Texas web site (http://www.utexas.edu/world/univ/state/). A search of the web sites found on this list was conducted resulting in a compilation of information from a representative sample of 302 universities. All universities that were surveyed can be categorized as “not for profit” institutions and include a business school or program. The web sites were examined for curricular content with respect to information systems courses which provide the “technology proficiency” component of business bachelors degrees and to determine the extent to which degree programs provide courses which satisfy the “core IS requirements” described above.

Given the results shown above, it is apparent that the call for the inclusion of a set of “core IS requirements” in business school curricula has been taken to heart by colleges and universities across the United States. Thus, the efforts of the AIS task force are supported by the faculties and administrators of these institutions. It can be argued that we are at the “maturation stage” of a cyclical trend which will see the business programs of colleges and universities opt out of using teaching information systems tools or applications in favor or the approach or teaching a set of “core IS requirements” which represents a more academically appealing option at the college or university level.

REFERENCES AACSB International. Eligibility Procedures and Standards for Business Accreditation (proposed), September 12, 2002. Dwyer, C. and C.A. Knapp. How Useful is IS 2002? A Case Study Applying the Model Curriculum. Journal of Information Systems Education, Vol. 15(4), 2004, pp. 409-416. Ehie, I.C., Developing a Management Information Systems (MIS) Curriculum: Perspectives from MIS Practitioners. Journal of Education for Business. Vol. 77(3), 2002, pp. 151-158. Foltz, C.B., M.T. O’Hara, and H. Wise. Standardizing the MIS Course: Benefits and Pitfalls. Campus-Wide Information Systems, Vol. 21(4), 2004, pp. 163-169. Gambill, S., J. Clark, and J.L. Maier. CIS vs MIS vs …: The Name Game. The Journal of Computer Information Systems. Vol 39(4), 1999, pp. 22-25. Ives, B., J. Valacich, R.T.Watson, and R. Zmud. What Every Business Student Needs to Know About Information Systems. Communications of the Association for Information Systems, Vol. 9(30), 2002. Landry, J.P., J.H. Pardue, H.E. Longnecker, Jr., and D.F. Feinstein. A Common Theme for IS Degree Programs. Communications of the ACM. Vol. 46(11), 2003, pp. 117-120. Lightfoot, J.M., Fad Verses Fundamentals: The Dilemma for Information Systems Curriculum Design. Journal of Education for Business. Vol. 75(1), 1999, pp. 43-50. Nieuwenhuysen, P. Information Literacy Courses for University Students: Some Experiments and Some Experience. Campus-Wide Information Systems. Vol. 17(2), 2000, pg. 167.

RESULTS Of the 302 Business degree programs surveyed, a total of 186 include the “MIS” course in the core business curriculum while 158 programs require one or more “Applications” courses. This equates to 61% and 52% respectively. A total of 72 (or 24% of Business degree programs) require both an “Applications course and an “MIS” course while 45 programs (or 15%) require neither. These results are summarized in Figure 1 below.

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974 2006 IRMA International Conference

Research in Progress: A Field Study of Career Anchors and Women in the IT Force Jeria L. Quesenberry, School of Information Sciences & Technology, The Pennsylvania State University, 307G Information Sciences & Technology Building, University Park, PA 16802, P 814-865-8952, F 814-865-6426, [email protected]

HUMAN SIDE OF IT TRACK The information age has created an increasing dependence on information technology (IT) as it becomes a primary component of the national and global economy. As a result, researching the composition and predicting the direction of the IT workforce has become an important matter for discussion. A major challenge currently facing IT management is the recruitment and retention of the necessary personnel needed to meet the current and future demands of the information age. At the same time, there is growing discourse that points to the importance of diversity in the global IT economy (e.g. Florida, 2005; Gravely, 2003; Trauth et al., 2006). Despite the shortage of IT professionals and the organizational and social benefits of diversity, women are largely under represented in the IT workforce. A challenge in addressing the under representation of women in the IT workforce is the identification of an appropriate theory for the basis of understanding data about gender and IT. Recently, the Individual Differences Theory of Gender and IT has been proposed by Trauth (Trauth 2002; Trauth et al., 2004), which focuses on personal characteristics and individual responses to environmental influences in order to understand women and their relationships to IT careers. To date, the majority of the individual differences theory research has improved our understanding of the under representation of women in the IT workforce by focusing on individual and societal factors. At this point the individual differences theory has not been used to systematically explain the role of organizational factors in the under representation of women in IT. Therefore, in an attempt to extend the applicability of Trauth’s theory, this study aims to investigate the role of organizational factors, specifically the role of career anchors, in the under representation of women in the IT workforce. A central aspect of internal organizational factors is employee career anchors. A career anchor is “that element of our self-concept that we will not give up, even if forced to make a difficult choice” (Schein, 1987, 158). A career anchor is seen as a person’s self-concept consisting of self-perceived talents, values and the evolved sense of motives that are pertinent to his or her career. Schein (1987) identified eight career anchors of managerial competence, technical or functional competence, entrepreneurship and creativity, autonomy and independence, sense of service or dedication, pure challenge, lifestyle integration and security or stability. DeLong (1982) then added the career anchor of identity and separated security or stability into two independent anchors of organizational stability and geographic stability. Researchers have investigated the role of career anchors in the female under representation in the IT workforce and their results, to date, have been mixed. Crook et al. (1991) found in their study of over 300 IT personnel, that gender differences were not determinate factors in career anchor determination. Rather, men and women equally valued stable careers (organizational security), helping others (service/dedication) and challenges in their careers (challenge/variety). Yet on the other hand, Igbaria et al. (1991) reported that in their study of 464 MIS

employees women were more lifestyle oriented and less technically oriented than men. The mixed results of these studies, coupled with the complexities in understanding gender and the under representation of women in the IT workforce, presents an interesting opportunity for research. Hence, this study extends the theoretical applicability of the individual differences theory by empirically investigating the role of career anchors in female occupation decisions. In doing so, the following research questions will be addressed: 1) how are career anchors manifested in the experiences of women in the IT workforce and how do these manifestations contribute to the individual differences theory?; 2) do those whose job types match their career anchors report higher levels of job satisfaction and lower turnover intention than those who do not?; and 3) what recommendations and interventions can be made for policy-makers and human resource personnel in order to recruit and retain women in the IT workforce? The exploratory nature of this research suggests a qualitative methodological approach in two phases. The first phase consists of a priori theme identification of career anchors via an in-depth literature survey and open-coding of an existing qualitative dataset of 120 interviews.1 The second phase consists of a qualitative investigation for conceptual refinement of factors identified in the initial phase. Approximately 90 minutes in-depth interviews will be held with 30 female participants in the American IT workforce. During the in-depth interviews, the Career Orientations Inventory (COI) questionnaire will be administered, which is a 40 item that provides background information about an individual’s area of competence, motives and values. The researcher will also utilize theoretical/selective coding and open coding techniques in phase one and two of data collection. Findings from this study can directly be applied to industry by exploring the demands and motivations of new workers, comparing how they react to their workplace environment and further examining the administrative structures and policies that successfully accommodate IT workers. Vital in this understanding is the application of a theoretical perspective that is robust enough to account for within gender differences. The research would not only serve as a resource for the current work environment, but also suggests issues and trends for industry to use in a proactive and strategic manner for planning and management. As a result businesses can be better positioned in a holistic manner (e.g. human resource planning, operational expectations and corporate goal alignment) for the rapidly evolving business climate. Finally, findings from this study could be put into practice through recommendations for public policy and initiatives that account for the issues confronting the information society by articulating the ways in which organizational factors are influencing American women and their participation in IT careers.

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Emerging Trends and Challenges in IT Management REFERENCES Crook, C.W., Crepeau, R.G. and McMurtrey, M.E. (1991). “Utilization of the Career Anchor/Career Orientation Constructs for management of I/S Professionals.” Proceedings of the 1991 ACM SIGMIS/CPR Conference, 26-31. DeLong, T.J. (1982). “Reexamining the Career Anchor Model.” Personnel, 59(3), 50-61. Florida, R. (2005). The Flight of the Creative Class: The New Global Competition for Talent. HarperCollins Publishers: New York. Gravely, M.J. (2003). When Black and White Make Green. Impact Group Publishers: Cincinnati, Ohio. Igbaria, M., Greenhaus, J.H., and Parasuraman, S. (1991). “Career Orientations of MIS Employees: An Empirical Analysis.” MIS Quarterly, 15(2), 151-169. Schein, E.H. (1987). “Individuals and Careers.” In Lorsch, J.W. (Ed.) Handbook of Organizational Behavior. Prentice-Hall, Englewood Cliffs, New Jersey. Trauth, E.M. (2002). “Odd Girl Out: An Individual Differences Perspective on Women in the IT Profession.” Information Technology and People, 15(2), 98-118.

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Trauth, E.M., Huang, H., Morgan, A.J., Quesenberry, J.L., and Yeo, B. (2006). “Investigating the Existence and Value of Diversity in the Global IT Workforce: An Analytical Framework.” In Niederman, F. and Ferratt, T. (Eds.) Managing Information Technology Human Resources, Information Age Publishing: Greenwich, Connecticut. Trauth, E.M., Quesenberry, J.L., & Morgan, A.J. (2004). “Understanding the Under Representation of Women in IT: Toward a Theory of Individual Differences.” Tanniru, M. and Weisband, S. (Eds.), Proceedings of the 2004 ACM SIGMIS Conference on Computer Personal Research, Tucson, Arizona, USA, ACM Press: New York, 114-119.

ENDNOTES 1

The existing qualitative dataset has been collected by Eileen M. Trauth in a multi-year study sponsored by National Science Foundation (Grant Number EIA-0204246).

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976 2006 IRMA International Conference

The Role of E-Collaboration in Participative Budgeting Kevin E. Dow, Department of Accounting, College of Business Administration, Kent State University, Kent, Ohio 44242, P: (330) 672-1109, F: (330) 672-2548, [email protected] Penelope Sue Greenberg , Department of MIS/DS, School of Business Administration, Widener University, Chester, PA, 19013, P: (610) 499-4475, F: (610) 499-4614, [email protected] Ralph H. Greenberg , Department of Accounting, Fox School of Business & Management, Temple University, Philadelphia, PA, 19122, P: (215) 204-6830, F: (215) 204-5587, [email protected]

ABSTRACT The increasing use of collaborative technologies and group support systems in the budgeting process has already begun to affect the procedures and outcomes of that process. Even though sizable bodies of research exist in both group support systems (GSS) and participative budgeting (PB), there is a paucity of evidence on how GSS have impacted the budgeting process and outcomes. The objective of this research is to integrate the extant literatures on GSS and PB into a theoretical model that is then used to empirically examine selected impacts of these technologies. The theoretical model is an adaptation and extension of the Theory of Planned Behavior (Ajzen 1991). A survey will be used to test hypotheses arising from the model.

OVERVIEW Communication, collaboration, and group support technologies such as web-based chat tools, web-based asynchronous conferencing tools, email, listservs, collaborative writing tools, workflow control systems, and document management applications have already begun to impact decision-making processes and outcomes. While an extensive literature exists concerning the impacts on e-collaboration of computer-mediated communication (CMC) and group support systems (GSS), one type of managerial decision process that has received little attention in the ecollaboration literature is participative budgeting. Budgeting is an area of continuing interest to managers and scholars because of its important role in communicating goals and constraints, and in motivating and evaluating employees. Participation by subordinates in the budgeting process has been found to have many benefits, including reduced information asymmetry between superiors and subordinates, increased subordinate satisfaction, and higher subordinate motivation. Traditionally, in practice and in research, participation has been assumed to take place in face-to-face meetings between the superior and the subordinate. As in other areas within organizations, group support systems are being deployed in participative budgeting (Smith, Goranson, & Astley, 2003). Unlike some other areas like project management, the role of e-collaboration technologies on participative budgeting has received scant attention. This is unfortunate because the deployment of budgeting GSS is likely to have intended and unintended impacts on both the process and the outcomes of the participative budgeting.

exist between the tasks and variables examined in the GSS literature and those present in budgeting situations. For example, in GSS studies, the group’s objective is to accomplish the immediate task at hand. In budgeting, the participation task has both immediate and subsequent objectives. The immediate objectives are the communication of information relevant to performance goals and the setting of those goals. The subsequent objectives are to improve attitudes toward and to motivate performance of a task that will be evaluated using the goals as the benchmark. The objective of this research is to integrate the extant literatures on GSS and PB into a theoretical model that is then used to empirically examine selected impacts of these technologies. The theoretical model is an adaptation and extension of the Theory of Planned Behavior (Ajzen 1991). A survey will be used to test hypotheses arising from the model.

THEORETICAL MODEL The Theory of Planned Behavior (TPB) is widely accepted as a premise for predicting consciously intended behavior (Ajzen 1991). TPB is an extension of the Theory of Reasoned Action (Ajzen and Fishbein 1980; Fishbein and Ajzen 1975) which relies heavily upon expectancy theory. According to TPB (a simplified model is depicted below), an individual’s behavior is guided by the intention to behave and intention is determined by three kinds of attitudes: (i) personal attitude toward the behavior, (ii) social expectations or social attitudes concerning the behavior which is referred to as the subjective norm, and (iii) the individual’s perceived control over the behavior. In an effort to explain behavior and not just predict it, TPB also deals with the salient perceptions or beliefs that are the antecedents of these attitudes.

Research has shown that, relative to face-to-face communication, group support systems may have positive effects, negative effects or no effects. In an extensive literature review, Fjermestad (2004) found that the type of task, the GSS and their interaction have significant effects on outcome variables. For example, GSS is better for idea generation tasks, face-to-face is better for achieving consensus, and communication medium does not seem to affect satisfaction.

The three types of antecedent salient perceptions or beliefs in TPB correspond to the three kinds of attitudes or influences. Personal behavioral beliefs concerning positive and negative attributes of the behavior are assumed to lead to the personal attitude toward the behavior. Normative beliefs concerning the likelihood that important, referent individuals approve or disapprove of the behavior. Normative beliefs result in perceived social attitudes, expectations and pressure (the subjective norm). Control beliefs deal with the perceived presence or absence of requisite resources and opportunities and with the anticipated obstacles and impediments to performing the behavior. Control beliefs give rise to perceived behavioral control. Thus, these perceptions lead to the attitudes, which are assumed to jointly determine the formation of an individual’s behavioral intention, which, in turn, leads to behavior. As a general rule, the more favorable the attitude, the subjective norm, and the greater the degree of perceived control, the stronger the intention to perform the behavior (Ajzen 1991).

However, it may not be appropriate to extrapolate prior GSS research findings to the participative budgeting process. Inherent differences

This model will be extended to incorporate selected findings from the e-collaboration literature, with emphasis on specific characteristics of

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Emerging Trends and Challenges in IT Management Figure 1. Theory of Planned Behavior

GSS that are currently in use for budgeting in small to mid-size organizations. The model will also be extended to incorporate selected findings from the participative budgeting literature, with emphasis on results concerning organizational and procedural justice. Hypotheses will be developed concerning the impact of the characteristics of GSS and justice on attitudes, norms and control. The ideal sample population for this research is managers who are involved in the budgeting process. It is our intention to include both managers using budgeting GSS and those not using budgeting GSS, so that we can make comparisons. To the extent possible, we plan to use questions and metrics from previously validated survey research instruments. To the extent that this is not possible, we will attempt to statistically validate and evaluate metrics used for the extended model.

BACKGROUND READINGS & REFERENCES Ajzen, I. 1991. The theory of planned behavior. Organizational Behavior and Human Decision Processes 50: 179-211. Ajzen, I. & Fishbein, M. 1980. Understanding attitudes and predicting social behavior. Prentice Hall, Englewood Cliffs, NJ.

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Baltes, B.B., Dickson, M.W., Sherman, M.P., Bauer, C.C., & Laganke, J.S., (2002). Computer-mediated communication and group decision making: A meta-analysis. Organizational Behavior And Human Decision Processes, 87(1), 156-179. Hartwick, J., & Barki, H., (1994). Explaining the role of user participation in information systems use. Management Science, 40(4), 440-465. Covaleski, M.A., Evans, J.H., III, Luft, J.L., & Shields, M.D., (2003). Budgeting research: Three theoretical perspectives and criteria for selective integration. Journal of Management Accounting Research, 15, 3-49. DeSanctis, G. 1983. Expectancy theory as an explanation of voluntary use of a decision support system. Psychological Reports 52 (February) 247-261. Dow, K. E., Greenberg, R. H., & Greenberg, P. S. 2005. E-Collaboration and Management Control Systems: The Case of Participative Budgeting. Working Paper Submitted to The Encyclopedia of ECollaboration, Ned Kock, ed. (forthcoming 2006). Fjermestad, J., (2004). An analysis of communication mode in group support systems research. Decision Support Systems, 37, 239263. Gopinath, C., & Becker, T. E. 2000. Communication, procedural justice and employee attitudes: Relationships under conditions of divestiture. Journal of Management, 26(1): 63-83. Hartwick, J., & Barki, H. 1994. Explaining the role of user participation in information system use. Management Science, 40(4). Lindquist, T. M. 1995. Fairness as an antecedent to participative budgeting: examining the effects of distributive justice, procedural justice and referent cognitions on satisfaction and performance. Journal Of Management Accounting Research, 7: 122147. Magner, N. R., & Welker, R. B. 1994. Responsibility center managers’ reactions to justice in budgetary resource allocations. Advances in Management Accounting, 3: 237-253. Seddon, P. & Yip, S-K. 1992. An empirical evaluation of user information satisfaction (UIS) measures for use with general ledger accounting software. Journal of Information Systems, Spring 75-92. Shields, J. F., & Shields, M. D. 1998. Antecedents of participative budgeting. Accounting, Organizations & Society, 23(1): 49-76. Smith, P.T., Goranson, C.A., & Astley, M.F., (2003). Intranet budgeting does the trick. Strategic Finance, 84(11), 30-33.

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978 2006 IRMA International Conference

Cognitive Reconstructive Remote Sensing for Decision Support in Environmental Resource Management Ivan E. Villalon-Turrubiates & Yuriy V. Shkvarko IEEE, CINVESTAV, Unidad Guadalajara , Av. Científica 1145, Colonia El Bajío, C.P. 45010, Zapopan Jalisco, MEXICO, T: (+5233) 37703700, F: (+5233) 37703709, [email protected]

ABSTRACT In this paper, the problem of reconstruction of different characteristic signatures (CSs) of the monitored environmental scenes from the multispectral remotely sensed data is cast in the unified framework of the statistically optimal Bayesian inference making strategy aggregated with the proposed cognitive descriptive regularization paradigm. The reconstructed CS maps are then treated as sufficient statistical data required for performing the environmental resource management tasks. Simulation examples with the real-world remote sensing data are provided to illustrate the efficiency of the proposed approach.

INTRODUCTION In the environmental resource management applications [4], the estimates of different environmental CSs [8], [9], [10] constitute the statistical data of interest used to perform the management support tasks. In view of this, we refer to the initial stage of the decision support problem as a problem of high-resolution and high-quality reconstruction of the CSs from a set of available measurements of the multi-sensor/multi-spectral data. In principal, we propose a new approach to reconstructive imaging and mapping of different CSs stated and mathematically treated as statistical nonlinear ill-conditioned inverse problems. The descriptive regularization (DR) based investigation of such class of problems was originally undertaken in [1], [4] and developed in recent papers [6], [7] in the scope of the robust regularization methodology. Some recent publications in this field employ the information theory-based approaches [7], [12] but all those are again developed within the DR methodology that simply alleviates the ill-posed nature of the corresponding pattern estimation or scene reconstruction inverse problems [11]. The key distinguishing feature of a new approach proposed in the present study is that the problems of reconstructive multi-sensor imaging and CSs mapping are treated in the unified framework of the statistically optimal Bayesian minimum risk (MR) strategy aggregated with the proposed new cognitive DR paradigm. The advantage of the environmental mapping and feature extraction employing the developed fused MR-DR method over the case of the conventional spatial processing with the use of different previously proposed regularization techniques was verified through extensive simulations. The resolution and information content of different reconstructed CSs were substantially improved: regions of interest and distributed object boundaries of the reconstructed CSs were much better defined, while ringing effects were substantially reduced. The simulation examples illustrate enhanced overall performances attained with the proposed MR-DR method with the use of the real-world remote sensing imagery.

MR-DR METHOD DR Projection Formalism for Data Representation Viewing it as an approximation problem [2], [6] leads one to a projection concept for a reduction of the data wavefield u(y) observed in a given

space-time domain Y ‘ y to the M-D vector U of sampled spatialtemporal data recordings. The M-D observations in the terms of projections [2], [7] can be expressed as

u(M)(y) = (PU(M)u)(y) = ∑ Umφm(y)

(1)

with coefficients U m = [u, h m]U; m = 1, …, M, where P U(M) denotes the projector onto the M-D observation subspace U (M) that is uniquely defined by a set of the basis functions {f m(y)} that span U(M). In analogy to (1), one can define the projection scheme for the K-D approximation of the scene scattering function over a given spatial image domain X ∋ x as follows,

e(K)(x) = (PE(K) e)(x) = ∑ Ekϕk(x);

(2)

E k = [e, g k] E; k = 1, …, K, where P E(K) defines a projector onto the K-D image subspace E (K) spanned by K basis functions {j k(x)}. The {jk(x)} and {g k (x)} compose the dual bases in E (K), and the linear integral projector operator is specified by its kernel P E(K)(x, x') = ϕ jk(x) g k∗ ( x '). Problem Model General model of the observation wavefield u is defined by specifying the stochastic equation of observation of an operator form [6]: u = Se + n; e ∈ E; u, n ∈ U; S : E → U, in the Gilbert signal spaces E and U with the metric structures induced by the inner products, [u 1 , u 2 ] U ∗

= ∫ u1 ( y )u 2 ( y )dy , and [e1, e2]E = e1 (x)e 2∗ (x)dx , respectively. The operator

∫

Y

X

model of the stochastic equation of observation (EO) in the conventional integral form [2], [4] may be rewritten as

u(y) = (Se(x))(y) = ∫ S (y , x) e(x)dx + n(y).

(3)

X

Using the presented above DR formalism, one can proceed from the operator-form EO (3) to its conventional vector form,

U= SE+ N,

(4)

in which E, N and U are the zero-mean vectors composed of the coefficients E k , N m , and Um. These are characterized by the correlation

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Emerging Trends and Challenges in IT Management +

matrices RE = D = D(B) = diag(B), RN, and RU = SR ES + RN, respectively. The vector, B, is composed of the elements B k = ; k = 1, …, K, and is referred to as a K-D vector-form approximation of the Spatial

Bˆ as the discreteform representation of the brightness image of the wavefield sources distributed in the environment remotely sensed with the array radar (SAR), in which case the continuous-form finite dimensional approxi-

Spectrum Pattern (SSP). We refer to the estimate

mation of the estimate of the SSP distribution Bˆ ( K ) (x) in the environ-

GENERAL FORM OF SOLUTION OPERATOR Routinely solving the minimization problem (8) we obtain

F = KA,αS+ R −N1 ,

where

ment in a given spatial image domain X ∋ x can be expressed as follows

KA,α = (S+ R −N1 S + αA–1)–1

ˆ )ϕ(x) , Bˆ ( K ) (x) = ∑ Bk |ϕk(x)|2 = ϕT(x)diag( B

and the desired SSP estimate is given by

(5)

where j(x) represents a K-D vector composed of the basis functions {j k(x)}. Experiment Design Considerations In the traditional remote sensing approach to image formation [3], the

979

Bˆ MR− ED = {KA,αS+ R −N1 Y R −N1 SKA,α}diag = {KA,α aver {Q(j)Q+(j)}KA,α}diag , j∈J

−1

where Q (j) = {S+ R N U(j)} is recognized to be an output of the matched spatial processing algorithm with noise whitening.

matched filter S +P U(M)u(M)(y) = eˆ ( K ) is first applied to the data u(M)(y) to form the estimate

eˆ ( K ) (x)

MR-DR-Robustified Algorithms of the complex scattering function e (K)(x)

and the resulting image is formed as the averaged squared modulus of such ( j) the estimates, i.e. Bˆ ( K ) (x) = aver{| eˆ( K ) (x) |2}. In that case, the degenerate

Signal Formation Operator (SFO) S (M) = P U(M)S uniquely specifies the system ambiguity function (AF) [12].

Robust spatial filtering (RSF) Putting A = I and a = N 0/B 0, where B 0 is the prior average gray level of the SSP, the F can be reduced to the following Tikhonov-type robust spatial filter

FRSF = F (1) = (S+S + (N0/B0)I )–1S+. MR-DR Strategy

Bˆ is recognized to be a vector of the principal diagonal of anstimate of the correlation matrix R E(B), i.e. = {}diag . Thus one can seek to estimate = {} diag given the data correlation matrix RU pre-estimated by some means [4], In the descriptive statistical formalism, the desired SSP vector

ˆ U = Y = aver {U(j)U+(j)}, R j∈J

(6)

Matched spatial filtering (MSF) In the previous scenario for a >> ||S+S||, the F becomes

FMSF = F(2) ≈ const ⋅ S+

i.e. reduces to the conventional MSF operator.

by determining the solution operator F such that

ˆ E }diag = {FYF+}diag . Bˆ = { R

(7)

Fig. 1. Rough radar image formed using conventional MSF technique

To optimize the search of F we propose here the following MR-DR descriptive regularization strategy

F → min{ ℜ (F)}, F

ℜ (F) = trace{(FS – I)A(FS – I)+} + α trace{FRNF+}

(8)

that implies the minimization of a weighted sum of the systematic and fluctuation errors in the desired estimate Bˆ , where the selection (adjustment) of the regularization parameter a and the weight matrix A provides the additional degreees of freedom incorporating any descriptive properties of a solution if those are known a priori [5], [6].

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980 2006 IRMA International Conference Fig. 2. Enhanced scene image formed applying the RSF method

method. All scenes are presented in the same 512-by-512 pixel image format. The advantage of reconstructive imaging using the MR-DRoptimal ASF estimator (Fig. 3) and its robustified suboptimal RSF version (Fig. 2) over the case of conventional MSF technique (Fig. 1) is evident. The spatial resolution is substantially improved with both (RSF and ASF) techniques; the regions of interest and distributed scene boundaries are much better defined. The presented study revealed also the way for deriving the suboptimal RSF technique with substantially decreased computational load. Being a structural simplification of the optimal ASF estimator, the RSF technique permits efficient non-adaptive numerical implementation in both iterative and concise direct computational forms. The proposed robust and adaptive nonlinear estimators contain also some design parameters viewed as the system-level degrees of freedom, which with an adequate selection can improve the performance of the corresponding techniques. The proposed methodology could be considered as an alternative approach to the existing ones that employ the descriptive regularization paradigm [1] - [4] as well as the MR method for SAR image enhancement recently developed in [8], [9].

Fig. 3. Scene image reconstructed applying the ASF method

The provided simulation examples illustrate the overall performance improvements attainable with the proposed methods. The simulations were performed over a typical environmental scene borrowed from the real-world remote sensing imagery. The reconstructed CS maps are treated as sufficient statistical data required for performing the environmental resource management tasks.

REFERENCES [1] [2]

[3] [4]

[5]

[6] Adaptive spatial filtering (ASF) Consider now the case of an arbitrary zero-mean noise with correlation matrix R N, equal importance of two error measures in (9), i.e. a = 1, and ˆ = diag( Bˆ ). In this case, the solution dependent weight matrix A = D the MR-DR solution operator defines the adaptive spatial filter

[7]

[8]

ˆ −1 )–1S+ R −N1 . FASF = F(3) = H = (S+ R −N1 S + D

[9] [10]

SIMULATIONS AND CONCLUDING REMARKS In the present study, we simulated conventional side-looking imaging radar (i.e. the array was synthesized by moving antenna) with the SFO factored along two axes in the image plane: the azimuth (horizontal axis) and the range (vertical axis). We considered a triangular shape of the imaging radar range ambiguity function of 5 pixels width, and a sin(x)/ x shape of the side-looking radar antenna radiation pattern of 15 pixels width at 0.5 from the peak level. Simulation results are presented in Figures 1–3. The figure notes specify each particular employed imaging

[11]

[12]

J. Munier, and G.L. Delisle, “Spatial analysis in passive listening using adaptive techniques”, in Proc. IEEE, 75, pp. 21-37, 1987. S.E. Falkovich, V.I. Ponomaryov and Y.V. Shkvarko, Optimal Reception of Space-Time Signals in Channels with Scattering, Moscow: Radio i Sviaz Press, 1989. A.K. Jain, Fundamentals of Digital Image Processing, N.J.: Englewood Cliffs, 1989. R.K. Raney, Principles and Applications of Imaging Radar, Manual of Remote Sensing, New York: John Wiley & Sons, 1998. I. Chudinovich and C. Constanda, Variational and Potential Methods in the Theory of Bending of Plates with Transverse Shear Deformation, Boca Raton-London-New York-Washington DC: Chapman & Halls/CRC, 2002. Y. V. Shkvarko, “Unifying regularization and Bayesian estimation methods for enhanced imaging with remotely sensed data Part I: Theory”, IEEE Trans. on Geoscience and Remote Sensing, pp. 923-931, 2004. Y. V. Shkvarko, “Unifying regularization and Bayesian estimation methods for enhanced imaging with remotely sensed data Part II: Implementation and performance issues”, IEEE Trans. on Geoscience and Remote Sensing, pp. 932-940, 2004. J. Capon, “High-resolution frequency-wavenumber spectrum analysis”, in Proc. IEEE , 1969, vol. 57, pp. 1408-1410. R.N. McDonough, Nonlinear Methods of Spectral Analysis, S. Haykin, 1984. E. Dadgeon and R.M. Mersereau, Multidimensional Digital Signal Processing, N.J.: Prentice Hall Inc., 1984. D. Ingman and Y. Merlis, “Maximum entropy signal reconstruction with neural networks”, IEEE Trans. Neural Networks, vol. 3, pp. 195-201, 1992. Y. V. Shkvarko and I. E. Villalon-Turrubiates, “Intelligent Processing of Remote Sensing Imagery for Decision Support in Environmental Resource Management: A Neural Computing Paradigm”, 16 th Annual Information Resources Management Asociation (IRMA) International Conference: Managing Modern Org. with Information Technologies, pp. 1060-1062, 2005.

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Emerging Trends and Challenges in IT Management

981

Intelligent Processing for SAR Imagery for Environmental Management Ivan E. Villalon-Turrubiates, IEEE, CINVESTAV, Unidad Guadalajara, Av. Científica 1145, Colonia El Bajío, C.P. 45010, Zapopan Jalisco, MEXICO, T: (+5233) 37703700, F: (+5233) 37703709, [email protected]

ABSTRACT A new intelligent computational paradigm based on the use of Kalman filtering technique [4] modified to reconstruct the dynamic behavior of the physical and electrical characteristics provided via reconstructive SAR imagery. As a matter of particular study, we develop and report the Kalman filter-based algorithm for high-resolution intelligent filtration of the dynamic behavior of the hydrological indexes of the particular tested remotely sensed scenes. The simulation results verify the efficiency of the proposed approach as required for decision support in environmental resources management.

INTRODUCTION Modern applied theory of reconstructive signal and image processing for environmental monitoring and resource management [8] is now a mature and well developed research field, presented and detailed in many works ([1], [2], [3] are only some indicative examples). Although the existing theory offers a manifold of statistical and descriptive regularization techniques to tackle with the particular environmental monitoring problems, in many application areas there still remain some unresolved crucial theoretical and data processing problems related particularly to the extraction and enhancement of environmental characteristics for decision support in environmental management and end-user computing aspects that incorporate the high-precision filtering techniques for evaluation and prediction the dynamic behavior of the particular extracted environmental processes. In this study, we undertake an attempt to develop and verify via computational simulations a new intelligent filtering method that provides the possibility to track, filter and predict the dynamical behavior of a physical characteristics extracted from the remotely sensed scenes provided with the real-world high-resolution SAR data as it is required for decision support in environmental resources management. The proposed methodology aggregates the Kalman filtering technique [4] with the high-resolution algorithms for enhanced SAR imagery [1], [5]. In the simulations, we tested the data provided with the spaceborne SAR with fractionally synthesized array [1], [2].

MATHEMATICAL MODEL OF THE LINEAR DYNAMIC PROBLEM Consider the following model of the Equation of Observation (EO) in continuous time [6]

where S0(t) is the deterministic “carrier” signal of a given model, and l(t) is the unknown stochastic information process to be estimated via processing (filtration) of the observation data signal u(t). Regarding l(t), it is considered that it satisfies some dynamical model specified by the following linear differential equation

d N λ (t ) d N −1 λ (t ) d N −1 x(t ) + α N −1 + ... + α 0 λ (t ) = β N −1 + ... + β 0 x(t ) . N N −1 dt dt dt N −1

The stochastic model can be redefined as follows: the differential equation (3) may be transformed into a system of Linear Differential Equations of order 1 via performing replacement of variables [6], and may be represented in a canonical vector-matrix form

dz (t ) = Fz (t ) + Gx(t ) , dt

ë (t ) = Cz (t ) .

 − α N −1 − α  N −2 F =  ...   − α1  −α 0 

1 0 ... 0 0

0 1 ... 0 0

... ... ... ... ...

0 0  ... ,  1 0 

 β N −1  β  G =  N −2  ,  ...     β0 

C = [1 0 ... 0] .

Considering that x(t)=x(t) is white noise, the statistics are ξ (t ) = 0 and

ξ (t )ξ ∗ (t ' ) = Pξ (t )σ (t − t ' ) [6], where P x(t) is the Disperse Function that represents the dynamics of the process variance developed in a continuous time. Accepting the model of the information process and output of a Linear Dynamic formation system defined above, the Equation of Observation can be defined as follows

(5)

(1)

where n(t) is the White Gaussian Noise and t ∈ T , starting at t0 (initial instant of time). Regarding the signal process, the following linear amplitude-modulated model S(l(t)) is considered,

where

H (t ) = S 0 (t )C(t ) . This model allows formal generalization of

an arbitrary m-channel observation u(t). The aim of the Linear Dynamic Filtration is to find an optimal estimate of the information process l(t) in current time t ( t 0

S (λ (t )) = λ (t ) S 0 (t )

(4)

where

u(t ) = S 0 (t )C(t )z (t ) + n(t ) = H(t )z (t ) + n(t ) u (t ) = S (λ (t )) + n(t )

(3)

(2)

→ t ) via processing the information data vector

z(t) taking in account the a-priori dynamic model of l(t). In other words, one have to design the optimal dynamic filter that when applied to the observation vector u(t) provides the optimal estimation of the desired

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982 2006 IRMA International Conference process that satisfies the a-priori dynamic model specified by the stochastic dynamic state equation [6].

ëˆ (t ) = C(t )zˆ (t ) .

(6)

The Canonical Discrete Form of a LDS represented in state variables is [6]

(11)

opt

The problem is as follows: using this estimate

zˆ (k) is necessary to design opt

the algorithm for producing the optimal estimate z(k+1) incorporating new measurements u(k+1) according to the State Dynamic Equation (SDE), this estimate must satisfy the dynamic equation

z (k + 1) = Ö(k )z (k ) + Ã(k )ξ (k ) .

z (k + 1) = Ö(k )z (k ) + Ã(k )x(k ), ë (k ) = C(k )z (k ) where

zˆ (k ) = zˆ (k ) .

(12)

(7)

Ö(k ) = F (t k )∆t + I and Ã(k ) = G (t k )∆t . In this case, the Eq.

According to the dynamicl model, the anticipated mean value becomes

(5) in discrete time becomes

m z (k + 1) = z (k + 1) = z (k + 1) zˆ (k ) . u( k ) = H ( k ) z ( k ) + n ( k ) .

(8)

The statistical characteristics of the a-priori information in discrete time are [6] Model Noise (initializing or generating model) {x(k)}: î (k ) = 0 ;

•

(13)

Thus, mz(k+1) must be considered as a-priori conditional mean-value of the stat vector for the next (k+1) estimation step, according to the z(k+1) model

m z (k + 1) = Ö z (k ) u (0), u (1),..., u (k ) + Ã ξ (k ) = Özˆ (k ) .

(14)

î (k )î ( j ) = Pî (k , j ) . ∗

•

∗ Observation Noise {n(k)}: n(k ) = 0 ; n(k )n ( j ) = Pn (k , j ) .

•

Random State Vector {z(k)}: z (0) = m z (0) ; z (0) z (0) = Pz (0) .

That is why the prognosis of the mean-value of the next step becomes

∗

m z (k + 1) = Özˆ (k ) . Now it is possible to reduce the estimate strategy to the one-step optimization procedure:

The Disperse Matrix P z (0) (initial state) satisfies the following Disperse Dynamic equation

Pz (k + 1) = z (k + 1)z ∗ (k + 1) = Ö(k )Pz (k )Ö + (k ) + Ã(k )Pî (k )Ã + (k ) .

(9)

STRATEGY OF OPTIMAL DYNAMIC KALMAN FILTER The Kalman filter is an estimator used to estimate the state of a Linear Dynamic System (LDS) perturbed by white Gaussian noise using measurements that are linear functions of the system state corrupted by additive white Gaussian noise. The mathematical model used in the derivation of the Kalman filter is a reasonable representation for many problems of practical interest, including control problems as well as estimation problems. The Kalman filter model is also used for the analysis of measurements and estimation problems [4]. The optimal strategy is to design an optimal decision procedure (optimal filter) that, when applied to all registered observations, provides an optimal solution to the state vector z(k) subjected to it’s a-priori defined dynamic model given by the Statistic Dynamic Equation (SDE). The Optimal Estimate is defined as optimal in the sense of the Bayesian Minimum Risk Strategy (BMR) [6]

zˆ (k ) = z (k ) u (0), u (1),..., u (k ) . opt

Fig. 1. Implementation Signal Flow Diagram

z(0) Pz (0) Ö(k) Ã(k )

Initial Conditions Dynamic A-priori Data

A− Priori Data

z(0)

zˆ (k +1)

Measurement Data

+ u(k +1)

{u(k )}

Σ

PN−1 (k +1)

−

H+ (k +1)

+

K(k +1)

H(k + 1)Ö(k)zˆ (k)

Σ

Σ

+

W

1 z

Ö(k )zˆ (k )

H(k +1)

Adaptation Loop

Fig. 2. Tested SAR image

(10)

In discrete time, the design procedure is based on the concept of mathematical induction, that is, suppose that after k observations

{u (0), u (1),..., u (k )} , one had produced the desired optimal estimate defined for the ultimate step

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Ö(k )

zˆ (k )

Desired Dynamically Filtered Process

C(k +1)

ëˆ (k +1)

Emerging Trends and Challenges in IT Management Fig. 3. Dynamics of hydrological indexes (in the normalized virtual time)

N o rm a liz e d H y d ro lo g ic a l I n d e x e s

1 O rig in a l E s t im a t e d

0 .9 0 .8 0 .7 0 .6 0 .5 0 .4 0 .3 0 .2 0 .1 0

0

10

20

30 40 50 Tim e (p ix e le d virt u a l m o n t h s )

60

70

zˆ (k + 1) = z (k + 1) u (0), u (1),..., u (k ), u (k + 1) = z (k + 1) zˆ (k ); u (k + 1) ; zˆ (k + 1) = z (k + 1) u (k + 1); m z (k + 1) .

(15)

For the ultimate (k+1) step of measurements, the Equation of Observation becomes [6] u (k + 1) = H ( k + 1)z ( k + 1) + n (k + 1)

(16)

with the summarized a-priori information given by Eq. (14). Applying the Bayesian-Wiener time [6], zˆ ( k + 1) = m z (k + 1) + W (k + 1)[u ( k + 1) − H (k + 1)m z ( k + 1) ]

(17)

where the Dynamic Filter Operator is specified as follows,

SIMULATIONS AND CONCLUDING REMARKS In the simulations, we considered the SAR with partially/fractionally synthesized array [1], [2] as a prime remote sensing imaging system. Figure 2 shows the 2-D 256-by-256 pixel format original scene image provided by the carrier SAR sensor system in 2005. This data was borrowed from the real-world remotely sensed SAR imagery of the tested scene of the Guadalajara region (Forest of Primavera) in Mexico. To study the dynamics of the particular hydrological indexes [3] of these scenes that were considered as the particular physical characteristics of interest, the experimental data covered the period of expertise from the year 2000 up to the year 2005, respectively. Figure 3 shows the results obtained with the application of the Kalman technique algorithm summarized in the previous section for enhanced filtering of the dynamics of the hydrological indexes [3] of the tested scenes, studied in the normalized virtual time [7] related to the physical time of the dynamics of the characteristics under our particular study. In the reported simulations we applied the a priori dynamic scene information modeled by Eq. (19). This study intends to establish the foundation to assist in understanding the basic theoretical aspects of how to aggregate the enhanced SAR imaging techniques with Kalman filtering for high-precision intelligent filtration of the dynamical behavior of the physical characteristics of the remotely monitored scenes for decision support in environmental resources management. In our particular study, the dynamics of the hydrological indexes of the SAR maps of the particular tested terrestrial zones (Guadalajara region) were processed. The reported results can be also expanded to other fields related to the study of the dynamical behavior of different physical characteristics provided by remote sensing systems of other particular applications. The reported results of simulation study are indicative of a usefulness of the proposed approach for monitoring the physical environmental characteristics, and those could provide a valuable support in different environmental resource management applications.

REFERENCES [1]

W(k + 1) = K (k + 1)H + (k + 1)PN−1 (k + 1) ; K ( k + 1) = [Ø ( k + 1) + Pz−1 (k + 1) ] ; −1

Ø(k + 1) = H (k + 1)P (k + 1)H(k + 1) ; 1 . PN−1 (k + 1) = PN (k + 1) +

−1 N

[2] (18)

The Figure 1 shows the Optimal Procedure of the discrete Kalman filter technique in a flow diagram form. The Optimal Procedure is defined by the Stochastic Dynamic State Equation [6]

zˆ (k + 1) = Ö(k )zˆ (k ) + W(k + 1)[u(k + 1) − H(k + 1)Ö(k )zˆ (k )]

[3] [4] [5]

(19)

The model of the problem is applied considering that H(k) is the Signal Formation Operator (SFO) that corresponds to the SAR imaging system [1]. The particular SFO was modeled by the sinc-type spectral ambiguity function [9]. The z(k) is the observation data vector from the image, u(k) is the observation data vector contaminated by additive Gaussian noise, and l(k) is the dynamically filtered information process.

[6]

[7]

The data dynamics was approximated by the following model

z (0) = 0 ;

[8]

Pz (0) = N 0 É ; Ö( k ) = F(t k )∆t + I ; Ã( k ) = G (t k ) ∆t .

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[9] (20)

Y.V. Shkvarko, “Unifying regularization and Bayesian estimation methods for enhanced imaging with remotely sensed data. Part I – Theory”, IEEE Trans. Geoscience and Remote Sensing, vol. 42, pp. 923-931, March 2004. Y.V. Shkvarko, “Unifying regularization and Bayesian estimation methods for enhanced imaging with remotely sensed data. Part II – Implementation and performance issues”, IEEE Trans. Geoscience and Remote Sensing, vol. 42, pp. 932-940 , March 2004. M. Skolnik, Radar Handbook, McGraw-Hill, 1990. M. Grewal, Kalman filtering, theory and practice using Matlab, John Wiley & Sons, 2001. Y. V. Shkvarko and I. E. Villalon-Turrubiates, “Intelligent Processing of Remote Sensing Imagery for Decision Support in Environmental Resource Management: A Neural Computing Paradigm”, 16th Annual Information Resources Management Asociation (IRMA) International Conference: Managing Modern Organizations with Information Technologies, pp. 1060-1062, 2005. S.E. Falkovich, V.I. Ponomaryov and Y.V. Shkvarko, Optimal Reception of Space-Time Signals in Channels with Scattering, Moscow: Radio i Sviaz Press, 1989. I.E. Villalon-Turrubiates, O.G. Ibarra-Manzano, Y.S. Shmaliy, J.A. Andrade-Lucio, “Three-dimensional optimal Kalman algorithm for GPS-based positioning estimation of the stationary object”, Proceedings of the International Conference on Advanced Optoelectronics and Lasers (CAOL), 274-277, September 2003. R.K. Raney, Principles and Applications of Imaging Radar, Manual of Remote Sensing, New York: John Wiley & Sons, 1998. Y.V. Shkvarko, “Theoretical Aspects of Array Radar Imaging via Fusing Experiment Design and Descriptive Regularization Techniques,” 2nd IEEE Workshop on Sensor Array and Multichannel Signal Processing, Washington DC, August 2002.

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984 2006 IRMA International Conference

The Use of Paralingual Web Pages to Improve Trust in E-Government Web Sites in Regions of Highly Bilingual Populations Roy Segovia & Murray E. Jennex San Diego State University, 603 Seagaze Dr. #608, Oceanside, CA 92054, F 760-722-2668, [email protected], [email protected]

INTRODUCTION The World Wide Web (Web) has become increasingly integrated into society generating a wider impact on our lives. Additionally, the Web is becoming more global in scope and application. This globalization of the Web is seen in the proliferation of languages that are now encountered in the myriad of web pages that exist, whereas initially most web pages were in English. The wide impact is seen in the many services and functions that are now available through web pages and portals that consumers and citizens now use on a daily basis. One of the newer applications of the web is electronic government or, e-government. This is composed of a vast range of information and services that governments at all levels can provide their constituents using the Internet. The impetus to implement e-government can be attributed to government’s growing awareness of the need to attain more democratic governance (Coleman and Gotze 2001; OECD 2001), coupled with a widespread public interest in the potential of ICT to empower citizens and to increase government accountability (Hart and Teeter 2003). Cost control and improved service to citizens is another driver. The United States E-Government initiative targets use of improved Internet-based technology to make it easy for citizens and businesses to interact with the government, save taxpayer dollars, and streamline citizen-to-government communications. Current E-Government Strategy identifies several high-payoff, government-wide initiatives to integrate agency operations and information technology investments. The goal of these initiatives is to eliminate redundant systems and significantly improve the government’s quality of customer service for citizens and businesses (USOMB, 2005). Trust in government has historically been problematic; constituent citizens are known to have a high level of distrust in their governing bodies. Trust in government has been declining for more than three decades now, and has been the topic of a substantial amount of research in political science (Levi and Stoker, 2000 and Hibbing and TheissMorse, 2002). In the state of California, a recent study exposed an unexpectedly high level of distrust in government by California citizens. During 2004, a series of dialog-oriented seminars were held by Viewpoint Learning in various locations in California. One of the seven major findings of the study was that “profound mistrust of government and elected officials emerged as a central underlying issue…” Furthermore, “this mistrust was both more intense and more persistent than expected, outstripping the levels that have been measured by polls and focus groups” (Rosell, Gantwerk, and Furth, 2005). As with traditional trust in government, there are known issues with trust in e-government websites. This is clearly the effect of the general mistrust by citizens in their government bodies, as mentioned previously. The principal reason given for mistrust of the Web is an artifact

of the internet itself. Namely, the internet is now perceived to be beyond the control of the hosts and providers in terms of security and trust. Despite the use of lock icons, digital signatures, passwords, privacy policy statements, and other security techniques, internet users feel that “hosts and providers have lost control of the digital data transport medium as well as the software infrastructure that supports it.” Thus the growth of e-government has been impeded in recent years (Mercuri, 2005). An echo of the technology-based trust issue comes from Reinhard Scholl of the International Telecommunication Union (ITU). He points to the Geneva Plan of Action, “which recognizes that confidence and security are among the main pillars of the Information Society.” The ITU provides support for national e-government projects, including enhancing security and trust in the use of public networks (Khalil-babnet, 2005). Beyond the technology issue of trust, Gassert covers various aspects of building trust in e-government. He states the importance of fostering confidence and not suspicion and expresses the need for interfaces to have ease of use and usability (Gassert, 2004). Thus improvement of trust in government is a critical issue. In the study by Viewpoint Learning, the citizens in the study voiced a strong desire to find constructive solutions to the problems facing the state (Rosell, Gantwerk, and Furth, 2005). In a geographical area with a high proportion of bilingual speakers, usage of e-government websites may be improved in the same way as has been shown effective in electronic commerce (ecommerce). That is, with regard to language issues, researchers have found that customers are far more likely to buy products and services from Web sites in their own language, even if they can read English well. Furthermore, attention to site visitors’ needs should be an important consideration in Web design, because such attention can help a site build trust with customers (Schneider, 2003). For countries where there are multilingual populations it is expected that trust in government will be less than single language countries. This makes the challenge for government bodies in these countries seeking to provide e-government resources as twofold. First, how to provide website resources that adequately address the language issues of the multilingual citizens; second, how to improve trust in the governing body from those citizens. We propose that a method for improving trust in multilingual nations is to use a format of web page design involving paralingual content. Paralingual web design involves placing content in both languages but instead of having separate pages for each language, the multilingual content is placed side by side. This allows readers who are bilingual to easily see both versions and readily determine if the same information is being said in each version. It is expected that trust will be increased through this citizen validation process.

Copyright © 2006, Idea Group Inc. Copying or distributing in print or electronic forms without written permission of Idea Group Inc. is prohibited.

Emerging Trends and Challenges in IT Management One of the primary reasons for the undertaking of this research is the assertion that trust in e-government is improved among bilingual populations by seeing the website content in both languages side by side on the same page. This format allows the bilingual (or multilingual) site visitor to see at one time that the information is the same in both languages. This is in comparison with web pages where the information is separated into different pages and the site visitor is unable to directly compare the information. As Gassert stated, the improved usability of this web design will improve trust in the web site. Likewise, for bilingual citizens who may have better communication skills in the alternate language, the improvement of trust may result from the increased knowledge transfer from the paralingual web page. This research in progress paper reports on our efforts to validate that paralingual websites will increase citizen trust.

RESEARCH QUESTION This research seeks to determine if the use of paralingual website design will improve constituents trust in their E-government websites. Two hypotheses were tested: H1: H2:

Use of paralingual web pages will not decrease usablity. Use of paralingual web pages will increase trust in the page content and government sponsor.

RESEARCH METHODOLOGY This research utilizes an experiment to test the hypothesis that paralingual website design for E-government will increase trust in the users. To conduct this experiment several pages on the website of a voluntary municipality were converted to the paralingual format. The voluntary municipality was located approximately 10 miles from the United States border next to Mexico. This municipality was known to have a high proportion of English-Spanish bilingual residents and a population that is 60% Hispanic. The original English content on three pages of the municipality website was supplemented with the equivalent translation in Spanish placed horizontally adjacent to each other. Municipality officials encouraged constituents and residents in the vicinity through a series of public announcements to visit the modified web pages and to complete a brief survey documenting their opinions on the website. The respondents to the survey had the choice of filling out the survey in English or Spanish, presumably their primary language of communication. The survey consists of eight questions. Four questions deal with demographics of the respondents. Two questions dealt specifically with trust. The first asked: “Please respond to this statement: I have a greater trust now than before in my understanding of the National City website.” The second asked: “Please respond to this statement: I have a greater trust now than before in the information on the National City website because it is in English and Spanish side by side.” The last two questions asked if the respondent was aware there were multiple languages spoken in the community and how usable the web site was with respect to reading and comprehending the web page material. Responses to the trust and usability questions were based on a Likert scale and were analyzed statistically for significance of differences between groups. Two major groups were compared, the respondents to the English survey and the respondents to the Spanish survey. Currently survey responses are being collected and will be statistically analyzed when a sufficient number of responses have been collected to make the analysis statistically valid.

PRELIMINARY RESULTS So far 92 responses have been analyzed 17 in Spanish and 75 in English. Analysis of these responses with respect to trust and usability was conducted using the Mann Whitney U test and Spearman’s rho. There

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was no significant difference between English and Spanish responses with respect to improving trust in the National City web site. There was a significant difference between English and Spanish responses with respect to increasing trust based on seeing English and Spanish side by side; with the Spanish responses showing increased trust. Finally, English and Spanish responses both found the web site usable with respect to reading and comprehending the paralingual material with no significant differences found between the two groups. Interpretation of these results supports the conclusion that with the web site being usable, both English and Spanish speakers increased their trust in the web site. However, it also shows that Spanish speakers increased their trust in the web site when the material was presented in a paralingual format while English speakers did not. This was an expected finding and it leads to the conclusion that using a paralingual format for egovernment increases trust among minority language speakers. This is useful as it supports governments in using a paralingual format for web page design for the purpose of increasing minority trust. For democratic societies this is a significant finding.

REFERENCES Coleman, S., and Gøtze, J, (2001). Bowling Together: Online Public Engagement in Policy Deliberation. Hansard Society, London, available at http://bowlingtogether.net, accessed 10/4/2005. Gassert, H., (2004). How to Make Citizenz Trust E-Government. University of Fribourg, E-Government Seminar, Information Systems Research Group. Available at http://edu.mediagonal.ch/ unifr/egov-trust/slides/html/title.html accessed November 29, 2005. Hart, P.D. and Teeter, R.M., (2003). The New E-government Equation: Ease, Engagement, Privacy and Protection. A report prepared for the Council for Excellence in Government, 2003 available at http://www.excelgov.org/usermedia/images/uploads/PDFs/ egovpoll2003.pdf, accessed 10/5/2005 Hibbing, J.R. and Theiss-Morse, E. (2002). Stealth Democracy: Americans’ Beliefs About How Government Should Work. Cambridge University Press. Khalil-babnet, M., (2005). WSIS Prepcom-2: Cybersecurity an Issue for All. Available at http://www.babnet.net/en_detail.asp?id=935 accessed November 29, 2005. Levi, M. and Stoker, L., (2000). Political trust and trustworthiness. Annual Review of Political Science 3: 475-507. Mercuri, R. T. (2005). Trusting in Transparency. Communications of the ACM, Association for Computing Machinery, 48(5), pp. 15. National Performance Review, (1993). From Red Tape To Results: Creating A Government That Works Better And Costs Less. Washington, D.C.: Government Printing Office. Organization for Economic Co-operation and Development (OECD), (2001). Citizens as Partners, Information, Consultation and Public Participation in Policy-Making. Osborne, D. and Gaebler, T., (1992). Reinventing Government: How The Entrepreneurial Spirit Is Transforming The Public Sector. Reading, MA: Addison-Wesley. Rosell, S., Gantwerk, H., and Furth, I., (2005). Listening To Californians: Bridging The Disconnect. Viewpoint Learning, Inc., available at http://www.viewpointlearning.com/pdf/ HI_Report_FINAL.pdf. Accessed 1/15/2006. Schneider, G. P. (2003). Electronic Commerce, Fourth Annual Edition. Boston: Thomson Course Technology. United States Office of Management and Budget (USOMB), (2005). EGov: Powering America’s Future With Technology. Available at http://www.whitehouse.gov/omb/egov/index.html. Accessed 10/5/2005.

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986 2006 IRMA International Conference

Managing Concurrent XML Structures: The Multi-Structured Document Building Process Noureddine Chatti, Sylvie Calabretto, & Jean-Marie Pinon LIRIS-INSA de LYON, 7 av. Jean Chapelle, F-69621 Villeurbanne Cedex - France, T 0033472436174, F 0033472438713 {noureddine.chatti, sylvie.calabretto, jean-marie.pinon}@insa-lyon.fr

ABSTRACT In this paper we deal with the problem of multiple structuring of documents. We have proposed a specific model called Multi-structured Document Model (MSDM) approaching the problem in a generic way. To build a multi-structured document from existing XML structures of the same initial document, we have developed a parser called MultiXML-Parser (MXP). This parser will be integrated in a multi-structured document management system.

1 INTRODUCTION Actually, XML is a standard for content document structuring. It allows encoding of hierarchical structures. A problem arises when we want to define and to manage simultaneously different structures for the same contents. In this case, these structures are called concurrent, since they share the same content. For example, humanities and more particularly the study of mediaeval manuscripts, imply concurrent hierarchies or structures. Indeed, we can consider two main structures on manuscripts that overlap: the manuscript book structure (a sequence of columns and lines) and the “syntactic” structure (a sequence of phrase and words). Another structure in this domain can be the “damaged” structure (a sequence of damaged elements). The TEI guidelines [8] provide various examples of possible multiple structures. Among them, we can mention: in verse drama, the structure of acts, scenes and speeches often conflicts with the metrical structure. It is very difficult to encode multiple structures in the same XML file. In fact, often, the result of the structures superposition cannot be a well formed XML document due to the structures interlacing (elements overlapping problem). The XML tree model is suitable only for a single hierarchy. The concurrent structures management problem has been encountered by our industrial partner, the CNAF-CNEDI (the National Computer Science Research Center of the Caisse Nationale d’Allocations Familiales) which manipulates legal texts through two different structures: logical structure and semantic structure. The logical structure is defined for the visualisation needs, and the semantic structure is specified to be used by inference systems. These structures are encoded separately in XML format. The main disadvantage of this solution is the content redundancy which makes difficult the document evolution management and may lead to content incoherency. To overcome this limitation, we have developed a parser called MXP (Multi-XML Parser) which allows to build a unified representation of several separate XML structures of the same content. This unified representation built by the MXP parser is named a multi-structured document. The MXP parser will be integrated in a specific environment dedicated to multi-structured document management.

2 RELATED WORK The problem of concurrent structures encoding has attracted many attentions, and several approaches has been proposed. The CONCUR option [1] is an SGML functionality which allows referencing of several

parallel DTDs for the same content. In such SGML document, all structures cohabit in a single file. In this file, the first structure is encoded in a standard way, and for every added structure, a special prefix, denoting the reference to the corresponding DTD, is associated with each start tag. This solution is interesting but it was rarely implemented. For XML, that does not support multiple structuring, the problem is more persistent. In the TEI guidelines, several methods have been proposed to allow encoding of multiple hierarchies [9] in XML. These methods consist in fragmenting elements which do not nest within others. The TEI proposals cannot answer the general problem of the multiple structures encoding because they are not based on appropriate and clear models. To bridge the gaps of existing markup languages, some other works have been carried out in order to define new syntaxes. MECS (Multi-Element Code System) [2] was the first proposed language which allows overlapping between elements. TexMECS [3] is based on MECS language, but it is more complex. This language defines complex structures where elements can have multiple parents. LMNL (Layered Markup and aNnotation Language) [4] defines a specific syntax based on the notion of range, allowing the encoding of multiple structures where elements can overlap. Due to their complexity and incompatibility with XML syntax, these languages remained at experimental stages.

3 THE MULTI-STRUCTURED DOCUMENT MODEL To answer the problem of multiple structuring, we have proposed a specific model, called Multi-Structure Document Model (MSDM) [5]. In MSDM, the problem is approached in a more general way. In fact, we suppose that structures can share just some content fragments, and not necessarily exactly the same content. For our model, concurrent structures are a particular case of multi-structured documents. In this model, which is inspired by the model defined in [6, 7], a multi-structured document is defined using the following notions: •

•

•

Document Structure (DS): this is a description of a document content defined to a specific use. Such structure may be, for example, a physical structure defined for a presentation goal. Base Structure (BS): this structure is visible only internally within the multi-structured document. It is defined strictly in order to organize the content in disjoint elementary fragments. These fragments serve to reconstitute, by composition, the original content associated initially to the document structure elements. Correspondence: a correspondence is a relation between two elements of two distinct structures. The origin of a correspondence is always an element of a document structure. If the correspondence target is an element of the base structure the correspondence is noted DS®BS. This kind of correspondence associates an element of a document structure to its content in the base structure. For example, in Figure 1 the first correspondence on the left associate the text content “a b” to the origin element in the document structure. When the correspondence target belongs to a document structure the correspondence is

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Emerging Trends and Challenges in IT Management Figure 1: Illustration of the multi-structured document model

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4.1 Initialisation of the Multi-structured Document When the first XML file is passed to the MXP parser the multi-structured document, initialisation has begun. During the analysis of the first file, the base structure is initialized, the first document structure is generated and the needed correspondence relations between these tow structures are established. The base structure is initialized with the set of text fragments (PCDATA) tagged in the first XML structure. For each new analyzed PCDATA a new fragment element in the base structure is inserted. Afterwards, a new correspondence linking this fragment with the element in document structure, containing initially the new PCDATA, is created. During this first phase some information will be stored in memory in order to be used in the next phase. The textual content of the first structure is stored as a string after removing all whitespaces. This string is named CompactContent. In order to facilitate the text-matching process, needed for the second phase, a mapping table is created to store, for each fragment reference (f1, f2, etc. in Figure 3) in the base structure, his corresponding text start position in CompactContent. The middle frame in Figure 3 shows an example of a multi-structured document with the CompactContent string and the mapping fragments table after the initialization phase.

denoted DS®DS. The correspondences DS®DS allow to make explicit some hided relations between document structures. Such correspondence may be used to express a synonymy relation between two elements for example. As shown in Figure 1 a multi-structured document is defined by a set of document structures, a base structure and a set of correspondences. In a short representation, a multi-structured document may be defined as the following triplet: .

4 THE MULTI-XML PARSER We are developing, actually, a multi-structured document management system, based on a MSDM implementation. To facilitate multi-structured document production from existing XML structure, we have developed a specific parser called Multi-XML Parser (MXP), which will be integrated to the multi-structured document management system. This parser allows generating a multi-structured document from separate XML structures of a same initial document. To build the multi-structured document the MXP parser performs several steps (Figure 2). As shown in Figure 2, the MXP parser is based on a SAX parser (Simple API for XML) [SAX 02]. SAX is an event-driven model for processing XML. Unlike the DOM (Document Object Model) parser, SAX does not build a complete representation of the parsed document in memory. When SAX reads an XML document, it dispatch events (like start element, end element etc.) that we can capture and treat them in an implementation of the event handler interface. This method is more difficult but it offers better performances. The parsing process of multiple XML structures may be divided in two main phases: the initialisation phase, and the actualisation phase.

4.2 Actualization of the multi-structured document After the initialisation phase, a first version of the multi-structured document is created. However, this multi-structured document has only one document structure. The parsing of an additional XML file will then actualize the multi-structured document by inserting a new document structure. During the actualization phase three operations will be performed: the new document structure generation, the actualization of the base structure, and the creation of the correspondence relations. Before creating a new correspondence with the base structure when a new PCDATA is encountered, MXP tries to retrieve all fragments in the mapping table that matches (entirely or partially) with this one. This action is performed by means of a correspondence retrieval algorithm, which takes into account the fact that the text content in each structure is not necessarily identical. We consider the following variables: • • •

CompactContent is the variable that contains the text content of the first structure without whitespaces. FragMap is the mapping table of fragment positions in CompactContent. _PCDATA contains the text of a PCDATA without whitespaces. For example if PCDATA = “a text fragment” then _PCDATA = “atextfragment”.

The following steps constitute a part of the correspondence retrieval algorithm: When a new PCDATA is parsed do: 1. 2.

Pattern = _PCDATA If CompactContent contains exactly one occurrence of Pattern then:

a. b.

get the start position of Pattern in CompactContent, in terms of this position and the length of _PCDATA get from FragMap all fragments which cover the PCDATA, calculate the real positions (with whitespaces) at which fragments will be split, make the needed fragments decompositions and actualize the base structure and all correspondences associated with these fragments, create the new correspondence relation which links the element containing the PCDATA with the corresponding fragments composition in the base structure.

Figure 2: The Multi-XML Parser

c. d.

e.

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988 2006 IRMA International Conference Figure 3: Illustration of the multi-structured document building precess

5 FUTURE WORK Recently, we have proposed a multi-structured encoding format based on XML syntax. Now, the main perspective of this work is to define a multi-structured query language which may be exploited in several application areas. In addition to the legal texts of the CNAF-CNEDI, we are envisaging to test our system on a collection of structures describing manuscripts from several points of view. The web may be also an important application area of the multi-structuring. In fact, for example we can add structures including semantic information to existing web pages. With an appropriate query language (multi-structured query language), we can improve the information retrieval results.

6 REFERENCES

3.

Else if CompactContent contains several occurrences of Pattern then:

a. b.

Pattern = concatenate (Pattern, next _PCDATA in the parsed structure). Go to 2.

4.

…

We have removed the whitespaces from the text content to simplify the algorithm and to avoid possible errors. In the lower frame of Figure 3, we can see the modifications affected to the multi-structured document in the middle frame, after parsing the second XML structure S 2. The fragment f 1 is split into three others fragments f 3, f 4 and f 5, and the fragment f 2 is split into f6 and f 7. The document structure S 2 is generated and inserted in the multi-structured document. Finally the correspondence relations between S 2 and the updated base structure are established. The mapping table, which has been updated after parsing S 2, will be used if a third structure is presented to the MXP parser.

[1] Barnard, D., Burnard, L., Gaspart, J., Price, L., and SperbergMcQueen, C.M. 1995. Hierarchical Encoding of Text: Technical Problems and SGML Solutions, Computers and the Humanities, Vol. 29, No. 3, pp. 211 – 231. [2] C. Huitfeldt. MECS - A Multi-Element Code System. Working Papers from the Wittgenstein Archives at the University of Bergen, No 3, Version October 1998. http://helmer.hit.uib.no/claus/mecs/ mecs.htm [3] C. Huitfeldt, C. M. Sperberg-McQueen. TexMECS: An experimental markup meta-language for complex documents. Rev. 17 Februhttp://www.hit.uib.no/claus/mlcd/papers/ ary 2001. texmecs.html. [4] J. Tennison, W. Piez. The Layered Markup and Annotation Language (LMNL). In Extreme Markup Languages 2002. August 2002. http://www.extrememarkup.com/extreme/ [5] N. Chatti, S. Calabretto, J.M. Pinon. Vers un environnement de gestion de documents à structures multiples. 20ème JOURNEES BDA 2004, Montpellier. 19-22 October 2004, pp. 47-64 [6] R. Abascal, M. Beigbeder, A. Benel, S. Calabretto, B. Chabbat, P.A. Champin, N. Chatti, D. Jouve, Y. Prie, B. Rumpler, E. Thivant. Documents à structures multiples, SETIT 2004, Sousse Tunisie, Mars 2004 [7] R. Abascal, M. Beigbeder, A. Benel, S. Calabretto, B. Chabbat, P.A. Champin, N. Chatti, D. Jouve, Y. Prie, B. Rumpler, E. Modéliser la structuration multiple des documents. Actes de la Conférence H2PTM Hypertexte et Hypermédia Créer du sens à l’ère du numérique, Ed. Hermès, Paris, 24-26 September 2003, pp. 253258 [8] Sperberg-McQueen, C.M.. and Burnard, L. (eds.) (2002). TEI P4: Guidelines for Electronic Text Encoding and Interchange. Text Encoding Initiative Consortium. XML Version: Oxford, Providence, Charlottesville, Bergen. [9] The XML Version of the TEI Guidelines : Multiple Hierarchies. http:/ /www.tei-c.org/P4X/NH.html

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Web Services Based Tools for Personal Financial Planning Oliver-Braun & Günter Schmidt Dept of Information & Technology Management, Saarland University, PO Box 15 11 50, D-66041 Saarbruecken, Germany [email protected]

1. INTRODUCTION Mission and concern of this chapter is to present an application of Web Services in the field of personal financial planning. This application is embedded in a software system FiXplan (IT-based personal financial planning) for personal financial planning. Personal financial planning is the process of meeting life goals through the management of finances (Certified Financial Planner’s (CFP) Board of Standards, 2005). We will describe the system with the help of a model. Our model fulfills two kinds of purposes: First, the analysis model is a conceptual model that can help financial planners to do their job. Second, at the design stage of system development, system developers can take the analysis model and apply the system architecture to them. The model combines business concepts of personal financial planning with technical concepts from information technology. The contribution is structured as follows: Section 2 provides a short review of the state-of-the-art in the field of personal financial planning research. In Section 3, we describe our model for personal financial planning. Finally, Section 4 resumes the results of the book chapter and discusses future research opportunities within the field of web services based tools for personal financial planning.

2. PERSONAL FINANCIAL PLANNING The field of personal financial planning is well supplied with a lot of textbooks, among them: Böckhoff and Stracke (2001), Keown (2003), Nissenbaum, Raasch, Ratner (2004), Schmidt (2005) and Woerheide (2002) to name just a few. Most books can be used as guides to handle personal financial problems e.g. maximize wealth, achieve financial goals, determine emergency savings, maximize retirement plan contributions, etc. There are also papers in journals ranging from the popular press to academic journals. Braun and Kramer (2004) give a review on software for personal financial planning in German-speaking countries.

Our model for personal finacial planning has two purposes: First, the analysis model can help financial planners to do personal financial planning in a systematic way. Second, at the design stage of system development, system developers can take the analysis model produced during system analysis and apply the system architecture to them. An intrinsic part of our model at the architecture level is the usage of web technologies as web technologies have already and will strongly influence the design and implementation of financial information systems in general. 3.2 Analysis Model The basic analysis use case model is shown in Fig. 3.2. In the following, we will describe the subsystem Core Personal Financial Planning in detail. Core Personal Financial Planning includes three use cases Determining the client’s financial status, Determining a feasible to-be concept, and Determining planning steps that are elaborated in more detail in sections 3.2.1 through 3.2.3. 3.2.1 Determining the client’s financial status Determining the client’s financial status means to answer the question “How is the current situation defined?”. We will pick the following scenarios as a kind of main success scenario. Determining the client’s financial status: 1.

Data gathering. The Financial Planner asks the client for information about the client’s financial situation. This includes information about assets, liabilities, income and expenses.

Figure 3.1. Analysis model and system architecture

3. FIXPLAN (IT-BASED PERSONAL FINANCIAL PLANNING) In this section, we describe shortly our system for personal financial planning. In Section 3.1 we describe the framework for our model, and in Sections 3.2 and 3.3 (parts of) the models for the analysis and architecture level are described.

System

Analysis model 1

3.1 Framework for our Model of a System for Personal Financial Planning Our model for personal finacial planning consists of two parts (see Fig. 3.1): 1. 2.

Analysis model. Can help financial planners to do personal financial planning. System architecture. Can help system developers to develop logical models at the design stage of system devekopment.

Analysis model n

Analysis model N

System architecture

Design model 1

Implementation 1

Design model k

Design model K

Implementation m

Implementation M

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990 2006 IRMA International Conference he like to vacation? How much would he like to spend on the vacation? What assets, such as a new computer or a new car, would he like to acquire? Intermediate goals are usually more financial in nature and less specific in terms of activities and acquisitions. As one thinks further into the future, one cares more about having the financial ability to do things and less about the details of what one will do. Most intermediate goals would likely include more than just wealth targets. For example, a client may target a date for buying his first home. Intermediate goals often address where one wants to be in five or twenty years. For most people, long-term goals include their date of retirement and their accumulated wealth at retirement. What sort of personal balance sheet does a client want to have at retirement?

Figure 3.2. Basic use case model Personal Financial Planning Establishing and defining the client-planner relationship

Core Personal Financial Planning

Determining the client’s financial status

Determining a feasible To-be concept Client Financial Planner Determining planning steps

Implementing the financial planning recommendations

Monitoring the financial planning recommendations

2.

Data evaluation. The Financial Planner uses two financial statements: balance sheet and income statement. 3. Data analysis. The Financial Planner analyses the results from balance sheet and income statement.\ He can investigate for example the state of the foresight and pension plan, risk management, tax charges, return on investments and other financial ratios. 3.2.2 Determining a feasible To-be concept The use case scenario is as follows: Determining a feasible To-be concept: 1.

2.

3.

Data gathering and Feasibilty check. The Financial Planner asks for information about the client’s future financial situation. This includes information about the client’s future incomes and expenses and the client’s assumption on the performance of his assets. Future inclomes and expenses are determied by life-cycle scenarios. The Financial Planner asks the client for his requirements on a feasible To-be concept. A to-be concept is feasible if and only if all requirements are fulfilled at every timepoint. Data evaluation. The Financial Planner uses two financial statements: (planned) balance sheets and (planned) income statements. Data analysis. The Financial Planner analyses the results from balance sheets and income statements. He can investigate for example the state of the foresight and pension plan, risk management, tax charges, return on investments and other financial ratios.

In this section, we will concentrate our discussion at the first step: Data gathering. Future incomes and expenses are determined by financial goals. Financial goals are not just monetary goals, although such goals are obvious and appropriate. Goals can be short term, intermediate term, and long term. Short-term goals are for the coming twelve months. What does a client want his personal balance sheet to look like in twelve months? What would he like to do during the coming year: where would

Life-cylcle scenarios as proposed in Braun (2006) are for example applying for a personal loan, purchasing a car, purchasing and financing a home, auto insurance, homeowner Insurance, health and disability insurance, life Insurance, retirement planning, estate planning. Requirements at a feasible To-be concept as proposed in Braun (2006) are primarily requirements at balance sheets such as the composition of the entire portfolio, a cash reserve, etc. According to the financial goals of a company, a client may have the following two main requirements at a feasible To-be concept: Assurance of liquidity (i.e. to have all the time enough money to cover his consumer spendings) and prevention of personal insolvency (i.e. to avoid inability to pay). Assurance of liquidity (liquidity management) as proposed in Braun (2006) means that one has to prepare for anticipated cash shortages in any future month by ensuring that enough liquid assets to cover the deficiency are available. Some of the more liquid assets include a checking account, a savings account, a money market deposit account, and money market funds. The more funds are maintained in these types of assets, the more liquidity a person will have to cover cash shortages. Even if one has not sufficient liquid assets, one can cover a cash deficiency by obtaining short-term financing (such as using a credit card). If adequate liquidity is maintained, one will not need to borrow every time one needs money. In this way, a person can avoid mayor financial problems and therefore be more likely to achieve financial goals. Prevention of personal insolvency can be done by purchasing insurance. Property and casualty insurance insure assets (such as car and home), health insurance covers health expenses, and disability insurance provides financial support if one becomes disabled. Life insurance provides the family members or other named beneficiaries with financial support in the event of your death. Thus, insurance protects against events that could reduce income or wealth. Retirement planning ensures that one will have sufficient funds at the time you retire. Key retirement planning decisions involve choosing a retirement plan, determining how much to contribute, and allocating the contributions. If the feasibilty check (see Braun (2006)) fails, Personal Financial Planners can apply their knowledge and experience to balance the financial situation. They can make actions that will adjust to the financial structure by changing requirements at a feasible to-be concept, by changing future expences (such as expenses for a car), or by alternative financing expenses (for example by enhancement of revenue). These actions may be necessary to ensure that the main financial goals of the individual the financial planning is made for are fulfilled. 3.2.3 Determining planning steps The planning steps are determined by the financial goals of the client as gathered in step 2 and exactly those activities of the Personal Financial Planner to achieve a feasible To-be concept. 3.3 System Architecture Architecture gives the rules and regulations by which the software has to be constructed. Fig. 3.3 shows the general architecture of our prototype FiXplan (IT-based Personal financial planning), and the data flow between the User Interfaces, the Application Layer, and the Sources Basically, the system contains the following components:

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Emerging Trends and Challenges in IT Management Figure 3.4: Service provider and service consumer

Figure 3.3: General Three-tier architecture of FiXplan

Clients

Server Visual Basic

EXCEL

SOAP/HTTP

User Interfaces

Sources

Java Classes

EXCEL-SHEET HTML/HTTP

accNr SOAP/HTTP

CreditBalance.xls

External Web Sites WEB BROWSER

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balance

WS Consumer

Web Server: SOAP Interface ShowBalance.php

accNr

Application Server: Core Application Logic

balance

SOAP/HTTP

accNr

WS Provider PHP Scripts

Java Server Pages

SOAP/HTTP

FiXplan Main System HTML/HTTP

SOAP/HTTPS

balance GetBalance.php

WEB BROWSER

Sources

System FiXplan

FiXplan Web Services Toolbox

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Bank BankGiro Giro Service Service GetSaldo.jws WS Provider

Financial Applications PHP Classes WS Consumer

SQL

Database Server

•

• •

Clients. Used by personal financial planners or clients to use our Web Services. User Interfaces may be web browsers such as the Internet Explorer or Mozilla, or applications such as Microsoft Excel. Server. As described in the analysis model. The Web Services Toolbox provides useful tools for personal financial planning. Sources. Used as a repository for the tools of the personal finance framework.

• • • • • • •

Getting married Raising a family Coping with divorce Funding a college education Dealing with your parents Losing your life partner Planning for retirement

5. REFERENCES The three-tier architecture of FiXplan supports modular deployment of both device specific user interfaces through multichannel delivery of services and new or adapted operational processes and strategies. All connectivity interfaces are based on standard specifications. FiXplan is both: Web Service Provider and Web Service Consumer as shown in Fig. 3.13: In this example, a Visual Basic function called from an Excel-Sheet sends a SOAP message to the PHP Web Service ShowBalance.php. ShowBalance.php calls the function GetBalance.php that gets the balance via a SOAP message from the Web Service of a Bank Giro Service. ShowBalance.php retrieves the balance of account accNr and constructs a SOAP message that can be consumed by a Visual Basic function in the Excel Sheet.

4. OUTLOOK ON FURTHER RESEARCH Further research is needed to enlarge the toolbox of personal financial planning tools, for example tools that handle questions such as

Böckhoff, M., & Stracke, G. (2001). Der Finanzplaner. Sauer. Braun, O. (2006). Lebensereignis- und Präferenzorientierte Persönliche Finanzplanung - Ein Referenzmodell für das Personal Financial Planning. In Proceedings der Konferenz Neue Entwicklungen im Financial Planning. Liechtenstein, 2006, forthcoming. Braun, O., & Kramer, S. (2004). Vergleichende Untersuchung von Tools zur Privaten Finanzplanung. In S. Geberl, S. Weinmann & D. F. Wiesner (Eds.), Impulse aus der Wirtschaftsinformatik (pp. 119133). Heidelberg: Physica. Certified Financial Planner’s (CFP) Board of Standards, Inc. (2005). Retrieved January 3, 2005, from http://www.cfp.net Keown, A. J. (2003). Personal Finance: Turning Money into Wealth. Upper Saddle River, Prentice Hall. Nissenbaum, M., Raasch, B. J., & Ratner, C. (2004). Ernst & Young’s Personal Financial Planning Guide (5th ed.). John Wiley & Sons. Schmidt, G. (2005). Persönliche Finanzplanung - Modelle und Methoden des Financial Planning. Springer. Woerheide, W. (2002). Core concepts of Personal Finance. John Wiley and Sons.

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992 2006 IRMA International Conference

The Impact of Distance Learning on Graduation Rates for Information Systems Students Michael Mick & Susan E. Conners Purdue University Calumet, School of Management, 2200 169th Street, Hammond, Indiana 46323, T: 219-989-2135 (Mick), -4115 (Conners), F: 219-989-3158 (Mick), [email protected]

INTRODUCTION The use of distance learning methods to deliver post-secondary education has grown in the last decade. The number of students desiring this format, the increase in distance learning course offerings, and the number of institutions offering distance learning formats to deliver their curricula raise questions concerning the effect of distance learning on graduation rates, such as whether these courses prepare students as well as traditional on-campus courses for graduation. Student retention and success in succeeding courses and persistence to graduation are significant measures for assessing programs. One of the most common measures of the relative success of a curriculum is the graduation rate of students following that course of study. While a number of measures for course efficacy may be used, the actual measure of the degree program is the number of students persisting to graduation. Using distance learning to deliver courses may impact that graduation rate and ultimately contribute to the success or failure of a curriculum.

RESEARCH PROJECT The research in progress investigates whether information systems students taking thirty percent or more of college-level courses in a distance learning mode are more or less successful in persisting to graduation. These students are compared to students who take courses principally on-campus, with both sets of students following the same general curriculum. The study examines a ten-year history of students majoring in Information Systems at a Midwestern public university. The major was selected not only for reasons of availability of data and consistency in curriculum, but also because using a set of students who are generally familiar with technology therefore minimizing any impact that might arise from those who are “technology-challenged”. The study compares those who have taken few or no distance learning courses with those who have taken at least thirty percent of their courses via distance learning. The research compares six-year graduation rates, as that is the current standard for measuring graduation success, given that not all students progress to graduation within four years.

number was chosen by the authors as a significant number of distance learning classes. This population of students is then compared to the remaining population of students in the same time frame for graduation rates. The ten year history was chosen as it represents the time frame that the university first started to offer distance learning courses to the present. The student information database for this institution is an Oracle database with the SCT Banner system. The subset of data for the information systems majors was imported to a MS Access database for the purpose of this research. The data originally obtained for this analysis was an un-normalized single table of registration records by student for each term attended within the requested time frame. Each registration record included the term, subject, course, and grade, reported as pass, fail, withdrawn, or incomplete. Pseudo identification numbers were used to group records by student in order to maintain confidentiality. The records contained additional requested information such as gender, ethnicity, admit term, graduation term, age range, and student major. These records were transformed into the four tables as depicted in figure 1. Table Student contains one record per unique student id, while StudentStatus contains one record per student per term, and Registration has one record for each enrolled course for each student by term. The Term table simply holds a description for each possible term code. A Java program was created that queried that database for all registration records for each student, accumulating totals by student on course type (distance learning courses versus non-distance learning courses) and grade for each course type (as described above), as well as major (using the last major for those who changed major) and whether the major was IS or non-IS. From this, percentages of DL and non-DL courses were computed, as well as a ratio of DL to total courses, on an individual student basis.

Figure 1.

RESEARCH METHODOLOGY The purpose of this research is to determine the effect of distance learning courses on graduation rates for information systems majors in a baccalaureate degree program. The research consists of first seeking to answer the question if students taking thirty percent or more distance learning courses are they more or less successful than the student population in general. The second component will be to identify other variables related to distance learning and persistence to graduation. All data on students is mined from a student information database maintained by the university. Students are selected by major and courses are examined to differentiate students who have taken thirty percent or more of their classes via distance learning courses. The thirty percent Copyright © 2006, Idea Group Inc. Copying or distributing in print or electronic forms without written permission of Idea Group Inc. is prohibited.

Emerging Trends and Challenges in IT Management Time of matriculation for a student was calculated as the difference between the admit term and the graduation term, if graduated, or if not graduated, the last term for which there was a registration record. Terms were reported as a code, indicating the term (0 for summer, 1 for autumn, 2 for spring) and the school year (e.g., 1998-1999, 1999-2000, etc.). Because the school utilized a rolling admissions, a student could begin in any of the three terms (summer, autumn, or spring) and officially graduate in any of the three. From this data, two Excel spreadsheets were created. The first containing the per-student data described above, and the second with totals on a term basis. In the second, totals were created for all graduates, all nongraduates, and for counts of less than the thirty percent DL rate, and counts equal to or greater than thirty percent, for all students ordered by admit term and for all IS majors. Additionally, counts for IS graduates, and counts below and equal to or above the thirty percent DL rate for IS graduates are listed by graduation term. The programs and database queries described in the preceding paragraphs were used to acquire the basic data to answer the research question. Further research with additional variables of gender and age will be conducted.

ANALYSIS OF RESEARCH The basic research question looks at two variables. The first variable is students who have taken thirty percent or more of their coursework via distance learning. The second variable is successful graduation. The initial analysis seeks to identify the number of students with thirty percent or more distance learning courses that successfully graduated and compare that number to the graduation rate of the remaining student population. The next part of the research has not yet been completed at the time of the submission of this paper. The second part of the research includes investigating other factors in relation to successful students who graduated taking some of their classes via distance learning. The variables include percentage of distance learning courses taken, gender, and age ranges and their relationship to persistence to graduation.

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Statistical trends of students persisting to graduation and those who do not graduate of both the distance learning and the traditional students will be identified based on the number of distance learning courses taken toward graduation. Further trends of demographic information including age and gender will be identified in the both populations. The first distance learning courses for information systems students were taught in 1995/1996 academic year. There were only a few courses taught in the early years. There were not a consistent number of courses offered distance learning every semester. These factors must be considered when interpreting the initial results.

RESULTS The result of the first part of the research shows an increase in the number of information systems students graduating while taking 30% or more of their courses distance learning. Because distance learning courses did not begin until the fall semester of 1995, the first six year graduates are noted in the 2001/2002 academic year. In the group graduating in 2001/2002 academic year, 4% had taken 30% or more of their courses in distance learning. The next year 2002/2003 showed a marked increase to 10% of the students taking 30% or more of their courses distance learning. That number was sustained in the 2003/2004 school year with 10% of the graduating information systems major meeting the 30% or more distance learning mark.

CONCLUSION While this initial data analysis does not provide a great deal of detail, the basic numbers indicate that students choosing distance learning courses do persist to graduation in a four year undergraduate curriculum. Further tracking of data and monitoring the success rates of students choosing distance learning classes is warranted. This research provides a ten year period of analysis and the results may prove valuable in future curricula and delivery decisions for academic institutions. The results of the second part of the research may also assist in identifying profiles of successful distance learning students.

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994 2006 IRMA International Conference

Agile Practices, Promises of Rigor, and Information Systems Quality Sue Kong, PhD Program, #79, Rutgers Business School, Newark and New Brunswick, Rutgers University, Newark, NJ 07102, T: (973) 946-3680, F: (973) 833-0429, [email protected] Kenneth E. Kendall & Julie E. Kendall School of Business Camden, Rutgers UniversityCamden, NJ 08102, T: (856) 225-6586, F: (856) 424-6157, {ken, julie}@thekendalls.org

INTRODUCTION It has been widely recognized that the plan-based, process-centric and formal systems development methodologies (e.g. Systems Development Life Cycle) are well suited for predictable environments, but lacking in environments with substantial uncertainty (Boehm, 2002, 2003a, 2003b, 2004a, 2004b). In order to cope with uncertainty, practitioners (Beck, 1999; Beck and Fowler, 2001; Cockburn, 2002 and 2004; Schwaber and Beedle, 2002) introduced agile approaches, which are people-centric, less formal, iterative and adaptive. Debates have been raised around agile approaches, especially on the quality effects of agile approaches. Specifically, some researchers believe that agile approaches cannot achieve persistent high systems quality because the constant adaptation will introduce design flaws and coding errors (Paulk, 2001 and 2002). Conversely, other researchers argue that agile methodology increases quality of information systems due to its customer centric and adaptive approach (Armitage, 2004, Huo, Verner, Zhu and Ali Babar, 2004; Opperthauser, 2003). The inconclusive debates around the quality effect of agile approaches have caused great confusion and misunderstanding. The scrutiny of this issue, the impact of agile approaches on quality of the information systems, thus becomes emergent to the research community. However, to our best knowledge, the contemporary literature has largely neglected systematic study of this research question. This paper will examine the impact of agile approaches on the quality of information systems theoretically and empirically. Specifically, we will employ a survey study among information systems personnel to verify our hypothesis drawn from theoretical study. This research will expand our knowledge and inform practitioners.

DEFINITION AND MEASUREMENT OF QUALITY OF INFORMATION SYSTEMS Quality definition originated from the manufacturing industry. The classic quality definitions include “fitness for use” and “customer satisfaction” (Juran, 1999). Similarly, the Institute of Electrical and Electronics Engineers (1987) defines software quality as “the totality of features and characteristics of a software product that bear on its ability to satisfy given needs.” Because information systems are one type of software, we believe that this software quality definition also applies to information systems. DeLone and McLean (1992 and 2002) presented a well known model, D&M Information Systems Success Model (the “D&M Model”), for measuring the effectiveness of information systems. This model consists of six important systems success measures, they are: Systems Quality, Information Quality, Service, Use, User Satisfaction and Net Benefits (DeLone and McLean, 2002). While the D&M Model organizes and resolves the seemingly conflicting arguments regarding the measurement of information systems success, it only addresses the dependent

variables (the output of the development process) and leaves the independent factors that lead to systems success outside the scope. We believe the inclusion of the independent factors, such as the system development methodology, will provide an insightful way to evaluate the various software development methodologies and practices.

RESEARCH MODEL AND SURVEY DESIGN Kendall, Kendall and Kong (2006) believe that the quality of the information systems is highly dependent on the practices and values of the people who develop and implement the systems. Based on the understanding that agile methodology first impacts individual information systems personnel (developers, testers, managers, etc.) through agile practices, principles and values, then affects the team dynamics, and finally influences the quality of information systems (which could be measured by the dependent variables), we propose our research model as Figure 1. Drawn from our model, we hypothesize the following: H 1: H 2: H 3: H 4:

Agile methodology usage is positively associated with net benefits for information systems personnel. Net benefits for information systems personnel are positively associated with net benefits for team. Net benefits for team are positively associated with information quality of the delivered systems. Net benefits for team are positively associated with systems quality of the delivered systems.

Figure 1: The Impact of Agile Approaches on the Quality of Information Systems H3

Information Quality Fitness for Use

Agile Approaches Usage

H1

Net Benefit for IS Personnel

H2

Net Benefit for Team

H4

System Quality Customer Satisfaction

H5 Service Quality

Before Final Release (Development Process)

After Final Release (System in Use) Final Release

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Emerging Trends and Challenges in IT Management H 5:

Net benefits for team are positively associated with service quality of the delivered systems.

A survey study will be conducted to examine the impact of agile approaches on the quality of information systems. Because values and principles are hard to detect and measure, this study will focus on agile practices. Specifically, through literature review, we will identify a typical set of agile practices among other widely used vigorous software practices for research. We will then survey information systems personnel on their view of the impact of agile methodology on them and their team and on the various quality aspects of the delivered systems. Furthermore, we’d like them to identify what software practices, agile or vigorous, tend to improve the quality of the systems. As suggested by Churchill (1979), Straub (1989), Moore and Benbasat (1991) and Chin, Gopal and Salisbury (1997), our survey study will be divided into the following three stages: 1.

2.

3.

Item Creation Stage. At this stage, we will focus on literature review and developing the questionnaire. We plan to use the constructs of our research model as the basic items for the questionnaire. Agile methodology usage is measured using the items from Henderson and Cooprider (1990) and Collins and King (1988), including frequency of use, degree of use, time of use, proficiency and dependency.These items will then be reviewed by field experts to validate the content validity to ensure that these items do reflect the construct of interest appropriately. A pilot questionnaire will be developed at the end of this stage. Pilot Study Stage. Before conducting the survey, a pilot study will be conducted with a convenient sample of 10 users. The purpose of the pilot study is two fold: i) to check how long the survey will take and collect respondent’s feedbacks to further revise the questionnaire; ii) to assess the construct validity and reliability of the questionnaire. We will use factor analysis to assess the construct validity and finalize thequestionnaire. Full Scale Survey. The finalized questionnaire will be distributed to respondents and the results will be analyzed. The population for the full scale survey is information systems personnel, such as managers, programmers, testers, in selected organizations. We will select three (“3”) to five (“5”) organizations of various sizes and in various industries and send their information technology department an invitation asking them to fill out the survey. Most surveys will be conducted online because online surveys can overcome the geographic limitation as well as being cost-saving. Once a satisfactory number of answers are collected 1, we will carry out statistical analysis of the survey results.

We are currently in the process of finalizing the questionnaire and looking for organizations to collect data.

CONTRIBUTION AND FUTURE STUDY This research has the following contributions: •

•

First, past studies have been mostly focused on one or two specific quality definitions and measurements, such as the product conformance quality measured by defect (bugs) rate or the service quality measured by customer satisfaction. Differently, our research model offers a holistic structure to insight various quality aspects and their interrelationship with each other. Such approach helps people to see the whole picture better, which will further aid the clarification of the seemingly inconsistent findings in the discussion of quality effect of agile approaches. Second, contemporary literature frequently lacks of empirical evidence despite making claims. In order to fill this void, we will employ a survey study to verify or refute claims.

The future study topics include but are not limited to the following:

•

•

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The dynamics of various agile practices. Certain agile practices, such as design simplicity, don’t work well independently. Such agile practices much be utilized in certain combination in order to achieve good quality results. Understanding the dynamics among agile practices will help us to deploy agile approaches effectively. The suitability of agile approaches with organizational and project context. Agile approaches are not universal solutions. For example, some practitioners found agile approaches not work well in organizations that emphasize optimization; other practitioners claimed that agile approaches did not work well with life critical systems. Identifying the suitable organizational and project context for agile approaches will lower the chance of failure.

REFERENCES Armitage, J. (2004). “Design: Are Agile Methods Good for Design?” interactions, Vol. 11, Issue 1, January 2004. Beck, K. (1999). Extreme Programming Explained: Embrace Change, Addison Wesley, Boston, 1999. Beck, K. and M. Fowler (2001). Planning Extreme Programming, Addison-Wesley, Boston, 2001. Boehm, B. (2002). “Get ready for agile methods, with care,” Computer, Vol. 35, Issue 1, January 2002, pp.64-69. Boehm, B. and R. Turner (2003a). “Observations on balancing discipline and agility,” Proceedings of the Agile Development Conference, 2003, pp.32-39. Boehm, B. and R. Turner (2003b). “Using risk to balance agile and plandriven methods,” Computer, Vol. 36, Issue 6, June 2003, pp.5766. Boehm, B. and R. Turner (2004a). “Balancing Agility and Discipline: Evaluating and Integrating Agile and Plan-Driven Methods,” Proceedings of the 26 th International Conference on Software Engineering, May 2004. Boehm, B. and R. Turner (2004b). Balancing Agility and Discipline: A Guide for the Perplexed, Addison-Wesley, Boston, 2004. Chin, W.W., A. Gopal, and W. D. Salisbury (1997). “Advancing the theory of adaptive structuration: The development of a scale to measure faithfulness of appropriation,” Information Systems Research, 1997, Vol. 8, pp. 342-367. Churchill, G.A. (1979). “A paradigm for developing better measures of marketing constructs,” Journal of Marketing Research, Vol. 16, pp. 64-73. Cockburn, A. (2002). Agile Software Development, Boston, AddisonWesley, 2002. Cockburn, A. (2004). Crystal Clear: A Human-Powered Methodology for Small Teams, Boston, Addison-Wesley, October 2004. Collins, P. and D. King (1988). “The Implications of CAD for work and performance,” The Journal of Applied Behavioral Science, Vol. 24, Issue 2, pp.173-190. Cronbach, L.J. (1951). “Coefficient Alpha and the international consistency of tests,” Psychometrical, Vol. 16, September 1951, pp. 297-334. Cronbach, L.J. (1971). “Test Validation,” in Educational Measurement, 2nd Edition, R.L. Thorndike (eds.) American Council on Education, Washington, D.C., 1971, pp. 443-507. DeLone W.H. and E.R. McLean (2002). “Information Systems quality Revisited,” Proceedings of the 35 th Hawaii International Conference on Systems Sciences (HICSS-35’02), 2002. DeLone, W.H. and E.R. McLean (1992). “Information Systems quality: The Quest for the Dependent Variable,” Information Systems Research, Vol. 1, Issue 1, 1992, pp. 60-95. Henderson S. and J. Cooprider (1990). “Dimension of IS planning and design aids: a functional model of CASE technology,” Information Systems Research, Vol. 1, Issue 3, pp.227-308. Huo, M. J. Verner, L. Zhu and M. Ali Babar (2004). “Software Quality and Agile Methods,” Proceedings of the 28 th Annual International Computer Software and Applications Conference (COMPSAC’04), 2004.

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996 2006 IRMA International Conference Juran, J. M. (1999). Juran’s Quality Handbook, Fifth Edition New York, McGraw-Hall, 1999. Kendall, K.E. and J.E. Kendall (2005). Systems Analysis and Design, 6th Edition, Upper Saddle River, NJ, Pearson Prentice Hall, 2004. Kendall. J.E., K.E. Kendall and S. Kong (2006). “Improving Quality Through The Use Of Agile Methods in Systems Development: People and Values in the Quest for Quality,” in Duggan, E.W. & H. Reichgelt (Eds.), Measuring Quality Requirements in Information Systems, Chapter 6, Idea Group Publishing, 2006. Moore, G.C. and I. Benbasat (1991). “Development of an instrument to measure the perceptions of adopting an information technology innovation,” Information Systems Research, 1991, Vol. 2, pp 192-222. Opperthauser, D. (2003). “Defect Management in an Agile Development Environment,” Cross Talk, the Journal of Defense Software Engineering, Sept. 2003.

Paulk, M. C. (2002). “Agile Methodologies and Process Discipline,” Cross Talk, the Journal of Defense Software Engineering, Oct. 2002. Paulk, M.C. (2001). “Extreme Programming from a CMM Perspective,” IEEE Software, Nov./Dec. 2001. Schwaber, K. and M. Beedle (2002). Agile Software Development with Scrum, Prentice-Hall, 2002. Straub, D. W. (1989). “Validating instruments in MIS research,” MIS Quarterly, Vol. 13, 1989, pp 147-169.

ENDNOTES 1

The satisfactory sample size can be calculated as suggested by Kendall and Kendall (2005, p. 126).

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Emerging Trends and Challenges in IT Management

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Exotic Options with Stochastic Volatilities Sanju Vaidya, Division of Math & Computer Information Science, Mercy College, Dobbs Ferry, NY 10522

SECTION 1. INTRODUCTION In 1973, Fischer Black and Myron Scholes made a major breakthrough by developing a model for pricing stock options. In 1997, they were awarded the Nobel Prize in Economics for their outstanding work. The Black-Scholes model and its extensions are very popular for pricing many types of options. Individuals, corporations, and many financial institutions use derivatives like options and futures to reduce risk exposures. The Black-Scholes model is based on the assumption that the asset volatility is either constant or a known function of time over the life of the option. In 1987, J. Hull and A. White examined the problem of pricing of a European call option on a stock that has a stochastic volatility. They proved that when there is a positive correlation between the stock price and its volatility, out-of-the money options are under priced by the Black-Scholes formula, while in-the-money options are overpriced. When the correlation is negative, the effect is reversed. Derivatives with more complicated payoffs than the standard European or American call options and put options are sometimes referred to as exotic options. Most exotic options trade in over-the counter market and are designed by financial institutions to meet the requirements of their clients. In Vaidya [6], some computational techniques for pricing standard options and certain exotic options, Lookback options are discussed. The payoff from the Lookback options depend upon the maximum or minimum stock price reached during the life of the option. In 1979, M. Goldman, H. Sosin, and M. Gatto found valuation formulas for European Lookback Call and put options on a stock when the volatility is constant or a known function of time. In Vaidya [7], the problem of pricing European Lookback call options on a non-dividend paying stock with stochastic volatility is examined. It turned out that the price of a European lookback call on a stock that has a stochastic volatility has a bias relative to the price of the European lookback call on the stock with constant volatility. When the volatility is positively correlated with the stock price, the price of the European lookback call options is below the price of European lookback call options on the stock with constant volatility. When the volatility is negatively correlated with the stock price, the reverse is true. Another important type of Exotic options is Asian options. The payoff from an Asian option depends upon the average price of the underlying asset during the life of the option. There are no exact formulas for pricing Asian options. In 1993, J. Hull and A. White found efficient procedures for pricing these average options on stocks when the volatility is constant. So this leads to the following question.

It turned out that the price of a European average call option on a stock that has a stochastic volatility has a bias relative to the price of the European average call on the stock with constant volatility. When the volatility is positively correlated with the stock price the price of European average call options is below the price of the options on the stock with constant volatility. When the volatility is negatively correlated with the stock price the price of European average call options is above the price of the options on the stock with constant volatility.

SECTION 2. NOTATION AND TERMINOLOGY We will use the notation and terminology from Sections I and II of Hull and White [4].

SECTION 3. RESEARCH METHOD AND CONCLUSION We will use Monte Carlo Simulation to analyze the problem. We will use the antithetic variable technique and the control variable technique as described in Hammersley and Handscomb [3] and Hull and White [4]. The time interval (T - t) is divided into n equal subintervals. Two independent standard normal variates x i and y i (where i is from 1 to n) are sampled. They are used to generate the stock price Si and variance V i at time i in a risk neutral world using the following formulas.

 r Vi−1  t x V t  − 2  ∆ + i i −1∆ 

Si = Si −1e 

(

)

 µ −ζ 2 2 ∆t + ρ x ζ ∆t + 1− ρ 2 y ζ ∆t  i i 

Vi = Vi −1e 

Let X be the strike price and Savg be the arithmetic average of the stock prices S0 , S1 ,.....Sn .The value of e

− r (T −t )

 max(0, S avg − X )  is calculated

to give one sample value p 1 of option price. A second price p 2 is calculated by replacing x i with − xi (1 ≤ i ≤ n ) and repeating the calculations p3 is calculated by replacing y i with − yi (1 ≤ i ≤ n) and p 4 is calculated by replacing x i with –x i and y i with − yi (1 ≤ i ≤ n) . Then two samples values q1 and q2 are calculated by simulating S using x i with –x i with V kept constant at V 0. This gives the following two estimates of the pricing bias: p1 + p3 − 2 q1 2

and

p2 + p4 − 2 q2 .These estimates are averaged over a larger 2

Research Question: What happens to pricing of European average call options on assets when the volatility is stochastic?

number of simulations.

Research Method and Conclusion: We will use Monte Carlo Simulation to analyze the problem. We will use the antithetic variable technique and the control variable technique as described in Hammersley and Handscomb [3] and J. Hull and A. White [4].

It turned out that the price of a European average call option on a stock that has a stochastic volatility has a bias relative to the price of the European average call on the stock with constant volatility. When the volatility is positively correlated with the stock price the price of European average call options is below the price of the options on the stock with constant volatility. When the volatility is negatively correlated with the stock price the price of European average call

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998 2006 IRMA International Conference options is above the price of the options on the stock with constant volatility.

4.

5.

REFERENCES: 1.

2.

3.

Black F. and M. Scholes, “The Pricing of Options and Corporate Liabilities”, Journal of Political Economy, 81 (May-June 1973), 637-659 . Goldman M., Sosin H., Gatto M., “Path Dependent Options: Buy at the Low, Sell at the High”, The Journal of Finance, XXXIV No. 5 (Dec. 1979), 1111 - 1127. Hammersley J.M. and Handscomb D.C., Monte Carlo Methods, London, Methuen, 1964.

6.

7.

Hull J., and White A. “The Pricing of Options on Assets with Stochastic Volatilities”, Journal of Finance XLII (June1987), 281-300. Hull J. and White A. “ Efficient procedures for valuing European and American path-dependent options”, Journal of derivatives, volume 1 (Fall 1993) 21-31. Vaidya S, “Computational Techniques for Pricing Options”, Proceedings of Information Resources Management Association International Conference, 2003. Vaidya S, “Lookback Options with Stochastic Volatilities”, Proceedings of Northeast Decision Sciences Institute, 34 th Annual Meeting,, 2005.

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Emerging Trends and Challenges in IT Management

999

Adoption of Pharmaceutical Sales Force Automation Systems: An Exploratory Study Sung J. Shim, Stillman School of Business, Seton Hall University, 400 South Orange Avenue, South Orange, NJ, 07079, Telephone: 973-761-9236, Fax: 973-761-9217, Email: [email protected]

INTRODUCTION The pharmaceutical industry in the United States spends about $15 billion per year advertising its products to the medical profession [1]. Pharmaceutical detailing, which is using sales representatives to call on physicians to promote products, accounts for about 45 percent of this spending [2]. In order to help sales representatives track sales leads, sales, service requests, and other sales-related information, many pharmaceutical companies have adopted sales force automation (SFA) systems. While pharmaceutical SFA systems adoption is increasing, little systematic research has been done to understand the factors associated with the adoption of pharmaceutical SFA systems. This paper explores the factors contributing to the adoption of pharmaceutical SFA systems with a focus on the system characteristics specifically related to pharmaceutical sales tasks and the effects of those system characteristics on the perceptions of usefulness and ease of use within the technology acceptance model (TAM). The study uses data from a survey of sales representatives at a large pharmaceutical company that has adopted SFA systems. On a theoretical level, the study tests TAM in a context of pharmaceutical SFA systems and extends the line of research on TAM by examining system characteristics as antecedents of the constructs of TAM. On a practical level, the findings on the systems characteristics associated with the TAM constructs can prove helpful to those who use or plan to use pharmaceutical SFA systems.

CONCEPTUAL BACKGROUND TAM [3] posits that perceived usefulness and perceived ease of use are important factors that determine the user’s attitude towards his or her intention to use and actual usage of information systems. Perceived usefulness is defined as “the degree to which a person believes that using a particular system would enhance his or her job performance,” while perceived ease of use is defined as “the degree to which a person believes that using a particular system would be free of effort” [3]. Using the cases of electronic mail system, file system, and graphics packages, Davis [3] showed that both perceived usefulness and perceived ease of use have direct effects on intention to use and actual usage, while perceived ease of use also has an indirect effect on intention to use and actual usage via perceived usefulness. Since Davis [3] introduced TAM, numerous empirical studies have validated TAM across different user populations and information systems. Previous studies on TAM in general agree that TAM is a powerful and parsimonious framework to predict and explain the adoption of information systems. Further, Davis called for “future research (to) consider the role of additional (external) variables within TAM” [4]. Previous research has identified system characteristics as a major category of external variables of TAM [5, 6, 7, 8]. Prior studies that included system characteristics within TAM demonstrate that system characteristics have direct or indirect effects on both perceived usefulness and perceived ease of use of information systems. As noted by Hong, et al [9], however, most of these studies do not highlight the effects of individual system characteristics on the constructs of TAM, since they either used a dummy

variable to represent different information systems or adopted a single overall construct to substitute for the system characteristics. Therefore, there is a need for research to investigate the individual effects of specific system characteristics on the constructs of TAM. The current study attempts to identify the SFA system characteristics specifically related to pharmaceutical sales tasks and to examine the individual effects of those characteristics on the constructs of TAM.

METHODS AND DATA Pharmaceutical SFA systems involve system characteristics that differ from other SFA systems. In order to identify the SFA system characteristics specifically related to pharmaceutical sales tasks, we first examined the process of pharmaceutical sales with the SFA system in consultation with several sales representatives at the target pharmaceutical company. Then, we developed a list of SFA system characteristics specifically related to pharmaceutical sales tasks, and asked the survey respondents to rate the importance of each SFA system characteristic in successfully performing their sales tasks. The extent of their agreement on the importance of SFA system characteristics were measured using 7-point scales ranging from ‘not important at all’(= 1) to ‘very important’ (= 7). The mean ratings of SFA system characteristics identified were found to be all high enough to confirm that the characteristics under consideration are in fact important in successfully performing pharmaceutical sales tasks. Figure 1 shows this study’s research model, which incorporates the factors of SFA system characteristics as antecedents of perceived usefulness and ease of use in TAM. The research model consists of three latent variables including perceived usefulness, perceived ease of use, and usage, and factors of SFA system characteristics. The research model posits that SFA systems usage is influenced by perceptions of usefulness and ease of use of SFA systems, which in turn are influenced by the factors of SFA system characteristics. The items about the SFA system characteristics were also measured by the extent of the user’s satisfaction with the characteristics. User satisfaction has been proposed as “a substitute for objective determinants of information system effectiveness” [10], as the most surrogate measure of system success [11], and as “the most useful assessment of system effectiveness” [12]. This study adopted the items of perceived ease of use, perceived usefulness, and usage from the previously validated inventory and modifies them to suit the current context. The items of perceived usefulness and perceived ease of use were measured by the extent of the user’s agreement on the items. The items of usage included usage frequency and usage volume. Usage frequency was measured as the number of visits to physicians that the user makes on average each day, as the user has to use the SFA system at each visit. Usage volume was measured as the number of minutes that the user uses the SFA system on average per each visit to physician. Responses were received from 148 sales representatives, representing a response rate of 51 percent, but 20 responses were not usable due to lack of data. The sample comprised of the remaining 128 responses, of which 51 (40 percent) were male and 74 (58 percent) were female (three

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1000 2006 IRMA International Conference Figure 1. Research model

REFERENCES [1]

[2]

[3]

[4]

[5]

respondents did not provide information on their gender). On average, the respondents have been in the current pharmaceutical sales position for about three years with pharmaceutical sales experience of about seven and half years. They make about eight visits to physicians on average each day. On average, they use the SFA system for about 15 minutes per visit to a physician and about 55 minutes elsewhere (e.g., home) per day. On average, the respondents have used the SFA system for about 11 months for pharmaceutical sales tasks. The specific procedures of data analysis, which are currently being conducted, include the confirmatory factor analysis for the reliability and validity tests and the structural equation modeling and path analysis to estimate parameter values for the linkages in the model. We hope to report on the results of data analysis at the conference.

RESULTS The main results of this study will be the identification of specific system characteristics associated with the adoption of pharmaceutical SFA systems and the effects of those system characteristics on the perceptions of usefulness and ease of use of the systems. On a practical level, such understanding will prove a helpful viewpoint for those who use or plan to use pharmaceutical SFA systems. On a theoretical level, the research model along with empirical data will contribute to capturing the factors associated with SFA systems adoption and extending the line of research on TAM.

[6]

[7]

[8]

[9]

[10]

[11]

[12]

Bates, A., Bailey, E. and Rajyaguru, I., “Navigating the Edetailing Maze,” International Journal of Medical Marketing, 2(3), 2002, pp. 255-262. Fisher, J. and Wang, R., Pharmaceutical Marketing for the Millennium, 2001, WR Hamvrecht + Co., San Francisco, California. Davis, F. D., “Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology,” MIS Quarterly, 13(3), 1989, pp. 319-340. Davis, F. D., “User Acceptance of Information Technology: System Characteristics, User Perceptions and Behavioral Attitudes,” International Journal of Man-Machine Studies, 38, 1993, pp. 475-487. Agarwal, R. and Prasad, J., “Are Individual Differences Germane to the Acceptance of New Information Technologies?” Decision Sciences, 30(2), 1999, pp. 361-391. Igbaria, M., Guimaraes, T., and Davis, G. B., “Testing the Determinants of Microcomputer Usage via a Structural Equation Model,” Journal of Management Information Systems, 11(4), 1995, pp. 87-114. Jackson, C. M., Chow, S., and Leitch, R. A., “Toward an Understanding of the Behavioral Intentions to Use an Information System,” Decision Sciences, 28(2), 1997, pp. 357-389. Venkatesh, V., “Determinants of Perceived Ease of Use: Integrating Control, Intrinsic Motivation, and Emotion into the Technology Acceptance Model,” Information Systems Research, 11(4), 2000, pp. 342-365. Hong, W., Thong, J. Y. L., Wong, W., and Tam, K., “Determinants of User Acceptance of Digital Libraries: An Empirical Examination of Individual Differences and System Characteristics,” Journal of Management Information Systems, 18(3), 2001-2002, pp. 97-124. Ives, B., Olson, M. H., and Baroudi, J. J., “The Measurement of User Information Satisfaction,” Communications of the ACM, 26(10), 1983, pp. 785-793. Guimaraes, T. and Gupta, Y., “Measuring Top Management Satisfaction with the MIS Department,” OMEGA, 16(1), 1988, pp. 17-24. Hamilton, S. and Chervany, N. L., “Evaluating Information System Effectiveness,” MIS Quarterly, 5(1), 1981, pp. 76-88.

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Emerging Trends and Challenges in IT Management

1001

Speed Analysis of Camera Motion in Video Sequence Thitiporn Lertrusdachakul, Terumasa Aoki, & Hiroshi Yasuda The University of Tokyo, 4-6-1 Komaba, Meguroku, Tokyo, 153-8904, Japan, T: +81-3-5452-5277, F: +81-3-5452-5278, {pom, aoki, yasuda}@mpeg.rcast.u-tokyo.ac.jp

ABSTRACT This paper presents an approach to determine speed of camera motion in video sequences. The technique is based on the analysis of motion trajectories of the corners and interesting points in an image sequence. The spatio-temporal information of the feature points is a key significance in determining camera motion and speed value. The experimental results of speed analysis of camera panning, tilting, zooming, and the combination of panning and tilting are described. We also discuss the applications to help infer the higher-level semantic content and query information for the future video retrieval.

1. INTRODUCTION Recent advances in digital technology, data compression and storage device open new opportunities and present approaches that change the way moving pictures look and are used. Digital video is now increasingly available and more pervasive. With a rich set of standardized tools to describe multimedia content of MPEG-7, the meaning and manipulation of the content have become more accessible to the users and enable the generation of new unique applications. Search and browsing performances become more effective since the detail of content that can be described using MPEG-7 is quite comprehensive. In a video sequence, motion features provide the easiest access to the temporal dimension and are hence of key significance in video indexing. When used in combination with other features such as color or texture, they significantly improve the performance of similarity-based video retrieval. They also enable motion-based queries, which are useful in contexts in which motion has a rich meaning such as sport or surveillance [1]. Camera motion is one aspect to help infer higher-level semantic content and query information in video retrieval. Several approaches have been developed to estimate camera motion. The early researches are based on the analysis of optical flow computed between consecutive images [2]-[4]. However, the estimation of optical flow, which is usually based on gradient methods or block matching methods, is computationally expensive [5]. Recent researches have moved to directly manipulate MPEG-compressed video to extract camera motion using the motion vectors as an alternative to optical flow [6]-[9]. However, the main purpose of MPEG is allowing a reasonable rendering quality at high compression rates. Therefore, the motion estimation can afford to be wrong so long as the errors to correct it are small. In the case of lowtextured and uniform area, the correlation methods used to estimate motion in the first place does not work. This leads to a reason that why the MPEG encoder delivers numerous wrong motion vectors on the background when formed by large uniform regions. In addition, the accuracy in determining camera zoom operation is difficult to achieve because of noises due to independent object motions or the MPEG encoding process, such as quantization errors, and other artifacts. Moreover, the speed of camera motion still has not been focused in the previous researches.

analysis of motion trajectories of image features which is described in section 2. Section 3 presents the methodology in determining speed of camera motion. The experimental results and application are discussed in section 4. Section 5 summarizes the proposed approach and describes the future research direction.

2. CAMERA MOTION ANALYSIS Image features are local, meaningful and detectable parts of an image [10]. They are stable even if there are some changes in image such as illumination, viewpoint, scale, rotation and addition of noise. Using local features, the most important and meaningful parts of the image can be kept, discarding all the noisy and no useful data. This lead to the motivation that if we continuously track those key locations of the image which are more rich of information than others, the motion trajectories could be sufficient to provide a description of global motion characteristic of the whole image sequence. Edges and corners are basic features for image recognition and motion analysis. The motion is unambiguous at a corner while it is ambiguous at an edge. Therefore, we select corners as the image features for motion tracking in our camera motion analysis. By observing the motion trajectories of image features over temporal change, we envisage the

Figure 1. The spatio-temporal characteristic of various camera motions

In this paper, we propose a new approach to determine speed of camera motion in video sequences which help the users to search more accurate information into the temporal domain. The technique is based on the analysis of motion trajectories of image features.0A video sequence is temporally segmented into several camera motion subunits by pattern Copyright © 2006, Idea Group Inc. Copying or distributing in print or electronic forms without written permission of Idea Group Inc. is prohibited.

1002 2006 IRMA International Conference possibilities of accomplishing the spatio-temporal characteristic of camera motion in video sequences. Figure 1 shows the spatio-temporal characteristic of various camera motions. Given a video consists of image sequence with (x, y) image dimension and t temporal dimension. The camera motion can be inferred directly from the spatio-temporal patterns of motion trajectories in (x, t) and (y, t) dimensions. For instance, motion trajectories of horizontal lines in both (x, t) and (y, t) dimensions depict static camera motion. Motion trajectories of slanted lines in (x, t) dimension and horizontal lines in (y, t) dimension indicate panning motion while tilting has the horizontal trajectories in (x, t) dimension and slanted lines in (y, t) dimension. For zooming, the motion trajectories are either expanded in or out for both (x, t) and (y, t) dimensions. The combination of panning and tilting has the motion trajectories of slanted lines in both (x, t) and (y, t) dimensions. The direction of the slanted trajectories indicates the direction of camera motion. We have implemented the algorithm to analysis the motion trajectories of image feature in determining camera motion. The detail can be found in [11]. Although the feature points are disappeared due to the camera movement, object motions, and scene change, the algorithm relies on the stable feature points with the longest tracking duration.

3. SPEED ANALYSIS We determine speed of camera motion based on the slope of motion trajectories. The algorithm consists of three steps as follows. 3.1 Feature Point Selection Since some of feature points disappear quickly due to the movement of camera, analyzing all image features might not be necessary in determining speed of camera motion. The motion trajectory of long tracking duration implies the stability of feature point tracking over temporal change, which provides more efficient analysis. Then we find the effective region that gives the longest tracking duration for each camera motion as described in Fig. 2. The magnitude and direction of arrow show the moving distance and direction of feature points in shaded area due to the camera motion. Tracking duration can be inferred directly from the moving distance, which is proportional to the tracking time. The region that gives the longest tracking duration (i.e., the largest magni-

tude of moving distance in the direction opposite to the camera motion) is defined as the effective region for feature selection in determining speed of camera motion. Only feature points inside shaded area are used for the speed computation. 3.2 Period Selection To make the most reliable outcome, we cut out 5 percent of total time at the beginning and at the end of period of each camera motion. Only motion trajectories in the middle part are used for the analysis. This is to filter out too short trajectories and unreliable time duration during scene change. 3.3 Speed Computation We apply linear regression to determine the slopes of the selected trajectories from Sections 3.1 and 3.2. Then we find the average slope in (x, t) and (y, t) dimensions. Since the motion trajectories sometimes generate the groups of variety of slopes due to the object motions, we filter out the extremely great and small values of slopes including the minor groups of slopes. Only the slopes of dominant group are processed. Then the slope is normalized into the same pixel unit regardless of image size. Let the slopes of motion trajectories in (x, t) and (y, t) for image size of (m´n) pixels be mx and my, respectively. The normalized slopes are computed as follows.

mnx =

mx ×1000 m

mny =

my × 1000 n

The speed of camera motion can be determined by Eq.(1). Let mnxy be a set of mnx and m ny. The speeds of camera panning, tilting, zooming, and the combination of panning and tilting are represented as SPpan, SPtilt, SP zoom , and SP pan & tilt, respectively. SP pan = abs(average(m nx)) SP tilt = abs(average(m ny))

Figure 2. The effective region for speed analysis of each camera motion

SP zoom = abs(average(m nxy)) SPpan & tilt =

(( average( mx )) 2 +( average( m y )) 2 ) m 2 +n 2

(1) × 1000

4. EXPERIMENTAL RESULTS We conduct the experiments to determine the speed of camera motion using the real compressed videos. Fifty shots consisting of five kinds of motions (i.e., static, panning, tilting, zooming, and the combination of panning and tilting) are tested in the experiments. Figure 3(a) shows the example of video sequences and their feature points. The corresponding motion trajectories and result of speed analysis are shown in Figs. 3(b) and 3(c), respectively. The algorithm determines camera motion and its speed in time domain which leads into the interesting applications of video retrieval and scene analysis. In video retrieval, the users are possible to identify the target video with more accurate information of camera motion and its speed. Moreover, they are also possible to give the feedback of the retrieved videos in the term of speed comparison to improve the search results. In scene analysis, the relation of sequence of camera motions, speed, and time duration is possible to infer the events of sport games or the kinds of stories.

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Emerging Trends and Challenges in IT Management Figure 3. The example of tested videos, (a) image sequence and feature points, (b) The corresponding motion trajectories, (c) result of speed analysis

(a)

1003

5. CONCLUSIONS This paper presented the speed analysis of camera motion in video sequences based on the analysis of motion trajectories of image features. The video sequence is temporally segmented into camera motion subunits by using the spatio-temporal information obtained from tracking the image features along an image sequence. The speed analysis is performed by applying linear regression to the motion trajectories after filtering out unreliable trajectories and tracking period. The approach helps to facilitate the motion annotation and content description of a video particularly in the applications of video retrieval, indexing and scene analysis. The efficiency of video searching can be improved since the users can easily query more information in the temporal domain. Searching time can be reduced because the scope of targets is more specific due to the speed information. We expect to expand the application into the scene analysis of sport games in the future.

REFERENCES

(b)

(c)

E. G. R. Iain, H.264 and MPEG-4 video compression: video coding for next-generation multimedia (Wiley, 2003). K. Jinzenji, S. Ishibashi, & H. Kotera, Algorithm for automatically producing layered sprites by detecting camera movement, International Conference on Image Processing, 1997, 767-770. J. Denzler, V. Schless, D. Paulus, & H. Niemann, Statistical approach to classification of flow patterns for motion detection, International Conference on Image Processing, 1996, 517-520. P. Bouthemy, M. Gelgon, & F. Ganansia, A unified approach to shot change detection and camera motion characterization, IEEE Trans. Circuits Syst. Video Technology, 9(7), 1999, 1030-1044. R. Jin, Y. Qi, & A. Hauptmann, A probabilistic model for camera zoom motion detection, The Sixteenth Conference of the International Association for Pattern Recognition, Quebec City, Canada, 2002. R. Wang, & T. Huang, Fast camera motion analysis in MPEG domain, International Conference on Image Processing, 1999, 691-694. P. Jong-Il, S. Inoue, & Y. Iwadate, Estimating camera parameters from motion vectors of digital video, IEEE Workshop Multimedia Signal Processing, 1998, 105-110. E. Ardizzone, M. La Cascia, A. Avanzato, & A. Bruna, Video indexing using MPEG motion compensation vectors, IEEE International Conference on Multimedia Computing and Systems, 1999, 725729. K. Jae-Gon, S. C. Hyun, K. Jinwoong, & K. Hyung-Myung, Efficient camera motion characterization for MPEG video indexing, IEEE International Conference on Multimedia and Expo, 2000, 1171-1174. E. Trucco, & A. Verri, Introductory techniques for 3-D computer vision (Prentice Hall, Englewood Cliffs, NJ, 1998). T. Lertrusdachakul, T. Aoki, & H. Yasuda, Camera Motion Estimation by Image Feature Analysis, The Third International Conference on Advances in Pattern Recognition, 2005, 618-625.

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1004 2006 IRMA International Conference

Small Business Experience and Governance of Employee Owned Personal Digital Devices W. Brett McKenzie, Computer Information Systems, Roger Williams University, Bristol, RI 02809, P 401-254-3534, [email protected]

ABSTRACT This research examines the policies regarding the use of personal digital devices in Small to Medium Enterprises (SME), with an emphasis on small business. Where larger enterprises have focused attention on the potential exposure to data compromise through deliberate or inadvertent misuse of data, SMEs appear less concerned. This study uses interviews and a local survey to examine both the use of digital devices and the policies for security of digital devices.

INTRODUCTION In 1999, Wen Ho Lee, who was accused of downloading classified, nuclear material to a 150 MB digital tape, brought pubic attention to an individual’s ability to download large quantities of data and the possible motives and consequences of such action (US vs. Wen Ho Lee, 1999). Since then, portable digital devices have grown in capability, such as cell phones and PDAs being able to operate on an IP network via wireless. Similarly, they have expanded in storage, such as the MP3 players with gigabyte size hard drives. Connectivity to the network raises security issues just as storage allows replicating and removing from a site large quantities of corporate data. Additionally, the use of portable digital devices in the workplace raises management issues because the devices may be owned by all levels of employees, from the hourly warehouse laborer to the CEO as well as contract employees, such as a cleaning service. Their governance and use in the workplace has become an increasing issue. With the proliferation of these digital storage devices, the trade press has indicated concern for the possible compromise of proprietary or privacy data through deliberate or inadvertent storage of corporate information on portable media (Rosten, 2005). Flash memory with gigabyte storage capacity included in mundane objects, such as pens, Swiss Army knives, and watches or jewelry, has increased the potential to store and transport large data files surreptitiously. In 2004, Gartner created a stir by recommending that companies ban all digital storage devices, in particular, the Apple iPod (Contu, 2004). Large enterprises frequently control the presence of digital devices in the workplace through issuance to an employee of trusted devices. A centralized institutional unit or service provides a cell phone, laptop, or mobile device and integrates it into the enterprise. This form of control minimizes, but does not eliminate individual use of personally owned devices. Subsequently, security companies, such as Safend (http:/ /www.safend.com/), Reflex Magnetics (http://www.reflexmagnetics.co.uk/), and SecureWave (http://www.securewave.com/ sanctuary_DC.jsp), have introduced products to manage USB/Firewire ports and the Plug-and-Play features of the desktop operating systems. These electronic control systems are integrated into the corporate security policies and may be coupled with polices to prohibit personal devices. These latter policies, however, seem to be associated with the more formal corporate environments. Ownership, for the purpose of this study, considers individually owned devices and extends the concept of ownership to an individual’s

exclusive control over a portable device, such as a laptop or cell phone provided for the individual. Additionally, the study does not consider activities to prevent data compromise through loss or mechanisms to recover misplaced portable digital devices, which can also compromise business data (Herold, 2005).

SMALL BUSINESS ENVIRONMENT Small businesses, however, face a very different environment. This study uses the UN Economic Commission for Europe (UNECE, 1996) definition, which defines small business as having less than 50 employees, revenue of less than EU 7 million, and is independently owned. These businesses are usually more personal and frequently operate without a dedicated IT staff. In this world, personal and company portable technology, such as cell phones, are often blended with one device serving both roles. Security experts recommend considering three dimensions when creating security policies: confidentiality (protecting private information), availability (allowing authorized access), and integrity (reliability of data). When conducting a Google search on security policies for digital devices using the search terms and variations of “policy for portable devices” it is interesting to note that colleges and universities, especially those with health care facilities, dominate the results. This may be attributed, not only to the more open academic environment, but also to universities having to face the issues because of a younger and more digitally well-informed population. Secondly, the focus on medical areas reflects the social practices of those entrusted with medical data, whose privacy must be protected in the United States under the HIPAA (1996) statutes. The Texas Workforce Commission provides the most comprehensive guidance for small business. Their Internet, E-mail and Computer Usage Policy includes a recent addition on the use of digital camera devices, including cell phones, and personally owned computers (Texas Workforce, 2005). It, however, does not include policies for USB storage devices or portable players. In the supporting discussion on employee workplace rights, the issues of portable players are considered. This, however, is more from attributing liability of possible hearing loss to workplace environmental conditions rather than from listening to too loud music.

USAGE PATTERNS The majority of the small businesses interviewed to date have employees who spend more of the day in the field than in an office location. The cell phone has become a critical item for all employees. No businesses have noted instances of abuse either by employees incurring unreasonable charges or management harassing the employees by calling at inappropriate times. These businesses have discovered that providing a cell phone and limiting or preventing the use of a personal cell phone has improved productivity. For one company, a cell phone provided to employees is a significant “perk” for the hourly field workers. Management has discovered that

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Emerging Trends and Challenges in IT Management keeping workers on the job towards the end of the day is much less fraught when the employee can call home. This has been a great advantage for employee moral and has increased productivity. Interestingly for the same company, lower level employees were issued a basic phone, while management had phones with cameras because of cost differences. This policy was formalized so that all job supervisors would have camera phones. As the work often entails installing custom furniture and fixtures, sending a photograph electronically allowed management at the home office to verify site conditions against the plans saving on a visit to resolve a discrepancy. In discovering other consequences of new technology, one company learned the pitfalls of eavesdropping facilitated by the technology. The original cell phones included a push-to-talk feature. This was changed to allow only handsets, because a client had overheard an inadvertent comment broadcast via the push-to-talk mode. In the medical practices, more restrictive policies were expected. However, many small medical practices still maintain most of their records on paper. For example, it is only within the last nine months that they have converted to an electronic patient scheduling system. This may reflect national practices of complex third party billing which discourages a centralized system. The recent change in the US government support for medications, however, is causing a reassessment of these practices. In these instances, the companies have discovered, counter to the recommendations of the larger corporate environment, which are to discourage use of employee owned devices, that defining and allowing technology is better than trying to prevent it. It has, however, required experimentation because the technology has changed the nature of the work. In neither case, have the owners instituted separate policies for the office staff governing either USB or MP3 devices. It is possible that the culture of the smaller company is such that these items have not become an issue.

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CONCLUSIONS The concern expressed by the larger enterprises regarding security that is not seen among these smaller businesses, may reflect the shift to knowledge work in large corporations. The smaller businesses investigated to date are more concerned with reliable employees and quality of work in the field. The proprietary company data is restricted to a much smaller circle than in a larger enterprise with the consequence of lower levels of concern for compromise.

REFERENCES Contu, R. (2004), How to Tackle the Threat from Portable Storage Devices Downloaded from: http://www.csoonline.com/analyst/ report2714.html Herold, R. (2005) Privacy Policies For Portable Devices, Security Pipeline, Sept 01, 2005. Downloaded from: http:// www.securitypipeline.com/handson/170102450 Locking down USB ports: Interview with Vladimir Chernavsky, CEO of Smartline, Network World, Sept. 27, 2005. Downloaded from: http://www.networkworld.com/research/2005/0926radio.html Rostern, J. (2005). Dangerous Devices The Internal Auditor. Oct. 2005. 62:5 p. 29-33 Texas Workforce Commission (2005) Internet, E-Mail, and Computer Usage Policy Downloaded from: http://www.twc.state.tx.us/ news/efte/internetpolicy.html United Nations Economic Commission for Europe. Definition Of SMEs In The European Union Downloaded from: http://www.unece.org/ indust/sme/def-eu.htm US Vs Wen Ho Lee, (1999), United States District Court For The District Of New Mexico. downloaded from: http://www.fas.org/irp/ops/ ci/docs/lee_indict.html

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1006 2006 IRMA International Conference

The Influence of Educational, Social, and Economic Factors on the International Digital Divide, as Measured by IT Usage and Expenditure James Pick & Rasool Azari School of Business, University of Redlands, 1200 E. Colton Avenue, Redlands, CA 92373, P 909-748-6252, F 909-335-5125 Rasool_azari, [email protected]

ABSTRACT The objective of this paper is to examine, for a sample of nations, the extent of influence of educational, social, and economic factors on five dependent variables: per capita prevalence of three technologies (pcs, internet host units, and mobile phones), ICT expenditure as percent of GDP, and ICT infrastructure quality. International data on 56 countries are drawn from the Global Information Technology Report (Dutta et al., 2002-2003) and the World Development Indicators 2003 (World Bank, 2003). Utilizing the unit of analysis of the nation-state, linear regression analyses are conducted to test the paper’s three research questions.

INTRODUCTION The rapidly increasing disparity in the utilization and expenditure of technology is apparent worldwide. This is commonly referred to as the “Digital Divide,” i.e. that society has major divisions in intensity of IT utilization and application. In a recent annual report on the global digital divide, the World Economic Forum indicated that 88 percent of all internet users are from industrialized countries that comprise only 15 percent of the world’s population. Brazil has the fastest worldwide rate of growth in computer and Internet usage, but only 13 percent of its population owns a computer and 5 percent has access to the Internet. According to the same report: “More than 80 percent of people in the world have never heard a dial tone, let alone sent an e-mail or downloaded information from the World Wide Web” (World Economic Forum, 2002). Despite much talk about the power of IT to transform the economic development process, relatively little research has been performed in a global context on how IT is being used in developing countries, what barriers exist to the diffusion and adoption of IT in different world regions and cultures, and what lessons can be learned to support leaders and policy makers in reducing or overcoming the international digital divide.

METHODOLOGY The framework for the study is based on the model developed by the World Economic Forum in collaboration with the Center for International Development (CID) at the Harvard University and published in the Global Information Technology Report (GITR, 2002-2003). Our research framework is depicted in Figure 1 below. The right side of this model, the usage of ICT and their sub-components is adopted from the Networked Readiness Index Framework of the GITR from Figure 1 above. Data for the Global Competitiveness Report (Dutta et al., 2003)

Figure 1. Framework for the socioeconomic factors Technology Usage Socioeconomic Factors

Individual/Business/Government

Technology Expenditure Individual/Business/Government

were downloadable from over 4,000 surveys in 82 countries that include well over 100 questions. We explore the association of several socioeconomic factors on some of the sub-components of this model used by GITR in 82 countries. Our unit of analysis is the nation-state and data are collected from GITR (2002-2003) and the World Development Indicators 2003 from the World Bank. The nation-state as a unit of analysis has the weakness of aggregating the many different levels of technology within a single nation-state. However, this is addressed by interpreting the effects as national ones, i.e. national factors result in national expenditures and usages. Another problem might be that macro units miss the variety of human situations of inequality and the question of the differing capabilities of people to overcome them (Sen, 1995). However, the intent of this paper is to measure, interpret, and assess the larger effects that influence nations as a whole, rather than focusing on individual diversity.

VARIABLES USED IN THIS STUDY Variables were chosen to support the framework in Figure 1 based on prior studies, including Sharma and Gupta (2003), Simon (2004), Florida (2002, 2005), and Azari and Pick (2004, 2005). Since the data sources had some missing data, this choice of variables reduced the size of the sample of nations with complete data to 56 for regression analysis. Dependent Variables • Personal computers per 1,000 people • Internet host users per 1,000 people • Mobile phones per 1,000 people • Information and communications technology expenditure per capita • Index of overall ICT infrastructure quality

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Emerging Trends and Challenges in IT Management Independent Variables • Gross National Produce (GNP) in $billions per capita • Foreign Direct Investment in $ millions per capita • Availability of scientists and engineers • Public spending on education (percent of GNP) • Primary pupil teacher ratio (pupils per teacher) • Secondary school enrollment (net enrollment ratio in percent) • Percentage of expenditure in education • Quality of math and science education • Quality of local IT training programs • Government prioritization of ICT • Percent of females in the labor force • Gini Index • Commercial energy use per capita

RESEARCH QUESTIONS 1.

2.

3.

What are the most important socioeconomic factors that influence average per capita national technology usage for personal computers, internet hosts, and mobile phones? What are the most important socioeconomic factors that influence average per capita national technology expenditure for information and communications technology? What are the most important socioeconomic factors that influence ICT infrastructure quality?

FINDINGS Stepwise regression analysis was applied for the five dependent variables. With GNP excluded, the most significant and positive correlate, for all dependent variables, is quality of math and science education. The second most significant correlate for PCs per capita, internet hosts per capita, and ICT spending portion of GNP is scientists and engineers in R&D per capita. A close third in significance is availability of scientists and engineers for internet hosts per capita, mobile phones per capita, and ICT infrastructure quality. Also primary pupils per teacher is inversely significant for mobile phones per capita. In summary, the associations of three variables are predominant: math/ science education quality, scientists and engineers in R&D, and availability of scientists and engineers. Training, education, and presence of these professionals appear to be essential for technology worldwide. There may be reverse directional effects which are not investigated here. The findings regarding scientists and engineers correspond to the results of the previous publications for U.S. counties (Azari and Pick, 2005). A difference is that the U.S. findings also demonstrated the importance of ethnic composition and in some cases support services. The findings on education are consistent with other research at the national levels (Warschauer, 2003; Zhu and Wang, 2005).

DISCUSSION The major results, when GNP is excluded, are that technology is stimulated by scientific and technical education, by scientific and engineering talent, and by scientists and engineers engaged in R&D. These will be discussed in terms of the national unit of analysis of this study. At the level of regional, local, or metropolitan units within nations, research has shown that scientific and technical education contributes to technology (Florida, 2002; Azari and Pick, 2004, 2005). These studies indicate that the positive effects of education are not limited to technical students, but apply to general college attainment and to broad scientific education. In other words, communities and metropolitan areas benefit by having an educated population with an abundance of scientists, engineers, and other technical professionals. The contribution to higher levels of technology per capita are from the capability of communities to conduct R&D, to fill scientific and technical jobs, and to attract in-migration of scientific talent. An example of such a community is the Silicon Valley near San Jose in California.

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In the current research, the quality of math and science education can influence nations in a somewhat analogous way. Nations foster creativity including in technology through forming educated segments of the population referred to by Florida (2005b) as the “creative class,” which he defines as employees in science, engineering, health care, business law, architecture and design, entertainment, and the arts. This class is estimated at 40 million in the U.S. and 125 million worldwide (Florida, 2005). Besides the U.S., nations with high percentages of “creative class” are Ireland, Belgium, Australia, Netherlands, New Zealand, Estonia, the U.K., Canada, Finland, and Iceland. These nations can compete better economically in technology and other creative industries. Analogous to the rationale for communities, nations with high quality of scientific education attract foreign students and talented immigrants who add to the level of technology (Florida, 2005). Florida carries this argument further, suggesting that governments and businesses can be proactive in seeking talented students and top-skilled immigrants, examples being Australia and Ireland. The results for availability of scientists and engineers and for scientists and engineers in R&D per capita also follow the above arguments for localities and regions. If there is a strong pool of scientific talent, then a nation’s industry and universities can be more creative and productive, leading to greater prevalence of technology and its infrastructure, and a stronger economy in general.

POLICY IMPLICATIONS The paper suggests policy that can be taken by the countries and their governments to foster effective use of technology and reduce the digital divide. Steps recommended for national governments to foster greater national levels of technology are to emphasize high quality of education at all levels and especially in math and science; upgrade skills; improve basic infrastructure to support educational outcomes; invest in poverty reduction, health, and infrastructure, which allows educational gains to be better realized; attract scientific talent both domestically and internationally; reduce the gender divide; and encourage societal openness and tolerance. Educational advance is especially crucial in developing nations, where educational investments directed towards technology have not always been successful (Warschauer, 2003). We reason that the presence of a scientifically educated population, with a creative science/engineering workforce performing more R&D contributes to higher levels of technology utilization and infrastructure. The first two points on national policies to improve educational access and infrastructures in the tertiary sector with a focus on digital literacy and creativity are especially important and are strongly supported by the paper’s findings. More developed nations have struggle with finding the budget and political support to broadly advance higher education. This becomes a question of national leadership in giving high priority to educational improvement programs and providing the necessary resources, expertise, and national educational leadership to succeed. In developing nations, the problems are more critical and difficult (James, 2004, 2005). When literacy itself is a national challenge such as in some African, Asian, and Latin American nations, digital literacy and creativity may not receive as much attention or funding. Those nations may be better to focus funding for digital literacy and creativity in certain regions and metropolitan areas, as a stimulus to the nation. The successes of the state of Kerala in India is an example. Another approach, recommended by Florida (2005) is to stimulate education is to form international consortia with the goal of advancing digital literacy worldwide.

REFERENCES Anonymous. 2004. “Building Bridges, Virtually,” UN Chronicle; Dec 2003-Feb 2004, 40(4); Research Library Core. Available at www.un.org/chronicle. Azari, R. and Pick, J.B.. (2004) Socio-economic Influence on Information Technology: The Case of California,” in Quigley, M. (ed.), Information Security and Ethics: Social and Organizational Issues, Idea Group Publishing, Hershey, PA, pp. 48-72.

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1008 2006 IRMA International Conference Azari, R. and Pick, J.B. (2005) Technology and Society: Socioeconomic Influences on Technological Sectors for United States Counties, International Journal of Information Management, 25, 1, 2537. Dutta, Soumitra, Bruno Lanvin, and Fiona Paua. 2003. Global Information Technology Report 2002-2003. Readiness for the Networked World, New York: Oxford University Press. Florida, Richard. 2002. The Rise of the Creative Class. New York: Basic Books. Florida, Richard. 2005. The Flight of the Creative Class: The New Global Competition for Talent. New York: HarperBusiness.

Sen, Amartya. 1995. Inequality Reexamined. Cambridge, Massachusetts: Harvard University Press. Warschauer, M. (2003) Dissecting the “Digital Divide”: A Case Study in Egypt, The Information Society 19:297-304. World Bank. 2003. The World Development Indicators. Washington, D.C. The World Bank. World Economic Forum. (2002) Annual Report of the Global Digital Divide Initiative, World Economic Forum, Geneva, Switzerland. Zhu, J.J.H. and Wang, Enhai (2005) Diffusion, Use, and Effect of the Internet in China, Communications of the ACM 48, 4, 49-53.

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Emerging Trends and Challenges in IT Management

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Virtual Project Risk April Reed & Linda Knight DePaul University, School of Computer Science, Telecommunications & Information Systems, 243 S. Wabash, Chicago, IL 60604, F: (312)362-6116, [email protected], [email protected]

ABSTRACT Virtual teams have evolved since the 1990’s and are becoming increasingly popular for many reasons, i.e. securing the right person for the project, outsourcing, offshoring and the resulting need to work with global resources, as well as avoidance of travel due to cost and security concerns. Are there significant and important differences between virtual teams and traditional teams that are critical to successful project completion? This paper will discuss a research in progress aimed at identifying differences in successful virtual and traditional teams.

BACKGROUND A virtual project is defined as a project where some or all of the team members are not co-located. These team members can be located a mile away, a state away or across an ocean. Powell et al define virtual teams, “Virtual teams are groups of geographically, organizationally and/or time dispersed workers brought together by information and telecommunication technologies to accomplish one or more organizational tasks”.(Powell et al., 2004) Most projects run into problems at some time before their completion. Before a problem actually occurs on a project, there is the risk of it occurring. If potential project risks are known before they occur, it is possible that pre-planning, i.e. a risk management plan, can prevent the risk or minimize it once it has occurred. Considerable literature has been written on the benefits of risk management. Boehm, an early proponent of risk management, suggested focusing on the top critical risks of a project to improve project success.(Boehm, 1991) The Standish Group, who produce the annual CHAOS report on information technology project success has reported very little improvement in the project success rate over the past several years.(Standish Group International, 2001) The purpose of this research is to identify any differences in critical risk factors between virtual and traditional software projects. This study is important to determining the critical risk factors specific to virtual projects so that risk management for those projects can be appropriately focused. If a set of the most critical risks, specific to virtual projects, can be identified, they can lead to a customized risk management plan which should improve the chances of having a successful project.

RESEARCH METHODOLOGY AND RESULTS Multiple research methodologies will be used to conduct this study. This paper will discuss the first part of a larger study. First, a survey tool was developed to identify risk factors for both virtual and traditional projects. The tool was submitted and approved by the institution’s human subjects review board. Next, the survey tool was used in face-toface interviews with a pilot group of information technology project management practitioners. The practitioners were encouraged to discuss hurdles encountered on two recent specific projects, a virtual project and a traditional project. The hurdles identified in the interviews were used to help develop a list of project risk factors. During the interview portion of this study, many risk factors were identified and charted. The following is a discussion of three of those risk factors: 1) communication, 2) management of remote resources and 3) trust.

Communication Communication is important to virtual projects; it holds project teams together. There are many aspects of communication, such as the vehicle or tools used to communicate, the methods used to communicate, i.e. written or verbal, and the importance of non-verbal cues. One interviewee spoke about the importance of communication for a team that was located at two separate sites. Due to previous circumstances, there was an “us versus them” attitude between the two sites. Face-to-face communication was deemed important in this situation. The interviewee stated: “Once you put a face to a voice, you start to care about each other.” Another interviewee commented on virtual team communication, saying “It is more difficult to communicate over the phone than walking over to the persons’ desk to talk.” Technology and communication can come together to facilitate virtual team communication. One of the differences between virtual teams and traditional teams in the area of communication are the tools. On a virtual team, the tools may be the only way to share information vital to the project, i.e. requirements documents, coding specifications, documented processes and procedures. These are not just quick, back and forth messages; they are working documents needed to complete the project. Teams working across organizational, departmental or geographical boundaries often have problems exchanging information electronically because they reside on different LANs, they do not have security access to the necessary directories or there is no common storage location. One interviewee indicated these types of issues can impact projects and result in loss of time. An interviewee also pointed out the added importance of carefully planning and organizing communication particularly in virtual teams. Obviously, it is very important for virtual teams to be supported by the necessary tools to communicate effectively. Virtual teams have the potential to be exceptional; but, they will need support from the companies that want to use them. Kirkman and Mathieu believe the resources important to virtual team success are: software tools and accompanying hardware, training and development in virtual team processes and most importantly, giving the teams the time they need to learn to work together in new ways.(Kirkman & Mathieu, 2005) Management of Remote Resources The difference in management style needed for remote resources was identified in the interviews as a factor that initially slowed down the project but improved over the duration of the project. One interviewee indicated managing remote resources was definitely different from managing on-site resources. The degree of importance this risk factor carries is probably based on an individual managers’ comfort level with the concept of remote work. Unfortunately, managers are generally not being trained on how to manage virtual teamwork. One interviewee stated, “It takes longer (to do the project) when learning how to manage remote resources while doing it.” A solution to improving this factor would be to provide training to managers on working with remote resources before they are assigned a virtual project team. The management skill sets for virtual teamwork may develop eventually over time; however, training could speed up the learning curve.

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1010 2006 IRMA International Conference Trust Walther et al define trust as “… an expectancy held by an individual or a group that the word, promise, or verbal or written statement of another individual or group can be relied upon”.(Walther et al., 2005) Trust becomes an issue in virtual projects particularly because it’s difficult to believe what you can’t see. One project manager who was interviewed said “I couldn’t see if the people were working”. This bothered him, so he developed ways to determine who was working and who wasn’t. In this particular project, there were other negative things that were taking place on the project, so it is possible this impacted the ability to trust. It may be the case, that trust is improved by face-to-face communication. Since virtual teams have little or no face-to-face communication, trust could be harder to repair. Powell, et al listed trust as one of the eight major issues that early virtual team work identified.(Powell et al., 2004) Focusing on team building may improve trust on virtual teams. However, the real problem there will be how to engage in team building activities with remote resources.

OBSERVATIONS FROM THE INTERVIEWS Conducting the first part of the study via face-to-face interviews resulted in rich data that is not possible to obtain through paper surveys. The interviewees often gave detailed information about problems that occurred and how they were resolved. All interviewees had managed virtual projects, making it likely that virtual projects are becoming a more common form of project. An unexpected outcome of the interviews was the discovery that some project managers and team members had not participated in a traditional project in a number of years. Perhaps this is an indication that traditional projects are decreasing. Further research is needed to determine which type of project is more common today, virtual or traditional. A recent comment on virtual teams supports suspicions of their increasing role; “We believe that as we move into the future, various driving forces …..will lead companies to use virtual teams as a norm and discover that the virtual experience may be preferable to meeting face-to face.”(Jones et al., 2005) An observation from several of the interviews is that many companies seem to have evolved into using virtual teams without much thought, because it is cost effective, i.e. lower travel costs, lower office space overhead, less long-term payroll commitment. However, none of the

managers interviewed had been trained to work in this new virtual environment. In fact, there seemed to be very little formal support by these companies of the virtual team process.

CONCLUSION In summary, it is possible for each of the risks discussed; communication, managing remote resources and trust to occur on traditional projects although each of these was only discussed in connection with virtual projects. The following two assumptions about being made about these risks, 1) these risk factors are more likely to happen on virtual projects due to the distance attribute and 2) these risks are more critical on virtual projects. Determining if these two assumptions have any validity is one of the objectives of the larger study. In other words, what still seems to be important is determining which risks are more likely to occur on virtual teams and which are critical, i.e. having the greatest impact on a virtual project. The next steps in this study are to revise the survey tool based on feedback from the pilot group interviews. Then, to conduct a focus group of a different set of information technology practitioners to ensure the list of risk factors is conclusive. Finally, an online survey, based on the survey tool, will be sent to a larger population of practitioners.

REFERENCES Boehm, B. W. (1991). Software risk management: Principles and practices. IEEE Software(January 1991), 32-41. Jones, R., Oyung, R., & Pace, L. (2005). Working virtually: Challenges of virtual teams: Idea Group Inc. Kirkman, B., & Mathieu, J. (2005). The dimensions and antecedents of team virtuality. Journal of Management, 31(5), 700-718. Powell, A., Piccoli, G., & Ives, B. (2004). Virtual teams: A review of current literature and directions for future research. The DATA BASE for Advances in Information Systems, 35(1), 6-33. Standish Group International, I. (2001). Extreme chaos. Walther, J. B., Bunz, U., & Bazarova, N. (2005, 2005). The rules of virtual groups. Paper presented at the Proceedings of the 38th Hawaii International Conference on System Sciences 2005, Hawaii.

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Emerging Trends and Challenges in IT Management

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The Impact of Information Technology on Productive Efficiency: An International Comparison Winston T. Lin & Paige P. Tsai Dept of Management Science & Systems, School of Management, The State University of New York at Buffalo, Buffalo, NY 14260, P 716-645-3257, F 716-645-6117, {mgtfewtl, ptsai3}@buffalo.edu

INTRODUCTION AND A LITERATURE REVIEW The economic measures of IT benefits in organizational performance frequently used include profitability, productivity, costs, quality, operative efficiency, consumer surplus, and Tobin’s q (cf. [22]). Quite a few research results were able to confirm the contribution of IT in organizations. However, some of them derived only weak or even inconclusive results. For example, the so-called productivity paradox of IT [3] has confused both managers and researchers during the 1980s [14] and is claimed to have disappeared in early 1990s. The productivity paradox of IT suggests that the huge amount of investments in IT has been found uncorrelated with significant organizational performance improvement in aggregate output productivity. Typical explanations to the productivity paradox include the following: (i) massive investment in IT started only from recent years [26]; (ii) because of the time-lagged effects of IT, it takes time to realize the benefit of IT [11]; (iii) output mismeasurement [5, 33]; (iv) input mismeasurement [8]; (v) overinvestment in IT [26]; and (vi) lack of organizational changes accompanying the IT investment [6]. A performance measure called productive (technical) efficiency, which has been rarely used in the past and was introduced by Lin and Shao [20] to evaluate the business value of IT at the firm level in the MIS literature for the first time, is becoming more frequently applied to the measurement of the impact of IT investments in production processes. The use of productive efficiency is motivated by the following reasons: (i) productive efficiency exerts a positive effect on productivity growth [7]; (ii) productive efficiency can be applied to all types of organization, unlike some financial measurements that can only be applied to financial organizations; (iii) productive efficiency is closely related to productivity and effectiveness; and (iv) if combined with other measures, a more complete analysis of IT contribution can be provided. There has been too much emphasis on U.S. firm and lack of crosscountry studies [24] as far as the business value of IT is concerned; and, as a consequence, knowledge accumulation concerning macro-characteristics and IT value at the country level has been inhibited. This suggests that research in IT business value at the macro-level is needed. Indeed. research on IT value at the firm level appears to be abundant as reflected by a long list [1, 2, 4, 9, 12, 18, 21, 23, 26, 28, 30, 31, 33, 35, among many others]. On the contrary, the studies devoted to IT value at the country level are countable. First, our attention is paid to the Kraemer and Dedrick’s study [16] which, using correlation analyses to examine the payoffs from IT investments on productivity and economic growth in twelve Asia-Pacific countries over the period 1984 to 1990, has collectively concluded that IT investment has paid off in productivity improvement and challenged the so-called productivity paradox, where by collectively we mean that it is not possible to determine whether the paradox does or does not exist in an individual country within its methodological framework. Second, the cross-country research of Dewan and Kraemer [10] has again been concerned with the productivity paradox for seventeen developed countries over the period 1965 to 1994. Its analysis suggests that,

collectively, the developed countries are receiving a positive and significant return on their IT investments, implying the absence of the paradox. Third, Dewan and Kraemer [11] have examined the relationship between IT and productivity by estimating Cobb-Douglas regression models, based on a country-level panel data set from thirty-six countries (of which twenty-two are considered developed and fourteen developing) during the 1985-1993 period, without replying on any performance measure. Collectively, the sign and significance of the estimated coefficients of the IT input have led them to conclude that the productivity paradox disappears from the group of developed countries but does exist in the developing countries. Fourth, Lin and Chen [19] have provided an comparative analysis of the productive efficiencies of major industries in Taiwan and China, using a two-equation model. They have concluded that the industries in Taiwan perform more productively efficient than their counterparts in China. More interestingly, they are able to identify the contributors of productive (in)efficiency from the financial, educational, economic, political, social, and geographic differences between Taiwan and China. Fifth, by Shu and Lee [32], productivity and three types of efficiencies (i.e., productive, allocative, and scale) of IT industries have been analyzed for fourteen OECD countries, within the framework of the Cobb-Douglas function estimated by a full information maximum likelihood procedure. It has concluded that individual countries’ productive efficiencies are low, with the U.S. having the best productive efficiency (0.6268), followed by Japan (0.6229), and Norway having the worst productive efficiency (0.4142). Since it has used the same performance measure as used in the present study, we are particularly interested in its estimated results of the productive efficiency. We will provide a comparison of this study’s IT-efficiency with Shu-Lee’s ITefficiency and Jorgenson’s IT-Productivity in the G7 countries [15]. Sixth, [13] represents a good example analyzing the growth of productivity and productive efficiency in OECD industrial activities. But, it does not consider the role of IT investments and, therefore, is of little interest to us. Seventh and final, Lee [17] have undertaken an investigation on twenty countries (including sixteen developed/newly industrialized and four developing economies FROM 1980-2000) in a Cobb-Douglas production regression. Results show that IT contributes to economic growth in many developed and newly industrialized economies, but not in developing countries. This research joins the short list of relatively few studies to address the important issue of accessing the business value of IT at the country level. Thus, the objective of this paper is two-fold: to assess the impact of IT on the productive efficiency between developed and developing countries collectively and to compare the productive efficiencies with and without IT of individual countries across different stochastic production frontiers (the Cobb-Douglas function, Box-Cox and Box-Tidwell transformations, and translog functions).

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1012 2006 IRMA International Conference Complete results and discussions will be presented in the 2006 IRMA Conference. REFERENCES [1]

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P. Alpar and M. Kim, A microeconomic approach to the measurement of information technology value, Journal of Management Information Systems, 7, 2 1990, pp. 55-69. A. S. Bharadwaj, S. G. Bharadwaj and B. R. Konsynski, Information technology effects on firm performance as measured by Tobin’s q, Management Science, 45 1999, pp. 1008-1024. M. N. Baily and R. J. Gordon, The productivity slowdown, measurement issues and the explosion of computer power, in W.C. Brainard and G.L. Perry (eds.), Brookings Papers on Economic Activity, Washington, DC:The Brookings Institute 1998, pp. 347-431. E. Brynjofsson and L. M. Hitt, Beyond computation: information technology, organizational transformation and business performance, Journal of Economic Perspectives, 14 2000, pp. 23-48. E. Brynjofsson, Information technology and the productivity paradox: review and assessment, Communication of the ACM, 35 1993, pp. 66-77. E. Brynjofsson and L. M. Hitt, Paradox lost? firm-level evidence on the returns to information systems spending, Management Science, 42 1996, pp. 541-558. R. E. Caves and D. R. Barton, Efficiency in U.S. manufacturing industries, Cambridge, MA: The MIT Press 1990. S. Devaraj and R. Kohli, Performance impacts of information technology: is actual usage the missing Link? Management Science, 49 2003, pp. 273-289. S. Dewan and C. Min, The substitution of information technology for other factors of production: a firm-level analysis, Management Science, 43 1997, pp. 1660-1675. S. Dewan and K. L. Kraemer, International dimensions of the productivity paradox, Communications of the ACM, 41 1998, pp. 56-62. S. Dewan and K. L. Kraemer, Information technology and productivity: evidence from country-level data, Management Science, 46 2000, pp. 548-562. B. L. Dos Santos, K. G. Peffers and D. C. Mauer, The impact of information technology investment announcements on the market value of the firm, Information Systems Research, 4 1993, pp. 1-23. F. Fecher and S. Perelman, Productivity Growth and Technical Efficiency in OECD Industrial Activities, in R.E. Caves (ed.), Industrial Efficiency in Six Nations, Cambridge, MA, The MIT Press 1992, pp. 459-488. L. M. Hitt and E. Brynjolfsson, Productivity, business profitability, and consumer surplus: three different measurements of information technology value, MIS Quarterly, 20 1996, pp. 121-142. D. W. Jorgenson, Information technology and the G7 economies, World Economics, 4 2003, pp. 139-170. K. L. Kraemer and J. Dedrick, Payoffs from Investment in Information Technology: Lessons from the Asia-Pacific Region, World Development, 22 1994, pp. 1921-1931. S. T. Lee, R. Gholami and T. Y. Tong, Time series analysis in the assessment of ICT impact at the aggregate level - lessons and implications for the new economy, Information & Management, 42 2005, pp. 1009-1022. F. Lichtenberg, The output contributions of computer equipment and personnel: a firm level analysis, Economics of Innovation and New Technology, 3 1995, pp. 201-217.

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W. T. Lin and Y. H. Chen, Productive efficiency of major industries from Taiwan and China, The State University of New York at Buffalo and National Sun Yat-Sen University 2002. W. T. Lin and B. B. M. Shao, Relative sizes of information technology investments and productive efficiency: their linkage and empirical evidence, Journal of the Association for Information Systems, 1(7) 2000, pp. 1-35. W. T. Lin and B. B. M. Shao, Assessing input effect on productive efficiency in production systems: the value of informtion technology capital, International Journal of Production Research in Press, pp. 45 pages. W. T. Lin and B. B. M. Shao, The business value of information technology and inputs substitution: the productivity paradox revisited, Decision Support Systems in Press, pp. 33 pages. G. W. Loveman, An assessment of the productivity impact of information technologies, in T. J. Allen and M. S. Scott Morton (eds.), Information Technology and Corporation of the 1990s: Research Studies, Cambridge, MA: The MIT Press 1994, pp. 84110. N. Melville, K. Kraemer and V. Gurbaxani, Review: information technology and organizational performance: an integrative model of IT business value, MIS Quarterly, 28 2004, pp. 283322. C. J. Morrison, Assessing the productivity of information technology equipment in U.S. manufacturing industries, The Review of Economics and Statistics, 79 1997, pp. 471-481. S. D. Oliner and D. E. Sichel, The resurgence of growth in the late 1990s: is information technology the story? The Journal of Economic Perspectives, 14 2000, pp. 3-22. K. M. Osei-Bryson and M. Ko, Exploring the relationship between information technology investments and firm performance using regression splines analysis, Information & Management, 42 2004, pp. 1-13. P. Schmidt, Frontier production functions, Econometric Reviews, 4 1986, pp. 289-328. B. B. M. Shao and W. T. Lin, Examining the determinants of productive efficiency with IT as a production factor, Journal of Computer Information Systems, 41 2000, pp. 25-30. B. B. M. Shao and W. T. Lin, Measuring the value of information technology in technical efficiency with stochastic production frontiers, Information and Software Technology, 43 2001, pp. 447-456. B. B. M. Shao and W. T. Lin, Technical efficiency analysis of information technology investments: a two-stage empirical investigation, Information & Management, 39 2002, pp. 391401. W. S. Shu and S. Lee, Beyond productivity - productivity and the three types of efficiencies of information technology industries, Information and Software Technology, 45 2003, pp. 513-524. W. Shu and P. A. Strassmann, Does information technology provide banks with profit? Information & Management, 42 2005, pp. 718-787. D. Siegel and C. J. Morrison, External capital factors and increasing returns in U.S. manufacturing, The Review of Economics and Statistics, 79 1997, pp. 647-654. K. Y. Tam, The impact of information technology investments on firm performance and evaluation: evidence from newly industrialized economies, Information Systems Research, 9 1998, pp. 85-98. D. M. Waldman, A stationary point for the stochastic frontier likelihood, Journal of Econometrics, 19 1982, pp. 275-279.

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Emerging Trends and Challenges in IT Management

1013

E-Business Innovation and Firm Performance Namchul Shin, IS Department, Ivan G. Seidenberg School of CSIS, Pace University, 163 William Street, Room 223, New York, NY 10038, Tel: 212-346-1067, Fax: 212-346-1863, [email protected]

ABSTRACT

PREVIOUS RESEARCH ON E-BUSINESS VALUE

Companies develop e-business initiatives to improve communications with customers and suppliers. However, one of the challenges for information systems managers is to determine whether such investment generates any value with respect to firm performance. By extending previous research done by Shin (2004), this research empirically examines the relationship between e-business innovation and firm performance. It employs the Information Week’s annual data set on innovative users of IT for two years: 2000 and 2001. The measure of e-business innovation is constructed by combining the categories of ebusiness strategy and customer knowledge available from the data set. This study attempts to show how firms can improve their performance with e-business innovation by providing empirical evidence for the economic payoffs generated from e-business innovation.

Previous IS research has used the resource-based view (RBV) of the firm to analyze IT business value and explain the leverage effect of organizational resources on IT investment (Clemons and Row 1991; Bharadwaj 2000). The theory posits that firms create value by combining heterogeneous resources that are economically valuable, rare, costly to imitate, or not substitutable (Barney 1991). Using the RBV as a theoretical basis, Zhu and Kraemer (2005) examine the value created by actual e-business use. They argue that IT-enhanced capabilities that integrate various business resources are tailored to a firm’s strategic context and cannot be easily copied by other firms. Thus, such IT capabilities can deliver the potential to create business value. Focusing on the actual way e-business is used, not simply on its adoption, Zhu and Kraemer (2005) show that actual e-business use and its capabilities contribute to performance improvement in companies in the retail industry. In their earlier study (2002), Zhu and Kraemer also demonstrated a significant relationship between e-commerce capability and firm performance measured by inventory turnover and cost of goods sold (COGS).

INTRODUCTION E-business initiatives are developed to improve communications with customers and suppliers. Companies invest in e-business technologies for customer relationship management (CRM) and supply chain management (SCM) in order to facilitate information sharing, transactions, customer service, and inventory management. However, one of the challenges for information systems (IS) managers is to determine whether such investment generates any value with respect to firm performance (Zhu 2004). While the value created by e-business investment has been an issue in both academic and business worlds, there has been little research examining e-business value empirically. Previous research on information technology (IT) value generally emphasizes the organizational changes in business processes and strategies coupled with IT investment (Clemons and Row 1991; Hitt and Brynjolfsson 1996; Malone 2001; Rangan and Adner 2001). For example, a company can create value by using IT to streamline its business processes and transform the way it does business. Likewise, IT can deliver much benefit by leveraging a firm’s current strategic positioning or by fostering new strategic opportunities. By applying the same reasoning to the creation of e-business value, this research empirically examines the relationship between e-business innovation and firm performance. The study employs the Information Week’s annual data set on innovative users of IT for two years: 2000 and 2001. The data set includes four categories of IT innovations for each firm based on the early adoption and creative use of technologies and business practices, which indicates the quality of IT innovations, not the quantity of IT investments. The four IT innovation categories are technology strategy, e-business strategy, business practices, and customer knowledge. The measure of e-business innovation is constructed by combining the e-business strategy and customer knowledge categories. Applying the definition of IT innovation provided by Information Week, e-business innovation refers to the early adoption and creative use of e-business and customer management technologies and practices (for example, e-marketplaces, enterprise portals, extranets, CRM, and SCM).

Using the publicly available Information Week 500 data set for the two years from 1999 to 2000, Shin (2004) empirically examined the contribution of e-business initiatives to firm performance by constructing a measure of e-business initiatives by combining e-business and CRM innovations. His findings showed that the contribution of e-business initiatives is significant for gross margin, revenue per employee, and return on equity (ROE). The present research extends Shin’s study (2004) by employing a more recent data set and a different methodology that minimizes the potential influence of a firm’s prior performance.

ECONOMETRIC APPROACH Data Sources and Variable Construction The study uses two data sources: the Information Week 500 data set on innovative users of IT for 2000 and 2001 and the Compustat database. The IT innovation data were collected annually through a survey of senior IT executives on their organizational priorities and spending plans. Information Week rated various categories of IT innovations for each firm by the quality of IT innovations (how companies used IT in their organizations), not by the size of IT spending (how much companies spent on IT). The data set for 2000 and 2001 includes four IT innovation categories, scored at three levels (gold, silver, and bronze) for each firm based on its early adoption and creative use of technologies and business practices. The four IT innovation categories are technology strategy, e-business strategy, business practices, and customer knowledge. The measure of e-business innovation is constructed by combining the categories of e-business strategy and customer knowledge. The following process is used to construct the e-business innovation measure: The numbers, 3, 2, and 1 are assigned to gold, silver, and bronze respectively. Then an e-business innovation index is created by adding the numeric

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1014 2006 IRMA International Conference values of both e-business strategy and customer knowledge. This procedure transforms the nominal variables of the two innovation categories into a continuous composite measure. This helps to alleviate potential statistical issues associated with using a number of nominal variables as independent variables in the regression models (Zhu and Kraemer 2002). Data items such as sales, COGS, return on asset (ROA), and ROE, and the number of employees are also obtained from the Compustat database for the same firms included in the Information Week 500 data set. Multiple performance ratios such as Tobin’s q, gross margin, revenue per employee, ROA, ROE, and the ratio of COGS to sales (a cost measure) are employed as measures of firm performance. Validity of the IT Innovation Variables The Information Week 500 data set has been partially validated by Shin (2004). Observing the weaknesses of using the qualitative (perceptual) IT innovation variables, he shows their nomological validity. When the predicted relationship specified by theory is found to be significant, despite variations in measurement, then the instrument may be considered as nomologically valid. Since the hypotheses developed allow him to examine the predicted relationships, the discovery of positive and significant relationships demonstrate the nomological validity of the IT innovation variables employed in his study. He also provides qualitative evidence of IT innovations by using case examples to corroborate the validity of the constructs. Shin (2004) further states that although the survey instrument might lack academic rigor, it is probably relevant practically since the editing team of Information Week 500 has had experience in designing the instrument and collecting the data annually for over a decade. Methodology To analyze the relationship between e-business innovation and firm performance, an analysis of the combined data set for two years is performed by using the two-stage least-squares (TSLS) regression, which uses one-year lagged e-business innovation as an instrument variable. This method is employed to minimize the potential bias caused by the simultaneity problem. Possible lag effects will be also examined. Even though the performance ratio variables and qualitative e-business innovation variable avoid the possible problem of heteroscedasticity, the total number of employees is used to control for differences in firm size. In order to control for industry- and year-specific effects, dummy variables for each industry categorized by the North American Industry Classification System (NAICS) code and for each year are included. The Model The model measures the relationship between e-business innovation and firm performance while controlling for firm size, industry and year. V it = β 0 + β1EIit + β 2EMPit + β 3INDUSTRYit + β 4YEARit + ε EIit stands for e-business innovation. EMP it denotes the total number of employees. V it represents firm performance measures that will be replaced in turn by each of the six performance variables: Tobin’s q,

gross margin, revenue per employee, ROA, ROE, and the ratio of COGS to sales. INDUSTRYit and YEARit denote dummy variables for industry and year, which control for differences in industry characteristics and market trends respectively. is the residual term with zero mean, which captures the net effect of all unspecified factors.

EXPECTED CONTRIBUTIONS This study empirically analyzes the contribution of e-business innovation to firm performance. E-business innovation is measured by a combination of the IT innovation categories of e-business strategy and customer knowledge, which indicates the early adoption and creative use of e-business and customer management technologies and practices. This study attempts to demonstrate how firms can improve their performance with e-business innovation by providing empirical evidence for the economic payoffs generated from e-business innovation. By extending the previous research done by Shin (2004), this study corroborates the importance of the complementarity of e-business technologies and innovative e-business practices, a subject that has received attention in recent e-business value research.

REFERENCES Barney, J.B. “Firm Resources and Sustained Competitive Advantage,” Journal of Management, vol. 17, no. 1, 1991, pp. 99-120. Bharadwaj, A.S. “A Resource-Based Perspective on Information Technology Capability and Firm Performance: An Empirical Investigation,” MIS Quarterly, vol. 24, no. 1, March 2000, pp.169196. Clemons, E. K. and Row, M.C. “Sustaining IT Advantage: The Role of Structural Differences,” MIS Quarterly, vol. 15, no. 3, 1991, pp. 275-292. Hitt, L. M. and Brynjolfsson, E. “Productivity, Business Profitability, and Consumer Surplus: Three Different Measures of Information Technology Value,” MIS Quarterly, vol. 20, no. 2, 1996, pp. 121-142. Malone, T.W. “The Future of E-Business,” Sloan Management Review, vol. 43, no. 1, Fall 2001, p. 104. Rangan, S. and Adner, R. “Profits and the Internet: Seven Misconceptions,” Sloan Management Review, vol. 42, no. 4, Summer 2001, pp. 44-53. Shin, N. “An Empirical Investigation of the Economic Payoffs of EBusiness and CRM innovations,” International Journal of Electronic Business, vol. 2, no. 4, 2004, pp. 351-365. Zhu, K. “The Complementarity of Information Technology Infrastructure and E-Commerce Capability: A Resource-Based Assessment of Their Business Value,” Journal of Management Information Systems, vol. 21, no. 1, Summer 2004, pp. 167-202. Zhu, K. and Kraemer, K.L. “e-Commerce Metrics for Net-Enhanced Organizations: Assessing the Value of e-Commerce to Firm Performance in the Manufacturing Sector,” Information Systems Research, vol. 13, no. 3, September 2002, pp. 275-295. Zhu, K and Kraemer, K.L. “Post-Adoption Variations in Usage and Value of E-business by Organizations: Cross-Country Evidence from the Retail Industry,” Information Systems Research, vol. 16, no. 1, March 2005, pp. 61-84.

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Emerging Trends and Challenges in IT Management

1015

A Prototype Decision Support System for ERP Evaluation in Small and Medium Enterprises Leopoldo E. Colmenares G., Universidad Simón Bolívar, Departamento de Tocnologíca de Servicios, Valle de Sartenejas, Edif. Ciencias Básicas 2, Caracas 1080-A. Venezuela, [email protected]

ABSTRACT This paper presents the work in progress regarding a research project scheduled to be concluded during the latter part of 2006. The purpose of the research is to develop a Decision Support System - which use a model based on the Analytic Hierarchy Process- what will assist managers from Small and Medium Enterprises of Venezuela, in the evaluation process of a ERP system to their organizations.

1) INTRODUCTION Confronted with intensifying competition, growing markets and increasingly selective customers, Small and Medium Enterprises (SMEs) are constantly in search of ways to achieve better business performance and secure competitive advantage trough effective employment and management of their resources. To improve business performance, organizations need an efficient planning and control systems that synchronizes planning of all processes across the enterprise. An enterprise resource planning (ERP) system is an integrated enterprise computing system to automate the flow of material, information and financial resources among all functions within an enterprise on a common database. Because the virtual saturation of the ERP market, vendors have recently moved their attention towards SMEs, by offering simplified and cheaper solutions (Tagliavini et al, 2002) such as compact packages and ERP outsourcing or the application service provision (ASP) (Shakir and Hossain, 2002) In spite of the benefits potentially offered by ERP systems (Wei and Wang, 2004) experiences on the field show that SMEs often fail in recognizing the economic and organizational impacts related to its use (Tagliavini et al, 2002); as a consequence, the adequate evaluation and selection of an ERP system become a critical decision that should be supported by a structured approach. Moreover Bernroider and Koch (2002) state that “considering ERP software selection with its complex and far-reaching implications poor decision making by SMEs can result in disastrous situations” This paper proposes a prototype Decision Support System (DSS) to ERP evaluation in SMEs. The DSS uses a model based on the Analytic Hierarchy Process (AHP) method to multicriteria decision making. The aim of the research is to assist to SMEs managers from Venezuela in the ERP evaluation process.

2) LITERATURE REVIEW A number of methods have been proposed to help organizations make decision in ERP system or other information system (IS) selection, Winter and Leist (1998) developed a cost-based model model of information systems optimization. Sistach and Pastor (2000) propose a method named SHERPA for the evaluation of an ERP system in SMEs. Lee and King (2000) combined the Analytic Network Process and 0–1 goal-programming model to select an IS project. Stefanou (2001) provides a general framework for the ex-ante evaluation of ERP software. Shakir and Hossain (2002) maps six models of decision making

for the selection and implementattion of ERP systems. Wei and Wang (2004) propose a model for selecting an ERP system using twodimensional analysis and fuzzy set theory. However, the applicability of these methods is often weakened by sophisticated mathematic models or limited attributes to carry out in a real-world ERP system selection decision, especially when some attributes are not readily quantiable, as well as not too easy for SMEs managers to understand. On the other hand most of above-mentioned methods were developed to be used for large companies rather than SMEs in developing countries. The Analytic Hierarchy Process (AHP) is a highly flexible decision methodology that can be applied in a wide variety of situations. It is typically used in decision situations which involve selecting one decision alternatives from several candidate decision alternatives on the basis of multiple decision. The AHP utilization in the ERP evaluation task has been discussed in various studies. For example, Teltumbde (2000) proposed a framework based on the Nominal Group Technique and AHP to select an ERP system. Alarcon (2004) proposes a model based on AHP to ERP selection in manufacturing large companies in Venezuela and, lastly Wei and Wang (2004) have developed a ERP system selection framework using the AHP method. This framework seeks to align the ERP evaluation process with the competitive strategies and goals of companies. However, as stated previously, these methods are suitable just for large companies and not adapted for ERP evaluation in SMEs. This study presents a prototype DSS for ERP evaluation in SMEs, based on the AHP framework to synthesize decision makers’ tangible and intangible measures, inherent in ERP system selection task and facilitates the group decision-making process. The criteria used by the AHP model is based on previous research of Colmenares (2002) which specifies the criteria should be used to software evaluation in SMEs. Furthermore the AHP method have been modified from the usual AHP approach in that a rating scale will be assigned to each subcriteria related to every alternative, instead of assessing direct pairwise comparisions among the alternatives, following the Liberatore’s (1987) proposal.

3) THE AHP MODEL FOR ERP EVALUATION The AHP method, introduced by Saaty (1995), directs how to determine the priority of a set of alternatives and the relative importance of attributes in a multiple criteria decision-making problem. The AHP modeling process involves four phases, namely, structuring the decision problem, measurement and data collection, determination of normalized weights and synthesis-finding solution to the problem. We structured an AHP base hierarchy for ERP evaluation that could be applied by any SME facing the ERP system selection problem. 3.1) Structuring the Decision Problem This phase involves formulating an appropriate hierarchy of the AHP model consisting of the goal, criteria and subcriteria, and the alternatives. The goal of SMEs is to select the most suitable ERP system. This

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1016 2006 IRMA International Conference Figure 2. DSS architecture

Figure 1. AHP hierarchy

Level 1: S elec t mos t s uitable ERP s y s tem

Goal Level 2:

V endor

Negotiations of pay ment

S upport Tec hnic al Staf f

Func tional Requirements

Grac e Period

Quantity c lients

Pay ments Plan Terms of Pay ment

Func tional Staf f Trainning

Level 3:

Tec h/Gral Requirements

Financ ial Produc tion Human Res ourc es Logis tic

Ev alu ation M o del

D atab ase

Factors

S oftw are

Doc umentation

Operating s y s tem

Quality manuals

Hardw are

Glos s ary

Cos ts

Lic ens e

Sourc e c ode

Doc . in S panis h

Criteria

U ser In terface

GUI Clear S c reens

Level 4:

Hardw are

Rollbac k

Subcriteria

Interf ac es

Error Mes s ages

Roy alties Fee

Online help

DBMS

Eas e of Us e

D S S fo r ER P Evaluation

Interf ac es

D ecisio n M akers

Level 5: Rating Scale

Outs tanding (O)

Good (G)

A v erage (A )

Fair (F)

Poor (P)

Figure 3. Evaluation model S y s tem A

S y s tem B

S y s tem C

Level 6: Alternatives

goal is placed on the first level of the hierarchy as shown in figure 1. This is divided into main factors, namely software and vendor (Colmenares, 2002), which form the second level of the hierarchy. The third level of the hierarchy occupies the criteria defining the factors of software and vendor of the second level. There are two criteria related to vendor, namely support and negotiations of payment. On the other hand, the criteria associated with software are functionals requirements, technical and generals requirements, documentation, costs, and ease of use (Colmenares, 2002) The fourth level consists of the subcriteria, and is grouped with respect to the seven criteria occupying the third level as shown in Fig. 1 (Colmenares, 2002) The factors, criteria and subcriteria used in these three levels of the AHP hierarchy can be assessed using the basic AHP approach of pairwise comparisons of elements in each level with respect to every parent element located one level above. A set of global priority weights can then be determined for each of the subcriteria by multiplying local weights of the subcriteria with weights of all the parent nodes above it. The fourth level of the hierarchy contains the rating scale. This level is different from the usual AHP approach in that a rating scale will be assigned to each subcriteria related to every alternative, instead of assessing pairwise comparisons among the alternatives in the usual fashion. The use of a rating scale instead of direct pairwise comparisons among alternatives can be found in Liberatore’s (1987) study. The main reason for adopting this method is that the evaluation of an ERP system can involve a large number of technical details consisting of several subcriteria. It may be practically too difficult to make pairwise comparisons among the ERP systems with respect to every subcriteria. The use of a rating scale can eliminate these difficulties allowing evaluator assigns a rating to a ERP system without making direct comparisons. As suggested by Liberatore (1987), a five-point rating scale of outstanding (O), good (G), average (A), fair (F) and poor (P) is adopted. The lowest level of the hierarchy consists of the alternatives, namely the different systems to be evaluated in order to select the most suitable ERP system.

4) THE PROTOTYPE DSS FOR ERP EVALUATION Decision Support Systems are a type of management information system that enable the decision-making process to be supported from beginning to end (Rojas et al, 2001).The DSS allows modify the AHP hierarchy for the ERP system evaluation problem, by adding or eliminating subcriteria from its fourth level, so constructs the objective hierarchy and the appropriate subcriteria are specified to provide

D e f in e S u b c r ite r ia

D e v elo p D e c is io n Hier a r c h y

C o m p a r e F a c to r s /C r ite r ia S u b c r ite r ia P a ir w is e

R atin g S c ale

R ate Alter n a tiv es

C o m p u te N o r m a liz ed P r io r ity W eig h ts a n d C R

C o m p u te G lo b a l C o m p o s ite P r io r ity W e ig h ts

G lo b a l P r io r ity W e ig h t o f E R P

detailed guidance for the remaining three phases of AHP method. The prototype DSS consists of three parts: evaluation model, user interface and database. The figure 2 shows the DSS architecture. Next the architecture’s components are described. 4.1) Evaluation Model The model for ERP systems evaluation through AHP method is depicted in figure 3. The basis for the evaluation model is the AHP hierarchy. This hierarchy is totally defined by selecting the subcriteria from fourth level as stated previously. Then the factors, criteria and subcriteria of the hierarchy must be assessed using the basic AHP approach of pairwise comparisons, using the Saaty’s (1995) intensities of importance, in order to establish which criteria are more important than others. The values are then placed in a matrix and the normalized principal eigenvector is found to provide the weighting factors which provide a measure of relative importance for the decision maker. To examine for consistency the principal eigenvalue λ max is calculated. Deviations from consistency are represented by the consistency index (CI), where:

CI =

λ max − n n −1

Allied to the CI is the consistency ratio (CR), this is the ratio of the CI to the average CI or random index (RI) of a randomly generated reciprocal matrix, i.e. a correction for random error.

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Emerging Trends and Challenges in IT Management After computing the normalized priority weights for these three levels of the hierarchy, the next phase is to synthesize the solution for the ERP evaluation problem. The normalized local priority weights of factors, criteria and subcriteria obtained previosly are combined together with respect to all successive hierarchical levels to obtain the global composite priority weights of all subcriteria used in the fourth level of the AHP model. The next step is to rate each alternative (ERP system) with respect to each subcriterion, as explained in section 3.1, should be used Liberatore’s (1987) five-point rating scale of outstanding (O), good (G), average (A), fair (F) and poor (P). The global priority weight of each ERP system is obtained by multiplying the global priority weight of each subcriterion with the global priority weight of ERP system rating, and adding the resulting values. Finally, these global priority weights need to be normalized. 4.2) User Interface The prototype DSS for ERP evaluation is being written in REALbasic object-oriented programming language under a compatible PC and it runs on Windows operating system. This tool allows to build a graphical user interface (GUI) through use of menus, radio-buttons, push-buttons, listboxs, and so on. Basics functions of the system consist of: a) b) c) d)

Insert/Modify/Delete Insert/Modify/Delete Perform compute of Perform compute of

data about ERP systems and its vendors. data on fourth level of AHP hierarchy. the the weighting factors. the normalized global priority weights.

4.3) Database The database provides parameters for the model and store the results of the model execution. The database design in two-fold: a logical design and a physical design. The entity-relation model for the logical database design and a relational database scheme using SQLite database manager is being used. Below database’s main tables are outlined: 1) 2) 2) 3) 4) 5) 6)

ERP (code_ERP, name, code_vendor) Vendor(code_vendor, name, description, …..) Factors(code_factor, description, weight, lambda) Criteria(code_criterion, description, weight, lambda) Subcriteria(code_sub_criterion, description, weight) Rating(code_rating, description, weight) ERPrated(code_erp,code_sub_criterion,code_rating)

5) SUMMARY AND CONCLUSION This paper shows an ongoing project on the development of a DSS for ERP systems evaluation in SMEs. The ERP systems selection is a important issue for SMEs in Venezuela and around the world. The proposed DSS allows to build an AHP hierarchy and carry out the remaining phases of the AHP method. The DSS can be a effective tool for help SMEs managers in Venezuela to acomplish succesfully the ERP selection task.

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ACKNOWLEDGEMENTS This research is supported by DID-SL. Project number S1-NCSH-00300.

6) REFERENCES Alarcon, N. (2004) Selección de Software ERP para las Empresas de Manufactura en Venezuela. Universidad Simón Bolívar. Tesis de Maestría no publicada. Badri, M.A., Davis, D., Davis, D., 2001. A comprehensive 0–1 goal programming model for project selection. International Journal of Project Management 19, 243–252. Bernroider, W. and Koch, S. (2002). A Framework for the Selection of ERP Packages for Small to Medium and Large Organizations. In: Enterprise Resource Planning: Global Oportunities and Challenges. Idea Group Inc. Colmenares, L. (2002). Developing an Expert System to Software Selection in Small Business. In: Information Technology Management in Developing Countries. IRM Press. 304-308. Lee, J.W., Kim, S.H., 2000. Using analytic network process and goal programming for interdependent information system project selection. Computers & Operations Research 27, 367–382. Liberatore, MJ. (1987) An extension of the analytic hierarchy process for industrial R&D project selection and resource allocation. IEEE Transactions on Engineering Management. 34,12-18. Rojas, T., Pérez, M.A., Grimán, A.C. and Mendoza, L.E. (2001) Decision Support System To Support Software QualityThrough The Selection of Case Tools. In: Proceedings of Seventh Americas Conference on Information Systems. 310-316 Saaty, T.L. (1995). The Analytic Hierarchy Process. RWS Publications. Pittsburgh. Santhanam, R. and Kyparisis, G.J. (1996). A decision model for interdependent information system project selection. European Journal of Operational Research 89, 380–399. Shakir, M. and Hossain, L. (2002) A Framework for Assessing ERP Systems Functionality for the SMEs in Australia. In Enterprise Resource Planning: Solutions and Management. Idea Group Inc. Sistach, F. and Pastor, J.A. (2000) Methodological acquisition of ERP solutions with SHERPA”, in First World Class IT Service Management Guide (Ed. J. van Bon), tenHagenStam. Stefanou, C.J. (2002) A framework for the ex-ante evaluation of ERP software. European Journal of Information Systems. 10 (4), 204 – 215. Tagliavini, M., Faverio, P., Ravarini, A., Pigni, F. and Buonanno, G. (2002) Exploring the use of ERP systems by SMEs. In: Proceedings of the 6th World Multi-Conference on Systemics, Cybernetics and Informatics. Teltumbde. A. (2000) A framework for evaluating ERP projects. International Journal of Production Research. 38 (17), 4507 4520 Wei, Ch. and Wang M. (2004) A comprehensive framework for selecting an ERP system. International Journal of Project Management, 22 (2), 161-169. Winter, R. and Leist, S. (1998). Optimal Allocation of Standardized Application Software Packages to Business Process Steps. In: Information Systems - Current Issues and Future Changes, pp. 439-454.

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1018 2006 IRMA International Conference

Stimulating Creativity and Innovation through People-Concepts Connectivity within On-Line Collaborative Workspaces Marc Pallot, EsoCE-NET, Rome, Italy, [email protected] Wolfgang Prinz, Fraunhofer Institut FIT, St. Augustin, Germany, [email protected] Kulwant Pawar, University of Nottingham, Nottingham, UK, [email protected]

ABSTRACT Constantly changing customer demands and intense global competitive environment imposes the compelling need to better support knowledge workers, operating as eProfessionals, within creativity sessions and innovation tasks while increasing inter-personal productivity in order to remain competitive on the global market. As a consequence, working organisation is shifting towards networked individuals driven simultaneously by the necessity of focusing on core competency while stimulating the emergence of creative ideas and breakthrough innovation. These in turn push organisations to implement new ways of working and interacting among diverse competency fields that require more effective and efficient collaborative approaches. This paper presents the vision of an e-space for all or networked individual shared workspaces within a group forming networks approach. The driving idea is to connect people and concepts together as a kind of knowledge hub where both individuals and communities are exposing knowledge on the Web through networked shared workspaces. An attempt is made to implement and explore the people-concepts connectivity approach within the framework of the AMI@Work ERIA communities used as a living lab, and evaluate its potential impact on creativity, innovation and interpersonal productivity. The paper concludes in introducing a brand new scientific domain of “Knowledge Connection” which is related to the existing domains of Knowledge Creation, Representation and Visualisation.

work according to chain production models but rather more as dynamically and spontaneously assembled groups of people working together in a collaboration mode, which means a seamless work to achieve common goals. The social capital will be the main driver, which means that people constitute the best asset of businesses. Professionals will spend more time in people-networking like activities than ever (i.e. online professional communities and social networks). This is confirmed by the EsoCE-Net survey on professional life balance as shown in figure 1. ICT role will be essential for supporting this professional and contextual social exchange, and seamless interaction within a complex virtualised world where people are in the foreground, as the centre of all attentions, while supporting technologies are operating in the background, almost invisible. In the academic research community, these trends lead to the Social Computing, Social Desktop or Social Web initiatives [Hoschka, 1998]. We consider an eProfessional as a Professional whose business and tasks can only be achieved using modern cooperation technologies. These technologies enable an eProfessional being part of groups and communities as well as knowledge networks, and being involved in distributed cooperation processes that have not been possible before. This paper addresses creativity and innovation potential through people-concepts connectivity within on-line collaborative workplaces. Our goal is to design, explore and evaluate how future innovative collaborative workplaces could stimulate creativity and innovation while increasing inter-personal productivity.

INTRODUCTION AND VISION Within few years, significant social, organisational and economical changes as well as a relentless technology evolution will lead the way of working for eProfessionals into a dramatic change. People will no longer

EXISTING THEORIES AND WORK

Figure 1. Results of the eProfessionals Vision 2010

Flexible Arrangements in the Workplace Working organisation is shifting towards more flexible forms such as networked individuals, often named eProfessionals, in the goals of stimulating creativity and innovation while increasing productivity. These in turn push organisations to implement new ways of working and interacting among diverse competency fields that require more effective and efficient Collaborative Working Environments. Patricia Vendramin discussed an important challenge for the future of work [Vendramin, 1998]: how to develop flexible telework or mobile work patterns avoiding a deterioration of working conditions? What can be a social scenario of flexibility? In the 2004 UK survey on flexible working [Puybaraud, 2005], it is mentioned that “The Holy grail for any organisation is to assess employees’ productivity and increase it”. However, in this case productivity is subjective and depends on many factors such as motivation, well-being, morale, job satisfaction, and level of provided support as revealed in this survey.

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Emerging Trends and Challenges in IT Management Figure 2. Community Window Model

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Broadcast media or traditional industrial age businesses grow roughly in ratio depending on how many listeners or customers they have, which is a proportional growth. However, if it is a network, where the participants can communicate with each other, the rules change. Bob Metcalfe, the inventor of Ethernet, noticed that, and it is known as Metcalfe’s Law, that the value of a network increases with the square of the number of members. David Reed suggested that if it is not just a network, but a community, the rules change again. The number of different interactions that might happen within a group of N people would be 2N, which is an exponential growth. So, if the members of the network can’t just communicate oneto-one, but they can get together in groups of all kinds of sizes, the potential value is huge. It is what potentially can happen but there is no certitude about it. Groups don’t necessarily form spontaneously. It would be extremely interesting to discover factors that help groups to form and to self-organize.

RESEARCH APPROACH Interpersonal Communication and Productivity While productivity of individual work has been considerably increased for years by Information Technology, very few has been done in term of collaborative work and interpersonal productivity. Actual business cases of mobile work are mainly focusing on the increase of individual productivity while mobile and collaborative technologies are sitting on huge possible gains of interpersonal productivity. A model known as the Johari Window [Luft and Ingham, 1969] illustrates the process of interpersonal communication. It is an easily understood model of communication which employs a four-part figure to reflect the interaction of two sources of information - self and others. The squared field, representing the “interpersonal space,” is partitioned into four “regions”. The Arena is the portion of the total interpersonal space devoted to mutual understanding and shared information. This known by the self - known by others facet of the relationship is thought to control interpersonal productivity. The assumption is that productivity and interpersonal effectiveness are directly related to the amount of mutually-held information. Therefore, the larger the arena becomes, the more rewarding, effective, and productive the relationship is apt to be. The arena can be thought of as the place where good communication happens. One can increase the size of this region by increasing the amount of exposure and feedback seeking. Figure 2 is showing an adaptation of the Johari window model at the age of the Internet, Web and shared workspaces where eProfessional individuals, groups and communities can expose and share their knowledge on the web. This extended Johari Window model is named the on-line Community Window Model and illustrates the process of Web enabled interpersonal communication through the use of collaborative shared workspaces. The model is quite similar to the Johari one and employs a four-part figure to reflect the interaction of two sources of knowledge – self, the eProfessional characterised by its individual shared workspace and others, characterised by the group or community shared workspaces. The size of the squared field, representing the “arena”, is increased by knowledge exposition into two different regions. The dashed region represents the source of incremental innovation and the solid filled region represents the source of breakthrough innovation [Pallot et al., 2005]. Group Forming Networks David Reed, an Internet veteran, is credited with what is sometimes called Reed’s Law, which says, essentially, that networks that facilitate easy group forming are subject to potentially exponential growth [Reed, 1999].

Our research approach, beside the traditional literature review, starts with the development of vision scenarios for identifying innovative vision elements which are then compared with the state-of-the-art elements in order to identify the resulting gaps to be addressed to reach the vision. In parallel to the development of vision scenarios and identification of gaps, we have tentatively extended the Johari Window Model into the on-line Community Window Model where we try to evaluate the impact of Web technologies on the initial model for both measuring the whole work community and prescribing ways to improve the collaborative workplace. Secondly, we use this extended window model to locate the emergence of creative ideas and characterise the possible areas of incremental innovation as well as breakthrough innovation. Concurrently to this work, an on-line community survey, dedicated to “on-line people networking”, is conducted within an innovative way of consulting the AMI@Work European Research and Innovation Area (ERIA) communities through the combination of complementary polls posted on the communities’ website. The main objective of this on-line survey is to validate the emerging vision elements and deducted research challenges. We have used other existing surveys and reports such as the 2003 and 2004 surveys dedicated to flexible working in order to better understand drivers for change and both employers and employees expectations as well as challenges to be addressed in the light of these changes and expectations. Findings The AMI@Work European Research and Innovation Area (ERIA) communities are used as a “Living Lab” where we are exploring and evaluating the people-concepts connectivity approach. We are actually implementing a new version of the communities’ website to implement, support, explore and evaluate people-concepts connectivity within the communities shared workspaces and its potential impact on creativity, innovation and inter-personal productivity through a number of metrics derived from social network analysis techniques and group forming networks law. Collected metrics data should provide pragmatic and realistic indications on whether we could validate the people-concepts connectivity approach to better support interactions among totally unknown people.

CONCLUSION AND FUTURE WORK We are promoting an “individual shared workspace” for every eProfessional like the famous motto “an e-space for all”. All those individual shared workspaces form a Network from where eProfessionals could start forming groups or communities as well as needed shared workspaces according to their common interests and collaboration needs. This approach is compliant with above Reed’s law if we can demonstrate that this network of eProfessionals’ individual shared

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1020 2006 IRMA International Conference workspaces really facilitates easy group and community forming which are subject to potentially exponential growth. It would dramatically boost and stimulate creativity and innovation while increasing considerably productivity if we think just about how fast and easy it will become to connect knowledge and reach a mutual understanding with other eProfessionals sharing the same interest. Formalised concepts within communities appear to be a corner stone linking collaborative resources together which open new possibilities such as discovering automatically useful collaborative resources within a broad population of virtual communities and in visualising or browsing resulting people-concepts maps. This lead to stimulate creativity and innovation in providing much faster and broader access to existing knowledge and people know-how and thus more opportunities to collaborate and more alternative solutions to explore. It is tentatively named “Knowledge Connection”. The next stage consists to evaluate whether Knowledge Connection could become a new scientific domain by its own at the crossroads of Collaborative Work, Knowledge Creation, Representation and Visualisation.

ACKNOWLEDGMENT This work has been partly funded by the European Commission through the COMIST IST Project. The authors wish to acknowledge the European Commission for their support. We also wish to acknowledge our gratitude and appreciation to all project partners and communities members for their contribution.

REFERENCES AMI, 2004: “AMI@Work Family of Communities, an Initiative to Catalyse Systemic Innovation” http://www.mosaic-network.org/ pub/bscw.cgi/d55630/AMI@Work%20Article.pdf Peter Hoschka & Wolfgang Prinz, 1998: “CSCW Research at GMD-FIT: From Basic Groupware to the Social Web” Luft, Joseph, 1969: “Of Human Interaction”, Palo Alto, CA: National Press. Pallot, Prinz & Schaffers, 2005: “Future Workplaces, Towards the Collaborative Web”. Proceedings of the AMI@Work Communities Forum Day, Munich, June 2005. Puybaraud, 2005: “Work loneliness: The Impact of Flexible Working”. Article published in the MOSAIC Newsletter n° 3, January 2005. Reed, 1999: “That Sneaky Exponential – Beyond Metcalfe’s Law to the Power of Community Building”, Context magazine, 1999 Vendramin, G. Valenduc, 1998: “FTU Foundation Travail-Université, Telework in the scenarios for the future”, Telework’98

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Emerging Trends and Challenges in IT Management

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Evaluation of E-Commerce in Continental Native American Nations Yun-ke Chang, School of Computer & Info., Nanyang Technological University, 31 Nanyang Link, Singapore 637718, [email protected] Miguel A. Morales Arroyo, Shumens, BLK 100 # 02-01, Nanyang Crescent, Singapre 637819, [email protected] Suliman Hawamdeh, MSKM, SLIS, College of Arts & Sciences, University of Oklahoma, 4502 E. 41st St., Tulsa, OK 74135, [email protected] Jaime Jiménez, IIMAS, UNAM, Apdo. Postal 20-726, Admón. 20, Del. A. Obregón, 01000 Mexico, DF, [email protected]

ABSTRACT This paper presents an evaluation of seven Native American e-commerce portals in order to identify their problems which can be addressed by decision and policy makers. The evaluation methodology used was developed by Van der Merwe and Bekker (2003). From the results of this study, some of the problems that Native American e-commerce businesses confront are technical, organizational, and access to credit and infrastructure.

LITERATURE REVIEW E-commerce has created exceptional and significant opportunities for companies in countless business environments to interact with their customers (Kim et al., 2003). Native American Nations has foreseen the opportunities that technology could provide them. With the Web as primary infrastructure, e-commerce offers several tangible and intangible benefits. For Native American Nations, an online presence is the forum used to communicate with customers; to facilitate business transactions; to preserve their cultural heritage; native organizations; to supply resources on genealogy and demographics, educative opportunities, culture, literature, history, spiritual practices, sovereignty, and contemporary life (Taylor, 2002). The Internet has sites that respectfully present Native Americans with truthful information, quality merchandise to sell, and as normal human beings with authentic existence. However, the Internet has also sites that present incorrect information, and represent Native Americans through lens that distort their image (Cubbins, 2000). At present, Native Americans perceive e-commerce presence as an alternative for economic development. Some of them sell products and services. Also, they are proprietary of casinos (Evans and Topoleski, 2002; Kearney, 2005). The strategies Native American nations are using for generating economic development and have the objective of paying for education and healthcare (Wood, 2003). Also, there are ecommerce sites that belong to individuals or groups that are for profit, but keeping strong links with their cultural background. Well-designed portals can help create loyal clientele and increase profits, poorly designed ones may lead to frustrated consumers and subsequent losses (Cunliffe, 2000). In spite of the importance of this topic, research and literature focusing on e-commerce evaluation are limited and our review has found little research of this nature for ecommerce portals. Some of them include the following: • •

•

Schubert and Selz (1999) described a web assessment model created by the Competence Center for Electronic Markets; Liu et al. (2000) proposed criteria for the design of e-commerce sites derived from a survey of web masters working for Fortune 1000 companies; DeLone and McLean (2004) proposed six dimensions — system quality, information quality, service quality, use, user satisfaction, and net benefits;

• • • •

Phippen et al. (2004) considered customer lifecycle analysis and customer behavior analysis in their research in web analytics; Kim and Lee (2003) conducted research on e-catalogs evaluation; Mao et al. (2005) proposed measures of effectiveness for web sites; and Van der Merwe and Bekker (2003) proposed a comprehensive set of evaluation criteria for e-commerce sites.

The evaluation criteria proposed by Van der Merwe and Bekker (2003) was adopted in this study as it is broader than the other frameworks reviewed.

STATEMENT OF PURPOSE The objective of this paper is to evaluate seven randomly selected Native American e-commerce portals in order to identify their problems. The significance of the study is based on two factors: a) little research has been done in this area, and our literature review has found little research of this kind has been developed for minorities and specifically for Native Americans, and b) the instrument used and the results obtained by this research could help Native American businesses enhance their e-commerce sites.

METHODOLOGY Seven Native American’s e-commerce sites were evaluated. A gateway to the presence of Native American Nations is the Lisa A. Mitten’s website “NATIVE AMERICAN SITES and home of the American Indian Library Association Web Page” (http://www.nativeculturelinks.com/ indians.html). This site provides a category called Native businesses, which provides access to ninety nine Native American business sites. Not all the sites in this category can be considered e-commerce sites; there are companies, Native American business associations, et cetera. Those that are not e-commerce site were skipped, and finally seven sites were chosen randomly. Each of these portals evaluated belongs to a Native American nation or is developed by individuals belonging to that Nation. The evaluation instrument used was developed by Van der Merwe and Bekker (2003). These evaluation criteria incorporate five distinct categories: interface, navigation, content, reliability, and technical infrastructure. In order to guarantee objectivity, three different individuals did the evaluation. The evaluation procedure has two steps, as follows: a)

Gather data - Values were assigned using an interval scale zero to ten. Zero represents the non-existence of the attribute. After the evaluations were completed, common agreement was achieved in the way the evaluation criteria were used. The e-commerce sites were retrieved from 13 to 15 of December.

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1022 2006 IRMA International Conference b)

Analyze the results - the results were tabulated and drawn using radar graphics. Each specific evaluation criteria will be compared for each e-commerce portal to describe the degree of maturity of each Web site.

Figure 2. Navigation

Instrument The researchers adapted the evaluation criteria, and the modified instrument containing 110 items to assess in five categories and twenty subcategories. The interface category assess: graphic design principles, the value of the graphics and multimedia, style and text, and flexibility and compatibility. The navigation category assess: logical structure, user friendly, search engine service, and navigational necessities. The content category assess: product or service related information, company and contact information, information quality, and interactivity. The reliability category assess: customer profile, order process, afterorder follow up, and customer service. Finally, the technical category assess: speed, security, use of software and database, and system design. Limitations Four sub-categories were difficult to assess: after-order follow up, customer service, speed, and security.

Figure 3 Content

RESULTS The degree of technical sophistication found in e-commerce sites has a wide spectrum of sophistication, going from static one page sites to sites making use of database catalogs, and credit card payments using pay pal services. In the interface design, the subcategories – Graphic design, graphics and multimedia, style and text, and flexibility and compatibility have the following averages: 6.8, 6.4, 7.5, and zero. The following issues are not addressed in any one of those seven sites: printable versions for pages available, text-only versions, special consideration for disable individuals, and the page size to fit the browser window. The best issue addressed is style and text. The graphic design and the use of graphics are good in two sites, fair in another, and the rest of them have room for improvement. In fig. 1, each one of the vertices represents a site, and the subcategories are measured from zero to ten. The navigation category sub-categories averages are the following: logical structure – 5.6, user friendly – 7.5, search engine – 4.5, and navigational necessities, which includes “no broken links” – 6.4. In navigation, two sites do a good job, one a fair, and the rest of them have space for improvement. For more details, see figure 2. The average assessment values for the sub-categories of content are the following: product or service related information – 5.8, company and contact information – 6.4, information quality – 6.8, and interactivity – 1.5. In this category, two sites do a fair job, one acceptable, and the rest have opportunity to improve. The content category is the one least

Figure 1. Interface

related to content, but the values are the lowest. This category is related to the description of product or services, contact information from the e-commerce site. The sub-category that requires more technology is least developed and includes issues like customization and personalization of content for the user, and the creation of an interactive community of buyers (fig. 3). The fourth category reliability was not assessed completely because the researchers could not assess the customer service and the after-order follow up. Storing customer profile and the order process were assessed, but only one site do a fair job in these two categories. In the technology category, some aspects were not possible to measure such as speed, adequacy of software and database. It was possible to review security and the overall system design. Security is one of the areas in which these e-commerce sites require help.

CONCLUSIONS Bregendahl and Flora (2002) found in their research specific opportunities and challenges to develop e-commerce in Native American nations. Some of the opportunities and challenges are the following: a) credit and finance, b) making the most of cultural capital, c) enhancing tribal assets, d) social and cultural obstacles, e) lack of infrastructure, and f) the necessity of technical assistance and training. From the results of this study, some of the problems that Native American e-commerce businesses confront are technical, organizational, and access to credit and infrastructure. This reflects that digital divide may still be a reality for minority groups. As Prieger pointed out before, this situation has

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Emerging Trends and Challenges in IT Management evolved over the time, and today for Native American nations, it means to have restricted access to broadband internet access (Prieger, 2003). Criticism can be done to this type of research – the instrument is not adequate, the researchers do not understand the complexity of Native American reality, and/or it represents the point of view of outsiders. This research should not be understood as a critic to the Native American e-commerce sites evaluated, but as information that can be used in the policy making or decision-making processes.

REFERENCES Bregendahl, C., Flora, C. (2002). Native American Business Participation in E-commerce: An assessment of technical Assistance and Training needs, North Central Regional Center for Rural Development. Cubbins, E. (2000). Techniques for Evaluating American Indian Web Sites, retrieved Oct. 1, 2005, from http://www.u.arizona.edu/ ~ecubbins/webcrit.html Cunliffe, D. (2000). Developing usable web sites: A review and model. Internet Research: Electronic Networking Applications and Policy, 10(4), 295-307. D’Angelo, J. & Little, S.K. (1998). Successful web pages: What are they and do they exist? Information Technology and Libraries, 17(2), 71-81. DeLone, W. H., & McLean, E. R. (2004). Measuring E-commerce Success: Applying the DeLone and McLean information system success model. International Journal of Electronic Commerce, 9(1), 31-47. Evans, W. N., Topoleski, J. H. (2002), The social and economic impact of Native American Casinos, National Bureau of Economic Research, Working Paper 9198.

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Kearney, M. S. (2005). The Economic Winners and Losers of Legalized Gambling, National Tax Journal, Vol. 58 (2), 281-302. Kim, S.-E., Shaw, T. and Schneider, H. (2003). Web site design benchmarking within industry groups”, Internet Research: Electronic Networking Applications and Policy, 13 (1), pp. 17-26. Liu, C., Arnett, K.P., & Litecky, C. (2000). Design quality of web sites for electronic commerce: Fortune 1000 webmasters’ evaluations. Electronic Markets, 10(2), 120-129. Mao, J., Vrendenburg, K., Smith, P. W., & Carey, T. (2005). The state of user-centered design practice. Communications of the ACM, 48(3), 105-109. Phippen, A., Sheppard, L., & Furnell, S. (2004). A Practical Evaluation of Web Analytics. Internet Research, 14(4), 284-293. Prieger, J. E. (2003). The supply side of the digital divide: is there equal availability in the broadband internet access market?, Economic Inquiry, 41 (2), 346-363. Schubert, P., & Selz, D. (1999). Web assessment - measuring the effectiveness of electronic commerce sites going beyond traditional marketing paradigms. Proceedings of the 32nd Hawaii International Conference on System Sciences, vol 5. Retrieved October 18, 2005, from http://csdl2.computer.org/comp/proceedings/hicss/1999/0001/05/00015040.PDF Taylor, R. H. (2003). Focusing on Native Americans: basic Web resources pathfinder, Collection Building, 21(2), 60-70. Van der Merwe, R., & Bekker, J. (2003). A framework and methodology for evaluating e-commerce web sites. Internet Research, 13(5), 330-341. Wood, F. B. (2003). Tribal connections health information outreach: results, evaluation, and challenges, Journal of Medical Libraries Association, 91(1), 57-66.

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1024 2006 IRMA International Conference

Estimating Signal Strengths in Indoor Wireless Systems in Order to Deliver a Cost-Effective Solution Optimizing the Performance of the Network Gabriel Astudillo & Lenny Garófalo Escuela Superior Politécnica del Litoral, Km 30.5 Av. Perimetral, Ecuador Hernán Córdova, Vrije Universiteit Brussel (Dept ELEC/TW), Pleinlaan 2, B-1050 Brussels, Belgium, & Escuela Superior Politécnica del Litoral, Km 30.5 Av. Perimetral, Ecuador, [email protected], [email protected]

ABSTRACT Proper AP placement is necessary to provide adequate signal coverage and also to minimize co-channel coverage overlap. In this document, we present the test-bed used in our lab and the procedure and methodology we have created (modified) to achieve accurate measurements. We describe a procedure for carrying out the estimation of AP coverage patterns in order to eliminate the need to re-measure coverage patterns for every candidate combination of AP locations. It is expected to obtain a difference no bigger than the 3 dB between the estimated signal strength and measured signal strength.

I. INTRODUCTION Nowdays, indoor networks are getting more popular and its use is widely spread, growing its share into the international market. At the beginning, this solution was not popular and therefore suitable, because of its low rate speeds. Thereby, important institutes as IEEE and WiFI Alliance worked together to develop a standard: IEEE 802.11x. The purpose of this paper is to show different methods for reducing the infrastructure deployment costs of wireless networks, specifically for systems that are willing to transmit very high data rates. One important issue in the design and implementation of a wireless local area network is the selection of the Access Point (AP) locations. Proper AP placement is necessary to provide adequate signal coverage and also to minimize cochannel coverage overlap. Importance of suitable placement of APs is then very significant. Placing APs too far apart could seem to be economical but usually not such effective due to this solution could lead to gaps in coverage and thereby, reducing the effective coverage and degrading the total performance of the wireless system. On the other hand, placing APs so closely leads to excessive co-channel coverage overlap, degrading system performance even to the point on which the link goes totally off. This is our main concern. Currently, AP placement involves a trial and error technique. There is not established neither a procedure nor a methodology to solve this issue. This study pretends to reach an approach to this situation and delivers a methodology and measure the reliability of itself. The state-of-the-art in this field is very interesting. Even though there are a lot of papers that mention and discuss this issue, most of them establish empirical measurements and techniques [1, 2] that still are falling into the trail and error technique. Obviously this technique will be used at the beginning of the research but the main idea is to simulate and be able to estimate the coverage of each AP optimizing the resources without degrading the system. Wireless Local Area Networks are not completely deployed in Ecuador. For example, Hot-Spots are still not installed as it is supposed to be and they are not working either on that way.

We certainly believe that delivering a procedure and methodology will promote the use of WLAN´s and will save a lot of money to clients and at technology delivering a cost-effective solution to the market. In section II, the measurement setup will be presented and discussed. The algorithm design and its advantages over its drawbacks will be covered in section III. An example will be provided in Section IV showing the way the algorithm can be implemented. Finally, section VI concludes the paper highlighting the main points addressed during the entire document and also referring to the current and future work.

II. MEASUREMENT SETUP A. Data Collection Methods and Tools used Wireless network data was collected using NetStumbler. This program was selected because of its ease of use and installation; the program runs on the Windows platform. This program observes reasonable privacy guidelines in the sense that: •

• •

Access Points are detected only if they are publicly broadcasting their SSID, or the client card is configured to look for that specific SSID. No attempt is made by the software to gain access to the network. Other traffic on the network is not intercepted or analyzed in any way

For the driving scans, a Compaq Armada 1575DM Pentium MMX processor laptop running the Microsoft Windows 98 operating system and NetStumbler 0.4.0 software for data collection was utilized. Wireless signal strength data was collected with a D-Link DWL-122 USB Adapter connected to the Laptop USB port and to move the AP (D-Link DWL700AP) inside the coverage area we will use a test cart with mast in which we have placed a directional antenna of 80 degrees (DWL-M60AT) connected to the AP (Figure 1 shows a close up of the antenna, laptop and test cart) Another important aspect on the design of wireless networks is to use attenuation factors obtained by the experimentation “in situ”. This assured that the results are close to the reality. For this reason and according to previously measurements, we have elaborated a chart with the attenuation values for the most common materials, which are shown in the table 1.

III. ALGORITHM DESIGN Our work will try to reduce the difference between the estimated value and the measured value, using the algorithm of the neighbor’s discovery

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Emerging Trends and Challenges in IT Management Figure 1. Test Cart SETUP (A) Test cart( B) Close view of the laptop with NetSlumber (C) Close view of the antenna

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Figure 2. The Measurement Grid

B

A

C

Table 1. Attenuation values for the most common materials founded in the Testing Area

The second step of the design process can be made much faster and more efficient if the signal coverage patterns of relocated APs can be quickly estimated. This reduces the need to move APs and re-measure their coverage patterns. With this approach, APs are moved “virtually,” rather than physically, and their new coverage patterns are estimated rather than measured. In this way, we describe a procedure for carrying out the estimation of AP coverage patterns in order to eliminate the need to re-measure coverage patterns for every candidate combination of AP locations.

IV. APPLICATION EXAMPLE In the following example we will illustrate the procedure to use the proposed algorithm: The first step is to locate the AP in the covering area. For this purpose, we have selected a near location to the backbone of the Faculty of Electrical and Computer Engineering (FIEC) and we will take initial measures in 8 points next to the AP. It is necessary to highlight that in the measurement area is located a wall of concrete of 12 cm. of thickness and that will allow us to apply the variant proposed to the model considering the Wall attenuation factor (WAF) together with the empiric model of the Wall Attenuation Factor (WAF). In [1] the propagation model used is the free space path loss model, which is adjusted for outdoor environments without obstacles, or points so close to the access point. However, for the area in which we will carry out the study, we found multiple concrete walls with a thickness of 12 cm, aluminum divisions and plywood with a thickness of 8 cm, which leads us to use a model that is adjusted better to the conditions of the study.

-50 (-49) 1,1 AP

1) 2) 3) 4) 5) 6) 7)

Initial selection of AP locations; Obtaining of the attenuation factors characteristic of the study area Application of the WAF model with the factors obtained in 2 to estimate the signal strength Test and redesign which is adjusting the AP locations based on signal strength measurements; Creation of a coverage map; Assignment of frequencies to APs; Audit, which is documenting the AP locations and a final set of signal strength measurement at the frequencies selected.

2,1 L=1

-52 (-52) 2,2 L=0

-58 (-55) 3,1 L=3

1.

1,3 L=1

1,2 L=1

-50 (-49)

We have modified a design procedure adding the steps 2 and 3, reported in detail in [2], which includes five steps, enlarging it to 7 steps:

-70 (-69)

-71 (-70) 2,3 L=1

-58 (-56) 3,2 L=2

-73 (-72) 3,3 L=1

For each point we calculate the signal strength using

s = s * − 10n log(d ) − kWAF where k is the number of walls and After the initial selection of AP locations (the first step) is complete, APs are temporarily installed at the locations selected. The coverage areas of these APs are measured (see figure 2). Typically, coverage gaps and/or excessive overlaps are found. Based on the measurement results, the AP locations are adjusted as needed, more measurements are done, more adjustments are made, etc., until an acceptable design is found. The process is in principle iterative. It may be necessary to repeat this design– test–redesign cycle several times to find an acceptable solution.

2.

WAF it is the attenuation factor, which was encountered through the experimentation like WAF=14dBm for a concrete’s wall of 12 cm of thickness. The measured signal strength in each node is shown in the figure 4 and the calculated measured signal strength is shown in parenthesis. The excess of lost L of each measured is calculated using these two values the value of L it is shown inside each node.

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1026 2006 IRMA International Conference 3.

4. 5. 6.

We assign a weight W to each edge which are shown inside the squares, these weights can be positive or negative, if they are negative they are normalized according to the procedure settled down in [1] The AP is moved to a new location (see figure 5) Using the algorithm of the neighbour’s discovery we finds the neighbouring nodes We calculate signal strength for each one the 2 nearest nodes (2,3) and (3,2) to the new location of the AP with

s est = s − 10n log(d ) − kWAF .

V. CURRENT WORK At the moment of writing the present document we are in the phase of comparison of the results obtained with the estimated values and measured values and we hope to obtain a difference no bigger than the 3 dB between the estimated signal strength and measured signal strength.

REFERENCES [1]

*

7.

The signal strength for all the other nodes is calculated. The smallest sum possible of the weights of the edges that connect a node with a nearer neighbour it is used. The reference values of the estimated signal strength before being adjusted based on Wmin it is shown in parenthesis. The estimated signal strength which has been adjusted considering Wmin is shown without parenthesis.

[2]

[3] [4]

A. Hills, “Large-scale wireless LAN design,” IEEE Commun. Mag., vol. 39, pp. 98–104, Nov. 2001. A. Hills and D. B. Johnson, “A wireless data network infrastructure at Carnegie Mellon University,” IEEE Pers. Commun., vol. 3, pp. 56–63, Feb. 1996. Jani Tamminen, M.Sc. “2.4 GHz WLAN Radio Interface” Radionet Oy , Nov. 2002. Chris Lentz “802.11b Wireless Network Visualization and Radiowave Propagation Modeling”, Technical Report TR2003451, June 1, 2003

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Emerging Trends and Challenges in IT Management

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Application of a Collaborative Virtual Environment for Learning Molecular Biology Miguel A. Garcia-Ruiz, Ricardo Acosta-Diaz, Maria Andrade-Arechiga, & Juan Contreras-Castillo School of Telematics, University of Colima, Ave. Universidad 333, Colima, 28040, Mexico, P/F 52 312 31611075 {mgarcia, acosta, mandrad, juancont}@ucol.mx

ABSTRACT This paper explores a collaborative virtual environment (CVE) applied to support molecular structure learning. Due to many students of all levels have difficulty understanding the structure of molecules and other information in molecular biology and biochemistry courses, CVEs seem suitable to support its learning, because students can inspect virtual models of molecules, as well as learning in collaboration. In addition, literature reports that virtual reality has been used in education to facilitate learning of abstract or complex information with positive success. We started a research project that used virtual environments containing virtual molecules of DNA and amino acids. They can be studied by students using the local network and the Internet, thus many students could benefit. A pilot usability study was set up, in which preliminary results shows ease of molecule analysis and communication among students.

1. INTRODUCTION Chemistry students of all levels have difficulty learning and understanding biochemistry concepts due of its abstractness, as in the bonding of two molecules (Birk and Kurtz, 1999). The problems of learning molecular structure are basically due to incomprehension of molecular scale, difficulty of perception of three-dimensional features, and complexity of molecular bonds, among others (Dor and Barak, 1999; Birk and Kurtz, 1999). Plastic and wood model sets have been used for learning and teaching molecular structure since the fifties, but they present a number of disadvantages, such as inaccuracy of scales and bond angles, difficulty to manipulate and store, and incapacity to show some molecular properties such as bond order (Petersen, 1970). Since the eighties, computer-assisted learning (CAL) programs, especially multimedia and computer-based graphical representations, have been commonly used in classrooms and computer rooms to support learning of molecular structure, using stand-alone molecular visualizations and modelers. One of the most popular and free molecular visualization program is Rasmol, developed by Roger Sayle in 1996. With the widespread use of the Internet starting in mid nineties, molecular visualizations have been easily done by groups of students, downloading graphical representations of molecular structures from Web pages or collaboratively watching and analyzing the same molecular graphic using plug-ins for Web browsers (Rzepa et al., 1997).

models (Byrne, 1996), and others, to name some. With virtual reality, students can understand abstract or complex concepts in a new way, using various sensory channels, thus supporting the learning process (Dede et al, 1997). In addition, Virtual reality technology can make concepts more explicit and concrete, recreating situations or concepts that can be difficult to do in a real environment (Dede et al, 1997; Sherman and Craig, 2003). For example, a student could explore a virtual atomic structure with virtual protons, and virtual electrons moving around its core (Byrne,1996).

2. USABILITY STUDY A series of virtual environments are being developed, containing virtual molecules of DNA (Deoxyribonucleic Acid) and twenty basic amino acids. These molecules were chosen because they are widely studied in biochemistry and related courses (Cohen, 2003). The data for making the virtual molecules were obtained from PDB (Protein Databank) files downloaded from the RSB Protein Data Bank website (Berman et al., 2000). The virtual molecules were shown using a virtual environment browser called DIVE (Distributed Interactive Virtual Environments) (Carlsson and Hagsan, 1993). DIVE is a free VR browser, which has its own language, and also can handle Tcl/Tk and VRML (Virtual Reality Modeling Language) scripts. It can be downloaded from http://www.sics.se/ dive/. Students access a virtual environment made in DIVE through a local network or the Internet, where they are represented in the environment as avatars (a graphical personification of a student), as well as to communicate each other using a text chat window, and using the voice with a microphone. In this manner, a virtual molecule can be shared, seen, analyzed, and manipulated by all the students. It is possible to use other virtual reality browsers and programming libraries to do collaborative learning such as VR Juggler (Cruz-Neira et al., 2002), but we consider they are more difficult to program and configure than DIVE. A usability study was carried out to get first insights of the visualization of virtual molecules, as well as the analysis of the use of the collaborative virtual environment. Eight Computer Science students were asked to participate in the study. They had very basic knowledge of molecular

Figure 1. Some virtual molecules shown in DIVE browser.

Recently, virtual reality (the 3D graphical simulation with interaction) has been used for analyzing and learning molecular structure and bonding. Stand-alone applications have been developed and used to support comprehension of bond formation, molecular site receptors, and amino acids structures (Su and Loftin, 2001; Sherman and Craig, 2003). However, there is limited research on the benefits of learning molecular structure using collaborative virtual environments. In addition, this technology has been successfully used in a number of educational areas for reinforcing complex or abstract concepts and for simulation, such as in Zoology (Allison et al. , 1997), Algebra (Bricken, 1992), atomic Copyright © 2006, Idea Group Inc. Copying or distributing in print or electronic forms without written permission of Idea Group Inc. is prohibited.

1028 2006 IRMA International Conference Figure 2. Configuration of the collaborative virtual environment.

students shown problems with the communications using the voice. 90% declared that the chat window was very useful for comments exchange on the virtual molecule.

4. DISCUSSIONS

Figure 3. Students analyzing a view of virtual molecule of DNA.

All of students declared in the questionnaire that they preferred to learn biochemistry using a collaborative virtual reality environment in conjunction with other technologies, such as multimedia CD-ROMs and Web pages. Most students strongly prefer the use of VR to learn biochemistry than from traditional pedagogical tools alone (i.e. the blackboard). In addition, it was noticed that students shown an increase of their participation, especially interest and collaboration, compared to activities done in a conventional classroom. This increase of participation and interest using a computer-mediated communication (in this project, participants used the text messaging in the collaborative virtual environment) has been reported in other research studies using virtual reality in education (Byrne, 1996; Dor and Barak, 1999).

5. CONCLUSIONS Initial tests of the collaborative virtual environment were encouraging. Nevertheless, it is necessary to make certain technical adjustments, such as the voice communications. This happened because we needed to increase the microphone gain, and perhaps to use better microphones. We also have to adjust the use of the keyboard for changing the viewpoint. Due to DIVE browser is free, and its computer requirements are relatively low compared to other virtual reality programs, it can be installed and used in almost any today’s computer room. structure. A virtual molecule of DNA was chosen for this test because of its particular structural features, such as amino acids conformation, helicoidal structure, and other features described in Cohen (2003). A usability questionnaire was designed with four open questions and five Likert scales to obtain information about participants’ demographics, video games previous experience (to see if this could affect participants’ performance in the study), possible discomfort in the visualization, ease of watching the structural features, preference, and collaboration. For this study, participants were asked to use four computers with Windows 2000 operating system, connected to a local network running at 100Mbps (See Figure 2.). All the computers were at the same room, situated one another approximately 5 meters apart. The students were seated in pairs in front of each computer (Figure 3). All the students were sharing the same virtual environment showing a DNA virtual molecule, which was seen and manipulated using DIVE browser. A chemistry teacher (acting as a moderator) explained DNA’s main molecular structural features, such as conformation, chirality, chemical composition, bonding, and others, as the molecule model was rotated. The teacher explained the virtual molecule using the text chat system of DIVE, and showed the molecule from many angles and from the inside of the DNA molecule, as well as zooming in and out, as he was explaining the structure. The molecule explanation lasted about 30 minutes. During the explanation, students could ask the teacher or to another student about the virtual molecule using the text chat window or their voice using the microphone. After the explanation, students were asked to fill in the usability questionnaire.

3. PRELIMINARY RESULTS Most of participants declared in the questionnaires that it was very easy to watch the molecular features on the computer screen, even though four of them answered in the questionnaire to have a sight problem (myopia and astigmatism). All students positively responded to a question that asked how useful collaborative VR should be to learn molecular structure in chemistry courses. Regarding the preference questions, all students preferred to learn biochemistry using VR in conjunction with other didactic media, such as multimedia and Web pages. 65% of students declared that using the keyboard arrow keys was very easy to change the view point of the molecule. However, 45% of

6. FUTURE WORK A study is being planned to compare a group of students without a moderator and having them manipulate and analyze the molecule, following certain predefined tasks. Further tests are needed with larger number of students, and doing tests on the Internet as well, having groups of students that could be remotely connected online. DIVE architecture is ready for working with many students on the Internet, previous installation of DIVE and proxy servers. It is necessary to do a polygon optimization to the source code of the virtual molecule of DNA, since it is a large file, and it could not be adequately displayed on remote or slow Internet accesses. Once the virtual environment system is tested and updated, we will apply it to regular molecular biology, biochemistry and related courses.

REFERENCES Allison, D., Wills, B., Hodges, L. F., and Wineman, J. (1997). Gorillas in the Bits. In Proceedings of the 1997 Virtual Reality Annual international Symposium (VRAIS ’97)). VRAIS. IEEE Computer Society, Washington, DC, 69. Berman, H.M., Westbrook, J., Feng, Z., Gilliland, G., Bhat, T.N., Weissig, H., Shindyalov, I.N., Bourne, P.E. (2000). The Protein Data Bank. Nucleic Acids Research , 28. Birk, J.P., and Kurtz, M.J. (1999). Effect of Experience on Retention and Elimination of Misconceptions about Molecular Structure and Bonding. Journal of Chemical Education, 76(1). Bricken, W., & Winn, W. (1992). Designing Virtual Worlds for Use in Mathematics Education: The Example of Experiential Algebra. Educational Technology, 32, 12-19. Byrne, C. (1996). Water on Tap: The Use of Virtual Reality as an Educational Tool. PhD Thesis. University of Washington, Seattle, WA. Carlsson, C., & Hagsan, O. (1993). DIVE - A Platform for Multi-User Virtual Environments. Computers and Graphics, 17(6). Cohen, J. (2003). Guidelines for Establishing Undergraduate Bioinformatics Courses. Journal of Science Education and Technology, 12(4).

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Emerging Trends and Challenges in IT Management Cruz-Neira, C., Bierbaum, A., Hartling, P., Just, C., Meinert, K. (2002). VR Juggler – An Open Source Platform for Virtual Reality Applications. Published at 40th AIAA Aerospace Sciences Meeting and Exhibit 2002, Reno, Nevada, January. Dede, C., Salzman, M., Loftin, R. B., & Ash, K. (1997). Using Virtual Reality Technology to Convey Abstract Scientific Concepts (In Press). Lawrence Erlbaum, Hillsdale, NJ. Dor, Y. J., & Barak, M. (1999). Computerized Molecular Modeling as a Collaborative Learning Environment. In Hoadley, C., & Roschelle, J. (Eds.), Proceedings of the Computer Support for Collaborative Learning (CSCL) 1999 Conference. Stanford University, Palo Alto, CA, Lawrence Erlbaum Associates. Petersen, Q.R. (1970). Some Reflections on the Use and Abuse of Molecular Models. Journal of Chemical Education, 47(1).

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Rzepa, H. S., Murray-Rust, P. and Whitaker, B. J. (1997). The Internet as a Chemical Information Tool, Chem. Soc. Revs., 1997, 1-10. Sherman, W. R., Craig, A.B. (2003). Understanding Virtual Reality. San Francisco: Morgan Kauffman. Silverman, B.G. (1995). Computer Supported Collaborative Learning (CSCL). Computers and Education, 25(3). Su, S. and Loftin, R.B. (2001). A Shared Virtual Environment for Exploring and Designing Molecules. Communications of the ACM, 44(12). Winn, W. (1993). A Conceptual Basis for Educational Applications of Virtual Reality. Tech. rep., Human Interface Technology Laboratory, University of Washington. Report No. TR-93-9.

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1030 2006 IRMA International Conference

Trends of Web Services Adoption: A Synthesis Vincent C. Yen, Dept of Information Systems & Operations Management, Wright State University, Dayton, OH 45435, [email protected]

ABSTRACT The technology of Web Services has been a hot area in the software industry for many years. Surveys designed to get an answer of various kinds of questions such as why, when, how and where Web services are adopted and applied have been conducted in the past five years. Some of those survey results are available from the Internet. Since conducting a large scale Web services survey takes time and large financial support the research conducted in this paper is a synthesis from published survey results. All surveys indicate Web Services is moving along and will become a strong component of information systems infrastructure.

and reasons for adopting or not adopting this technology a research based primarily on what has been done and published on the Internet is conducted. The conclusions are drawn from the synthesis of such publications.

OBJECTIVES OF STUDY The objective of the study can be explained in the diagram below.

Web Services

INTRODUCTION For components to be reusable across different architectural environments new standards of integration and interoperability have been developed. The maturation of the Internet and the World Wide Web accelerates the idea for the global distributed computing. An important issue is how to make large number of heterogeneous application systems on the Internet interoperable. The answer is to develop standards, for example; CORBA, COM, DCOM, and Java/RMI initiatives. CORBA (Common Object Request Broker Architecture) is a specification defined by the Object Management Group, DCOM is an extended version of COM of Microsoft’s distributed common object model, and Java/RMI is the remote method invocation mechanism. However, these technologies are not compatible and difficult to use. The success of these standards is rated as marginal (Chung, Lin, & Mathieu, 2003). A recent approach to tackle the interoperability problem is XML-based Web services, or simply Web services. This approach uses Web standards of HTTP, URLs and XML as the lingua franca for information and data encoding for platform independence. Three XML-base protocols, one for communication, one for service description, and one for service discovery have become de facto standards or the core specifications. They are: • • •

SOAP (the simple Object Access Protocol) provides a message format for communication among Web services; WSDL (the Web Services Description Language) describes how to access Web services; UDDI (the Universal Description, Discovery, and Integration) provides a registry of Web services descriptions.

Additional standards that are essential for applications of Web services have been developed. Two major standards under the category of “Web services composition” are the Business Process Execution Language for Web Services (BPEL4WS) (Fischer, 2002) – called Business Process Execution Language (BPEL) later, and another competing standard the Business Process Modeling Language (BPML) developed by Business Process Management Initiative (BPML, www.bpmi.org). Programming tools are now available for creating and composing Web services. For example, BPEL4WS has been incorporated in Microsoft’s ASP.Net and BPML has been incorporated in JAVA. It is obvious that this technology could become a potential revolution in providing “services” within a company and on the Internet, and its impact might be paramount. To understand what the market trend is like

Business Applications

People

Technologies

Organization

Strategies Business value ERP, CRM, SCM Re-engineering RFID EDI Business Process and Workflow, etc.

Knowledge Skill Training Altitude of Acceptance, etc.

Platform Standards Etc.

Demographics Management commitment Security policy Etc.

Some survey questions of interest are to: • • • • • • • • • •

Find out whether companies are ready to adopt Web Services, and if so, with what timeframe. Find out what kind of Web Services will emerge, and how they will be distributed (payable or not). Find out about choices in terms of technologies and solutions. Identify the main technological drivers and threats. Identify attitudes and concerns of developers in their development efforts in the Web services. Where would Web Services be generating values for business? How much interest existed in applying WS to the supply chain operations? Readiness in using WS. What steps are taken to build company’s WS capability? Internet-Based Procurement About future uses of and barriers to Internet-based eCommerce activities.

Due to the limitations of available data it is difficult to find adequate answers to some of these questions, questions under “organizations” in particular. Nevertheless, published data do provide information to certain vital questions of interest. These areas are presented in the following sections.

REVIEW OF PUBLISHED SURVEYS The name of Web services was first mentioned by Bill Gates in July, 2000 (Levitt, 2001). Early surveys conducted beginning the year 2001 reveal some aspects of Web services adoption characteristics. This study does not use all surveys conducted in the past because they are either not easily available or they require huge fees for their reports. This study uses data

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Emerging Trends and Challenges in IT Management primarily published on the Internet free of charge. The form of the free survey results that are available often are announced as a piece of news, not a complete report. This form of data certainly has some limitations for interpretation. However, the data still have value when they are used collectively. In 2001, TechMetrix Research (2001) conducted a survey titled “Web Services Adoption & Technology Choices” among the subscribers of TechMetrix/SQLI’s TrendMarkers newsletters. A similar survey was conducted by them in 2002/2003 and was published in 2003 as an update. The responses come from various countries of the world. The survey contains information such as: company size, geographical distribution, job title, industry type. The aims of the study are to find out: readiness of Web services adoption, what kind of Web services will emerge, the main drivers and threats, technology choices and solutions. This paper will only use portions of data from these surveys.

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Top five responses are: standardization (60%), business process automation (59%), business flexibility (52%), operational savings (48%), better integration with business partners (43%). 2, If your adoption has fallen short of expectations, which of the following reasons best describes why? Top three responses are: Legacy systems couldn’t be cost-effectively integrated (50), cost more than expected (33%), introduced more complexity into IT system (36%). AMR (Vahidy, 2005) uses a survey to find how components of SOA were most used in actual deployments; here are only two items of interest to this paper: Web services (71 percent), and BPM framework (14). The survey also finds most companies (57 percent) have standardized on Web services as an SOA component.

FUTURE INVESTMENTS IN SOA Surveys done by Yakee Group of Boston in 2004 and 2005 reveal that

SURVEYS OF 2002 IDC has estimated that just 5 percent of U.S. businesses in 2002 had completed a Web services project. Borland Software conducted a survey among its users conference and results indicate that an unprecedented 80 percent of respondents are either currently using Web Services or are planning to use them in the very near future. Borland customers are using Web Services across many industries, but of those surveyed, a surprising 24 percent are in healthcare, 14 percent are in finance, and 14 percent are in government. As reported by Fontana (2002), the Hurwitz Group found in its Web Services Primary Research Opportunity Study, in which it polled 300 IT professionals, that 45% of companies are implementing Web services, while another 36% are testing the technology. When the two percentages are added it equals to 81% - a figure comparable to the survey by Borland. The results also show that 47% are using Web services for internal integration projects and 25% for external integration projects. Survey of CIOs by BEA Systems (Hayday, 2002) in Europe shows 54% of European companies adopted Web services, and 59% expect benefits. TechMetrix Research (2004) finds 26% have already started projects and another 26% are testing/prototyping. It may be said that there are 52% of respondents have projects in Web services when the two percentages are combined.

SURVEYS IN 2003 According to Mimoso (2004a), of 273 Global 1000 companies surveyed recently by Westbridge Technology, 37% are currently using Web services in production, and 26% plan either to deploy a Web service within six months or to complete a proof of concept. Of those using Web services, 70% are using them internally, while 48% are exposing them to the Internet for business-to-business transactions. In a survey conducted by IDC (2004), it shows about 61% of government organizations (central/local) are already using Web services.

SURVEYS 2004 Fifty-two percent of web services deployments have occurred in the United States, with the rest of the world accounting for the remaining 48 percent, the Radicati Group said in a report entitled “Web Services Market 2004-2008.” Europe accounts for 39 percent of all deployments this year, followed by Asia Pacific with 6 percent and the rest of the world 3 percent.

SURVEYS 2005 From Information Week (Babcock, 2005) survey, here are responses to two questions. 1.

What is your company’s business case for adopting an SOA or Web Services standards?

1. For 2005 (Mimoso, 2004), 75% plan on investing in the technology and staffing necessary to enable a service-oriented architecture; by industry the greatest investments in SOA are coming from the wireless telecom and manufacturing markets (78%), financial services (77%) and health care (71%). 2. For 2006 (Stansberry, 2005), the surge of SOA implementation in 2006 reaches saturation in many verticals: Wireless (93%), Retail (92%), Financial (89%), ? Manufacturing (76%), and Government (75%).

BENEFITS AND THREATS Surveys reviewed do have information on motivations and reasons for non-adoption. However, it is quite limited. Benefits and Technical Drivers • Standards compliance and interoperabilty • Scalability • Tools for development productivity • Tools for administration • Reuse services • Lower integration costs • Faster delivery of products • Making application development more flexible • Iincrease customer satisfaction and revenue • Important to business goals • They reduce the burden of internal and external integration. • They allow for true reusability. • They are a platform-independent facilitator, enabling data to flow across applications and systems. • They break down internal silos by providing information across traditional technological barriers. • Web services extend the life of legacy systems by extracting specific business processes, such as licensing and appointment and quoting, and making them available in new forms Threats • Security and authentication issues • Interoperability issues (e.g. non-compliant SOAP implementations) • Lack of standard Business Schemas • Service Level Agreement of WS providers • Lack of awareness in the business • Developing effective ROI cases • Standards compliance and interoperabilty • Scalability • Tools for development productivity • Tools for administration • General knowledge of SOA within their enterprise • Governing development standards within their enterprise

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1032 2006 IRMA International Conference CONCLUSION

REFERENCES

Publicly available survey results on the adoption of Web services are available in limited forms. Even though the data are limited they still contain valuable information. For example, by looking at “Using or building WS” data over time, there is a clear rising trend. In the years of 2001, 2003, 2004, and 2005, the percentages of major companies or organizations using and building Web services are 28, 52, 52, 70 (an average over three pieces of survey data). This ad hoc trend analysis should be indicative and reflecting the real world progresses. It would be interesting to compare with more formal approaches based on longitudinal studies. Another area the data reviewed has information on “what motivates or deters the users from using Web services”. That information is useful not only to end users but also to IT vendors. Other information contained in the survey but not extracted here are technologies used, industry group differences, etc. It is obvious that there are more research to be done in order to answer the research objectives set forth in the early part of this paper.

Babcock, Charles (2005). InformationWeek Oct. 31. Fontana, John (2002). Network World Fusion, 05/17/02 Hayday, Graham (2002). CIOs slowly turning to Web Services. http:// zdnet.com.com/2100-1106-960985.html. Jason Levitt, 2001, From EDI To XML And UDDI: A Brief History Of Web Services, Information Week, Oct. 1. IDC (2004). Western Europe, Government Sector, Web Services and New Technologies, Levels of Adoption and Investment Plans: An IDC Survey. www.idc.com. Mimoso, Michael S. (2004a). More enterprises exposing Web services to Net, SearchWebServices.com Mimoso, Michael S. (2004b). SOA prominent on 2005 budgets. Yankee Group of Boston, SearchWebServices.com. TechMetrx Research (2001). Web Services Adoption & Technology Choices Report. http://www.techmetrix.com/products TechMetrx Research (2003). Adoption of Web Services & Technology Choices, Version 2 – February 2003 Analysis of Survey Results. Stansberry, Matt (2005). Yankee Group: SOA everywhere by 2006, SearchDataCenter.com. Vahidy, Tamina (2005). The SOA Revolution. http://www.line56.com/ print/default.asp?ArticleID=7099 Webmethods (2005). Survey of 480 Global 2000 companies. www.Webmethods.com.

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Emerging Trends and Challenges in IT Management

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RFID: Risks to the Supply Chain Sanjay Goel, University of Albany, State University of New York, 1400 Washington Avenue, Albany, NY 12222, [email protected] Jakov Crnkovic, University of Albany, State University of New York, 1400 Washington Avenue, Albany, NY 12222, [email protected]

ABSTRACT Many businesses are incorporating RFID technology into the supply chain to improve efficiency and reduce errors, such as, late deliveries, excess inventory, and shortage of inventory. Application of this technology is very broad and is limited only by technological challenges in their design the cost of procuring them. In addition, there are several consumer concerns posed by RFID deployment, such as, privacy, security, and environmental damage. Thus far, issues with the introduction of RFID technology have been examined in isolation; a clear comprehensive view of the impact of the technology has not yet emerged. When considering RFIDs, companies typically perform a costbenefit analysis that incorporates the deployment cost and the productivity gains. Consumer concerns in deployment of this technology also need to be incorporated in the business analysis. This paper presents a scheme for comprehensively examining the risks of deploying RFID technology using a matrix-based approach.

INTRODUCTION Companies are increasingly adopting RFID technology for tracking goods and products, primarily through the supply chain (Sarma et al., 2003). RFID technology can be used to tag goods with special wireless sensors that respond to radio frequency probes allowing them to be detected without line-of-sight access. Coupled server data able to identify where and when the item was manufactured, how long and where it has been in the store (in the back room and/or on the shelf), its price history, its placement on the shelf (e.g. what was next to it), there is room for an in-depth analysis at several levels. Since RFID does not require direct contact or line-of-sight scanning, it provides a significant productivity advantage over traditional barcodes by allowing rapid inventory of products and providing real-time visibility to the supply chain. Technologically, a RFID system consists of three components: 1) an antenna, 2) a transceiver, and 3) a transponder (or tag). The transponder provides the data. Together, the antenna and transceiver collect and aggregate information. There are two types of RFID tags: 1) active, and 2) passive. Passive RFID tags do not have a power source and reflect the RF-energy of the receiver’s antenna. In contrast, active tags have their own power source that allows them emit RF-energy. In passive tags, the radio signal from the antenna activates the transponder, which then reflects the energy and transmits a radio signal back to the antenna. Passive tags have a lower overall cost and an indefinite lifespan because it is not dependent on battery life. Active tags can support higher data rates, increased processing speeds, and longer signal range from the tag reader to the tag. The potential of RFID portrayed in the literature is decidedly mixed. Quotes demonstrating apprehensiveness are easy to find, such as that by Shutzberg (2004): “We believe many early adopters have underestimated the cost of implementing RFID. Moreover, faster-than-usual technology obsolescence should make RFID costlier, as additional investments will be required to leverage evolving capabilities”. However, more optimistic views are also prevalent, such as that by Schwartz (2004): “RFID is going to change the way companies do business … it will give unprecedented visibility into the supply chain and will someday give companies the ability to make decisions while goods are in transit – decisions that could swing millions of dollars to the plus column”.

Implementation of any new technology comes with obstacles that need to be managed. Many important business challenges like establishing RFID Standards, ROI, and managing the explosion of data have been discussed in the literature (Holstein et al., 2005). While this technology has been touted to improve efficiency in the supply chain by streamlining operations and allowing inventory levels reduction, there are significant risks to using this technology that need to be considered while evaluating its incorporation into the supply chain. Threats include spoofing, physical destruction, eavesdropping, counterfeiting, and denial-of-service (Henrici & Müller, 2004). While the risks of this technology have been discussed extensively in the literature, work on aggregating these risks to estimate organizational exposure has not been done. In this paper, we will analyze these risks and present a risk analysis framework (Goel & Chen, 2005) to model the risks of using RFIDs in the supply chain. The framework computes the exposure of the organization due to threats exploiting vulnerabilities in the supply chain. The rest of the paper is organized as follows: Section 2 presents the methodology for analyzing the RFID risks, Section 3 presents the results of the analysis, and Section 4 presents the conclusions of this work.

RISK ANALYSIS Risk analysis is the process of systematically examining the potential losses that an organization can incur due to internal or external threats. Risk is often portrayed in terms of assets, threats, vulnerabilities, and controls where threats exploit vulnerabilities to damage assets and controls mitigate the impact of threats on the assets. The framework uses a series of matrices where assets, threats, vulnerabilities, and controls are collected, along with the probabilities correlating these parameters. Assets are items of economic value owned by an individual or an organization and can be of two types: 1) tangible assets (have a physical existence, i.e., cash, equipment, and people), and 2) nontangible assets (cannot be physically touched, i.e., a brand, trust, and employee morale). Vulnerabilities are weaknesses in an organization (e.g., security holes in software, security procedures, administrative controls, physical layout, internal process controls, etc.) that allow unauthorized access to information or disruption of operations. Threats are sources of harm, which can exploit vulnerabilities to cause damage to organizational assets. Controls are mechanisms that can be deployed to either eliminate or mitigate the impact of threats. The procedure that was used for risk analysis employs three matrices: 1) an asset-vulnerability matrix (data on the impact of a vulnerability on an asset), 2) a vulnerability-threat matrix (data on the potential of a threat exploiting a vulnerability), and 3) a threat-control matrix (data on the impact of a control on mitigating a threat). The data in the assetvulnerability matrix is aggregated and cascaded into the vulnerabilitythreat matrix, which is then aggregated to obtain a relative ranking of different threats. Controls can be also incorporated in the analysis by cascading the aggregate information from the vulnerability-threat matrix to the threat-control matrix and then aggregating the data to obtain the relative importance of different controls. The focus of this work is collecting data on assets, threats, vulnerabilities, and controls; gathering the coefficients of sensitivity among different assets, vulnerabilities, threats, and controls; and analyzing the data to determine risk

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1034 2006 IRMA International Conference posture and the impact of controls on mitigation of threats. More details on the procedure can be obtained from Goel and Chen (2005). RFID risks stem from several sources, which include: security, privacy, as well as failure of tags and readers. The fundamental problem in this work is the lack of data for effective quantitative valuation of the risk impacts of this technology. For some risks, such as the failure rates of devices (e.g. transponders and receivers), data is available from the literature. However, it is more difficult to obtain accurate values from non-tangible losses such as privacy, security, and consumer acceptance. This research will employ qualitative evaluation in the risk analysis. While RFID technology is evolving and the price of tags is gradually reducing, privacy and security requirements may require technology changes that will increase additional burden. Based on trends in the industry, RFID technology will soon be so pervasive that consumer advocates will force privacy legislation on the use of such identifiers. This would likely result in significant financial impact due to compliance requirements mandating periodic audits. In addition, the RFID systems installed today may become obsolete as the technology changes and new formats and tools emerge. This work will allow organizations to determine their organizational exposure and explore the feasibility of implementing RFID technology into their supply chains. By perturbing the variables in the risk matrices, sensitivities that reflect the impact of market changes on decision-making can be computed.

Table 2. Asset-vulnerability matrix

Table 3. Vulnerability-threat matrix

OBSERVATIONS FROM THE PILOT STUDY The observations presented here are based on a pilot study that investigates the key threats, vulnerabilities, and controls necessary for an organization, which intends to implement RFID technology into the supply chain. The final data set will be collected from different European company executives engaged in the Executive MBA joint program run by the Graduate School of Business Administration (GSBA) from Zurich, Switzerland and University at Albany. The complete data set will be reported in the journal version of the paper. The results presented here demonstrate the process followed to collect the data and to interpret the data. A series of matrices were used to collect the risk data, as discussed earlier. In the first step, the assets, threats, vulnerabilities, and controls were enumerated and added to the matrices. In the second step, the valuations were given in the matrices based on a scale of 0 (no impact), 1 (low impact), 3 (medium impact), and 9 (high impact). In the first matrix, the assets were collected and ranked, as indicated in Table 1. According to this table, reliability, productivity, communication, supply chain, and employee morale were determined to be the most important assets of the organization. Table 2 shows the asset-vulnerability matrix that relates the assets to the vulnerabilities of the organization. The relative ranking of different assets was transferred to the asset-vulnerability matrix from the asset table (Table 1). The relative impact of each of the vulnerabilities in exposing an asset was gathered from the users and the data was aggregated to compute the relative impact of different vulnerabilities. The most important vulnerabilities were determined to be management deficiencies followed by the supply chain and market competition. A surprising observation from this was that liability appeared to be a weaker

Table 1. Assets of the organization

Table 4. Threat-control matrix

vulnerability than most of the other vulnerabilities, especially since companies are becoming increasingly concerned about liabilities. The vulnerability-threat matrix (Table 3) contains the aggregated data from the asset-vulnerability matrix and data on the chance threats would exploit any vulnerability. The largest threat was determined to be defective RFID readers, followed by hacking, defective RFID tags, sabotage, and obsolescence of technology. Surprisingly, privacy-related issues and lawsuits did not surface to the top even though these factors are receiving the greatest attention in the press. The threat-control matrix (Table 4) shows that the most important control was middleware (software that manages data collection and security of the data). This was followed by the following categories: new legislation, RFID dismantler, and redundant server in order of importance. Research came relatively low even though the authors feel that significant research is required in order to ensure reliability of RFIDs as well as security and privacy of data collected through these sensors.

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Emerging Trends and Challenges in IT Management CONCLUSION

REFERENCES

The paper emphasizes the importance of aggregating the different risks of incorporating RFID technology in the supply chain. It presents data collected in a pilot test survey and shows the interpretation of a single data sample to give readers an understanding of the process of examining risks related to use of RFID technology. This approach is adaptable wherein new assets, threats, vulnerabilities, and controls can be added to update the risk posture. In addition, the results from this approach can be used for cost benefit analysis to determine the benefit of incorporating RFIDs in the supply chain. The journal version of paper will present the final set of matrices from the data collected in the test sample. A rationalization and some directions for the future needs in the RFID field will also be provided.

1.

2.

3.

4.

5. 6.

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Goel, S. & Chen, V. (2005). Information Security Risk Analysis - A Matrix-Based Approach. Proceedings of the Information Resource Management Association (IRMA) 16 th International Conference, San Diego, CA, May 2005. Henrici, D., and Müller, P. (2004). Tackling Security and Privacy Issues in Radio Frequency Identification Devices. A. Ferscha and F. Mattern (Eds.): PERVASIVE 2004, LNCS 3001, 219-224, 2004. Springer-Verlag Berlin Heidelberg. Holstein, W.K., Crnkovic, J., and Ribeiro, M. (2005) Management Issues in RFID Projects. Proceedings of the Information Resource Management Association (IRMA) 16 th International Conference, San Diego, CA, May 2005. Sarma, S.E., Weis, S.A., and Engels, D.W. (2003). RFID Systems and Security and Privacy Implications. B.S. Kaliski Jr. et al. (Eds.), CHES 2002, LNCS 2523, 454–469, Springer-Verlag Berlin Heidelberg. Schwartz, E., (November 29, 2004). RFID: Look Before You Leap. Information Week. Shutzberg, L. (November 1, 2004). Early Adopters Should Be Wary of RFID Costs. Information Week.

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1036 2006 IRMA International Conference

Course Management Systems: A Tool for International Student Collaboration Diane Boehm, Saginaw Valley State University, SE 123, 7400 Bay Rd., University Center, MI 48710, [email protected] Lilianna Aniola-Jedrzekjek, Poznan University of Technology, Pl. M. Sklodowskiej - Curie 5, 60-965 Poznan, Poland, [email protected]

University faculty around the world share responsibility to help their students learn how to interact and communicate successfully with those from other cultures. Since the beginning of this new century, the world has seen “the creation of a global, Web-enabled playing field that allows for multiple forms of collaboration—the sharing of knowledge and work—in real time, without regard to geography, distance, or, in the near future, even language,” according to New York Times bestselling author Thomas Friedman in The World is Flat (p. 176). Consequently, college students today must prepare themselves for such sharing of knowledge, as well as for work in a global marketplace, where highly educated and culturally aware knowledge workers will thrive, and where those who lack these capabilities will see their options shrink. Students can most successfully develop strategies for international collaboration, we believe, by actually engaging in such collaboration. One strategy to accomplish this goal is to design online collaborative projects involving students of different countries. Modern technological tools, such as course management systems, offer a structure that enables both synchronous and asynchronous student interactions to be conducted successfully. For the past several years, we have used the Blackboard course management system to conduct student online collaborative projects, linking students in writing courses at Saginaw Valley State University, a regional state university in Michigan, USA, with students in English language courses at Poznan University of Technology, Poznan, Poland. (PUT students are enrolled into the SVSU course.) Our collaborations have been marked by both challenges and rewards; the greatest reward has been seeing students learn firsthand about collaboration across cultures, even as they were learning more about themselves and their own culture in the process. The challenges can indeed appear formidable. When we have discussed past collaborative projects with colleagues from other universities, one experienced teacher indicated she had twice attempted similar projects; in both instances, “the students ended up hating each other.” Clearly this was not the outcome intended! Hashimoto & Lehu identify three special challenges for virtual working groups to be successful: careful attention to language and tone, given the lack of non-verbal cues; a need to develop rapport and trust when physical interaction is not possible; and agreement on a method to accomplish tasks in spite of individual and cultural differences. Our experience has identified a number of additional factors that must be taken into account when planning virtual crosscultural student collaborations to achieve desired outcomes. First and foremost is that many students have had limited experience working successfully in teams or groups; this is especially true of many international students, who come from a higher education experience with little or no emphasis on group functioning. Bosworth’s Taxonomy of Collaborative Skills (1994, p. 27) identifies five capabilities students need to collaborate successfully: • •

interpersonal skills to establish effective relationships groupbuilding/management skills to organize work and maximize participation

• • •

inquiry skills to elicit, clarify and critique ideas conflict prevention/resolution skills to handle inevitable differences that arise within a group presentation skills to synthesize and communicate information in various formats.

For virtual collaboration, technology skills are also required. Not all students will possess all skills, nor be equally motivated to develop them. Because group participation is inevitably uneven, group tensions may directly affect project success. Thus the course instructor would be wise to assess students’ skills and design course activities to develop needed abilities. These skills should also be taken into account when forming the crosscultural student groups and planning their interactions. Equally formidable are project timelines. Explicit timetables are essential if groups are to meet project deadlines. However, because universities in other countries function on a calendar different from the USA, semesters in different institutions may overlap by only 5-6 weeks, a very short period of time when students must progress from initial contact, to working together as a team, all the way through to presenting a finished group project. Time differences create further complications, making any synchronous communication difficult to schedule. Other obstacles may also present themselves. Whereas most US students have ready access to computers and the internet, that may not be true for students in all other countries. In addition, English language proficiency, a critical factor if work is to be conducted in English, may vary widely within any group of international students. (And unfortunately, few American students are fluent enough in another language to be able to conduct work in any language other than English.) These factors likewise must be considered when developing a collaborative project. Furthermore, there is always the challenge of developing an engaging, relevant assignment that will interest students from different cultures, be manageable for students at different levels of English language proficiency, and be able to be accomplished in the time allotted. Generally, we have had the most success with differentiated assignments, with each cultural group contributing different components to the collaboration. Polish students brainstormed ideas with US students, conducted research and developed summaries or bibliography annotations, responded to questions and drafts, located graphics, and created Powerpoint presentations. SVSU students also brainstormed ideas, conducted research and wrote summaries or bibliography annotations, then synthesized research from both groups, drafted documents, and developed edited text to be converted to Powerpoint presentations. Finally, there is the need to surmount cultural differences, differences which for most students will be invisible and intangible, but which could have significant impact on group success. Rains & Scott argue that for “globally dispersed virtual classroom teams, additional training is perhaps most needed to address cultural differences,” since “virtual team members are most likely to blame members from other cultures for problems” (p. 284). Since cultural characteristics are likely to be

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Emerging Trends and Challenges in IT Management invisible to those from any given culture, resources such as Culture, Leadership and Organization: The GLOBE study of 62 Societies may provide a starting point for instructors. To date we have been unable to locate any useful inventory of cultural characteristics that could be used to help students identify and understand cultural differences; such a tool would be invaluable, since it would help students learn about their own cultural biases as well as the many unique ways in which cultures may differ. All of the factors above, then, demand thoughtful consideration to lay the groundwork for effective collaboration. Based on our experiences with multiple international student collaborations over a period of several years, certain processes must occur during the interactions for a collaborative project to be successful: • • • • •

Build community within the group and establish group identity Generate ideas and determine project outcomes and tasks Arrange division of tasks Develop project materials, files, and presentations Evaluate outcomes.

Fortunately, course management systems such as Blackboard can provide a framework and tools with which to accomplish these tasks and provide a record of interactions, so previous interactions and conversations can easily be revisited. Though synchronous tools offer appealing immediacy, time differences as discussed previously necessitate that asynchronous tools will most likely be employed to enable the necessary processes of ongoing collaboration, as the chart below suggests:

Tasks Build community within the group and establish group identity Generate ideas and determine project outcomes and tasks

Arrange division of tasks

Develop project materials, files, and presentations

Evaluate outcomes

• • • • • • • • • • • • • • • • • •

Tools Personal webpages Posted video self- introductions Virtual chats (archived) Discussion boards Virtual chats Discussion boards File exchange Email Models posted to Course Documents Virtual chats Discussion boards Email Virtual chats Discussion boards Document file exchange Email attachments Powerpoint file exchanges Survey functions

As open-source course management software becomes more sophisticated and readily available, these functions may be expanded to include other technological tools, such as blogs, instant messaging, and voiceover Internet protocols (we plan to experiment with Skype in the future). If technology is available, we would also like to experiment with audio- and video-conferencing (e.g., Microsoft NetMeeting). All of these tools offer exciting possibilities, but require access, training for both instructors and students, and thoughtful integration into group

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processes. Nevertheless, it is exciting to envision the type of crosscultural interactive learning experiences we may be able to offer students in the near future. We hope also to identify or develop a cultural inventory that can be used to help students develop awareness of cultural characteristics and differences. Are virtual international student collaborations worth the extra investment of time, planning, and problem-solving we have described? We are convinced that such collaborations provide a learning experience unlike any other. Some problems are inevitable; these too provide a necessary learning experience. Ultimately, the multiple dimensions of such a learning experience will benefit students long after a course concludes. When we read students’ anonymous reflections on their collaboration experience (most recently, for example, from an SVSU class of first semester freshmen), we know that it was worth any extra effort. Students reflect on many discoveries: “the outside world pays more attention to us than we do them. People in Poland knew about our weather and disasters and everyday news”; “I never realized how much I didn’t know about other countries’ cultures and how much they know about ours. Yes, I know about current events happening overseas and historical events, but I don’t know much about the actual culture, such as their customs, language, traditions, etc. I was surprised when the Polish students even knew that Eminem came from Detroit”; “just talking with them a few times made me realize how different simple things are viewed in each culture! I am not that naive to think everyone is the same in all countries, but it never really hit home until this project began.” Student collaboration across cultures using virtual tools can be the first step to a lifelong experience of learning about and valuing people and cultures from every corner of the world.

REFERENCES Bosworth, K. (1994). Developing collaborative skills in college students. In K. Bosworth & S. J. Hamilton (eds.), Collaborative Learning: Underlying Processes and Effective Techniques (pp. 25-31). San Francisco: Jossey-Bass. Friedman, T. L. (2005). The World is Flat: A Brief History of the Twentyfirst Century. New York: Farrar, Straus and Giroux. Hashimoto, K. & Lehu, J. (2006). Students international collaboration project (SICP): A cross-cultural project using virtual teams to learn communication styles. In S. P. Ferris & S. Godar (Eds.), Teaching and Learning with Virtual Teams (pp. 221-244). Hershey, PA: Information Science Publishing. House, R. J., Hanges, P. J., Javidan, M., Dorfman, P. W., & Gupta, V. (2004). Culture, leadership and organization: The GLOBE study of 62 societies. Thousand Oaks, CA: Sage. Rains, S. A. & Scott, C. R. Virtual teams in the traditional classroom: Lessons on new communication technologies and training. In S. P. Ferris & S. Godar (Eds.), Teaching and Learning with Virtual Teams (pp. 268292). Hershey, PA: Information Science Publishing.

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1038 2006 IRMA International Conference

Implementing Educational Technology in K-12 Public Education: The Importance of Factors to Senior School Administrators in Pennsylvania Lawrence A. Tomei, Robert Morris University, Moon Township, PA David Carbonara, Duquesne University, Pittsburgh, PA

INTRODUCTION Use of Technology. The word “technology” has taken on several connotations during its relatively recent arrival in the middle of the 20th century. Technology has always been described from the perspective of hardware; specifically, devices that deliver information and serve as tools to facilitate a task and solve problems. From its initial ancestry, the definition of technology expanded in concert with the phenomenal increases in applications and further refinement to our collective understanding of how technology impacts teaching and learning. Technology and the Reality of Education. Between 1998 and 1999, the number of computers in the US schools increased 13 percent, and almost 80 percent of schools have Internet connections (Shelly, 2000). However, schools are experiencing difficulty in effectively integrating these technologies into existing curricula (Brand, 1998). The commitment to technology is incumbent upon all levels of all stakeholders involved in education. Administrators, teachers and parents, even the local community, must work together if learning is to benefit from technology. Yet, we all know from experience that it can very difficult to focus on integrating technology to support learning without overcoming basic technological equipment and facilities issues. Schools that serve students in economically disadvantaged areas typically have greater challenges than schools in more affluent communities. For some, buildings are so old that providing the necessary infrastructure is very difficult. For others, a lack of security is a problem manifested by outfitting computer classrooms with iron bars on outside windows. Schools in particular communities have severe access issues in part because of problems with basic electric service; many schools are simply unable to handle the additional load required by computer networks without major (expensive) modifications. Studies have found technology to be effective if it is embedded in other school improvement efforts (McNabb, 1999; Byrom, 1998; Goldman et al, 1999; and, Wilson & Peterson, 1995). Technology as a Teaching and Learning Strategy. Research investigations have also determined that technology contributes to raising student learning outcomes in two primary ways: (a) through active, meaningful learning and challenging collaboration, and (b) via real-life tasks involving technology as a tool for learning, communication, and collaboration (Jones et al, 1995). School boards are willing to spend money on preparing schools to be technology compliant, however, in today’s outcomes-based atmosphere, board members (and their constituents) expect tangible results. Research confirms that more computers, more hardware, software, and increasing the number of computer peripherals without giving teachers training hardly ever impact students. Many school districts have computers, laser disks, digital cameras, scanner and other technology

equipment that are only used by a very small percent of the faculty. “One of the biggest barriers to effective use of technology in education is the lack of professional development” (Norman, 2000). The Business of Technology. Many educators are convinced that once computers are installed and teachers trained, results are instantaneous (Crouch, 1999). Even with the best equipment, training, and intentions, this common misunderstanding concerning how long it takes technology to become a part of the school often creates disconnects among the many constituents of instructional technology. The business of using technology effectively in schools is more accurately reflected as a step-by-step process that takes considerable time and effort before manifesting itself. Involved in this intentional process are people, funding, and resources. Students, teachers, administrators, curriculum designers, technology coordinators, financial managers, and parents are only a few of the “people” with a vested interest in the business of technology. (Tomei, 2002). Likewise, the capital costs of hardware and software represent only the shell of technology funding that also embraces training, maintenance, and support and has propagated itself into the multi-billion dollar educational technology industry in the United States alone (Testimony to the US Congress, 1995). A close examination of any school’s comprehensive technology plan turns up a plethora of assets involved in a successful technology program. From facility planning to training programs to risk management and purchasing policies, technology is often defined in terms of its impact on resources. Some school leaders use computer technology in their personal, professional practice and thus believe that others should use it also. They may find that the use of technology creates a vehicle to share information, and a facility to collaborate. The technology skill may have a direct impact on their belief of the efficacy of computer use. This belief may affect their decision on how well technology is integrated into the classroom. “One cannot have a disposition without an associated skill” (Raths, 2001). In his article, James Raths discusses the relationship between dispositions and skills. He discusses beliefs as predispositions. However, some school districts believe that they are ‘doing’ technology when in reality, they are not. They create this façade of computer use. The question then becomes one of trying to identify why the façade exists. What are the practices of school district leaders integrating technology? What are the beliefs of school district leaders about technology use in school districts?

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Emerging Trends and Challenges in IT Management REVIEW OF THE LITERATURE Synopsis of the Literature Review: Four Key Studies Texas A&M University Survey of State-wide Technology Integration. Prior to a comprehensive study conducted by Texas A&M University in 2000-01, the Texas State Legislature accelerated the integration of technology into public education with a substantial infusion of funding into technology education. These efforts resulted in a considerable technology infrastructure throughout the state’s 812 districts. In an attempt to document, validate, and verify the robustness of their efforts, as well as isolate the key factors affecting successful technology integration into K-12 schools, Texas A&M University surveyed participating districts and posed the following questions (Texas A&M University, 2002): 1. 2. 3. 4. 5. 6.

What district policies affect technology resources and technology integration? What is the district’s present technology infrastructure? What level of district support is provided to assure technology sustainability? What level and kind of technology use occurs in the district? What level and manners of professional development are provided by the district? What technology outreach does the district provide to the community?

It was discovered that uninterrupted technology funding was the key concern for districts state-wide while teacher training ranked a close second. National School Boards Association (NSBA) Challenge Survey. During October 2004, the NSBA conducted an e-mail survey consisting of ten questions sent to 2,000 technology specialists, teachers, administrators and school board members. Specifically, the survey asked respondents’ opinions regarding: 1. 2. 3.

4. 5.

6.

What is the biggest challenge facing your school district in the area of technology? Please rate your school’s district’s K-12 curriculum in preparing students for the 21st century knowledge society? Are new teachers entering the classroom better prepared than in the past to effectively integrate technology into the classroom to improve academic learning? Has the use of technology in the classroom increased educational opportunities for your students? How has technology increased educational opportunities for students? Are they more engaged in learning; improved performance on tests; increased critical thinking skills; or stronger ability to communicate? Is home access to the Internet a problem for low income students in the district?

a.

If so, what steps have been taken to fix the problem for lowincome students?

7. 8.

How important has the federal E-rate program been in helping the school district set and meet technology goals? Would an Federal Communications Commission’s (FCC) decision to suspend new grants from the E-rate program impact your school district?

a.

Describe the impact in terms of dollars and programs.

More than 900 replies to the survey were received. Forty-six percent of respondents stated that integrating technology into the classroom is their major challenge while 47 percent identified technology funding. Six percent recognize closing the digital divide as their most challenging technology-related issue.

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Table 1. Critical Factors Affecting the Integration of Technology in K12 Schools: A Synopsis of Findings of Selected Studies Critical Factors (Selected Studies)

• • • • • • • • • • • • •

Technology funding Teacher training Integrating technology into the classroom Technology funding Digital divide Funding Teacher comfort level matching technological applications to particular subject areas Technology-based methods classes Cooperating teachers who support and encourage the use of technology Guidance for student teachers regarding available technology Use of technology tools for classroom teaching Use of technology at varying levels of academic student achievement

Twenty Factors (Technology Façade) 1. Technologies used by classroom teachers 2. Accessibility of computer facilities 3. Location of school computers 4. Classroom teachers’ applications of technology 5. Computer teacher expected to have lesson plans 6. Status of classroom curriculum software 7. Extent of teacher technology training 8. Extent of teachers participation on the technology committee 9. Extent of parents, community leaders, alumni, and students participation on the technology committee 10. Access to technology professionals 11. Technology Funding/ Budgeting 12. Teacher recognition program for technology development/ use 13. School technology plan 14. Contents/ coverage of school technology plan 15. Computers in school labs and classrooms 16. "Scope And Sequence" of student technology competencies 17. Teacher use of technology at varying levels of instruction 18. Learning objectives that include technology-based resources 19. Use of technology resources to present a lesson 20. Student experiences with computers classroom/ laboratory

Critical Factors in the Effective Use of Technology. The study conducted at Walden University by Laura J. Dowling and Darci J. Harland in January 2001 further confirmed certain critical factors for technology integration in the K12 environment. The authors found: availability of computers as a result of variable funding, teacher comfort level, and matching technological applications to particular subject areas were among their chief concerns. Factors Influencing Student Teachers’ Use of Technology. Brent, Brawner, and Van Dyk (2003) compiled a series of recommendations for maximizing the effectiveness of instructional technology programs in a K-12 environment. Their findings included the advantages of experiences with technology-based methods classes integrated throughout the entire student teacher preparation program; identification of cooperating teachers who support and encourage the use of technology in their own classrooms; explicit guidance regarding available technology in schools where student teachers are placed; implied expectations that at least two lessons will be delivered using technology tools; and, a commitment from student teachers regarding the use of technology at varying levels of academic student achievement. A recap of the critical factor found in these four studies is found in the left-most column of Table 1. The studies offered a review of the literature that produced an inventory of key factors appropriate for consideration by K-12 public school districts, classroom teachers, and higher education teacher preparation programs. However, these studies placed equal importance on each of the factors examined and did not attempt to isolate those most important to district decision-makers. In 2003, the Technology Façade was introduced to serve as a guide for the assessment of instructional technology in K-12 schools. The 20item checklist encompasses three critical elements: (1) the Use of Technology and its impact on teaching and learning in the classroom; (2) the Necessary Infrastructure that consists of people, financial

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1040 2006 IRMA International Conference investments, and resources; and, (3) the use of technology as a Viable Instructional Strategy for the classroom.

5 (with “1” being least important to “5” as most important) was used to assess each of the twenty factors of the Technology Façade.

Since its inception in 1996, the Façade checklist has provided an authentic assessment instrument for hundreds of schools and school districts seeking to advance more effective technology programs. Some of the Façade’s factors resemble closely those found in previous studies; others are unique to the publication. The right-most column of Table 1 depicts the 20 factors of the Façade and highlights (bold) common factors from the studies examined. With the possible exception of two characteristics found in the Factors Influencing Student Teachers’ Use of Technology study (Brent, Brawner, & Van Dyk, 2003) pertaining to the preparation of student-teachers the Façade checklist contained all factors considered relevant to a school district decision-maker. However, none of the studies, including the Façade, offered a perspective regarding the importance of factors or the weight they should carry when making decisions. That became the purpose of this study.

Data analysis began in November 2005 with conclusions and recommendations formed during December 2005. Analysis was completed and the required IRMA report provided to conference track on January 10, 2006. Initial results were presented for the first time at the IRMA 2006 International Conference.

Portions of the Teachers’ Attitudes Toward Information Technology survey were used as a survey instrument to determine the professional disposition of the respondent to the use of technology. This survey originated at the Texas Center for Educational Technology. Teachers’ attitudes toward computers is a Likert/Semantic Differential Instrument that measures attitudes on 7-20 subscales. It was developed by Rhonda Christensen and Gerald Knezek as part of the 1995-97 Matthews Chair for Research in Education project of the College of Education, University of North Texas (Knezek, 1997). “One cannot have a disposition without an associated skill” (Raths, 2001). In this article, James Raths discusses the relationship between dispositions and skills. He discusses beliefs as pre-dispositions. However, in all cases, change can occur and thus dispositions can change. The question for this study revolves around the relationship between technology practice and dispositions. Do relationships exist between the practice of technology implementation in K-12 schools and the role of technology disposition of leaders in school districts. Participants There are 501 school districts in the Commonwealth of Pennsylvania. For the most part, districts are governed by nine-member boards of directors elected by their respective constituencies to a four-year term of office. In Pennsylvania, the legal qualifications for school board membership require candidates to be an adult citizen of the state and reside in the school district that s/he services. In addition to such bare legal requirements, those wishing to serve as a school board member should possess certain basic qualities, including: a high standard of personal integrity; a broad viewpoint to be able to represent impartially all the people of the community; good physical energy, sound mental health, and social poise above the average; a profound interest in the welfare of all the children in the community; and, a willingness to develop a sympathetic understanding of the teaching and learning process as it involves the human relationships between teachers and pupils. (PA School Board Association, 2004). Beyond these minimal considerations, however, there are no requirements that board members possess a financial, technical, or educational background. While such responsibilities are implied in the administrative staff and professional staff of the district, board members are often asked to judge the acumen of very technical issues, not the least of which, include information and instructional technology. The Study The research sought to include an investigation of all 501 school districts including as many of the superintendents and approximately 4500 school board members as possible. A link to the online Web-Surveyor © questionnaire was sent to all 501 school districts in the Commonwealth of Pennsylvania via email addresses provided by the Pennsylvania Department of Education. District were asked to provide the web address to each of their superintendents and elected school board directors linking them to a short survey instrument in which a rating factor of 1-

FINDINGS Responses were received from 125 of the 501 school districts (25%) polled. Although email addresses were found for all districts state-wide, 40 districts (8.0%) were returned as incorrect or non-existent accounts and were forwarded to PDE for their attention. Of the responses received, the majority was completed by district superintendents (72.7%), followed by district administrators (17.4%), school board members (8.3%), and others (1.7%). As a result, the emphasis of this paper (which began as a look at factors critical to school board members) shifted to an examination of factors as they pertain more generally to senior school administrators as a whole. Critical Factors Affecting the Integration of Technology in K-12 Schools. Based on the distribution of responses taken from Question 2 of the online survey, it was found that eight of the 20 factors (40%) were identified by respondents as “extremely important” and received a concurrence rating exceeding 60 percent. As such, they were selected to represent the most important factors for consideration in the integration of technology. The results pertaining to critical factors of the questionnaire are depicted in Table 2. After plotting the responses indicating agreement that a particular factor was “extremely important,” it was determined that seven of the 20 factors were identified as critical to school district administrators. Factor 7, technology training for classroom teachers, outstripped the other items as the most significant factor for consideration, followed closely by Factor 3 which examined whether technologies are used by the teachers. The seven factors uncovered as critical decision-making criteria will hold in good stead any administrator seeking to promote an instructional technology program. In addition, respondents were given the opportunity to identify any additional factors for consideration. These included: correlation with student achievement (and overall evidence of student performance), teacher technology certification process, elimination of paper communications, state funding infrastructure, and use of grants to acquire funding to facilitate technology implementation.

Table 2. Descriptive Statistics from Critical Factor Questions Technologie s used by classroom teachers

Rati ngs Min Max Mea n Std Dev

Accessibility of computer facilities

Classroom teachers’ applications of technology

Computer teacher expected to have lesson plans

Status of classroom curriculum software

Extent of teacher technology training

Extent of teachers participation on the technology committee

Extent of participa tion on the technolo gy committe e

Access to technolog y profession als

F1

F2

F3

F4

F5

F6

F7

F8

F9

F10

66.7

40.2

70.5

66.4

51.6

55.4

76.0

61.5

35.2

50.8

0.0 498.0 116.0

1.0 235.0 95.5

0.0 522.0 115.17

0.0 492.0 114.83

0.0 384.0 107.0

0.0 408.0 110.67

0.0 558.0 116.33

0.0 456.0 112.17

0.0 234.0 98.67

0.0 372.0 108.50

199.15

110.20

104.1 7

154.46

Use of technology resources to present a lesson

Student experienc es with computers classroom / laborator y

Technology Funding/ Budgeting

Rati ngs Min Max Mea n Std Dev

Location of school computers

206.99

Teacher recognition program

School technology plan

196.18 Contents/ coverage of school technology plan

150.33 Computers in school labs and classrooms

167.64

"Scope And Sequence" of student technology competencies

221.34 Teacher use of technology at varying levels of instruction

180.40 Learning objectives that include technologybased resources

F11

F12

F13

F14

F15

F16

F17

F18

F19

F20

59.0

36.1

63.1

66.4

43.3

45.5

40.5

40.0

45.9

47.9

0.0 438.0 111.0

0.0 185.0 93.67

0.0 468.0 113.17

0.0 492.0 113.67

0.0 318.0 105.67

0.0 336.0 107.50

0.0 288.0 104.5

0.0 246.0 100.5

0.0 294.0 107.33

0.0 348.0 107.5

173.34

87.69

185.68

194.09

139.89

148.46

129.61

116.99

141.31

155.07

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Emerging Trends and Challenges in IT Management Table 3. Descriptive Statistics from Disposition Questions Technology helps me to organize my time

Mean

Technology increases my productivity

Technology solves more problems than it causes

Technology increases student learning

D1

D2

D3

D4

4.47

4.59

4.08

4.28

Technology increases communication between administrators

D5

4.64

Technology is use by the administrators to solve problems

D6

4.30

Technology relieves teachers of routine duties

D7

3.93

Technology relieves administrators of routine duties

D8

3.95

I like to use technology in my daily activities

I woul d be lost witho ut the techn ology I use

D9

D10

4.65

4.2 4 0.0 89 0.9 69

S.E.M.

0.066

0.055

0.091

0.067

0.053

0.063

0.080

0.085

0.053

Var

0.530

0.376

1.010

0.550

0.346

0.491

0.783

0.883

0.346

Critical Dispositions Affecting the Integration of Technology in K-12 Schools. Table 3 lists the descriptive statistics for the ten disposition questions. The Likert scale consisted of a range from one to five. The rank order of these ten place “I like to use technology in my daily activities” as the most agreed to statement, followed by “Technology increases communication between administrators”. The least agreed to statement was “Technology relieves teachers of routine tasks”. Administrators believe that technology helps the communication role of administrators, but does not affect teachers in the same way. All correlations were positive. This finding suggests that a non-inverse effect is in place. The disposition that possessed the most significant results was listed as, “Technology helps me to organize my time” followed by “Technology increases student learning”. These results may be interpreted as one of a positive belief of the effects of technology on administrator’s organization of their time and that technology can help children learn. These dispositions are linked to the importance of providing technology in the schools, to train the classroom teachers and that teacher participation are all related to supporting the use of technology to improve teaching and learning. This study was not a path analytic study, so no conclusions about which came first (disposition or school leader’s practice) can be made. The only inference we can make is that a positive correlation exists between dispositions, such as, Technology helps me to organize my time and school leadership items, such as, Classroom teachers use technology for: grading, lesson preparation , out of class assignments.

RECOMMENDATIONS FOR FURTHER STUDY Regardless of the respondents who participated in this study, further study specifically of school board members is needed before a conclusive statement can be rendered regarding the most important factors and dispositions for this particular category of school administrator. As described earlier, the emphasis of this paper shifted to an examination of factors as they pertain more generally to senior school administrators. The majority of the respondents (72.7%) were district superintendents while only 8.3% were actual school board members; the original target for this study. While investigators believe that the results will not be significantly different and that the key factors important to district superintendents will also be those most critical to school board decisionmakers, such claims cannot be made without further study which will be conducted as a follow-on to this paper. Disposition concepts need to be further defined. More information about dispositions, in general, is needed. There also exists a need to more clearly define the concept and facets of technology dispositions. We know that dispositions can come from a belief structure and that consistent and repeated practice can influence the development of dispositions. Perhaps a path analysis study of the beta coefficients and a factor analysis will help.

REFERENCES Brand, G. A. (1998). What research says: Training teachers for using technology. Journal of Staff Development, 19, 10-13. Brent, R., Brawner, C., & Van Dyk, P. (2003). Factors influencing student teachers’ use of technology. Journal of Computing in Teacher Education, 19(2), 61-68.

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Byrom, E. (1998). Factors that affect the effective use of technology for teaching and learning: Lessons learned from the SEIR-TEC intensive site schools [Online]. Available: http://www.seirtec.org/ publications/lessondoc.html Crouch, N. R. (1999). Best practices in K-12 technology. [On-line]. Available: http://iccel.wfu.edu/publications/others/ bp100899.htm Dowling, L.J. & Harland, D.J. (2001). Critical Factors in the Effective Use of Technology. Walden University [Online]. Available: http://www.dowlingcentral.com/gradschool/Edu6420/ project1.html Goldman, S., Cole, K., & Syer, C. (1999). The technology/content dilemma [Online]. Available: http://www.ed.gov/Technology/ TechConf/1999/whitepapers/paper4.html International Society for Technology in Education (2005). National Educational Technology Standards for Teachers: Preparing Teachers to Use Technology [Online]. Available: http:// cnets.iste.org/teachers/ Jones, B.F., Valdez, G., Nowakowski, J., & Rasmussen, C. (1995). Plugging in: Choosing and using educational technology. Washington, DC: Council for Educational Development and Research. Available online: http://www.ncrel.org/sdrs/edtalk/ toc.htm Knezek, Gerald (1997) Computers in education worldwide: Impact on students and teachers. Proceedings, 13th International Symposium on Computers in Education, September 22, Toluca, Mexico. McNabb, M. (1999). Critical issues in evaluating the effectiveness of technology. [On-Line]. Available: www.ed.gov/Technology/ TechConf/1999/confsum.html National School Boards Association. (October 27, 2004). Funding, Integrating Technology Into Classroom Top Challenges, Annual T+L2 Conference, Denver CO. [Online]. Available: http:// w w w . n s b a . o r g / s i t e / print.asp?TRACKID=&VID=2&ACTION=PRINT&CID=90&DID=34656 Norman, M. M. (2000). The human side of school technology. The Education Digest, 65(7), 45-52. Pennsylvania School Boards Association Executive Board, adopted Jan 16, 2004 [Online]. Available: http://www.psba.org/psba/ psbagoals.asp Raths, J. (2001). Teachers’ beliefs and teaching beliefs. Early Childhood & Practice: An Internet Journal on the Development, Care, and Education of Young Children. Shelly, R. W. (2000). From literacy to fluency in instructional technology: Taking your staff to the next level. NASSP Bulletin, 84(614), 61-70. Testimony to the US Congress, House of Representatives Joint Hearing on Educational Technology in the 21st Century, Committee on Science and Committee on Economic and Educational Opportunities [Online]. October 12, 1995. Available: http:// www.newhorizons.org/strategies/technology/dede1.htm Texas A&M University (2002). Technology and the Texas State Legislature: Barriers to Technology in the Classroom. Texas A&M University Library. Texas Center for Educational Technology (2005). Retrieved May 5, 2005 from http://www.iittl.unt.edu/IITTL/publications/ studies2b/ Tomei, Lawrence A. (2002). The Technology Facade: Overcoming Barriers to Effective Instructional Technology. New York: Allyn & Bacon Publishers. U.S. Advisory Council on the National Information Infrastructure. (1996). KickStart initiative: Connecting America’s communities to the information superhighway. New York: West Publishing. Available online: http://www.benton.org/publibrary/ kickstart/kick.home.html Wilson, B.G., & Peterson, K. (1995). Successful technology integration in an elementary school: A case study [Online]. Available: http:/ /carbon.cudenver.edu/~bwilson/peakview.html

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1042 2006 IRMA International Conference

ETMS-Web: A Low-Cost Innovative Solution to Manage the Sale Staff Anna Bruno, SOIN 2000 s.r.l., Via Marugi 7, 73100 Lecce, Italy, Tel: +39 0832 217504, Fax: +39 0832 711306, [email protected] Andrea Pandurino & Nicola Fiore Dipartimento Ingegneria dell’Innovazione, Università di Lecce, Via per Arnesano, 73100 Lecce, Italy, Tel: +39 0832 320229, Fax: +39 0832 320279, [email protected], [email protected]

ABSTRACT The growing competition in the marketplace, suggests companies to adapt continuously to the emerging needs and obliges them to provide more services in order to maintain a good position within marketplace. Thus, monitoring and auditing the different company fields, is the most important competitive element. For the pharmaceutical sector (strongly limited by law) the promotion activity has to be executed in a directly through the Sales Staff (Pharmaceutical Promoters) and its monitoring is very critical. The Electronic Territory Management Systems (ETMS) now existing, allow a good control on the Sales Force, but they are exclusively used by the main Pharmaceutical company (leaders on the marketplace), because of the high costs related to developing and maintaining them. In this paper we present SOIN 2000’s experience, that has realized the modeling of an ETMS web-based system (to be provided in Application Service Providing) in collaboration with University of Lecce. This solution allows, at a low cost, the small pharmaceutical company to provide advanced services to manage the Sales Force.

INTRODUCTION AND BACKGROUND The health marketplace is strongly regulated by law bounds that prevent pharmaceutical companies to advertise their product using conventional mass media channel for ethical products. Thus, the only way is the direct promotion activity made by sales force for medicals and health operators, the pharmaceutical companies real customers through the prescription of a therapy or a product to a patient. This promotion activity, based on the direct contact (the “visit”) between the promoters and the health operator, is fundamental. To improve the “visit” the company marketing management trains sales force in order to support its promotion activity. In the large company, marketing management is structured in different levels, hierarchical sorted, each of them is coordinated by a sales manager. The business structure varies for the different companies depending on the marketing strategy and on the typology of treated products.

created many opportunities to increase productivity and the efficacy for customer oriented actions. This evolution has leaded to PRM (Pharmaceutical Relationship Management): complex systems allowing company to acquire customer preferences in order to collect relevant information for marketing. A PRM’s system includes different activities such as managing the initiatives customer oriented, publishing of web sites centered on specific products, monitoring sales force activities, call center providing a support for customer interacting with pharmaceutical companies, Training, managing indirect sales (IMS sales)[1], managing direct sales. We present a case study on an Electronic Territory Management System (ETMS) which allows an adequate checking for the sales force activity. ETMS is used by the sales management resources (back-end) to assign objectives and contacts to the sales force (front-end) in order to have an automatic report on a visit. Given the fact that the main activity of promoters consists in making the visits at physician’s office, the use of devices such as mobile devices is desirable; promoter needs, in fact, to register the data about visits, consulting contacts list, annotating his vacations or work permits, visualizing the trend of work activity in order to achieve the assigned aims so he can re-plan the diary. The adoption of a centralized ETMS system allows the company not only to manage better the sales force, but also to promoters to organize better their activities; for example allowing to physician/customer to access the system it is possible to negotiate the promoters visits according to physician’s commitments. The Proposed Solution Many market solutions already exist to satisfy the requirements of an ETMS system. They are generally developed “in-house” by pharmaceutical companies with high costs for maintenance; on the contrary the small pharmaceutical companies, which needs a strong promotion and checking of the activities, is obliged to a manual manage of the system. The proposed ETMS solution, called ETMS-WEB, allows the small pharmaceutical companies to provide advanced service. In order to reach the more companies, the solution is web-based and use the multidevices (laptop, PDA) and it is in a modular structure.

Apart from the business structure, the promoter coordinators check the sales objectives. These links between the different levels in the sale force are the basis of the organizational structure.

To grant these advantages, the solution requires more attention during the design phase: designer has to manage all static and dynamic elements and has to see the inevitable interactions.

Because of the sales force activity is based on the visit, it results to be strongly connected to the territory, divided in different geographical areas (nation, region, province, brick, micro-brick) each of them assigned to one ore more ISF. Unlike the previous cases the territorial structure definition is the same for every pharmaceutical company.

So the use of suitable design methodologies has a fundamental importance. If there exist consolidated methodologies to develop traditional software, it is not true for the developing of web applications. We use the UWA [2] [3] (Ubiquitous Web Application) methodology to model ETMS –Web system because this is within the academic methodology, the only one separating the informative, navigational and presentation elements from which related to the operations. The use of UWA methodology allows to improve the system quality, the application efficacy and usability, the design process and the efficiency of the whole developing and maintaining application cycle.

ELECTRONIC TERRITORY MANAGEMENT SYSTEM The pharmaceutical companies invest money to introduce customer centered initiatives. The technology evolution related to marketing

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Emerging Trends and Challenges in IT Management The UWA Methodology UWA focuses on the user and models all the application considering his central position. After the indispensable phase of the Requirement Analysis, made following a goal-oriented approach, the methodology suggests a sequence of steps briefly summarizable in: •

•

• •

•

•

• •

•

For each stakeholders we have identified the high level goals and then these goals have been decomposed and detailed in order to define the system requirements.

ETMS-WEB MODELLING According to UWA, the requirements were collected through the requirements elicitation phase in which the stakeholders and the related objectives (called goals) are identified.

The main objective for Sales Management stakeholder is to increase the profit through an increasing of sales. In order to reach this objective, it is necessary to identify the possible contacts for the visits slicing them according to some characteristics such as prescription attitude, patients number, etc. An other objective is to organize adequately the sales force making attention on the training and optimizing the distribution on the territory and the physicians assignment to a promoter.

During the analysis phase, the use of stakeholder allows to obtain a global view of the. The only identification of the UML [4] actors who or what is interacting with domain of application (ETMS), results to be very limiting, on the contrary the stakeholder is who or what is involved or interested in a system even if it doesn’t interact with it directly.

The objective “distributing with the Back office that decided by the manager. continuously to verify the

The identified stakeholders for ETMS Web Application are: • •

Back-office Operator: he is a human back-office area resource. Configurator: he is a human resource belonging to back office or to the Software House and his task consists in the execution of start-up, adaptation customization of the system for a peculiar pharmaceutical company Certificator: he is a human resource belonging to back office whose task is the execution of the activities needed to validate the ISF proposed contact. Supervisor: he is a human resource belonging to Sales force executing management tasks Promoter: he is a human resource belonging to Sales Force executing the front-office activity (visit to physician’s office, promotion, etc.) Installator: he is a human resources with a technical profile executing the needed activities for booting and starting up the system.

•

Information Design describes the application information giving it a structured organization. Important features of this phase are that, during the construction of the information structure, the user point of view is held as fundamental. Navigation Design clears the most important aspect of hypermedia applications, reconsidering the information and its organization more typically from the viewpoint of its fruition, defining the user navigational paths. Publishing Design, using the results of previous steps, describes the application through “pages” and “fruition units”. Operations Design: it’s the step in which all the functional and transactional, being beyond the pure hypermedia paradigm, are modeled.

Software House X: it’s the ETMS-WEB application promoter to be proposed to the various pharmaceutical company Sales Management Area: it’s the decision making area of a pharmaceutical company, responsible for marketing strategies leading the sales force activity.

Sales Force on the territory” is in common have to insert and update the assignments The sales force activity has to be checked reachment of the established objectives.

After the requirements definition phase we have proceeded with the information model; the entities of the system, their semantic associations and their access structure have been defined.

Figure 1. Requirements Elicitation of the stakeholder “Sale Director” U Define the specific profile attributes Acquire new customers

Sales Management

Maximize the sales

Subdivide through the behavior

Trace the Sale Staff Activity

Planning the Sales Staff Planning the promotion

Empower Sales

U

C

Back-office Reporting the coverage, sequence and

Distribute the Sale Staff on territory

Assigning territory to Sales Assigning structures to Sales

Assigning contacts To Sales Force

Update Insert

O

Check the reached sale goals

Arranging training activities

Update associatio

Apply the targeting algorithm

U Define the weight of the targeting coefficient attributes

Define the U no-promotion activities Training Sales

U

Update associatio

U

1043

Insert association

U

U

Insert associatio

U

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1044 2006 IRMA International Conference Figure 2. Information Model In-the-large diagram Work in

[1..*]

[1..*]

Sale Staff

made

Made by

After navigation design we have defined both publishing and operation design and then the implementation phase has begun and it is not yet concluded. Operative Unit

[1..*]

Associated to

50:500,100

[1..*]

[1..*]

1:10,5

propose

[1..*]

[1..*] Is located in

Visit Made by 2000:25000,5000

No promotion Activities

Promote

Physician

[1..*]

100:5000,1000 1:100,10

Pharmaceutical company

Promoted in [1..*]

Product 10:1000,200

1:1

[1..*]

Associated to

Assigned to

[1.*]

Company Area 2:20,10

CONCLUSION AND FUTURE WORK According to the proposed project objectives, we have analyzed the different stakeholder’s needs through a complete Requirements Elicitation using a goal-oriented approach. Moving from this requirements elicitation and using UWA methodological, we have realized the design of ETMS-Web application. The UWA user centered approach allows to obtain a design aimed to the needs of each stakeholder so improving the application quality. Thus we have designed a low cost tool to check the sales force activity and easily adapting to each requirements. The design phase is infact allows to manage better possible evolutions or adaptations. At the moment we are in the implementation phase of the first ETMS-Web prototype. Once the implementation phase will be concluded, we have to realize a version of the tool compliant with different devices such as PDA or smart phone, in order to satisfy the mobility need of pharmaceutical products promoters.

The identified entities for ETMS Web Application are the following: • • • • • • • • •

Physician: this entity represents the physician visited by promoters Human resource: abstract entity specialized in sales force resource and back office resource Product: it represents the information related to pharmaceutical products proposed to physicians Operative unit: abstract entity representing information related to the structure or to the territory assigned to a promoter Pharmaceutical company: isolated entity representing the information related to the generic company Visit: it contains the information related to the visit to the physician’s office Company structure: it represents the information about hierarchy Task: contains the information about the specific tasks assigned to the different human resources Role: contains the information about the roles of the different hierarchical level within company structure (sales manager, area manager, etc.)

We show below an example for in-the-large modeling i.e. a general view of all the entities and semantic associations for the Sales Management considered user. Each entity is then detailed describing the slots (in the small modeling) For each entity we have realized the in the small diagram which allows to specify the information content through its components and slots. In figure 3 we can se as an example how the “sales force” entity is divided in components: personal data, career, objectives (information about the objectives such as n° of visits etc), curriculum. After having specified information design in-the-large and in-the-small an identified the access structures we have defined the navigation model.

REFERENCES [1] [2] [3]

[4]

A.A.V.V., http://www.imshealth.com. UWA Consortium. General Definition of the UWA Framework. Technical report EC IST UWA Project, 2001. L. Baresi, F. Garzotto, Paolo Paolini, From Web Sites to Web Applications: New Issues for Conceptual Modeling, Proceedings WWW Conceptual Modeling Conference, Salt Lake City, October, 2000. L. Baresi, F. Garzotto, and P. Paolini, Extending UML for Modeling Web Applications, Proceedings of 34th Annual Hawaii International Conference on System Sciences (HICSS-34). IEEE Computer Society, 2001.

Figure 3. In-the-small diagram of the “Sale Force” Entity

Sale Staff Personal Data 1

100:5000,1000

1

1

Carrier

Goal s

1

Curriculu m

Figure 3: In-the-small diagram of the “Sale Force” Entity

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Emerging Trends and Challenges in IT Management

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Knowledge Dissemination Using a Hybrid of Teaching Techniques: Lessons Learned from the Case of The American University in Cairo Khaled Dahawy & Sherif Kamel Dept of Management, School of Business, Economics & Communication, The American University in Cairo, 113 Kasr El Eini Street, Cairo, 11511, Egypt, {dahawy, skamel}@aucegypt.edu

ABSTRACT The aim of any teaching institute is to provide suitable environments to accelerate the learning process. The Experiential Learning Theory suggests that there is a relationship between the learning environments, learning techniques and suitable teaching techniques. Therefore, it is important to study these relationships to improve the learning process which is reflected on the outcome gained from the recipients of the knowledge disseminated. Learning and teaching techniques are classified into two groups: active-like (A-like) techniques and passive-like (Plike) techniques. Thus, the objective of this paper is to examine the importance level of these techniques and their relative implications, as well as their degree of preference. The methodology used is based on an empirical research with the use of a survey questionnaire where students studying courses in the department of management at the American University in Cairo as well as their professors were asked to complete a survey questionnaire to indicate the importance level for each technique.

INTRODUCTION Over the past two decades, the educational system has been undergoing a dramatic shift. Teaching has been moving from a “largely teachercentered, product-based activity, to a more student-centered, processbased activity. Rather than being passive learners, students are now encouraged to be active in the process or ‘experience’ of learning” (Mellor 1991). The question is whether this new student centered teaching style is appropriate for all students irrespective of their pedagogical preferences, or is there a need to tailor the teaching techniques to the needs of the students. Education like any other process found in life, has inputs and outputs. The input to the education process is teaching, while the output is learning. Therefore, the main objective of any instructor is satisfying the learner’s expectations. Instructors often use teaching techniques that they believe will help them achieve their desired objectives. These techniques include case studies, projects, lectures, and exams among others. Applying the same teaching technique(s) for a group of students with similar pedagogical preferences may be suitable, but it will be unsuitable if this group has different preferences. Consequently, the efficacy of a teaching technique will differ from one student to another; each student will have his own preferences. Both Johnson and Warner (1991) report that a teaching technique that is effective for one student might not be as effective as for another student. Several studies (Holland, 1989; Kolb and Fry, 1975; Witkin et al, 1977) indicate that fundamental differences in learning styles lead to differing pedagogical preferences, and individuals develop differing learning styles (Rodrigues 2004). Some students learn better through active-like (A-like) techniques, such as individual research projects, where students bear high responsibility

for learning while others learn better through passive-like (P-like) techniques, such as reading textbooks, where students bear low responsibility for learning. Hence, if an unsuitable technique is used, it may hinder the learning process. Thus, instructors should examine the teaching techniques, in order to use the most relevant ones that will help them achieve their objective, which is satisfying the learners’ expectations to learn best. This manuscript examines the importance level of ten teaching/learning techniques that are commonly used by students enrolled and faculty teaching at the department of management of the school of business, economics and communication of the American University in Cairo in the following concentration areas: business administration, marketing, accounting, finance, and management information systems. Both groups (students and faculty) were surveyed and were asked to rate the importance level of six passive-like and four activelike teaching/learning techniques which are demonstrated in table 1. It is important to note that Egypt is a developing nation, in the midst of developing its education processes. The existing status of education is relatively poor, where the educational quality suffers from lack of modern curricula and far less volume of teachers when compared to the number of students. Therefore, the outcome of high schools is usually students who expect the teacher to lead, and provide learning points; it is more or less a one-way teaching process where the teacher is expected to do all the talking and provide the complete structure. Thus, it might be arguable that students always prefer the passive learning techniques. The case of the American University in Egypt, established in 1919, combines the American liberal system in teaching with local educational requirements that cater for the cultural norms and values. The university has been the leader in Egypt and the region in over 80 years and it works on bettering the education system and changing the students’ attitude more towards the active structure and being more participative and more involved.

Table 1. Learning and Teaching Techniques Acti ve -like and Passive -like Learning/Te aching Techni ques Passive-like (B-Lik e) teaching/learning techniques § Lectures by instructors § Reading textbooks § Guest speakers § Videos shown in class § Classroom presentations by students § Co mputerized learning assignments Active-like (A-Lik e) teaching/learning techniques § Case studies § Individual research projects § Group projects § Classroom discussions

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1046 2006 IRMA International Conference The objective of this research paper is two fold: First, it clarifies the preference of the different teaching/learning techniques that may be used in different courses. Second, it helps professors and instructors in accurately selecting the technique that best suits their students’ preferences. The results of this paper can also be considered as guidance for managers in how to conduct training sessions for different disciplines. However, teachers also will find the results of this study beneficial as they will understand these teaching/learning techniques, and choose the most suitable one while communicating with their students.

Table 2. Organization of Full-Time Faculty Unit Accounting

Number of Faculty 4

Finance M anagement M arketing M anagement of Information System/Operations M anagement Total

4 5 5 5 23

THE AMERICAN UNIVERSITY IN CAIRO PROFILE The mission of the American University in Cairo (AUC) is to provide high quality educational opportunities to students from all segments of Egyptian society as well as from other countries, and to contribute to Egypt’s cultural and intellectual life. The university offers programs at the undergraduate, graduate and professional levels as well as an extensive continuing education program. The language of instruction is English. The university advances the ideals of American liberal arts and professional education and of life-long learning. As freedom of academic expression is fundamental to this effort, the university encourages the free exchange of ideas and promotes open and on-going interaction with scholarly institutions throughout Egypt and other parts of the world. The pursuit of excellence is central to the university’s mission, and the university maintains high standards of academic achievement, professional behavior and ethical conduct. Toward this end it also provides a broad range of disciplines and learning opportunities and strives to contribute to the sum of human knowledge. The university environment is designed to advance proficient use of the tools of learning as well as students’ thinking capabilities, language and personal skills. The department of management is dedicated to offering quality classroom instruction and to enhancing personal development through interaction among faculty and students. The faculty of the department of management maintains active involvement with the business community through applied research, consulting and training. The programs of the department prepare undergraduates for careers in business in Egypt, the Middle East and the global community. Graduates leave the program with the knowledge and skills necessary to function as professionals, entrepreneurs, and visionary leaders in the complex organizations of the 21 st century. Case studies, projects, and other pedagogical methods in most courses focus on organizations and the business environment in Egypt and the region. Additionally, the faculty and business leaders have developed a comprehensive list of competencies (values and attitudes, knowledge, and skills) that students are expected to attain before graduation. The department of management offers two undergraduate degrees; a Bachelor of Business Administration (BBA) and a Bachelor of Accounting (BAC). The department also offers an MBA with several concentrations. The management department has 23 full-time faculty organized into five units as indicated in Table 2. AUC may be unique in the world in its demand for a multicultural faculty. As part of its agreement with the Egyptian government, AUC strives to maintain diversity of background in its faculty by employing 45 percent Egyptian, 45 percent American and ten percent other nationalities. As of fall 2004, the distribution of the faculty by nationality was 51.9% Egyptian, 37.9% percent American and 10.2% other nationalities. During fall 2004 the management department at AUC had 636 students enrolled divided into 355 in BBA degree program, 119 in BAC program and 162 in MBA. Table 3, 4, and 5 show the classification of the students based on the citizenship of origin, and gender. Table 5 shows the classifications of the students enrolled in BBA depending on there area of concentration.

EXPERIENTIAL LEARNING THEORY The learning style refers to the components of individual differences that are important to knowledge and skills acquisition (Shade, 1989a).

Table 3. Citizenship of Department of Management Students, fall 2004 Country Canada Egypt Germany India Jordan Kazakhstan Korea Libya Nigeria Palestine Poland Qatar Ro mania Saudi Arabia Sri Lanka Sudan Syria Yemen Total

BBA 341 1 1 5 1

BAC 102

MBA 1 156

3 1 1 1 2

1

1 1 1 6 2 2 1 355

1

2 1 119

1 162

Total 1 599 1 1 8 1 1 1 1 3 1 1 1 7 2 4 1 2 636

Table 4. Gender of Department of Management Students, fall 2004

Male Fe male Total

BBA % Nu mber 100 28.2% 255 71.8% 355 100.0%

BAC Nu mber % 69 58.0% 50 42.0% 119 100.0 %

MBA Nu mber % 95 58.7% 67 41.3% 162 100.0 %

Total Nu mber % 264 41.5% 372 58.5% 636 100.0%

Table 5. Number of Students enrolled in BBA/Classified by Area of Concentration Finance Management Marketing Management of Informat ion System/Operations Management Total

116 97 121 21 355

People who share common historical and geographical settings adapt to the same set of environmental results and as a result they have a unique learning style (Shade, 1989b). Moreover, the characteristic of the learning style within a nation is usually enhanced through children development and their interaction with the educational system. A nation’s culture has a great impact on the preference of the teaching/ learning technique. For example, learners from Egypt as compared to Western learners hold different teaching preferences. Western learners prefer learning through active-like techniques; they learn through their own discovery (Punn 1989a, Punn 1989b, Jarrah 1998, and Ladd and Ruby 1999). On the other hand, learners from Egypt prefer learning through the passive-like techniques; they expect that teachers provide all the learning points and deliver much of the discussions in class. Some people want less control and prefer that the teacher provide structure, while other people want greater control and personal responsibility in

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Emerging Trends and Challenges in IT Management the learning process. Hence, there are many aspects of individual differences that shape the way in which one acquires knowledge and skills (Dunn et al, 1975).

Table 6 - Summary of the Relationships from Learning Abilities to Suitable Techniques

Experiential learning theory (ELT) defines learning as the process whereby knowledge is created through the transformation of experience (Mainemelis et al. 2002). Kolb 1984 states that knowledge results from the combination of grasping and transforming experience. ELT introduces two modes of grasping experience that are dialectically related; (1) Concrete experience and (2) Abstract conceptualization, and two modes of transforming experience that are dialectically related; (1) reflective observation, and (2) active experimentation. ELT states that individuals learning styles are determined by the individual’s way of resolving these two dialects. Kolb 1984 defines the four learning abilities as follows: •

•

•

•

An orientation toward Concrete Experience focuses on being involved in experiences dealing with immediate human situations in a personal way. It emphasizes feeling as opposed to thinking; a concern with the uniqueness and complexity of present reality as opposed to theories and generalization; an intuitive “artistic” approach as opposed to the systematic, scientific approach to problems. People with concrete experience orientation enjoy and are good at relating to others. They are usually good intuitive decision makers and function well in unstructured situations. The person with this orientation values relating to people and being involved in real situations, and has an open minded approach to life. An orientation toward Reflective Observation focuses on understanding the meaning of ideas and situations by carefully observing and impartially describing them. It emphasizes understanding as opposed to practical application; a concern with what is true or how things happen as opposed to what will work; an emphasis on reflection as opposed to action. People with reflective orientation enjoy intuiting the meaning of situations and ideas and are good in seeing their implications. They are good at looking at things from a different perspective and at appreciating different points of view. They like to rely on their own thoughts and feelings to form opinions. People with this orientation value patience, impartiality, and considered, thoughtful judgment An orientation toward Abstract Conceptualization focuses on using logic, ideas, and concepts. It emphasizes thinking as opposed to feeling; a concern with building general theories as opposed to intuitively understanding unique, specific areas; a scientific as opposed to an artistic approach to problems. A person with an abstract concept orientation enjoys and is good at systematic planning, manipulation of abstract symbols, and quantitative analysis. People with this orientation value precision, the rigor and discipline of analyzing ideas, and the aesthetic quality of neat conceptual system. An orientation toward Active Experimentation focuses on actively influencing people and changing situations. It emphasizes practical applications as opposed to reflective understanding; a pragmatic concern with what works as opposed to what is absolute truth; an emphasis on doing as opposed to observing. People with an active experimentation orientation enjoy and are good in getting things accomplished. They are willing to take some risk in order to achieve their objectives. They also value having an influence in the environment around them and like to see results.

Prior research (Rodrigus 2004, Fry 1978, Kolb 1077, and Bilgan 1973) indicated the presence of a strong relation between the learning ability orientation and the learning environment. People with abstract conceptualization learn best where learning is math based, hard, and paradigmatic (Symbolic Domain Environment). People with reflective observation ability learn best where learning is theory based (Perceptual Domain Environment), people with concrete experience ability learn best where what is learned is humanities based, soft, non-paradigmatic

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Learning Ability

Learning Environment

What is Learned

Outcome

Concrete experience

Affective domain

Hu manities based, soft, nonparadigmatic

Self-direction, and selfunderstanding

Reflective observation

Perceptual domain

Theory based, pure

Abstract conceptualizat ion

Symbo lic domain

Math-based, hard, paradigmatic

Emancipation fro m assumption, complete and complex perspective Order, mental coherence, and clear thin king

Active experimentation

Behavioral domain

Practical use, application

Specific, clearly defined, and practical goals

Learning Interests

Suitabl e Techni que

Marketing, and business administrati on concentratio ns

Activelike techniq ues

Accounting, finance, and management information systems concentratio ns

Passivelike techniq ues

(Affective Domain Environment), and people with active experimentation learn best where emphasis is on practical use and application (Behavioral Domain Environment). Kayes (2002) further posits the presence of a relationship between the learning ability orientation and the outcome. The outcome of active experimentation is the achievement of specific, clearly defined and, practical goals. The outcome of abstract conceptualization is order, mental coherence, and clear thinking. The outcome of reflective observation is emancipation from assumptions, complete and complex perspectives. The outcome of concrete experience is self direction and self understading. Rodrigus (2004) suggests that the Affective and perceptual domain environments prefer A-like teaching, while the symbolic and behavioral domain environments prefer P-like teaching. Based on this he posits that individuals with quantitative oriented interests (accounting, finance, and management information systems), relating to the symbolic and the behavioral domain environments would feel more comfortable with abstract conceptualization and active experimentation learning abilities. On the other hand, individuals with behavioral interests (marketing, management, and international business) relating to the perceptual and affective domain environments would feel more comfortable with concrete experience and reflective observations learning abilities. Table 6 represents a summary of the previously discussed relations. Based on the previous discussions, and since the objective of this paper is to examine the importance level of these techniques and their relative implications, as well as their degree of preference, the following hypothesizes are generated and tested. Preference of the active-like techniques • H1a.Students enrolled in the business administration and marketing concentrations will rate the active-like techniques higher than students enrolled in the accounting, finance, and management information systems concentrations. •

H1b.Faculty teaching in the business administration and marketing concentrations will rate the active-like techniques higher than faculty teaching in the accounting, finance, and management information systems concentrations.

Preference of the passive-like techniques • H2a.Students enrolled in the accounting, finance, and management information systems concentrations will rate the passivelike techniques higher than students enrolled in the business administration, and marketing concentrations

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1048 2006 IRMA International Conference •

H2a.Faculty teaching in the accounting, finance, and management information systems concentrations will rate the passivelike techniques higher than faculty teaching in the business administration, and marketing concentrations

RESEARCH METHODOLOGY The research method used included the use of a survey questionnaire among graduate and upper undergraduate students who are studying courses in the accounting and business majors in the American University in Cairo, as well as their professors. The objective of that questionnaire is to illustrate and examine the importance level of the ten teaching/learning techniques that were previously mentioned. The professors and students were asked to rate each technique on a Likertlike scale, ranging from “not important”, “a little important”, “somewhat important”, “important”, and “very important”. It was believed that most of the participants would have had experience with all the ten techniques, since they are at the graduate and upper undergraduate levels. The questionnaire is administered by 3 teaching/research assistants that will visit all the graduate and upper undergraduate classes in the management department in the American University in Cairo. The assistants will personally distribute the questionnaires in the classrooms and collect them after they are completed by the students. The assistants will visit each individual professor in his/her office and ask him/her to complete the questionnaire. The heading of the questionnaire stated that it is intended to measure the degree of preference of the professor, instructor or student, of the teaching methodology. In addition, the questionnaire will be distributed only to professors teaching courses, as well as students studying courses in the business and accounting majors in the America University in Cairo.

LIMITATIONS The findings of this research manuscript are restricted to graduate and undergraduate students at one university. There is a need to replicate this study in various schools and universities to make the results more generalized.

REFERENCES Biglan A (1973) The characteristics of subject matter in different academic areas, Journal of Applied Psychology, Volume 37 Number 2, pp. 195-203

Dunn R, Dunn K and Price G E (1975) Learning Style Inventory, Price Systems, Lawrence, KS Fry R E (1978) Diagnosing professional learning environments: an observational framework for assessing situational complexity, unpublished doctoral dissertation, MLR No. 387081, Massachusetts Institute of Technology, Cambridge, MA Hofstede G (1980) Culture’s Consequences: International Differences in Work-related Values, Sage, Beverly Hills, CA Holland R P (1989) Learner characteristics and learner performance: implications for instructional placement decision, in Shade, B.J.R. (Ed.), Culture, Style and the Educative Process, Charles C. Thomas Publisher, Springfield, IL, pp. 167-83 Jarrah F (1998) New courses will target transition to university, China Morning Post, 23 April, p. 28 Johnson H (1991) Cross-cultural differences: implications for management education and training, Journal of European Industrial Training, Volume 15 Number 6, pp. 13-16 Kayes D C (2002) Experiential learning and its critics: preserving the role of experience in management learning and education, Academy of Management Learning and Education, Vol. 1 No. 2, pp. 137-49 Kolb D A (1984) Learning Style Inventory Technical Manual, McBer, Boston, MA Ladd P D and Ruby R Jr (1999) Learning style and adjustment issues of international students, Journal of Education in Business, Vol. 74 No. 6, pp. 363-7 Mainemelis C, Boyatzis R E and Kolb D A (2002) Learning Styles and Adaptive Flexibility: Testing Experiential Learning Theory. Management Learning Volume 33 Number 1, pp. 5-23 Pun A S L (1989a) Developing managers internationally: culture free or culture bound? Symposium presentation at the Conference on International Personnel and Human Resource Management, Hong Kong, 13 December Pun A S L (1989b) Action learning in the Chinese culture: possibility or pitfall, paper presented at the 1989 Manchester International Human Resource Development Conference, Manchester Reynolds M (1999) Critical reflection and management education: rehabilitating less hierarchical approaches, Journal of Management Education, Volume 23, Number 3, pp. 537-53 Warner M (1991) How Chinese managers learn, Journal of General Management, Volume 16, Number 4, pp. 66-84 Witkin H A, Moore C, Goodenough D R and Cox P W (1977) Field dependent and field independent cognitive styles and their educational implications, Review of Educational Research, Volume 47, Number 1, pp. 1-64

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Emerging Trends and Challenges in IT Management

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Potential Weaknesses in Risk Assessment for Business Data Communications Philip Irving, Sonia Tindle, & John Tindle University of Sunderland, School of Computing & Technology, David Goldman Informatics Centre, St. Peter’s Campus, SUNDERLAND, SR6 0DD, UK, T: +44 (0)191 5152752, F: +44 (0)191 5152781, {philip.irving, sonia.tindle, john.tindle}@sunderland.ac.uk

ABSTRACT

FAILURE OF CURRENT RA METHODOLOGIES

Initial research presented by the authors in 2003 suggested that a particular area in ICT is excluded from current risk assessment processes - the point where Systems Development (SD) and network engineering overlap. Extensive on-going research has confirmed this gap and risks it poses to both Business Data Communications and SD. The lack of existing relevant literature supports this view. Preliminary results from an empirical survey indicate that neglect of this area allows risks to threaten SD/change.

Effective control relies upon network failure being identified as part of the software or systems change RA process. Extensive literature searches by the authors and MSc students indicate that it is unlikely that current SD/change RA methods would identify such risks (Velde, 2002; Irving and Edwards, 2003; Irving, 2004; Chew, 2005). Similarly, it is unlikely that acceptance testing would flag up problems. While network impact may be included in the test criteria, it would be difficult to assess before the end product had been produced (Zeed, 1996).

INTRODUCTION Current RA methods often approach the evaluation of computer systems from a socio-technical perspective, overlooking sub-systems. One sub-system that we believe is often neglected is the network. Corporate networks are arguably the single most important sub-system of all; data flows represent the life-blood of an organisation and any interruption will have serious implications. While such network failures normally fall outside the project manager’s influence, they may cause his software systems to under-perform or fail to operate. This paper updates previous work by Irving and Edwards (2003).

RA AREA OF OMISSION The IT industry has an unenviable record for unsatisfactory systems development projects. In 1995 US companies alone spent an estimated $59 billion in cost overruns and another $81 billion on cancelled software projects (Johnson, 1995). Five years after publication of Boehm’s (1987) initial work, equally surprising was that few organisations used formal RA (Griffiths & Wilcocks, 1994). Software RA attempts to address these issues. Literature within network RA is mostly security related (Myerson, 1999), reflecting the priority most organisations assign to maintaining data privacy and security. However, equally important is the need to ensure easy access to that data. One of the most feared security threats is the Denial of Service (DoS) attack where the organisation is denied access to its network and data (Irving, 2003 and 2005; Myerson, 2002), usually with catastrophic effects (Glennen, 1997). Preventing such attacks is one of the key objectives of network security (Lewis et al., 2003). An application which requires more than the available bandwidth will flood the network with data, forming queues at key networking devices. As the buffers fill, packets will be dropped in an attempt to throttle back the network traffic, giving the same symptoms as a DoS attack (Cisco, 2004). Quality of Service (QoS) would be unlikely to aid the problem unless the offending application is given a lower priority (Cisco, 2004b). It is unlikely too that network design would highlight the problem. After initial design, maintenance of the network is a somewhat iterative process: reviewing traffic flows, then predicting and planning for network growth.

Of the main published software RA methods, only RiskIT and SERUM could possibly identify the networking risks. Even here, specialist knowledge would be required by the teams. Unfortunately, these methods don’t mandate such knowledge or staff in the project teams (Irving 2004).

PRELIMINARY FINDINGS The literature surveys confirmed the need for RA identified by Hall (1998) and the authors have clearly shown that there is a gap where network and software RA overlap. An empirical survey is currently being undertaken in a large not-for-profit organisation in the North East of England to determine practice in this area. Stratification (Kendall and Kendall 1992) was used to determine appropriate layers to survey and the investigation was undertaken via interviews over a one month period. All software bought or developed runs on the network, making network performance critical to project success. At the organisation level, all major business systems are procured. Of the non-major business systems, 50% were developed in-house with the remaining 50% being bought in. Budgets ranged up to £300,000 (including hardware) with the typical budget being between £15k and £50k. Larger systems (up to £2m) were procured by specially formed project teams. As with most organisations, the financial risks of a failed project are formidable. It was found that RA was unusually high on the agenda of the organisation as a result of recent audit criticism. Such RA was mainly operational but some had filtered down to project level. A client-led project focussed approach is used; the client department establishes the project and the central IT team work as “contractors”. Control is via fortnightly progress meetings. Projects are managed through a subset of the PRINCE methodology (Prince 2005). Risks are identified through brainstorming and recorded on a risk identification sheet very similar to the SEI/SRE model (Sisti 1994). There is no specific toolkit for the identification of risks such as that found in the RiskIT method (Kontio 1997). Further, RA takes place as part of the project rather than before its inception, unlike methods such as RAMESES (Edwards 2000). The brainstorming technique is not iterative and relies on all risks being identified by team members. Risks are then graded by their impact and likelihood of occurrence for subsequent management. Such an RA technique would be unlikely to identify networking risks which is evidenced even with the inclusion of a networking professional

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1050 2006 IRMA International Conference in the project team. There is evidence to suggest that not all risks are identified. Nevertheless, this approach seems to be successful, with the majority of projects coming in on time and in budget compared to only 30% found by OTR (1992). However, funding and timescales are tightly linked to specific budgets which is likely to be jeopardised if the project overruns. At the departmental level SD was undertaken piecemeal with no formal RA. Whilst the projects developed at this level weren’t mission critical, they did reside on the network alongside mission critical applications and had the potential to wreak havoc. It was found that network RA appears to be limited to verifying that the proposed solution speaks IP and will operate with the network devices. No attempt is made to determine how much additional traffic will be placed on the network and whether the network will be able to cope with the additional load. Where the system is a replacement, there is an assumption that the new system will use the same amount of bandwidth as the old. As we are moving more towards web based applications and seeing a change from the old 80/20 rule where 80% of network traffic was local to the new 80/20 rule where 80% of traffic traverses the corporate backbone (Irving 2005), this is an unreliable assumption. Additionally, no baseline data exists of network performance (other than the network backbone) and no trials are carried out to determine bandwidth required by the new application. Even during installation no measurements are taken pre/post installation. Although there have been no catastrophes, there is evidence to suggest that some applications are performing worse on the live network than they were on a private network, despite backbone measurements suggesting a maximum of 40% utilisation. This was identified during one large project which trialled the software on a private network first. Fortunately the new system, even though impeded by the network, still performed better than the system it replaced. To the users, therefore, it represents a step forward.

CONCLUSIONS Clearly RA is desirable in SD/change (Hall, 1998). Yet evidence (Standish 1995), suggests that it is not widely practised and that software projects continue to be a problem. There are many reasons for this from the difficulties inherent in SD projects (BSI, 1995) to the difficulties in applying the RA techniques, yet there are clearly enormous benefits to their application. Since the beginning of the 1990’s a number of RA methods have been developed which address a wide range of SD problems. A thorough review of each of these methods found that there was a general lack of support for network RA for systems change. Similarly, thorough reviews of network RA revealed almost no treatment apart from minor consideration by Myerson (2002). In today’s competitive environment, organisations cannot afford to be risk averse; instead, they are forced to take risks to gain a competitive advantage (Neumann 2000). Thus RA and management are crucial to the well being of the organisation. Early evidence from our empirical survey clearly demonstrates that even a formal project management method and the addition of a member of networking staff to the project team is insufficient to identify all of the networking risks. This suggests the need for a formal method or toolkit such as that in the RiskIT approach (Kontio 1997). Overall we conclude that there is a need for network consideration during the RA phases of SD projects, that risks do go unnoticed by current practice and do impact upon end system performance. The results obtained so far in this survey have led us to believe this is indeed a weakness in the SD/change process worthy of further investigation.

REFERENCES Boehm, B.W. (1987), “Improving Software Productivity”, IEEE Computer, pp 43-57, May, 1987. Chew, B. (2005). Network Risk Assessment. MSc Dissertation, University of Sunderland 2005. Cisco Systems (2004). Building Scalable Cisco Internetworks. Cisco Press 2004. Cisco Systems (2004b). Building Cisco Advanced Switched Networks. Cisco Press 2004. Edwards et al. (2000) “The RAMESES method: Decision support for systems change in SMEs (a guide for SMEs). University of Sunderland. Glennen, A. (1997) Computer Insurance – the only constant is change. Insurance Brokers’ Monthly and Insurance Adviser 47, 12 (1997), 11-13. Griffiths, C. and Willcocks, L. (1994) Are Major Information Technology Projects Worth the Risk?, Oxford Institute of Information Management/IC-PARC, Imperial College, 1994. Hall, E. M. (1998) Managing Risk: Methods for Software Systems Development.1998 Addison Wesley. Irving, P. J. (2003). Computer Networks. Learning Matters, London. ISBN: 1903337062. Irving, P. J. and Edwards, H.(2003) Network Risk Assessment for Systems Change. International Research Management Association (IRMA) 2003. Irving, P. (2004). Network Risk Assessment for Systems change. MSc thesis. University of Sunderland. Irving, P. (2005) Computer Networks 2 nd Edition. Lexden Publishing, Ipswich, UK. ISBN: 190499508X Johnson, J. (1995) Chaos: The dollar drain of IT project failures. Applic. Dev. Trends 2, 1 (1995), 41-47 Kendall, K. E. and Kendall, J. E. (1992). Systems Analysis and Design. 2nd Edition. Prentice-Hall editions. Prentice-Hall International ISBN: 0-13-880907-0. Kontio, J. (1997) The Riskit Method for Software Risk Management, Version 1.00. CS-TR-3782 University of Maryland (can be downloaded from http://mordor.cs.hut.fi/~jkontio/riskittr.pdf) Lewis, W. (2003) An Empirical Assessment of IT Disaster Risk. Communications of The ACM September 2003/Vol. 46, No. 9ve.x Myerson, J. (1999). Risk Management . International Journal of Network Management Vol 9, Pages 305-308. Myerson, J. M. (2002) Identifying Enterprise Network Vulnerabilities. International Journal of Network Management. Volume 12, Pp 135-144. Neumann, P. G. (Editor) (2000). Risks to the Public in Computers and Related Systems. ACM Sigsoft, Software Engineering Notes vol. 25 No. 4. July 2000 Pp 7-11. OTR Group, Computer Weekly, Dec 12th, 12, 1992. Prince 2005. http://www.ogc.gov.uk/prince2/ last accessed 22/11/05. Sisti, F. and Joseph, S. (1994) “Software Risk Evaluation method v 1.0”, Software Engineering Institute Technical Report, CMU/SEI-94TR-19, SEI, Pittsburgh, PA., Dec. 1994.Standish Group, “CHAOS report”, 586 Olde Kings Highway, Dennis, MA 02638, USA, 1995. Velde, N-H. (2002). Risk Assessment of Network and Systems Changes. MSc IT Management Project, University of Sunderland, UK. Zeed, HM (1996) Modelling the maintenance process at Zurich Life Insurance. 12th International Conference on Software Maintenance (ICSM’96)

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The Safety Effect of the Red Light Running Cameras: Applying Data Mining Techniques Using Fatality Analysis Reporting System (FARS) Data Scott Solomon, Jay Liebowitz, & William Agresti Dept of Information Technology, Graduate Division of Business & Management, Johns Hopkins University, 9605 Medical Center Dr., Rockville, MD 208050-3332, [email protected], {jliebow1, agresti}@jhu.edu Hang Nguyen, Dept of Information Technology, Graduate Division of Business & Management, Johns Hopkins University, 9605 Medical Center Dr., Rockville, MD 208050-3332, & GEICO Student Scholars in Discovery Informatics, [email protected]

ACKNOWLEDGEMENT The authors gratefully acknowledge the grant and support from the GEICO Educational Foundation, David Schindler, and Karen Watson for the GEICO Scholarship in Discovery Informatics.

to increased traffic rates. “The study found that rear-end crashes rose 15 percent at camera locations. But because broadside crashes are more dangerous and cause greater damage, the study concluded that the cameras can help reduce the costs of traffic accidents” (Wilber & Willis, 2005).

Initially, our paper reviews prior literature and techniques on the effectiveness of red-light cameras in terms of traffic accidents, injuries, fatalities, red-light tickets, and cost. We then apply data mining techniques to examine the data stored in the U.S. Department of Transportation’s key database on vehicle fatalities to try to tease patterns and rules related to red-light controlled intersections.

But there are some limitations in the study. First, it doesn’t account for spillover effects, where the benefits of cameras at some locations can be reflected at sites without cameras. Second, the study blames the city for focusing solely on revenues, even though the city was acting in the interest of public safety because data showed initial improvements, prior to the long-term study presented by The Washington Post and the city had not expanded the program significantly prior to the results of a longterm study (Wilber & Willis, 2005).

2. LITERATURE REVIEW

3. DATA MINING

1. INTRODUCTION

From 1992 to 2000, the number of fatal crashes at signal-controlled intersections in the United States increased by 19 percent (IIHS, 2001). Red light running (RLR) was the single most frequent cause of these crashes, as pointed out by the Insurance Institute for Highway Safety (IIHS, 2001) and equivalent to more than three times the rate of increase for all other fatal crashes during the same period. According to the Federal Highway Administration (FHWA), crash statistics show that nearly 1,000 Americans were killed and 176,000 were injured in 2003 due to RLR related crashes. The monetary impact of crashes to the society is approximately $14 billion annually (FHWA, 2005). The California Highway Patrol estimates that each RLR fatality costs the United States $2,600,000 and other RLR crashes cost between $2,000 and $183,000, depending on severity (CA Bureau of State Audits, 2002). A 2005 study conducted within the District of Columbia by Wilber and Willis (2005) showed remarkably different results than most of the other studies: “The analysis shows that the number of crashes at locations with cameras more than doubled, from 365 collisions in 1998 to 755 last year. Injury and fatal crashes climbed 81 percent, from 144 such wrecks to 262. Broadside crashes, also known as right angle or T-bone collisions, rose 30 percent, from 81 to 106 during that time frame. Traffic specialists say broadside collisions are especially dangerous because the sides are the most vulnerable areas of cars” (Wilber & Willis, 2005). The study argues that crashes and injuries may have increased despite or because of the red light cameras. Some of this increase may be related

In response to the controversy of whether it’s ultimately a safety tool to reduce red light running and traffic crashes, our research applies data mining techniques to traffic data collected in Washington D.C. and Maryland to determine the supporting data patterns. Traffic data has been collected from the U.S. Department of Transportation’s Fatality Analysis Reporting System (FARS) database (see Table 1). Based on our analysis, data mining techniques have not been used in the past to evaluate the effectiveness of red light camera enforcement. Our study applies data mining techniques to contribute to past research. For our research, we narrowed the data to the years 2000-2003 and for only Maryland and Washington DC. First, we limited data to all fatal crashes where a violation for red-light running was charged. Second, we limited the original data to fatal crashes at signal- controlled intersections, whether a ticket was issued or not. We used C5.0, C&RT and CHAID decision tree models, as well as K-Means and Neural Network models for the data mining analysis. As indicated by the results of K-Means Models, car collisions are more likely to happen on Fridays and Sundays. Types of car crashes involved in running red lights are mostly rear-end crashes and angle front-to-side collisions, as 1,517 cases and 890 cases were recorded, respectively. On the other hand, results of Neural Network Models show the relationships between fatal crashes at red-light-signal controlled intersections and harmful events, and between fatal crashes at red-light-signal controlled intersections and the manner of collision. The strongest relationship is a collision with another moving object, most likely another vehicle. The second strongest link is between fatal crashes and pedestrians. With the respect to the nature of the crash, the strongest relationships are angle and front-to-side collisions.

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1052 2006 IRMA International Conference Table 1. FARS Major Variables Used in Our Data Mining Application Variable VIOLCHG1 or VIOLCHG2 or VIOLCHG3

Description Violations Charged (99 factors)

DAY_WEEK

Date of the crash/accident

HARM_EV

First harmful event applies to the crash. (50 events)

M_HARM

The most harmful event variable applies to the vehicle (50 event) Manner of Collision

MAN_COLL

Examples Used 1 Fail to Stop for Red Signal 2 Fail to Stop for Flashing Red 3 Violation of Turn on Red 4 Fail to Obey Flashing Signal (Yellow or Red) 5 Fail to Obey Signal Generally 6 Other 1 Sunday 2 Monday 3 Tuesday 4 Wednesday 5 Thursday 6 Friday 7 Saturday 8 Unknown 1 Traffic Signal Support 2 Fell from Vehicle 3 Thrown or Falling Object 4 Culvert 5 Curb 6 Unknown 0 Not Collision with Motor Vehicle in Transport 1 Front-to-Rear (Includes Rear-End) 2 Front-to-Front (Includes Head-On) 3 Angle - Front-to-Side, Same Direction 4 Angle - Front-to-Side, Opposite Direction 5 Angle - Front-to-Side, Right Angle 6 Angle - Front-to-Side/Angle-Direction Not Specified 7 Sideswipe - Same Direction 8 Sideswipe - Opposite Direction 9 Rear-to-Side 10 Rear-to-Rear 11 Other (End-Swipes and Others) 99 Unknown

For future work, our data was not specific to intersections and further research is being conducted to examine violations before the camera is installed, a short time lag after the camera is installed (6 months – 2 years), and after a significant time period has passed after the camera is installed (5 – 10 years).

REFERENCES AND BIBLIOGRAPHY Berry, M., & Linoff, G. (2004). Data Mining Techniques. Indiana: Wiley. Blakely, L. (2003). Red-Light Cameras: Effective Enforcement Measures for Intersection Safety. ITE Journal, v. 73, no. 3, 34-6, 43. California State Auditor Bureau of State Audits Red Light Camera Programs (2002). Although They Have Contributed to a Reduction in Accidents, Operational Weakness Exit at the Local Level. Sacramento, CA. Federal Highway Administration (2005). Red Light Camera Systems – Operational Guidelines. U.S Department of Transportation, Washington, D.C.

Flannery, A. & Maccubbin, R. (2002). Using Meta Analysis Techniques to Access the Safety Effect of Red Light Running Cameras. TRB 2003 Annual Meeting. Hevesi, A. (2001). Read Means “Go”: A Survey of Red Light Violations in New York City and Red Light Camera Usage in Other Major Cities. Report by the City of New York. Office of the Comptroller. Office of Policy Management. Hunter, C. (2003). Red Light Running in Rhode Island. URITC Project No. 536146. Institute of Transportation Engineers (1999). Automated Enforcement in Transportation. ITE Informational Report. Insurance Institute for Highway Safety (IIHS) (2000). Status Report. Vol. 35, No. 3, Arlington, VA. Insurance Institute for Highway Safety (IIHS) (2001). Automated Enforcement Myths. Retrieved from the WWW: http:// www.hwysafety.org/research/topics/myths.html Lum, K.M. & Y. D. Wong (2003). Impacts of Red Light Camera on Violation Characteristics. Journal of Transportation Engineering, v. 129, no. 6, p. 648-56. Lum, K.M. & Y. D. Wong (2003). A Before-and-After Study on RedLight Camera. ITE Journal, v. 73, no. 3, p. 28-32. McGee, H & Eccles, K. (2003). The Impact of Red-Light Camera Enforcement on Crash Experience. ITE Journal. Miller, John S. (2003). Two Methodological Considerations for Evaluating Safety Impacts of Photo-Red Enforcement. ITE Journal, v. 73, no. 1, 20-4. n. a., (1999). Two Methods to Reduce Dangerous Driving. Consumers’ Research Magazine, v. 82, no. 1, 21. New York City Red Light Camera Program (1997). Program Review: Twelve Months Ended December 31, 1996. Electronic Data Systems. O’Connell, K. (2000). Los Angeles County Red Light Photo Enforcement Pilot Program. Institute for Court Management. Court Executive Development Program. Phase III Project. Radwan, E., Klee, H. & Abdel-Aty, M. (2003). Evaluation of Red-Light Running and Limited Visibility Due to LTV’s Using the UCF Driving Simulator. Central for Advanced Transportation Systems Simulation. University of Central Florida. Retting, R., Williams, A. & Farmer, C. (August 1999). Evaluation of red light camera enforcement in Fairfax, VA, USA. ITE Journal, v. 69, no. 8, p. 30-4. Retting, R. Weinstein, H. Williams, A. & Preusser, D. (2000). Reducing crashes on urban arterials. Arlington, VA: Insurance Institute for Highway Safety. SPSS Inc. (2004). Clementine 9.0 User’s Guide. Chicago, IL. Wilber, D. & Willis, D. (2005). D.C. Red-Light Cameras Fail to Reduce Accidents. Washington Post. October 4. p. A01 The National Campaign to Stop Red Light Running. (2002). A Guide to Red Light Camera Programs. Stop on Red = Safe on Green.

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Emerging Trends and Challenges in IT Management

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Building a Tool for Expertise Discovery Sara Tedmori, Thomas Jackson, & Dino Bouchlaghem Loughborough University, Loughborough, Leicestershire, UK, LE11 3TU, T 44 (0) 1509 635649, {s.m.j.tedmori, t.w.jackson, n.m.bouchlaghem}@lboro.ac.uk Holger Adelmann, AstraZeneca R&D Charnwood, Loughborough, Leicestershire, UK, LE11 5RH, [email protected] Rama Nagaraju, Eureka Moment Software, 9284 Haden Ln., West Chester, OH 45069, [email protected]

ABSTRACT There is increasing interest in systems that aid employees to find those with the expertise they require. This paper discusses the evolution of expert finding tools, with particular reference to solutions that exploit email sources and identifies related gaps. The authors then propose Email Knowledge Extraction (EKE), a system for expertise discovery which addresses the issues highlighted by gap analysis.

1. INTRODUCTION In working environments, people are put in situations where they need to make a decision or look for information to resolve an ambiguity or a complexity. Early studies on information seeking behaviour show that people searching for information prefer asking other people for advice rather than searching through a manual for information (Bannon, 1986). A study by Kaurt and Streeter (1995) back up this perception by showing that people were the most valued and used sources of help in software development projects. Campbell et al. (2003) state that people ask others they know to find someone with a particular skill or experience, following pointers until an appropriate person is found. They also argue that there is a huge cost involved in following pointers to experts. These costs include efforts repeated by different people looking for the same answers, miscommunication that leads to the wrong expert and time pressures that lead to taking the advice of the not-so-expert who happen to be found quickly (Campbell et al, 2003). Research has shown that employees learn more effectively by interacting with others and the real value of information systems lies in their ability to connect people to people, so they can collaborate with each other (Bishop, 2000; Cross and Baird, 2000; Gibson, 1996; Wellins et al., 1993). Searching for the right piece of information becomes a matter of searching for the right person to refer to. This has lead to the interest in systems, which connect people to others by making people with the necessary expertise available to those who need it, when they need it. In this paper the authors identify the email communication system as an information source that could be utilised to locate experts within an organisation. The authors discuss the evolution of the expert finding approaches (section 2), with particular focus on expert finding agents that exploit email content as evidence of expertise (section 3). The gaps associated with the current approaches of agents which utilise email are then highlighted (section 4), and finally the authors propose an architecture for an email knowledge extraction system to aid knowledge location within the workplace (section 5).

2. TRADITIONAL EXPERT FINDING APPROACHES The traditional way of providing automated expert assistance relies on the development of expert databases that require users to manually register and enter their expertise data. Expert databases suffer from many drawbacks. Firstly, maintaining a manually built database requires intensive and expensive labour. Secondly, unless the users regularly update their details to reflect changes in their expertise profiles, the

systems will soon become out of date and inaccurate. Thirdly, expertise descriptions are usually incomplete and general, in contrast with the expert related queries that are usually fine-grained and specific (YimamSeid and Kobsa, 2003). The other problem with traditional expert systems is the ability to search and successfully locate the required information stored within the system. Large global enterprises sometimes have disparate expert databases that are sometimes restricted to one region and do not enable the employee to take full advantage of the global expert resource (Adelmann, personal communication). Yimam-Seid and Kobsa (2003) note that using search engines to locate an expert is ineffective. This is due to the fact that the search process is based on a simple keyword matching task, which may not always lead to relevant experts. The task can be very time consuming when a large number of hits are returned. Moreover, Yimam-Seid and Kobsa argue that it is entirely the user’s task to extract and compile all the required data to identify the best expert (Yimam-Seid and Kobsa, 2003). Most importantly, traditional expertise assisting technology adds an extra work load to people’s work as they have to maintain their profiles on top of everything else they do. Hence, people are less likely to use it. Expertise software must therefore be integrated into existing business processes. The drawbacks of the traditional approaches coupled with advances in information technology has resulted in a shift towards systems that automate or semi-automate the process of discovering expertise.

3. EXPERT FINDING SYSTEMS EXPLOITING EMAIL The International Data Corporation (IDC) has predicted that 35 billion emails will be sent globally every day by the end of 2005. IDC’s Email Usage Forecast and Analysis report further estimates that the number of emails sent annually in Western Europe will be 1.6 trillion in 2005 (Mahowald and Levitt, 2002). With so many email messages being sent each day, it seems logical that a percentage of them will contain key phrases that will help identify experts within organisations. From an academic prospective, attempts to develop systems that exploit email to augment the process of finding the right expert can be traced back to the work of Schwartz and Wood in 1993. Their system deduces shared-interest relationships between people. To avoid privacy problems, they decided to analyse the structure of the graph formed from “From:/To:” email logs, using a set of heuristic graph algorithms. The output of the system is a list of related people with no essential ranking order. A user searches the system by requesting a list of people whose interests are similar to several individuals known to have the interest in question. This implies that the person should have beforehand a social network with the appropriate contacts relevant to their query and that a novice can not properly take advantage of the system. Since 1993 there have been several research projects to identify experts from email communication. For example, The Know-who system is an email agent that helps to manage the information the users receive through emails (Kanfer et al., 1997). A Know-who agent monitors all email messages received by the user and maintains a list of all those from

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1054 2006 IRMA International Conference whom the user received email message(s). Based on the content of email communication with the people in the user’s social network, it responds to the user’s natural language query with a name(s), email address, and confidence level of the person(s) most likely to answer the question (or with a reference to another person who might know the answer). One potential limitation of Know-who is that it only identifies people within the user’s social network. This makes it unfeasible to identify individuals outside the user’s social network with common interests, thus impeding the process of expertise assistance. Sihn & Heeren (2001) presented XpertFinder, a system which analyses email communication of users for the preparation of expertise profiles. The part of the message entirely created by the sender and the address fields of emails are analysed and allocated to predefined subjects with the aid of a subject area tree. Within each subject area, XpertFinder allows anonymous highlighting of the people who are frequently communicating. Users submit their requests by emailing the XpertFinder system, which in turn completes the selected recipients email addresses and forwards the email. Experts are identified both by high communication intensity (e.g. whether or not they decide to reply to users’ queries if they were forwarded to them) as well as communication contacts in specific subject areas (Sihn and Heeren, 2001). Systems similar to XpertFinder are hard to share and reuse because they are based on a predefined subject tree. They are labour intensive to build and require ongoing maintenance. Commercial systems for expert identification using emails include: Tacit’s ActiveNet (Tacit, 2005), AskMe Enterprise (Ask Me, 2005) and Corporate Smarts’ Intelligent Directory (Corporate Smarts, 2005). All of which extract keywords and phrases from users’ emails and electronic documents. The information is placed into an expertise profile and distilled into a searchable database in order to enable users to query the system and find relevant people. Unfortunately, with regards to the commercial systems, no sufficient data is available on how these systems perform. Most of the system information is only available provided in the form of white papers serving as marketing tool to promote an organisations product and point of view. To avoid the dilemma of lack of sufficient data and to help analyse the existing systems, the authors have conducted domain analysis in order to identify opportunities for improvement.

4. GAP ANALYSIS OF EXISTING SYSTEMS To analyse the existing systems and the newly emerging technologies, domain analysis is needed. Domain analysis can be defined as the process of identifying, capturing, and organizing domain knowledge about the problem domain with the purpose of making it reusable when creating new systems (Prieto-Diaz and Arrango, 1991). A domain model of expert finding systems has been proposed by Yimam-Seid and Kobsa (2003). This model was used by the authors in order to acquire and consolidate information about applications in the expert finding systems domain, with the intention of identifying the gaps of existing technologies that particularly exploit email as the basis for expertise recognition. The authors have identified five gaps, namely (1) an expertise profile gap, (2) an expertise matching gap, (3) an expertise representation gap, (4) a user control gap, and (5) a cultural and management gap. In the following sections, the authors will describe each of these shortcomings and suggest some ways to tackle them. 4.1 Expertise Profile (model) Gap The core of expert finding systems heavily relies on the expertise profile (model) and on how accurate these systems are in their expertise matching process. Expertise profile (model) refers to information specific to an individual such as the individual’s skills, interests, expertise, personal details, et cetera. Common to most systems is the automatic extraction of key phrases from within the body of emails and the creation of the users profiles, such as Know-who email agent (Kanfer et al., 1997), Ask me (Ask Me, 2005), ActiveNet (Tacit, 2005), and Corporate Smarts’ Intelligent Directory (Corporate Smarts, 2005). It

is important to look at key phrases and not only keywords because sometimes a combination of keywords provides a more meaningful explanation. In ActiveNet, a user profile consists of a list of noun phrases from the sent items. In Corporate Smarts’ Intelligent Directory, a term becomes searchable when it is used in email communication among a group of people. This term will then be added to the user’s profile. Admittedly, extracting key phrases that describe the individual’s expertise from an email body poses an immense challenge. Emails are freestyle text, not always syntactically well formed, domain independent, of variable length, and on multiple topics (Tzoukermann et al. 2001). Moreover, the authors were unable to find an empirical evaluation on how effective these systems are in their key phrase extraction process from the email text. The potential key phrases extracted should give some sort of indication of skills and experience traded in the exchange of emails. Such key phrases ought to disclose skills such as technical expertise, management skills, industry knowledge, education and training, work experience, professional background, knowledge in subject areas and so forth. This requires an evaluation criterion that specialises in measuring the accuracy of these systems in terms of how many key phrases are correctly identified, in order to build a more accurate expertise profile. 4.2 Expertise Matching Gap When a user queries the system, the system needs to match the user’s needs with the expertise profiles by using retrieval techniques. It needs to measure similarity between an expert’s expertise and a user’s request. A search facility is usually provided for users to enter several keywords. However according to Liu (2003), it can suffer from the following drawbacks: • • • •

Some relevant experts are missed Some irrelevant experts are retrieved Too many experts are retrieved Too few experts are retrieved.

These problems need to be addressed by correctly matching the user’s needs with the expertise profiles to ensure that relevant experts are not overlooked and irrelevant experts are minimized. 4.3 Expertise Representation Gap Following expertise matching, the system needs to represent the output to the user. The major drawback of most systems (Schwartz and Wood, 1993; Tacit’s ActiveNet) is that the output is presented to the user with no relevant order. The reason behind this is the mechanism employed to rank the identified experts. McDonald and Ackerman (1998) distinguished between two stages in finding expertise within organizations, expertise identification and expertise selection. Some systems only go as far as expert identification through merely textual analysis. Rarely do they support expertise selection and this is an area for further development. 4.4 User Control Gap Some systems provide the users with the facility to edit their profiles to reflect changes to their expertise. Others like Corporate Smart’s allow their users to use system filters to allow its users to select the email message that they do not wish to include in the system sift. However, if a user fails to select a certain message, some of the personal interests which might be regarded as private by the users, could be published in the public domain. This situation requires system features that preserve and protect the privacy of the individual users through enabling them to control the system in how it uses their emails 4.5 Cultural and Management Gap Although information technology can aid in storing, disseminating, and accessing lots of data and information, it neither creates or guarantees

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Emerging Trends and Challenges in IT Management Figure 1. EKE Generic Architecture

the ongoing creation of knowledge nor promotes knowledge sharing. Technology alone is not sufficient to achieve success (Cross and Baird, 2000). Many well-planned knowledge management (KM) initiatives have been unsuccessful as they fail to acknowledge the cultural and management change dimensions of KM. Changing organizational culture is not an easy task. The challenge is to get people sharing knowledge instead of hoarding it. Thus when embarking upon a KM programme, organisations need to tackle issues such as trust, privacy, motivation, and the barriers to sharing knowledge.

5. AN OVERVIEW OF THE PROPOSED SYSTEM The primary aim of this research is to provide a fully automated and highly scalable system that uses the knowledge sent via email to ensure that: • •

Expertise and knowledge is able to be located quickly and easily. Expertise and knowledge is available to the people who need it.

As the name suggests, Email Knowledge Extraction (EKE) is a tool that mines the information contained in employees’ emails. EKE automatically finds interest areas by picking out key phrases from an employee’s e-mail messages. For ethical and privacy reasons, and to overcome the user control gap, each individual has the option of authorising whether he/she wants his/her knowledge in each area made public. This paper is a continuation of work reported in a previous submission by the authors (Jackson and Tedmori, 2003) to IRMA International Conference in which a pre-written program called KEA was used to extract the keywords from the email messages. It was noted, however, that after further analysis, the keywords extracted from KEA were occasionally incoherent and did not communicate knowledge fields within the organisation. In light of this, an alternative design is proposed which is concerned with modularity and reusability. Figure 1 shows the newly proposed generic structure of EKE. One of the key elements of EKE is the ability to capture email messages before they are sent to the server, so individual keyword extraction profiles can be deployed rather than generic ones that apply to the whole organisation. Thus, there is a need to design “email interceptor software” that intercepts the messages before they are sent to the remote email server and retrieves the email content. A software plug-in will be used for this task. In order to minimize processing overhead on the client machines, as soon as the email content is retrieved, the added plug-in will issue an http

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request to a web service passing to it the email content. On the server, the web service runs extracting key phrases from the email content and storing them in a temporary buffer. In order to build a good quality expertise profile and to overcome the expertise profile (model) gap, the web service has to be intelligent so that it extracts meaningful key phrases that identify knowledge holders within the organisation. The key is separating knowledge from noise. The extraction web service uses natural language processing. It picks key phrases purely based on the grammatical part of speech tags that surround these phrases, using a predefined set of rules. A rule is a sequence of grammatical tags that is likely to contain words that compose a key phrase. The approach used here does not use a controlled vocabulary, but instead chooses key phrases from the email text itself. At a certain point in time, a server side application collates all of the extracted keywords and displays them to the user for their approval. The user has to specify the extracted keywords as private or public and rank them using a scale of three to denote their expertise in that field (e.g. basic knowledge, working knowledge, or expert). The keywords accepted by the user are then stored on a main database on the server. The keywords in the database can then be retrieved based on user’s queries. Finally, the need to design an interface for searching the main database and an interface to output the results of the queries to the users comes into play. The result returned is a list of experts in the organisation ranked by their suitability to answer the user’s query.

7. SUMMARY The gap analysis model used in this paper has enabled information about applications in the expert finding systems domain to be consolidated and has identified gaps in existing technologies. The analysis has shown that the core of expert finding systems rely heavily upon the expertise profile model and, depending on how accurate the model is, determines the systems ability to match expertise. The key element behind the expertise profile model is its ability to extract relevant key phrases that match the sender’s expertise. The analysis has added to the body of knowledge within the expert finding domain and has enabled a proposed architecture to be presented for review.

REFERENCES AskMe, http://www.askmecorp.com, accessed on 16-09-2005 Bannon, L. J. (1986), Helping Users help each other. In User Centered System Design, New Perspectives on Human-Computer Interaction’, Lawrence Erlbaum Associates, Hillsdale, NJ. Bishop, K. (2000), Heads or Tales: Can Tacit Knowledge Really be Managed. Proceeding of ALIA 2000 Biennial Conference, Canberra, pages 23-26. Campbell, S.C., Maglio, P.P., Cozzi, A., Dom, B. (2003), Expertise identification using email communications. Proceedings of the twelfth international conference on information and knowledge management, New Orleans, LA, pages 528531. Cross, R. and Baird, L., (2000), Technology Is Not Enough: Improving Performance by Building Organizational Memory. MIT Sloan Management Review, Vol.41 No.3, pages 69-78. Corporate smarts, http://www.corporatesmarts.com, accessed on 1609-2005 Gibson, R. (1996) Rethinking the Future. Nicholas Brealey Publishing, London. Jackson, T.W. and Tedmori, S. (2004), Capturing and Managing Electronic Knowledge: The Development of the Email Knowledge Extraction. Innovations Through Information Technol-

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1056 2006 IRMA International Conference ogy, Khosrow-Pour, M. (ed.), Idea Group, IRMA, New Orleans, USA, pages 463-466. Kanfer, A., Sweet, J., and Schlosser, A. E. (1997), Humanizing the net: Social navigation with a ‘know-who’ email agent. Proceedings of the 3rd Conference on Human Factors and the Web, Denver, Colorado. Kaurt, R. E. and Streeter, L. A. (1995), Coordination in Software Development. Communications of the ACM volume 38, Issue No. 3, pages 69-81. Liu, P. (2003), An Empirical Investigation of Expertise Matching within Academia. PHD thesis, University of Leeds. Mahowald R. P. and Levitt M. (2002), Worldwide Messaging Applications Forecast and Analysis, 2002-2006: Getting the Message Out. IDC White Paper. McDonald, D.W. and Ackerman, M.S.(1998), Just talk to me: A field study of expertise location. Proceedings of the 1998 ACM Conf. On Computer-Supported Cooperative Work, Seattle, WA. New York: ACM press, pages 315-324. Prieto-Diaz, R. (1987), Domain Analysis for Reusability. Proceedings of COMPSAC’87: The Eleventh Annual International Computer Software & Applications Conference, Tokyo, Japan, pp:23 – 29.

Sihn, W. and Heeren, F. (2001), Xpertfinder - expert finding within specified subject areas through analysis of e-mail communication. In EUROMEDIA 2001: Sixth Annual Scientific Conference on Web Technology, New Media, Communications and Telematics Theory, Methods, Tools and Applications, pages 279-283. Schwartz , M. F. and Wood, D. C. M. (1993), Discovering shared interests using graph analysis. Communications of the ACM, volume 36, issue No.8, pages 78-89. Tacit, http://www.tacit.com, accessed on 16-09-2005 Tzoukermann, E., Muresan, S., Klavans, J.L, (2001), GIST-IT: Summarizing Email using Linguistic Knowledge and Machine Learning. In Proceeding of the HLT and KM Workshop, EACL/ACL. Wellins, R. S., Byham, W. C., and Wilson, J. M. (1993), Empowered Teams: Creating Self-directed Work Groups that Improve Quality, Productivity, and Participation. The Jossey Bass management, San Francisco. Yimam-Seid, D. and Kobsa, A. (2003) Expert Finding Systems for Organizations: Problem and Domain Analysis and the DEMOIR Approach. In Journal of Organizational Computing and Electronic Commerce Vol.13, No.1, 1-24.

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Emerging Trends and Challenges in IT Management

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Information and Knowledge Sharing by Undergraduate Students in Singapore Shaheen Majid & Ting Jer Yuen Division of Information Studies, School of Communication & Information, Nanyang Technological University, Singapore 637718, T 65 6790 4295, [email protected]

ABSTRACT Active information and knowledge sharing is an essential element of effective learning at the tertiary level. The purpose of this study was to investigate the knowledge sharing patterns of undergraduate students in Singapore, their perceptions of the knowledge sharing activity, avenues of knowledge sharing, preferred communication channels, and the factors inhibiting or motivating information and knowledge sharing among the students. A questionnaire was used for collecting data and 180 respondents from three public universities in Singapore participated in the study. It was found that students preferred sharing knowledge during classroom and tutorial discussions as well as with their own team members for completing group projects. There was only a limited information and knowledge sharing with the members of other groups and while working on individual assignments. An interesting trend was observed where students freely shared their information and knowledge with peers for those projects and assignments that were not graded. Finally, the paper suggests certain measures for improving information and knowledge sharing among students.

1.

INTRODUCTION

Active information and knowledge sharing is considered an important attribute of a learning organization. However, several studies suggest that many organizations experience knowledge sharing problems among their employees. In addition to certain other factors, it is possible that the reluctance to share information and knowledge could have its roots in the prevailing education systems in certain countries where students face pressure to outperform their classmates. There is likelihood that this intense competition might have created some anxiety in the minds of these students, resulting in avoidance to share knowledge with their peers. This attitude, developed during the students’ life, could then become part of their personality and likely to continue at the workplace. 1.1 Learning Styles and Knowledge Sharing Many studies have highlighted the fact that information and knowledge sharing plays a vital role in the learning and development of individuals (Robson et al, 2003; Rafaeli & Ravid, 2003). In addition to lecturercentric approaches, several new instruction strategies such as problemoriented teaching, contextualised teaching, target-oriented teaching and collaboraive teaching are gaining popularity. These innovative teaching methods have already turned instruction into sharing (Hong & Kuo, 1999). Educators agree that students prefer different learning methods which suit their personalities and learning styles. According to the GrashaReichmann Student Learning Style Scales (GRSLSS), the students can be categorized into the following six groups according to their learning styles: a)

b)

Independent learners - prefer independent study, self-paced instruction, and would prefer to work alone on course projects than with other students. Dependent learners - look at their teacher and peers as a source of guidance and prefer an authority figure to tell them what to do.

c)

d)

e)

f)

Competitive learners - learn in order to perform better than their peers do and to receive recognition for their academic accomplishments. Collaborative learners - acquire information by sharing and by cooperating with teacher and peers. They prefer lectures with small group discussions and group projects. Avoidant learners - not enthused about attending class or acquiring class content. They are typically uninterested and are sometimes overwhelmed by class activities. Participant learners - interested in class activities and discussion, and are eager to do as much class work as possible. They are keenly aware of, and have a desire to meet, teacher expectations.

These different learning styles can be categorized into 2 general groups according to their social aspect: individual-oriented (Independent and Avoidant learners) and collaborative-oriented (Dependent, Collaborative, Competitive and Participant learners). As social communication is considered to be an essential component of the educational activities, another popular learning style has been developed and is called the interactive learning style (McShannon & Derlin, 1999). Grantham (2005) highlights that many learning institutions are incorporating group-based discussion and cooperative activities in their instruction approaches. These interactive learning activities bring benefits such as higher student achievement, better communication skills, promote group cooperation and encourage information sharing. In addition, the peer group also serves to support students emotionally in coping with the pressures of academic work, fulfil personal needs and social status, and enhance interpersonal development (Educational Broadcasting Corporation, 2004). It is, therefore, quite evident that interaction and sharing of information and knowledge among students is a basic and essential ingredient of the learning process. Similarly, student achievement is likely to be higher in cooperative situations as well as result in more frequent use of higher-level reasoning strategies, more frequent process gain, and more positive attitudes towards their fellow students (Johnson & Johnson, 1990). It can also help students answer questions and solve problems, learn new things, increase understanding regarding a particular subject, or merely acts as a means to help one another (Hogberg & Edvinsson, 1998). 1.2 Barriers to Information and Knowledge Sharing Despite the various advantages that are inherent in knowledge sharing, there are many instances where knowledge is not shared effectively. There are many situations where students show the tendency of ‘hoarding’ their information and knowledge or feeling reluctant to share it with their classmates which defeats the spirit of cooperative learning. This can be attributed to various physical, technological, psychological, cultural and personality factors. People tend to recognise the importance of knowledge as a source of power which is based on the thinking that knowledge is an individual’s private asset and a source of competitive advantage. This motivates them to either hold it back or share it with selected individuals (McLure & Faraj, 2000). Another factor that promotes or restricts information and knowledge sharing is the mutual trust which develops over the time period through interpersonal rela-

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1058 2006 IRMA International Conference tionships. Strong personal ties and mutual respect can also motivate individuals to share their knowledge with their peers (Von Krogh, 1998). For this reason, it is important that adequate time and opportunities should be provided to students to frequently communicate with one another to foster close social relations (Poulfelt, 2003). Davenport and Prusak (1998) observe that knowledge has a value to an individual and its sharing should be matched by appropriate incentives and rewards. They identify reciprocity, repute and altruism as three important factors that can motivate knowledge sharing. Certain other knowledge sharing barriers, highlighted by several other studies, include: lack of time; lack of understanding what to share and with whom to share; absence of knowledge sharing culture; and the fear of sharing wrong information (Ardichvili et al., 2003; Skyrme, 2002; Chow et al., 2000). Collaborative learning is considered as one of the more established, popular and effective learning approaches. However, an essential element of the collaborative learning is the active and voluntarily sharing of information and knowledge by the learners. It is, therefore, highly desirable for educators and other academic stakeholders to properly understand the knowledge sharing behaviour of students and the barriers that impede this vital activity. Unfortunately, most of the information and knowledge sharing studies have been done in organisational settings and very little is known about the knowledge sharing patterns of tertiary students. The main objective of this study was to investigate the information and knowledge sharing behaviour of undergraduate students in Singapore, the type of information shared by them and the communication channels used for this purpose, and the factors that inhibit or motivate knowledge sharing among students.

2. METHOD The study used a pre-tested questionnaire for eliciting responses from the participants. As some of the questions were of a sensitive nature, this method allowed participants to remain anonymous and provide honest responses. The online questionnaire was constructed by using the NSurvey software and the survey was hosted on one of the University’s servers. The online questionnaire was considered advantageous as compared to other distribution channels because it allowed error checking in the submitted responses as well as ensured that all questions were answered. Besides, the functions of consolidation and tabulation saved time and reduced human error in manually collating the data. Information about the study was disseminated to students in all the three public universities in Singapore by sending an email, indicating the objectives and the URL of the survey. The data was collected over a period of 6 weeks, from March till end of April 2005.

3.

FINDINGS

A total of 180 students participated in the study and 71% of them were female while the remaining 29% were male respondents. The respondents came from a wide variety of disciplines such as arts, business, engineering, physical and natural sciences, and computer science and information technology. The distribution of respondents by their year of study was also fairly spread.

3.1 PREFERENCE FOR INFORMATION AND KNOWLEDGE SOURCES The respondents were asked to rank, on a scale of one to five, various information and knowledge sources that they prefer to consult for seeking answers to their study-related queries. The Internet, as expected, appeared at the top of the list with a mean score 4.28 (Table 1). It was interesting to note that classmates appeared second in the ranking (mean score 3.84), followed by the library (mean score 3.25) and course instructors (mean score 3.22). It was not surprising that the Internet ranked first due to its enormous resources, easy accessibility and convenient use. It was, however, heartening to note that the respondents valued their peers as an important source for acquiring the needed information and knowledge.

Table 1: Preference for Information and Knowledge Sources Mean Score

Standard Deviation

The Internet

4.28

0.92

Classmates

3.84

0.98

Library resources

3.25

1.23

Course instructors and tutors

3.22

1.17

Other friends outside the university

1.99

1.07

Source

Table 2: Perceived Frequency of Information and Knowledge Sharing by Peers Situation While working on group assignments (within their own group) During class and lab discussions While working on group assignments (with students from other groups) While working on individual assignments

Frequently

Sharing Frequency Less Frequently

Never

167 (92.8%)

12 (6.7%)

125 (69.4%)

52 (28.9%)

1 (0.5%) 3 (1.7%)

42 (23.3%)

116 (64.4%)

22 (12.2%)

40 (22.2%)

115 (63.9%)

25 (13.9%)

3.2 Knowledge Sharing Frequency Through an indirect question, the respondents were asked to indicate their opinion regarding the frequency of knowledge sharing done by their peers with other students in various study-related situations. A large majority (92.8%) of the respondents felt that their peers share knowledge more frequently with their own team members while working on group assignments (Table 2). It was followed by knowledge sharing during class discussions (69.4%). On the other hand, based on the perception of the respondents, the information and knowledge sharing was limited with the members of other groups as well as while working on individual assignments. It appeared that students were more likely to share information and knowledge with other students when they were expected to contribute as a team member or when their own interest was involved. They were less likely to share with those students with whom they were competing for grades. In order to verify this assumption, a supplementary question was used to ask respondents about the possible frequency of information and knowledge sharing by their peers if grades were not involved. It was interesting to note that for two situations where limited information and knowledge sharing was expected, a major change in the attitude was observed. Earlier, only 23.3% of the respondents expected their peers to ‘frequently’ share information with the members of other groups and now this figure jumped to 54.4% respectively. Similarly, if grades were not involved, the number of respondents expecting ‘frequent’ information sharing by their peers surged from 22.2% to 53.3% of the respondents. It appears that keen competition among students to outperform each other for obtaining better grades is likely to inhibit information and knowledge sharing by them. 3.3 Attitude towards Knowledge Sharing The respondents were given different statements to determine their overall attitude towards information and knowledge sharing. It was interesting to note that, in general, a majority of the respondents exhibited a positive attitude towards sharing (Table 3). Nearly 72% of the respondents ‘agreed’ or ‘strongly agreed’ that knowledge sharing was beneficial to students. Another 53.9% of the respondents ‘agreed’ or ‘strongly agreed’ that students should share information voluntarily while 45% of the respondents gave the same rating to the statement that ‘sharing is caring’. A split response was received for the statement that students should only share their knowledge when their peers asked for it. A majority of the respondents disagreed with the remaining three statements which put information and knowledge sharing in somewhat negative context. It

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Emerging Trends and Challenges in IT Management Table 3: Attitude towards Information and Knowledge Sharing Perception 1 2 3 4 5 6 7

I feel that it is important to share knowledge with other students for the benefit of all Students should voluntarily share information with their peers I feel that “sharing is caring” Students should share information with their peers only when approached Many students feel that they might be penalised by lecturers for sharing information It is better to avoid sharing information with peers whenever possible Many students have the mindset that sharing information is a type of plagiarism

Strongly Agree 26 (14.4%) 14 (7.8%) 11 (6.1%) 3 (1.7%) 5 (2.8%)

Agree 103 (57.2%) 83 (46.1%) 70 (38.9%) 59 (32.8%) 21 (11.7%)

3 (1.7%)

6 (3.3%)

3 (1.7%)

18 (10.0%)

Response Level No Disagree Opinion 44 6 (3.3%) (24.4%) 56 (31.1%) 67 (37.2%) 53 (29.4%) 14 (7.8%) 27 (15.0%) 17 (9.4%)

25 (13.9%) 27 (15.0%) 61 (33.9%) 96 (53.3%) 103 (57.2%) 107 (59.4%)

Strongly Disagree 1 (0.6%) 2 (1.1%) 5 (2.8%) 4 (2.2%) 44 (24.4%) 41 (22.8%) 35 (19.4%)

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Table 6: Possible Barriers to Information and Knowledge Sharing Reason Lack of depth in relationship Afraid that others would perform better People only share with those who share with them Do not want to be perceived as a ‘show-off’ Afraid to provide the wrong information Lack of knowledge sharing culture Shy to provide own opinions Lack of time Lack of appreciation of knowledge sharing Afraid that an opinion mismatch would offend others Do not know what to share

Number of Respondents 157 (87.2%) 138 (76.7%) 118 (65.6%) 113 (62.8%) 112 (62.2%) 106 (58.9%) 106 (58.9%) 83 (46.1%) 82 (45.6%) 66 (36.7%) 58 (32.2%)

Table 4: Preferred Channels for Sharing Information Table 7: Suggestions for Improving Information and Knowledge Sharing Mean Score

Standard Deviation

Face-to-face interaction

4.67

0.64

Online chat (ICQ, MSN Messenger, etc.)

3.22

1.27

Communication Channel

Email

3.18

1.11

Telephone

2.91

1.15

Online message board

2.32

1.22

appeared that, on the whole, the respondents were convinced and supportive of information and knowledge sharing among students. However, their actual behaviour could be different due to certain other de-motivating factors. 3.4 Channels Preferred for Information and Knowledge Sharing The respondents were asked to rank, on a scale of 1 to 5, some most commonly used communication channels for sharing information and knowledge with their peers. The face-to-face interaction was ranked first (mean score 4.67) due to its obvious advantages (Table 4). Various chatting services were ranked second (mean score 3.22), closely followed by email (mean score 3.18). Surprisingly, the online message boards ranked the lowest. 3.5 Motivators for Information and Knowledge Sharing Table 5 shows the possible motivators for information and knowledge sharing, as identified by the respondents. It was found that 63.3% of the respondents felt that the most motivating factor to share information and knowledge with their peers was the desire to learn from one another. Two other motivating factors were the wish to help others (50.6% respondents) and to maintain reciprocity in the relationship (41.1% respondents). It appeared that the respondents had a clear and positive understanding that learning is a collaborative and interactive effort and information and knowledge sharing can help achieve this objective.

Table 5: Information and Knowledge Sharing Motivators Motivator

Number of Respondents

To learn from each other

114 (63.3%)

To help others

91 (50.6%)

To maintain reciprocity in relationship

74 (41.1%)

Self satisfaction

36 (20.0%)

To obtain reward or recognition

31 (17.2%)

To cultivate image of expertise

11 (6.1%)

Suggestion Instil a sharing culture Eliminate or less emphasis on grades, less competitive learning Give more group assignments Create online forums, discussion / message boards Provide incentives (bonus marks, rewards) for sharing Foster familiarity and interaction among students Include more interactive classes, discussion sessions and study groups Encouragement and guidance by lecturers and tutors Provide conducive environment (notice boards, study rooms) Change students’ mindset – ‘Grades are not everything’

Number of Respondents 17 14 10 10 10 9 9 8 7 5

3.6 Barriers to Information and Knowledge Sharing The respondents were asked to indicate possible reasons that restrict active information and knowledge sharing among students. An overwhelming majority (87.2%) of the respondents felt that it was due to lack of depth in relationship (Table 6). Some 76.7% of the respondents revealed that students usually do not share their information and knowledge because they feel other students will outperform them. Lack of reciprocity in relationship was another inhibitor which was pointed out by 65.6% of the respondents. Certain other information and knowledge sharing barriers, reported by several studies, such as lack of time, lack of appreciation, fear of providing wrong answers, and not knowing what to share, were not considered hindering the information and knowledge sharing activity. As reported by many earlier studies, it appeared that a lack of trust and competition among peers were the two major barriers to information and knowledge sharing. 3.7 Suggestions for Improving Information and Knowledge Sharing among Students The suggestions, offered by at least 5 or more respondents, for improving information and knowledge sharing among students are summarised in Table 7. It appeared that students felt that creating an informationsharing culture, having less emphasis on grades, assigning group projects, conducting interactive classes, and creating more opportunities for interaction among students can help improve information and knowledge sharing among students.

CONCLUSION In the so called ‘knowledge society’, actively and voluntarily sharing of information and knowledge is imperative. Citizens should fully understand and appreciate the value of sharing for the overall betterment of the society. Students, being the most crucial segment of the society and the main driving force for future growth and development, need to infuse the information and knowledge sharing habit in their personality. It was interesting to note that the respondents valued their peers as an important source of knowledge and, on the whole, showed a positive attitude towards information and knowledge sharing. However, a lack of depth in peer relationship and the urge to outperform peers academically were probably the two main inhibitors to information and knowledge

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1060 2006 IRMA International Conference sharing. The fear is that unnecessary competition during a student’s academic life could leave an imprint on their thinking and personality. This attitude, if left unchecked, is likely to persist at the workplace which may be aggravated due to intense work pressures and competition among colleagues for better career advancement. It is, therefore, desirable for the academic institutions to reconsider their teaching approaches and put more emphasis on collaborative learning to avoid unnecessary competition among students. They also need to review their student assessment policies and procedures to make them less competitive and threatening. In addition, academic institutions need to create a conducive knowledge sharing environment by providing ample interaction opportunities to students for developing cordial relationships which will help promote mutual trust and respect. Once they start regarding their classmates as their learning partners instead of competitors, they are likely to share their ideas and knowledge more frequently.

5.

6.

7.

8.

9.

10.

REFERENCES 1.

2.

3.

4.

Ardichvili, A., Page, V. & Wentling, T. (2003) Motivation and Barriers to Participation in Virtual Knowledge-sharing Communities of Practice. Journal of Knowledge Management, 7(1), 6478. Chow, C. W., Deng, F. J. & Ho, L. J. (2000). The openness of knowledge sharing within organizations: A comparative study in the United States and the People’s Republic of China. Journal of Management Accounting Research, 12 (November), 65-95. Davenport, T. H. (1998). Some Principles of Knowledge Management. Retrieved December 29, 2004 from http:// www.mccombs.utexas.edu/kman/kmprin.htm Educational Broadcasting Corporation (2004). What are the benefits of cooperative and collaborative learning? Retrieved January 6, 2006 from http://www.thirteen.org/edonline/ concept2class/coopcollab/index_sub3.html

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Grantham, D. (2005). Understanding student learning styles and theories of learning. Retrieved May 18, 2005 from http:/ /www.ukcle.ac.uk/events/grantham2.html Hogberg, C. & Edvinsson, L. (1998). A design for futurising knowledge networking. Journal of Knowledge Management, 2(2), 81-92. Hong, J. C. & Kuo, C. L. (1999). Knowledge management in the learning organisation. Leadership & Organisation Development Journal, 20(4), 207-215. Johnson, D. W. & Johnson, R. T. (1990). Cooperative learning and achievement. In S. Sharan (1990), Cooperative Learning – Theory and Research. NY: Praeger Publishers. McLure, M. and Faraj, S. (2000). It is what one does: Why people participate and help others in electronic communities of practice. The Journal of Strategic Information Systems, 9(2-3), 5573. McShannon, J.R. & Derlin, R. (1999). Interactive Learning Styles of Undergraduate Engineering Students in New Mexico: A New Model. Paper presented at the annual conference for the American Society of Engineering Education, Dallas, TX, March, 1999. Poulfelt, F. (2003). 6 principles of knowledge sharing. Retrieved January 6, 2006 from http://www.providersedge.com/ docs/km_articles/6_Principles_of_K-Sharing.pdf Rafaelie, S. & Ravid, G. (2003). Information sharing as enabler for the virtual team: An experimental approach to assessing the role of electronic mail in disintermediation. Information Systems Journal, 13(2), 191-206. Robson, R., Norris, D. M., Lefrere, P., Collier, G. & Mason, J. (2003). Share and share alike: The e-knowledge transformation comes to campus. EDUCAUSE Review. Skyrme, D. J. (2002). The 3Cs of knowledge sharing: culture, competition and commitment. Retrieved January 6, 2006 from http://www.skyrme.com/updates/u64_f1.htm Von Krogh, G. (1998). Care in knowledge creation. California Management Review, 40(3), 133-153.

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Emerging Trends and Challenges in IT Management

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Abstracts The Value of Search Engine Optimization: A Case Study of a New E-Commerce Web Site

The analysis helps bridging the existing gap in our understanding of expected purpose and actual process of e-business implementation. This research contributes an effective approach in studying the process of organizational transformation enabled by the Internet. The study also provides strong empirical support for end-to-end digitization of the entire value chain from customers to the suppliers for enhanced business performance.

Ross A. Malaga, School of Business Montclair State University, Montclair, NJ 07043 (973) 655-3419, [email protected] ABSTRACT Search engine optimization (SEO) efforts attempt to improve a Web site’s rankings in search engine results pages. The goal of this paper is to ascertain the impact of a search engine optimization project on Web site traffic and determine if such a project provides value to the business. The paper follows an SEO project at a new Web site. The project used on-page and off-page optimization techniques. The site’s search engine rankings and traffic were measured after each phase in the project. In addition, the results of the SEO project are compared with a search marketing campaign to determine which provides greater return on investment.

Keywords: e-business implementation process, strategic planning, information sharing capabilities and collaborative process capabilities.

A Database-Oriented Approach to the Introductory MIS Course Efrem G. Mallach, PhD, Associate Professor Charlton College of Business University of Massachusetts Dartmouth North Dartmouth, MA 02747 P 508 990-9670, [email protected]

E-Business Implementation Process in China Jing Zhao*, Wilfred V. Huang** and Zhen Zhu* *Center for International Cooperation in E-Business

ABSTRACT This paper notes that hands-on activity is largely absent from today’s introductory MIS course, detracting from its interest and value to students. It is suggested that designing and developing a database application can be an appropriate way to add hands-on content to this course in 2005. Specific suggestions for integrating the theory and database sides of such a course, and for an outline of a book for such a course, are made. Feedback on these ideas is solicited.

College of Management, China University of Geosciences Wuhan 430074, P.R.China

Role of Information Exchange in Damping Supply Chain Oscillations

**College of Business, Alfred University

Ken Dozier & David Chang

Alfred, NY 14802, U.S.A.

University of Southern California Engineering Technology Transfer Center

ABSTRACT Implementing e-business requires a dynamic approach that can respond to changes in technology, management direction, customer and supplier behavior, and competition. Enterprises will encounter internal and external influential factors in e-business development. Understanding the relationship of these factors will lead to successful implementation. We will explore the e-commerce implementation, and the rationale to implement the process and to articulate the components and their interrelationships. We study how the firm resources and capabilities are exploited to execute strategies for improving efficiency and competitive advantage. A model of the e-business implementation process is proposed, and is tested with survey data collected from the enterprises in Hubei Province of China.

ABSTRACT Supply chain oscillations satisfy a sound wave-like dispersion relation when a company responds only to the status of the companies immediately above and below it in the chain. However, when information exchange makes it possible for the company to respond to the status of all the companies in the chain, the dispersion relation changes from that of a sound wave to that of a plasma oscillation. The plasma oscillationlike dispersion relation has much higher phase velocities than the phonon-like oscillations, and the associated Landau damping shows information-induced suppression of the supply chain oscillations.

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1062 2006 IRMA International Conference

Determinants of Information Systems Project Failures in Sub-Saharan Africa: A Review of the Critical Factors Mary Otieno, Middlesex University The Burroughs, Hendon, London NW4 4BT ABSTRACT Introducing an IT/IS initiative in Sub-Saharan Africa is a complex undertaking, with wide-reaching impact on the organisations and people involved. This paper presents findings from a review of a wide range of literature emanating from different domains reporting different perspectives on failure of information systems and technologies in African countries. This paper identifies the critical factors that contribute to information systems projects failure in Sub-Saharan Africa; examines the impact of failure on those organisations; and to test the ability of a framework in categorisation of failure factors with the view to improving the development and deployment of information systems and technology initiatives in Sub-Saharan countries.

Keywords: Information systems, Project Failure, Sub-Saharan Africa, Organisations

a metropolitan area that is a center for state government, home to several national and international companies, has numerous small and midrange technical shops, and home to a small to medium sized (7500 students) university. The university supports both a BA and BS in computer information science as well as a well used continuing education department. This paper describes the leaders from the technology community, the university staff make-up, and the professionals who participated in the educational model. The paper describes classes that were developed, the order in which the classes were delivered, and the feedback from both the companies that participated as well as the professionals who participated. A brief discussion with respect to how the model must be continually enhanced, when the model must be changed, and where the model might best be used both nationally and internationally is presented and analyzed.

Enhancing the Accessibility of Information Assets Available on an E-Commerce Platform through Data Mining Analytics Stephen Kudyba, Department of Management New Jersey Institute of Technology

A Model for Educating the Transitional Technical Professional

[email protected] Kenneth Lawrence, Department of Management

Gary Schmidt

New Jersey Institute of Technology

CIS Department, Washburn University 17th and College Topeka, KS 66621 P 785-670-1740, [email protected] ABSTRACT Transitional Technical Professional: employees in the same technical position for at least five years seeking to upgrade or enhance their technical skills. Research has documented thirty percent of the current technical staff are over fifty years in age and over eighty percent are greater than thirty years of age. The same research has indicated that while the next five years will see a number of technical job holders retire or change positions, those that remain will face an ever changing profession in which current skills will require minor replacement, enhancement, or even complete re-tooling. If the technical industry is to keep such professionals knowledgeable, enthusiastic, and productive, education will also need to provide direction and council for such professionals. While educational institutions continually modify curriculums to accommodate new and futuristic concepts, little time is spent dealing with redoing coursework that now is ‘out-of-vogue’. The model developed for this ‘out-of-vogue’ curriculum was developed for the entering professional not generally for the transitional professional. Therefore, a common question asked is “How does one, in the profession even as little as five to ten years, find a comprehensive educational path to again become current in the technology profession?” This paper outlines the development of a model for educating such professionals. The environment that produced this model comes from

ABSTRACT This paper links theoretical principals to a case study that addresses how organizations can better manage website functionality, enhance the online experience for consumers and increase company revenue through the utilization of data mining analytics in an ecommerce platform. More specifically, the work describes the process by which data mining analytics can be used to better identify consumer preferences for goods and services available on-line and match additional products with these preferences during the on-line visit. The ultimate result is more effectively managed resource content, reduced customer search time and increased firm revenue per customer transaction.

A Cross-Sectional Study on Internet Searching Skills by Health Facilities of a Latin-American University1 Norelkys Espinoza2, Ángel G. Rincón 3, Belkys Chacín4 ABSTRACT Use of on-line databases has improved the search of scientific knowledge especially in the health science area, making a more efficient search for investigations and reports of any topic in any field. Thereby, medical databases have been providing the necessary information in order to make rational decisions by health professional in their clinical practices based on a quality scientific knowledge; this has been called Evidence

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Emerging Trends and Challenges in IT Management Based Medicine. Since the creation of Internet, databases are easy to use for seeking and retrieving biomedical information, they have made easier and faster the diffusion of scientific knowledge. To improve seeking and retrieving scientific information, searching must be performed as an expert search, accepting it as the search of scientific literature where a variety of aspects come together. These aspects include the selection and analysis of databases, seeking strategies and all resources that researches use gain knowledge However, many health professionals still resist to change their procedures to look out for information. Thereby the goal of this cross sectional study is to find out the strategies used by faculties of Health Science Schools of the University of Los Andes in Venezuela, to seek for scientific information. Faculties of Medicine, Dentistry and Nutrition where interviewed to know their skills in searching for scientific information. A randomized sample of 38 active teachers was interviewed with a multiple choice questionnaire. The following variables were registered: age, gender, profession, academic degree, years of service in the university, frequency of scientific information search, browser or search engine used, training in new technologies, reasons of seeking information, limitations and odds in the access to hardcopy scientific papers, were asked to the teachers. Data recollected was analyzed with SPSS 7,5 ® and a descriptive analysis was performed. The average age of the participants was 37 and at least 52% had more than 10 years in the academic practice. Location more frequent used to access internet was their homes (50%) followed by universities offices (34%). We found that just 29% of the faculties retrieve information using exclusively Health Databases like: Medline, Lilacs or Cochrane Library. The majority of teachers are using general browsers like Yahoo, AltaVista and Google for seeking medical scientific information. Also 26% of the faculties never use the internet or medical databases to search information. The e-mail service was the more frequent internet service used by them, Medline (Pubmed) was the most popular medical database and finally the economical cost is the major concern in acquiring hardcopies of scientific paper followed by the total lack of knowledge of how to obtain the papers. We conclude that the university faculties are indeed using Internet and new technologies but in spite of having full and free access to Internet from the University, they do not know the basic tools to seek scientific valid information.

ENDNOTES 1

2

3

4

This research has been possible thanks to the CDCHT of the Universidad of Los Andes (ULA), Project O-125-05-04-B. Assistant Professor. Facultad de Odontología, Universidad de Los Andes. Calle 24 entre Avs. 2 y 3. Mérida, Venezuela. Tlf/ fax: 0274-2402379. [email protected], [email protected] Instructor. Facultad de Odontología, Universidad de Los Andes. Calle 24 entre Avs. 2 y 3. Mérida, Venezuela. Tlf/fax: 02742402379. Correo: [email protected] Instructora. Departamento de Ciencias Morfológicas. Facultad de Medicina. Universidad de Los Andes. Tlf/Fax:58-274-2403121. Correo: [email protected]

IT Global Sourcing: What is its State of Maturity? Mehdi Ghods, The Boeing Company Seattle, Washington, (425)865-2511 [email protected] Now that IT offshore outsourcing or “offshoring” has evolved into “global sourcing”, businesses and companies are undertaking efforts to understand and incorporate this function into their overall sourcing strategy. These efforts have introduced new challenges, as the approach

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to “global sourcing” requires moving beyond the purpose of having access to low-cost labor (the primary reason for offshoring). This study and presentation are intended to explore and discuss the service providers’ global delivery models, and factors such as productivity, capability and quality, as well as the impacts of the global sourcing on the IT professionals, skills and workforce worldwide.

Cybercrime, Cyberwarfare, and Cyberterrorism in the New Millennium Shin-Ping Tucker, PhD Assistant Professor of Computer Information Systems Dept of Business & Economics University of Wisconsin- Superior Belknap and Catlin, PO Box 2000 Superior, WI 54880-4500 T: 715-394-8466, [email protected] ABSTRACT The whole world is now connected as never before. The Internet has become an integral part of our way of life; however, as our dependency on Internet increases, so too does our vulnerability. Over the past several years, individual cyber criminals have cause billions of dollars in losses through the use of viruses, worms, identity theft, and unauthorized access to computers. In the future, many believe that coordinated efforts by national governments or terrorist groups have the potential to do hundreds of billions of dollars in damage as well as put the lives of countless people at stake (Panko, 2004; Jessup & Valacich, 2006). The abuse of cyber technology may threaten national security, public safety and community well-being, and devastate the lives of affected individuals. Cybercrime refers to online or Internet-based illegal acts. Today, cybercrime is one of the FBI’s top priorities. Hundreds of different methods and tricks are used by innovative cyber criminals to get money from innocent people. The U.S. Department of Justice defines cybercrime as any violations of criminal law that involve knowledge of computer technology for their perpetration, investigation, or prosecution (Laudon & Laudon, 2006). Cyberwarfare refers to an organized attempt by a country military to destroy or disrupt the information and communication systems of another country. The goal of cyberwarfare is to turn the balance of information and knowledge in one’s favor in order to diminish an opponent’s capabilities and to also enhance those of the attacker. Unlike cyberwarfare, cyberterrorism is not launch by governments, but by individuals and organized groups. A cyberterrorist may use the Internet or network to destroy or damage computers for political reasons. The extensive damage might destroy the nation’s air traffic control system, electricity-generating companies, or a telecommunications infrastructure. Cyberterrorism usually requires a team of highly skilled individuals, millions of dollars, and several years of planning (Shelly, Cashman, & Vermaat, 2005). U.S. military networks and U.S. government agencies suffer hundreds of hacker attacks each year. Most experts believe that cyberwarfare and cyberterrorism are imminent threats to the U.S. Groups from a number of countries have been probing and mapping U.S. networks, and at least 20 countries are believed to be developing offensive and defensive cyberwarfare capabilities (Laudon & Laudon 2006). Such cyberwarfare might target the software that runs electrical power grids, air traffic control systems, medical capabilities, or networks of major banks and financial institutions. A major cyberterrorism that cripples a global

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1064 2006 IRMA International Conference information infrastructure could have devastating implications for a world economic system. Thus, cybercrime, cyberwarfare, and cyberterrorism pose complex problems that reach into new areas for national security and public policy. The purpose of this study intends to differentiate the terms of cybercrime, cyberwarfare, and cyberterrorism. Based on these findings, the solutions are proposed for the problems of cybercrime, cyberwarfare, and cyberterrorism, respectively.

leveraging specialized knowledge and learning gained from architecting solutions for a few business functions and applying it across the enterprise. Vijay will talk about the key characteristics of this delivery model as well as the realized benefits for clients.

Evaluation of Multicarrier Modulation Technique Using Linear Devices

The Impact of Organizational Culture and Knowledge Management on Organizational Performance

(Dept ELEC/TW), Pleinlaan 2, B-1050 Brussels, Belgium, & Escuela Superior Politécnica del Litoral,

Zhang Li, Tian Yezhuang, & Qi Zhongying

Km 30.5 Av. Perimetral, Ecuador, [email protected], [email protected]

Hernán Córdova, Vrije Universiteit Brussel

School of Management Harbin Institute of Technology

ABSTRACT

No.13 Fayuan Street,Nangang District Harbin,China,150001 {zhanglihit, tianyezhuang1; qzy}@hit.edu.cn ABSTRACT This paper examines the impact of organizational culture and knowledge management on organizational performance in Chinese manufacturing companies. Based on the classification of organizational culture and process of knowledge management, this paper presents a conceptual model on the impact of organizational culture and knowledge management on organizational performance. By using survey questionnaire in Chinese manufacturing companies, this paper conducts empirical study to test the hypotheses related to the impact. The results show that there is a significant correlation between organizational culture and knowledge management, and they have an impact on organizational performance. Keywords: organizational organizational performance

culture,

knowledge

Mutlicarrier modulation techniques like OFDM and DMT are suitable for high rate systems in timedispersive channels, allowing a system free of ISI. However, these techniques also present disadvantages. One of them is well-known problem of the high peak-to-average-power-ratio involved in those systems, yielding to saturation in the power amplifiers and therefore, involving high costs in the design. Different techniques have been proposed in the literature. In this paper, we proceed to evaluate those techniques considering linear devices exclusively. The results shown here present a clear commitment among the trade-offs inherent from these techniques. Complexity, power efficiency and accuracy of the system are the most important factors when real design constraints have to be considered. The full paper will be developed from this abstract as follows. In section II, the theory related to multicarrier modulation is presented and discussed in time-dispersive channels. The problem of PARP and the techniques to decrease this effect are discussed in section III. Simulations showing the performance and tradeoffs involved in the deployment of these techniques are shown in section IV considering the use of linear devices. Finally, Conclusions are treated on section V, where the main topics discussed over the entire document are summarized and future work is also presented.

management,

Outsourcing: An Innovative Delivery Model Vijayanand Vadrevu, Practice Head, WT Chemicals & Pharma Practice, Wipro Technologies ABSTRACT Wipro Technologies has developed an innovative IT services delivery methodology that has helped its clients improve their IT services sourcing efficiencies through strategic offshore initiatives. This innovative model enables organizations to manage globally distributed functions or services efficiently, through combination of virtual shared services organization, process standardization and re-use. It also enables

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Emerging Trends and Challenges in IT Management

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Panels How to Get Published

The Potential and Perils of Information Technology Portfolio Management

A Panel of IGI Editors-in-Chief Session Chair: Lawrence A. Tomei, Robert Morris University, USA A panel discussion for participants seeking to publish in an IGI Journal. Who better to give you advice than our 27 Editors-in-Chief? Not all editors will be there, but many will – and every editor contributed to our new Guidelines for Publishing in an IGI Journal. Get your copy hot off the press at IRMA 2006. We’ll cover: • • • • •

I’ve written this fantastic article. Can I get help publishing my material? My article is interesting. How can I be sure someone else wants to read it? My manuscript is ready. Where do I send it? The editorial review process. Is there a long lead time and how will the editor communicate with me? Promotion and tenure. How do I package a published article in my promotion and tenure portfolio?

Assessing the Value of e-Learning Systems Presenter: Dr. Yair Levy [email protected] Presentation Type: Round Table discussion Emphasis of Presentation: Research and Practice ABSTRACT The presentation will discuss a new book titled “Assessing the Value of e-learning Systems” that is authored by the presenter. The presentation will address a new theory developed to assess learners’ cognitive value and satisfaction of e-learning systems to provide a robust measure of effectiveness of such systems. Up to date every measure done in industry for the assessment of IS Effectiveness, has been looking only at the ‘satisfaction’ or users’ perceived satisfaction. Failing to measure learners’ perceived value can cause companies to totally ‘miss-the-boat’ and concentrate their efforts on non-effective system characteristics. This presentation will help scholars as well as administrators of e-learning systems/programs understand the power in measuring and studying learners’ perceived value as well as satisfaction of e-learning systems. By assessing both measures (learners’ perceived value and satisfaction), scholars and administrators can compute a robust measure of effectiveness of such systems.

Dr. John T. Christian Information Resources Management College National Defense University, B62, 300 5th Ave., Fort McNair Washington, DC 20319-5066 P: 202-685-2020, [email protected] Governmental agency chief information officers are in a constant battle to provide increasingly diverse information technology (IT) support with decreasing funding levels. Besides the latest IT, agency colleagues want on-time and on-budget delivery of IT projects in development. In addition, these colleagues want minimal maintenance of current IT legacy systems even as agency operational demands increase. Attempts by the IT department to meet these diverse expectations often results in a patchwork quilt of IT projects. Incidental needs may be met while strategic needs go wanting; high priority IT development projects may languish while lower priority projects charge ahead; and peripheral legacy systems may enjoy full maintenance while other essential legacy systems stutter along with stop-gap maintenance. Most agencies appear to have abundant IT projects which incompletely address their expectations for supporting the agency’s strategic goals. To better address these expectations requires each IT department to inventory and comprehend its universe of IT projects, determine what value and risk are associated with each IT project, and identify what resources are expended for each IT project. Applying financial investment portfolio techniques to the management of agency IT projects is one method enjoying acceptance and success by agencies and their IT departments. The investment portfolio method directs how the clustering and alignment of IT projects may form an IT investment portfolio supporting one or more agency strategic goals. This portfolio would be composed of well defined IT projects judiciously selected to support a particular agency strategic goal (or goals). The investment portfolio method also describes how investment portfolios are created and modified and how criteria are assembled for selecting or rejecting investments as members of a portfolio. The results of applying the investment portfolio method and its attendant governance procedures finds each IT project reconsidered as an IT investment within an IT investment portfolio. Further, this method aids in the concurrent identification of an IT investment’s value and risk and its comparison to other IT investments. Thus, a defined portfolio promotes the clear alignment of IT investments to an agency’s strategic goals. One or more IT investment portfolios may be assembled to support fully all agency strategic goals. This portfolio management approach also permits agencies to discover what strategic goals are supported by which IT investments and what resources are expended for which IT investments. In addition, an agency may comprehend what value and risk levels their investments currently represent and what value and risk levels the agency is willing to accept in its investments. An IT investment may provide high value by aligning with and supporting one or more agency goals. However, this IT investment may also expose the agency to certain levels of risk—higher

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1066 2006 IRMA International Conference risk than the agency would want to accept. Understanding one investment’s value and risk forms the basis for comparison between and across all investments. Panelists will discuss other issues such as actions to align investment portfolios with strategic goals and objectives and the potential barriers for integrating budgeting, finance, and program management expectations with IT investments.

Agile and / or Plan Driven Software Development Panel of IRMA 2006, Washington DC, May 2006

The panel will take up novel “hybrid” developments in the field of software process, e.g. agile versions of the Unified Process or Microsoft Solution Frameworks, extensions of agile process models complying with standards like CMMI, or adoptions of standards like CMMI to incorporate ideas of agile process models. Another issue will be visions about further developments in the field of software processes in practice and research.

REFERENCES Boehm, B.W., and Turner, R. (2003) Balancing Agility and Discipline, Addison-Wesley, 2003. Paulk, M. C. (2001) Extreme Programming from a CMM Perspective, IEEE Software, 18, 19-26. Paulk, M. C., Curtis, B. and Chrissis, M. B. (1993) Capability Maturity Model for Software, v. 1.1, Software Engineering Institute, Carnegie Mellon University, Pittsburgh, PA.

Track chairs Dr. Jacob Nørbjerg, Dept of Informatics, Copenhagen Business School Njalsgade 80, DK-2300

Copenhagen S

Ph: +45 3815 2478, Fax: +45 3815 2401, [email protected] URL: http://www.inf.cbs.dk

International Tracking and Reporting Systems for Combating the HIV/AIDS Pandemic

Dr. Wolfgang Zuser, OBJENTIS Software Integration GmbH Vienna, Austria, http://www.inso.tuwien.ac.at [email protected] P +43/(0)1/58801-0, F +43/(0)1/58801-40199

ABSTRACT In recent years we have witnessed the development and diffusion of two very different ideas in software development. On the one hand, the software process improvement idea founded on software capability maturity models that emphasize a disciplined approach to predictable, planned and documented software development. And on the other, the agile movement, that emphasize flexibility, people and working software over documentation and plans. Both ideas are successful, judging from practitioner interest as well as conference and journal contributions, but they also appear to be mutually exclusive as indicated in the Agile manifesto’s juxtaposition of the agile and process-oriented ideas (www.agilemanifesto.org ). During the early days of eXtreme Programming and other agile approaches and their rising popularity, the debate focused on finding the “best” approach to software development. Experience reports and studies about both agile and heavyweight process types document, however, both success stories and failures, indicating that each approach has strengths as well as weaknesses depending on the environment it is used in. There are, however, also attempts to bridge what appears to be a gap between two very different philosophies about software development. Paulk(2001) notices, for example, that agile approaches to software development, such as eXtreme Programming are compatible with the idea of software capability and maturity as formulated in; e.g. the Software Capability Maturity Model (CMM) (Paulk et al., 1993). Today, a considerable number of experts seek opportunities to successfully combine the two paradigms, or like Barry Boehm and Richard Turner (2003) have stated, to “balance agility with discipline”. Therefore agile and process oriented ideas may not be as far apart as originally thought. This panel will discuss the strengths and limitations of both paradigms, within different types of projects and organizations. The panelists will be asked to share their personal experiences with either type of process and to suggest points of improvement.

Susan J. Griffey, DrPH, BSN, Senior Vice President, Global Health & Development, Social & Scientific Systems, Inc. 8757 Georgia Avenue, 12th Floor Silver Spring, MD 20910, [email protected] Evidenced-based policy- and decision-making requires accurate, reliable, and timely information. The US movement to electronic health records - fostering use of an evidence base - is a multi-year, public-privatecommunity partnership effort. On a global scale, a similar collaborative effort to ensure information access across boundaries and time zones is under way so that countries – and the world - can respond to the HIV/ AIDS crisis. Information technology management is at the heart of the solutions. The US government (USG) has mandated a coordinated and unified system for all USG agencies working in those countries in the President’s Emergency Plan (EP) for AIDS Relief. Centralized information needs in Washington, DC, are responded to from country-based reporting systems – each different and adapted to the local USG context. In addition, USG country systems – and the global system – are working with other international efforts such as UNAID’s Country Response Information System (CRIS) to ensure use of standard indicators and definitions, standard data collection and reporting methodologies, and seamless integration of data from multiple sources. Social & Scientific Systems, Inc. (SSS) has worked closely - through contracts with the US Agency for International Development (USAID) - with USAID and the Office of the Global AIDS Coordinator (OGAC) at State Department to rapidly develop and implement globally within 6 months in 2004 the Country Operations Plan and Reporting System (COPRS) for EP tracking and reporting. This global effort initially included the 15 priority EP countries and, in 2005 and beyond, is being expanded for additional countries. Key to successful and continued use is to ensure that COPRS is able to report on the US achievements in combating HIV/AIDS as interventions and countries multiply in this pandemic. SSS through a USAID/Uganda project - Monitoring and Evaluation of Emergency Plan Progress (MEEPP) – is developing and implementing a comprehensive HIV/AIDS performance management, monitoring, and reporting system to support the USG EP team in Uganda

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Emerging Trends and Challenges in IT Management to manage and report on HIV/AIDS interventions at country level and in COPRS. In another example in Zambia, the Partner Reporting System uses an automated link to COPRS for transfer of indicator and financial data. The panel will cover:

•

Successfully coordinating efforts across diverse US Federal Agencies working on a global scale to fight HIV/AIDS

•

Maximizing data collection and reporting efficiency through data standards and data exchange:

•

The COPRS experience: Common and customized features of a global tracking and reporting system to meet USG user needs centrally and at country level (including training users in remote locations and in secure USG environments) Results of international agreements and coordination efforts between USG and various international agencies including UNAIDS

•

•

The MEEPP Project: Meeting the needs of diverse clients to battle HIV/AIDS by maximizing available information technology to ensure efficiency and accuracy

•

Additional country examples of adaptations and linkages specifically defining ways that IT management challenges have been met

Transforming Technologies: Organizational and Leadership Dimensions

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zations require technologies that can transform their operations into sleek, agile business processes. The emerging technologies of today’s marketplace focus primarily on enhancing inter and intra-organization processes such as communication, information sharing, teamwork, and collaboration. These processes have become increasingly important as organization break down stovepipes, work cross-functionally, and create partnerships and alliances with other organizations in efforts to transform their operations for the information age. Technologies such as wiki’s, peer-to-peer networks, discussion boards, groupware, and instant messaging are being used to support these new information age modes of working, thinking, and organizing. As in the industrial age, the success of these emerging technologies is highly dependent on the human factor. Organizational practices, culture and climate, leadership, politics, cognition, and human behavior all combine to moderate the success of today’s communication and collaboration technologies. This ninety minute panel will examine these moderating variables, providing empirical suggestions for their successful management in transformed organizations. The panel is divided into two segments. In the first sixty minutes, the panelists will give presentations focusing on organizational, cognitive, and leadership variables and their interaction with communication and collaboration technologies. Dr. Gingrich will examine the variables of organization culture and behavior and how they interact with emerging technologies. Dr. Irving Lachow will examine the variables of cognition and leadership and how they interact with emerging technologies. Both panelists will draw on empirical data from the literature as well as best practices from the private and public sectors. For the last thirty minutes of the panel, there will be a forum involving both the panelists and the audience. The forum is intended to integrate the presentations with the audience members’ experience. For example, how useful are the best practices to audience members’ organizations? Are the lessons learned more useful in the private sector than in the public sector? Should they be modified for the public sector? If so, how? The panel moderator will facilitate the discussion.

Moderator: Dr. Gerry Gingrich, Faculty Information Resources Management College National Defense University, Fort McNair Washington, DC 20319-6000 P: 202-685-2103, [email protected]

Web-Based Systems for Distance Education and e-Learning: Towards e-Learning Online Communities Georgios A. Dafoulas, Senior Lecturer

Panelists: Dr. Gerry Gingrich, Faculty

Curriculum Leader Pedagogy

Information Resources Management College National Defense University, Fort McNair

School of Computing Science, Middlesex University

Washington, DC 20319-6000 Dr. Irving Lachow, Faculty Information Resources Management College National Defense University, Fort McNair Washington, DC 20319-6000

Today’s global, interconnected society places increasing competitive demands on our organizations and their leadership. Challenges and threats arise not just locally but also globally through a web of relationships and interconnections. Speed to market, just-in-time logistics, realtime design, and tailored, niche markets are all characteristics of today’s information rich, fast-paced, and highly competitive environment. To respond with the necessary speed and intelligence for survival, organi-

[email protected] ABSTRACT This tutorial draws on previous experiences of two EU-funded projects (distance education and intercultural learning over the Internet), a distance education programme delivered to eight locations in five countries from Europe, Asia and Africa, the coordination of a 16partner think-tank consortium for the study of cognitive systems and the international workshop on e-Learning Online Communities. Both in EU and the US we are witnessing an attempt for the simultaneous development of courses and learning materials specifically designed for global students alongside the e-learning technologies and pedagogical tools required to support them. The benefits of these efforts primarily result in the professional development of e-learning practitioners and researchers including designers of courses, developers of learning con-

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1068 2006 IRMA International Conference tent, tutors and trainers involved in distance education, programme administrators, and managing personnel of institutions teaching overseas. E-learning developers, trainers, tutors and managers, aim on advancing their e-tutor skills as their role is crucial in facilitating distance learners undertaking bilateral online programmes internationally. This enables such e-learning professionals to provide competent support of students through a variety of e-services and web applications. Furthermore, diversity management skills are highly needed for improving mutual learning, trust and confidentiality. Cultural awareness is needed to provide better market opportunities, for fostering the competitiveness of content and language players on the global network. In the European Union’s rich cultural diversity, values, attitudes and beliefs vary so much as to cause problems without proper intercultural and multicultural awareness. Worldwide, there is a great need for citizens to have a better understanding of the level of their own intercultural and multicultural competence. The ICT evolution of the past two decades leading to the proliferation of the World Wide Web was the primary factor for Online Communities to transform from a social interaction medium to virtual environments with commercial value. The increased popularity of Online Communities triggered the diversification of the community building process depending on those aspects forming the core of a community and enticing Internet users to become members; hence the birth of online communities focusing on education. Currently several institutions have created eLearning Online Communities and there is early evidence of their future success.

Outline Following from the above abstract, the tutorial consists of four sessions:

Short bio of the lead presenter Dr George Dafoulas is the curriculum leader in pedagogy for the Middlesex University Global Campus that offers undergraduate and postgraduate courses in five countries over three continents. Global Campus formed a substantial part of Middlesex University’s ‘Queens Award’ in 2004. George is a senior lecturer in Business Information Systems for School of Computing Science at Middlesex also visiting the School of Informatics at the University of Manchester. He has worked on thirteen projects funded by EU, DTI, EPSRC and ESRC. His written work includes more than thirty publications in journals, international conferences and books while his Global Campus book on “Methodologies and Tools for the Engineering of Information Systems” is in press. He is the sole organizer of the “e-Learning Online Communities” international workshop series, editor of five international journals and codirector of the Magnum Opus Partnership that specializes in e-services for the education sector.

Listening to Learn: Educating Information Age Leaders Kathleen M. Schulin, DPDS, Professor Leader, Strategic Leader Development Program National Defense University Information Resources Management College Ft. Lesley J. McNair, Washington, DC 20319 P 202-685-2787, [email protected]

Session I: From theory to practice – pedagogy online Examines the feasibility of transferring distance education pedagogical aspects online and using the web as a medium for delivery, communication and assessment.

Mary S. McCully, PhD, Professor Chair, Chief Information Officer Department

Session II: Understanding culture in the web Provides evidence of awareness-related failures in using web based applications and e-services by exploring a number of case studies.

National Defense University Information Resources Management College Ft. Lesley J. McNair, Washington, DC 20319

Session III: Web-based applications for distance education delivery and support Describes fundamentals of Virtual Learning Environments, discusses their main features and attempts an overview with a series of hands on activities.

Session IV: Developing and evaluating an e-Learning Online Community Adopts a step-by-step interactive/participative approach of following the Community Centred Development suggested by Jenny Preece to develop an e-Learning Online Community and introduce an innovative multi-methodological evaluation approach.

Description of the target audience Primarily the target audience consists of e-learning professionals, particularly e-lecturers and e-tutors, trainers and e-strategists. Furthermore, professionals in the corporate sector with an interest in investigating training needs and developing training for staff may also benefit from the proposed tutorial content. Finally web developers, designers and user-centred design experts could find interesting this “alternative” twist on web information systems.

P 202-685-3178, [email protected] WORKSHOP ABSTRACT Educating the leaders of modern organizations requires information age learning tools and environments. Individuals have many different learning styles. Students engaged in graduate-level executive education also have many different constraints on their time. Yet, the prime pedagogy for education is text based. This means lots of readings. In 2004 Duke University, in concert with Apple made headlines by providing an iPod to every entering freshman. At the same time, the National Defense University’s Information Resources Management College began prototyping the integration of audio material, through the use of iPods, into a couple courses. This workshop will explore the results of the College’s 14-month prototype in a 3-graduate hour course—The Changing World of the Chief Information Officer. Additionally, through interaction with the audience, the workshop will identify best practices to consider in integrating audio material into graduate-level executive education classrooms. This prototype involved 233 students in 12 course offerings. The students were middle age, mid to senior level government managers and leaders. Each of the students involved in the prototype were offered an iPod upon arrival for the 1-week residential portion of a 5-week

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Emerging Trends and Challenges in IT Management eResident course. All students were given the opportunity to complete a 19-item questionnaire, with 16-Likert scale questions and 3-open ended questions. Seventy three percent of the students completed the questionnaire. What did these students tell us about their experience? How often, and for what length of time, did students use the iPod throughout the week? What were the students’ views of the impact on their learning, as a result of being issued an iPod with select course readings? Did students recommend the expansion of this prototype to other College courses? This workshop will discuss the survey results of these and other iPod prototype questions. Additionally, the workshop

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will explore the experiences conference attendees have with using audio material in the classroom. This workshop will close with a list of attendee developed best practices to consider in integrating audio material into graduate-level executive education classrooms.

DISCLAIMER The views expressed in this abstract are those of the authors and do not reflect the official policy or position of the National Defense University, the Department of Defense, or the U.S. Government.

Doctoral Symposium Submissions A Framework of Enterprise Resource Planning (ERP) Systems Implementation in Kenya: An Empirical Study Jim Otieno & Geetha Abeysinghe Middlesex University, School of Computing Science {J.Otieno, G.Abeysinghe}@mdx.ac.uk ABSTRACT Organisations have widely accepted Enterprise Resource Planning (ERP) systems as one of the choices to obtain competitive advantage. This study focuses on ERP implementation in Kenya, where the successful implementation rate is still low and many firms have not been able to achieve the intended goals. The research aims at developing an ERP implementation framework based on sound organisational, Information Systems (ISs) theories, and empirical findings. The work is still in its preliminary stage and therefore, any conclusions drawn at this time must be characterised as premature, although our preliminary analysis of the findings has already yielded some useful insights that were not found in the published literature and which are unique to Kenyan setting. This sets the foundation for further investigation.

Keywords: ERP; Business process reengineering; ERP systems implementation; CSFs, case study

1.0

INTRODUCTION

Hong and Kim (2002) define Enterprise Resource Planning (ERP) systems as, “configurable information systems packages that integrate information and information-based processes within and across-functional areas in an organisation”. The main aim of ERP is to integrate functional divisions within organizations (like finance, marketing, procurement, inventory, sales and distribution, human resources planning and payroll). There are significant contextual differences between firms implementing ERP package in Kenya and ERP vendor firms which are mainly based

in Europe and North America. Orlikowski (2000) asserts that where such contextual differences between the package and implementing organisation exist, it is important to explicitly consider the sources of contextual differences and how the differences may affect the implementation and subsequently the use of the ERP systems. This research is aimed at exploring the reciprocal interaction between technology and context. It looks at how organisational characteristics influence ERP implementation outcome in Kenyan context, and in return how the ERP system influence the organisational characteristics. Preliminary findings revealed limited usage of ERP systems in Kenya, and limited scope of implementation in terms of number of modules implemented, resulting in reduced expected benefits. The study confirmed Markus et al. (2000) findings that many ERP systems fail to be used to full functionality once installed within an organization. Limited functionality is an indication that ERP is being used as a transaction processing system rather than a strategic tool as observed in Kenya. This state of affairs speaks of the limitation of scholarly knowledge about how ERP acts in practice. The research continues in a similar trend as described here as we attempt to understand the organizational and national factors which contribute to successful system implementations.

2.0 LITERATURE REVIEW ERP systems are generic systems which may be configured to meet a range of organisational requirements (Hong and Kim, 2002). Soh et al. (2000) discovered significant mismatch between the context of the implementation environments and the context embedded in the package while carrying ERP implementation study in a hospital in Singapore. The authors attributed the mismatch to differences between the structures embedded in the organisations and the nations (as reflected by its procedures, rules and norms) and those embedded in the package. There are significant contextual differences between firms implementing ERP package and ERP vendor firms. Given that foreign vendors have 100% market (source: research data) in Kenya, there is likely to be considerable cultural conflicts considering that these systems were developed in Western countries and are being implemented in Kenyan context which have built-in value bias reflecting the value priorities of the culture in Western countries (Soh, 2004). Paradoxically, there is no literature on ERP implementation experiences in Kenya and Africa at large in spite of many scholars calling for the documentation of ERP implementation experiences, as a way of organisational learning in order to avoid implementation pitfalls which can lead to catastrophic outcomes (Leopoldo and Otieno, 2004).

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1070 2006 IRMA International Conference Recht and Wilderom (1998) write that the transfer of ERP into developing countries is likely to face the “double-layered [national and organisational] acculturation” problem. However, culture factor was given more attention only in recent two years (Al-Mashari et al., 2003; Hong and Kim, 2002; Motwani et al., 2002; Boersma and Kingma, 2005). Hence, it is essential to address cultural dimensions that cover both these two layers. This is consistent with the approach of Krumbholz et al. (2000, p. 269) who argue that: “corporate and national cultures can be described using multiple dimensions which give us a set of overlapping characteristics with which to describe aspects of culture”. Literature seems to prioritize critical success factors in order to advice managers about which of the factors are most critical for the organization (Ward et al., 2005; Markus et al., 2000., 2001; Shanks et al., 2000). Organizations and researchers may find consulting a list of a priori ‘factors of successes’ beneficial, although such items are not inthemselves keys to a preferred outcome. Rather, they tend to focus attention on controlling and simplifying innately complex situations.

5.0 PROPOSED ENTERPRISE RESOURCE PLANNING (ERP) IMPLEMENTATION FRAMEWORK The proposed model (Figure 1) attempts to represent ERP implementation phenomenon in a real world situation as basis for achieving greater understanding in the Kenyan context. Figure 1: Proposed Model

Project management & Standards

Organisational context

Critical success factors

Organisational culture Organisational structure Workforce competency Management style / strategic orientation Organisational units interdependence Competition environment Size and complexity of org Organisation IT Infrastructure Business Process Maturity Job satisfaction

3.0 RESEARCH METHOD By definition, case study research is well suited to the study of IS implementation, especially when context is important and the phenomenon is contemporary, which the researcher has no control over, the research is largely exploratory and it addresses the ‘how’ and ‘why’ question (Benbasat et al., 1987). Multiple cases were used to increase methodological rigor of the study through “strengthening the precision, the validity and stability of the findings” (Miles and Huberman, 1994). Contrary to common misconception that case studies provide little basis for scientific generalisation, case studies are generalisable to theoretical propositions, not to populations or universes (statistical generalisation) (Yin, 1994). In total, we carried out the study in four large organisations in Kenya. Two of the organisations are state-owned with one running SAP R/3, and the other EBIZFRAME. Two organisations are privately owned with one running SAP R/3, and the other BAAN.

3.1 Validity Through triangulation of sources (diverse range of individuals and organisations); methods (of data collection: interviews, press publishing, meeting minutes); and theories (draws from TAM Model, McLean and DeLone Success Model (2003), and Trauth Model (2001) serving as a theoretical base), the research is capable of providing multiple measures of the same phenomenon in each setting resulting in the development of converging lines of inquiry. Thus, the construct validity of the case study could be more convincing and accurate. Moreover, by using replication logic of the same interview protocol in multiple-case studies, the external validity of the information collected can be obtained.

4.0 DATA ANALYSIS Content analysis was the method chosen for analysing data because it is well suited to surface themes and concepts from interviews and summarises great volumes of qualitative data. We interviewed 27 respondents. An initial coding sheet was created based on the literature, researcher’s personal experience, and notes taken during the interviews. Frequency was calculated for each item representing the number of times that item (concept) was mentioned in the interviews. Totals and averages were computed for each item, dimension, and category. This data provide a good indication of the relative importance of the ideas to the participants. Ten major themes were identified. (The constructs and dimensions are visually shown in the proposed model in Figure 1).

Vendor Benefits for ERP

Orgnisation Motivation

On time On budget

Org actual benefits Individual Benefits

ERP Implementation & Adaptation ERP Implementation Scope

Organisation Anticipated benefits

ERP Outcome

ERP Project Outcome

Operational / Functional Benefits

Degree of integration ERP Implementation Approach

Strategic Benefits

External Environment Competitive environment Legislation /Political Economic Professionalism

National and Organisational context National and Organisational influence on ERP

ERP system implementation and negotiation ERP influence on organisation

ERP implementation outcome

Organisational context is a multidimensional construct. Some of the organisational aspects which emerged from data analysis to be of great relevance to ERP implementation and usage in Kenya are briefly discussed below. Organisational culture Initial findings show that organisational culture significantly affects ERP system implementation right from adoption. It also plays a great role in adaptation and conflict resolution during ERP implementation. There were numerous cases where organisational culture and ERP culture conflicted in our case study organisations. We may find it relevant to incorporate Hofstede’s “power distance” and “uncertainty avoidance” culture dimensions, and Trompenaars’ universalism versus particularism national culture dimension as antecedent variables for organisational culture. Organisation structure This construct tends to measure the degree of formalisation, whether the organisation is centralised, and the global structure of the organisation. Empirical data shows that there is correlation between organisational structure and degree of integration. Interdependence among organisational units From data, the strength of the link between derived organisational benefits is influenced by the degree of interdependence among organisational units. If sub-units are highly interdependent, then there is likely to be high degree of integration whereas if sub-units are relatively autonomous, then the effect of coordination improvements resulting from integration will be relatively less. Management style and strategic orientation This construct is derived from Huang and Palvia (2001) work. We find the three dimensions: leadership style, efficiency control, management

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Emerging Trends and Challenges in IT Management theory, from Cameron and Quinn (1999) competing values framework, relevant to this work and could be used to make this construct operational Organisational Motivation (s) Decision to adopt ERP and adaptation decisions result from motivation pressures (e.g. perceived need) and are based on organisational anticipated benefits. However, decisions are greatly influenced by a variety of things that include (e.g. budget, IT infrastructure) and environmental realities (e.g. knowledge, cultural implications). Vendor Benefits Vendor benefits reflect what ERP is capable of accomplishing for an organisation from the vendor perspective. Vendor benefits significantly influence organisation anticipated perceived benefits which in turn influence motivation for ERP implementation. External environment Environment is the setting and associated influences that directly affect perceptions, decisions, operations, and outcomes. For this research we limit this construct to three dimensions namely: legal, professional and competitive environment which we identified to have great influence on ERP implementation. Scope of implementation Scope specifies what the organisations wishes to integrate. Our initial observation shows that the scope of implementation directly affects the degree of integration. The number and nature of modules implemented are the two identified dimensions of the scope of implementation. Examples include: internal (organisational, divisional, and departmental), external (customers, suppliers, government, competitors, alliances, industry organisations, and the public), and geographic area. This would be made operational by examining the number of modules implemented by the case study organisations and the nature of the modules implemented. Degree of integration Degree of integration refers to the amount of integration resulting after ERP implementation. There is correlation between the scope of implementation (number of modules variable) and degree of integration but number of modules dimension is not the sole determinant of degree of integration. Organisational Benefits The benefits derived from ERP implementation by the organisation and by individuals. Benefits were originally conceived as one-dimensional construct. The results from qualitative research suggested that benefits were multidimensional constructs. Dimensions identified are: strategic benefits, operational benefits and individual benefits. The benefits are greatly influenced by the degree of integration and the project management and standards construct. A complete and detailed coverage of the model can be found at URL: http://www.cs.mdx.ac.uk/research/PhDArea/research_students/Jim/ jo_profile.html

6.0 FURTHER WORK This work is still at its preliminary stages. Further is being carried out to identify items for some dimensions, and to determine the relationships and interrelationships among the constructs. Initial findings have already yielded some useful insights that were not found in the published literature and which are unique to Kenyan setting. This set the foundation for further investigation.

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7.0 REFERENCES Amaoko-Gyampah, K., and Salam, A.F. (2005), “An extension of the technology acceptance model in an ERP implementation environment”, Information & Management, Vol. 41, pp. 731-745 Al-Mashari, M., Al-Mudimigh, A., and Zairi, M., (2003), “Enterprise resource planning: A taxonomy of critical factors”, European Journal of Operational Research, Vol. 146, pp. 352-364 Benbasat, I., Goldstein, D.K., and Mead, M., (1987), “The case research strategy in studies of Information Systems”, MIS Quarterly, Vol. 11, pp. 369-386 Boersma, K. and Kingma, S. (2005), “Developing a cultural perspective on ERP”, Business Process Management Journal, Vol. 11 No. 3, pp. 123-136. Cameron, K. S., & Quinn, R. E. (1999), Diagnosing and changing organizational culture. Reading: Addison-Wesley. DeLone, W.H., and McLean, E.R. (2003), “The DeLone and McLean Model of Information Systems Success: A Ten-Year Update”, Journal of Management Information Systems, Vol. 19, pp. 9-30. Hofstede, G. (2001), Culture’s Consequences: International Differences in Work Related Values, 2001 edition, Thousand Oaks, CA: Sage Publications, Inc. Hong, K.K. and Kim, Y.G. (2002), “The critical success factors for ERP implementation: An organisational fit perspective”, Information and Management, Vol. 46, pp. 25-40 Huang, Z., and Palvia, P. (2000), “Implementation issues in developing and advanced countries”, Business Process Management Journal, Vol. 7 No. 3, pp. 276-284 Krumbholz, M. and Maiden, N., (2001), “The implementation of enterprise resource planning packages in different organisational and national cultures”, Information Systems, Vol. 26, pp. 185204 Kumar, K. and Bjorn-Anderson, N., (1990), “A cross-cultural comparison of IS designer values”, Communication of the ACM, Vol. 43, pp. 23-26 Leopoldo, E. and Otieno, J., (2005), “Critical Success Factors of ERP implementation”, Encyclopedia of Information Science and Technology, pp. 628-633 Markus, M.L., Axline, S., Petrie, D., and Tanis, C., (2000), “Learning from adopters’ experiences with ERP: Problems encountered and success achieved”, Journal of Information Technology, Vol. 15, pp. 245-265 Miles, M. B. and Huberman, A. M., (1994), “Qualitative Data Analysis: An Expanded Sourcebook”, 2nd Edition, Sage, CA. Motwani, J., Mirchandani, D., Madan, M., and Gunasekaran, A., (2002), “Successful implementation of ERP projects: Evidence from two case studies”, International Journal of Production Economics, Vol. 75, pp. 83-96 Orlikowski, W., (2000), “Using technology and constituting structures: a practice lens for studying technology in organisations”, Organisation Science, Vol. 11 No. 4, pp. 404-428 Recht, R., and Wilderom, C. (1998) “Kaizen and culture: on the transferability of Japanese suggestion systems”, International Business Review, Vol. 7, pp. 7-22 Robey, D., Ross, J.W., and Boudreau, M., (2002), “Learning to Implement Enterprise Systems: An Exploratory Study of the Dialectics of Change”, Journal of Management Information Systems, Vol. 19 No. 1, pp. 17-46 Shanks, G., Parr, A., Hu, B., Corbitt, B., Thanasankit, T., and Seddon, P., (2000), “Differences in Critical Sucess Factors in ERP Systems Implementation in Australia and China: A Cultural Analysis”, 8th European Conference on Information Systems ECIS, Vienna , Austria, (2000) Soh, C., Sia, S.K., and Tay-Yap, J., (2000), “Cultural fits and misfits: is ERP a universal solution?”, Communication of the ACM, Vol. 43 No. 4, pp. 47-51 Trauth, E.M. (2000). The Culture of an Information Economy: Influences and Impacts in the Republic of Ireland, Dordrecht, The Netherlands: Kluwer Academic Publishers.

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1072 2006 IRMA International Conference Trompenaars, F. (1993). Riding the waves of culture: Understanding diversity in global business. New York: Irwin. Ward, J., Hemingway, C., and Daniel, E. (2005) “A framework for addressing the organisational issues of enterprise systems implementation” Journal of Strategic Information System, Vol. 14 No. 3, pp. 97-119.

Attracting Female High School Students to the IT Industry Donna M. Grant, DePaul University School of Computer Science, Telecommunications & Information Systems 243 South Wabash Avenue Chicago, IL 60604-2301, [email protected] INTRODUCTION The under-representation of women in the Information Technology (IT) industry is a critical Information Systems phenomenon. According to the National Center for Education Statistics (2003), in the 20022003 academic year, although women earned 57% of the bachelor’s degrees in all disciplines, they only earned 27.0% of the bachelor degrees in IT. Additionally, in September 2005, the Society of Information Management released a report predicting a shortage of IT professionals with project management and business-savvy technical skills due to the soon-to-retire IT baby boomers (McGee, 2005). As a society, why should we be concerned with the under-representation of women in the IT field? As Americans, many of us consider diversity as fairness or equal opportunity. This is true, but there is more at stake than just fairness or equal opportunity when we contemplate women in the IT industry. As Ed Lazowska (2002) stated, “Engineering solutions are enriched and enhanced by the diversity of the engineering teams that create these solutions. A non-diverse engineering workforce inevitably leads to diminished-indeed, improvised engineering solutions” (p. 11). Furthermore, technology has become such an essential element of our society that for the creators of technology solutions to be dominated by one gender is truly a travesty.

representation and attract high school girls to entering an IT field for their college major.

LITERATURE REVIEW During the past two decades, numerous researchers have reported on the shrinking pipeline of women in IT and the possible barriers that effect female high school students’ choice of IT as a major. (Camp, 1997; O’Lander, 1996). In this preliminary report, I have outlined only a few factors reported in previous research. For the final submission, a comprehensive table of barriers will be created to construct a model. The literature cites numerous explanations for the under-representation of women in IT. According to Teague (2000) many girls do not view information technology as a plausible career alternative. Rowell et al. (2003) report “…enjoyment and interest have been shown to be a major reason students select a career…” (p. 54). Their research illustrates that males were 17.0% more likely to have a career interest in IT. Girls may have the misconception that the fundamental career in IT is a programmer, a social loner, sitting in a dark room glaring at a computer all day. (Beyer et al., 2004). Additionally, during their early childhood years, girls tend to not have the same “magnetic attraction” to computers as some of their male counterparts (Margolis & Fisher, 2002). Girls usually do not identify themselves as “hackers” or “computer geeks,” and due to social gender stereotyping, the computer has been labeled as a “boy’s activity” (Kiesler et al., 1985; Moorman & Johnson, 2003). Girls who are attracted to the IT field are so outnumbered that there is a severe “sense of isolation” (Frenkel, 1990). As if this sense of isolation were not enough, boys’ compelling attraction to computers and gender stereotyping facilitate the crippling perception of some parents and teachers that “boys and men, not girls and women will excel in and enjoy computing” (Margolis & Fisher, 2002, p. 16). Furthermore, one of the most cited research concerns regarding the under-representation of women in IT is the view that girls and women do not have sufficient female IT mentors and role models (Cohoon, 2002; Spertus, 1991; Townsend, 2002). As a result, the computer culture is an alienating and difficult environment for girls to succeed (Pearl et al., 1990). Additionally, researchers have reported that some women who have considered a major in IT feel less self-confident in their computer capabilities (Beyer et al., 2004; Shashaani, 1994). Considering the likelihood of a snowballing effect with many of these explanations, it is no wonder that some girls lack the inspiration to choose IT as a major.

METHODOLOGY RESEARCH PROBLEM My research involves the attitudes of high school girls toward IT, and what might be done to encourage their interest in IT careers. Prior research on this topic has yielded isolated and often conflicting results. To remedy this situation, my research will produce a consolidated, comprehensive model to address the following research questions: • • • •

What are the major factors that contribute to why fewer high school girls choose IT as a major in college? Which factors are most significant? Are there any factors that were not identified in previous research? What are the interrelationships among these factors?

OBJECTIVES We must attract more women to the IT industry to improve the diversity of IT solutions, to generate new ideas and to create a technology workforce that mirrors the world we live in. This research will produce a comprehensive model identifying the factors that cause fewer high school girls to choose IT as a major. The model will further distinguish the most significant factors and identify the relationships amongst them. The results of these findings will enable researchers and practitioners to develop policies and programs to reverse the trend of under-

The methodology will encompass three major activities and will be utilized to conduct a multi-step research approach. First, a literature review will be conducted to create a comprehensive, synthesized model of the major factors that cause fewer high schools girls to choose IT as a major. The work of previous researchers will be analyzed, combined, and categorized to display one common model of the major factors. Second, a survey will be conducted to serve as a mechanism to validate the model, to identify the most significant factors, to discover additional factors, and to recognize the interrelationships between factors. Prior to the administering the survey a pilot will be conducted to pretest and validate the survey instrument and the administration process. The survey will be structured utilizing a combination of a Likert scale and open-ended questions. The survey will be administered to female, junior and senior high school students in the Chicago area. Additionally, a monetary incentive will be provided to the participants to increase the response rate. Third, the model will be reconstructed to incorporate the knowledge gained from the survey.

OUTCOMES AND EXPECTED SIGNIFICANCE The underlying factors explaining why fewer female high school students are interested in a career in IT are likely to be vast and complex. For our society to ensure diversity of ideas in the creation of technology solutions, we must develop policies, practices, and programs that serve

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Emerging Trends and Challenges in IT Management as a vessel to increase the number of women in the IT industry. Particularly during a time of declining IT enrollments, the prediction of an IT workforce shortage, and the current under-representation of women in the IT industry, IT researchers and practitioners must develop successful strategies to attract women to the IT field. A comprehensive model of the factors and their relationships will serve as a foundation for exploring new strategies and programs to attract high school girls to the IT industry.

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The Information Cycle in the European Commission’s Policy-Making Process Evangelia Koundouraki Manchester Metropolitan University Department of Information and Communications

REFERENCES Beyer, S., Rynes, K., & Haller, S. (2004). Deterrents to women taking computer science courses. IEEE Technology and Society Magazine, 23(1), 21-28. Camp, T. (1997). The incredible shrinking pipeline. Communications of the ACM, 40(10), 103-110. Cohoon, J. M. (2002). Recruiting and retaining women in undergraduate computing majors. ACM SIGCSE Bulletin, 34(2), 48-52. Frenkel, K. A. (1990). Women & computing. Communications of the ACM, 11(11), 34-46. Kiesler, S., Sproull, L., & Eccles, J. S. (1985). Pool halls, chips, and war games: Women in the culture of computing. Psychology of Women, 9(4), 451-462. Lazowska E. (2002) 19 th Century Design in a 21st Century World. ACM SIGCSE Bulletin, 34(2), 11-12. Margolis, J., & Fisher, A. (2002). Unlocking the clubhouse: Women in computing. Cambridge, Massachusetts: MIT Press. McGee, Marianne Kolbasuk. (2005). New program aims to woo more kids into IT careers. InformationWeek. [Online]. Available: http://informationweek.com/ story/showArticle.jhtml;jsessionid=L03QZWT3ZXB32Q SNDBCSKH0CJUMEKJVN?articleID=170703150 Moorman, P., & Johnson, E. (2003). Still a stranger here: Attitudes among secondary school students towards computer science. Proceedings of the 8 th annual conference on innovation and technology in computer science education, 193-197. National Center for Educational Statistics. (2003). U.S. Department of Education, Postsecondary Studies Division, Washington, D.C. O’Lander, R. (1996). Factors effecting high school student’s choice of computer science as a major. Proceedings of the symposium on computers and the quality of life, 25-31. Pearl, A., Pollack, M. E., Riskin, E., Thomas, B., Wolfe, E., & Wu, A. (1990). Becoming a computer scientist. Communications of the ACM, 33(11), 47-57. Rowell, G. H., Perhac, D. G., Hankins, J. A., Parker, B. C., Pettey, C. C., & Iriarte-Gross, J. M. (2003). Computer-related gender differences. Proceedings of the 34th SIGCSE technical symposium on computer science education, 54-58. Shashaani, L. (1994). Gender-differences in computer experience and its influence on computer attitudes. Journal of Educational Computing Research, 11(4), 347-367. Spertus, E. (1991). Why are there so few female computer scientists? AIT Technical Report 1315. MIT AI Lab. Teague, J. (2000). Women in computing: What brings them to it, what keeps them in it? GATES, 5(1), 45-59. Townsend, G. C. (2002). People who make a difference: Mentors and role models. ACM SIGCSE Bulletin, 34(2), 57-61.

Geoffrey Manton Building, Rosamond Street West Off Oxford Road, Manchester, M156LL T: +44 161 2476144, [email protected] AIMS AND OBJECTIVES This research aims to explore the information cycle in the European Union (EU) policy-making process, within the specific context of the European Commission, with an emphasis on the information-seeking behaviour, information requirements and satisfaction levels of its policy makers. This will be achieved through the realization of the following objectives: 1.

1.

2.

3.

to critically analyze information theories, concepts and paradigms related to policy and decision-making activities within an organizational context and to apply these to the European Commission; to identify and categorize the different information types 1 , media2 and sources3 used in the policy-making process by the Enterprise Directorate-General and the Information Society Directorate-General of the European Commission for Innovation policy-making (DG Enterprise and Industry) and e-Business 4 policy-making (DG Information Society) respectively; to identify and analyze the information behaviour and needs of the European Commission’s policy makers in the selected DGs as policy-making processes unfold, and to develop an information processing framework for that part of the EU policy-making process involving the European Commission.

LITERATURE REVIEW Information is a vital component in any political system (March, 1987), key constituent of organizational life and significant variable of decision- and policy-making process. However, information as a concept is elusive and therefore, hard to contextualize either in isolation or as a continuum of data, information and knowledge. The typical distinction between these context is that data are “observations of states of the world” easy to be stored and managed, while information is data with relevance and purpose and knowledge “a fluid mix of framed experience, values, contextual information and expert insight that provides a framework for evaluating and incorporating new experiences and information” (Davenport, 1997; Marchard and Davenport, 2000; Drucker, 1988; Davenport and Prusak, 1998, p.5;). Knott and Wildavsky (1980) and Lindquist’s (1990) approaches on information and knowledge impel further analysis of these concepts and their role in the policy process. Frishammar (2003) claimed that information may be classified as soft or hard, while Kaye (1995) classified information according to its format, status and location. He also stressed the significance of the way the recipient of information perceives a specific source within the context the information is disseminated. 5 Lord and Maher (1990, p.10) have examined several information processing models (e.g. rational, limited capacity, expert and cybernetic) contending that “each model has advantages with respect to different criteria”. Corner et al. (1994) scrutinized the parallel process model, which integrates organizational and individual level information processes and involves the following stages: attention encoding, storage/retrieval, choice and outcomes, while Davenport’s (1997) model

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1074 2006 IRMA International Conference discerns four steps: determining information requirements; capturing information; distributing information, and using information. In addition to this, information flows delineate the picture of an organization, bound together by formal and informal channels of communication. Katz and Kahn have depicted three information flow directions within organizations: communication down the line; communication upward, and horizontal communication (Gilchrist, 1985). Organization theory in addressing the question ‘Why organizations process information?” suggests two answers: to reduce uncertainty and equivocality. 6 Uncertainty could be perceived as ‘the difference between information processed and information required to complete a task’ (Tushman and Nadler, 1977, p. 615) and consequently, organizations are expected to be ‘prepared’ to cope with it. Studies on organizational design have also shown that information is used within an organizational environment in order to reduce or remove uncertainty (Tushman and Nadler, 1977, Frishammar, 2003). Many scholars have examined information seeking behaviour by occupational categories (e.g. scientists and engineers, humanities scholars, managers and so on), and developed a number of information seeking models (Wilson, 1981; Krikelas, 1983; Kuhlthau, 1988). Even though academics examined the composition of the European Commission and its role in various policy areas, there is lack of research on the information needs of the Commission’s policy-makers and information dissemination and use during the whole policy-making process. The overarching purpose of this research is to systematically examine the European Commission’s policy-making processes through a thorough examination of existing information processing models and through an information flow prism. The European Commission is a complex organization (Cram, 1994), which lies at the heart of the EU system of governance (Nugent, 1997) and has a formal role in EU policy-making. The Commission’s roles and powers have been scrutinized through various theoretical prisms (neofunctionalism, intergovernmentalism, institutionalism, and so on). The European Commission, as an organization, is handling huge amount of data and information for its policy- and decision-making processes and identification and classification of this information might help to better understand the way policy-making unfolds and its policy makers’ information needs and requirements. In addition, an outline of the European Commission’s organizational setting will enhance the understanding of the major actors and processes in policyand decision-making and facilitate the identification of the channels, formal and/or informal, through which information travels, and define the information requirements and needs of the Commission’s policy makers. The Commission has a multi-tiered hierarchical structure; the lower echelons of the institution, in general terms, are charged with more administrative and technical aspects of the policy and decision-making process, while the upper echelons are concentrated on political and sensitive aspects of the Commissions duties (Nugent, 1999). The Commission officials compose a special ‘microcosm’ of European public space. From an ‘informational’ point of view, information is a wheel for its administrative and political functions within the Commission. Its policy makers are charged with the task of making important decisions within the enlarged and increasingly complex European Union and these are the result of continuous formal and informal interactions, negotiations and bargaining between various internal and external actors (e.g. other European institutions, interest groups, NGOs, lobbying etc.). The focus of this research is therefore, to explore the information needs of the European Commission and the extent to which the policy-making process can be made more effective and efficient by better structuring of information acquisition, filtering and sharing. Expected outcomes There is a dearth of research on information requirements in the EU policy-making process which this project will address. Specifically, this research will contribute to the body of academic knowledge of policymaking models within the information cycle and information flows

paradigm of information science by determining the role and potential of information resources and processes in policy-making. It will explore (a) the dynamics of the policy cycle (Stone et al., 2001), and (b) who the major internal and external actors are in order to examine the information dimensions of the policy cycle. It will focus on the types of information gathered, processed and used for the policy-making process in the examined DGs of the European Commission, how this information is acquired by policy-makers as policy-making processes unfold (Saunders and Jones, 1990), and how policy-making effectiveness and efficiency might be enhanced by filtering information. In order to accomplish the aim of this study, the research will also determine: (a) the types of information policy makers need and use for policy-making; (b) how and where do policy makers obtain the information used for policy- and decision- making; (c) how this information is filtered and cross-checked during the various stages of the policy-making process so as to be accurate, up-to-date and relevant, (d) how information for policymaking is organized within a porous organization such as the European Commission.

METHODOLOGY The research will employ a case study strategy focused primarily on two units of the European Commission in its empirical phase. The selection of these DGs has two specific purposes. First, Innovation Policy (in DG Enterprise and Industry) and eBusiness Policy (in the DG Information Society) have common policy goals (see ‘Information Society thematic portal’) and policy development here may utilise and benefit from similar and/or identical information resources and processes. Second, selecting two Commission sub-units facilitates cross-comparison leading to the provision of a more generalized picture of information processes and flows. The following research methods will be employed: literature review and documentary analysis; survey (interviews and questionnaires). The latter will enable the researcher to enrich the findings of the literature review by (a) improving the categorization of different types of information in the policy-making process, (b) identifying the formal and informal media through which information for policy-making is acquired, disseminated and used (or refused) by policy makers and (c) specifying the Commission’s policy makers information needs in order to provide a richer picture of the information process in policy-making. The researcher has been accepted for a five-month in-service training at the Commission, which will enable her to acquire more specialized knowledge and practical experience of the studied policies and procedures of the Commission, and specifically within DG Enterprise and Industry,. Data analysis and discussion 1) Documentary analysis: textual and content analysis of relevant primary and secondary source material, 2) Questionnaire analysis: statistical and descriptive analysis, and 3) Interview analysis: content analysis supported by the software package NUD*IST which is used in qualitative data analysis in the context of case studies. The findings of the applied research methods will contribute to the establishment of an information cycle framework for the European Commission’s policymaking process. The accuracy of the research will be pursued through a process of evidence triangulation.

REFERENCES CORNER et al., 1994. Integrating Organizational and Individual Information Processing Perspectives on Choice. Organization Science, 5 (3), pp. 294-308. CRAM, L., 1994. The European Commission as a Multi-Organization: Social Policy and IT Policy in the EU. Journal of European Public Policy, 1 (2) pp. 195-217. DAFT, R.L. and LENGEL, R.H., 1986. Organizational Information Requirements, Media Richness and Structural Design. Management Science, 32 (5), pp. 554-571. DAVENPORT, T. H., 1997. Information Ecology: Mastering the Information and Knowledge Environment. New York: Oxford University Press.

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Emerging Trends and Challenges in IT Management DAVENPORT, T.H. and PRUSAK, L., 1998. Working Knowledge: How Organizations Manage What They Know. New York: Oxford University Press. DRUCKER, P., 1988. The Coming of the New Organization. Harvard Business Review, 66, pp. 45-53. FRISHAMMAR, J., 2003. Information use in strategic decision making, Management Decision, 41 (4), pp. 318-326. GILCHRIST, A., 1985. The flow and management of information in organisations In: B. CRONIN, ed., 1985. Information Management: From Strategies to Action. London: Aslib. KAYE, D., 1995. The Sources of information, formal and informal. Management Decision, 33 (5) pp. 13-15. KNOTT, J. and WILDAVSKY, A., 1980. If dissemination is the solution, what is the problem?, Knowledge, 1 (4), pp. 537-74. KRIKELAS, J., 1983. Information-seeking behaviour: patterns and concepts, Drexel Library Quarterly, 19, pp. 5-20. KUHLTHAU, C.C., 1988. Developing a model of the library search process: Cognitive and affective aspects, Reference Quarterly, 28, pp. 232-242. LINDQUIST, E.A., 1990. The third community, policy inquiry, and social scientists In BROOKS, S and GAGNON, A.-G. (eds.), Social Scientists, Policy, and the State. New York; London: Praeger, pp. 21-51. LORD, R. G. and MAHER, K. J., 1990. Alternative InformationProcessing Models and Their Implications for Theory, Research and Practice. The Academy of Management Review, 15 (1), pp. 9-28. MARCH, J.G., 1987. Ambiguity and accounting: the elusive link between information and decision-making, Accounting, Organizations and Society, 12, pp. 153-168. MARCHAND, D.A. and DAVENPORT, T. Mastering information management. London: Financial Times Prentice Hall, 2000. NUGENT, N., 1997. At the Heart of the Union: Studies of the European Commission. Basingstoke: Macmillan. NUGENT, N., 1999. The Government and Politics of the European Union. Basingstoke: Macmillan. SAUNDERS, C. and JONES, J. W., 1990. Temporal Sequences in Information Acquisition for Decision Making: A Focus on Source and Media. The Academy of Management Review, 15 (1), pp. 29-46. STONE, D. et al., 2001. Bridging Research and Policy. An International Workshop Funded by the UK Department for International Development, Radcliff House, Warwick University, 16-17 July 2001. TUSHMAN, M. L. and NADLER, D. A., 1978. Information Processing as an Integrating Concept in Organizational Design. The Academy of Management Review, 3 (3), pp. 613-624. WILSON, T., 1981. On user studies and information needs, Journal of Documentation, 37, pp. 3-15.

ENDNOTES 1

2

3

4

5

6

Types of information might include numerical data, factual knowledge, instructions and commands and so on (Kaye, 1995) and might differ in quality, currency, reliability, validity, objectivity, detail, coverage, and format. Media (or channels) refer to those mechanisms (e.g. face-to-face communication, emails) used to transfer information from a source to the policy maker. Information sources might be classified arranged by (a) format into oral vs. documentary, textual vs. audio-visual/multimedia, paper-based vs. electronic, (b) status into personal vs. impersonal and formal vs. informal, published vs. unpublished, open confidential vs. secret and (c) location into internal vs. external (Kaye, 1995). E-Business covers both e-commerce and the restructuring of business processes to make the best use of digital technologies. KAYE, D., 1995. The Sources of information, formal and informal. Management Decision, 33(5) pp. 13-15. Daft and Lengel (1986, p. 556) defined uncertainty as ‘the

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absence to information … As information increases, uncertainty decreases’, while claimed that equivocality means ‘ambiguity, the existence of multiple and conflicting interpretations about an organizational situation’.

B2B E-Commerce Adoption in the Financial Services Sector: A Strategic Perspective Moses Niwe, Dept of Computer & Systems Sciences Stockholm University & Kungliga Tekniska Högskolan Forum 100, SE-164 40 Kista, Stockholm, Sweden T: +46737867436, [email protected] ABSTRACT We analyze Internet/web based B2B e-commerce adoption with the perspective of B2B e-commerce initiatives being an integral part of the corporate strategy. The aim is to develop a framework of guidelines for B2B e-commerce adoption in the financial services sector, considering empirical data generated from expert opinions in the financial services sector.

INTRODUCTION Business to business (B2B) e-commerce technologies have gained strategic importance worldwide, in this age of globalization, innovation and pressure for increased quality in combination of lowering costs [1, 2, 3, 4]. For this reason, B2B e-commerce technologies have a key strategic role in organizations across all sectors in the global Internet based economy [5, 6, 7, 8]. This is confirmed with the literal exponential figures from Forrester, Gartner, IDC, Jupiter and other technology related research groups that all predict that worldwide B2B e-commerce revenue alone will exceed $15 trillion by the year 2010. The global networked economy, [1, 2, 10] with an open environment of web based B2B e-commerce [8] offers new opportunities for financial institutions [5, 7]. Information and knowledge have become strategic resources, upon which businesses make their decisions [11, 4, 12]. Strategic thinking has become important because there are many players, in the web based environment, and many business deals are possible [13]. In that regard many financial institutions need to draw up carefully structured B2B e-commerce strategies as part of the corporate strategy [14, 15]. Analysis of B2B e-commerce in the financial sector shows that famous business models like e-marketplaces do not necessary perform well [16, 17, 18]. Business models for e-commerce are constantly changing as far as financial institutions are concerned, and consequently, strategic alliances to meet new strategic business opportunities [19, 20, 21]. For example in 2000 according to Bank of America, press release, “Bank of America, one of America’s largest bank, and Ariba, Inc, the leading B2B e-commerce platform provider, jointly announced an agreement designed to broaden and accelerate B2B eCommerce adoption through an unprecedented, comprehensive suite of Internet-centric B2B financial services and a new B2B marketplace for Bank of America’s customers”. Available at http://www.bankofamerica.com/newsroom/press Many case studies in B2B e-commerce have been discussed [14, 13, 22]. But few empirical studies have concentrated on using the Internet for B2B e-commerce adoption from a strategic perspective, [9, 23], leave alone the financial services sector. With the continuous improvement of hardware and software in microcomputers and communication channels, [24], gone are the days of concerns with technical barriers such as speed in using the Internet in B2B e-commerce. Hence focus on strategic

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1076 2006 IRMA International Conference perspectives is paramount, if we are to maximize the use of the Internet for B2B e-commerce [3]. The earliest forms of e-commerce applications began with the electronic transfer of funds in about the early 70’s. These applications were limited to multinationals and a few small businesses that could afford [25]. Through Internet usage, with more electronic business processing, financial institutions have a unique position to exploit by being committed to enabling the payments of business transactions [26, 17, 3]. Ecommerce requires a financing mechanism, and financial institutions are best positioned to provide that service by virtue of their payments expertise [18].

Topic1: Key features of B2B e-commerce in the financial services sector Under this topic we will address the principles, products and partners for a B2B strategy. We will provide guidance in dealing with potential problems, e.g. managerial issues of B2B adoption. More specifically, shortage of in house skills (see table 1), budget constraints, lack of collaborative culture, and obtaining senior management approval will be addressed. Table 1: Example guideline People/skill requirements What are the people requirements as far as B2B e-commerce adoption in financial services sector is concerned?

RESEARCH PROBLEM B2B e-commerce is changing the commercial marketplace [3, 8]. Financial service institutions are ready to meet the gap as premier financial service providers for the evolving B2B exchange marketplace [17, 26]. However the road to B2B e-commerce adoption is littered with failures. Past failures has been attributed with focusing only on operational and implementation issues in some instances and ignoring the strategic aspects [30, 22, 23, 9].

RESEARCH OBJECTIVE AND QUESTIONS The goal of this research is to provide a framework of guidelines and recommendations for the adoption of B2B e-commerce in the financial services sector from a strategic perspective. This is done through answering the following questions. What factors should financial institutions consider when adopting and using B2B e-commerce technology to design services that are competitive, and efficient? How should financial institutions capture and adhere to requirements for information systems operating in a global economic environment?

• • • • •

Have visionary and committed senior management leadership specifically in charge of B2B ecommerce initiatives Build a knowledge base for B2B e-commerce initiatives In some instances, hire outside expertise Cultivate culture of internal change management for B2B e-commerce adoption Educate personnel about benefits of B2B e-commerce initiatives

Topic2: B2B e-commerce adoption strategy Under this topic issues addressed include, proven methodologies, products that allow gaining competitive advantage, sector- standard technologies. We will provide guidance for organizational issues such as, how to plan the business strategy (see table 2), what are the business goals and requirements (see table 3) for the operation of B2B e-commerce, what are the client issues before, during and after adoption and how to deal with them, where could the B2B e-commerce solutions be used to improve transactions with customers? Table 2: Example guideline Business objectives What are the key points of strategic planning that will allow you to maximize profits?

METHODOLOGY The study will use an integrated approach of qualitative techniques comprising in depth interviews and expert opinion [28, 17, 22, 13]. Qualitative research approaches are suitable for answering research questions of exploratory nature [29]. We chose this approach because the main body of empirical knowledge is tacit – it lies in people’s heads, experiences and work practices, most of which is not documented. Hence in this study we will interview experienced experts in the financial services sector [18]. We shall use interviews, observations and documentation reviews for data collection [17]. Expert opinion is used, to have the financial sector’s perspective central to the research process, hence providing means of validation for the research result. The research process follows with developing the research questions that are to be used in data collection using interview guides and observation checklist. A pilot study will be done to test the draft of our interview guide. The second step involves selecting the experts to be used and the appropriate data gathering techniques. The third step involves preparation and data collection. This will be accomplished with the help of an Interview guide, using structured and unstructured interviews with experts that were or are involved in the e-commerce implementation of the financial institution. The interviews will be recorded so the interviewer can replay them in evaluation and analysis of data to get all details that might have been missed in the live sessions. Documentation sources will include the firm’s documentation both past including archival records and present documentation where applicable. Other sources will include onsite visits, telephone and e-mail communications. The fourth step will involve evaluating and analyzing the data. Some of these activities will be iterative and simultaneous.

FRAMEWORK OF GUIDELINES The framework will provide a description of building, running and managing of B2B e-commerce systems. The framework will include guidelines according to the following topics.

• • • • •

Increase revenue and create value by focus on new markets Devising new mechanisms to lock in customers More long term strategic planning, with long term financial returns on investment Exploiting technology to address changing customer needs Avoid the desire to see quantifiable returns in unfeasible timeframe

Table 3: Example guideline Business strategy requirements Where is the company, where do you want to be and how will the company compete in relation to sector standard technologies, proven methodologies, leadership Products? • • • • •

Restructure content strategies to focus on interactivity and integration B2B community strategies focusing on products, relationships and transaction information sharing E-marketplace commerce strategies emphasizing collaboration hubs and value added services Think global to achieve economies of scale Tailor e-commerce initiatives to support those areas where maximum value can be extracted

Topic3: Business processes In this topic we address business process related issues, such as what is the structure of the business process, what are the key actors and resources in the business processes, what organizational and industrial structures support these business processes, how to introduce these business processes within the organization, what are the relationships between business process, business goals and business requirements (addressed in topic 2)

Table 4: Example guideline Business partners How to find B2B collaborating business partners? • • • • •

Move Electronic Data Interchange (EDI) enabled connections to the Internet. Refining internal policies to accommodate strategic alliances Building business relationships that go beyond transactions Signing partnerships with several B2B exchanges. Form strategic alliances to meet new strategic business opportunities

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Emerging Trends and Challenges in IT Management Table 5: Example guideline Business process requirements What are the process requirements as far as B2B e-commerce adoption in financial services sector is concerned? • • • • •

Understand, the stages of B2B e-commerce growth Standardize the processes through a web based centralized hosted industrial system which lowers service costs in B2B e-commerce adoption Process reengineering, integration and management; Analyzing and streamlining business processes concurrently with B2B implementation Develop a business process model to gain an understanding of the business operations Build decision rules in the B2B e-commerce processes geared at improving operational efficiency

CONCLUSION This research will contribute to existing literature by providing a set of guidelines for B2B e-commerce adoption in the financial services sector from a strategic perspective. The emphasis is on investigating and describing the features and function provided by B2B e-commerce technologies [9] rather than the technical implementation solutions that change from time to time. The guidelines developed will be presented in a more structured form, e.g. as organizational patterns with identifying a problem, context, goal, solution and related examples were applicable. An insight will be provided that is beneficial to business managers and strategic leaders in the financial sector that are seeking to formulate new strategies in the global internet based economy to take advantage of the B2B ecommerce technology [3, 6, 20, 31] .

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1078 2006 IRMA International Conference

Author’s Index Abad-Mota, Soraya .............................................................................. 204 Abascal, Rocio ...................................................................................... 371 Abbasi, Eram ......................................................................................... 871 Abdelghaffar, Hany ............................................................................. 728 Abeysinghe, Geetha ........................................................................... 1069 Abraham, George ................................................................................. 657 Abuosba, Khalil A. ............................................................................... 966 Abu-Taieh , Evon M. .......................................................................... 868 Acosta-Díaz, Ricardo .......................................................................... 337 Action, Thomas ................................................................................... 615 Acton, Thomas .................................................................................... 430 Adelmann, Holger .............................................................................. 1053 Aggarwal, Anil ...................................................................................... 322 Aggestam, Lena ...................................................................................... 4 6 Agresti, William ................................................................................. 1051 Agustin, Idline ...................................................................................... 854 Ahmad, Norita ...................................................................................... 494 Aji, Zahurin Mat .................................................................................. 813 Al Kattan, Ibrahim ..................................................................... 551, 680 Al Nunu, Ahmed .......................................................................... 551, 680 Al-Fedaghi, Sabah S. .............................................................................. 2 6 Al-Hakim, Latif .......................................................................... 719, 799 Ali, Hamdi F. ........................................................................................ 362 Ali, Shawkat .......................................................................................... 281 Alkattan, Ibrahim ................................................................................ 901 Alkhaili, Abdulaziz ............................................................................... 901 Al-Mahid, Maha T. ............................................................................. 868 Almanhali, M. ...................................................................................... 672 Alsuwaidi, Khalifa Ali .......................................................................... 316 Alvarez R, Francisco ........................................................................... 776 Amirian, Susan ...................................................................................... 698 Anand, Sriram ....................................................................................... 137 Anderson, Lisa A. ................................................................................ 168 Anderson, William ............................................................................... 644 Andrade-Arechiga, Maria .................................................................. 1027 Aniola-Jedrzejek, Lilianna ............................................................... 1036 Aoki, Terumasa .................................................................................. 1001 Argelio, Carlos ..................................................................................... 648 Arroyo, Miguel A. Morales .............................................................. 1021 Arteaga, Jaime Muñoz ................................................................ 224, 648 Artz, John M. ....................................................................................... 443 Asaari, Muhammad Hasmi Abu Hassan ................................... 712, 784 Astudillo, Gabriel ................................................................................ 1024 Augustine, Fred K., Jr. ......................................................................... 972 Augustine, Idline .................................................................................. 548 Azari, Rasool ...................................................................................... 1006 Babu, S. Ramesh ................................................................................... 465 Bai, Liang .............................................................................................. 239 Barjis, Isaac ......................................................................... 548, 559, 854 Barjis, Joseph ...................................................................... 192, 548, 559 Barnes, David ........................................................................................ 918 Baroody, A. James ............................................................................... 790 Baumgartner, Robert ........................................................................... 133 Benson, Steve ....................................................................................... 392 Berbner, Rainer ........................................................................... 527, 531 Berri, Sidi ............................................................................................... 854 Beugré, Constant D. ............................................................................ 834 Bieber, Michael ........................................................................... 421, 603 Biehl, Norman ...................................................................................... 862 Biesalski, Ernst ..................................................................................... 427 Blancero, Donna Maria ....................................................................... 644 Blashki, Katherine ...................................................................... 160, 448 Boddie, William S. ............................................................................... 545

Boehm, Diane ..................................................................................... 1036 Bouchlaghem, Dino ........................................................................... 1053 Boylan, Stephen ................................................................................... 316 Brain, Michael Edward ........................................................................ 571 Brandon, Daniel ................................................................................... 109 Braun, Oliver ........................................................................................ 989 Braz, Maria Helena L. B. .................................................................... 736 Brehm, Nico ......................................................................................... 494 Brehm, Nico ......................................................................................... 865 Brown, Ahern ....................................................................................... 584 Bruno, Anna ....................................................................................... 1042 Bryde, David ......................................................................................... 122 Burgess, Stephen ......................................................................... 341, 349 Burke, M. E. ........................................................................................... 1 5 Burks, Eddy J. .............................................................................. 127, 906 Busch, Peter ................................................................................. 490, 504 Butcher-Powell, Loreen Marie .......................................................... 313 Butt, Arsalan ......................................................................................... 927 Byun, Juman ......................................................................................... 329 Calabretto, Sylvie ................................................................................ 986 Caladine, Richard ................................................................................. 247 Calloway, Linda Jo ............................................................................... 208 Cameron, Brian .................................................................................... 313 Camona, Jesus ....................................................................................... 399 Campbell, Traci ................................................................................... 506 Carbonara, David ...................................................................... 745, 1038 Carbone, Daniel ................................................................................... 341 Carmona, Jesus ..................................................................................... 839 Catanio, Joseph T. ............................................................................... 421 Chacín, Belkys .................................................................................... 1062 Chalekian, Paul M. .............................................................................. 832 Chang, David ...................................................................................... 1061 Chang, Yun-ke .................................................................................... 1021 Chatti, Noureddine ............................................................................... 986 Chaudhry, Abdus Sattar ....................................................................... 804 Chen, Edward T. .................................................................................. 130 Chen, Hui-ching ................................................................................... 409 Chen, Jim Q. ........................................................................................... 3 8 Chen, Kuan-Chou ....................................................................... 696, 904 Chen, Nong ........................................................................................... 892 Chen, X. Mara ...................................................................................... 114 Chen, Zhixiang ..................................................................................... 949 Cheung, Man-Ying ............................................................................... 293 Chin, Amita Goyal ............................................................................... 418 Chin, Sung Y. ........................................................................................ 475 Chirkova, Rada ..................................................................................... 666 Cho, Bong Gun ..................................................................................... 475 Choi, Yong Jun ............................................................................ 325, 329 Chou, Charles ........................................................................................ 386 Christian, John T. .............................................................................. 1065 Chu, Hung-ju ......................................................................................... 277 Chuang, Carin .............................................................................. 696, 904 Chung, Lawrence ................................................................ 534, 668, 816 Clegg, Benjamin T. .............................................................................. 631 Collins, Jim D. ........................................................................................ 1 1 Colmenares G., Leopoldo E. ............................................................ 1015 Colombo, Alberto ................................................................................ 412 Conboy, Kieran .................................................................................... 374 Conboy, Kieran .................................................................................... 623 Conners, Susan E. ................................................................................ 992 Contreras-Castillo, Juan ........................................................... 337, 1027 Córdova, Hernán ........................................................... 857, 1024, 1064 Crnkovic, Jakov ................................................................................. 1033

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Emerging Trends and Challenges in IT Management Dafoulas, Georgios A. ...................................................... 516, 627, 1067 Dahanayake, Ajantha .......................................................................... 892 Dahanayake, ANW .................................................................... 486, 797 Dahawy, Khaled ................................................................................. 1045 Dahlan, Noornina ................................................................................ 712 Damiani, Ernesto ................................................................................. 412 Da-quan, Tang ........................................................................................ 5 5 Darbyshire, Paul .......................................................................... 349, 578 Darmont, Jerôme ................................................................................. 685 Dasgupta, Subhasish ................................................................... 700, 934 Dattero, Ronald ............................................................................ 82, 196 Daun, Christine .................................................................................... 920 Dayasindhu, N ............................................................................. 793, 877 de Cavalho, Marly Monteiro ............................................................. 512 De Haes, Steven ................................................................................... 353 de Oliveira, José M. Parente .............................................................. 309 de Oliveira, Marcos Antonio ............................................................. 512 Deschoolmeester, D. ........................................................................... 740 Deselaers, Thomas ............................................................................... 911 Dexter, H. ............................................................................................... 8 6 Dharmaraj, N. ....................................................................................... 895 Diaz, Ricardo Acosta ......................................................................... 1027 Dolins, Steven B. ................................................................................. 724 Dologite, Dorothy G. .......................................................................... 441 Donalds, Charlette ............................................................................... 850 Donnellan, Brian .................................................................................. 623 Dow, Kevin E. ............................................................................. 702, 976 Dozier, Ken ......................................................................................... 1061 Driscoll, Donna A. ............................................................................... 970 Du, Timon C. ........................................................................................ 386 Duggan, Evan W. ........................................................................ 216, 850 Düsterhöft, Antje ................................................................................ 862 Edberg, Dana ......................................................................................... 168 Edwards, Arthur ................................................................................... 337 Elbannan, Mohamed A. ...................................................................... 482 Ellis, Kirsten .............................................................................................. 1 Emurian, Henry H. .............................................................................. 438 Ereryel, U. Yeliz .................................................................................. 188 Eschenbaecher, Jens ............................................................................ 639 Espinoza, Norelkys .................................................................. 939, 1062 Even, Adir ............................................................................................. 749 Fakas, Georgios John ........................................................................... 677 Farren, Neil ........................................................................................... 615 Favre, Liliana ............................................................................... 259, 264 Fei, Qi ...................................................................................................... 3 8 Fen, Fong Pin ....................................................................................... 804 Feng, Kuoching ..................................................................................... 130 Fernandes, Clovis Torres .................................................................... 309 Fernando, MSD ............................................................................ 797, 832 Ferneley, Elaine ................................................................................... 415 Ferrand, Brett ......................................................................................... 3 0 Feuerlicht, George ................................................................................ 118 Fink, Kerstin ......................................................................................... 152 Fiore, Nicola ....................................................................................... 1042 Flanigan, Eleanor J. ............................................................................. 698 Flax, Lee ............................................................................................... 490 Flores, Marco ........................................................................................ 939 Flynn, Don F. ....................................................................................... 947 Foo, Gerhardine ................................................................................... 719 Forbrig, Peter ........................................................................................ 862 Forster, Paul W. ................................................................................... 779 Forté, Paul ............................................................................................ 192 France, Laure ........................................................................................ 683 Frolick, Mark ........................................................................................ 525 Frontini, Maria Alice .......................................................................... 479 Fuchs, Georg ................................................................................ 345, 862 Gackowski, Zbigniew .................................................................... 63, 388 Galup, Stuart D. ...................................................................................... 8 2 Gao, Jing ................................................................................................ 607

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Gao, Yuan .............................................................................................. 836 Garcia-Ruiz, Miguel A. ............................................................. 337, 1027 Garófalo, Lenny ................................................................................. 1024 Garrity, Edward J. .................................................................................. 3 4 Garrot, Elise .......................................................................................... 424 Gasiorkiewicz, Lech ............................................................................. 242 Geller, James ......................................................................................... 968 Gellings, Cornelia ................................................................................. 709 George, Sébastien ................................................................................. 424 Gewald, Heiko ....................................................................................... 148 Ghods, Mehdi ...................................................................................... 1063 Ghous, Asim .......................................................................................... 595 Gingrich, Gerry ................................................................................... 1067 Goel, Sanjay ........................................................................................ 1033 Gomes, Geórgia R. R. .......................................................................... 736 Gomez, Elizabeth Avery ..................................................................... 603 Gómez, Gustavo Rodríguez ................................................................. 224 Gómez, Jorge Marx .................................................................... 494, 865 González, Héctor Perez ...................................................................... 224 Gorthi, Ravi .......................................................................................... 377 Graham, Lila Rao ........................................................................ 333, 942 Grant, Donna M. ................................................................................ 1072 Grant, Gerald G. ................................................................................... 333 Grant, Gerry .......................................................................................... 367 Graser, Falk ........................................................................................... 639 Greenberg, Penelope Sue ............................................................ 702, 976 Greenberg, Ralph H. ................................................................... 702, 976 Griffey, Sue J. ..................................................................................... 1066 Grimaila, Michael R. ................................................................... 176, 180 Güld, Mark Oliver ................................................................................ 911 Gupta, Pramila ...................................................................................... 281 Gutiérrez-Pulido, Jorge Rafael ........................................................... 337 Hagenhoff, Svenja ................................................................................. 6 8 Haiazi, Muhamed Ali ........................................................................... 357 Hakeem, Addul ..................................................................................... 960 Hanafizadeh, Payam ............................................................................ 888 Harindranath, G. .................................................................................. 876 Harlow, Charles .................................................................................... 949 Havelka, Douglas J. ............................................................................. 883 Hawamdeh, Suliman ........................................................................... 1021 Hazari, Sunil .......................................................................................... 694 Heckmann, Oliver ...................................................................... 527, 531 Heili, Joseph ......................................................................................... 683 Hentea, Mariana .................................................................................. 290 Heraud, Jean-Mathias .......................................................................... 683 Hill, James .................................................................................... 430, 615 Hill, Seamus .................................................................................. 304, 623 Hinton, Matthew ........................................................................ 691, 918 Hinz, Daniel J. ............................................................................. 148, 820 Ho, Kevin K. W. .................................................................................... 9 1 Ho, Shuk Ying ........................................................................................ 9 1 Ho, Shuyuan Mary ............................................................................... 188 Hobson, Libby ...................................................................................... 565 Hosseini, Seyed Ali Akbar .................................................................. 888 Hsu, Jeffrey ........................................................................................... 130 Hu, Jyh-haw .......................................................................................... 277 Hu, Wen-Chen ...................................................................................... 277 Hu, Yanli ............................................................................................... 239 Huang, Haiyan ...................................................................................... 930 Huang, Hsieh-Hong ............................................................................. 951 Huang, Kuo-chuan ............................................................................... 968 Huang, Wilfred V. .............................................................................. 1061 Huerta, Esperanza ................................................................................ 472 Hvolby, Hans-Henrik .......................................................................... 586 Hwang, Richard ..................................................................................... 386 Ibrahim, Huda ....................................................................................... 813 Irving, Philip ...................................................................................... 1049 Islam, Hafizul ........................................................................................ 399 Jackson, Thomas W. ................................................................ 611, 1053

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1080 2006 IRMA International Conference Jafari, Hassan Abedi ............................................................................. 297 Janczewski, Lech J. .............................................................................. 269 Janlert, Lars-Erik ................................................................................. 232 Jantavongso, Suttisak .......................................................................... 448 Jasti, Chaitanya .................................................................................... 949 Jeffers, Patrick I. ................................................................................. 688 Jennex, Murray E. ............................................................................... 984 Jiménez, Jaime .................................................................................... 1021 Jin-yang, Tang ........................................................................................ 5 5 Joham, Carmen ..................................................................................... 565 Johnson, Alice ........................................................................................ 5 0 Johnson, Karin E. ................................................................................ 114 Joseph, Rhoda ....................................................................................... 688 Joshko, Lucie ........................................................................................ 591 Ju, Patricia H. ....................................................................................... 409 Ju, Teresa L. ......................................................................................... 409 Jun-feng, Song ........................................................................................ 5 5 Kahn, Beverly ........................................................................................ 6 0 Kamel, Sherif ............................................................................. 728, 1045 Kamthan, Pankaj ........................................................................ 879, 881 Kang, Myong ........................................................................................ 619 Karia, Noorliza ............................................................................ 712, 784 Karimi, Forough ................................................................................... 706 Kaspar, Christian ................................................................................... 6 8 Kats, Yefin ................................................................................... 844, 968 Keim, Tobias ............................................................................... 651, 829 Kendall, Julie E. ................................................................................... 994 Kendall, Kenneth E. ............................................................................ 994 Kero, Robert E. .................................................................................... 724 Khashnobish, Amit .............................................................................. 619 Khatnani, Vijay .................................................................................... 825 Kido, Kunihiko ..................................................................................... 143 Kim, Anya ............................................................................................ 619 Kim, Daeryong ..................................................................................... 834 Kim, Euijin ............................................................................................ 220 King, Ernest W. .......................................................................... 127, 906 Kirwan, Orla ......................................................................................... 374 Kish, Josephine Cocian ....................................................................... 567 Kish, Maria H.Z. .................................................................................. 567 Kisielnicki, Jerzy A. .............................................................................. 7 8 Knight, Linda V. ....................................................................... 937, 1009 Kochikar, V.P. ...................................................................................... 465 Kock, Ned ............................................................................................. 399 Kong, Sue .............................................................................................. 994 Koniecek, Greg ..................................................................................... 578 König, Wolfgang .................................................................................. 235 Kontio, Juha ......................................................................................... 509 Koronios, Andy .................................................................................... 607 Koundouraki, Evangelia .................................................................... 1073 Kristensen, Terje ................................................................................. 562 Krupa, Tadeusz ............................................................................ 242, 661 Ku, Cheng-Yuan ................................................................................... 951 Kudyba, Stephan ................................................................................ 1062 Kulkarni, Sagar S. ................................................................................. 846 Kumar, Ashwani ................................................................................... 164 Kuo, Pu-Yuan ....................................................................................... 538 Kurbel, Karl ........................................................................................... 156 Kurniawan, Andie ................................................................................ 377 Lai, Vincent .......................................................................................... 386 Lally, Laura ............................................................................................. 2 3 Lamo, Yngve ........................................................................................ 562 Lapczynski, Patricia H. ...................................................................... 208 Laurindo, Fernando José Barbin ........................................................ 479 Lawrence, Kenneth ........................................................................... 1062 Lawson, Joseph M. .............................................................................. 180 Lazarony, Paul J. ................................................................................. 970 Lederer, Albert L. .................................................................................. 5 0 Lederer-Antonucci, Yvonne .............................................................. 825 Lee, Chu Keong .................................................................................... 908

Lee, Goon Tuck ................................................................................... 712 Lee, In ................................................................................................... 397 Lee, Sheng-Chien ................................................................................. 277 Lee, Wookey ........................................................................................ 753 Lee-Partridge, Joo Eng ......................................................................... 9 4 Lehmann, Thomas .............................................................................. 911 Lertrusdachakul, Thitiporn .............................................................. 1001 Letaifa, Soumaya Ben ......................................................................... 457 Levy, Yair ........................................................................................... 1065 Lew, Jeanette ........................................................................................ 381 Lewis, Stan ................................................................................... 127, 906 Li, Gang ................................................................................................. 160 Li, Koon-Ying Raymond .................................................................... 293 Li, Zhang ............................................................................................. 1064 Liao, Che-Chan .................................................................................... 538 Lichtenstein, Sharman ........................................................................ 571 Liebowitz, Jay ..................................................................................... 1051 Lin, Shien .............................................................................................. 607 Lin, Winston T. ................................................................................. 1011 Little, Stephen ..................................................................................... 691 Liu, Zhong ............................................................................................ 238 Lo, Jim .................................................................................................. 619 Lojeski, Karen Sobel ............................................................................ 704 Loos, Peter ........................................................................................... 920 López, Juan Muñoz ............................................................................. 648 Lu, Hongen ........................................................................................... 762 Lynn, Susan A. ..................................................................................... 322 Ma, Shanshan ........................................................................................ 200 Macaulay, Linda A. ............................................................................. 954 Macconi, Renato .................................................................................. 412 MacDonnell, Michael .......................................................................... 631 Madlberger, Maria ................................................................................ 913 Madravio, Mauro ................................................................................. 412 Magai, Robert ....................................................................................... 753 Mahfouz, Ahmeyd ............................................................................... 468 Mahmood, A. Kamil ............................................................................ 415 Mahmood, Zaigham ............................................................................ 541 Majid, Shaheen ................................................................................... 1057 Malaga, Ross A. ........................................................................ 822, 1061 Malinowski, Jochen .................................................................... 651, 829 Mallach, Effrem G. ............................................................................ 1061 Maltempi, Marcus Vinicius ................................................................. 554 Malus, Christian ................................................................................... 575 Mansingh, Gunjan ....................................................................... 333, 942 Maria, Jakovljevic ............................................................................... 273 Martin, Michael W. ............................................................................. 666 Martinez, Liliana ................................................................................. 259 Matheis, Thomas ................................................................................. 920 Mathiyalakan, Sathasivam ................................................................. 916 McCally, Mary S. ............................................................................... 1068 McClain, Charles .................................................................................. 452 McHaney, Roger .................................................................................. 715 McKenzie, W. Brett .......................................................................... 1004 Medlin, B. Dawn .................................................................................. 255 Meletiou, George .................................................................................. 635 Melia, Denise ........................................................................................ 304 Melkas, Helinä ........................................................................................ 6 0 Melo, Rubens N. ................................................................................... 736 Mendez, Francis A. .............................................................................. 688 Merhout, Jeffrey W. ................................................................... 883, 932 Merten, Patrick ................................................................................... 885 Mick, Michael ...................................................................................... 992 Miller, David W. .................................................................................. 970 Miller, Gillian S. ................................................................................... 519 Mills, Annette M. ................................................................................ 942 Mishra, Sushma ..................................................................................... 418 Mockler, Robert J. ............................................................................... 441 Mohamudally, Nawaz .......................................................................... 925 Molla, Alemayehu ............................................................................... 635

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Emerging Trends and Challenges in IT Management Montrose, Bruce .................................................................................. 619 Moon, Jonghoon .................................................................................... 3 4 Moscicki, Jerome ................................................................................. 591 Mughal, Khalid ..................................................................................... 562 Muñoz, Jaime ........................................................................................ 776 Murphy, Alan .............................................................................. 811, 898 Nagappan, Sarojini Devi ..................................................................... 595 Nagaraju, Rama ................................................................................... 1053 Naleppa, Heather ................................................................................. 957 Natarajan, Rajesh ................................................................................. 435 Nguyen, Hang ..................................................................................... 1051 Niwe, Moses ........................................................................................ 1075 Norbjerg, Jacob ................................................................................... 1066 Nurcan, Selmin ..................................................................................... 285 O’Boyle, Peter ..................................................................................... 430 Okpa, Nwayigwe ................................................................................... 854 Okunoye, Adekunle .................................................................... 525, 635 Olivier, Emerson .................................................................................. 685 Onken, Marina ..................................................................................... 644 Ortelbach, Björn .................................................................................... 6 8 Ortiz, Julio Angel ................................................................................. 599 Osman, Wan Rozaini Sheik ................................................................ 813 Ostheimer, Bernhard .................................................................. 251, 758 Ostrowska, Teresa ............................................................................... 661 Othman, Nafishah ............................................................................... 813 Otieno, Jim ......................................................................................... 1069 Otieno, Mary ...................................................................................... 1062 Padmanabhan, Sriram .......................................................................... 793 Pai, Hsueh-Ieng .................................................................................... 879 Pai, Hsueh-Ieng .................................................................................... 881 Pallot, Marc ........................................................................................ 1018 Pandurino, Andrea ............................................................................. 1042 Parameswaran, Nandan ....................................................................... 377 Parrott, Colleen ................................................................................... 114 Passerini, Katia .................................................................................... 603 Pawar, Kulwant ................................................................................... 1018 Payne, Brian R. .................................................................................... 790 Perdomo, Bexi ...................................................................................... 939 Pereira, Claudia .................................................................................... 264 Perera, Dharani Priyahansika ............................................................ 160 Perrelli, Hermano ................................................................................ 581 Pesantez, Joffre ................................................................................... 857 Petch, J. ................................................................................................... 8 6 Petie, David .......................................................................................... 122 Petrova, Krassie .......................................................................... 228, 255 Pick, James ......................................................................................... 1006 Pierce, Elizabeth .................................................................................... 6 0 Pinon, Jean-Marie ............................................................................... 986 Ploder, Christian .................................................................................. 152 Politis, Dionysios ................................................................................ 677 Pradhan, Sujan ...................................................................................... 762 Prakash, Naveen .................................................................................. 501 Prévôt, Patrick .................................................................................... 424 Prinz, Wolfgang ................................................................................. 1018 Qu, Haixia ............................................................................................. 228 Quan, Jing “Jim” ........................................................................... 82, 196 Quesenberry, Jeria L. ........................................................................... 974 Rabaey, Marc ........................................................................................ 514 Rabeau, Yves ......................................................................................... 457 Radaidah, M. ......................................................................................... 672 Ramayah, T. ......................................................................................... 712 Rangel, Edgar Maldonado ................................................................... 599 Rao B. R., Shrinivasa ........................................................................... 895 Rautenstrauch, Claus ............................................................................ 865 Ravi, Jamuna ......................................................................................... 793 Ravindra, M.P. ..................................................................................... 465 Razak, Rafidah Abd ............................................................................. 813 Reed, April .......................................................................................... 1009 Reed, Karl .............................................................................................. 412

1081

Regan, Elizabeth .................................................................................. 944 Reichart, Daniel ................................................................................... 862 Reichgelt, Han ...................................................................................... 192 Reichinger, Gerd ................................................................................... 133 Reichinger, Kurt ................................................................................... 133 Reilly, Richard R. ................................................................................. 704 Reinhart, Kai ........................................................................................ 427 Richards, Debbie .......................................................................... 490, 504 Richards, Faizel .................................................................................... 772 Rincón, Angel ..................................................................................... 1062 Rittgen, Peter .............................................................................. 172, 459 Roberts, Martyn ..................................................................................... 3 0 Rodger, James A. .................................................................................. 787 Rodrigues, Lewlyn L.R. ....................................................................... 895 Rodríguez, Francisco Alvarez ............................................................. 224 Roithmayr, Friedrich ........................................................................... 152 Rolland, Colette ................................................................................... 501 Rosa, Mauricio ...................................................................................... 554 Ruiz I., Eduardo .................................................................................... 204 Rumpler, Béatrice ................................................................................ 371 Ryan, Michael R. ................................................................................. 704 Sadorsky, Perry ...................................................................................... 4 2 Sahasrabudhe, Vikas ............................................................................. 934 Sahni, Puja ............................................................................................ 367 Saleh, Kassem .............................................................................. 680, 901 Salo, Jari .................................................................................................. 9 7 Samarrai, Wallied ................................................................................. 548 Sánchez-Morcilio, Rosarito ................................................................ 394 Sanders, G. Lawrence ............................................................................. 3 4 Sankar, Ravi .......................................................................................... 960 Santos, Raúl Aquino ............................................................................. 337 Sarkar, Nurul I. ............................................................................ 101, 715 Sarkhosh, Reza ..................................................................................... 706 Sarlak, Mohammad Ali ....................................................................... 297 Schlie, Theodore .................................................................................. 462 Schmidt, Gary ..................................................................................... 1062 Schmidt, Günter ................................................................................... 989 Schroeder, Neil J. ................................................................................. 176 Schubert, Henning ................................................................................ 911 Schulin, Kathleen M. ......................................................................... 1068 Schultz, Robert A. ................................................................................ 842 Schumann, Heidrun ..................................................................... 345, 862 Schwickert, Axel C. .................................................................... 251, 758 Scott, Murray ........................................................................................ 430 Segovia, Roy ......................................................................................... 984 Seidenfaden, Lutz ................................................................................... 6 8 Seitz, Juergen ........................................................................................ 402 Selim, Hassan M. .................................................................................... 7 3 Sena, James A. ........................................................................................ 1 9 Shah, Mahmood H. .............................................................................. 541 Shalhoub, Zeinab Karake .................................................................... 589 Shankaranarayanan, G. ....................................................................... 749 Sharma, Anil ......................................................................................... 316 Shea, Timothy ...................................................................................... 584 Shehabuddin, T. .................................................................................... 672 Shekar, B. .............................................................................................. 435 Shim, Charlie Y. ................................................................................... 475 Shim, Sung J. ......................................................................................... 999 Shin, Namchul .................................................................................... 1013 Shkvarko, Yuriy V. .............................................................................. 978 Siddiqui, Arshad .................................................................................... 871 Sikder, Iftikhar ..................................................................................... 654 Simons, Gene R. ................................................................................... 494 Siqueira, Sean W.M. ............................................................................. 736 Sledgianowski, Deb ............................................................................... 470 Small, Chris ........................................................................................... 192 Smith, Stephen ..................................................................................... 611 Sol, HG ......................................................................................... 486, 797 Solomon, Scott ................................................................................... 1051

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1082 2006 IRMA International Conference Son, Sertaç ............................................................................................ 235 Song, Il-Yeol ....................................................................... 200, 475, 657 Song, Zhichao ....................................................................................... 285 Spitzer, Klaus ........................................................................................ 911 Spronck, Pieter .................................................................................... 362 Stea, Bob ............................................................................................... 876 Steinbach, Theresa A. ......................................................................... 937 Steinert, Martin ................................................................................... 885 Steinmetz, Ralf ............................................................................ 527, 531 Stewart, George W. .............................................................................. 216 Subramanian, Ramesh .......................................................................... 732 Suddul, Geerish ...................................................................................... 925 Supakkul, Sam ..................................................................... 534, 668, 816 Surynt, Theodore J. ............................................................................. 972 Syed, Nadeem A. .................................................................................. 871 Szota, Mark ...................................................................................... 1, 105 Tabatabai, Mina Rohani ...................................................................... 888 Tadisina, Suresh ................................................................................... 220 Tai, Vincent .......................................................................................... 269 Talburt, John R. ................................................................................... 506 Talevski, Aleksander Sasha ................................................................ 105 Tan, Bonny ........................................................................................... 908 Tan, Jennifer ........................................................................................ 854 Tan, Yin Leng ...................................................................................... 954 Tang, Ya ............................................................................................... 779 Tao, Yan ............................................................................................... 691 Tapia, Andrea ....................................................................................... 599 Tarbet, Gary ......................................................................................... 462 Tasdemir, Cagil .................................................................................... 767 Tedesco, Patricia ................................................................................. 581 Tedmori, Sara ..................................................................................... 1053 Tello, Steven F. ................................................................................... 963 Theodoridis, Konstantinos P. ............................................................ 677

Thies, Christian ................................................................................... 911 Thoben, Klaus-Dieter .......................................................................... 639 Timmerman, Martin ........................................................................... 514 Tindle, John ........................................................................................ 1049 Tindle, Sonia ....................................................................................... 1049 Toklu, Candemir .................................................................................. 767 Tomei, Lawrence A. ................................................................. 745, 1038 Tor, Yavuz ............................................................................................ 949 Tordella, Robert ................................................................................... 732 Torreao, Paula ...................................................................................... 581 Tsai, Page P. ....................................................................................... 1011 Tucker, Shin-Ping .............................................................................. 1063 Tuefel, Stephanie ................................................................................. 885 Turczyk, Lars Arne .................................................................... 527, 531 Vaassen, Eddy ....................................................................................... 362 Vadervu, Vijayanand .......................................................................... 1064 Vaidya, Sanju ......................................................................................... 997 Van Belle , Jean-Paul ........................................................................... 772 van den Herik, H. Jaap ........................................................................ 362 van der Rijt, Pernill G.A. .................................................................... 406 Van Grembergen, Wim ........................................................................ 353 Vanarase, Vijay ..................................................................................... 644 Vandenborre, Koenraad ....................................................................... 514 Vandijck, Eddy ...................................................................................... 514 Venable, John ........................................................................................ 184 Venables, Anne ..................................................................................... 595 Venkataraman, Jakakumar ................................................................. 137 Verhage, Lambertus ............................................................................. 922 Verville, Jacques ................................................................................... 399 Viaene, S. ............................................................................................... 740 Villalon-Turrubiates, Ivan E. .................................................... 978, 981 von Lubitz, Dag ........................................................................................ 5

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