Organizational Learning Approach to Process Innovations : The Extent and Scope of Diffusion and Adoption in Management Accounting Systems 9781780527352, 9781780527345

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AN ORGANIZATIONAL LEARNING APPROACH TO PROCESS INNOVATIONS: THE EXTENT AND SCOPE OF DIFFUSION AND ADOPTION IN MANAGEMENT ACCOUNTING SYSTEMS

STUDIES IN MANAGERIAL AND FINANCIAL ACCOUNTING Series Editor: Marc J. Epstein Recent Volumes: Volume 1:

Setting the Standard for the New Auditors Report: An Analysis of Attempts to Influence the Auditing Standards Board

Volume 2:

The Shareholders Use of Corporate Annual Reports

Volume 3:

Applications of Fuzzy Logic and the Theory of Evidence to Accounting

Volume 4:

The Usefulness of Corporate Annual reports to Shareholders in Australia, New Zealand, and the United States: An International Comparison

Volume 5:

A Power Control Exchange Framework of Accounting: Applications to Management Control Systems

Volume 6:

Throughout Modeling: Financial Information Used by Decision Makers

Volume 7:

Applications of Fuzzy Sets and the Theory of Evidence to Accounting II

Volume 8:

Corporate Governance, Accountability, and Pressures to Perform: An International Study

Volume 9:

The January Effect and Other Seasonal Anomalies: A Common Theoretical Framework

Volume 10:

Organizational Change and Development in Management Control Systems: Process Innovation for Internal Auditing and Management Accounting

Volume 11:

US Individual Federal Income Taxation: Historical, Contemporary and Prospective Policy Issues

Volume 12:

Performance Measurement and Management Control: A Compendium of Research

Volume 13:

Information Asymmetry: A Unifying Concept for Financial and Managerial Accounting Theories.

Volume 14:

Performance Measurement and Management Control: Superior Organization Performance.

Volume 15:

A Comparative Study of Professional Accountants’ Judgements

Volume 16:

Performance Measurement and Management Control: Improving Organizations and Society

Volume 17:

Non-Financial Performance Measurement and Management Practices in Manufacturing Firms: A Comparative International Analysis

Volume 18:

Performance Measurement and Management Control: Measuring and Rewarding Performance

Volume 19:

Managerial Attitudes Toward a Stakeholder Prominence within a Southeast Asia Context

Volume 20:

Performance Measurement and Management Control: Innovative Concepts and Practices

Volume 21:

Reputation Building, Website Disclosure and the Case of Intellectual Capital

Volume 22:

Achieving Global Convergence of Financial Reporting Standards: Implications from the South Pacific Region

Volume 23:

Globalization and Contextual Factors in Accounting: The Case of Germany

STUDIES IN MANAGERIAL AND FINANCIAL ACCOUNTING VOLUME 24

AN ORGANIZATIONAL LEARNING APPROACH TO PROCESS INNOVATIONS: THE EXTENT AND SCOPE OF DIFFUSION AND ADOPTION IN MANAGEMENT ACCOUNTING SYSTEMS BY

SELESHI SISAYE Duquesne University, Pittsburgh, PA, USA

JACOB G. BIRNBERG University of Pittsburgh, Pittsburgh, PA, USA

United Kingdom – North America – Japan India – Malaysia – China

Emerald Group Publishing Limited Howard House, Wagon Lane, Bingley BD16 1WA, UK First edition 2012 Copyright r 2012 Emerald Group Publishing Limited Reprints and permission service Contact: [email protected] No part of this book may be reproduced, stored in a retrieval system, transmitted in any form or by any means electronic, mechanical, photocopying, recording or otherwise without either the prior written permission of the publisher or a licence permitting restricted copying issued in the UK by The Copyright Licensing Agency and in the USA by The Copyright Clearance Center. No responsibility is accepted for the accuracy of information contained in the text, illustrations or advertisements. The opinions expressed in these chapters are not necessarily those of the Editor or the publisher. British Library Cataloguing in Publication Data A catalogue record for this book is available from the British Library ISBN: 978-1-78052-734-5 ISSN: 1479-3512 (Series)

In Memory of Eileen Stommes, Ph.D. June 20, 1947 to July 10, 2006

CONTENTS ABOUT THE AUTHORS

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ACKNOWLEDGMENTS

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INTRODUCTION

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1. WHY INNOVATIONS FAIL: ORGANIZATIONAL PROCESSES AND STRUCTURAL BARRIERS TO INNOVATIONS 1.1 1.2 1.3 1.4 1.5 1.6

Organizational Processes and Constraints of Innovations An Overview of Structural Barriers to Innovations Contingency Framework of Sociology Organizational Learning: Single and Double Loop Adoption and Diffusion Issues Related to SF- and CR-Based Technological Innovations Adoption–Diffusion and Innovation Lag

2. ADOPTION AND DIFFUSION OF PROCESS INNOVATIONS IN MANAGEMENT ACCOUNTING SYSTEMS 2.1 2.2

3.2 3.3

1 3 4 9 15 16 19

Approaches to Innovation 20 Organizational Learning: Single- and Double-Loop Learning 33 within the Context of Management Accounting Innovations

3. THE EXTENT AND SCOPE DIMENSIONS OF PROCESS INNOVATIONS 3.1

1

41

An Overview of the Dimensions of Extent and Scope 41 of Innovations Scope of Innovation Dimension: Autonomous and Systemic 46 Management Accounting Innovations Typologies 50

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4. MECHANISTIC AND ORGANIC INNOVATIONS 4.1 4.2 4.3 4.4

SF Mechanist Approaches Cell 1: Mechanistic Innovations Cell 2: Organic Innovations Effects of Organizational Structures on Mechanistic and Organic Innovations

5. ORGANIZATIONAL DEVELOPMENT (OD) AND ORGANIZATIONAL TRANSFORMATION (OT) PROCESS INNOVATION STRATEGIES 5.1 5.2 5.3

Cell 3: Organizational Development Cell 4: Organizational Transformation Organizational Development and Transformation Approaches in Management Accounting Innovations

6. ORGANIZATIONAL LEARNING AND PROCESS INNOVATIONS: AN INTEGRATED FRAMEWORK 6.1 6.2 6.3 6.4

7.2

71 72 78 84 87

An Overview of the Literature on Organizational Learning 87 The Two Stages of Organizational Learning: Adoption 97 and Diffusion Organizational Learning and the Birth and 104 Bureaucratization of Accounting Rules The Adoption–Diffusion Processes of Organizational 106 Learning in the Management Accounting Literature

7. CONCLUSION AND IMPLICATIONS FOR FUTURE RESEARCH 7.1

51 52 60 63 65

Resource-Based Approach to Organizational Learning and Performance Conclusion: Implications for Future Research

111 111 114

REFERENCES

121

AUTHOR INDEX

133

SUBJECT INDEX

139

ABOUT THE AUTHORS Seleshi Sisaye is Professor of Accounting at the Palumbo-Donahue School of Business, Duquesne University. His research interests are in organizational sociology, management control systems, process innovations, sustainable development, and reporting. His publications have appeared in accounting, management, sociology, and international development journals. He has assumed leadership positions within the Accounting, Behaviour and Organization Sections of the American Accounting Association. He holds two PhDs in Development Sociology from Cornell University and Accounting from the University of Pittsburgh. Jacob G. Birnberg is The Robert W. Murphy Jr. Professor Emeritus of Management Control Systems at Katz Graduate School of Business, University of Pittsburgh. He has published extensively in the leading accounting, management, and psychology journals in the areas of behavioral accounting, management control systems, behavioral decision making, among others. He has received numerous teaching, research, and service awards from the University of Pittsburgh, American Accounting Association, Accounting, Behaviour, and Organizations and Management Accounting Sections. His PhD is in accounting from the University of Minnesota.

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ACKNOWLEDGMENTS It is difficult to list the names of those individuals who have supported our research over the years from the inception to the final completion of the book. We acknowledge those individuals who have provided their generous time and assistance over the years. First, we express our appreciation to Dr. Marc Epstein, Distinguished Research Professor of Management, Jones Graduate School of Business, Rice University, Studies in Managerial and Financial Accounting series editor. We have worked and collaborated with Marc for many years. We are very grateful for his continued support and encouragement, which made it possible for us to complete the book on a timely basis. We are highly indebted to Ms. Emma Whitfield; editorial staff of Emerald Group Publishing Limited for her generous assistance in providing us the time needed to complete the book. Emma has been instrumental in arranging editorial assistance, in particular in the preparation of the subject index consistent with Emerald publishing requirements. The genesis of the ideas discussed in this book can be found in two articles that we published in 2010. They are ‘‘Organizational Development and Transformational Learning Approaches in Process Innovations: A Review of the Implications to the Management Accounting Literature,’’ Review of Accounting and Finance, Vol. 9, No. 4, 2010, pp. 337–362; and ‘‘Extent and Scope Dimensions of Diffusion and Adoption of Process Innovations in Management Accounting Systems,’’ International Journal of Accounting and Information Management, Vol. 18, No. 2, 2010, pp. 118–139. They are published by Emerald Publishing Group. We are very grateful for Emerald copyright policies that enabled us to use the materials from these two articles throughout the book. Ms. Margaret M. Vojtko has provided expert editorial assistance in the preparation of the first draft of the book. We thank Margaret for her time that she has freely invested in the early stages of the preparation of the manuscript. Mrs. Debbie Kennedy has been very kind in putting together the reference list, author index, and table of contents. She has provided skillful secretarial assistance in typing the entire manuscript of the book as well as the supplements. We are indebted to Debbie for all the work that she put in the book and the generous time that she has provided in getting the xi

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manuscript ready on a timely basis. Shutian Zheng has provided valuable research assistance in bibliographic search, content analysis and expert technical assistance in the early stages of the manuscript preparation. Last, but not the least, we thank Stephanie Birnberg for her support and encouragement throughout the publication process. We have most benefited from the support that we have received from our family and the sacrifices they have made to support our project. We are dedicating the book in memory of Eileen Stommes, PhD, for her outstanding public service and devotion to her family and friends. Eileen has been a good friend and colleague, has published and contributed substantially in the areas of agricultural marketing and transportation, and rural development. She is survived by her husband, Dr. Seleshi Sisaye, and daughters, Sarah Laura and Anne Elizabeth Sisaye. We are pleased to dedicate our book in recognition of her work and accomplishments as a professional, colleague, wife and mother of her two beloved daughters.

INTRODUCTION Research in management accounting systems over the years has been shaped by theories and methodologies adapted from the social science disciplines. Sociology is one of those social science disciplines that have impacted research in management accounting. Sociological theory in organizational learning, and adoption and diffusion of innovation has been utilized in management accounting research. In the past 20 years, the most significant developments have included the application of gradual and transformational organizational learning theories from sociology to management accounting systems research. Organizational learning has been viewed as a source of competitive advantage that helps organizations respond to changes in their institutional environments by adopting and diffusing innovations that will contribute toward improving their performance. Organizational learning encompasses new insights, knowledge, and modification of behaviors. Learning occurs through adoption of new technologies, shared experiences, knowledge, and mental models. An organization’s effective diffusion of innovations borrowed from outside the organization can become part of the learning strategy and contributes to successfully redirecting an organization’s strategies to help it adapt to the ever-changing business environment. In organizational behavior and sociology literatures, organizational learning refers to the study of how organizations respond and adapt to new and changing environments by adopting innovative practices. When this occurs, the learning process in organizations is assumed to involve the adoption and diffusion of innovations in the organization. This view is based on the literature in sociology. Management accounting literature is concerned with the design of management accounting systems. An important aspect of this study is process innovations and their implementation. Recent innovations in accounting systems, such as activity-based costing (ABC), have been addressed and studied extensively. This literature has recognized that, because the process of implementing any innovation in organizations is multifaceted, it needs to address questions such as why certain innovations succeed and others fail, and why the same innovation is successful in one organization and not in another. xiii

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These questions are the focus of this book. The book describes in detail the learning methodologies that organizations pursue in the design and implementation of management accounting innovations. We argue that organizations utilize sociological process innovation approaches to appraise the structural, cultural, and human resource capabilities that will both contribute to the success of management accounting innovations and, at the same time, minimize such constrains as could lead to their failure. We recognize that, at present, there is no generally accepted framework in sociology to aid us in making such an evaluation. Consequently, there is no integrative framework with which to study accounting innovations as organizational learning. Instead, this book contributes to expanding theory and methods in management accounting literature by utilizing a contingency framework from literatures that deal with organizational learning and the sociology of adoption and diffusion theories. This framework is applied to the study of organizational learning to understand better the success or failure of management accounting innovations implementations. As noted earlier, the book addresses two sets of interrelated questions commonly associated with management accounting innovations:  The first set of questions relates to why are some management accounting innovations more successful than others?  The second set of questions addresses why are innovations successful in some organizations but not in others? We develop a process innovation framework to understand these research questions consisting of four types of innovations. The contingency framework we propose argues that, the management accounting innovations in complex organizations can best be understood by examining two behavioral and structural characteristics present in any innovation. These are referred to as the extent and the scope dimension of an innovation. The extent dimension denotes the degree to which the organization’s existing systems are affected, whereas, scope has been defined as the proportion (number) of units within the organization that are impacted by the innovation. The extent and scope dimensions of innovations are adopted from the organizational behavior literature. In that literature, extent of innovations is subdivided into technical and administrative, and the scope of innovations is subdivided into autonomous and systemic. By integrating these two dimensions, we developed four types of process innovation: mechanistic, organic, organizational development (OD) and organizational transformation (OT). These are presented in Table 1.

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Table 1. Typologies of Management Accounting Innovations Based on Extent and Scope of Innovations Dimensions. Scope Technical

Autonomous Cell 1: Mechanistic

Extent Administrative

Cell 3: Organizational Development

Systemic Cell 2: Organic Cell 4: Organizational Transformation

DEFINITION OF TERMS A glossary of definitions is provided below to familiarize the reader with some of the sociology and organizational behavior literature terminology used throughout this book. We also relate this terminology to management accounting concepts to combine these two streams of literature into an integrated process innovation framework in management accounting systems.

Innovation Innovation has been viewed as an intentional attempt to introduce new ideas, products, technologies, administrative programs, or other process changes in an organization. Innovation is either induced internally or necessitated externally. In management accounting, these new programs may include the introduction of quality improvement programs and changes in management accounting control and/or reporting systems. Process Innovation Process innovation addresses the ways new ideas are implemented to change organizational activities, including the management accounting reporting and control systems. Process innovation is concerned with generating acceptance among those charged with implementation. Whereas innovation, in general, is an ongoing process that evolves over a period of time, process innovations in management accounting control systems often involve incremental change strategies that are either technical or administrative in nature. When an organization introduces an innovation, the effect of that innovation will be influenced by the learning strategy that the organization adopts as part of the innovation process. This choice will affect the

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magnitude of the organization’s innovation strategies (OD or OT) and the relative extent of change (technical or administrative). Diffusion of Innovation Diffusion of innovation addresses the flow and the process by which information is spread throughout the organization. An example of an innovation that affects accounting directly is ABC. Innovations indirectly affecting the accounting function are just-in-time technology (JIT), total quality management (TQM), or business process reengineering (BPR).

Organizational Learning In organizational behavior literature, organizational learning is referred to as the study of how organizations adapt to new and changing environments by adopting innovative practices (see Davenport, 1993). It is related to diffusion analysis in sociology (Rogers, 1971, 1995; Rogers & Shoemaker, 1971). Organizational learning has also been viewed as a source of competitive advantage that helps organizations to respond to changes in their respective institutional environments and, in turn, to adopt innovations that will improve performance. ‘‘Organizational learning entails new insights and modified behavior. [It] occurs through shared insights, knowledge, and mental models’’ (Stata, 1989, p. 64). An organization’s effective utilization of innovation is enabled by its learning strategy (Attewell, 1992; Fichman & Kemerer, 1997; Lant & Mezias, 1992; Mezias & Glynn, 1993; Schulz, 2001), contributes to its ability to redirect its strategy successfully (Windrum, 2001), improve business performance (Lopez et al., 2005), and to adapt to its changing competitive environment. Organizational learning has been described as a two-stage process: singleloop and double-loop learning (Argyris & Schon, 1978, 1996). Incremental change strategies are embedded in single-loop learning, whereas radical change approaches are associated with double-loop learning. Single-Loop Learning Single-loop learning is used to describe those accretions in an organization’s knowledge that result in incremental changes. Single-loop learning is intended to find better ways (i.e., new knowledge) of doing what the organization already is doing. The objective of single-loop learning is to find new ways and methods to accelerate organizational learning and improvements. These changes can occur in various ways. For example, an organization’s

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management accounting system may alter the overhead allocation base from labor hours to machine hours as a particular process becomes more automated. Some organizations change through trial and error; other changes are planned such as the decision to adopt an innovation that has been successful elsewhere. The rationale for adopting an innovation in these cases is the cost-benefit analysis. This is the essence of single-loop learning. Double-Loop Learning Double-loop learning has been associated with new knowledge that leads to radical or innovative changes in the organization. Double-loop learning occurs when an organization either detects or corrects errors in the operating procedures/activities or when it significantly modifies existing operating procedures (Van de Ven, 1986). Double-loop learning leads an organization to institute new procedures to transform the way the organization conducts its activities. Double-loop learning also occurs when an organization is able to ‘‘detect and correct errors in the operating norms’’ and activities of the organization (Van de Ven, 1986, p. 603). Double-loop learning allows an organization to institute new norms and procedures to transform organizational activities. It is second-order learning that leads to reorientation (Lant & Mezias, 1992). It is associated with discontinuous change (Bessant, 2005) and development of new paradigms to do things differently than in the past. For example, if an organization adopts a new approach to inventory costing such as ABC, it is primarily limited to technical innovations and do not involve transformational changes.

Technical Innovation Damanpour and Evan (1984) defined technical innovation as focusing on improving the technological performance of the organization. Technical changes in accounting focus on improving the techniques by which accountants gather, process, calculate, and report data on operating activities of the organization. Activity-Based Costing as a Technical Innovation ABC is a technical innovation in calculating product costs. ABC provides accounting information about the cost of activities associated with producing goods and delivering them to customers. Activity drivers that generate costs are assigned to products and customers, while cost drivers are

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INTRODUCTION

assigned to all activities that generate those costs. Product costs are determined by adding the costs of each activity incurred in making the product (Kaplan, 1989). Overhead is identified with activities that generate costs, rather than being allocated to products or operating departments based on pre-existing allocation bases. The objective of ABC is to eliminate non-value-added activities that do not contribute to improved performance (Argyris & Kaplan, 1994; Kaplan, 1989).

Administrative Innovation Damanpour and Evan (1984) described administrative innovation ‘‘as those that occur in the social system of an organization y an administrative innovation can be the implementation of a new way to recruit personnel, allocate resources, and structure tasks, authority and rewards. It comprises innovation in organizational structure and in the management of people’’ (p. 394). When management accounting control systems are introduced as administrative innovations, they perform organizational control functions to monitor, motivate, or conduct performance evaluation. ABC as an Administrative Innovation Implementation requires the structural support of formalization, centralization, and decision making in the organization’s bureaucratic structure. Thus, ABC can also involve elements of an administrative innovation when the change requires several adaptive process stages before the costing system itself can be successfully initiated and implemented. A critical part of the initiation process may include a program about attitudinal change, education and training, and strong management support.

Autonomous Innovation Innovations can be either autonomous (standalone) or systemic (integrative). Teece (1996) defined an autonomous innovation as ‘‘one that can be introduced without modifying other components or items of equipment component or device;’’ in other words, it ‘‘stands alone’’ (p. 205). While technological innovations are self-contained (autonomous), administrative innovations involve structural re-alignment, personnel changes, and a wide range of organizational levels and tasks for adoption of innovation changes.

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Systemic Innovation A systemic innovation requires ‘‘significant readjustment to other parts of the system’’ (Teece, p. 205). In systemic innovation, information flows are integrated to minimize institutional barriers to innovation. Systemic innovations in accounting require coordination of resources: personnel, financial and material, as well as sharing information technology and communication channels across units to implement a managed inventory scheduling system. ABC as a Systemic Innovation ABC assumes ‘‘that manufacturing is an integrated process that starts when supplies, materials, and parts arrive at the plant’s loading dock and continue even after the finished product reaches the end user. Service is still a cost of the product, and as is installation, even if the customer pays’’ (Drucker, 1995, p. 55). ABC takes a systemic approach in analyzing and integrating ‘‘what was once several activities – value analysis, process analysis, quality management, and costing – into one analysis’’ (Drucker 1995, p. 55).

The Institutional Framework Barnett and Carroll (1995) classified institutional theory as an adaptive change process framework because it examines the impact of external environmental factors and market conditions on organizational change and development (pp. 217–218). The institutional approach focuses on adaptive change strategy to improve existing systems, technologies, products, and services (Mezias & Glynn, 1993). However, the institutional framework emphasizes the functional approach of maintaining the existing organizational structures and systems whether the process innovation change is either incremental or radical. Incremental changes seek solutions that help an organization adapt to the environment with minimal structural change (e.g., TQM). Radical changes advocate significant process innovations that require a complete transformation of the organization’s mission, strategies, and leadership (e.g., BPR). The institutional framework maintains that organizations, irrespective of their structural arrangements (mechanistic or organic), can successfully change if they implement adaptive strategies of either incremental or radical change to implement process innovation.

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Management Accounting Process Innovation Typologies We have classified four types of innovations in management accounting systems. We combined extent (technical and administrative) and scope (autonomous and systemic) to identify four types of innovations: mechanistic, organic, OD, and OT as shown in Table 1. Mechanistic Innovations The term ‘‘mechanistic innovations’’ is defined as both technical (extent) and autonomous (scope) innovations. When environmental change is internal, and the response is incremental (single loop), the innovation strategy is labeled mechanistic. As mechanistic innovations occur frequently in large manufacturing and production-oriented organizations. Manufacturing organizations have functional structures suited for processing noncomplex, routine, and repetitive large-scale tasks that do not require specialization of technical expertise. Functional organizations have bureaucratic structures that are hierarchically differentiated with several layers of management hierarchy. Vertical and horizontal hierarchical arrangements and differentiation are required to process the workflow. Differentiation and specialization eventually contribute to formalized control systems and relationships that create communication barriers and reduce the flow of information. Decision making becomes centralized, with minimal involvement of lower management levels. These characteristics make innovation across units more difficult. Organic Innovations Organic innovations are defined as characterized by administrative (extent) and systemic (scope) of process innovations. When external environmental conditions result in incremental (single loop) change, management accounting innovation follows an organic strategy. In sociology, the word organic describes organizational structures that are flexible and adaptable to changes in their institutional environments. Organic structures have horizontal hierarchy, little differentiation, limited chain of command, minimal bureaucratic features, and decentralized decision making, all of which facilitate the flow of information and the dissemination of innovation within the organization (Burns & Stalker, 1961). There is less reliance on formal control systems to monitor employee and organizational performance.

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Organizational Development OD refers to the third typology in the innovation process. OD is defined as technical (extent) and systemic (scope) innovations. When environmental change is internal, and the response to change is radical (double loop), innovation follows an OD strategy. OD is used in organizational change and sociology literature to describe cultural innovation programs intended to modify employee cognition and behavior. In accounting, the OD approach is important because accounting innovations, for example, ABC, are directed to change management behavior and their use of accounting data to evaluate performance. OD applies to the use of ABC data at the divisional or unit level. Organizational Transformation OT refers to the fourth typology in the process of innovation framework. OT has been defined as administrative (extent) and systemic (scope) innovation. When changes in the external environment initiate radical change (double-loop learning), process innovation adheres to an OT intervention strategy. OT is targeted to change organizational structures as well as individual and groups within the organization. OT change in programs has a broad scope that requires comprehensive change in the organizational paradigm. This paradigm shift affects behavior across the entire organization, thereby creating new behaviors that provide employees with a new way of viewing their jobs. OT intervention leads to both cognition change and commitment to radical change. Radical technological innovations such as BPR have made significant structural changes in manufacturing processes, inventory, and production scheduling, delivery techniques, product design, and quality improvements.

The Impact of Information Technology on OT Information technology is critical for OT process innovation. Accounting as a financial and economic information system thus becomes the cornerstone of the business process. As information managers, accountants monitor information on organizational performance to assess that requires improvement, the need for functional integration of accounting systems that connect organizational units, and appraise the readiness of the human, financial, and technological resources to carry out business innovation.

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OD and OT Approaches in ABC Accounting innovations can either follow an OD or OT innovation strategy. The initial adoption of an innovation decision (experimental stage) is generally limited to a single unit or department. While OD innovation intervention is limited to a single organizational unit or function, OT focuses on changing several units or functions with interdependent operating activities. OD and OT intervention play complementary roles, because OD intervention is often critical in the adoption/initiation decision, and OT intervention is required during implementation.

ORGANIZATION OF THE BOOK We apply the process innovation framework to suggest guidelines on how to address the two questions posed above: why some innovations fail and others succeed and why some innovations are successfully implemented in some organizations, but fail in others. The framework is applied to study recent management accounting innovations including ABC and balanced scorecard (BSC). We elaborate that the success of management accounting innovations depends on the degree to which the strategy adopted by the organizations is appropriate for the extent and scope dimensions of the innovation they desire to adopt and diffuse. These organizational innovations can be successfully designed and implemented within the context of these four typologies. In other words, the process of adoption and diffusion in management accounting innovations can be planned and implemented following these four types of organizational process innovation. Accordingly, this book is organized into seven chapters. We have included in the book table of contents, acknowledgments, references (bibliography) as well as subject and author indices. A summary of the chapters are provided below. Chapter 1 discusses the organizational processes and structural barriers to the diffusion and adoption of innovations. In this chapter, we address the question of ‘‘why innovations fail?’’ We discuss barriers to innovations to describe why innovations may fail. We argue that failure of potentially beneficial innovations is primarily associated with leadership characteristics and/or employees’ resistance to change. We review the sociology and accounting literature and discussed several possible issues that contribute to

Introduction

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resistance to innovations. Some of these include lack of enthusiasm among innovation champions, resource constraints to undertake innovations, as well as improper framing or a lack of perceived benefits. This is particularly true when innovations involve radical and transformational changes in existing systems. Single-loop as a gradual and double-loop as a radical approach to organizational learning are discussed within the context of barriers to innovations. Chapter 2 addresses the organizational learning strategies of adoption and diffusion of process innovation approaches. We reviewed the literature in organizational sociology and organizational behavior to extend the adoption and diffusion analysis to management accounting systems. In Chapter 3, we present the theoretical framework of organizational learning and process innovations. We discuss the four dimensions used to define the extent of innovations (technical and administrative), and the scope of innovations (autonomous and systemic). The chapter briefly introduces the four types of innovations that are discussed in details in the next two chapters. In Chapters 4 and 5, we present the four typologies of innovations in detail. Research questions related to these four typologies are discussed in these chapters. Chapter 4 compares mechanistic and organic innovations and Chapter 5 OD and OT innovations. These two chapters relate accounting innovations and systems to the four types of innovations. Accounting innovations have been largely influenced by developments in management philosophies such as TQM and BPR. These management philosophies are discussed, and are related to management accounting changes and developments. Chapter 6 elaborates the organizational learning framework by incorporating the two stages in sociological theories of process innovations: adoption and diffusion. We present these two stages of innovation within the framework of OD and OT innovation strategies and relate them to management accounting innovations, namely ABC and BSC. Chapter 7 is the conclusion. It summarizes the argument and discusses areas for future research that can be addressed within this framework. Particular points raised are on the need by researchers and policy makers to approach the subject of management accounting innovations as multidisciplinary particularly when the implementation of innovations addresses cultural, organizational, and human resource capabilities and constraints. We raise several research questions and discuss the policy implications of the organizational learning framework that we promote for the adoption and diffusion of process innovations.

CHAPTER 1 WHY INNOVATIONS FAIL: ORGANIZATIONAL PROCESSES AND STRUCTURAL BARRIERS TO INNOVATIONS

This chapter asks ‘‘Why do some desirable innovations fail?’’ and discusses potential barriers to innovations. We address structural barriers to innovations within the context of organizational processes and the constraints of innovations.

1.1. ORGANIZATIONAL PROCESSES AND CONSTRAINTS OF INNOVATIONS Strange and Soule (1998) outlined the processes of innovations as follows. ‘‘Innovations are novel (at least to the adopting community), making communication a necessary condition for adoption. Innovations are also culturally understood as progressive, strengthening the hand of change agents. And since innovations are risky and uncertain, adopters carefully weigh the experience of others before acting’’ (p. 267). Zaltman, Duncan, and Holbek (1973) utilized a sociological framework to approach innovations within the context of organizational change and management. They also suggested that innovations involve ideas or practices that are considered new or novel by those individuals, groups, or organizations that are adopting them, and, therefore are a potential risk to the adopters. In other works, innovations have contextual implications because the process involves their adoption by organizational members. In view of the fact that innovation involves learning new knowledge and 1

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ORGANIZATIONAL LEARNING AND PROCESS INNOVATIONS

acquiring new behaviors, it requires an organizational structure and context that supports innovations and their effective planning and implementation. These systems should be able to identify problems and act on them. Thus, organizations manage innovations by organizing their activities through an ongoing trial and error process. Over time, these behaviors become routines in the form of policies, procedures, and structures. They determine the course of the innovation (Bessant, 2005, pp. 35–37). Innovation as a learning mechanism is a continuous process of adaptive learning that requires breaking away from existing assumptions that focus on knowledge stabilization and inhibit change and adopting those activities that make viable the emergence of possible knowledge from new instruments. These new instruments may involve dialogue, intervention techniques, reflections from transactions, and constructions of positions in the field or area of interventions – all to destabilize existing knowledge and open up new possibilities and movements in different directions (Engestroom, 2007, pp. 271–275). On the contrary, innovation as a process of intervention strategy follows a sequence of two stages. According to Zaltman et al. (1973), the first is the initiation stage that involves an awareness of the new idea or technologies. The second stage is the implementation stage that includes the adoption of the innovation. When innovations are adopted, they become key factors in enhancing the competitive position of organizations. Organizational and environmental factors influence the innovative capability of organizations and improve their strategic position within the industry and market. Resources can act as constraints or enablers in the adoption of the innovation processes. Organizations that have slack resources are in better competitive positions to realize the benefits of innovation. Herold, Jayaraman, and Narayanaswamy (2006) refer to organizational slack as resources available to organizations in excess of those required to meet their current needs. It implies that organizations have a cushion or excess resources to adopt innovations (p. 373). March and Simon (1958), and Cyert and March (1963) viewed slack as conducive to an organization differentiating between goals and innovations. In other words, increased slack might increase an organization’s willingness and ability to take risks associated with innovations because an unsuccessful innovation is less of a threat to the organization’s ongoing activities. For example, Herold et al. (2006) found a relationship between slack and the undertaking of innovations ‘‘for industries that rely more on patent protection.’’ These firms need protection because they ‘‘need to be efficient in these activities in order to remain competitive’’ (p. 387). In other words, they want to avoid unnecessary use of resources for the future beyond what

Why Innovations Fail

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they currently need to undertake innovations. These organizations have learned through experience with previous innovations how to balance and manage their resources to be competitive. By contrast, resources are a constraint when there are shortages of available funds to finance the cost of a proposed innovation and create barriers to the initiation and/or adoption process. From a population ecologist perspective, resources are also dependent on geographical location that can influence resource availability and competition. Barnett and Carroll (1987) suggested that companies in different locations are more competitive regardless of organizational form in contrast to companies that are located in the same or in nearby geographical areas. Their critical point is when location creates interdependencies among organizations; the environment (i.e., location) serves to determine the degree of competition or interdependence among them. In addition, employee resistance to innovations, inadequate information flows within the organization resulting in misinformation, inability to determine market and customer reactions or support to innovations also can be barriers to a successful outcome. Structural barriers and constraints arising from organizational factors associated with coordination, centralization, and bureaucratized (inflexible) managerial control system can be potential obstacles to and hindrance in the successful adoption of innovations.

1.2. AN OVERVIEW OF STRUCTURAL BARRIERS TO INNOVATIONS Given adequate resources, failure of potentially beneficial innovations is primarily associated with aspects of leadership and/or resistance to change. The sociology and accounting literatures suggest that possible issues that contribute to resistance to innovations include improper framing or a lack of perceived benefits. This is particularly true when innovations involve radical and transformational changes in the existing system. We have advanced the view that barriers to innovations are greatest when innovations are complex, such as accounting innovations in multiple divisions and/or units. These accounting innovations involve both technical and administrative changes. They shape divisional and/or unit performance, and, in the process, they influence the allocation of rewards and incentives among managers. They may be actively resisted by managers when the managers believe the technological and administrative innovations are

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related to performance evaluation and management compensation and could adversely impact them. These impediments to innovations in accounting will be within the context of activity-based costing (ABC) and the balanced scorecard (BSC). We also suggest that there are cultural and organizational factors that explain why some innovations fail to be adopted even when such innovations would meet the requirement of having positive expected economic returns to the organization and the managers. We identify these factors to be associated with the failure of the rewards to be perceived by the potential adopters as meeting their needs (rewarding them) or requiring too great an expenditure of resources (time and effort as well as money) on their part relative to their expected benefits. It is also possible that what may be beneficial from the organization’s perspective is detrimental to a specific manager(s). This can occur for various reasons ranging from poor leadership to an inappropriate reward structure. Thus, the adoption and diffusion of innovations is contingent upon organizational contextual and structural characteristics. In the next section, we utilize the contingency framework to describe those factors that either create barriers or impediments and/or facilitate the design and implementation of process innovations.

1.3. CONTINGENCY FRAMEWORK OF SOCIOLOGY The sociological contingency framework applies open systems theory and decision-making approaches that take into consideration external environmental factors. These include social, economic, political, governmental, environmental, socio-cultural, market, and technological developments (Steiner, 1979; Steiner, Miner, & Gray, 1982; Yasairdekani & Nystrom, 1996). These factors are of interest to researchers whether or not contingency guidelines are appropriate and adaptable to specific decisionmaking situations/contexts (Tushman, Newman, & Romanelli, 1986). The sociological contingency framework relates the development of strategic decisions as mediating organizational resource allocation decisions as organizations attempt to allocate their limited scarce resources or competencies to maximize business opportunities by minimizing current potential environmental threats (Porter, 1980). The contingency approach thus provides a situational and an ‘‘if-then’’ strategic decision-making guideline, tailored to specific organizational decisions, which include management accounting innovations. An ‘‘if-then’’ perspective allows the

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consideration of the extent to which changes in external ecological and environmental factors influence decisions regarding the allocation of organizational resources. The contingency framework thus enables organizations to develop strategies to match the requirements of their external environment with internal resources and capabilities to adopt and diffuse the appropriate process innovations (Sisaye, 2011). Organizations attempt to change and adapt their strategies contingent on both institutional (internal) and market (external) forces. The characteristics of leadership and top management composition, that is, whether or not there exists heterogeneity involving age, sex, tenure, education, values, experience; influences, whether or not management takes a broad or narrow scope in viewing problems/opportunities that shapes the type of strategic change the organization undertakes. Naranjo-Gil and Hartman (2007) utilized the prospector vs. defender typology from the strategy literature to determine whether or not management utilized broad or narrow views of strategic change in adopting management accounting systems (MAS). They found that prospector organizations looked for flexibility and a broader and more interactive scope in their MAS compared to defender organizations. The latter opted for a narrower scope of MAS to support the strategies they adopt to manage the institutional and market forces faced by the organization. It would appear that organizational performance is contingent upon the existence of a fit between selected strategic structural factors related to strategy type – prospectors and defenders (Simons, 1987). In general, contingency factors shape the strategic posture and performance of organizations. Simon (2007) discussed several contingency factors related to strategy deliberations arising from emergent and ambiguous to planned conditions and market orientations. He suggested that where accountants were involved in decision making, MAS had roles in strategic decisions of organizations. Strategic decisions in organizations involve contingent situations that are ambiguous and unknown. Process innovations in organizations are strategic decisions because they require resource allocations and management’s willingness to accept the risks-failures or benefits-success associated with the initiations and adoption of innovations. The learning strategy that the organization utilizes in the adoption of innovations shapes the scope (breadth or depth) of the innovations. Sociology offers two competing approaches; the structural functional (SF) and the conflict radical (CR) approaches (see Sisaye, 2011). We have incorporated both of them to describe organizational learning effectiveness in process innovations decisions. We utilize both approaches as is appropriate to better understand organizational learning.

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Single-loop and double-loop learning are associated with each of the SF and CR approaches. Sociological contingency frameworks of both the SF (single-loop) and CR (double-loop) approaches are applied to examine the extent to which environmental factors, industrial organizational structures, technological developments, ecological issues, government regulatory agencies, and cultural and social forces shape decisions that may contribute to conflicting goals in society. As we discuss below, the two approaches view problems facing the organization quite differently and take sharply differing views of organizational learning.

1.3.1. The Structural Functional Theoretical Framework The SF approach takes a more focused view. It examines the functional and institutional importance of structures in societal change. It studies the most important components of the social system and the characteristics of the organization as a whole. Because in the SF approach each organization is considered unique, the approach advocates a contingency view of organizations, that is, the appropriate course of action for a specific organization is dependent on the characteristics of the organization’s internal and/or external environment. The contingency approach accounts for those particular social relationships that define a given system (i.e., organization, sub-unit or group of sub-units), where changes occur within the system, and what types of change characterize the system. To set the social context of a given organization, the SF contingency approach defines the test of significance in terms of its functional relevance for the maintenance of the organization’s social systems that are being studied. Social structures, in turn, have causal effects on actors, individual and group behaviors, and on social relationships. They provide networks where actors can interact in meaningful exchange relationships (Whitmeyer, 1994, pp. 153–156). When exiting structures modify or change, it is expected that actors’ behaviors also change. In searching for legitimacy, organizations adopt structures and procedures that are accepted by their political and social environment. These structures are diffused across several organizations that operate in the same cultural environment (Ribeiro & Scapens, 2006, p. 96) and organizations successfully operating in similar environments can be expected to exhibit similar structures. According to Ambrose and Schminke (2003), structures have defined and recurring sets of behavioral relationships among organization members. These structures consist of those charters, power

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relationships, rules and regulations that determine work behaviors, power relationships, and decision-making processes in the organization. Ambrose and Schminke (2003) described organizations as consisting of two types of structures: mechanistic and organic. These organizational structures do affect or influence performance of individuals and teams/groups (pp. 295–296). They will be discussed in subsequent chapters. Functional structures affect the distribution of positional power in organizations. In this context, structural power refers to power acquired through the formal position occupied in the organizational hierarchy (Krackhardt, 1990, p. 345). Structural power provides access to organizational resources. To have access to these resources, actors employ several forms of structural powers: positional or legitimate. The tactics that actors employ to translate power potential to power use affects the resultant structural power advantage to influence others in accepting process innovations (Brass & Burkhardt, 1993, pp. 444, 449). Therefore, it is critical to understand the SFrational assumptions and their relationships to organizations and management, and the impact on process innovations decisions. The SF approach argues that the organization consists of two major goaldirected systems or functions. These are task and social systems. SF researchers that view organizations as task system focus on the technical and productive orientation of the organization. We have referred to this as the ‘‘mechanistic’’ or ‘‘production’’ view of process innovations. Under the production view, the concern is on task accomplishment and the primary consideration is on the economic efficiency and effectiveness of process innovation programs and initiatives (Kabanoff, 1991, p. 419). Morgan (1986) has advanced the technical/production and task orientation view of organization. He used the machine metaphor, which is analogous to the mechanistic view. The metaphor assumes that organizations process operational characteristics in the same way as machines. Like machines, they have mechanistic systems that operate efficiently. Their behavior is predictable. Organizations, like machines, are controlled by management through budgets and standards. In this setting, organizational management is viewed in a way that is akin to a machine on a short-term basis where budgets and accounting performance indicators play important roles in measuring individual/organizational performance. On the contrary, the social-system view of the organization has been concerned with relational issues that affect the maintenance of the system components of the organization. According to Kabanoff (1991), the social-system view has stressed those factors that are related to employee orientation and consideration, social environment, and personal work

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relationships. In the systems view, the objective has become the maintenance and preservation of the arrangement of roles or relationships created by the production subsystems. The fundamental dynamic here is the maintenance of cohesiveness, solidarity, or a sense of common fate, that is, the organization’s social environment, among system members (p. 419). Accordingly, the systems view of SF is focused on system maintenance to promote organizational goal achievement, stability, adaptability, and survival. The goal of management is to ensure that the organization is orderly and integrated so that input–output relationships and labor productivity are maximized. In this environment, accounting systems and practices have technical roles to play in the appraisal, evaluation, and rewarding of employees (Sisaye, 1997). The SF systems process operates indefinitely and involves modification and/or experimentation to improve existing systems, technologies, products and services on a continuous basis (Lant & Mezias, 1992; Mezias & Glynn, 1993). Given the SF emphasis on operating efficiency and effectiveness, it is logical that organizations characterized as SF follow a reactive/adaptive strategy to change that focuses on incremental, quick-fix, solutions rather than on a long-term solution. SF utilizes a step-by-step incremental strategy to institute modifications and small-scale improvements to correct problems without major organizational commitment in technical, financial, and human resources (Mezias & Glynn, 1993). Accordingly, the SF approach to organizational learning is single-loop (incremental). It legitimizes doubleloop (radical) learning as long as the outcomes of the process support the stability and maintenance of the social systems.

1.3.2. The Conflict-Radical (CR) Theoretical Approach The CR approach advocates radical and proactive innovation strategies to alter the organizational learning systems. The strategy is to experiment with or to explore new assumptions, ideas, and novel approaches that result in major breakthroughs in learning that have positive effects on society (Mezias & Glynn, 1993). It involves the development of new paradigms and perspectives in educational methodologies to institute radical changes. It is based on re-orientation learning, focusing on anticipating and responding to environmental changes to understand the consequential impact of learning in organizations and society (Metzger & Phillips, 1991). In general, the CR approach follows planned innovation strategies of organizational growth and transformational development (Sisaye, 2001).

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Despite chaotic appearance of this view, the CR learning strategy focuses on orderly double-loop, second-order learning and a well-planned imaginative and creative change approach. Metzger and Phillips (1991) have suggested that double-loop learning has the potential to re-orient and modify the institutional assumptions of corporations and society and re-define the educational systems programs to focus on organizational change and development. The CR approach views learning and innovations in terms of altering existing social contractual relationships among societal members. The consequential approach follows a radical approach that advances individual and institutional integrity, systemic and integrative thinking, to understand the consequences of management actions, and, if necessary, to be able to take corrective measures to avoid social, ecological, and environmental crises (Sisaye, 2011). The CR approach follows a proactive, double-loop learning approach to organizational learning.

1.4. ORGANIZATIONAL LEARNING: SINGLE AND DOUBLE LOOP Organizational learning has been viewed as a source of competitive advantage. It helps organizations to develop and adopt innovation strategies that enable organizations to respond effectively to changes in their institutional environments to improve their performance. Organizational learning has been viewed as entailing ‘‘new insights and modified behavior. [It] occurs through shared insights, knowledge, and mental models’’ (Stata, 1989, p. 64). Researchers from diverse disciplines: sociology, organizational behavior, to mention a few of them, have argued that an organization’s effective utilization of innovations is enabled primarily by an appropriate learning strategy (Attewell, 1992; Fichman & Kemerer, 1997; Lant & Mezias, 1992; Mezias & Glynn, 1993; Schulz 2001). Learning increases the organization’s ability to adapt to its changing competitive environment and successfully implement appropriate strategic changes intended to improve its performance (Lopez, Peon, & Ordas, 2005; Windrum, 2001). Thus, both the adoption and diffusion of innovations and organizational learning are important to organizations confronted with the need to innovate to improve long-term performance (Sandberg, 2007). Lumpkin and Lichtenstein (2005) have identified three approaches to organizational learning: behavioral, cognitive, and action. Behavioral learning deals with the capacity of organizational processes, structures and systems to support learning (pp. 453–454). Cognitive learning, on the contrary, focuses

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on individuals’ capacity to change their mental cognition and abilities to acquire, assemble, and interpret knowledge (pp. 454–455). Action learning addresses the application, practicality, and effectiveness of acquired knowledge in solving problems. It has implications for an improvement in an organization’s performance. The Argyris and Schon (1978) classification of learning into single- and double-loop is based on action learning and the impact learning has as incremental (single-loop) or radical (double-loop) change. Action learning enables individuals to be reflective, ask questions, increase their willingness to uncover problems, discontinue extant routines that hinder performance, and take appropriate actions that impact the organization at large. It changes patterns and styles of communication and interaction among members. Argyris and Schon (1978) suggested that, in action learning, there is openness and willingness to take competitive advantage in innovations and productivity (pp. 455–457). Members exchange ideas, commit themselves to problemsolving, and adapt to the new learning environment. There is discovery, awareness, and cooperation in creating synergies of the new knowledge that enhances the organization’s capabilities and competencies. Organizational learning, thus deals with developing knowledge and enabling organizations to become competitive to adapt to their environment. For example, in marketing, Kandemir and Hult (2005) suggested that learning broadens the scope of organizational market orientation to achieve a competitive advantage. It influences the culture and orientations that organizations have toward their customers. Organizations that have culture with innovative systems orientations are customer-oriented in terms of their products and services. Learning enables multinational corporations to compete globally by acquiring knowledge that is unique, develop new insights and have experiences that help them adjust to the international market environment. The global market is competitive and firms need new technological innovations, and products to meet consumers’ demands and needs. According to Vera and Crossman (2004), organizational learning can become a source of competitive advantage that drives the future strategic direction of an organization for renewal. When learning is institutionalized, it becomes a part of the operating activities of the organization, and eventually is embedded in policies, procedures and daily routines (pp. 222–225). Learning organizations are able to differentiate themselves from others by their ability to use their knowledge to obtain a relative advantage over their competitors. This entails management knowledge. In strategic learning, it refers to the ability of top management to use accumulated knowledge to

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improve and advance organizational performance vis-a-vis their competitors. Thus, strategic learning involves the use of experts with diverse backgrounds to gather, collect, interpret and analyze data for decisions that place the organization at a competitive advantage (Thomas, Sussman, & Henderson, 2001, pp. 331–342). Bapuji and Crossan (2004) suggested that the strategies of organizations shape learning and context to align learning with environmental changes. Thus, the structure (which is the context) shapes the learning process and its outcomes (p. 408). In organizational behavior literature, organizational learning is defined as the study of how organizations adapt to new and changing environments through the adoption and integration of new and innovative practices (see Davenport, 1993). Thus, in addition to adoption, learning is also related to diffusion analysis in sociology, which studies how innovations are disseminated across a particular population, that is, similar group (Rogers, 1971, 1995; Rogers & Shoemaker, 1971) and within an organization (Sandberg, 2007). In this book we apply the organizational learning framework to the management accounting literature to understand better why management accounting innovations succeed or fail in organizations. When an organization introduces an innovation, the nature and effect of that innovation will be determined by the learning strategy that the organization adopts. This choice will influence the magnitude of the organization’s change in terms of extent and scope. When process innovation is supported by organizational learning, it facilitates diffusion and adoption. Stata (1989) viewed organizational learning as a competitive advantage for organizations able to respond quickly to changes in their institutional environments (p. 64). In other words, to respond to competitive changes, organizations cannot effectively utilize process innovations without a well-developed learning strategy (Lant & Mezias, 1992; Mezias & Glynn, 1993; Porter, 1980). The learning strategy follows a two-stage process: single-loop and double-loop learning (Argyris & Schon, 1978). We have defined single-loop learning in terms of incremental change, and double-loop learning as radical change.

1.4.1. Single-Loop Learning The objective of single-loop learning is to find new ways and methods to accelerate organizational learning and improvements. Single-loop learning is intended to find better ways of doing things already being done. These changes can occur in various ways. Some organizations change through trial

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and error; others change by adopting innovations that have been successful elsewhere. The rationale for adopting an innovation in such cases is the cost–benefit analysis. This is the essence of single-loop learning. The focus of the single-loop learning pedagogy is on detection of errors/ inefficiencies and on their correction within the operations of the organization to improve its performance, strategy, and systems. Learning is designed to improve existing sets of activities within the organization and to modify their functionality and adaptation to changes to maintain the stability of the system. Thus, the adaptation process allows organizations to make incremental changes to improve performance. In general, incremental changes are ‘‘generated through continuous improvement processes, are more clearly defined and better understood than transformative changes’’ (Dibella, 2007, p. 237). Accordingly, there are fewer unknowns because the processes being adjusted or redesigned are not new. There is a greater likelihood that changes are understood and outcomes known. Resource expenditures required by design are limited with few unintended consequences.

1.4.2. Double-Loop Learning Double-loop learning occurs when an organization is able to ‘‘detect and correct errors in the operating norms’’ and activities of the organization (Van de Ven, 1986, p. 603). Double-loop learning allows an organization to institute new norms and procedures to transform organizational activities. It is a second-order learning that leads to re-orientation (Lant & Mezias, 1992), discontinuous change, and development of new paradigms to do things differently than in the past. Discontinuous change usually arises from changes in markets, technology, and competitive forces. There will be unanticipated interruptions and disruptions in operations. Because these discontinuous changes require significantly different adaptive strategies and approaches to management organization activities, organizations plan ahead to address them. Bessant (2005) noted that, when organizations face problems that are beyond their current domain or ‘‘normal operating conditions,’’ the viable alternative approach for addressing them is through discontinuous innovation. ‘‘Discontinuous can take a number of forms – for example a step change in technological development, the emergence of a totally new market or a dramatic shift in the political/regulatory environment’’ (p. 37). These changes happen most often to organizations operating in unstable

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conditions that give rise to discontinuous change. Bessant (2005) referred to discontinuous innovation as ‘‘generative’’ or ‘‘double-loop’’ learning that involved the development of new behaviors that, over time, eventually become embedded into routines (p. 38). Double-loop learning occurs when an organization moves from simply performing what they are doing better by referring to rules and procedures (single-loop) to improve their operations by constructively challenging current routines and activities. Organizations develop alternative assumptions, ideas, and resources to replace old rules even if they are functional. They will test new ideas to bring novel approaches and methods to the conduct of their operations and business. Double-loop learning also generates new technologies that lead to major changes in knowledge and activities within organizations. If double-loop learning is to become robust and advance the organizational learning process, it can do so by identifying, suggesting potential solutions, and eliminating unsuccessful solutions. As a result of this process, ‘‘errors are eliminated by reflecting on mismatches between tentative solutions tried and expected outcomes’’ (Blackman, Connelly, & Henderson, 2004, p. 19). In other words, there is reflective learning when new solutions develop to solve existing errors/problems (e.g., see Rowe, Birnberg, & Shields, 2008). Thus, double-loop learning questions existing operational activities to bring about radical changes that will alter and change these activities. Strategies, missions, and systems are altered to bring dynamic changes in the organization work activities and processes so that they become flexible and adaptable to the changing environment. Organizations acquire a new knowledge base and competencies that will enable them to interact and manage the external environment. They have acquired the knowledge required to utilize resources that are obtained either internally and/or externally. Managing the flow of information and integration of a different knowledge base increases the capability of organizations to manage resources effectively. Double-loop learning is most likely to occur when organizations face a dynamic environment with continuous changes in both the external and environmental sectors. In these conditions, a double-loop learning strategy, particularly one that involves paradigm changes, is necessary to sustain and improve organizational performance. Double-loop learning is also required when an organization accustomed to an incremental (single-loop learning) environment is faced with a discontinuous change in its external environment (e.g., see Rowe et al., 2008).

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Jamali (2005) suggested that organizations with matrix and decentralized structures, where teams manage uncertainties through innovations and change, are best equipped to handle changes in both their external and their internal environments (pp. 107–109). In general, organizations with decentralized structures encourage free flow of communication and information exchange leading to ongoing changes in organizational assumptions and behaviors. It is possible that these developments of double-loop learning may foster and ease paradigm changes in an organization’s culture, behavior, and mode of operations. Van Haaften (2007) argued that ‘‘paradigm change can be represented in terms of judgment criteria’’ that represent conceptual change. These conceptual changes have three components or basic structures (or steps). First, there is a ‘‘logical reconstruction of these constructive processes’’ to understand what the specific conceptual changes are (p. 209). Second, there have to be individuals or persons who accept these changes and then are involved in advancing them. Third, these concepts must lend themselves to structural analysis by others. Van Haaften (2007) advances Kuhn’s (1970) paradigm change by suggesting that it implied the rejection of existing accepted judgment(s), or, in Newton’s case, the view of the universe. For Kuhn, accepting ‘‘Einstein’’ by definition ‘‘implies rejecting Newton,’’ and ‘‘this is what makes it a paradigm change.’’ Accordingly, this involves structurally replacing ‘‘the initial judgment criterion’’ by new ones (Van Haaften, 2007, p. 211). Taylor (2005) gave an example of a paradigm shift in international migration management by the United States, Canada, Australia, and New Zealand in the 1990s where migration in limited form and controlled operation was accepted by Third World countries to manage migration through a global migration and labor protection program. Both Van Haaften (2007) and Taylor (2005) perceived paradigm change as involving both structural and conceptual changes in organizational learning and innovations. Whether learning involves the detection of errors, the development of new methods to solve existing problems, or a complete overhaul of the system of operations with new behaviors and modes of operations involving paradigm changes, organizational learning, whether single-loop (incremental), and/or double-loop (radical) is necessary to improve organizational performance. Accordingly, both single- and double-loop learning strategies shape both technological and administrative innovations. In SF and CR frameworks, both learning approaches are exemplified within the context of adoption and diffusion of technological innovations.

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1.5. ADOPTION AND DIFFUSION ISSUES RELATED TO SF- AND CR-BASED TECHNOLOGICAL INNOVATIONS Both SF and CR frameworks assume that the learning process starts with adoption of technological changes that affect production relations and economic organizations in society. The learning process is shaped by organizational power and structures, conflictual and coalition-based relationships, individual goals, social order, and distribution of resources. Learning and innovations have the potential to alter existing political power structures in the organization if they are adopted by those that are not part of the coalition. In other words, there are risks and uncertainties associated with learning that are mostly related to technological innovations, which could result in delays in adoption, resulting from power conflicts among coalition members. Such delays in adoption makes the result of the ‘‘technologically improved product’’ short-lived and obsolete (Butler, 1988, p. 20). While risks and uncertainties explain delays in adoption of innovations, differences in early and late adoption may be attributed to factors related to cohesion and structural arrangements that define individual and social relationships as well as timing differences in investment decisions. In a study of medical innovation, Burt (1987) discovered that SF attributes of physical proximity, structural equivalence, friendliness, and network relationships caused social contagion of diffusion of innovation. Structural equivalence indicated that in medical innovations, physicians adopted new formulations, for example, prescription drugs, when their peers in the medical hierarchy profession adopted these innovations. Soete and Turner (1984) noted that costs and resource outlays associated with innovations are the principal reasons for delays in innovation investments. SF-based economic assumptions stress return on investment and cost-saving mechanisms when making investments in technological innovations. It is assumed that organizations make different decisions about investment choices: when to adopt, how to seek the most profitable investment technique, where to invest, how to determine the cost of new investments, and obtain more information about time, costs, and alternatives. It may involve a rational decision to delay action until all the relevant information about other organizations’ experiences is obtained (Soete & Turner, 1984, p. 615). To this effect, Witt (1997) expressed the economic risks associated with early adoption decisions as follows: ‘‘The agents who adopted the new

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technology or variant at an early stage would have to bear a negative total relative benefit resulting from the initial network diseconomies. In contrast, those who adopt at a time when the diseconomies have already turned into network economies would profit from the ‘investments’ of the early adopters’’’ (p. 769). While some organizations learn the success of technological innovation through trial and error, other organizations have a policy of adopting and imitating only those innovations that have already proven to be successful. The economic rationale behind this decision is that the adoption of innovation ‘‘will increase a firm’s present value above the pre-innovation level’’ (Jensen, 1983, p. 162). See also Jensen (2001). While it is true that innovations born through trial and error succeed, there are structural, cultural, and power distributions as well as differential factors that hinder adoption and diffusion of innovations, thereby contributing to innovations lag. In the case of an innovation that has positive economic benefits to the organization, there may still be individuals/groups that lose resources, power, etc. These individuals/groups may benefit from and, therefore, prefer the status quote or an alternative innovation.

1.6. ADOPTION–DIFFUSION AND INNOVATION LAG In general, organizational lag refers to the relative differences in the degree by which organizations adopt technical and/or administrative innovations (Damanpour & Evan, 1984, p. 394). There are individual, group, and organizational differences that contribute to innovation lag. While individual factors deal with personality, behavior, and attitudinal constraints, organizational factors are more general and address institutional environmental factors that affect innovations. Divisional structures and arrangements influence the degree and success of innovations in organizations. These characteristics explain whether or not there is an innovation lag in organizations. For example, administrative innovations face organizational constraints. Bureaucratic procedures in operating systems of mechanistic structures and difficulties in establishing cost-benefit linkages in administrative innovations have contributed to innovation lag. Accounting control systems as part of administrative operating systems have experienced innovation lag over the years. However, recent developments in information technology (IT) have contributed to incremental changes in accounting, recording, and reporting of production and quality costs in business and manufacturing organizations.

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In addition to organizational type, divisional structures, work arrangements, as well as individual and group characteristics, all influence innovation behavior and the degree to which innovation can impact organizational performance. Information and communication are considered critical in the dissemination of innovation and in the creation of adoption lag. As noted earlier, some (Jamali 2005) believe that a matrix organizational structure facilitates the adoption of innovations. Rogers (1971) and Rogers and Shoemaker (1971) concluded that the flow of innovation information and technological know-how are important in the diffusion process of innovation. In particular, they stressed the level of contact between originators and adopters, personality characteristics of early adopters, the nature of the flow of information, and the choice of communication channels as key factors which affect the degree and speed of the adoption process. They suggested that the best strategy to accelerate the diffusion process is through the identification and dissemination of innovation by influential early adopters (opinion leaders referred to as ‘‘champions’’). Once they are identified, the next step is to provide them with the support they need to influence others (followers) to imitate them and adopt the innovation. Failure to target influential early adopters and lack of appropriate means of communication could reduce the demand for innovation information, resulting in innovation lag. Because it creates obstacles to adoption, it can be referred to as an adoption lag. In essence, what Rogers and Shoemaker (1971) are suggesting is comparable to the view of Grattet, Jenness, and Curry (1998) who viewed ‘‘diffusion as a process involving the homogenization of cultural practices and policy forms’’ (p. 288). In other words, diffusion involves cultural assimilation and the sharing of norms and values within the population of the targeted organization. If organizations do not have the necessary resources, cultures, and institutional structures, they will not be able to design and implement the adoption and diffusion of process innovations successfully. The lack of homogenization of ideas, views, values, beliefs, norms and, in general, shared culture create innovation lag. Because management control systems influence decisions regarding organizational power distribution, and resources allocation (Sisaye, 1999), they can affect the learning strategies pursued to design and implement process innovations. We develop a theoretical framework integrating theories of adoption–diffusion and organization. We use adoption–diffusion theory to describe the process whereby the innovation is planned and implemented. We use the theory of Argyris (1992), Argyris and Schon (1978, 1996) regarding organizational learning to describe the type of

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learning: single-loop or double-loop, required by the innovation. Finally, we utilize the work of Atwell (1992) and of Schultz (2001) on organizational learning, of Rogers (1971, 1995) and of Sandberg (2007) on adoption and diffusion theories to identify and understand the potential pitfalls faced by management in implementing accounting innovations. We argue that the two types of organizational learning: the SF (singleloop) or the CR (double-loop) approaches have an effect on the modes of adoption and diffusion of process innovation strategies. This is discussed in Chapter 2.

CHAPTER 2 ADOPTION AND DIFFUSION OF PROCESS INNOVATIONS IN MANAGEMENT ACCOUNTING SYSTEMS

The adoption and diffusion of process innovation has been applied in a wide variety of contexts in sociology and organizational behavior (Rogers, 1971, 1995; Rogers & Shoemaker, 1971). It has been applied to study the transfer of information technology (IT), the adoption of new innovative practices, and the use of change agents to communicate innovative methods to organization members. In organizational behavior literature, adoption has focused on studying initiation and implementation, while diffusion has elaborated on the dissemination of administrative and technological innovations as part of organizational change and transformation processes. Davenport (1993) extended diffusion analysis to study the successful adoption of new IT by an organization. We have incorporated Davenport’s (1993) process innovation research on the sociology of adoption and diffusion research in process innovations within the management accounting literature. We provide a contingency framework for understanding how adoption and diffusion of process innovations can be utilized to explain the success and/or failures of management accounting innovations. Researchers in organizational sociology, management, and product marketing for a long time have been interested in process innovation and diffusion theories. Recent applications of those theories to management accounting innovations, such as ABC, have generated significant changes in accounting theory and practice (see Anderson, 1995; Anderson & Young, 1999; Argyris & Kaplan, 1994; Gosselin, 1997; Jones & Dugdale, 2002). However, as yet, there is no integrative framework with which to study the process of accounting innovations in organizations. 19

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2.1. APPROACHES TO INNOVATION Researchers in the social sciences have studied the process by which new ideas are adopted (implemented) and how acceptance is generated among those charged with accepting and implementing an innovation. Sociology, in particular, has developed an extensive literature on diffusion analysis which examines how innovations are diffused (see Coleman, Katz, & Menzel, 1966; Leagans & Loomis, 1971; Rogers, 1971; Rogers & Shoemaker, 1971). While many of these studies dealt with the adoption and diffusion of a new product, for example, seed corn or drugs, the same analysis has been applied to process innovations, that is, system and organizational change. Process innovation has been defined as an intentional attempt to bring change and/or new methods of arranging work structures, processes or procedures in organizations, as well as changes in individual and group behaviors and roles (Damanpour, 1987; West & Farr, 1989). Organizations adopt process innovations for different reasons. Typically the reasons focus on the need to maintain or improve the performance of the organization or a sub-unit and/or to respond to changes in the organization’s external environment. Process innovation can be a discrete response to a particular change in the competitive environment or it can be ongoing, that is, evolving over a period of time, because of either internal or external change. In management accounting, process innovations include the introduction of quality improvement programs and changes in management accounting, reporting, and control systems. It is important to remember that process innovations are usually introduced within existing organizations whose cultures, domains, and boundaries may affect and be affected by the innovation. This can facilitate or inhibit the adoption and implementation of the process innovation. During the last decade of the 20th century, various process innovations occurred in business organizations that either involved accounting directly, for example, ABC, or affected the accounting function indirectly, for example, just-in-time technology (JIT), total quality management (TQM), or business process reengineering (BPR). These innovations have met with varying levels of success (Ittner & Larcker, 1998). For obvious reasons the failure of an innovation to be successfully implemented has raised questions. Various reasons have been offered for these failures. One possible explanation suggests the cause of the failure is in the implementation process rather than in the innovation itself. The adoption process was flawed in a way that resulted in the innovation being rejected. As Brunsson (1982) noted, there is a difference between the act of choosing the best course of

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action (decision making) and the process of implementing that course of action (gaining its acceptance). The former typically relies on a form of cost– benefit analysis. The latter is a more political process. It may not always be politically feasible to implement the ‘‘best’’ course of action. Implementation involves coalition formation in support of the innovation (Cyert & March, 1963; Pfeffer, 1992). Thus a successful innovation requires that the opinion leaders championing the innovation have both a desirable innovation and an appropriate plan to gain its acceptance. Only then can they implement and diffuse it. There is an extensive literature in process innovation in sociology, which examines how innovations are adopted and diffused (see Coleman et al., 1966; Leagans & Loomis, 1971; Rogers, 1971; Rogers & Shoemaker, 1971). The adoption of many technological innovations may be limited by the implementation costs, that is, research and development (R&D), or by legal exigencies such as patents and regulatory requirements. Technological innovations usually are driven by demand, and undertaking a particular technological innovation is motivated by profit potential or loss avoidance. Organizational sociology literature suggests that adopters of technical innovations can be divided into two groups: early and late. Early adopters are few in number and usually include organizations that follow a prospector strategy or are industry leaders. These are the organizations whose leaders are willing to take the risks that are associated with the experimentation with new technologies or systems. Once the early adopters have demonstrated the feasibility and desirability of an innovation, many others will follow. Thus, the number of late adopters will vastly outnumber that of early adopters. Researchers describe innovations as being driven by either supply or demand. Demand driven refers to the development of innovations to meet a need/demand already identified by potential adopters. They can be described as individuals/organizations already in search of a solution (innovation). In contrast, supply driven innovations are those where a new innovation leads to the potential adopters to identify a need of which they were previously unaware. Unlike technical innovations that often are demand driven, management accounting innovations are largely driven by supply. The adoption of these innovations is based on their availability from various sources, for example, academics, consulting organizations, and those that perform the necessary R&D to recommend the preliminary adoption of the innovation. Early adopting organizations are either in cooperation with the developer or on their own, have experimented with the new administrative system.

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The need for supply driven innovations is harder to demonstrate than the typical demand driven innovation for which a need already has been identified. Thus, they are potentially riskier. To minimize the possibility of unanticipated adverse consequences from the still untested innovations, the early adoption of these innovations are often undertaken as a two stage process. Initially the organization ‘‘experiments’’ with the innovation in a small segment, for example, a subunit, of the organization. The success of these initial adopters serves to popularize the innovation that results in the second stage: acceptance, implementations, and subsequent dissemination throughout the organization. Should it fail in its initial trial, the organizations (and the advocates of early adoption) have minimized their losses. In sociology literature, these two stages of in the implementation of process innovations are labeled adoption and diffusion. In the subsequent sections we apply a contingency framework to study the sociology of adoption and diffusion of innovations in complex organizations. We use the contingency framework to study these two stages of innovations: adoption and diffusion within management accounting contexts as described in Sisaye and Birnberg (2010b).

2.1.1. Stage 1: Adoption of Innovation There is a hierarchy of innovations in adoption decisions. This hierarchy emanates from the fact that, in adoption, there is a systematic process for the acquisition and synthesis of knowledge. In adoption, cognitive processing, according to Gatingon and Robertson (1985), has a ‘‘hierarchy of effects model’’ because the adoption process represents ‘‘awareness, knowledge, attitude formation, trial, and adoption’’ (p. 854). While cognition is important for individual adopters; the adoption process is different for groups, networks and organizations, in that it goes beyond specific innovations involving social and economic processes within organizations, and, in some instances, reflects local and national changes. In other words, the adoption of an innovation may include not only individuals and groups; it may involve organizations and also nations. Adoption occurs at the national level, when, for example, the adoption of social change includes political reforms affecting regions, states, political parties, or national groups. Wejnert (2002) discussed characteristics of innovations that are specific to adopters. She identified several factors including the adopters’ familiarity

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with the innovation, status and socioeconomic circumstances, relative position and adopter’s personality within the network or group. Wejnert (2002) suggested that organizations or groups ‘‘adopt innovations with many private, environmental consequences (that change the innovators’ environment)’’ (p. 303). Innovations are spread through contact or institutional arrangements where ‘‘firms belonging to the same professional organizations tended to adopt similar management styles’’ (p. 303). Membership in the same association (weak ties) encourages the adoption of generic management styles. Wejnert (2002) suggested that new or novel innovations that are widely popularized via the media, personal contacts, expertise, or networks are perceived as having fewer risks of being adopted. However, in these cases, larger established organizations can generally better able to take risks associated with innovations because of the greater availability of slack resources. The position of the actor advocating/supporting the innovation as well as characteristics related to the actor’s centrality of position within groups, networks, or an organizational network also serve as sources of influence that facilitate the adoption of innovations (Wejnert, 2002, pp. 303–306). Accordingly, when innovations that are promoted by influential opinion leaders, who are accepted within the organization and the community, are diffused and adopted, they can have positive consequences for the adopters. Although, the decision to adopt is voluntary, it can be promoted by others using education and persuasion through a stage-ordered or gradual phase approach. In this context, Dearing (2009) identified the degree to which adoption of readiness or stages of change differ among targeted populations. The innovators are the first to adopt, then, early adopters; late adopters who constitute the majority of the population follow. When innovations are adopted by highly influential opinion leaders accompanied by change agents, the communication of the innovation becomes effective, and thus increases the likelihood of its adoption by others whose evaluation of the innovation is strongly influenced by these opinion leaders. In this setting later adopters imitate those preceding them only after they are convinced that it is in their interest to adopt the innovation. Cultures, social groups, and power structures also influence the diffusion process (pp. 506–509). While most of the literature in process innovations refers to Rogers (1995) for his noted framework in diffusion of innovations, his name has not been associated with the adoption process. Dearing (2009) further elaborated Rogers’ (1995) approaches to include decisions to adopt innovations. Dearing (2009) argued that the adoption process is influenced by factors related to the ‘‘relative advantage,’’ and ‘‘simplicity’’ of the innovation, and

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its ‘‘compatibility’’ with existing individuals, groups, organization norms, and cultures. Characteristics associated with ‘‘observability and trialiability’’ facilitate the adoption process because they make its evaluation easier. In addition, while risks mitigate the decision to adopt, the question of ‘‘profitability’’ or cost–benefit analysis provides an economic rationale for the adoption decision. Accordingly, an experiment to demonstrate the innovation increases its likelihood of acceptance (pp. 509–510. Dearing’s Rogers’ italics). In organization management literature, these adoption characteristics have been associated with technical rather than administrative innovations. Literature regarding the adoption of innovation has largely concentrated on internal characteristics of an organization and on external factors that created the conditions appropriate for adoption decisions. Attewell (1992) specifically expanded Rogers’ (1971) concern for the causes of the diffusion process by focusing on the adopters. He identified four factors that affect the adoption decision of individuals or organizations: firm size, firm profitability, innovation champions, and organizational attributes. The first factor, firm size, suggests that larger firms have greater opportunities to innovate than small firms. The second factor, profitability, indicates that a more profitable firm has greater resources and capabilities to undertake innovations. The third factor, the presence of potential innovation champions, means that there are individuals in the organization who are motivated to persuade others to adopt a particular innovation. The last factor refers to internal and environmental attributes of an organization. These are related to divisional autonomy, degree of functional specialization/expertise, and centralization versus decentralization of the decision-making process regarding adoption (Daft, 1978; Perrow, 1986; Scott, 1987). In general, organizational/divisional bureaucratic structures affect innovation outcomes. In centralized organizations that adopt accounting innovations, the likelihood that these innovations will be successfully implemented is higher than in decentralized and less formal organizations. In decentralized organizations, individuals and/or units have the autonomy and flexibility to slow down or abandon accounting innovation implementation if they feel it is detrimental to their divisional interests (see Ansari & Euske, 1987; Brunsson, 1982). While in accounting decentralization and differentiated structures have a significant impact on the decision whether or not to adopt an innovation, Gosselin (1997) documented a case where a centralized structure was needed to support the successful implementation of ABC’s adoption. We add a fifth and sixth factor to the four factors outlined by Attewell (1992): fifth, the congruence between the innovation prospects and the

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organization’s competitive strategy and environment; sixth, the degree of management’s support for the innovation intended to institute management accounting reporting changes within the organization. 2.1.1.1. Congruency Between the Organization’s Competitive Strategy and Environment The fifth factor addresses the prevalence of competition, and the consistency of the organization’s decision to undertake an innovation with its strategy, for example, sustained efforts to improve the operating efficiency of the organization. According to Barnett and Hansen (1996), the organization’s competition or rival firms often are constraints on the organization’s behavior. They indicate that the nature of an organization’s competition changes when its cohort of rivals that share the same strategic interactions changes. When this occurs, the organization is then ‘‘confronted with new rivals that do not share the organization’s co-evolutionary history’’ (p. 143; see also Barnett & Carroll, 1987). The organization’s new rivals bring new constraints and change the dynamics of its competition. This creates opportunities for organizations to adopt innovation strategies related to organizational development (OD) and/or transformation (OT). Competitive strategy thus becomes a process through which a firm utilizes its resources or competencies to maximize environmental opportunities, while at the same time it minimizes potential threats raised by the environment (Porter, 1980). The interaction between strategy and structure influences the ability of the organization to adapt to environmental changes. According to Lant and Mezias (1992), ‘‘organizations with an adaptive strategy search for information that reveals the relationship between organizational characteristics and performance. That is, they determine which mix of organizational characteristics is associated with the highest performance and adopt those characteristics’’ (p. 55). In other words, performance is dependent on whether or not there exists a close relationship between current environmental changes and the ability of the organization to handle and process these changes (Porter, 1980, 1985). Process innovation strategies that are transformational in scope become the main core competencies for organizations in a high competitive environment. Their successes depend on whether or not they have the ability to sustain continuous change. To remain competitive, for example, manufacturing organizations that follow incremental intervention strategies ‘‘adopt’’ ABC. For example, ABC becomes the appropriate technical innovation approach for cost reduction strategies to attain improved organizational performance (Ittner, Lanen, & Larcker, 2002).

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However, researchers have also examined the potential interaction, that is, the ‘‘fit,’’ between innovation and the organization’s competitive strategy (Baptista, 1999; Butler, 1988; Gort & Will, 1986; Jensen, 1983, 2001; Porter, 1980, 1985; Schroeder, 1990). Thus, a firm that follows a low cost producer (incremental) strategy would be more receptive to ABC or JIT than one that follows a (transformational) strategy that stresses product innovation, as well as R&D. Accordingly, adoptions of technical management accounting innovations follow strategies that are assumed to meet cost-benefit tests (Attewell, 1992; Jensen, 1983, 2001). The adoption of innovations in many private and public organizations has been shaped by cost considerations. For example, Lapsley and Wright (2004) noted that the adoption of innovations in governmental organizations often is the result of budgetary pressures. This has been the case in health care organizations that have been forced to reduce costs in response to declining government levels of reimbursement of health care costs. They reported that adoption of innovations by local authorities and health care centers were in response to central government initiatives and mandates for cost control reform (pp. 361, 370). Strange and Soule (1998) referred to innovations in business management approaches or models as ‘‘cycles of protest and innovation.’’ These innovations bring protest and opposition at different levels by different groups. There are tensions, support, and competition when these ideas are spread throughout the organization. They cited ‘‘cycles of technological and managerial innovation’’ in business organizations pursued by management to transform them. Several strategies, including TQM and reengineering, were advocated by management consultants and agents ‘‘for enhancing quality, speeding innovation, downsizing, and empowering workers. These movements spread from firm to firm, often following a core-periphery pattern (from big manufacturing and high-tech to services to education and government’’ (p. 280). Strange and Soule (1998) noted that because of consultants’ competition and advocacy of different types of quality intervention programs, it has become increasingly hard for organizations to distinguish between TQM and reengineering in choosing the implementation of the quality improvement program that is best suited for the organization. Because of the lack of central organizations, either private or governmental, the diffusion of the best management practices was promoted by consultants, who modified the approach, depending on client organization. As a result, the lack of institutions or infrastructures to support the innovation made the innovation faddish, but lasted temporarily (Strang & Soule, 1998, p, 281).

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2.1.1.2. Organizational Commitment and Management Support (Buy-In) of the Innovation Our sixth factor, which is related to the demand for innovation adoption and implementation, is associated with organizational commitment, that is, top management support of the innovation. Managers can serve as agents of change in adoption of innovation throughout the organization when they champion the innovation. Rogers (1971, 1995) suggests that innovation champions can be most effective as sponsors and opinion leaders if they possess the basic knowledge and understanding of the innovation being championed. Jones, Herschel, and Douglas (2003) highlighted the importance of the champions being well informed about the nature of the innovation by referring to them as ‘‘knowledge champions’’ who are able to diffuse and transfer innovation within the organization effectively. When knowledge champions accept and commit themselves to accounting innovations, they will be best able to actively promote and advance the implementation processes. The study of Chrysler and Safety-Kleen corporations’ implementations of ABC as an activity-based management (ABM) system (Ness & Cucuzza’s, 1995) illustrated the importance of top management’s buy-in of an innovation. The chief operating officer (COO) at Chrysler and a divisional level manager at Safety-Kleen bought into ABC because they had a basic understanding of both the technical and the administrative components of ABC. Although the approaches used by Chrysler and Safety-Kleen differ slightly, both corporations recognized the potential for improved long-term profitability goals by identifying which products to produce and sell and which customers to serve as well. At Chrysler, the COO followed implementation of ABC throughout the organization, while at Safety-Kleen, a middle manager initiated the pilot project at one plant and then used its success to promote acceptance by executives and other plant managers (Ness & Cucuzza, 1995). To generate employee acceptance, the pilot project approach at SafetyKleen allowed managers to drop ABC if they found that its adoption did not improve decision making. This transferred the decision making rights to the managers and permitted them to buy in to the innovation. Within a relatively short time, this experiment convinced managers that ABC was instrumental in reducing costs and in increasing competitiveness and profitability (Ness & Cucuzza, 1995). At Chrysler, the COO was the principal advocate for using ABC to transform and restructure the company by forming ‘‘more flexible, efficient, cross-functional, and process-oriented teams to manage product development and realign distribution by developing closer links and relationships with suppliers and dealers’’

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(p. 130). The successes at both Chrysler and Safety-Kleen reveal that top management acceptance (buy-in) and support are crucial for the adoption of an innovation. They also support Sandberg’s (2007) claim that business performance becomes the main enthusiasm driver (i.e., top management support) for the diffusion of innovations throughout organizations. It is clear then that a critical factor affecting the adoption of an innovation is the congruence of the innovation and the firm’s competitive strategy. Because of increased competition, technological change, and globalization, organizations have emphasized planned intervention and effective implementation of innovations (McAdams, 2005). While many authors have viewed innovations primarily as improvements in the manufacturing technological (internal) process, they have also examined innovation’s role in an organization’s competitive (external) strategy (Schroeder, 1990). As a result, it is widely accepted that an organization can sustain competitive advantage through both imported innovations, for example, improved manufacturing technological processes, and internally generated innovations resulting from the organization’s own R&D of new products and processes (Baptista, 1999; Jensen, 1983, 2001). The degree to which organizations and industries adopt innovations and respond to them in the form of investment in new technologies is affected by several factors including market size, demand for new products and services, number of firms in the industry, and the industry’s life cycle (Butler, 1988; Gort & Will, 1986; Porter, 1980, 1985; Schroeder, 1990). Nevertheless, it is assumed that, in the early stages of an industry life cycle, technological innovations and creative responses to environmental changes are higher than in later stages. While the rate of adoption is lower at the start of the diffusion process, over time, it will gradually spread, in particular as the costs of adopting an innovation decline and the adoption of the innovation by other firms provides better understanding of its potential benefits and risks. In most organizations, changes in administrative and management control systems essentially are directly or indirectly the result of adoption of innovations. Recent developments in management innovations such as JIT, TQM, and BPR have contributed to changes in management accounting systems, notably ABC. Adoption and implementation are multidimensional and are subject to contextual and process factors. Anderson and Young (1999) discussing ABC described contextual factors as internal organizational factors related to individual performance, quality of information system, cost reduction, perceived importance of the unit to the company. The external environmental factors are related to competitive environment and environmental turbulence that influence the ABC implementation process.

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On the contrary, process factors related to top management support, commitment from local management and unions, as well as effective internal communication, influenced the outcome evaluation of ABC, particularly the use of ABC data for cost reduction and process improvements. Thus, it is clear that organizational and contextual factors do influence the diffusion process of innovations throughout the organization. The literature on the adoption of innovation suggests that certain organizations are better able to successfully adopt innovations because they have certain structural attributes that support innovations. Moreover, these organizations have slack resources and are capable of handling the economic and financial risks associated with innovations. They are well positioned to align their resources and competencies to undertake innovations that are consistent with the organization’s competitive strategy to improve their operating efficiencies to produce better products for their customers. They have innovation champions who can sponsor and provide guidance of the implementation of the management accounting innovations throughout the organization.

2.1.2. Stage 2: Diffusion of Innovation According to Rogers (1971, 1995), diffusion (dissemination) of information requires that there be an innovation to spread and a targeted population of potential adopters. Dissemination requires means of communication that the opinion leaders can use to transmit the information to the potential adopters. The likelihood of adoption depends on the potential benefit as perceived by individuals, groups, the organization itself, or the community at large who are potential adopters. While diffusion often is viewed as an individual process, networks play roles in this diffusion process, but this presupposes that, in diffusion, there is a ‘‘spread of abstract ideas and concepts, technical information, and actual practices within a social system’’ (Wejnert, 2002, p. 297). Strang and Soule (1998) and Wejnert (2002) provided a very extensive review of the literature regarding diffusion of innovations. They stress the ubiquitousness of the concept. Strang and Soule (1998) elaborated that ‘‘diffusion refers to the spread of something within a social system. The word ‘spread’ y denote[s] flow or movement from a source to an adopter, paradigmatically via communication and influence y the term ‘practice’ denote[s] the diffusing item, which might be a behavior, strategy, belief, technology, or structure. Diffusion is the most general and abstract term we have for this sort of process, embracing contagion, mimicry, social learning,

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organized dissemination, and other family members. The term ‘diffusion’ y denote[s] increasing incidence.’’ They attributed that ‘‘something diffuses when more and more people do it’’ (p. 266). Moreover, ‘‘diffusion models often treat the adopter as a reflective decision maker’’ (p. 267). In most studies, ‘‘the home territory of diffusion is the innovation. Innovations are novel y Innovations are also culturally understood as progressive, strengthening the hand of change agents. And since innovations are risky and uncertain, adopters carefully weigh the experience of others before acting’’ (p. 267). Accordingly, ‘‘diffusion studies thus generally investigate the introduction and adoption of an innovation’’ (p. 267). Diffusion focuses on ‘‘communication processes and channels, tracing the role of the mass media, professional change agents, and interpersonal interaction within the adopting community y Internally, the adoption of new practices requires the active efforts of innovation champions and a robust coalition for change’’ (p. 270). Mass media, networks, and personal interactions all assist in the diffusion and dissemination processes. If there are change agents who are educated and respected, they can play important roles in interpersonal diffusion processes. Macro-organizational diffusion research has considered a wide variety of internal factors such as organization’s environment, cultural behavior and organizational sources as being associated with the successful diffusion of innovations. In addition, external factors including market forces, competition and external environmental conditions influence the introduction and outcome of diffusion. Weinjert (2002) has developed a diffusion framework that integrated internal and external factors as sources that spread diffusion via communication from the source to the adopter. This framework has three components: characteristics of innovations, innovators, and environment context (Weinjert, 2002, pp. 298–299). The first factor, characteristics of innovations, centers on two internal dimensions of the measurement aspects of the innovation: public vs. private consequences, and benefits versus cost of innovations. Public consequences address innovations at national or state levels. By contrast, private consequences are limited to specific adopter, that is, groups or collective entities, such as organizations (p. 299). For example, in management accounting, an innovation’s consequences will be at the organization level – unit/divisions or organization-wide. The second set of internal factors are those in which innovators address technical or management styles that are administrative in nature; that is, where the spread of these innovations ‘‘occurs largely due to spatial and temporal contiguity between a source of a new practice and potential adopter. Two effects are particularly substantial here: a) spatial effects such as geographic

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proximity, interpersonal communication, institutional or individual coercion, and b) the pressure of social networks’’ (Wejnert, 2002, p. 300). In the last analysis, innovations are adopted when the benefits are greater than the costs based on cost–benefit analysis. The third external factor, according to Wejnert (2002), is related to the success of diffusion of innovations and depends on the suitability of environmental contexts. ‘‘Environment context variables fall into at least four subgroups: a) geographic settings, b) societal culture, c) political conditions, and d) globalization and uniformity’’ (p. 310). She has suggested that the effect of environmental contexts depended on whether or not the diffusion of innovations has private and/or public consequences. While geographical settings are relevant for private [consequences], the other three environmental contexts affect both private and public consequences within the context of ‘‘micro- and macro-level actors’’ (p. 310). Geographical location, that is, proximity, promotes faster spread of the innovation and earlier acceptance by adopters. A societal culture with shared belief systems of values and norms, as well as religion and ideology, influences the adoption of innovations. Socialization of the innovation to the culture involves the adaptation of new practices or policies with regard to organizational innovations encourage competition and promote adoption. As for political conditions, legislative policies and/or regulatory forces can influence innovations, for example, patents (Wejnert, 2002, pp. 311–313). Thus, diffusion is contextual dependent and occurs within a specified set of environmental contexts. Gattington and Robertson (1985) noted that ‘‘diffusion occurs within the boundaries of the social system or market segment. The diffusion pattern at the social system level is an outcome of the distribution of individual adoption decisions. These individual adoption decisions are influenced by personal characteristics, perceived innovation characteristics, personal influence, and marketing and competitive action’’ (p. 850). Accordingly, diffusion ‘‘occurs within a social system that possesses a set of values and norms’’ (p. 857). Consequently, the extent of the dissemination of the innovation depends on its fit or compatibility with organizational and employees values and norms (p. 857). In this context, the size of the population within the social system is dependent on the definition of those potential adopters, for example, percentage of women in the labor force as opposed to all women. Within this context, again, in the area of marketing, economic and legal considerations affect the extent of the marketing system for the diffusion model. System heterogeneity decreases the speed of the diffusion whereas system homogeneity facilitates the process (Gatingon & Robertson, 1985, p. 858).

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Gatingon and Robertson (1985) noted that, in general, ‘‘the diffusion process can be characterized in terms of three dimensions: the rate of diffusion, the pattern of diffusion, and the potential penetration level’’ (p. 858). That is, rate is related to the speed, the ‘‘pattern concerns the shape of the diffusion curve’’ which has ‘‘decreasing returns’’ with an ‘‘S-shaped’’ curve. Penetration is thus dependent on the size of the market. They argued that, in a market where there are similar brands, intense competition exists for market penetration which increases the rate of diffusion for the product. When there are new products that are not tested, diffusion is slower because of the ‘‘increased risk of making an early decision, purchase is postponed and the diffusion process slows’’ (p. 860). In general, when new products are developed and marketed, the perceived innovation characteristics and their relationship and compatibility to a firm’s market, ‘‘product/company fit,’’ strategy, or culture, affects their speed of diffusion within a social system (p. 861). There are numerous studies in the social science disciplines that have applied diffusion theory and research: sociology, organizational behavior, and marketing among others. Diffusion studies are largely based on the domain of research of specific disciplines. We have applied organizational sociological approaches of diffusion research and their relationships to management accounting and innovations systems. Within sociological approach, we have focused on macro-level factors as our unit of analysis: groups, teams, divisions/units and/or organizations at large. Sociologists who have applied diffusion studies in organizational contexts have elaborated Rogers’s (1971), and Rogers and Shoemaker’s (1971) suggestion that the flow of innovation information and technological knowhow is important in the process of innovation diffusion. This flow is facilitated by the level of contact between the originators and adopters of innovation, personality characteristics of early adopters, nature of the information flow, and the choice of communication channels, all of which are key factors that affect the degree and speed of the adoption process. They stressed that the best strategy for accelerating the diffusion process is through identification and involvement of opinion leaders who can be influential early adopters. Opinion leaders are referred to as ‘‘champions’’ when they sponsor innovations. Rogers (1971) and Rogers and Shoemaker (1971) argued that, once a potential innovation has been identified, potential early adopters must be enlisted. The next step is to provide them with the support and information they need to influence others (followers) to adopt the innovation. Therefore, information and communication are critical to the dissemination of innovation and to the length of the time lag between early and late adopters.

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The diffusion stage of management accounting innovations has been described by management accounting researchers, most notably in the case of ABC (Gosselin, 1997; Malmi, 1999). The work of Howell and Higgins (1990) on the role of champions in the diffusion of adoption can be applied to Jones and Dugdale’s (2002) description of actors (in other words, champions) and networks that aid the diffusion of ABC. As Jones and Dugdale (2002) noted, the ABC diffusion process was facilitated by the prominent status of the actors who advocated (championed) ABC as an accounting innovation, as well as by the support ABC received from individual and institutional networks within academia, industry, consulting firms, and textbook publishers. They argued that early adopters of ABC were well-established organizations that advocated its utility in the media and provided the impetus for its dissemination to other, potential adopters. The use of ABC was rationalized by means of pilot tests and experimentation. Jones and Dugdale (2002) described ABC’s development as a sociotechnical expert system embedded in the management of innovations in organizations. As ABC was translated from a local accounting procedure to a global accounting practice, it was accepted as an expert accounting system, that is, ‘‘a better mousetrap.’’ The ABC bandwagon became synonymous with modern management and innovation and was widely accepted in both the United States and Europe (see also Malmi, 1999). It can be inferred that the initial stage of ABC dissemination was facilitated by the centrality of ABC networks, that is, the early adopting organizations. ABC’s proximity and access to ‘‘suppliers,’’ that is, academics and management consultants, legitimized and institutionalized its position in both accounting theory and practice to the point where the ABC bandwagon was accepted as a panacea for managing uncertainty in modern organizations (Jones & Dugdale, 2002). In addition to contextual and process factors, organizational learning strategies: both single- and double-loop affect the management and implementation contexts of ABC.

2.2. ORGANIZATIONAL LEARNING: SINGLE- AND DOUBLE-LOOP LEARNING WITHIN THE CONTEXT OF MANAGEMENT ACCOUNTING INNOVATIONS When an organization introduces an innovation, the consequence of that innovation will be affected by the learning strategy that the organization has adopted. This choice, in turn, will influence the magnitude of the organization’s

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change as well as its extent and scope. When a process innovation is supported by organizational learning, it facilitates the adoption and diffusion processes. Stata (1989) viewed organizational learning as a competitive advantage for those organizations able to respond quickly to changes in their institutional environments. ‘‘Organizational learning entails new insights and modified behavior. [It] occurs through shared insights, knowledge, and mental models’’ (p. 64). In other words, organizations cannot effectively utilize a process innovation without a well developed learning strategy that facilitates their ability to respond to change (Lant & Mezias, 1992; Mezias & Glynn, 1993). Argyris and Schon (1978, 1996) have related organizational learning to the process of acquiring new knowledge. They described two types of organizational learning: single-loop and double-loop learning. In general, the organizational behavior literature suggests that organizations have two types of ‘‘innovations.’’ These are incremental (single-loop) and discontinuous (double-loop). Incremental changes are adaptations that occur within an already established/existing system/framework and require limited acquisition of new knowledge, if any, by the adopter. By contrast, discontinuous changes occur when the organization adopts a new system/ framework to improve its performance. Responding to discontinuous changes requires significant changes in the organization’s activities and, consequently, the acquisition of entirely new knowledge. While the focus of this book is on discontinuous change in the environment (double-loop learning) and the link between innovation and organizational learning, we use both single- and double-loop learning in our process innovation framework in the context of management accounting systems.

2.2.1. Single-Loop Learning and Management Accounting Innovations Single-loop learning is used to describe those accretions in an organization’s knowledge that are intended to find better ways (i.e., new knowledge) of doing things the organization is doing already (Argyris, 1992; Argyris & Schon, 1978). The objective of single-loop learning is to identify and implement new methods designed to improve organizational performance within existing systems. As a result, single-loop-based changes are gradual and occur in small increments. The learning process over time leads to a step-by-step accumulation of new skills, techniques, and knowledge that have the potential to contribute to the organization’s implementation and use of existing systems. It may be a trial-and-error process. Knowledge is acquired by the organization as the result of the innovation; that is, when

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formal learning occurs, it can lead to modifying or updating existing knowledge and/or mastery of new skills. In general, the objective of single-loop learning is to find new ways and methods to do what we already do better. These goals can be achieved in variously. Some organizations change by trial-and-error; others change by adopting innovations that have been successful elsewhere. The rationale for adopting an innovation in these cases is the cost-benefit analysis. This is the essence of single-loop learning. Single-loop learning is ubiquitous in organizations. Organizations regularly make incremental changes in elements of their management accounting systems as they learn more about their environment, for example, by obtaining better cost estimates of variables already included in a costing system or by adding a dimension to the control system that does not necessarily alter the system. Such changes are, in a relative sense, decorative and have limited impact on that portion of the organization affected by the change. When incremental changes are observable and successful at the unit level, however, they have the potential to be adopted by (diffused to) other units and divisions within the organization.

2.2.2. Double-Loop Learning and Management Accounting Innovations Double-loop learning is second-order learning that leads to reorientation of values and transformational changes by the organization (Lant & Mezias, 1992). It is associated with the presence of a discontinuous change in the organization’s environment (Bessant, 2005) and with the development of new paradigms for doing things differently than in the past by means of new approaches or ways of doing things. Double-loop learning occurs when an organization is able to ‘‘detect and correct errors in the operating norms’’ and activities of the organization (Van de Ven, 1986, p. 603). Double-loop learning allows/requires an organization to institute new norms and procedures to transform organizational activities. Unlike single-loop learning, double-loop learning involves radical changes that require the acquisition of significant amounts of new knowledge and greater effort on the part of the organization. This involves identifying problems that impact the organization and/or potential changes in the organization’s systems, which will be of benefit to the organization, presenting these problems to the appropriate segment of the organization, convincing it of the efficacy of the innovation and, ultimately, managing the innovation’s implementation. Thus, double-loop learning significantly

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modifies existing operating activities in such a way that the organization must change existing procedures, rules, and modes of operating activities accordingly and replace them with new and fundamentally different methods of conducting business. In accounting, double-loop learning occurs when an organization has instituted or adopted integrated management control systems, for example, the adoption of BSC as described by Kaplan and Norton (2001). The Argyris (1992) and Argyris and Schon (1978) classification of doubleloop learning parallel radical-transformational learning. Radical change involves transformation of the organization’s existing mission, strategy, policies, culture, leadership, and structural arrangements. It requires employees to adopt new cultures and approaches to the work environment that may be antithetical to previous behaviors. Sandberg (2007) noted that radical innovations require new behaviors that foster enthusiasm among its champions and core team members. Because radical innovations create ambiguity and uncertainty in an organization’s members, Sandberg (2007) argues that they require ‘‘champions’’. The champions’ role is to promote change and display commitment to it through courage and persistence. These champions utilize formal and informal networks to communicate the innovations and to sustain enthusiasm for them among employees within the organization. While double-loop learning can be considered to be a continuum, consistent with Sandberg (2007), we describe radical innovations and double-loop learning as dichotomous to reflect the nature of the factors leading to the identification of the need for change. At one extreme, it has an autonomous-division/unit-level orientation. At the other, it is a systemicorganization-wide strategy. That is, the organizational scope of double-loop learning depends on whether it is autonomous (limited/divisional) or systemic (extensive/organization-wide) for process innovations. When innovations in accounting follow double-loop learning strategies, they have both autonomous-technical and systemic-administrative dimensions and are intended to facilitate the implementation of long-term organizational plans and short-term divisional objectives. In management accounting, these processes include a wide variety of administrative systems, for example, organization-wide performance measurement and resource allocation systems, as well as information systems development and change. These innovations are designed to improve internal control and accounting systems, organizational structures, administrative processes, and departmental coordination. Control and motivation systems, including cost and budget systems, are examples of administrative

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innovations in accounting systems that support the operating activities of the organization and impact more than one functional area of the organization. The management accounting literature contains many examples of double-loop learning. Ness and Cucuzza’s (1995) discussion of organizational changes at Chrysler and Safety-Kleen parallel double-loop learning in systemic innovations. The double-loop approach is illustrated when an autonomous ABC system (the innovation) brought about changes in the organizations that were not only technical, but also dramatic improvements in administrative reforms. ABC gradually evolved from a costing system into an activity based management (ABM) system and became a systemic innovation for managing costs, processes, and market strategies. It transformed organizational management systems. For example, Chrysler integrated ABC as a continuous improvement program. To move the focus of ABC from a cost control to a strategic planning system for managing processes and market synergies, it was jointly managed by the Controller and the Vice-President of Continuous Improvement Programs. At Safety-Kleen, the strategic approach substituted regular performance measures based on operating budget standards with ABC-based performance measures targeted on industry benchmarks to reward plant managers for controlling unit costs for materials processed in its plants. In the cases of Chrysler and Safety-Kleen, managers at both organizations followed prospectors’ strategies whereby ABC was integrated into critical business management systems to a greater extent than any of their competitors. Moreover, their managers perceived that the adoption of ABC had strategic and long-term planning implications and that these radical administrative and technical improvements could be achieved through ABM by managing processes and market synergies. Accordingly, their learning processes combined both incremental and radical approaches such as education, persuasion as well as trial-and-error experimentations, which persuaded front-line managers and rank-and-file employees to accept ABC. The Chrysler and Safety-Kleen transitions from ABC to ABM can be considered an example of double-loop learning. Chrysler’s and Safety-Kleen’s experiences demonstrate that organizations can make the transition from ABC to ABM if they adopt the double-loop autonomous and systemic innovation strategies. When innovation involves the autonomous double-loop learning approach, ABC is used as a cost control program to manage divisions/units performances. On the other hand, when innovation evolves from autonomous to systemic double-loop, the shift from ABC to ABM occurs. The systemic double-loop learning

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mode entails the use of ABM to manage both costs and organizational processes related to markets, synergy, and product developments. This transition from ABC to ABM occurs when double-loop learning encompasses both autonomous and systemic innovations. The introduction of a new incentive scheme using non-financial measures such as those described by Banker, Lee, Potter, and Srinivasan (2000), or the introduction of BSC (Kaplan & Norton, 2001), are examples of new management accounting knowledge (adoption) that could lead to radical organizational change, that is, transformational learning (diffusion). Banker, Lee, and Potter (1996) suggested that the initial adoption of an innovation (initiation) may be technical and autonomous, that is, limited in its impact on the organization and its systems. This is related to our first question: why are some innovations adopted? However, ultimately their initial successful adoption by a single unit or only a few units subsequently may result in its being diffused throughout the organization, that is, administrative innovation. For example, the initial adoption of ABC is technical and tends to be autonomous in nature, that is, limited to a division or a unit for which it is most appropriate. The successful adoptionimplementation of ABC in the unit can lead to its diffusion to the other units or divisions of the organization. Such diffusion can be the result of inter-dependent relationships among divisions/units, or simply because of its obvious success. This is related to our second question: why are some innovations more successfully diffused than others? In contrast to innovations that are limited to a single unit or begin by being implemented within a single unit, an innovation that initially affects multiple units may require new sub-systems to support the innovation and to provide inter-unit coordination. For example, implementing an organization-wide ABC system may require more extensive data-gathering and reporting than was previously the case. It will become apparent that planning, coordinating, and designing supporting information subsystems need to be established to ameliorate coordination difficulties among the various units/divisions that have adopted the accounting innovations. An innovation initially may be implemented in multiple units rather than sequentially for various reasons. The units may be sufficiently interdependent that a change in one has implications for all the units. It also may be that the problem the innovation is intended to resolve is sufficiently significant that the organization cannot wait to proceed sequentially. As an example of double-loop learning in management accounting, BSC stresses the user’s need to think beyond the traditional management accounting model and integrate a new dimension(s) within it. The

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introduction of non-financial measures requires a re-orientation in the thinking, that is, double-loop learning, by those involved. Davis and Albright (2004) reported the results of a quasi-experimental field study within a single banking organization. Those units which adopted BSC subsequently reported superior performance relative to those that did not. Despite the potential benefits, Speckbacher, Bischof, and Pfeiffer (2003) reported data indicating the difficulty in the implementation of the BSC. The responses of the firms that participated in their survey demonstrated that the evolutionary process required moving from the traditional financial model to a BSC mixed financial and non-financial model, required a longer time frame for the benefits of BSC to be realized. In double-loop learning, autonomous and systemic innovations are the types of management accounting innovation with which researchers and consultants are typically concerned (Gosselin, 1997; Kaplan & Norton, 2001; Rowe et al., 2008). Thus, we are interested in understanding those innovations that make radical changes in the management accounting systems. We have related single and double loop to extent of innovations; single loop as technical and double loop as administrative innovations. As described earlier, we have extended double-loop learning to include scope of innovations, that is, as having an autonomous or systemic focus. We used learning modes, extent, and scope to develop the four types of process innovations. We defined extent as the degree to which the innovation affects the organization’s management accounting systems and members’ behaviors within the organization. We related extent to the two types of learning identified by Argyris and Schon (1978). On the contrary, scope refers to the breadth of an innovation’s impact on a continuum ranging from autonomous innovations that affect a single unit within the organization; and, at the other, by systemic innovations that span multiple/critical units within the organization. These extent and scope dimensions are analyzed in Chapter 3.

CHAPTER 3 THE EXTENT AND SCOPE DIMENSIONS OF PROCESS INNOVATIONS

We have utilized a sociological contingency framework to classify and study the adoption and diffusion of management accounting innovations. Innovations can vary in a portion of the organization and in the degree of change that occurs within a unit/division of the organization involved. Organizational sociology examines these aspects of innovation and label them as extent and scope (Sisaye & Birnberg, 2010a, 2010b). We examine these two dimensions below.

3.1. AN OVERVIEW OF THE DIMENSIONS OF EXTENT AND SCOPE OF INNOVATIONS Sisaye and Birnberg (2010a, 2010b) have described the extent and scope of the innovations dimensions as the degree to which learning has affected the organizational structures and processes of the organization. Within this framework, extent has been defined as the degree to which the innovation affects the organization’s management accounting administrative structures, systems, and behaviors of members or units within the organization. Extent is synonymous with the two types of learning identified by Argyris and Schon (1978) discussed earlier. Thus, the learning in the extent dimension varies from a technical change within an existing system (single loop) to the adoption of an entirely new administrative system (double loop). While this continuum extends from technical changes that affect a single process or task to administrative changes that affect organization-wide systems and structures, we will treat them as though they are dichotomous. As indicated 41

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earlier (Chapter 2), extent is associated with two types of learning: single loop (technical change within an existing system, i.e., gradual-incremental) and double loop (the adoption of an entirely new system, i.e., radicaltransformational) (Argyris & Schon, 1978, 1996). Thus, extent can be viewed as a continuum reflecting the degree to which the organization’s system has been changed. It is anchored at one end by small, incremental changes that improve or update existing systems. It is anchored at the other by the replacement of an existing system with one that is new and totally different from the prior system. As the extent of the innovation increases, the relationship between the old system and the new system becomes less and less apparent and the extent of the changes becomes greater and greater. However, the nature of the learning process, which we have labeled extent, does not completely describe the impact of an innovation on the organization. It is readily apparent that innovations also vary in the portion of the organization that is affected. The magnitude of innovation dimensionsubunit(s) or organization-wide has been referred as scope in organizational sociology. The greater the portion of the organization affected by the change, the greater the innovations scope. Thus, we use scope to refer to the breadth of an innovation’s impact, and it is defined as the ubiquitousness of innovation within the organization. Because it is related to the portion of the organization affected by the innovation, it addresses the question of how many units within the organization are affected by or that adopt the innovation. Thus, scope can be viewed as referring to the degree to which the innovation is integrated into the core activities of the organization. Scope can also be viewed as a continuum, anchored at one end by autonomous or self-contained innovations that affect a few individuals or a single unit within the organization; and, at the other, by systemic innovations that span multiple/critical units within the organization. Thus, we will treat the scope dimension as if it also is dichotomous. In combination, the extent and scope of the innovation describe the manner in which learning affects the structures and processes/activities of the organization.

3.1.1. Extent of Innovation Dimension: Technical and Administrative 3.1.1.1. Technical Innovation Technical innovations are the most limited changes that can occur. They affect a small portion of the organization’s systems and sub-units and lead

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to relatively small, that is, incremental, change in the way the organization performs an activity. Technical innovations alter the way products and services are produced and delivered by introducing new means of production or techniques that change the way work is performed (Damanpour, 1987). Technological innovations typically are observable, tangible and trial-able. Because of these characteristics their economic impact on the organization is likely to be measurable. Because the knowledge required to affect the change is incremental, it is as likely to originate from internal sources, that is, intra-organizational innovation, as from external sources. Many modified or new measurement and reporting techniques in management accounting fit into the technical category, for example, changing the basis for cost allocation within a unit or computerizing an existing activity. Because the changes caused by the innovation are readily visible to members of the organization, users’ perceptions of the benefits and costs related to the innovation can be identified and associated with the adoption or discontinuance of innovations (Hekkert, Suurs, Negro, Kuhlmann, & Smits, 2007; Riemer-Reiss, 1999). Although a technical innovation can be imposed from above, it is essentially a bottom-up strategy for managing change in organizations (Damanpour, 1987; Damanpour & Evan, 1984). The knowledge that facilitates the organization’s learning is as likely to be generated internally as externally. Regardless of the source, it is likely in most cases to be introduced at departmental and divisional levels by technical experts and specialists, including accountants, who are front line managers (champions/ advocates) who initiate and implement the innovation process. When technical innovations are targeted for specific administrative changes, for example, changes in accounting reporting systems, they can be imposed from above by central management. However, they tend to follow a bottom-up strategy in organizations for managing change in technical innovations (Damanpour, 1987; Damanpour & Evan, 1984). Technical innovations are mainly incremental. Incremental changes involve minor adjustments in the design of the management accounting and reporting system. The use of computers to allocate costs is an example of such a change. Process innovation, the basis of competition for many business organizations, is also an example of incremental change, but its focus is on TQM’s strategy of ‘‘driving down costs, and adding features’’ (Tushman & O’Reilly III, 1996, p. 10). Market and economic structures, for example, a knowledge-based economy, and a well-endowed human capital facilitate the success of process innovation (Gloet & Terziovski, 2004). When technological changes are revolutionary, the innovation alter the

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basic activities that constitute technology cycle combinations initiating downsizing or complete restructuring of the organization, similar to those strategies popularized by BPR (Sisaye, 2001). These two types of change may not be independent. Incremental changes often occur after transformational change as management attempts to fine-tune the outcome of the innovation. Administrative innovations are defined as those changes that occur in the organization’s social/organizational structure as opposed to the technological system of an organization. They involve major changes in the way an organization performs its activities. Thus they are more likely to have a greater effect on individuals and affect a greater portion of the organization. These changes have the potential to shape and, therefore alter, the internal structures of the organization that directly impact people. Administrative innovations also relate to changes in the way the organization is managed, for example, recruitment, resources allocation, or the structure of tasks, authority and rewards (Damanpour & Evan, 1984). All these are important to managers and changes can positively/negatively affect managers and their perception of their situation. Administrative innovations impact directly upon members of the work group, organization, or wider society. Thus, administrative innovation is a top-down change management strategy that impacts directly upon members of the work group, organization, or wider society. In implementing an administrative innovation an organization’s existing social and organizational culture as well as top management’s leadership behaviors and mutually shared vision influence the outcome of the (administrative) innovations (Elenkov, Judge, & Wright, 2005; Pearce & Ensley, 2004). Daft (1978) noted that the success of administrative innovation depends on organizational structural arrangements that support the innovation. Structural arrangements refer to the level and ratio of management groups in the organization’s hierarchy. When an organization is differentiated with several levels of management hierarchy, there is a tendency for more vertical communication and administrative intensity within the organization’s chain of command. Damanpour (1987) argued that administrative intensity, which refers to the level of hierarchy and number of management employees in the organization, is related to high managerial ratio and multi-layered management hierarchy. They suggested that a multilayered management hierarchical structure generally facilitates the adoption of administrative innovation. Because administrative innovations start at the top of the management hierarchy, it is administrative intensity which most affects the adoption process. As the management

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group composition increases, the chances for successful administrative integration and adoption increase (Damanpour, 1987, pp. 679, 682). In other words, in highly centralized organizations, the managers at the top have greater power than in a decentralized organization, and therefore, have greater ability to influence/impose the changes they desire to make or implement. Such administrative innovations tend to have limited impact on organizational transformation (OT) changes because of constraints inherent in the hierarchical structure. In accounting, typical administrative innovations are designed to improve control and auditing systems, organizational structures, administrative processes, and inter-departmental coordination. Control and motivation systems, including cost and budget systems, are examples of administrative innovation of accounting systems that support the operating activities of the organization and impact more than one functional area of management. The introduction of a new incentive scheme such as that described by Banker et al. (2000) or the introduction of the BSC (Kaplan & Norton, 2001) system would be examples of management accounting changes that may be introduced as incremental changes by adding one element of the BSC to a unit’s report, but have the potential ultimately to contribute to radical changes.

3.1.2. The Extent of Technical and Administrative Innovations in Accounting The extent dimension of an innovation is critical for classifying accounting systems changes as either technical or administrative innovations. Technical innovations are a bottom-up strategy, whereas administrative innovations are a top-down strategy for managing change in organizations (Damanpour & Evan, 1984; Gosselin, 1997). This difference reflects the degree of disruption caused by an innovation. Incremental changes within an existing system, for example, altering the basis of cost allocation from labor hours to machine hours, are easily absorbed by a unit. Thus while technical innovations can be initiated or imposed from above, it is essentially a bottom-up change strategy, because, in most cases, departmental and divisional level technical experts and specialists, who primarily are responsible for planning, initiating and implementing the change, are front-line managers who do not occupy upper level managerial positions. In contrast, administrative changes have as their ultimate, if not immediate, goal system changes that will be implemented across multiple

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if not all the organization’s units. As the result, an administrative innovation requires initiation by and the support of upper level management. It is not uncommon for consultants to play a role in the decision to implement or the actual implementation of the innovation. As discussed above, an organization may ‘‘experiment’’ by initiating the innovation in a segment of the organization before deciding whether or not to implement it organization wide (Banker et al., 2000). When used to classify an accounting system innovation, the extent of innovation can be affected by the intended audience as well as any changes required in the resource allocation and budgeting processes. The system change may be technical (incremental) or administrative (radical) depending on the extent to which existing systems are affected and the portion of the organization to which the change is applied. For example, ABC and other costing methods designed for performance evaluation and reward systems could be classified as either technical or administrative depending on the focus of the cost system and level of analysis – unit or organization. In other words, the extent of both technical and administrative innovations is prevalent in management accounting and control systems. The cost system is technical when it is bureaucratic and adaptive when it has administrative dimensions. In addition to the extent dimension, the management accounting typologies are also moderated by the scope dimension, which involves both autonomous and/or systemic innovations.

3.2. SCOPE OF INNOVATION DIMENSION: AUTONOMOUS AND SYSTEMIC Innovation is also defined by the breadth of the change occurring within the organization as the result of the innovation. The scope of a process innovation depends on whether or not the innovation is central to performing the operating activities and functions of the organization. Thus, scope in this context refers to the degree to which the innovation is integrated into the core activities of the unit/organization. The greater the centrality of the innovation, the greater is its scope. We have adopted the two dimensions of Teece (1996) to describe the scope of an innovation: autonomous/standalone versus systemic/integrative innovations. As the terms imply, they are the end points of a continuum describing the scope of any innovation. An autonomous innovation defines those innovations with the narrowest scope. It describes those changes that can

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be introduced without significant changes in other components of the system into which it is introduced. In that sense, it ‘‘stands-alone.’’ By contrast, the introduction of systemic innovation, represents the other end of the continuum, one whose introduction because it is more comprehensive and integrative requires significant modification in other parts of the organization’s systems.

3.2.1. Autonomous Innovations Autonomous innovations are, by definition, very narrow in their impact. They are directed toward a specific function, production system, operating activity or subunit of the organization. They can be implemented at the departmental/divisional level without affecting any other units in the organization. Autonomous innovations typically are limited to technological changes. Their success depends on whether it can be demonstrated that technological innovation contributes to the economic advantage of the adopter. If this is the case, early adopters will have at least a temporary advantage until the successful technological innovation has been diffused to later adopters. For example, a quality control innovation may win more customers, including some of their competitors’ customers to the initial adopter. However, because of the limited nature of these innovations and the relative ease with which the change can be implemented, profits from autonomous innovations can be short-lived as other organizations observe the success of the early adopters and follow their actions. The early adopters are viewed as an ‘‘experiment’’ by the potential later adopters. Conversely, should they fail; the later adopters can observe this and act accordingly. The autonomous change could involve a narrow ‘‘trial’’ limited to improving a certain aspect of the accounting function; for example, cash management. The change could also include a broad far-reaching a paradigm shift in philosophy; for example, redefining the accounting function in relationship to other functions of the organization, or changing the way accounting is integrated into the strategic planning process of the organization. When technological changes in accounting and control systems are viewed in terms of broader changes occurring within the organization, they can represent an ‘‘experiment’’ before the organization decides on whether or not to implement the innovation more broadly. Thus, the organization can strategically plan the way they proceed with an innovation. The accounting changes conducted within a subunit of the organization can create the precondition for system-wide administrative

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innovations. For example, ABC systems have become both integrative and systemic as ABC data is being used not only for cost control in manufacturing production decisions but also in marketing and product development decisions.

3.2.2. Systemic Innovations Systemic innovations typically are integrative because they affect multiple units within the organization. They require inter-departmental interaction and are intended to improve broad areas of organizational activities. Because systemic innovations are intended to improve broad areas of an organization’s activities, they require inter-departmental interaction. Unlike the technological innovations, they involve potentially heterogeneous groups/units and may lead to conflict in the organization because of conflicting goals, values, and interests of the different groups/units. The implementation process, therefore, likely will require coordination of resources and activities and sharing of information across divisions, functional areas, or programs. Without such coordination/cooperation, there can be conflict (e.g., see Rowe et al., 2008). The coordination of resources and activities and sharing of information across divisions, functional areas, or programs necessary for systemic innovations necessitates innovation champions who are capable of promoting boundary-spanning activities needed to disseminate information about the innovation within the organization. Boundary spanners are those individuals who have links with more than one unit and, therefore, are likely to be able to focus on creating organizational linkages among units to promote organizational innovation (Stommes, 2001). For systemic innovations to be realized, it is critical that coordination of resources and programs occur at the highest levels of the affected organizational units. Only individuals at the highest levels may be able to make the necessary changes and share the relevant information. Because systemic innovations span many organizational boundaries, there can be ‘‘losers’’ as well as ‘‘winners.’’ In the case of any innovation, this can lead to resistance to change and coordination difficulties. In this regard, information flows are key factors to minimizing organizational and departmental resistance to innovations and convincing the managers of the affected units that these changes are in the best interest of the managers and the organization (Rowe, Birnberg, & Shields, 2011). A systemic innovation approach, in contrast to an autonomous approach, views accounting innovation as a necessary step for improving total

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organization performance. It also focuses on the inter-dependence between the accounting function and other functions of the organization. Accounting changes as the result of implementing ABC, for example, are linked to overall improvements in organizational performance, including all control processes such as formal controls of budgetary goals, and informal controls based on group norms (accepted behaviors) and team-based performance targets that management uses to measure performance and the achievement of organizational objectives (Sisaye, 2006). Thus, because accounting can play a central role in the resource allocation and/or incentives of other managers, systemic accounting innovations require the management accountants to play the roles of facilitators and change agents in disseminating an accounting innovation throughout the organization. However, if the organization’s existing structures inhibit systemic innovations (e.g., see Rowe et al., 2011), there is a need for innovation champions, who have shared values and the authority to promote boundary-spanning (Stommes, 2001). In this regard, information flows may be important in minimizing organizational and departmental resistance to innovations. As Rowe et al. (2008) demonstrated, the systemic change, in that case, a change in the reporting system, highlighted departmental interdependencies. The reporting system was used to reduce goal conflict and facilitate a strategic change in the organization.

3.2.3. The Scope of Autonomous and Systemic Innovations in Accounting In accounting, autonomous innovations are rooted in the technical view of accounting and internal control, that is, they are intended to enhance the rules and procedural functions of accounting in safeguarding organizational resources and improving subunit performance. Systemic innovations, on the other hand, are intended to include all administrative processes, including accounting, needed to accomplish corporate objectives. In turn, these processes include various organization-wide controls for information systems development and technological change, authorization and reporting, management accounting systems, safeguarding, management supervisory and documentation. The examples of innovations in accounting mentioned above are typically implemented in the initial stage as autonomous. However, if they are successful, they will be implemented throughout the organization, that is, they will become systemic in scope because they affect operating activities throughout the organization. This is because accounting innovations involve

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inter-dependency relationships and affect more than one division; planning, coordination, and the design of supporting information subsystems are required. As such, there are more likely to be coordination difficulties among the various units/divisions which adopt the accounting innovations if the innovation is perceived as requiring more reporting and data gathering than the existing system. Thus, accounting innovations are more likely to meet with resistance by comparison with autonomous innovations that occur in manufacturing and production technologies. The impact of organizational structure (contextual) and process-management communication and related leadership behavioral characteristics on the diffusion of administrative innovations, particularly accounting changes, is significant in performance evaluation and reporting systems.

3.3. MANAGEMENT ACCOUNTING INNOVATIONS TYPOLOGIES A combination of the diffusion and adoption of innovation dimensions, namely extent, that is, technical and administrative innovations, and scope, that is, autonomous and systemic, yields four types of management accounting innovation typologies: mechanistic (cell 1), organic (cell 2), organizational development (OD) (cell 3) and OT (cell 4) as described in Table 1 (see Introduction, p. xv). Although we describe the four innovation typologies shown in Table 1, we argue that the OD and OT innovation typologies are the two predominantly approaches that are commonly associated with the types of management accounting innovations with which researchers and consultants are concerned (Gosselin, 1997; Kaplan & Norton, 2001; Rowe et al., 2008). We describe mechanistic and organic innovations in Chapter 4 to show that these two innovations in one form or another are incorporated in both OD (as mechanistic/technical innovation limited to a unit/division), and OT (as encompassing organic-administrative innovations that have organization-wide implications). Accordingly, these four types of innovation are discussed in the next two subsequent chapters. Chapter 4 deals with mechanistic and organic innovations, and Chapter 5 discusses OD and OT innovations.

CHAPTER 4 MECHANISTIC AND ORGANIC INNOVATIONS

This chapter describes the differences between mechanistic and organic innovations. Burns and Stalker (1961) have applied the mechanistic and organic typologies to describe organizational structures. Yeo (2007) has noted the importance of structures in organizational learning and suggested that, when organizational learning occurs, structures adapt themselves in response to changes to the environment (p. 543). We argue that the degrees to which organizations or units adopt either mechanistic or organic innovations vary according to organizational structures and therefore influence management accounting innovation typologies. We suggest that, when organizational structures and contextual factors are combined to affect management accounting innovations the SF assumptions of organizational sociology identify two types of organizational structures, namely, mechanistic, and organic, which have been assumed to affect innovations in organizations in different ways (Burns & Stalker, 1961). These structures, mechanistic-centralized and organicdecentralized, affect the extent to which an organization can adopt and successfully implement process innovations at the unit or organization level. Both the mechanistic-centralized and the organic-decentralized structures are associated with and are commonly used to describe technical innovations. However, they vary in the scope, that is, their autonomous or systemic innovations dimensions. When innovations have autonomous scope, that is, stand-alone innovations, they are described as mechanistic. When they exhibit systemic scope, that is, integrative, they are associated with organic innovations. It should be noted that accounting innovations go beyond individual organizational members learning to adapt to innovation changes. Rather, as with any innovation, innovations in management accounting systems are related to the propensity of an organization to undertake them. This propensity can be affected by the organization’s .

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strategy and structures (Gosselin, 1997). Thus, the ability of organizations to undertake management accounting innovations is primarily related to structural factors. Mechanistic innovations (cell 1) are commonly associated with centralized structures and corporate/headquarter focus. On the contrary, organic innovations (cell 2) are prevalent in decentralized structures with divisional autonomy and in unit/departmental orientation.

4.1. SF MECHANIST APPROACHES The mechanistic-organic assumptions of SF address those organizational factors related to structural arrangements, contextual factors, job-task work activities, and human resources management policies. Organizations adopt structures and procedures in search of legitimacy and institutionalization (Riebero & Scapens, 2006, p. 96). Structures manifest themselves in centralized (mechanistic) and/or decentralized (organic) forms. These structures can be loose or tightly controlled; they can involve independent or interdependent tasks. These conditions have a direct impact on the operation of management information and control systems that will, in turn, impact organizational learning and process innovations, which, ultimately, affects organizational performance.

4.1.1. Organizational Structural Arrangements The size, work structure, and task complexity of an organization determines the form and structural arrangements of that organization. Burns and Stalker (1961) defined the two types of organizational structures as described below: Mechanistic structures are large in size. They process non-complex, routine, and repetitive large-scale tasks that do not require specialized technical experts to handle work assignments. They exhibit hierarchical differentiation with several chain-of-command levels. Power is concentrated in top management that leads to centralized decision making. Mechanistic organizations are characterized by formalization, differentiation, and several layers of management hierarchy. When there are largescale, non-complex tasks, many employees are required to handle these tasks. There is the need for vertical and horizontal hierarchical arrangements as well as task differentiation to process the workflow. Differentiation

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minimizes frequency of contact and exchange of information among units. As these hierarchies separate workflow, face-to-face communication becomes difficult (Hull & Hage, 1982, p. 572). All these characteristics of the organization’s work arrangements and control systems can have inhibit process innovation and innovative behavior. Organic structures, on the contrary, are usually small or medium in size. They usually are associated with organizations performing complex tasks, which require specialists, and handle a relatively small amount of work. They have flexible organizational arrangements that are amenable and are more readily adaptable to changes in their institutional environments than mechanistic organizations. When the administrative structure exhibits decentralized structures, there is less differentiation with limited chain-ofcommand, and minimal bureaucratic features. Ozsomer, Calantone, and Benedetto (1997) noted that organizations that have ‘‘flexible structures facilitate the development and implementation of new ideas’’ (p. 401). As compared to centralized rigid structures, organizations with decentralized-flexible structures support innovations because their structures facilitate open communication, and less formal decisionmaking processes that help accelerate innovations. It also permits managers in individual units to undertake changes that later may be adopted by other units in the organization. The team approach to decision making is more appropriate to and consistent with divisionalized (organic) rather than centralized (mechanistic) organizations because of their decentralized and matrix structures (Sisaye, 2006). The existence of a matrix structure encourages and supports the formation of teams and team decision-making processes through lateral structures and communication channels. In such structural arrangements, the team-based approach reduces the association of decisions with specific individuals, rather identifying the group as a whole with the decisionmaking process. Morrill (1991), in a study of the executive decision-making process, noted that ‘‘matrix systems promote the syndication of risk by entire executive corps as groups of high-level managers embedded in complex authority relations are responsible for decision-making rather than individual managers. In such a structure, it is difficult to trace decisions to any one manager; most decisions must be traced to some group process within or between product teams or departments’’ (pp. 871–893). Accordingly, the team decision-making process ultimately is a joint responsibility of all members of the group, whereby each individual collectively shares the success or the failure associated with team decisions and the risk to any one individual for the decision is diminished.

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4.1.2. Contextual Job-Related Tasks Issues Organizational tasks/jobs can be either simple or complex when they involve coordination of functions that is interdependent among several departments or units. Tasks in centralized structures are relatively simple and mechanistic. However, in matrix and organic systems with decentralized structures, tasks can be relatively complex and interdependent, requiring a highly skilled labor force, experienced management, and autonomous cross-functional teams. As would be expected, the important issues differ between the two situations. Zetka, Jr. (1998) noted that decentralized organizations with coordinating work structures have interdependent tasks where efficiency, rationality of production processes, and cost control give rise for the need for units to work together. This can result in the formation of teams composed of representatives of different units/work groups/etc. In this situation there always is the possibility that a dominant actor may arise who can strongly influence the team and the team’s actions. This can occur when production techniques require pooled interdependence, where task performances are segmented from one another, and when the tasks performed by segments are relatively simple and task coordination occurs in a face-to-face interaction. This structure is prevalent in traditional (e.g., mechanistic type) manufacturing organizations where bureaucratic (accounting control) or simple personal control prevails. The operation of this team structure corroborates Ezzamel and Wilmott’s (1998) description of coercive accounting control systems. As Zetka, Jr. (1998) described, when the technological process includes tasks that require collective or group-based coordination skills, it is necessary to restructure those task units so that processing of complex information is available on a timely basis for the groups to coordinate their actions collectively (see also Perrow, 1986; Thompson, 1967). Accordingly, complex task structures in this setting require the development of mature groups that are synergetic. Complex organizations have organic work structures that are interdependent and require work teams to coordinate complex tasks. Tasks that are interdependent are complex; consequently, managing transaction costs among these functions becomes critical in management control (Williamson, 1975, 1987). Accordingly, work task-related contingencies influence the type of control system, namely, either command-control or participative, that will be predominantly utilized by the team to accomplish organizational innovations.

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4.1.3. Structure and the Control of Information Flow The form of the organizational structure, that is, whether highly or loosely controlled, the form of the control system and the flow and accuracy of information, has an effect on the innovation strategies, mechanistic or organic, adopted by the organization. When the organization is highly structured and mechanistic, it gives rise to what Ezzamel and Wilmott (1998) described as group-based power control or what Etzioni (1961) referred to as coercive control system. Under this control system, a dominant actor or coalition would centralize the accounting information system and centralize the coordination and flow of information. The centralization of control systems has been accelerated by recent advances in information technology, which has contributed to increased management demand for accounting information for strategic planning purposes. The tendency is to centralize mechanistic structures with command/ coercive control mechanisms because of the desire to control the utilization of the outputs of the information system. It is worth noting that, with advances in information technology, the use of accounting information has expanded beyond the traditional mechanistic management control function. Thus in these contexts, the SF approach has focused on supporting the functional maintenance of the social system, that is, the power of the dominant individual or group. To enhance their legitimacy and maintain their power, the dominant individual or group adopts an incremental innovation process. These innovations tend to be autonomous or stand-alone innovations. This is because innovations of this type lead to a minimum amount of change in and disruption of the organization, thereby minimizing the likelihood of an opportunity for a change in the power structure.

4.1.4. Functionalism and Differentiation Specialization and differentiation increases the size and complexity of the organizations. In addition, organizations tend to grow over time and as the result they tend to become more complex. This complexity creates a need for the organization to divide into more independent sub-units or departments (Boeker, 1989). This suggests that there will be a significant need for the formation of cross-functional work teams. Historically technological innovations and developments have transformed organizations from the unitary (U-form) or functional to the multiple (M-form) or divisional structures. Through mergers and acquisitions, M-form

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conglomerate organizational structures have emerged. The internal structures of (M-form) divisionalized organizations are highly differentiated, bureaucratized, formalized, and less democratic. Managers in these structures seek to solidify their power through coercive mechanisms by controlling the decisionmaking process for resource allocation decisions. They develop several levels of hierarchy to solidify their control over employees, work teams, consumers, and suppliers. The corporation has thus become a dominant institution where human behavior and character is shaped by means of an external reinforcement of values and beliefs that support and promote management actions (Dugger, 1988, p. 101). These external values are internalized by employees to become part of the corporate culture that supports organizational activities including the stressing of the need for improved organizational performance. As Dugger (1988) argued, the multiple divisionalized form of organizational structure ‘‘has to do with the organization and control of people. The technological revolution is in organization and information rather than in production and distribution y the invention and spread of the new M-form lifted the limit on size; computer technology and communication advances helped lift the old size constraints as well’’ (p. 85). It has been argued that the growth in the size of organizations has been driven by management’s desire for political power and control of economic resources. Economic power provides access to public policy and the ability to shape the laws, rules, regulations and administrative systems promulgated by the government (Galaskiewicz et al., 1985; Jacobs, 1988). As a result, managers have instituted autonomous and divisionalized units in complex organizations to manage the corporation efficiently and effectively. When managers decentralize power, it takes time for coalition group to grow large enough to exercise significant power economically and politically. These decentralized structures directly affect process innovation strategies. Given the centralization of authority/power in U-form organizations, the success of mechanistic innovations in these organizations can be attributed to centralized bureaucratic structures that facilitate the adoption and diffusion of innovations throughout the organization. It is apparent that, as organizations grow in size, internal structures become highly differentiated and bureaucratized, more formalized and less democratic. The decision-making process is politicized and tends to be dominated by a few groups who exercise hierarchical control over resources, employees, consumers, and suppliers. As Vogel (1987) argued, organizations that exercise political power do not follow the democratic principles of power. When there is a divided coalition of interest groups, decisions are

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reached through compromise and negotiated agreements (pp. 63–68). While divisionalized structures are arranged to counter the coordination problem created by organizational size and to manage businesses to maximize profits, the corporate bureaucracy, according to Galbraith (1967), has been transformed into ‘‘techno-structures’’. Corporate management became technocratic rather than bureaucratic by relying on accounting information systems to evaluate performance and to control behavior. Management control systems have reinforced goal congruence through the rewardincentives systems, including coercion. In these settings management typically has institutionalized several accounting systems, including budget targets, profit goals, and performance evaluation systems, to evaluate divisional performance, control management behavior, and develop a commonly shared corporate culture among employees and team members (Sisaye, 1997). As the result, management accounting systems have become avenues for reinforcing goal congruence through incentive systems, including coercion, if necessary, to secure employee and team compliance with organizational rules, procedures and goals. Thus, institutionalization becomes an effective means by which a planned process innovation change program can be incorporated into the organizational culture and team management/control systems (Sisaye, 2001). However, over the long term, bureaucratic rules and formal control systems may be dysfunctional if there are continual turbulent changes and discontinuity in the organizational environment. This calls for innovations that are incremental, that is, mechanistic or organic, to respond to sudden changes in the competitive environment.

4.1.5. Leadership and Crisis Management When there are volatile changes in the external environment, an organization’s choice of leadership to direct the organizational growth and development strategies becomes critical. If these turbulent changes cause an organization’s level of performance to fall below some internally acceptable target or benchmark, for example, the industry average, it can create a crisis within the organization. This can lead to the perception of the need for new leadership and the subsequent formation of work teams to solve the organization’s existing crisis through organizational learning and process innovations. During this transition period from the old to a new ‘‘equilibrium, which is superior from the previous one, it is critical that any changes in the prevailing management control systems align control and

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reporting systems with the likely changing organizational performance goals. In a crisis setting, the role of leadership is critical in the successful adoption and diffusion of any process innovations to align organization learning experiences with changes in organizations’ functions, structures, systems, strategies, and policies. The SF institutional approaches in sociology emphasize the key role of the leader in the early stages, evolution, and gradual adaptation of organizational systems to environment changes. Moreover, management of the crisis stage also depends on the ability of the leadership to institute adaptive organizational system change through a gradual, orderly, and consensual process. While environmental changes generate discontinuity and ‘‘dysfunction’’ in social systems, the institutional approach emphasizes the ability/necessity of leaders to facilitate an orderly adaptation process in social systems (Perrow, 1986). In this regard, Giddens (1987) noted that social actions and structures are influenced by dominant leadership characteristics that shape regular relations of autonomy and dependence in social interactions. These social systems are continually shifting and adapting as leadership resources, skills, roles, positions, and structures change over time. In the process, some systems persist through incremental innovations by adapting to environmental changes, while others must be totally changed. Management in these organizations institutes control system improvements which include changes that range from individually centered to team-based performance and reward systems to facilitate the innovations processes. Accordingly, the formation of cross-functional teams and work groups becomes paramount in the adoption of technological innovations throughout the organization (Sisaye, 2006). Thus, institutionalization becomes an effective process through which a planned change program can be incorporated into the organizational culture and team management control systems. However, over the longer term after the innovation has been implemented and integrated into the organization’s systems, bureaucratic rules and formal control systems may again become institutionalized. This can be dysfunctional for any organization where there are continual turbulent changes and discontinuities in the organization’s environment.

4.1.6. Characteristics of Mechanistic Accounting Systems Mechanistic accounting systems follow bureaucratic-behavior control systems where budget targets and standards are used to evaluate divisional

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performance. When accounting control systems are tight, mechanistic, and follow detailed bureaucratic-behavior evaluation rules and procedures in performance evaluations, they are referred to as restrictive control exchange systems. Managers who subscribe to mechanistic control systems are more likely to exhibit behaviors associated with technocrats who have practices of putting divisional performance goals and interests ahead of overall organizational objectives and interests. These managers may pursue technological advances that benefit their divisions even when such innovations do not contribute to increased profitability of the organization as a whole. To promote goal congruency, it is desirable for corporate management to institute responsibility-based accounting systems to control divisional management’s performance. However, because mechanistic control systems tend to be tight and restrictive, they focus on short-term accounting-based performance indicators. These structures promote immediate profit targets, that is, a short-term horizon, whereby an organization’s performance is managed on a quarterly or annual basis. Accounting bottom-line performance measures have thus advanced the stakeholders external control interests associated with profitability of divisionalized organizations. However, those economic changes that the organization may view as ‘‘crisis’’ have resulted over the years in changes in organizations’ formal control systems. Organizations have downsized to cut costs, pursued mergers, and take-over strategies for growth, instituted reengineering, and new structures to facilitate process innovations that aid its adaptation to its changed environment. These changes coupled with advances in information technology, and customer support through total quality and corporate cultural changes to support environmental management, in turn, all have changed the role of accounting information systems in organizations. In such a turbulent environment, standardized mechanistic accounting control systems will not contribute to improved divisional and corporate performance. If control systems are institutionalized as highly mechanistic and orderly systems, they create an organizational climate that promotes compliance and cooptation. These systems also discourage managers from taking risks for innovative changes. The cost an unsuccessful deviation from organizational norms is likely to be perceived as much higher than the gains to the manager of any successful innovation. While management control systems are necessary for motivation, coordination, and performance evaluation purposes, they can have serious dysfunctional consequences if they are implemented so as to create a restrictive and tightly controlled environment. On the contrary, a loosely structured control system also may not facilitate innovative behavior in the

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absence of an organizational structure and norms that promote autonomy, independence, coordination of activities, team work, and accountability of individual performance. In general, the design and implementation of control systems will be shaped by structural contingency variables such as organizational size, technology, business competitive environment, as well as by internal political processes of management coalition groups and external stakeholders. The interplay of power control and control of accounting systems, combined with the availability of organizational resources, influences the diffusion and adoption of mechanistic innovations processes in organizations (Sisaye, 1997).

4.2. CELL 1: MECHANISTIC INNOVATIONS Mechanistic innovations are more likely to prevail in large manufacturing and production-oriented organizations. Manufacturing organizations have functional structures suited for processing non-complex, routine, and repetitive large-scale tasks that do not require staff with specialized technical expertise. Functional organizations have bureaucratic structures that are hierarchically differentiated with several layers of management hierarchy. Many employees perform large-scale, non-complex tasks. Both vertical and lateral hierarchical arrangements and differentiation are required to process the workflow. Ambrose and Schminke (2003) argued that mechanistic structures have bureaucratic structures that are centralized and have hierarchical, formal rules of control, prescribed orders and regulations, defined job descriptions, as well as defined management–subordinate relationships (Ambrose & Schminke, 2003, p. 295). When an organization puts emphasis on procedural justice related to consistency, accuracy, and standardization, it is considered to be a functional organization. The human, that is, subjective, element is reduced by the decision-making process that focuses on ‘‘formal rules and procedures’’, which increases the illusion of ‘‘perceived organizational support’’ in individual social exchange relationships (Ambrose & Schminke, 2003, p. 297). According to Wejnert (2002), centralized structures are generally effective in organizations that have ‘‘vertical channels of influence. They possess highly centralized, stratified networks use coercive pressure on their members to achieve conformity of practices, causing homogeneity and increasing rates of adoption’’ (Wejnert, 2002, p. 308). In other words, where there are ‘‘vertical and horizontal channels of influence’’, organizational networks can facilitate adoption of information by members by ensuring contact with former

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adoptees and providing advice (Wejnert, 2002, p. 308). Workshops, seminars, and conferences provide educational advice and acceptance of new practices among participants (Wejnert, 2002, pp. 307–309). Thus, mechanistic structures provide stable systems that are suited for transactional leaders who promote institutionalized learning that focuses on gradual and incremental changes. According to Vera and Crossman (2004), there is a tendency for transactional leaders to prefer mechanistic structures that ‘‘are highly centralized, formalized and standardized’’ because they reinforce learning that follows ‘‘current routines’’, which ‘‘enable individuals and groups’’ to learn from their ‘‘experience’’ (p. 232). These leaders will follow systems and procedures to enact incremental change that work through existing bureaucratic structures and systems to implement innovations, learning, and change. In mechanistic structures, single-loop learning has action-oriented change characteristics that are directed toward changing members’ behaviors. Coghlan (2003) attributed this to the fact that the ‘‘mechanistic-oriented action research encompasses traditional action research as expressed in organization development and participatory action research leading to pragmatic outcomes such as the management of change or problem resolution’’ (p. 202). Generally, in mechanistic-oriented action research, learning ‘‘is directed at confronting and resolving a pre-identified issue in managing change or problem solving’’ (p. 453). The change agents work together with members of the organization in identifying the issue, taking the appropriate action and evaluation to appraise the action. The approach focuses on the change agent having the skills for the intervention process. It focuses on the leader or the consultant/agent as the principal actor for the change process (p. 453). Mechanistic-oriented intervention is primarily intended as an ‘‘instrumental approach to achieving planned pragmatic outcomes and generating usable knowledge’’ (Coghlan, 2003, p. 455). The changes focus on improving operational performance whether it is directed to a team or at a problem that needs to be solved to improve performance, for example, resolving communication problems between organization members, and/or clients, etc. The procedure is to collect data, analyze the problem, and take actions by management to resolve them (p. 458). When mechanistic structures prevail, differentiation minimizes both frequency of contact and exchange of information flow. As these hierarchies separate workflow, face-to-face communication becomes difficult (Hull & Hage, 1982, p. 572). Differentiation and specialization eventually contribute to formalized control systems and relationships that create communication barriers and reduce the flow of information, information sharing, coordination,

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and cooperation among organizational units and suppress dissemination of innovation. The decision-making process becomes centralized, with minimal involvement of employees at the lower levels of management. All these make an innovation across units much more difficult. Mechanistic structures support the institutionalization of management control systems featuring increased bureaucratization and the tightening of control of resource-sharing and allocation mechanisms through operational procedural manuals that require documentations, and adherence to operating procedures (Kober, Ng, & Paul, 2007, pp. 446–447). Although these management control structures change to fit management’s strategies, the changes are not likely to be extensive. Rather, they will encompass incremental and procedural changes. Jamali (2005) has attributed this gradual change process to the traditional management model of functional centralized structural systems being driven primarily by rules, prescriptions, efficiency, cost reduction, hierarchical structures, and division of labor to improve production. It is derived from scientific management principles of division of labor, functional management of centrality, stability, planning, organizing and controlling organizational operations, and bureaucratic management of subordination and hierarchical authority. This view assumes that organizations operate in a stable environment where any changes in markets and competitive environments are predictable (p. 105). When mechanistic innovation prevails, management planning and control systems become more formal and institutionalized, formal rules specify procedures and employee roles. Accounting numbers in effect control employee behavior as well as the operating activities of the organization. Accounting and audit tasks are centralized to handle operations and production activities that are routine, repetitive, and programmable (Dirsmith & McAllister, 1982). Management’s reliance on accounting control systems to monitor employee performance restricts the use to which personal feedback can be put and ignores the use of inter-personal relationships in management control systems among managers. Accounting systems support reward allocation systems which encourages individual manager’s compliance with management’s objectives. The accounting systems provide information (‘‘scorecard’’) that assists managers in achieving profitability and income objectives. These systems become instrumental in controlling employee behavior as well as the operating activities of the organization (Sisaye & Birnberg, 2010b). Because traditional mechanistic cost accounting systems are designed to allocate costs, determine product costing, and measure short-term performance, they create structural constraints to the implementation of organization-wide process innovation programs. By contrast, at the departmental level,

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bureaucratic structures play an important role in adoption and diffusion decisions. In centralized and formal organizations, the likelihood that administrative innovations will be implemented is high because the centralized structure found in mechanized organizations provides the support necessary to implement accounting innovations organization-wide. It is not necessarily the case for decentralized structures because management may have the ability to block the innovations if their perception of the innovations are that they are not promoting divisional goals and interests consistent with organization-wide interests. The predominance of a super-ordinate or subordinate relationship in performance evaluation and reward systems reduces coordination among departments and divisions and discourages the instigation of any dissemination of innovation across organizational divisions/departments. In other words, each unit is in a separate hierarchy. This favors standalone innovations, and inhibits the flow of innovation information across units at the same levels but in different hierarchies. These characteristics of mechanistic innovations create structural conditions that can inhibit the introduction of planned intervention and organization-wide innovation programs and prevent the effective participation of employees in process innovations affecting a significant number of the organization’s divisions/units. As a result, the maximum potential benefits from the diffusion of an innovation are not likely to be realized within the organization without changing the scope of the innovation process.

4.3. CELL 2: ORGANIC INNOVATIONS When the extent of innovation is technical, and the scope is systemic, management accounting innovation tends to become organic in orientation. The word ‘‘organic’’ has been used to describe organizational structures that are flexible and adaptable to changes in their institutional environments (Perrow, 1986; Scott, 1987; Young, Houghland, & Shepard, 1981). Organic structures are characterized by complex tasks that require subject matter specialists to handle relatively small tasks. In contrast to the mechanistic structure discussed above, they are characterized by horizontal hierarchies, little differentiation, limited chain of command, minimal bureaucratic features, and decentralized decision-making. All these facilitate the open flow of information and dissemination of innovation across divisions/units and within the organization (Burns & Stalker, 1961). In organic structures, there can be adaptability of rules and regulations, depending on the circumstances. In other words, there is limited rule fixing and observance when the

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environmental contexts call for change (Ambrose & Schminke, 2003, p. 295). There is generally less reliance on rigid formal control systems to monitor employee and organizational performance. According to Vera and Crossman (2004), most organic structures support transformational leaders; individuals who are receptive to change. These leaders prefer organizational structures that are decentralized and can coordinate groups, committees, teams work, and initiatives. Communication is a lateral process and involves coordination and integration. Members work together to accomplish the organization’s vision. Organic structures with adaptable systems are necessary to support strategies that call for the organization to be characterized by continuous change, process innovations, and growth (pp. 232–233). However, the changes undertaken under organic innovations are likely to be more complex than those undertaken by mechanistic organizations. To this effect, Coghlan (2003) has suggested that ‘‘organistic-oriented action research is more complex and subversive because it is guided by a primary aspiration to study the inquiry process and help it transform through increasingly intensive learning in action’’ (p. 452). In organic change, the group serves as the agent of change. It is a group-oriented approach where ‘‘the participants themselves engage in an action inquiry process in which inquiry into their own assumptions and ways of thinking and acting is central to the research problems’’ (p. 452). It allows members to identify and explore those assumptions that govern their behaviors, actions, and values. They question them and become conscious of those behaviors to direct their actions in a goal-oriented direction. The process involves collective reasoning and inquiry where the focus is on learning rather than on practical/immediate outcomes. Coghlan (2003) elaborated that organistic oriented action research is ‘‘guided by a primary aspiration to study the inquiry process and help it transform through increasingly intensive learning in action’’ (p. 455). The process thereby makes members aware of their own assumptions and those of others. During the discussion they can challenge existing assumptions and values and identify those that need to be changed (pp. 459–461). The organic change process of inquiry and dialogue among members is likely to increase employee satisfaction and engagement in work, as opposed to the experience of employees in mechanistic structures. Ambrose and Schminke (2003) attributed these perceptions of employee satisfaction as being dependent on organizational structures. They suggested that organic structures do provide basis for a justice that is based on ‘‘interpersonal transactions’’ which involve face-to-face communication. They referred to them as ‘‘interactional justices’’ and supervisory trust (p. 297). These

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characteristics direct the attitudes and behaviors of employees toward the operation of management control systems. Accounting systems and innovations under organic structures are more likely to promote trust and commitment among employees and, therefore, to support these changes. Within the context of organic innovations, management accounting systems are viewed as ‘‘informative’’. They provide the necessary economic and financial information about the company’s operating activities. By contrast, under mechanistic environment, they are used to control management behavior and company operations (Johnson & Kaplan, 1987). Decentralized structures enable an accounting staff to participate actively in the planning and implementation of programs that will affect their departmental accomplishments. Their full involvement and empowerment to make changes in accounting functions is expected to improve and enhance the quality of work performed in the accounting department. The prevailing assumption is that innovative organizations concentrate on managing their activities instead of managing costs because activity management created sources of competitive value for the organization (Johnson, 1992; see also Jones & Dugdale, 2002). Organic innovative systems encourage the institutionalization of teambased management approaches as substitutes for formal control systems where teams can independently establish their own performance goals (Drake, Haka, & Ravenscroft, 1999). A team-based management control system is inherently rooted in a cognitive approach to managing employees whereby they can use personal, face-to-face communication, flexible feedback, and interpersonal relationships to promote trust, cooperation, collegiality, and coordination among themselves and their respective divisions (Birnberg, 1998). Accordingly, organic systems encourage the dissemination of information and organization-wide process innovations. Whereas the mechanistic approach limits the scope of innovations to the domain of internal control and management accounting, organic changes support innovations that transcend accounting and the internal control function throughout the organization (Sisaye & Birnberg, 2010b).

4.4. EFFECTS OF ORGANIZATIONAL STRUCTURES ON MECHANISTIC AND ORGANIC INNOVATIONS Mechanistic and organic innovations are obtained by maintaining the extent dimension, that is, the type of an innovation, constant at the technical level and varying the scope dimension, that is, the number of divisions/units in

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the organization that are affected by the change, between autonomous (one or very few units) and systemic (many units). Mechanistic innovation (cell 1) is obtained when the extent dimension is technical and the scope is autonomous. On the contrary, organic innovation (cell 2) occurs when the extent is technical and the scope is systemic. When comparing mechanistic versus organic innovation, it is important to examine the effect of organizational structure on the adoption and diffusion of any process innovation in the management accounting systems. In other words, the success of accounting innovation depends on organizational structural arrangements. In decentralized organizations, there are small-scale autonomous units that handle small complex tasks and large-scale divisions that process some simple tasks. Decentralization promotes autonomy in decision-making and empowers managers to make investment decisions that improve the performance of their divisions. This indicates that organization type is not the only factor that affects innovation. The organization management literature suggests that organic type organizations encourage process innovation. For example, Hull and Hage (1982) indicated that the relationship between the size of the organization and its responsiveness to innovation is more applicable to high-technology firms than to other types of organization. They ‘‘argue[d] that the organic model is not the only appropriate model [for innovations]. For example, organizations having mixed structures for performing large scale and complex work can achieve a medium level of innovation’’ (p. 566). This suggests that large-scale organizations with decentralized structures have attributes that support organic innovations. In other words, there is a causal relationship between organizational structures and process innovation strategies. That is, the success of process innovation depends on the type of organizational structure. It has been documented that, while organic structures are best suited for technical innovations, mechanistic structures are more appropriate for administrative innovations (Daft, 1978; Damanpour, 1987; Hull & Hage, 1982). Gosselin (1997) suggested that mechanistic organizations with high management intensity and administrative hierarchy support administrative innovations. They possess both a centralized decision-making process and a concentrated power in top management which facilitate the adoption and diffusion of administrative innovations, including accounting and information system innovations. While a formal control system encourages structured administrative innovation, it cannot support such innovation without promoting changes in its hierarchical structure and chain of command. Because administrative innovations are introduced at organizational levels

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higher than the technical/operational hierarchy, the support of all higher levels of management is essential for administrative innovations to diffuse throughout the organization-at-large. According to Daft (1978), the success of administrative innovation depends on organizational structural arrangements that support innovation. Structural arrangements refer to the level and ratio of management groups in the organizational hierarchy. When there are more levels of management personnel, there is greater management hierarchy and intensity within the organization. Damanpour (1987) argued that administrative intensity, as related to high managerial ratio and multilayered management hierarchy, facilitates the adoption of administrative innovation. Because administrative innovations start at the top of the management hierarchy, administrative intensity affects the adoption process the most. As the management group ratio rises, the chance for successful administrative integration and adoption increases (Damanpour, 1987, pp. 679, 682). Such administrative innovations tend to be limited in scope because of constraints inherent in the hierarchical structure. The successful implementation of administrative innovations requires both behavioral and structural changes. Behavioral change strategies involve the adoption of new attitudes and values by individuals and groups. Attitudinal changes are learned over time and are brought about by cultural training programs. These educational programs involve work-force training, teaching of new cultural work behaviors such as team and cooperative work, and empowerment of workers to make changes. Top management provides leadership, vision, inspiration, support, and commitment to innovation programs. Management ensures that champions who are change agents/ facilitators are in the right place to implement innovation programs. There is an open line of communication with all organization members to solicit their support and commitment for planned programs. Organization members form functional teams that span and cut-across traditional boundaries to gather information, define/develop benchmarks, and implement change programs (Davenport, 1993, pp. 175–183; Stommes, 2001). Chia and Koh (2007) suggested that the successful adoption of administrative innovations in public organizations, for example, in their study of the Singapore government agencies, depended on the adoption of innovations that are influenced by perceived attitudes and cultures regarding the innovation by both organization members as well as management. In the adoption of administrative innovation in particular, both the specialists and the generalists play roles for the success and benefit of the innovation to the organization. The organization culture of management, employees, and the

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flexibility and adaptability of organizational structures influence the success for adoption of administrative innovations. This is particularly applicable to management accounting practices in public organizations. In the case of Singapore, the government adopted an objective statement about providing high quality services at lower costs to improve organizational performance. In essence, the government focused on budget-by-results for public expenditures. These changes were instituted and accomplished by health care organizations within the context of administrative innovations. There are several case studies related to housing projects that have reflected the impact administrative innovations on making the housing organization more responsive to community needs by allowing easy access to housing information. Hennessy (2005) examined four cases of housing authorities that introduced administrative reforms. She argued that administrative innovation makes the system more responsive to community needs through simplified non-bureaucratic structures that that are better able to respond to local needs. The structure is simplified through better information system structures that allow residents to have access to information online for easy reference and uploads to customers (residents) as well as staff (employees). Similarly, Barron (2006) provided examples from four cases of housing commissions/authorities which instituted administrative innovations. She suggested that the administrative structure was simplified where employees were divided into teams to compete. They conducted their own meeting instead of the ‘‘standard leader directed meeting’’ to encourage ‘‘full participation of employees’’ (p. 23). The teams competed in answering questions following the format of the television program ‘‘Jeopardy’’ – referred to as ‘‘housing jeopardy’’. It intensified competition to work together to give correct answers using the Web or other modes – telephone, office visit – of communication. Administrative reforms focused on broader organizational issues related to environment, cultural values, and behavior as well as the history of the organization. Instead of dealing with technical and interpersonal diffusion, these innovations address structural and institutional arrangements. Accordingly, administrative innovations, in general, address ‘‘the spread of behavioral strategies and structures rather than technical innovations, emphasize adoptions by social collectivities, works with a much larger historical and spatial canvas, and incorporates diffusion as one sort of explanation rather than as the overacting framework’’ (Strang & Soule, 1998, p. 268). These social collectives usually include behavioral and cultural changes directed toward administrative innovations.

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When management introduces cultural changes to support administrative innovations, process intervention changes facilitate the development of new behavior patterns to foster interpersonal and inter-group interaction and create improved formal and informal communication linkages within work groups/teams and among individuals at all organizational levels (Sisaye, 2005). According to Van de Ven (1986), ‘‘from a managerial viewpoint, to understand the process of innovation is to understand the factors that facilitate and inhibit the development of innovations. These factors include ideas, people, transactions, and context over time’’ (p. 591). The end result of process changes is to encourage divisions and departments to work together to achieve organizational level objectives (Rowe et al., 2008, 2011). When process innovations are accompanied by cultural changes, they have the desirable effect of motivating employees to participate in achieving departmental and organizational-wide objectives. On the contrary, structural change entails changes in an organization’s divisions/departments and functions, job design, organization of work processes, and performance evaluation systems (Zamutto & O’Connor, 1992). Technological innovations that may benefit the department or the organization as a whole also have resulted in the downsizing and restructuring of organizations. They can also lead to a paradigm shift within the organization. Kuhn (1970) stated that a paradigm shift occurs when there is a major departure from the existing accepted state of theoretical thinking, analysis, and mode of operations. The information technology revolution has led to such a paradigm shift in the way in which management accounting systems are viewed to support both mechanistic and organic innovations. The paradigm shift in accounting has been facilitated by a system (company-wide) rather than a functional (departmental) view of the role of accounting in process innovations. It suggests that a balanced and appropriate mix of strategy is necessary between technical and administrative innovations focusing on the relationship between product inputs (material, labor, capital) and outputs (products, customers, stakeholders). Accordingly, innovation entails a radical level of change. It requires a long-term horizon, a broad cross-functional scope, and a combination of both cultural (behavioral) and structural (organizational) changes. Process innovation uses information technology as the primary enabler of change. Innovation is likely to succeed if there is a top-down strategic vision and orientation to change involving the full participation, cooperation, and acceptance of the change process by employees at all levels of the organization.

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This paradigm shifts in management accounting systems has been aided by the adoption of organizational development (OD) and organizational transformation (OT) process innovations. Compared to mechanistic and organic innovations that focus on technical innovations, OD and OT focus more on administrative innovations that affect the organization’s overall structures, including accounting systems. While OD has an administrative autonomous scope focusing on a division-wide innovation strategy, OT in contrast has a systemic scope and has broader implications for changing the organization at large. Whether organizations adopt either or both the OD and/or OT process innovation strategies, they are implemented to align management control systems with overall improved performance and profitability objectives. The OD and OT administrative innovation strategies for process innovations are discussed in Chapter 5.

CHAPTER 5 ORGANIZATIONAL DEVELOPMENT (OD) AND ORGANIZATIONAL TRANSFORMATION (OT) PROCESS INNOVATION STRATEGIES

This chapter expands Sisaye and Birnberg articles (2010a, 2010b) to discuss organizational development (OD) and organizational transformation (OT) (cells 3 and 4) of the management accounting process innovation framework presented in the 2  2 contingency of Table 1. Compared to mechanistic and organic innovations presented in Chapter 4, OD and OT focus more on administrative innovations that affect the organization’s overall structures, including accounting systems. Administrative innovations have a broader impact than technical innovations that are limited to a single unit or department. They can impact several organizational tasks, including performance evaluation, reporting systems, accounting, and production functions. While both OD and OT reflect the broader administrative innovation strategy compared to mechanistic (cell 1) and organic (cell 2) innovations, they vary along the scope dimensions of the innovation strategy. On the one hand, OD has an autonomous scope. It is a limited approach to the innovation strategy. On the other hand, OT has a systemic scope and has broader implications for changing the organization at large. In general, OD and OT can be classified as dichotomous, or as two forms of organizational change strategies that can be placed on at opposite ends of a continuum. The dichotomy arises from the relative emphasis placed on the scope of innovation. When scope is limited to a single unit or function, it is 71

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Table 1. Typologies of Management Accounting Innovations Based on Extent and Scope of Innovations Dimensions. Scope Technical

Autonomous Cell 1: Mechanistic

Extent Administrative

Cell 3: Organizational Development

Systemic Cell 2: Organic Cell 4: Organizational Transformation

viewed as an autonomous innovation. By contrast, a systemic innovation is one that covers several interdependent or interrelated functions. Another way of describing the difference between them is the OD approach is selfcontained (autonomous), that is, limited to a department/division; whereas, OT has an integrative (systemic) scope that is organization-wide in orientation. However, both OD and OT follow a radical strategy embedded in double-loop learning. They pursue complementary strategies for process innovations. These differences in scope between OD and OT are apparent in their organizational learning strategies. The description of process innovation strategies demonstrates that the unit/ division focused change approach in OD is being classified as double-loop (autonomous) learning and OT as double-loop (systemic) learning strategy embedded in radical (reorientation) organizational learning. In other words, both OD and OT have been classified as double-loop learning with OD having an autonomous learning focus confined to a division and/or unit; whereas, OT has a double-loop systemic focus encompassing integration of learning organization-wide. Both OD and OT reflect administrative innovation strategies instead of the narrowly defined technical processes found in mechanistic and organic changes. Administrative innovations require that units/divisions pursue OD or undertake OT strategy to accomplish a significant organizational change. These changes more than likely reflect the adopter’s perception of a need to change to meet competition.

5.1. CELL 3: ORGANIZATIONAL DEVELOPMENT OD refers to cell 3 of the adoption-diffusion innovation typology defined in Table 1. It has an administrative extent and an autonomous scope. OD has

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been used pre-dominantly in organizational change and sociology literature to describe cultural innovation programs that are directed toward a change in individual employee behavior. In accounting, the OD approach is important because accounting innovations, such as ABC, are directed toward a change in managers’ behavior and the use of accounting data to evaluate performance. The OD approach is applicable in the use of ABC data at the divisional or unit level. Before explaining the application and use of OD in accounting innovations, we will define OD and summarize its innovation approaches as described in organizational sociology and behavior literature.

5.1.1. Organizational Development: Definition Porras and Silvers (1991) described OD as a change program designed to create a better fit between the organization’s capabilities and the demands of its current environment or to promote changes in the organization that help it better fit the future environment it expects to face. OD attempts to achieve this through planned intervention strategy for organizational and societal changes consistent with stability and maintenance of the social system (Sisaye & Stommes, 1985). Recently, the focus of OD has shifted from directly affecting individual and group cognition and behavior to a more indirect process intervention intended to alter behavior through changes in structure of the reward systems (Porras & Silvers, 1991). Because OD is concerned with multiple units, it treats culture as an internal organizational variable. OD interventions focus on the organization’s cultural subsystems to uncover the underlying values, beliefs, norms, and rules prevalent in the organization (Smirch, 1983). This knowledge allows leaders/managers to devise intervention strategies consistent with this culture to make the organization responsive to environmental changes. An innovation that is inconsistent with the culture of the organization at best is very difficult to achieve and is likely to be rejected. The OD approach advocates an SF system view of organizations and change. In this view of organizations, changes in organizational subsystems trigger adaptation of individual behavior consistent with organizational goals. Porras and Hoffer (1986) considered the functional-congruence view of OD as important for organizational change. They proposed that, ‘‘if behavior is influenced by characteristics of an organization’s internal environment – that is, its system elements – then altering the system elements should lead to altering behavior on the job. This, they proposed, is the function of OD interventions’’ (p. 480).

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OD strategy, when properly planned, not only changes employee behavior and improves management’s supervisory skills, but it can also enhance the organizational climate. Organizational climate, in turn, influences labor relations, ‘‘employees’ behavior and organizational performance’’ (Porras et al., 1982, pp. 443, 445). Organizations rely on OD intervention strategies and provide support to champions and experts who can facilitate congruity of employee behavior with organizational goals. Congruencies of behavior occur in those behaviors that are consistent with OD agents’ values, are adaptable to change, and open to new ideas and experiential learning. In all, they are adaptable to organization culture and values.

5.1.2. Organizational Development Process Innovation Strategies The OD intervention strategy is described as a reformist, double-loop, stepby-step, incremental process that focuses on division/unit level interventions. The approach emphasizes the importance of leadership and champions in the change management. As such, OD stresses cultural change and education that focus on changing and re-orienting employee attitudes, behaviors, work habits, and beliefs to facilitate the acceptance of the innovation. The OD approach to change involves a gradual adjustment and is phased-in over time. It emphasizes the importance of employee involvement, participation, consensus building, and, ultimately, the acceptance in the change process by those working in the unit(s). According to Buller and McEvoy (1989), in OD, ‘‘the initial adoption of a planned organizational change is a function of a number of individual, group, and organizational factors. These factors combine to determine the overall level of acceptance and commitment to the change by organization members’’ (p. 35). These factors are supported through training, employee involvement, promotion, and a combination of intrinsic as well as extrinsic rewards (Buller & McEvoy, 1989). The objective of OD is not only the improvement of administrative structures and organizational performance but also fostering the personal growth of employees that is expected to facilitate future innovations and learning.

5.1.3. OD and Double-Loop-Based Autonomous Change/Learning Strategy The OD approach to change advocates a gradual and incremental adjustment of change over time. It emphasizes the importance of consensus,

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participation, acceptance, and employee involvement in the change process. Institutionalization of incremental change is supported through training, employee involvement, promotion, and a combination of career growth and monetary rewards (Buller & McEvoy, 1989, p. 36). These incentives contribute not only to the personal development of organization members but also to the improvement of organizational performance. The OD intervention strategy is described as double-loop, autonomous and unit/division- focused. It places emphasis on leadership as change agents (champions) in the management of process innovations. As such, OD stresses cultural change and education, which focuses on altering employee attitudes, behaviors, work habits, and beliefs. Thus while the number of units/divisions affected is quite small, the changes required of the unit/ division are significant. These are radical changes in the thinking of the participants and thus the double-loop nature of the intervention strategy. The double-loop learning autonomous innovative approach of OD has been imitated and is popular in continuous improvement programs such as TQM. Like OD, TQM is based on the principles of education, training, and organizational learning to sustain continuous improvement and change in organizational performance. TQM follows OD’s intervention strategies of using teamwork, interdivisional cooperation, cultural change, and institutional development in the planning and implementation of successful process innovations (Sisaye, 2001). TQM utilizes OD’s approach of bottom-up participation and the use of change leaders (e.g., quality circles) as successful avenues for planning and implementing production and quality improvement programs. The autonomous double-loop gradual change strategy of TQM is reflected in the changes made in various accounting systems. For example, changes in accounting and internal control systems have a division focus that is primarily incremental, involving procedural and operating changes (Sisaye & Bodnar, 1994). When accounting innovations are viewed as OD intervention strategies, they become administrative tools involving changes in planning, budgeting, internal control, and reporting systems that affect managerial communication and decisionmaking processes. In general, the culture of OD shapes the accounting system and the degree to which planned administrative innovative changes can be designed and implemented in management accounting systems. We suggest that, in accounting, the line between OD autonomous and systemic double-loop learning can be illustrated by the organization’s allocation of overhead. As the allocation of overhead costs is expanded to include several cost pools and drivers to allocate overhead costs, as in ABC, the movement from double-loop autonomous (stand-alone) to systemic

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(integrative) learning becomes clearer. This can be considered to be a radical change when the ABC system not only changes the accounting system from one controlling costs and expenditures in a division (autonomous double loop) to one where ABC is integrated into the financial performance measure and reporting systems and is part of managing processes in the organization (systemic double loop). When organization-wide intervention requires systemic change, it can create coordination problems. Ansari and Euske (1987) report an example of this. Headquarters failed to recognize that a successful implementation of the new system necessitated an institutional environment that led management to accept the change either because of its obvious merit or its support by headquarters. In the defense headquarter and depots (divisions) management control environment which they described, the repair depots were physically removed from headquarters in Washington, DC, and were decentralized operationally as well. Announcing the new system was not sufficient to overcome the resistance to change which, in fact, was not even observable by headquarters. This illustrates that employee resistance to a change/innovation may be present in the adoption and implementation of accounting innovations, particularly in traditional manufacturing organizations. As Ness and Cucuzza (1995) reported, employee resistance was the ‘‘single biggest obstacle for ABC implementation’’ to overcome at Chrysler and Safety-Kleen (p. 130). Introducing changes in an organization can lead to fear and ambiguity among employees regarding job security, and new performance measures can result in opposition and resistance to innovations by the employees. Ness and Cucuzza (1995) revealed that both Chrysler and Safety-Kleen overcame employee resistance through persuasion and education. These two corporations followed a planned OD autonomous change strategy where education about ABC-generated consent and commitment from employees. Seminars and workshops were conducted regularly. At the same time, experimentation with the introduction of ABC at a plant and at division levels facilitated involvement of local and front-line managers in the implementation of ABC.

5.1.4. OD and Administrative Innovation The OD approach to innovation involves both the extent of administrative innovation and the scope of autonomous innovation. As such, it is a popular approach among managers who advocate autonomous changes in

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administrative structures and accounting-reporting systems that tend to have department- or division-focused. To implement an OD-oriented administrative innovation, management pursues not only autonomous double-loop learning but also institution building to make these changes are permanent. The assumption is that, once administrative innovations are successfully implemented and there are cultural changes to support them, these changes support and complement technical innovations. According to Damanpour and Evan (1984), ‘‘an administrative innovation that brings structural changes has more impact in organizational performance than one can expect from technical innovation alone. Administrative innovation supports and facilitates the adoption of technical innovations and improves the organization’s ability for institutional problem solving. Administrative innovations can change an organization’s climate, communication, interdepartmental relations, personnel policies, and so on. In turn, they provide new opportunities for the initiation and adoption of innovations in the technical system’’ (p. 406). Administrative innovation focuses on hierarchical levels that link the organization to its broader environment. Once such institutional environmental issues are addressed, an organization is in a better position to adopt technical innovations. The OD approach to process innovation is autonomous double loop that follows a gradual change strategy that tends to be evolutionary in nature. The strategy has been popular in continuous improvement programs such as TQM (Sisaye, 2001; Sisaye & Bodnar, 1994). TQM is based on the principles of education, training, and organizational learning to sustain continuous improvement and change in organizational performance. TQM uses teamwork, interdivisional cooperation, cultural change, and institutional development in planning and implementing successful process innovations. TQM’s approach of bottom-up participation and the use of change leaders (e.g., quality circles) have been advocated for production and quality improvement programs. Its autonomous double-loop learning and management of change strategy is reflected in various accounting control systems, including ABC. These innovations have a broader focus that tends to be primarily incremental, involving procedural and operating technical information changes (Sisaye, 2005). New measurement and reporting techniques in management accounting could fit into the technical category, for example, changing the basis for cost allocation within a unit or computerizing an existing data collection/analysis activity. Accounting as an administrative tool involves planning, budgeting, internal control, and reporting systems that affect managerial communication and

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decision making. Accordingly, organizational contextual and process factors, including culture, shape the accounting system and the degree to which planned administrative innovative changes in accounting systems can be implemented (Anderson & Young, 1999; Young, 1992). Organizations utilize OD intervention strategy to introduce planned administrative innovation programs. As mentioned earlier (Chapter 2), a popular OD intervention strategy in the 1990s was TQM, which was implemented to develop new operating methods to improve product quality or streamline an administrative system, for example, personnel or accounting. However, unanticipated problems which can affect successful implementation of the innovation program are likely to prevail if these change programs do not involve all members of the organization, including the accounting staff, and if they do not have the full support of management as part of the overall organizational change strategy. Brynjolfsson, Renshaw, and Alstyne (1997) had noted that targeted changes in a single system can be counter-productive. ‘‘It may be that no single isolated change can improve a process, but that a coordinated change can’’ (p. 38). This approach calls for an OT strategy that requires simultaneous change in all organizational systems. In essence, administrative innovations, when systemic and integrative, can facilitate the OT process. Because all systems are inter-related, an OT strategy change in one administrative subsystem affects all other organizational systems.

5.2. CELL 4: ORGANIZATIONAL TRANSFORMATION Organizational transformation refers to cell 4 of the innovation diffusion typology defined in Table 1. OT displays both an administrative extent and a systemic scope. The difference between OD and OT lies along the scope dimension, where OD has an autonomous scope and OT has an integrative or systemic focus. In contrast to OD, OT is present when the change is targeted at altering organizational structures as well as the individual and group members of the organization rather than focusing on accountingrelated systems within a particular unit. In transformative change, new processes are conceptualized and formulated. There are many unknowns and uncertainties. Accordingly, ‘‘transformative change requires the examination and shifting of long-standing assumptions, values, and beliefs. The broader or more transformative the scope of the change, the greater the number of assumptions or values to be changed and the greater the degree of difficulty in effecting change’’

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(Dibella, 2007, p. 237). Transformation requires both attitudinal and behavior changes to accomplish long-term results. Because learning occurs in small incremental and adaptive behavioral changes over time, OT likewise evolves over time from an accumulation of small incremental changes (Romanelli & Tushman, 1994). OT innovations are, as the name suggests, characterized by major strategic changes in the organization’s direction. In other words, OT has a broader focus beyond the cultural change programs of OD that are targeted to changing individual employee behavior at division level (Porras & Silvers, 1991). OT focuses on a broader/integrative scope of comprehensive change in organizational paradigm. It typically is the result of external forces instigating the change. When there are profound external environmental changes or instabilities, they create pressures for organizational adaptations to change. These changes could be associated with radical and revolutionary changes that result in organizational adaptations and transformations (Suarez & Oliva, 2005). Accordingly, OT creates conflict and requires power to overcome them to make these changes constructive. However, conflict gives rise to negotiations, discussions, and, in general, becomes dialectic in turn giving rise to transformation of knowledge and organization activities (Macpherson & Jones, 2008, pp. 177–179). Therefore, managing dialectic change as well as systematic continuity and discontinuity in the presence of power conflict and resistance to change is likely to produce synthesis by shifting the directives of change to the functional contributions of systems that could result in OT (Engestrom, Kerosuo, & Kajamaa, 2007). These changes in OT have been predominantly targeted to changing organizational structures as well as the individual and group members of the organization.

5.2.1. Organizational Transformation: Definition Porras and Silvers (1991) viewed OT as promoting paradigmatic change that helps the organization better to fit into its current environment or to create a more desirable future environment. It focuses on organizational learning and a new vision for the organization (p. 54). The paradigm shift in OT affects the entire behaviors of the whole organization, thereby creating new organizational behavior and giving individual employees a new way of viewing their job (p. 58). Thus, OT intervention leads to both a change in cognition and a commitment to radical change.

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The OT process in organizations involves reciprocal exchange relationships to promote congruency and coherence among various units of the organization. Congruence promotes stability and the alignment of resources to satisfy new requirements for system maintenance brought about by environmental changes (Bacharach, Bamberger, & Sonnenstuhl, 1996, pp. 477–478). Barnett and Carroll (1995) indicated that OT could involve a change in either content or process. When an organization changes its content, it has dramatically altered an element or all parts of its organizational structure, including mission, strategy, authority structure, and technology (see also Hannan & Freeman, 1984). In particular, structural change entails changes in organizations’ divisions/departments and functions, job design, organization of work processes, and performance evaluation systems (Zamutto & O’Connor, 1992). A process change, on the contrary, affects the way the organization operates within its environmental context, the sequence of activities, the decision-making and communication systems, as well as any resistance encountered within the organization. Both contents, including structural and process changes, have become instrumental in bringing about transformational change and development in organizations (Van de Ven & Poole, 1995). In OT, technological innovations such as BPR, when implemented, have made significant structural changes in manufacturing processes – among others, in inventory and production scheduling management, delivery techniques, product design, and quality improvements (Hammer, 1990; Hammer & Champy, 1993). BPR as an OT intervention strategy not only altered organizational systems but also resulted in downsizing and restructuring of organizations. BPR focused on process change within the context of the business of an organization. Accordingly, OT involved several forms of restructuring, including downsizing, outsourcing, divestment or acquisitions as strategies to increase shareholders’ value and wealth in the organization. Thus, accounting knowledge and techniques are developed to pursue the objectives of creating value and wealth to shareholders (Ezzamel, Willmott, & Worthington, 2008). Hauser and Papper (2007) concurred by suggesting that, because BPR is oriented to achieve specific and tangible structural changes, a context-based approach to BPR is constructed to achieve the objective of cost-saving devices and work-load reduction in specific firms and industries, for example, in manufacturing plants, as their study suggested occurred in the automotive industries (p. 686). A study by Herzog, Polajnar, and Tonchia (2007) of Slovenian companies that have experienced and had undergone radical changes documented that

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BPR success in organizations was dependent on top management commitment and proactive engagement in the implementation process. When top management was committed to change, they identified with BPR goals and participated in the formulation of strategies and their implementation (p. 5825). They also noted that educating employees about BPR and the use of teams for learning and adopting those changes was found to enhance the likelihood of BPR’s success. Moreover, information technology support contributed to BPR objectives by providing data (p. 5827). With the advent of new information technology, the implications of BPR’s resizing and work processes configurations are substantial for accounting and internal control, particularly with those repetitive, routine functions dealing with the management of current assets and liabilities (Sisaye, 1996; Sisaye & Bodnar, 1996). Thus, the information technology revolution has brought a paradigm shift in how management views the accounting internal control function as supporting OT innovations. Accordingly, accounting control changes are integrated into the context of structural changes within the organization at large. The new manufacturing environment thus required that the role of management control is to help develop techniques such as ABC to realign accounting methods with performance evaluation systems. Organizations learned from the new technology, where supervisors and employees could cooperatively work together to use accounting information to achieve organizational rather than divisional goals.

5.2.2. OT and Double-Loop Systemic-Based Radical Change Learning Strategy OT accompanies the BPR approach, which follows double-loop systemic learning. Davidson (1993) has suggested that BPR programs focus on business transformation (another term for OT), followed by organizational change. Thus, the philosophy that ‘‘transformation focuses first on business processes and infrastructure, and second on organizational structures and systems’’ prevailed (p. 77). In other words, business activities can be structured to improve performance ‘‘and to then drive organizational change to align with the new business model’’ (Davidson, 1993, p. 77). As an example of the OT approach, BPR is a business transformation strategy that has systemic focus. BPR assumes that organizational innovations encompass structural changes that involve more than improvements in operational performance (Sisaye, 2001). Accordingly, the focus of the transformation systemic process is on the development of core competencies

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and infrastructure to support core business activities in a changing environment. Organizations can build their ‘‘capabilities to introduce enhanced services and value-added processes that in turn can grow into new stand-alone businesses. The transformation philosophy focuses on the latent business growth potential of the core business represents a fundamental shift in management focus’’ (Davidson, 1993, p. 77). The OT approach thus recognizes the utility of open systems approach to institutionalize behavioral and structural strategies of change and the role of leadership to institute transformational changes (Young et al., 1981). Behery (2008) enumerated behavioral characteristics that are commonly associated with transformational leaders. They include behaviors that inspire trust, loyalty, and respect from their followers. These leaders set high standards of performance for their employees. They encourage creativity and productivity within the organization. They focus on long-term goals and motivate organizational members to achieve them (pp. 227–228). Vera and Crossan (2004) also described transformational leaders as exhibiting human relations-oriented behaviors that inspire others with their enthusiasm for the vision of the organizations at large. These leaders are facilitators and innovators. They are effective Chief Operating Officers (COOs) who can build trust and dependability among their co-workers and followers. Transformational leaders also promote change-oriented behaviors through inspiration and motivation. Through their democratic and participatory management styles, they encourage double-loop learning. They portray charismatic leadership qualities that organizational members associate with. They encourage open discussions and forums. They surround themselves with employees of diverse educational and experience backgrounds. They promote learning ‘‘within a context of change.’’ They encourage new ideas, experiments and taking risks for innovations or managing radical changes (Behery, 2008, p. 230). They align and adapt the organizational culture to support learning new ideas or innovations. They exhibit an open-systems approach to inquiry that encourages change by challenging existing norms and institutional behavior. They follow a prospectors’ strategy, that is, a proactive change approach to motivate followers to avoid resistance to change (Behery, 2008, pp. 231–233). OT is a strategic function. Strategic leaders guide the transformational change and learning processes by initiating and directing the overall process of learning. According to Vera and Crossman (2004), these strategic leaders exhibit both transformational and transactional leadership characteristics, depending on the situation and environment with which they are confronted. They can also enhance the team/group learning process through

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encouragement and support, and, if necessary, by challenging those involved (pp. 227–230). Strategic leaders understand that effective leadership is based on transactions exchange that involves merit award based on achieving predefined standards of performance. This involves monitoring employees’ behavior and suggesting remedial actions and recommendations to reach those targeted goals (Behery, 2008, p. 228). Vera and Crossman (2004) described strategic transactional leaders as task-oriented, focusing on coordinating and monitoring the activities of employee performance. In general, they are able to foster learning ‘‘within a context of stability’’ to reinforce mastery of specialized knowledge/competence to accomplish the work or the tasks by concentrating on organizational norms and culture. The strategy is to bring ‘‘incremental improvement in current ways of doing things.’’ They focus on meeting organizational goals. They pay close attention to ‘‘deviations, mistakes, or irregularities; and take action to make corrections’’ (p. 230). Their focus is on efficiency and stability changes in a systematic pattern to promote continuity through incremental evolutionary changes. They are able to adapt learning to fit the existing organizational culture by observing closely established norms and behaviors. They are defenders of the current systems for maintaining rules and procedures to promote work efficiency, standardization and formalization of administrative guidelines to minimize uncertainty of actions, decisions and risks (pp. 231–234). At the same time, they adopt incremental approaches to manage their environmental changes and uncertainties to adapt current operating systems with the prevailing marketing conditions and competitive environment. In management accounting, the implications of BPR for work process configurations are substantial particularly for accounting functions that are associated with routine and repetition. OT strategy complements BPR by utilizing ABC and BSC to support performance measurement goals that are designed to achieve organizational rather than divisional goals. Thus, the OT-BPR business transformation strategy assumes that organizational innovations encompass structural changes that go beyond improvements in operational performance (Sisaye, 2001).

5.2.3. The Impact of Information Technology on OT The role of information technology is critical for OT-oriented process innovations to take place in organizations. Information occupies ‘‘a central

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role as the enabler of entirely new, cross-functional business processes. Computer and communications technology enable organizations to break the old rules and conventions that dictated the design of business processes’’ (Gulden & Reck, 1992, p. 16). Information technology can serve ‘‘to increase flexibility, to improve communication, and to integrate different functions and organizations’’ (Dixon, Arnold, Heineke, Kinn, & Mulligan, 1994, p. 105). Accounting as an economic information system thus becomes a cornerstone in business process innovations. Accounting also provides financial information that supports process innovation and quality improvement programs. As information managers, accountants monitor information on organizational performance that requires improvement, assess the need for functional integration of the accounting systems that tie the organizational units together, and appraise the capability of the human, financial, and technological resources to carry out business innovation. Accounting innovations are examples of both OD and OT process innovation strategies that can change organizational cultures and systems.

5.3. ORGANIZATIONAL DEVELOPMENT AND TRANSFORMATION APPROACHES IN MANAGEMENT ACCOUNTING INNOVATIONS OD and OT frameworks both approach accounting innovations as administrative innovations, although they differ on the scope of the innovation. Scope is related to the breadth of organizational structures, management policies, and administrative systems included in the innovation process (see Chapter 3). While OD innovation intervention is limited to a single organizational unit or function, OT focuses on changing several units or functions with interdependent operating activities. Accounting innovation can either follow an OD or an OT innovation strategy, depending on the scope and the magnitude of change in management accounting and reporting systems. The magnitude of the innovation may depend on the complexity of organizational structures and the urgency with which the innovation is perceived to be required to become an organization-wide strategy. The focus of accounting innovation initially may be limited to a single unit or department (OD) if the innovation is complex or is significantly different than existing practices. However, if the need for change is perceived to be urgent, the innovation is much more likely initially to be implemented organization-wide (OT).

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At the initial decision to adopt innovation, the scope of accounting innovation, like any other innovation strategy, is generally limited to a single unit or department. At the departmental level, bureaucratic structures play an important role in the adoption decision. In centralized and formal organizations that adopt accounting innovations, the likelihood that these innovations will be implemented is higher than in decentralized and less formal organizations. Decentralized organizations have the autonomy and flexibility to slow down or abandon accounting innovation implementation, if they feel it is relevant to the protection of their divisional interests. In accounting, while vertical differentiation has more impact on the adoption decision, it is the centralized structure that is needed to support implementation of accounting innovation. Thus, OD and OT interventions play complementary roles in both the adoption/initiation or implementation and diffusion/dissemination decisions. While OT intervention is required in the adoption/implementation process, OD intervention is critical in the diffusion/initiation decisions. Organizational structures may create impediments to diffusion of innovations in organizations. Accounting innovations that involve administrative control changes are more likely to be resisted than technical autonomous innovations that occur in manufacturing and production technologies, for example, Ansari and Euske (1987). However, if these technical changes are successful, they can grow incrementally into administrative innovations that have a systemic effect organization-wide. Such has been the case of the compensation system described in Banker et al. (1996). Initially, the compensation system tended to focus on routine operations at the outlet level and had the characteristics of a technical innovation. However, its successful dissemination transformed the technical focus into an administrative dimension and affected the management of compensation systems at several outlets throughout the organization. The Banker et al. (1996) study reinforced the importance of organizational structures in the diffusion of administrative innovations, particularly accounting changes, which are highly significant in performance evaluation and reporting systems. For example, Malmi (1999) found that Finnish subsidiaries of multi-national firms were among the early adopters of ABC. He suggested that, when headquarters forced an adoption decision at the subsidiary level, this, in effect, dictated/facilitated adoption. It allowed central management to follow an OD gradual-autonomous learning strategy and to experiment with innovation at a unit or division level. This OD approach affords central management the opportunity to understand better how innovation can best be introduced into a unit. When innovation is

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successful in the initial unit(s), it not only reinforces management’s plan to move forward with the innovation, but it ultimately increases the expectation that the innovation can be adopted successfully by other divisions. This gradual adoption and diffusion process is consonant with an OT strategy of double-loop systemic learning. The systemic-integrative approach allows central management to diffuse the innovation to other units within the organization with reduced structural resistance and fewer disruptions to normal operating activities. Thus, OD and OT intervention strategies can be seen to play complementary roles in both the adoption/implementation and diffusion/dissemination decisions of accounting innovations. The Banker et al. (1996) and Malmi (1999) studies support the conclusion that, while OD intervention is critical in the diffusion/dissemination decision, OT intervention is required in the adoption/implementation process organization-wide. The successes of OT organization-wide innovations are related directly to the successful implementation of OD innovations at the divisional level. Therefore, OD and OT interventions can have broader implications on the adoption and diffusion of accounting innovations. They both pursue complementary learning strategies for management accounting innovations: autonomous double loop for OD and systemic double loop for OT. Accordingly, the autonomous change reflects the adoption (stage 1) in OD and the systemic change displayed in diffusion (stage 2) of organizational learning and innovation strategies that are discussed in Chapter 6.

CHAPTER 6 ORGANIZATIONAL LEARNING AND PROCESS INNOVATIONS: AN INTEGRATED FRAMEWORK

In this chapter, we integrate the literature on organizational learning and the sociology of adoption and diffusion of process innovations. We develop an integrative framework that relates this literature to that of management accounting.

6.1. AN OVERVIEW OF THE LITERATURE ON ORGANIZATIONAL LEARNING The literature on organizational learning is very rich and complex. Although most research on learning suggests that it involves individual cognitive, cultural, social, and institutional changes and development, there are slight variations in terms of the number of factors various authors associate with these changes. We discuss the work of several authors as providing a contextual framework for viewing learning as involving both the adoption and diffusion of innovations. For example, Lawrence, Maueus, Kyck, and Kleysen (2005) viewed learning as having four components which they referred to as the four I’s of organizational learning. These include: (1) intuiting, which arises from individuals when they develop new knowledge or new insights from their experiences; (2) interpreting those experiences into specific actions; (3) integrating actions, knowledge, or insights into shared understanding through mutual coordination and sharing; and, (4) institutionalizing learning by embedding their new knowledge and insights into through organization systems, procedures, rules, structures, actions, policies, and strategies. 87

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Similarly, Lopez et al. (2005) identified four components of organizational learning which are similar to but not identical to Lawrence et al.’s (2005). These include (1) acquisition of knowledge from internal and external resources; (2) distribution or dissemination of knowledge among organizational members; (3) interpretation of knowledge for use in decisionmaking; and, (4) organizational memory for the purpose of developing rules and procedures to store knowledge for future use in designing systems, improving administrative procedures, supporting organizational adaptation and fit to environmental changes, particularly in turbulent environments. By contrast, Chan, Cooper, and Tzortzopoulos (2005) listed five groupings, that they label facets of organizational learning. The first are contextual facets that include environmental uncertainty, task structure, and leadership commitment. The second group of factors is related to the policies the organization utilizes to facilitate learning in the organization. These include outlining the steps that management uses formally or informally to promote learning through cultural change, recognition, and reward. The third group addresses psychological factors such as risk avoidance and organizational commitment. The fourth aspect is cultural, including those norms and behaviors that promote transparency, integrity, issue orientation, inquiry, and accountability. Lastly, the fifth facet includes structural factors referring to the organizational learning mechanisms of integration where the people learn while performing the tasks; or, nonintegration, where the person learning is not necessarily the individual performing the tasks (pp. 749–750). In general, the structural facets support the creation, sharing, and application of knowledge to those tasks that improve organizational performance (p. 751). On the contrary, Jerez-Gomez, Cespedes-Lorente, and Valle-Cabrera (2005) focus on where the learning takes place. They described learning as consisting of three dimensions: individual, group and structural. They refer to individuals as having cognitive (psychological aspects) behavioral dimensions/assumptions, group as having sociological behavioral dimensions/assumptions, and structural as having organizational behavioral dimensions/assumptions. JerezGomez et al. (2005) suggested that in this context learning is integral to organizational behavior and can become a strategic resource for planning and managing organizations. Accordingly, learning is embedded in organizational, structural, and cultural processes that impact individual and collective knowledge. Learning, that is, new knowledge, is interpreted and shared by members, and is interpreted and stored in organizational memory in the form of rules, procedures, and policies. When knowledge is interpreted, it is shared, integrated, and disseminated/transferred to members and groups within the

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organization. Thus according to Jerez-Gomez et al. (2005), learning involves both acquisition of knowledge, sharing, and transferring them to organizational members, and collectively integrating them into part of the organizational culture and norms. Jerez-Gomez et al. (2005) argued that, when learning increases an organization’s ability to process knowledge, organizations now have the capability to acquire, interpret, and integrate new knowledge that can modify individual and group behaviors collectively to direct their efforts toward improving organizational performance. They also suggested that the organization’s ability to learn is facilitated by four dimensions: managerial commitment, systems perspective, openness and experimentation, and knowledge transfer and integration (p. 716). Managerial commitment refers to the support of management and the provision of structural arrangements conducive for the creation, adoption, and transfer of knowledge. In addition, there has to be a system that (a) provides members with a common or shared identity in order for them to rally around the organization as a series of systems that are interdependent and (b) allows them to develop relationships, have common understandings, and integrate knowledge. Openness and experimentation mean that, for learning to occur, there must be a willingness among members to accept new ideas and experiments openly to promote creativity and a desire to take risks. When this knowledge is integrated, it is accepted as having desirable practical applications and practices for implementing innovative changes that can be transferred and disseminated (Jerez-Gomez et al., 2005, p. 717). Ultimately, it is expected that the learning outcome leads to solving problems which the organization faces and addresses to improve competitive performance. In organizations, learning can lead to successful outcomes when there is integration of individual knowledge, exchange among members, coordination to achieve organizational goals, and direction for common objectives (Jerez-Gomez et al., 2005, pp. 719–721). These various approaches to organization learning suggest that learning is both an individual and a group process. Yeo (2007) provided an integrated view that examined learning as a process where individuals provide their behaviors and actions to promote organizational adaptation to the changing environment; that is, learning contributes to improving individual cognition by providing new insights. In addition, it has the potential to change organization members’ behaviors through dialogue and inquiry to provide a common or shared vision that enables the organization to detect, reduce, and correct errors. We have applied the individual, group, and organizational perspectives to our examination of the adoption and diffusion

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dimensions of learning. The literature, in general, suggests that organizational learning involves individual cognitive (psychological aspects) and group and organizational (sociological dimensions) changes.

6.1.1. Psychological Dimensions of Learning: Individual Cognitive Changes When it comes to individual cognitive change, organizational learning has been defined as a process that has the potential to change individual behaviors and actions. Individual learning involves the acquisition of knowledge and information by individual members of the organization, and their effective forms of communication (oral and/or written) which, over time, evolve into organizational practices. This process involves both ‘‘acquisition’’ of knowledge by individuals and ‘‘participation’’ by organization members. Elkjaer (2004) referred to this as two ways of organizational learning (p. 419). The third method addresses inquiry and reflective thinking about ideas and practices. It involves synthesis, that is, analysis and inquiry about knowledge where members are expected to acquire knowledge and participate in communities of social inquiry. This is referred as reflective learning (p. 421). These three processes indicate differences among organizational members in their work, life, and experiences. It also recognizes differences in members’ roles in organizational transactions and the implications these changes have on their affiliations to the organization (Elkjaer, 2004, pp. 430–431). Brown and Duguid (2001) elaborated the relationship between individual, group, and social learning. They suggested that learning has a sociocultural dimension that involves relationships among individual and group learning, and identification with the organization cultures and social systems. Learning requires both the acquisition of knowledge by the individual and individual’s identity. They used as an example that of a physicist, who has the acquired or learned expertise/knowledge after many years of formal training and practice but, at the same time, needs to have a social identity, that is, being recognized as a physicist by others with whom she/he interacts. Brown and Duguid (2001) argued that, when someone is recognized as a ‘‘learned person’’, that is, one with knowledge and/or skills in a given domain, he or she is credited with possessing ‘‘the ability to act in the world in socially recognized ways’’ (p. 200). Members of an organization possess expertise in different areas and at different levels. There exists a significant difference among physicists in the degree of shared knowledge that is

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acquired and attributed to some as specialists with expertise training, while others with broader backgrounds are referred to as generalists. Thus the learning process is said to be held collectively by organizational members. Accordingly, knowledge in organizations exists among individuals in their areas of specializations/expertise. It is necessary that the organization integrate the members’ knowledge to maintain the organizational capability and competitive advantage to respond to dynamic environment. Grant (1996) articulated the role of knowledge as organizational resources where multiple knowledge bases are jointly coordinated. ‘‘Integration of specialist knowledge to perform a discrete productive task is the essence of organizational capability, which is defined as a firm’s ability to perform repeatedly a productive task that relates either directly or indirectly to a firm’s capacity for creating value through affecting the transformation of inputs into outputs. Most organizational capabilities require integrating the specialist knowledge bases of a number of individuals’’ (p. 377; italics in original). Thus, the success of an organization depends on the integration of individual and group knowledge to develop a competitive advantage and to achieve improved performance.

6.1.2. Sociological Dimensions of Learning: Group and Organizational Changes Learning not only is a process that involves cognitive change through knowledge acquisition and past actions of individuals, but it also is a social process that involves adaptation to changes in behaviors of individuals in one’s group as well as those of other groups and organizations. These adaptive strategic changes include both external and internal behavioral changes among individuals and groups within the context of organizational learning, and they may be either incremental or radical. Bapuji and Crossan (2004) suggested that, when learning is internal, organizations learn from their experiences. When it is external, they learn from others, particularly, competitors’ past experiences or the industry at large. They can learn through inter-organizational alliances and cooperation with other firms through joint ventures or research and development (pp. 403–404). Learning from others improves existing organizational practices. The new knowledge acquired expands the organization’s knowledge into new arenas and areas to promote better understanding among members, to detect and correct errors, and to improve organizational practices (Lumpkin & Litchtenstein, 2005).

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According to Lopez et al. (2005), organizational learning can provide a competitive advantage for the organization. It can improve organizational performance. The new knowledge, that is, the learning that occurs, increases employees’ abilities to be innovative and to make decisions that better align organizational capabilities with the changing environmental conditions. Organizations then are better able to undertake new initiatives, primarily technological, that impact their business performance. In this way learning promotes new behaviors and knowledge that leads to better performance, in other words, to superior outcomes of products and services that attract new customers and retain existing clients. In general, learning improves the overall performance of an organization over time. Bryant and Terborg (2008) suggested that when groups and teams experience learning, they share knowledge through peer mentoring relationships’’ (p. 25). Mentoring fosters knowledge sharing that provides an organization with a competitive advantage. In general, organizations able to reinforce peer mentoring with training increase knowledge creation and sharing that becomes instrumental in improving the organization’s competitiveness. Organizational learning may also arise internally from organizational experiences or its past history and experiences; or, externally by learning from the diffusion of innovations. For example, learning can occur through government mandates to correct problems in situations involving product recalls. Haunschild and Rhee (2004) noted that, when organizations make an effort to learn from their experiences with product recalls, learning can ultimately lead to favorable outcomes resulting in fewer errors or mistakes in product and services. This is because knowledge acquired from the negative experience leads to ‘‘better product design or improved organizational processes that will reduce the incidence of errors’’ (p. 1546). In other words, when past results, for example, recalls fail to meet organizational standards, organizations will explore possible solutions, leading to learning from experience. This is an example of voluntary learning to solve a problem. Sometimes, it is possible that ‘‘these voluntary recalls may come from incremental organizational procedures that increase the likelihood of announcing a voluntary recall’’ (Haunschild & Rhee, 2004, p. 1557). Usually in products with multi components, a defect in one part affects the others. If this problem is detected internally, it reduces involuntary learning. In other words, it is internally induced rather than externally forced, for example, mandated recalls that reduce likely recurrences of errors that precipitate recall. Over time, it is hoped that the cumulative effect of past failures will

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generate and promote learning to reduce/eliminate future errors and, thereby, eliminate externally mandated requirements. However, in group contexts, politics and power may impact the ability of knowledge sponsors to influence thoughts and actions of others. Lawrence et al. (2005) suggested that ideas that are translated, interpreted and integrated at the group level need to be championed to be disseminated. These champions’ acceptance of new behaviors and their associated power bases affect the integration and institutionalization of knowledge within the group and the organization. The power to reward particular interpretations of knowledge and penalize others affects the adoption and construction of knowledge. When learning is said to be institutionalized, it is embedded in the organizational systems, structures, rules, manuals, procedures, policies, and strategies. Resistance to change has been addressed and overcome by innovation champions or managers. A power that is based on domination (hierarchical power) is effective in the politics of institutionalization of learning and innovation (p. 186). In addition, Lawrence et al. (2005) noted that political processes or organizational learning involves the influence to ascertain the ambiguity of interpretation associated with learning. This may necessitate the use of force to accomplish integration of collective action, domination to overcome resistance to change, and discipline to support expertise in acquiring knowledge (pp. 188–189). Learning thus is more than a simple process of calculation. It involves persuasion, command, or influence in the social interaction process. Accordingly, managers’ interventions can influence organizational learning through motivation and the use of incentives to identify and address organizational problems and possibly suggest remedial actions; for example, to reduce costs, improve production, among others. Arthur and Huntley (2005) gave examples of gain-sharing, where organizations learn from experiences of employee suggestions for managing performance by reducing production costs. As workers’ experience increased over time, per unit costs declined correspondingly. Arthur and Huntley (2005) elaborated gainsharing as deliberate learning strategies to acquire knowledge by encouraging employees to suggest ways of reducing costs or improving performance formally through financial rewards and monetary incentives. This experience-based learning is associated with work reduction in per unit costs. When accompanied by gain-sharing, the decline in unit costs was substantial. Over time, employees’ knowledge based suggestions can reduce per unit costs, but the effect of ‘‘cumulative knowledge depreciates over time’’. However, when organization learning practices introduce ‘‘a planned

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performance improvement program such as gain-sharing’’, it contributes to improved performance (Arthur & Huntley, 2005, p. 1166). In fact, this ‘‘suggestion based knowledge’’ will depreciate over time unless there is a continuous stream of new suggestions that support gain-sharing (p. 1166). Otherwise, decline in unit costs revert to pre-sharing levels. Managing ‘‘the knowledge depreciation rate through discovering the causes and taking actions are critical for the long term success of an organization’’ (Arthur & Huntley, 2005, p. 1167). Gain-sharing thus becomes practice-based learning for the purpose of coordinating shared knowledge across the organizations’ various units/divisions or businesses. When learning is practice-based, it involves social activities that will promote applied learning. There are organized collective activities for members and shared knowledge learned within these social contexts. There is ‘‘co-orientation’’ where learning is interactive (Macpherson & Jones, 2008, pp. 177–178). The ability of an organization to coordinate knowledge in its various functions provides a competitive advantage (Brown & Duguid, 2001). To this effect, Cross and Berdrow (2003) concluded that ‘‘organizational learning is seen as a means to develop capabilities that are valued by customers, are difficult to imitate, and hence contribute to competitive advantage’’ (p. 1089). They also noted that when organizations undergoing strategic renewal and managers are brought into the organization from the outside is likely to result in changes in the organization that, in turn, necessitate changes in cognition and behaviors at the individual, group, and organizational levels that support organizational learning (p. 1102). Thus, the strategic renewal learning process leads to changes in an organization’s systems, structures, strategies, and policies. According to Antonacopoulou, Ferdinand, Grace, and Easterby-Smith (2005), organizational renewal involves interaction and negotiation of order and disorder. As organizations develop capabilities to manage and coordinate resources, there is a renewal of competency. It integrates change, learning, and organizational dynamics. The change will affect the operating conditions of organizational activities. Thus, renewal is an ongoing process to restructure and stabilize an organization’s operations. However, any change of a significant magnitude can also involves what Antonacopoulou et al. (2005) referred to as disorder as the organization works its way through the learning process. The learning process may well include the need to experiment with different approaches in response to its environment and its competitors. In this context, organizations learn from their competitive environments to align, restructure, and improve their practices to remain in business. Organizational learning can become a resource to improve performance and competition.

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Dynamic capability involves the internal positioning and alignment of organizational resources to coordinate renewal and learning and to make it adaptable to external environmental changes in markets and by its competitors. Dynamic capabilities address change in organizations to improve the organizations’ ability to integrate and align resources to meet environmental changes. Learning can also become instrumental when organizations learn from the external experiences of other organizations’ cooperative ventures and alliances within the same industry or market (Bapuji & Crossan, 2004, pp. 403–405). Thus, organizational learning can facilitate innovations and implementation of change programs, including improved information systems management (Lin & Lee, 2005). Consequently, there is no question that managing information technology (IT) is important and plays a key role in assisting the organization to attain a competitive advantage. It is an invisible asset that collects, analyzes, and reports information on markets, customers, competitors, and organizational resources. Within the context of IT, Tippins and Sohi (2003) viewed organizational learning as a process of acquiring new knowledge. It ‘‘consists of four components: information, acquisition, information dissemination, shared interpretation, and development of organizational memory’’ (p. 749). Information acquisition deals with the gathering of information from internal (employees) and external (customers, markets) sources. Dissemination deals with distribution or sharing of information within the organization. Shared interpretation includes the process through which the information is interpreted, discussed, shared, and, ultimately, understood. The shared information is then ‘‘stored’’ in the organizational memory and is archived through procedures, declarations, or manuals. Thus, the IT process supports the process of generating organizational learning and organizational competency. Learning organizations that have IT strategies for customers and markets are better situated to provide the information managers need to introduce desirable innovations. Thus, in the long run, the process of IT benefits can enable a firm to improve performance when IT is used in conjunction with other organizational resources (Tippins & Sohi, 2003, pp. 751–756). In addition, Lin and Lee (2005) affirmed that organizational learning factors related to staff training and technical expertise accompanied by greater knowledge acquisition can facilitate the introduction and adoption of innovations within IT such as those associated with e-business inventions that transforms the overall organizational operational activities. According to Hanvanich, Sivakumar, and Hult (2006), the impact of organizational learning is on organizational outcomes related to improved

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performance. Process innovations are moderated by environmental and market competitive conditions, whether the environment is dynamic and turbulent, or static and stable. There are positive relationships in learning, organizational performance, and innovative behaviors in business environments characterized by high market volatility and technological changes. Environmental turbulence places greater emphasis on the ability of organizations to explore new avenues, mechanisms, and opportunities to serve their stakeholders. The learning experience suggests that, over time, organizations acquire expertise that enables them to operate/produce better and faster, with the result that there is a decline in production and manufacturing costs. Nevertheless, organizations have differences in their abilities to acquire and generate knowledge, and at the same time, learn from their competitors. Organizations choose to select those activities or routines that generate the best results from learning. The firm can then select and distribute those routines or rules that are effective in dealing with specific environmental changes. If there is interdependence of activities, the ability of organizations to isolate poor performances and determine appropriate actions to correct them is more complex. Therefore, learning tends to be less effective when there are interdependencies and any changes involve higher transaction costs (Williamson, 1975). As the degree of interdependence among organization functions increases, it becomes more difficult to determine where the problems are and which routines or rules are appropriate to address the problems. As a result, in this situation organizations simultaneously change or experiment through trial and error until they find appropriate corrective mechanisms for the observed deficiencies. During the learning process, their performance may decline. It improves when they find effective routines and solutions that yield better outcomes/results. The organization’s ability to detect and correct error diminishes when there are interdependencies that cause organizational inertia (Hannan & Freeman, 1984) and the presence of interdependence interrupts the learning process and the diffusion of information by limiting the ability of one of the individual interdependent units of the organization to engage in actions independently. If the environment is volatile, the ability of organizations with highly interdependent activities to learn and adapt declines further. As a result, their performance level is disadvantaged in the short term. In other words, the structure of the organization affects the ability of firms to learn and adapt at the very time the dynamic environments makes the greatest demand on them (e.g., see Rowe et al., 2008). Thus, while interdependence is

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intended to increase organizational efficiencies and minimize costs, it decreases the ability to maximize organizational learning outcomes and thereby achieving improved performance in the short term. Thus, learning is an evolutionary process where an organization’s ability to develop, organize, innovate, adopt, and disseminate knowledge depends on both internal resource capabilities and external environmental factors. Organizations that are able to adapt to both internal and external factors are capable of adopting and diffusing knowledge to improve their performance and as the result are able to obtain a market advantage over their competitors.

6.2. THE TWO STAGES OF ORGANIZATIONAL LEARNING: ADOPTION AND DIFFUSION Schulz (2001) suggested that the learning process usually follows a sequence of steps/stages that reflect how the sub-unit’s/organization’s experience influences the process by which knowledge is adopted and disseminated to peers and supervising units. He argued that organizational learning and change usually follows an evolutionary staged growth in terms of the ‘‘number of processes that create new knowledge or modify existing knowledge’’ (p. 663). These processes start with how knowledge is gathered or obtained (codified), followed by the extent to which it is analyzed (explored), and ultimately communicated (selectively diffused). Schulz (2001) described the process as having two inter-related stages. The first stage, acquisition/production (adoption), consists of the gathering of knowledge/information, its codification, and exploration. It is followed by the second stage, namely, the dissemination/distribution (diffusion) processes (p. 676). Nevertheless, when changes in the organization’s external environment persist and the organization faces a crisis, this can overcome management’s resistance to change and accentuate the need for organizational learning, and for proactive change and adaptation strategies of development and transformation. When the organization recognizes the need to innovate to solve a problem, specific innovations are championed by opinion leaders who both perceive the existence of the problem and ascertain what they consider to be a viable solution. These opinion leaders typically are executives or front-line managers who communicate and champion the innovation to lower level managers and/or employees. This represents the

Fig. 6.1.

Diffusion of Innovations

Necessitates Preconditions for Accounting Innovations

Cost Allocation Just-in-Time Activity Based Casting (ABC) Balanced Scorecard (BSC) Strategic Cost Accounting

     Organizational Size Profitability Environmental Attributes Innovation Congruency Organizational/Top Management Commitment

Factors Facilitating the Implementation Process  Presence of Innovation Champions

    

Coordinating With Potential Providers of Innovations

Championing the Need for Innovations  Prospectors/Leaders  Followers

Suppliers of Innovations  Accounting Firms  Academic Institutions  Textbook Publishers  Industry/Corporations  Management Consulting Firms

Organizations Recognize the Need to Innovate to Address the Problem

Adoption of Innovations

Examples of Management Accounting Innovations

The Adoption–Diffusion Processes of Innovations in Management Accounting Systems Sources: Adapted from Sandberg (2007) and Wejnert (2002).

Diffusion Strategies/Outcome  Diffusion of Successful Innovations  Division/Unit levels  Organizational Wide  Trial and Error Lessons  Organizational Learning Approaches  Adaptation Strategies For Failed Innovations  Lessons Learned  Feedback/forward Learning Strategies Lessons Learned Feedback/Forward Learning Strategies

Environmental Contexts  External  Competition  Political Systems  Economic Conditions  Regulatory Issues  International Conditions  Internal  Organizational structures  Centralization  Decentralization  Learning  Single loop  Double loop  Extent  Technical  Administrative  Scope  Autonomous  Systemic

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first stage of learning (adoption) illustrated in Fig. 6.1. In those instances where the problem is sufficiently severe or the organization has not been able to identify any specific innovation/knowledge required for a viable solution, organizations may identify an outsider (e.g., a consultant) as a champion (see Rowe et al., 2008, 2011). The implementation of a successful organization-wide innovation requires a second stage of learning and diffusion. This occurs when managers/ employees accept and implement the innovations at the division/unit level; the second stage of process innovation (diffusion) has taken place within the sub-unit. These two stages relate to the two questions we identified in the Introduction and in Chapter 1. Stage 1 considers why certain innovations are more likely to be implemented. Stage 2 helps us to understand why the dissemination of accounting innovations within the organization is more successful in some instances than others. Fig. 6.1 describes the process whereby an organization becomes aware of the need to change (innovate), and then later, how it disseminates (diffuses) the innovation to other parts/all of the organization. It traces how the adoption–diffusion process is shaped by various activities in which individuals, change agents, and organizations participate in the learning/ innovation processes. Accordingly, the learning process is analogous to the two phases described by Attewell (1992): awareness of the innovation and acquisition of the know-how required to implement the new process. In Fig. 6.1, the term ‘‘diffusion’’ refers to the dissemination of the innovation within the (intra)organization rather than its spread to other (inter)organizations. The experiences of Safety-Kleen with ABC and ABM illustrates the two stages of innovation, where, at stage one, the adoption of ABC was limited to a single division-wide intervention, making it an OD double-loop autonomous learning strategy. The success of ABC leads to stage 2 during which the innovation was disseminated or diffused to other divisions in the organization, making it ABM and double-loop systemic learning. As described in Fig. 6.1, the diffusion of an innovation within an organization begins with its identification by champions who obtain the support of their top management and acquire the information they need to influence others (followers) to adopt it. Thus, information and communication are critical to moving the innovation forward and in determining the length of the time lag between early and late adopters. Kumar and Krishnan (2002) discussed two types of lead–lag differences in the introduction of new technology among countries. The first process, which they identified as ‘‘waterfall strategy’’, pertained to the time or the order of entry when the diffusion process was introduced. This strategy

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follows the lead–lag approach, in which the lead country (or organization) adopts the new technology, and the lag country (or organization) follows (p. 328). The second process, referred to as the ‘‘sprinkler strategy’’, involves innovations which could be ‘‘simultaneously introduced’’ in multiple countries or organizations. In this case there is no lead–lag effect and no significant social, cultural, and economic differences among the adopters (p. 328). Most diffusion research suggests that dissemination occurs when there is a lead–lag difference between countries and/or organizations (Weinjert, 2002). The lead–lag approach is predominant view in research on diffusion in social and economic development. It also is referred as the ‘‘trickle-down’’ effect. In social and cultural change programs, the ‘‘trickledown’’ effect has been generally accepted by researchers to explain social and economic development (Leagans & Loomis, 1971). Katz (1999) related the ‘‘trickle-down’’ effect to the predominant theory of the S curve in diffusion research. The assumption is that it is ‘‘true, there is the general S curve in the adoption of innovations and its more sophisticated elaborations; there is the general rule of trickle-down from higher to lower status; and there is the apparent need for reinforcement from peers prior to adoption’’ (p. 147). Katz (1999) argued that there is no general theory or framework of diffusion except for ‘‘a set of tools for making generalizations possibley’’ (p. 147). In diffusion research, it is assumed that ideas or practices are communicated through networks or leaders who promote these values to adopting individuals and groups. In addition in organizations, the trickle-down process may also proceed from superiors to subordinates. In any case, diffusion is reciprocal and involves a two-way process. Despite the voluntary tone of the above discussion, in practice the process of diffusion is not necessarily always a voluntary process. It can also be imposed by forcing new ideas or culture to change existing patterns of social life. This can occur when consultants are hired by the organization’s leadership or a strong, politically powerful leader(s) in the organization supports a particular innovation. In general, diffusion involves an ‘‘imitation’’ process that assumes persuasion, command, or influence in the social interaction process. By imitation, we are referring to the copying of innovations and/or obeying of ‘‘request’’ of the champion by interconnected individuals and groups. It also can be a social contagion process where word of mouth plays an important role in the diffusion process. In other words, the adoption of innovation entails a social process where communication, persuasion, and interaction with opinion leaders facilitate the process. This is because opinion leaders are sources of social influence. They can identify a subset of initial potential

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adopters who then promote the adoption of a particular innovation within the community. Opinion leaders who are credible, accessible, and who have the means of advancing new practices and ideas are able to provide support and influence for dissemination of the innovation. They are early adopters who have tried the innovation, have been successful, and can influence its acceptance by subsequent or later adopters. Opinion leaders can function as change agents by facilitating ‘‘the task of transmitting information’’ (Gatingon & Robertson, 1985, p. 860). In most instances, potential opinion leaders can be recruited from adopters who have been successful in the past and therefore have credibility. Although communication is the key to an innovation’s diffusion, adoption of the innovation in a particular organization may entail a certain degree of modification of the innovation, or what Dearing (2009) terms as ‘‘intervention adaptation’’ (p. 513; italics in original). Over time, there are incremental adjustments in innovations designed to accommodate the organization’s work environments, and cultural contexts. Adoption, when planned and implemented, makes an innovation program in intermediary organizations such as public health or agricultural practices, for example, more effective and instrumental. According to Rogers (1995), the diffusion framework involves interpersonal communication or spread of information in the social system. Frenzel and Grupp (2009) further advanced this view by arguing that, in diffusion, there is ‘‘communication of information about the innovation as being crucial for its adoption’’ (p. 44). Personal influence may account for the spread of innovation. Yet, some successful innovations are adopted later because the information was either not quickly disseminated or discovered until later. If, on the contrary, the dissemination of information about innovations occurs only when they became ‘‘epidemic’’, it means adoption would more than likely be infectious for both the communication and the adoption of the innovation. Frenzel and Grupp (2009) suggested that the core assumption of the epidemic model is that innovations are likely to be adopted when targeted populations are ‘‘infected’’ by the innovation when it reaches them (p. 45). This is comparable to the information contagion approach where friendship ties, proximity, and the characteristics of comparable segments of a group or community facilitate interaction and communication for the spread of the innovation. Thus, personal influence of various types forms one of the basic components of the diffusion theory. The rate of spread of diffusion is dependent on personal influence. Among the factors which affect the character of the opinion leader are: relevance of personal influence, intent of

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influence, personal characteristics of the opinion leader, the form (verbal or non-verbal) of the communication medium, the direction of the influence (‘‘opinion seeking’’ or ‘‘opinion giving’’), and the network process (‘‘similarity among individuals’’) adopting the innovation (Gatingon & Robertson, 1985, p. 855). In general, personal interactions are more likely to prevail when there is a social attractiveness; among individuals who possess the same behavioral attributes. Accordingly, there are personal characteristics that are related or based on ‘‘higher income, higher education, younger, more socially mobile, more favorable attitudes toward risk, greater social participation and higher opinion leadership’’ associated with innovativeness (Gatingon & Robertson, 1985, p. 861). Weinjert (2002) related social-contagion effect, personal ties and characteristics to the cultural community approach of adoption and diffusion, if these behaviors are accepted by organization members and groups. She identified three factors in the institutionalization of behaviors that are considered acceptable policies and standardized practices, namely, (1) global adoption of technologies by multi-national corporations, (2) inter-connectedness of the world community through advanced communication systems and media, which render the process of diffusion universal, and (3) the transfer of process innovations to create comparable societal structures (p. 315). She also noted that computer and Internet usage globally is considered essential for modernity, growth, and development. The mass media can promote the diffusion of technology and advance its institutionalization and globalization by facilitating adoption and diffusion processes (pp. 316–317). Katz (1999) also noted that ‘‘diffusion also is facilitated by a compatible social structure’’ (p. 150). Diffusion can succeed when new ideas are introduced in a society that has ‘‘a compatible value systems (contraception has a harder time in Catholic countries) and compatible media (print serves participatory democracy better than television does).’’ That is, innovation is less costly to adopt when it is ‘‘less upsetting’’, that is, more consistent with current beliefs, and compatible with the status quo (p. 150). In organizations and societies with compatible value systems, innovation champions are accepted as leaders and play important roles in the dissemination of new ideas and information that support process innovations. Sandberg (2007) noted that enthusiastic champions serve as catalysts in organizations for the developmental stage of radical innovations (idea generation) and subsequent diffusion throughout the organization. ‘‘At the development stage, the enthusiasm spread from the champions and the core team to other parts of the organization, and in some cases also to other development partners’’ (p. 269). She associated radical innovations with

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technologically new and commercially successful products and services that offer substantial benefits to customers. The role of networking serves as a driving force in the diffusion of the innovation and its successful marketing to customers through ‘‘personal visits, customer education, simulations and trials’’ (p. 271). While radical innovations resulted in the development of new products and services (for example, the ePost Letter and the Nordic Walkers cases that were commercially successful), their diffusion to customers and their diffusion outside of the organization was a gradual process designed to sustain enthusiasm for the long term. There are several studies in management accounting that attribute the successful dissemination of accounting innovations to the diffusion literature in sociology. Two studies that are of particular interest are Banker et al. (1996) and Malmi (1999). These studies have described accounting innovations as following a trial-and-error strategy whereby innovations are first tried in one unit or a sub-unit and, if successful, are later implemented in other units within the organization. The Banker et al. (1996) study of a performance-based compensation plan illustrates this point. Because the performance-based system proved to be successful initially, it was gradually implemented in additional locations. When an accounting innovation is tried on an experimental basis in a unit/division and results in positive outcomes, the innovation can be more easily disseminated to other divisions within the organization. Similarly, Malmi (1999) discussed the role of corporate management in the ‘‘forced selection perspective’’ that led to early adoption of ABC among Finnish firms. The study corroborates the findings of Banker et al. (1996) on the role of headquarters in implementing an organization-wide change. While the initial support (championing) for the adoption of the innovation was dictated by top management, its diffusion from one unit to another was attributed to the innovation’s record of successful outcomes in those units that had already adopted it rather than its being imposed by top management. Thus, Malmi (1999) supports the model depicted in Fig. 6.1 where a successful adoption process requires that management (opinion leaders) championing the innovation dictate or mobilize sufficient support from other members of the organization for the innovation’s implementation and diffusion. Fig. 6.1 also incorporates the results of Sandberg’s (2007) study, which reported that top managements’ (champions’) deliberate support and involvement in large organizations (as is the case with Chrysler and SafetyKleen corporations discussed earlier) become necessary to adopt and disseminate the innovations throughout the organizations. In this view of

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learning, the adoption processes included the acquisition of knowledge (Schulz, 2001) and the diffusion stage encompassed the dissemination of that knowledge to targeted markets and differentiated customers (Sandberg, 2007). Thus, the diffusion-communication processes become central in the dissemination of new practices and modes of behavior to all organizational members. However, there may also be political powers and cultural change constraints that impact the adoption and dissemination of innovations. Fig. 6.1 lists several reasons for both the successes and the failures associated with diffusion of innovations. For example, one possible cause of a failed innovation is that the process used to facilitate the adoption of the innovation was flawed. As Brunsson (1982) noted, there is a difference between the economic decision (selecting the best course of action) and the political process (coalition formation) involved in implementing a course of action. The former typically relies on formal cost-benefit analyses. The latter is more political and involves persuasion and coalition formation (Cyert & March, 1963; Pfeffer, 1992). It may not be strategically possible to implement the ‘‘best’’ course of action or outcome, nor politically feasible to secure support for the adoption and diffusion of the innovation. We apply an evolutionary perspective to describe the two stages: adoption and diffusion processes of management accounting innovations. Fig. 6.1 outlines the process and provides the general framework for the evolution of management accounting innovations. It describes the process from the demand (adoption/implementation) for innovation to the diffusion (dissemination) processes. The need for an accounting innovation begins when external environmental and internal constraints give rise to the perception of the need for organizational learning. It is the cumulative effect of both the constraints and the perceptions of a need for change that affects whether or not a specific organization at a particular time adopts an innovation to meet a particular perceived need.

6.3. ORGANIZATIONAL LEARNING AND THE BIRTH AND BUREAUCRATIZATION OF ACCOUNTING RULES Organizational e-growth, development, and transformation require accounting innovations and learning. As organizations evolve over time, they create

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accounting mechanisms that among other purposes serve to maintain organizational stability and the status quo. Organizations develop new accounting rules only when they are necessary to address ‘‘new problems that do not seem to be covered by existing rules and when these problems are fairly recurrent, consequential or salient’’ (Schultz, 1998, p. 845). This enables the organization to retain what has been learned from past experiences in the form of ‘‘codified’’ rules and regulations. Thus, bureaucratization takes place (Schultz, 1998). However, this bureaucratization is not without its costs. Established rules may inhibit subsequent learning and, as the result, diminish the likelihood of subsequent innovations by the organization. In the case of accounting, this would mean that learning and innovation lead to the birth and codification of new accounting rules. As organizations over time develop more rules, the potential for greater bureaucratization is increased, which, in turn, may result in inhibiting future learning experiences. Specifically, Schulz (1998) stated: ‘‘As lessons from past experiences get encoded in rules or other systems of automated (organizational) responses, new experiences become scarce. As a result, learning through further codification of experiences declines. Making rules and routines helps organizations respond to problems in a programmed and efficient way, but, at the same time, rules create a dangerous sense of familiarity with problems that reduces the likelihood that new problems will be seen as opportunities to draw new lessons’’ (p. 872). Lawrenson (1992) described the bureaucratization of the organization’s decision making in British Rail. Before Margaret Thatcher’s becoming prime minister, British Rail was engineering-driven. Its incremental learning had created values and mechanisms that reinforced the importance of maintaining superior engineering. Decisions were made with the intent of maintaining an organization that reflected the highest engineering standards. British Rail responded to changes in the competitive environment by searching for engineering innovations. Financial measures played a secondary role in their decisions. As the environment changed and economic issues became more important under Thatcher’s plan to privatize it, the organization remained insensitive to the changing political environment. It required an explicit intervention by the government to override the existing bureaucratic rules and alter the organization’s orientation to learning and innovation (Dent, 1991).

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6.4. THE ADOPTION–DIFFUSION PROCESSES OF ORGANIZATIONAL LEARNING IN THE MANAGEMENT ACCOUNTING LITERATURE Organizations need for growth, political power, increased competitive posture and desire to adapt to environmental changes create the need for learning and innovation. Organizational learning becomes critical in promoting strategic planning and control systems to enact cost accounting changes (Kaplan & Norton, 2001) in organizations. The rise of new rivals, that is, external constraints, leading to the perception by management of the need for a change in cost management system is illustrated by the rise of competition from Japan in various industries, including that of automobiles. This competition created a sense of urgency and a need to adapt on the part of U.S. firms. The result was the adoption of various new (for the U.S. firms) management activities/processes such as JIT, Five Sigma quality control, and, in accounting, an increased interest in cost measurement, for example, ABC (Anderson, 1995) in many organizations. However, in other organizations the actual adoption of proposed changes such as ABC was resisted and in some instances rejected due to extant organizational structures and bureaucracy (Sisaye, 2003). Ansari and Euske (1987) reported a contrary example where an organization’s extant bureaucratic structure was able effectively to resist an external force attempting to alter the nature of the unit’s costing system. They observed resistance to change when ‘‘top management’’ in D.C. imposed a new costing method for the geographically decentralized repair depots. Management of the depots was satisfied with the old system and, therefore, was resistant to adopting the new method. Given the geographical separation between top management in D.C. and the repair depots and the lack of close supervision by top management of the repair depots, the change in the repair depots ‘‘external environment’’, that is, top managements attempt to impose a new costing system, was frustrated by the depots existing bureaucracy. They continued to use the old costing method for managing their activities and adapted the data to the new system only for reporting to headquarters. Barnett and Hansen (1996) noted that an organization’s history and the lessons learned from past failures and/or successes both serve as internal constraints to the adoption and diffusion of an innovation/change within the organization. These constraints are reflected in both the organization’s formal and informal structures related to strategy, policies, employees, and

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organizational culture, all of which include norms, shared values, and behaviors (Hannan & Freeman, 1989). For example, Anderson and Young (1999) reported that context and organizational factors affected the nature of the ABC system developed within a firm. They found that the complexity of the ABC system proposed increased with the size of the group involved in the development of the new cost system. This suggests that the system they adopted represented a compromise among the participants. The Anderson and Young (1999) study reveals that initially organizations may be rigid and resistant to change because they have stable routines and cultural practices that satisfy current performance levels and, therefore, the managers perceive no need to change and saw different costs associated with the proposed changes. As the result, the new system represented, as Brunsson (1982) proposed, a series of adaptations to the various extant routines of the sub-units. Over time, what are initially considered new accounting innovations tend, as described by Anderson and Young (1999) and Ansari and Euske (1987), to be resisted by organizational members. However, if they ultimately are accepted, they become the part of and are institutionalized as autonomous operating procedures used to administer stable and routine functions. Such bureaucratization of the innovation in management accounting leads to programmed rules and routines, that later tend to be mechanistic and associated with efficiency of work procedures (Burns & Stalker, 1961). In essence, technical innovations lead to the establishment of stable rules/ mechanisms, or what Schultz (1998) described as new birth and codification of accounting rules, that can contribute to resistance to new process innovations. When technical accounting procedures are bureaucratized, management planning and control systems become more formal and institutionalized. In these operating systems, mechanistic innovations prevail in day-to-day activities. Accounting tasks become centralized to handle those operations and production activities that are routine, repetitive, and programmable (Dirsmith & McAllister, 1982). Formal rules not only specify procedures, they also define employee roles. Accounting numbers, in effect, control employee behavior as well as the operating activities of the organization. Formal accounting control systems monitor employee performance and the existence of quantitative reports leads to their replacing the use of personalized and qualitative feedback and interpersonal relationships in control systems. The predominance of a formal intra-unit orientation, that is, controllability, in the organization’s performance evaluation and reward systems has another important effect. It reduces the interactions among units and

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discourages/inhibits the diffusion of a potential innovation within the organization. Each unit operates as a distinct and separate unit within the organization’s hierarchy. The members minimize its relationship with or connection to any other unit. This inhibits the flow of innovations across units and favors standalone innovations (Schulz, 1998). The awareness of the need for inter-unit cooperation may increase when organizational problems have ‘‘thematic relatedness’’, that is, possess a high degree of similarity, or reflect a joint dependence on the same resources as often is the case with accounting problems or procurement problems (Schultz, 1998). Although these changes might lead to acceptance by some and resistance by other members, the uncertainties surrounding these changes might require members to accept them or else leave the organization. Under these circumstances, the central management of the organization can develop relatively generic common rule (s) that can be utilized by many or all of the organization’s sub-units. The scale of the innovation/intervention also is relevant. When an innovation requires large-scale abolition of old rules to eliminate obsolete systems and helps to alter the system, the recommendation is that the organization undertakes a large-scale intervention program specifically intended not only to abolish old rules but also to replace them with new ones. It can be inferred that Schulz’s (1998) radical measures of rules changing are consistent with the OT approach described in Chapter 5. Organizational learning of the sort contemplated in management accounting, for example, ABC or BSC, requires a significant change in the organization’s rules and procedures. This involves an OD (autonomous) or OT (systemic) radical change strategy. This type of change is accompanied by organizational response to the natural selection process of new forms (innovations) and results in transformational second-order change (doubleloop) learning. Both ABC and BSC require a significant change in the manner a process is viewed, that is, ‘‘thinking outside the box’’. ABC requires accountants and managers to view a new and more complex set of cost drivers that includes drivers that have not been utilized in previous costing systems. BSC is an example of double-loop learning in management accounting that stresses product development and new markets which focus on delivery of goods and services that meet customers’ needs. It emphasizes the user’s need to think beyond the traditional management accounting model of short-term profitability (‘‘outside the box’’) and to integrate new dimensions. The introduction of non-financial measures of marketing, production, and human resources management requires reorientation, that is, double-loop learning, by those involved in managing the organization.

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An example of an accounting study that illustrates the double-loop learning approach of adoption–diffusion of innovation from a unit/division to organization-wide is that of Davis and Albright (2004). They reported the results of a quasi-experimental field study within a single banking organization and suggested that those units that had adopted BSC showed superior performance when compared to those who did not. However, Speckbacher et al. (2003) reported data indicating the difficulty in the implementation of BSC. The responses of the firms in their survey showed that the evolutionary process required when organizations move from the traditional financial model to a new approach utilizing both financial and non-financial inputs necessitated a longer time horizon for planning and implementation. These studies suggest that, although organization innovation refers to the adoption of new behaviors, ideas, or systems; process innovations that involve administrative processes or services that affect employees’ behaviors and organizational structures are more complex. They are contextdependent where decentralized structures that have complex job structures with flexibility in the diffusion of innovations. In general, centralized structures facilitate the adoption process. In the context of management accounting systems, the success of adoption–diffusion of innovations depends on the choice of management accounting intervention strategies/ typologies: OD or OT. In general, OD innovations involve both technical and administrative innovations in accounting. When OD focuses on technical improvements, accounting innovations address incremental changes that are targeted at formalization, specialization, and efficiency in operations, for example, work structures, processes or procedures, and changes in individual and group behaviors. Damanpour (1987), Damanpour and Evan (1984), and West and Farr (1989) refer to these changes as having micro-orientation, focusing on division and/or departmental structural changes. On the other hand, when OD process innovation is accompanied by transformational changes, accounting changes entail an administrative reform that corresponds to OT intervention strategies. The change is broader and addresses reorientation learning focused on new methods, for example, search for new market opportunities and product innovations, or seek alternative responses to environmental changes. Fox-Wolfgramm, Boal, and Hunt (1998) associated these changes with organizational adaptation commonly pursued by prospector organizations. Davis and Albright (2004) and Speckbacher et al. (2003) argued that BSC is successful in companies that are willing to invest in a longer time horizon to implement

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and realize the benefits of BSC. These characteristics are commonly associated with prospector organizations and support the argument that OD’s administrative innovations promote integrative and systemic changes when the time horizon is longer to support OT organization-wide interventions. Van de Ven (1986) noted several factors that facilitate and inhibit the development of innovations associated with technical and transformational changes. He suggested that ‘‘these factors include[d] ideas, people, transactions, and context over time’’ (p. 591). Molinsky (1999) argued that employees’ mores, customs and cultures can impede the management of organizational change innovations (Silva, Leitao, & Raposo, 2007). Perera, McKinnon, and Harrison (2003) highlighted the importance of the implementation stage of the innovation adoption when organizational values, norms, social systems, and past experiences of adopters affect choice of accounting innovations and their subsequent adoption decisions. Accordingly, differences in institutional and organizational behaviors and cultural processes among institutions of various sizes at either divisional or field levels contribute to variations in the adoption and diffusion of process innovations, for example, new practices, as discussed by Loundsbury (2001) in university recycling programs. It is widely accepted that, in larger organizations, greater structural complexity and interdependence require an emphasis on incremental as opposed to transformational changes. While organizations may prefer incremental approaches because of their desires for short-term, less disruptive improvements, they are more likely to pursue radical transformations of strategic change following a trial-anderror period of unsuccessful incremental changes. They undertake these radical reorientations primarily for two major reasons: first, because of sustained low performance, that is, internal cause; or, second, because of the urgent need to address major technological, social, and environmental changes, that is, external cause (Barley, 1986; Tushman & Romanelli, 1985). Although innovation involves learning, the nature of the learning process does not completely describe the manner in which an innovation affects the organization. Accordingly, we have applied the two interrelated organizational sociological dimensions of innovations processes, namely, (1) the adoption and diffusion theories of Rogers (1971, 1995), to approach organizational learning, and (2) process innovations in management accounting systems: mechanistic, organic, OD and OT innovation typologies.

CHAPTER 7 CONCLUSION AND IMPLICATIONS FOR FUTURE RESEARCH

This chapter integrates the resource-based approach to organizational change and OD based on the organizational learning literature. In the previous chapters, we argued that the level of the organization’s resources can serve to support or constrain learning and innovations in organizations. Resources serve as enablers for innovations and organizational ability and willingness to accept the benefits and/or risks associated with innovation. Depending on resource endowments, the organization likely will be more or less willing to undertake a particular organizational change. In addition we indicate that the perceived need for innovation is driven by the ability of the organization to identify a significant change in its environment. The problem created by the change may be internal or external to the organization. Finally, we point out the important role innovation champions play in moving the innovation from a proposed solution to an identified problem to an activity implemented by all or a part of the organization.

7.1. RESOURCE-BASED APPROACH TO ORGANIZATIONAL LEARNING AND PERFORMANCE The resource-based view of an organization suggests that differences in resources among organizations affect the propensities for organizations to undertake strategic planning initiatives in response to environmental changes. Organizational resources may be used less effectively when organizations engage in ‘‘exploitation’’ of knowledge that they already have acquired or when they try to use their resources to improve the products and/or services they already produce or provide rather than to undertake new or radically 111

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altered activities. Kraatz and Zajac (2001) suggest that organizations relatively well endowed with resources are less likely to engage in major strategic changes to adapt to environmental changes. This, may be because the abundance of (slack) organizational resources may permit them to survive environmental changes without undertaking any strategic changes. These organizations need to respond/innovate only when the environmental change is perceived to create a significant threat to the organization’s survival and/or growth. Kraatz and Zajac (2001) noted that organizations having the most success in the past are the least likely to change their goals because of their commitment to the current strategies that maximize the utilization of existing resources, even in situations that involve environmental uncertainty (p. 636). Most of the time, resources-rich large organizations are more likely to survive external threats from environmental change. Nevertheless, this does not rule out the fact that successful strategic changes are initiated/ undertaken by resources-endowed firms. When resource-endowed firms do undertake a strategic innovation, their superior resources can facilitate the innovation and increase the likelihood of its success. Thus when the resource endowed organizations do undertake the changes, they are likely to be adaptive to change and to benefit from strategic changes. The resource-based view of an organization emphasizes the importance of heterogeneity in a firm’s resources: physical, natural, economic, and financial. It suggests that those firms with heterogeneous resources who possess resources that are non-substitutable, difficult to imitate, and are rare and valuable, have a relative advantage over their competitors. When firms have both the resources and the complementary assets that provide access to both manufacturing and distribution facilities to implement best management practices associated with cost and quality of products and services, they have acquired competitive advantage strategies relative to their competitors. These advantages are related to externalities (liability costs, legal fees, clean-up costs) that support improved organizational performance (Barney, 1988; Christmann, 2000; Rumelt, 1974). Kraatz and Zajac (2001) revealed that, when organizations possess ‘‘valuable and distinctive resources’’, they are ‘‘more reluctant to change strategies in response to environmental changes’’ (p. 648). However, these changes can weaken the positive relationships between strategic change and performance (p. 648). Organizations can take advantage of learning as a competitive advantage to secure control of valuable and scarce resources. Those organizations that can accumulate such diverse or heterogeneous resources through acquisition, imitation, or substitution are able to improve their competitive advantage in the long term to sustain performance.

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Management accounting systems can enhance organizational resources when they are used to develop learning and knowledge systems related to product costs, customer preferences, market sectors, competitive firms, and other economic factors that influence performance. Accounting as an enabler of organizational resources can be integrated into the organization’s activities to improve learning, knowledge, and performance. When accounting systems are based on and utilized to take advantage of the organization’s experience, they can advance the efficiency and cost-saving mechanisms of technological operations. Therefore, accounting systems are critical resources that can help differentiate organizations from their competitors. In general, the resource-based view of the organization stresses capabilities arising from the heterogeneity of resources. It is argued that those organizations that obtain valuable resources that cannot be easily imitated have a competitive advantage over others. To this end, organizational learning can support performance related to resources acquisition, utilization, and capabilities to employ resources for competitive advantage (Uhlenbruck, Meyer, & Hitt, 2003, p. 262). Bapuji and Crossan (2004) have also suggested that organizations with endowment of resources, for example, complex organizations with ample resources, can take risks by managing the costs of innovation and learning (p. 408). However, environmental dynamism, uncertainty, and market volatility increase competition and short-term life cycles of products, which, in turn, increases the demand for innovations. Thus, when external environmental factors generate uncertainty in organizational strategies, structures, and systems, organizational change is desirable. This change requires certain preconditions for intervention and innovation. One of these conditions is the organization’s strategy. For example, Ozomer et al. (1997) described prospectors or market leaders as having an ‘‘aggressive strategic posture’’ that enables them to take risks to meet the demands of the external environment. They already have a propensity for initiating and pursuing innovative strategies. Environmental dynamism and uncertainty shape or create the need to adopt prospectors’ organization strategies and structures accordingly. They observed that the ‘‘strategic posture of the firm is found to be the most important determinant of innovativeness’’ (p. 410). They noted the effect of strategic posture for prospectors who are active interventionists is the initiation and implementation of appropriate strategies that support innovations. Overall, prospectors perceived environmental uncertainty as opportunities for interventions to change/innovate (Ozomer et al., 1997, p. 441).

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The adoption–diffusion literature suggests that external factors and structural mechanisms facilitate diffusion between the source (originator) and the adopter. Strange and Soule (1998) identified both external and internal sources as diffusion-contagious. Among the external sources that are commonly identified in agricultural (Leagans & Loomis, 1971) and pharmaceutical research (Coleman et al., 1966) are ‘‘mass media outlets like the newspaper, TV and radio, and change agents such as the Farm Bureau’s extension agent and the pharmaceutical company’s detail man’’ (Strange & Soule, 1998, p. 271). They have also identified internal influences as arising from ‘‘internal diffusion processes [which] operate via information and influence flowing within the adopting population’’ (p. 272). ‘‘Interaction networks’’ become the main facilitators of diffusion. Interaction, when faceto-face, facilitates the exchange of information creating close ties, cohesion, and influence within the network. Actors and agents play as facilitators. Moreover, actors’ prestige and influence coupled with geographical or spatial proximity aid the diffusion process. When several actors are involved in the diffusion process, Wejnert (2002) argued that competition among actors’ intensifies and their ability to facilitate adoption and to influence decisions depends on the centrality of their location in the network. She suggested that diffusion research must also focus on the actor’s role in and contribution to the diffusion process. Most importantly, it is the actor’s perception of ‘‘the value of an innovation and the actual feasibility of adoption’’ that impacts the diffusion process (p. 319). She associated differences between early (innovators) and later (lagers) adopters with differences in actors’ social and economic characteristics. She proposed that ‘‘an actor’s threshold of innovation accounts for difference of time in adoption’’ (p. 319). Rogers (1995) had noted these differences between early and late adopters as being associated with actors’ social and economic characteristics and positions within the network.

7.2. CONCLUSION: IMPLICATIONS FOR FUTURE RESEARCH In conclusion, we suggest that management accounting researchers pay particular attention to an organization’s approach to adoption and diffusion of innovation strategies, particularly when they are designing and implementing process innovation programs for an organization. The extent (technical and administrative), and the scope (autonomous and systemic)

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dimensions of the innovation processes shape the adoption and diffusion strategies appropriate for the design and implementation of the four typologies or dimensions of management accounting innovations in complex organizations. The innovation process continua can be reflected in a 2  2 contingency framework we outlined in Table 1. It yields four types of innovation change strategies: mechanistic, organic, OD, and OT. In prescribing or describing an innovation, it is, therefore, imperative for managers and accounting researchers to examine the nature of the innovation and the organizational setting. They must take into consideration the relationships among mechanistic, organic OD, and OT by means of the single-loop (incremental) and double-loop (discontinuous) organizational learning strategies. It is important to understand the sequence within which a successful innovation takes place. Schulz (2001) described the sequence of the learninginnovation process in organizations as consisting of two inter-related stages: adoption and diffusion. He related the first stage to the acquisition/ production (adoption) of knowledge that results in gathering information, codification, and exploration. This is followed by the second stage that is the distribution or dissemination (diffusion) processes. In an organization the adoption stage is when the organization acquires the knowledge related to the potential innovation. Diffusion, the second stage, involves the dissemination and transfer of that knowledge from a unit/division to the entire organization. When the two stages – adoption and diffusion – are applied to management accounting innovations, they are related to the two questions commonly associated with the success and/or failures of any innovation. Stage 1 reveals why certain management accounting innovations are more likely to be implemented (adopted) than others. Stage 2 details why the dissemination (diffusion) of some accounting innovations is more successful than others. These two stages of organizational learning-innovation imply that knowledge production (adoption) and distribution (dissemination) processes follow an evolutionary process. Critical to the understanding of the innovation process in management accounting systems in the context of the OD and OT types of innovations is the learning process. Autonomous-division focused (double loop) learning is associated with OD, and systemic-transformational (double loop) learning is associated with OT intervention strategies. Accordingly, the organizational context for either OD or OT change strategy is largely influenced by the scope of the innovation. While both OD and OT focus on the technical and administrative extent dimensions, their differences are associated with

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the scope, defined as the magnitude of change: OD is limited, what we labeled ‘‘autonomous’’, whereas OT is much more broadly applied within the organization. We labeled this as ‘‘systemic.’’ In other words, the scope of the change, autonomous or systemic, affects the mode of organizational learning required by the innovation: single or double loop. While single loop is associated with mechanistic or organic innovations, double loop is prevalent in OD and OT. However, the double loop can have either an autonomous or a systemic scope when it is associated with OD or OT. When the scope is autonomous, the innovation’s impact is limited to individual departments or divisions. It can be accomplished through OD’s (autonomous double-loop learning) intervention strategies of behavioral or cultural changes that affect employees’ behavior through education, training, compensation, and performance evaluation systems, or TQM’s strategy of incremental change. On the contrary, when scope is systemic, it has organization-wide implications. The changes become consonant with OT (systemic double-loop learning) innovation strategy. OT has been associated with BPR that requires radical approaches which necessitate organizational restructuring and job realignment, as well as displacement of employees whose skills might not be consistent with the new jobs or structures. We conclude that, depending on the scope and extent of process innovations, the four types of process innovation strategies – mechanistic, organic, OD, and OT – can be used by a wide range of organizations for successful initiation and implementation (adoption) of accounting innovations. If an innovation will have long-term administrative impact either on the departmental/unit level or at the organizational accounting and reporting functions and most do, we suggest that OD and OT strategies provide the preferred adoption and diffusion strategies to bring about those desired changes. We applied an evolutionary perspective to describe the adoption– diffusion processes of management accounting innovations. Fig. 6.1 outlined the constructs used to trace the process from the demand (adoption) to the diffusion (dissemination) of process innovations. We argue that one of the most critical factors that impacts the understanding of the innovation process and determines the intervention strategies in the context of OD and OT innovations is the learning process: OD as gradual (autonomous) and OT as radical (systemic) double-loop learning. Accordingly, the organizational context for either OD or OT is largely influenced by organizational structural (divisions or units) arrangements for OD or organizational wide for OT.

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When the organization structure is decentralized, the innovation’s impact can be primarily limited to individual departments or divisions. OD then becomes the appropriate intervention strategy when accompanied by the need for behavioral or cultural changes that resemble the TQM approach to incremental change. However, when the structure is centralized, an innovation more likely has organization-wide implications. The changes become consonant with OT-BPR which accompanies radical approaches necessitating longer-term organizational restructuring and job realignment programs. OD and OT strategies thus provide the appropriate adoption and diffusion strategies to accounting innovations depending on the scope of those changes: OD is division oriented while OT has systemic wide changes in organizational accounting and reporting functions. We find that the most important contribution of the adoption–diffusion process innovation framework is in its ability to facilitate the analysis of two critical research questions associated with management accounting innovations. The first question is related to why some innovations are readily accepted, while others, apparently similar and apparently equally desirable proposed innovations, are not? The second question deals with why some particular innovations succeed in some firms when the same innovation fails in others? We have also extended Argyris and Schon’s (1978) and Schultz’s (1998) theory of organizational learning to examine these two interrelated research questions of why some innovations succeed and others fail within the context of adoption and diffusion of ABC and BSC of management accounting innovations as illustrated in Fig. 6.1. We suggest that researchers who attempt to assess the strategic contingency (SF and CF) questions of if and why accounting innovations succeed/fail, should consider the issue of ‘‘organizational fit’’ as well as the usual economic (cost–benefit) factors typically considered (Ittner et al., 2002). Is the proposed innovation consistent with knowledge, norms and structure of the organization? If it is not, the organization must create an environment within the organization appropriate for its successful implementation. An example of the first question is: Why was ABC apparently more readily adopted than the BSC? Both had the goal of improving management’s effectiveness. One could hypothesize that ABC was more amenable to gradual (mechanistic or organic) introduction into the organization’s systems focusing on technical changes. Managers were used to costing systems. As such, ABC represented a more elaborate system. The change was incremental. The type of learning initially required is single-loop focusing on technical change and yields less disruption and resistance from

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members of the organization insuring that the decision will be made on an economic basis. When the innovation is implemented, it initially can be introduced as an incremental change, one that can be limited in both its scope and its breadth of administrative changes (OD single loop). This means that situations which are most likely to benefit from its initiation can serve as the prototype for its adoption by the firm. This minimizes the risk to the organization as well as the costs involved. It also enhances the cost-benefit of the experiment, that is, adopting it on a limited administrative change or reform basis, have an OD-autonomous scope. By contrast, in BSC as an organizational change strategy, OD-systemic is likely to be broad in its scope and breadth. The BSC requires that a single profit-related indicator be augmented with new and unfamiliar indicators reflecting other facets of the organization’s activities. The new indicators differ from the traditional financial measure(s), for example, profit, sales; indicates considered to be subjective non-financial measures, for example, customer satisfaction are considered to be as relevant as objective and more familiar measures, for example, accounting-related numbers. This means that old thinking patterns must be replaced by radical, new approaches. Changes like BSC could be expected to require a more carefully planned and a more costly implementation relative to innovations like ABC. While the potential gains may be significant, they are harder to demonstrate ex ante. By contrast, the potential disruption of the organization’s processes, for example, resistance to the change, is readily apparent to managers ex ante. Thus while both ABC and BSC have the goal of improving management’s effectiveness and improving the organizations long-term profitability, ABC has been more widely accepted than BSC. This likely is the case because ABC is more amenable to single and/or autonomous double-loop learning that requires gradual introduction into the organization’s systems as an incremental change. These changes can be instituted following OD strategy of limited breadth confined to a single division. When they are found to be successful at the division/business unit levels as Ness and Cucuzza’s (1995) described for Chrysler, they are adopted and implemented at the organization-wide levels. On the contrary, the introduction of BSC is expected to require systemic double-loop learning and an OT intervention strategy. This necessitates the development of a comprehensive strategic plan for the innovation with a longer-term time horizon that is more costly to implement by comparison with that of ABC. When accounting innovations call for BSC that require

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OT intervention strategies, the potential disruptions of the organization’s processes, for example, resistance to the changes, are expected to be significant. When systemic double-loop organizational learning strategies result in reorientation and paradigmatic learning changes, accounting innovations become instrumental in instituting transformational changes to replace existing accounting reporting and control systems. The framework can also be applied to issues in financial accounting and reporting. Responses to external reporting issues are typically a financial accounting problem, for example, the reporting of the cost of stock options in the income statement requiring an innovation. These changes often are advocated or initiated by forces external to the organization. These situations also exist in management accounting. For example, the OD-OT framework can be applied to issues in management accounting reporting changes advocated or initiated by forces external to the organization. The current movement toward measurement of environmental and ecological resources management concerns reflects is an example of such issues. The adoption–diffusion framework can thus assist in the understanding of how innovation will be received by the organization. It suggests that the greater the degree of the scope (autonomous or systemic) to which a reporting innovation will impact the activities of the organization, the greater the learning (double loop) effort required in implementing it. The framework can assist in the understanding how the innovation will be received by the organization.

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AUTHOR INDEX Albright, T., 39, 109 Alstyne, M. V., 78 Ambrose, M. L., 6–7, 60, 64 Anderson, S. W., 19, 28, 78, 106–107 Ansari, S. L., 24, 76, 85, 106–107 Antonacopoulou, E., 94 Argyris, C., 10–11, 17, 19, 34, 36, 39, 41–42, 117 Arnold, P., 84 Arthur, J. B., 93–94 Attewell, P., 9, 18, 24, 26, 99

Brown, J. S., 90, 94 Brunsson, N., 20, 24, 104, 107 Bryant, S. E., 92 Brynjolfsson, E., 78 Buller, P. F., 74–75 Burkhadt, M. E., 7 Burns, T., 51–52, 63, 107 Burt, S., 15 Butler, J. E., 15, 26, 28

Bacharach, S. B., 80 Bamberger, P., 80 Banker, R. D., 38, 45–46, 85–86, 103 Baptista, R., 26, 28 Bapuji, H., 11, 91, 95, 113 Barley, S. R., 110 Barnett, W. P., 3, 25, 80, 106 Barron, M., 68 Behery, M. H., 82–83 Benedetto, A. D., 53, 113 Berdrow, I., 94 Bessant, J., 2, 12–13, 35 Bies, R. J., 74 Birnberg, J. G., 13, 22, 39, 41, 48–50, 62, 65, 69, 71, 96, 99 Bischof, J., 39, 109 Blackman, D., 13 Boal, K. B., 109 Boeker, W., 55 Brass, D. J., 7 133

Calantone, R. J., 53, 113 Carroll, G. R., 3, 25, 80 Champy, J., 80 Chan, P., 88 Chia, Y. M., 67 Christmann, P., 112 Coghlan, D., 61, 64 Coleman, J., 20–21, 114 Connelly, J., 13 Cooper, R., 88 Crossan, M., 10–11, 61, 64, 82–83, 91, 94, 95, 113 Cucuzza, T. G., 27, 37, 76, 118 Curry, T. R., 17 Cyert, R. M., 2, 21, 104 Daft, R. L., 24, 44, 66–67 Damanpour, F., 16, 20, 43–45, 66–67, 77, 109 Davenport, T. H., 11, 19, 67 Davidson, W. H., 81–82 Davis, S., 39, 109 Dearing, J. W., 23, 101

134 Dent, J., 105 Dibella, A. J., 12, 79 Dirsmith, W. M., 62, 107 Dixon, J. R., 84 Douglas, D. M., 27 Drake, A. R., 65 Dugdale, D., 19, 33, 65 Dugger, W. M., 56 Duguid, P., 90, 94 Duncan, R., 1–2 Easterby-Smith, M., 94 Elenkov, D. S., 44 Elkjaer, B., 90 Engestrom, Y., 2, 79 Ensley, M. D., 44 Etzioni, A., 55 Euske, K. J., 24, 76, 85, 106–107 Evan, W. M., 16, 43–45, 77, 109 Ezzamel, M., 54–55, 80 Farr, J. L., 20, 109 Ferdinand, F., 94 Fichman, R. G., 9 Fox-Wolfgramm, S. J., 109 Freeman, J., 80, 96 Frenzel, A., 101 Galaskiewicz, J., 56 Galbraith, J. K., 57 Gatignon, H., 22, 31–32, 101–102 Giddens, A., 58 Gloet, M., 43 Glynn, M. A., 8–9, 11, 34 Gort, M., 26, 28 Gosselin, M., 19, 24, 33, 39, 45, 50, 52, 66 Grace, M., 94 Grant, R. M., 91 Grattet, R., 17 Gray, E. R., 4 Grupp, H., 101 Gulden, G. K., 84

AUTHOR INDEX Hage, J., 53, 61, 66 Haka, S. F., 65 Hammer, M., 80 Hannan, M. T., 80, 96 Hansen, M. T., 25, 106 Hanvanich, S., 95 Hargis, K. K., 74 Harrison, G. L., 110 Hartmann, F., 5 Haunschild, P. R., 92 Hauser, K., 80 Heineke, J. L., 84 Hekkert, M. P., 43 Henderson, J. C., 11 Henderson, S., 13 Hennessy, L., 68 Herold, D. M., 2 Herschel, R. T., 27 Herzog, N. V., 80 Higgins, C. A., 33 Hitt, M. A., 113 Holbek, J., 1–2 Houghland, J. C., 63, 82 Howell, J. M., 33 Hull, F., 53, 61, 66 Hult, G. T.M., 10, 95 Hunt, J. G., 109 Huntley, C. L., 93–94 Ittner, C. D., 20, 25, 117 Jacobs, D., 56 Jamali, D., 14, 17, 62 Jayaraman, N., 2 Jenness, V., 17 Jensen, R., 16, 26, 28 Johnson, H. T., 65 Jones, N. B., 27 Jones, O., 79, 94 Jones, T. C., 19, 33, 65 Judge, W., 44 Kabanoff, B., 7

135

Author Index Kajamaa, A., 79 Kandemir, D., 10 Kaplan, R. S., 19, 36, 38–39, 45, 50, 65, 106 Katz, S. E., 20–21, 100, 102, 114 Kemerer, C. F., 9 Kerosuo, H., 79 Kinn, J. S., 84 Kleysen, R. F., 87–88, 93 Kober, R., 62 Koh, H. C., 67 Krackhardt, D., 7 Kratz, M. S., 112 Krishnan, T. V., 99 Kuhlmann, S., 43 Kuhn, T. S., 14, 69 Kumar, V., 99 Kyck, B., 87–88, 93 Lanen, W., 25, 117 Lant, T. K., 8–9, 11–12, 25, 34–35 Lapsley, I., 26 Larcker, D. F., 20, 25, 117 Lawrence, T. B., 87–88, 93 Lawrenson, D. M., 105 Leagans, J. P., 20–21, 100, 114 Lee, S. Y., 38, 45–46, 85–86, 103 Lichtenstein, B. B., 9, 91 Loomis, C. P., 20–21, 100, 114 Lopez, S. P., 9, 88, 92 Lounsbury, M., 110 Lumpkin, G. T., 9, 91 Macpherson, A., 79, 94 Malmi, T., 33, 85–86, 103 March, J. G., 2, 21, 104 Maueus, M. K., 87–88, 93 Maxfield, D. G., 74 McAdams, R., 28 McAllister, J. P., 62, 107 McEvoy, G. M., 74–75 McKinnon, J. L., 110 Menzel, H., 20–21, 114

Metzger, M. B., 8–9 Meyer, K. E., 113 Mezias, S. J., 8–9, 11–12, 25, 34–35 Miner, J. B., 4 Molinsky, A. L., 110 Morgan, G., 7 Morrill, C., 53 Mulligan, P., 84 Naranjo-Gil, D., 5 Narayanaswamy, C. R., 2 Negro, S. O., 43 Ness, J. A., 27, 37, 76, 118 Newman, W. H., 4 Ng, J., 62 Norton, D. P., 36, 38–39, 45, 50, 106 Nystrom, P. C., 4 O’Connor, E. J., 69, 80 Oliva, R., 79 Ordas, C. J.V., 9, 88, 92 Ozsomer, A., 53, 113 Paper, D., 80 Patterson, J., 74 Paul, B. J., 62 Pearce, C. L., 44 Peon, J. M.M., 9, 88, 92 Perera, S., 110 Perrow, C., 24, 54, 58, 63 Pfeffer, J., 21, 104 Pfeiffer, T., 39, 109 Phillips, M. J., 8–9 Polajnar, A., 80 Poole, M. S., 80 Porras, J. I., 74 Porter, M. E., 4, 11, 25–26, 28 Potter, G., 38, 45–46, 85–86, 103 Ravenscroft, S. P., 65 Reck, R. H., 84 Renshaw, A. A., 78 Rhee, M., 92

136 Ribero, J. A., 6, 52 Roberts, N., 74 Robertson, T. S., 22, 31–32, 101–102 Rogers, E. M., 11, 17–21, 23–24, 27, 32, 101, 110, 114 Romanelli, E., 4, 79 Rowe, C., 13, 39, 48–50, 69, 96, 99 Rumelt, R. P., 112 Sandberg, B., 9, 11, 18, 28, 36, 98, 102–104 Scapens, R. W., 6, 52 Schminke, M., 6–7, 60, 64 Schon, D. A., 10–11, 17, 34, 36, 39, 41–42, 117 Schroeder, D. M., 26, 28 Schulz, M., 9, 18, 97, 104–105, 107–108, 115, 117 Scott, W. R., 24, 63 Shepard, J. C., 63, 82 Shields, M., 13, 39, 48–50, 69, 96, 99 Shoemaker, F. F., 11, 17, 19–21, 32 Simon, C., 5 Simon, H. A., 2 Simons, R., 5 Sisaye, S., 5, 8–9, 17, 22, 41, 44, 49, 53, 57–58, 60, 62, 65, 69, 71, 75, 77, 81, 83 Sivakumar, K., 95 Smirich, L., 73 Smits, R. E. H. M., 43 Soete, L., 15 Sohi, R. S., 95 Sonnenstuhl, W. J., 80 Soule, S. A., 1, 26, 29, 68, 114 Speckbacher, G., 39, 109 Srinivasan, D., 38, 45–46 Stalker, G. M., 51–52, 63, 107 Stata, R., 9, 11, 34

AUTHOR INDEX Steiner, G. A., 4 Stommes, E. S., 48–49, 67 Strang, D., 1, 26, 29, 68, 114 Suarez, F., 79 Sussman, S. W., 11 Suurs, R. A. A., 43 Taylor, S., 14 Teece, D. J., 46 Terborg, J. R., 92 Terziovski, M., 43 Thomas, J. B., 11 Thompson, J. D., 54 Tippins, M. J., 95 Tonchia, S., 80 Turner, R., 15 Tushman, M. L., 4, 79 Tzortzopoulos, P., 88 Uhlenbruck, K., 113 Van de Ven, A. H., 12, 35, 69, 80, 110 Van Haaften, W., 14 Vera, D., 10, 61, 64, 82–83 Vogel, D., 56 Weinjert, B., 22–23, 29–31, 60–61, 98, 100, 102, 114 West, M. A., 20, 109 Whitmeyer, J. M., 6 Will, R. A., 26, 28 Williamson, O. E., 54, 96 Willmott, H., 54–55, 80 Windrum, P., 9 Witt, U., 15 Worthington, F., 80 Wright, E., 26 Wright, P., 44 Yasairdekani, M., 4 Yeo, R. K., 51, 89 Young, R. L., 63, 82

137

Author Index Young, S. M., 19, 28, 78, 107 Zajac, E. J., 112

Zaltman, G., 1–2 Zamutto, R. F., 69, 80 Zetka, J. R., 54

SUBJECT INDEX Access to resources, 7 Accounting innovations, xiv, xv, xx, xxi, xxii, xxiii, 3, 4, 11, 18, 19, 21, 24, 26, 27, 29, 33–39, 41, 48–49, 50, 51, 52, 63, 66, 72, 73, 75, 76, 84, 85–86, 99, 103, 104, 107, 109, 110, 115, 116, 117, 118, 119 Accounting innovations lag, 16 Accounting rules, 104–105 birth, 104–105 bureaucratization, 104–105 Acquisition of knowledge, 88, 89, 90, 104 Activity based costing (ABC), xvii, xvi, xvii, xviii, xxi, xxii, xxiii, 4, 19, 20, 24, 25, 26, 27, 28–29, 33, 37–38, 46, 48, 49, 73, 75–76, 77, 81, 83, 85, 99, 103, 106, 107, 108, 117, 118 Activity based management (ABM), 27, 37–38, 99 Adaptation, 12, 31, 58, 59, 73, 88, 89, 91, 97, 98, 101, 109 Adaptive change, xix Administrative hierarchy, 66 Administrative innovations, xviii, 3, 14, 16, 24, 38, 39, 44–46, 50, 63, 66–70, 71, 72, 76–78, 84, 85, 109, 110 Administrative reform, 37, 68, 109 Administrative structures, 41, 53, 68, 74, 77 139

Administrative systems, 36, 41, 56, 78, 84 Adopters of innovations, 32 Adoption of innovations, xviii, 3, 5, 15, 16, 17, 22–29, 31, 50, 67, 77, 95, 98, 100 early adopters, 17, 21 influential adopters, 17, 32 Agents, 1, 15, 19, 23, 26, 27, 30, 49, 61, 67, 74, 75, 99, 101, 114 change agents, 1, 19, 23, 30, 49, 61, 67, 75, 99, 101, 114 organizational development agents (OD), xxi, 25, 50, 71–86, 99, 108, 109, 110, 111, 115–119 Attitudinal changes, 67 Autonomous innovations, xviii, 39, 46, 47, 49, 50, 72, 85 Balanced scorecard (BSC), 4, 36, 38, 39, 45, 83, 98, 108, 109, 110, 117, 118 Barriers to change/innovations, 1 cultural, 68 industrial, 6 management, 28 structural/organizational, 67, 69, 77, 80, 81, 83 Behavioral change, 67, 79, 91 Beliefs, 17, 29, 31, 56, 73, 74, 75, 78, 102

140 Bottom-up change, 45 Bottom-up participation, 75, 77 Boundary spanners, 48 Broad changes, 47 Budgets, 7, 36, 37, 45, 58 Bureaucratic process/behaviors, 58–59 Business process reengineering (BPR), 20, 28, 44, 80–81, 83, 116 Business transformation, 81, 83 Centralization, 3, 24, 55, 56, 66, 98 Centralized structures, 24, 52, 54, 60, 63, 85, 109 Champions of innovations, 27, 30, 32, 49, 93, 97, 102 Change agents, 1, 19, 23, 30, 49, 61, 67, 75, 99, 101, 114 Change champions, 67, 75 Changes block changes, 63 facilitators, 49, 67 Choice among alternatives, 15 Coalition, 15, 21, 30, 55, 56, 60, 104 formation, 21, 104 groups, 56, 60 power, 15, 56 Coercion, 31, 57 Coercive accounting control systems, 54 Cognitive changes, 90, 91 Communication, 1, 10, 14, 17, 23, 29, 30, 32, 61, 64, 67, 68, 77, 80, 84, 90, 99, 100, 101, 102, 104 horizontal, xx lateral, 53, 64 oral, 90 vertical, 44 written, 90 Competitive advantage, xiii, xvi, 9, 10, 11, 28, 34, 91, 92, 94, 95, 112, 113 Complementary assets, 112

SUBJECT INDEX Complex organizations, xiv, 22, 54, 56, 113, 115 Complex structures, xiv, 52, 54, 84, 109, 110 Comprehensive change, xxi, 79 Conflict radical theory, 8–9 Conflict theory of sociology, 5 Consequential, 8, 9, 105 Consultants, 26, 33, 39, 46, 50, 61, 100 Content, 80 Context, 88 Contextual factors, 28, 29, 51, 52 Contingency theory of accounting, 115 Continuous change, 12, 13, 25, 34, 35, 64 Continuum, 36, 39, 41, 42, 46, 47, 71 Control formal control systems, xx, 57, 58, 59, 64, 65, 66 less formal (informal) control systems, 49 Cooperation, 10, 21, 48, 62, 65, 69, 75, 77, 91, 108 Coordination, xix, 3, 36, 38, 45, 48, 50, 54, 55, 57, 59, 60, 61, 63, 64, 65, 76, 87, 89 Corporation, 9, 10, 27, 56, 76 Cost-benefit analysis, 12, 21, 24, 31, 35, 104 Cost management, 106 Cost-saving, 15, 80, 113 Crisis, 57, 58, 59, 97 Crisis management, 57–58 Cultural changes, 59, 68, 69, 74, 75, 77, 79, 88, 100, 104, 116, 117 Cultures, 10, 14, 17, 20, 23, 24, 31, 36, 44, 56, 57, 67, 73, 74, 84, 90, 110 Customers, 3, 10, 59, 103, 113, 118 satisfaction, 118 value, 94

Subject Index Decentralization, 24, 66 Decentralized repair depots, 106 Decentralized structures, 14, 51, 52, 53, 54, 56, 63, 65, 66, 109 Decision-making, xviii, xx, 4,5, 7, 21, 24, 27, 52, 53, 56, 60, 62, 63, 66, 78, 80, 105 Decisions, 4, 5, 6, 7, 11, 15, 17, 22, 23, 24, 31, 48, 53, 56, 63, 66, 83, 85, 86, 92, 105, 110, 114 Defenders, 5, 83 Development economic, 100, 104 political, 4 social, 4 Deviations, 83 Dialectic change, 79 Dichotomous change, 71 Differentiation, xx, 52, 53, 55, 60, 61, 63, 85 Diffusion of innovation, xiii, xvi, 4, 9, 15, 16, 22, 23, 28, 29–33, 56, 85, 87, 92, 98, 104, 109, 114 Discontinuous change, 12–13, 34, 35 Dissemination, 17, 19, 22, 29, 30, 31, 32, 33, 62, 63, 65, 85, 86, 88, 95, 97, 99, 100, 101, 102, 103, 104, 115, 116 Distribution, 7, 15, 17, 27, 31, 88, 95, 97, 112, 115 Divisional/departmental wide changes, 69 Divisionalized structures, 57 Downsizing, 26, 44, 69, 80 Dynamic capabilities, 95 Dynamic change, 13 Dysfunctional, 57, 58, 59 Ecology, 5, 6 Economic factors, 113 Education, 5, 23, 26, 37, 74, 75, 76, 77, 102, 103, 116 Efficiency, 7, 8, 25, 54, 62, 83, 107, 109, 113

141 Employee behaviors/beliefs, 62, 73, 74, 79 Employee resistance to change, 76 Employee suggestions, 93 Enablers of innovations, 2, 69, 111 Enthusiasm, 28, 36, 82, 102, 103 Enthusiastic champions, 102 Environmental changes, 8, 11, 25, 28, 58, 73, 79, 80, 83, 88, 95, 96, 106, 109, 110, 111, 112 Environmental contexts, 31, 64, 98 Environmental factors, 2, 4, 5, 6, 16, 28, 97, 113 external, xix, 4, 28, 97, 113 institutional, 16 internal, 14, 73 organizational, 57 Epidemic, 101 Evolution, 58, 104 Evolutionary change, 39, 77, 79, 83, 97, 104, 109, 115, 116 Exchange, 6, 10, 14, 53, 59, 60, 61, 80, 83, 89, 114 Executive group, 53 management, 53, 97 Experimental study, 39, 109 Expertise knowledge, 90 Externally induced changes, xv Facilitation, 4, 11, 20, 24, 32, 34, 36, 43, 49, 53, 56, 58, 59, 67, 69, 74, 82, 110, 114, 117 Facilitators, 49, 67, 82, 114 Failures, xiv, xxii, 3, 5, 17, 19, 20, 53, 92, 104, 106, 115 Field study, 39, 109 Financial information, 65, 84 Finnish subsidiaries, 85 Firms, 2, 10, 23, 24, 25, 28, 33, 39, 66, 80, 85, 91, 96, 98, 103, 106, 109, 112, 113, 117 Flow of innovations, 17, 32, 63, 108

142 Formal accounting systems, 107 Formalization, xviii, 52, 83, 109 Formal power, 7 Formal rules, 60, 62, 107 Form of organizations, 56 Four I’s of Learning, 87 Functionalism, 55 Functions, xviii, xxii, 7, 46, 47, 49, 54, 58, 65, 69, 71, 72, 80, 81, 83, 84, 94, 96, 107, 116, 117 Gain sharing, 93–94 Gathering knowledge, 95, 97, 115 Geographical factors, 106 Geographical locations, 3, 31 Geographical outlets, 85, 114 Geographical settings, 31 Geographical territories, 30 Globalization, 28, 31, 102 Goal congruence, 57 Goal orientation, 64 Gradual change/learning, 62, 75, 77 Growth, 8, 56, 57, 59, 64, 74, 75, 82, 97, 102, 104, 106, 112 Headquarters, 76, 85, 103, 106 Heterogeneity of resources, 113 Heterogeneous groups, 48 Hierarchical arrangements, xx, 52, 60 Hierarchy, 7, 15, 22, 44, 52, 56, 60, 63, 66, 67, 108 lateral, 53, 60 vertical, xx History of organizations, 68 Homogeneity, 31, 60 Horizontal, xx, 52, 60, 63 Ideas, xv, 1, 8, 10, 13, 17, 20, 26, 29, 53, 69, 74, 82, 89, 90, 93, 100, 101, 102, 109, 110 Identification, 17, 32, 36, 90, 99 Imitation, 100, 112

SUBJECT INDEX Impediments, 4, 85 Implementation, xiii, xiv, xv, xviii, xxii, xxiii, 2, 4, 19, 20, 21, 22, 24, 26, 27, 28, 29, 33, 34, 35, 36, 38, 39, 46, 48, 53, 60, 62, 65, 67, 75, 76, 78, 81, 85, 86, 95, 98, 99, 103, 104, 109, 110, 113, 115, 116, 117, 118 Incentives, 3, 38, 45, 49, 57, 75, 93 Incentive schemes, 38, 45 Incremental changes, xv, xvi, xix, 11, 12, 16, 34, 35, 42, 43, 44, 45, 61, 75, 79, 109, 110, 116, 117, 118 Independent, 44, 52, 55, 65, 96 Inertia, 96 Infections, 101 Information technology (IT), xix, xxi–xxii, 16, 19, 55, 69, 81, 83–84, 95 Innovation champions, 24, 27, 29, 30, 48, 49, 93, 98, 102, 111 Innovation lags, 16–18 Innovations, xv–xvi, 1–18, 19–39, 41–50, 51–70, 71–86, 87–110, Administrative innovations, xviii, 3–4, 14, 16, 24, 39, 44, 45–46, 50, 63, 66–70, 72, 77, 78, 84, 109, 110 autonomous innovations, xviii, 39, 46, 47–48, 72, 85 extent of innovations, xiv, xxiii, 39, 42–45 process innovation typologies, xv, xx–xxi scope of innovations, 41–50 sociological theory, xiii systemic innovations, xix, 37, 38, 39, 42, 46, 48–50, 72 technical innovations, xvii, 21, 42–45, 51, 66, 68, 71, 77, 107 Innovations as learning Input–output analysis, 8, 55, 69, 91

Subject Index Institutionalization, 52, 57, 58, 62, 65, 75, 93, 102 Institutionalizing, 87 Institutional theory, xix Integrating, xiv, xix, 17, 87, 89, 91 Integration, xxi, 11, 13, 45, 64, 67, 72, 84, 88, 89, 91, 93 Integrative change, 110 Interactional justices, 64 Interdependent, 38, 52, 54, 72, 84, 89, 96, 110 Internalization of values, 56 Internally induced changes, 92 Internal resources, 43, 114 International migration, 14 Interpersonal relationships, 65, 107 Interpreting, 87 Intervention adaptation, 101 Intervention strategies, 25, 73, 74, 75, 78, 86, 109, 115, 116, 119 Interventions, xxi, xxii, 2, 61, 73, 74, 75, 78, 79, 85, 86, 93, 108, 109, 110, 113, 116, 118–119 Intra-organizational innovations, 43 Intuiting, 87 Investment, 15, 16, 28, 66 Job-related tasks, 54 Just-in-time technology (JIT), 20 Knowledge acquisition of new skills/behaviors, 91, 95 Knowledge transfer, 89 Large scale, 52, 60, 66, 108 Leadership, 36, 44, 50, 57–58, 67, 74, 82, 88, 100, 102 characteristics, 5, 58 performance, 75, 83 Lead–lag effect, 100 Learning group, 82, 90, 91 individual, 90

143 psychological, 88, 90–91 social, 90 sociological, 91–97 Legal factors, 21, 31 Legitimacy, 6, 52, 55 Long term change, 9, 27, 36, 57, 79, 94, 103, 112, 116, 118 Machine metaphor, 7 Management accounting innovations, 19, 21, 26, 29, 33–39, 50, 51, 52, 72, 84–86, 104, 115, 116, 117 Management accounting systems, 5, 19–39, 51, 57, 65, 69, 70, 75, 98, 109, 113, 115 Management consultants, 26, 33 Management control systems, 17, 28, 36, 57, 58, 59, 62, 65, 70 Management hierarchy, 44, 52, 60, 67 Management styles, 23, 30, 82 Management, characteristics, 6 goals intensity, 66 Marketing management, 19 Market segments, 31 Mass communication, 30 Mass media, 30, 102, 114 Matrix structures, 53 Mechanistic innovations, xx, 52, 56, 60–63, 66, 107, Mechanistic structures, 16, 52, 55, 60, 61, 62, 64, 66 Mentoring, 92 Micro-orientation, 109 Mores, 110 Narrow changes, 5, 47 Non-financial measures, 38, 39, 108, 118 Norms, xvii, 12, 17, 24, 31, 35, 49, 59, 60, 73, 82, 83, 88, 89, 107, 110, 117

144 Operating budgets, 37 Operating systems/changes, 16, 75, 83, 107 Opinion leaders, 17, 21, 23, 27, 29, 32, 97, 100–101, 102, 103 Organic innovations, xx, 50, 51, 63–66, 70, 116 Organic structures, xx, 53, 63, 64–65, 66 Organizational adaptation, 79, 88, 89, 109 Organizational behavior, xiii, 11, 19, 32, 34, 79, 88, 110 Organizational constraints, 16 Organizational culture, 44, 57, 58, 82, 83, 84, 89, 107 Organizational design, 34 Organizational development, xxi, 25, 50, 70, 71–81, 84, 85–86, 109, 115–118 Organizational fit, 117 Organizational form, 3 Organizational interdependence, 52, 54, 96 Organizational knowledge, 10, 13, 34, 43, 89, 91, 115 Organizational learning, xvi–xvii, 9–14, 33–39, 87–110, 111–114 double loop learning, xvii, 6, 12–14, 33, 35–39, 75, 108, 118 gradual learning, 23, 85 incremental learning, 8, 10, 14, 105 single loop learning, xvi–xvii, 6, 11–12, 33, 34–35 transformational learning, 38 Organizational norms, 59, 83 Organizational performance, 5, 7, 11, 13, 14, 17, 25, 34, 49, 56, 58, 64, 68, 75, 77, 84, 88, 89, 92, 96, 112 Organizational processes, 1–18, 38 Organizational renewal, 94

SUBJECT INDEX Organizational resources, 4, 5, 7, 49, 60, 91, 95, 111, 112, 113 Organizational size, 24, 52, 55, 56, 57, 60 Organizational structural arrangements, 44, 52–53, 66, 67 Organizational structures, 6, 7, 36, 41, 45, 50, 51, 52, 55, 56, 63, 64, 65–70, 79, 81, 84, 85, 109 Organizational transformation, xxi, 71–86, Organizational wide changes, 103 Paradigm changes, 13, 14 Participation, 63, 68, 69, 74, 75, 77, 90, 102 Peers, 15, 92, 97, 100 Performance-based compensation, 103 Performance, 3, 4, 5, 7, 9, 10, 11, 12, 13, 14, 17, 20, 25, 28, 34, 36, 37, 46, 49, 50, 52, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 68, 69, 70, 71, 73, 74, 75, 76, 77, 80, 81, 82, 83, 84, 85, 88, 89, 91, 92, 93, 94, 95, 96, 97, 103, 107, 109, 110, 112, 113, 116 Personal growth, 74 Personal influence, 31, 101 Personnel, 67, 77, 78 Persuasion, 23, 37, 76, 93, 100, 104 Planned intervention changes/ strategies, 28, 63, 73 Planning, 2, 37, 38, 45, 47, 50, 55, 62, 65, 75, 77, 88, 106, 107, 109, 111 Political power, 15, 56, 104, 106 Population ecology, 3 Positions, 2, 7, 23, 45, 58, 114 Power, 6, 7, 15, 16, 17, 23, 45, 52, 55, 56, 60, 66, 79, 93, 106 Prescriptions, 62 Procedural change, 62, 75, 77

Subject Index Procedures, 2, 6, 10, 12, 13, 16, 20, 35, 36, 52, 57, 59, 60, 61, 62, 83, 87, 88, 92, 93, 95, 107, 108, 109 Process innovations, xv–xvi, 5, 7, 11, 17, 19–39, 41–50, 57, 66, 70, 71–86, 87–110, 116 Process reengineering, 20 Product development, 27, 38, 48, 108 Profitability, 24, 27, 59, 62, 70, 108 Programmable functions, 62, 107 Programmed solutions, 105 Psychological dimensions of learning, 90–91 Quality management, 20 Radical change/learning, xix, xxi, 8, 10, 13, 35, 36, 75, 79, 81–83 Recycling programs, 110 Relationships, 2, 6–7, 8, 9, 15, 25, 27, 32, 38, 50, 60, 61, 62, 65, 66, 69, 80, 89, 90, 92, 96, 107, 112, 115 Remedies, 83, 93 Researchers, 4, 7, 9, 19, 20, 21, 26, 33, 39, 50, 100, 114, 115, 117 Resistance to change, 3, 48, 76, 79, 82, 93, 97, 106 Resources based view of the firm, 111, 112, 113 Resources endowed, 112 Resource sharing, 62 Resources, 2–3, 4, 5, 7, 8, 13, 15, 16, 17, 23, 24, 25, 29, 44, 48, 49, 52, 56, 58, 60, 80, 84, 88, 91, 94, 95, 108, 111, 112–113, 119 abundance, 112 constraints, 2, 3 sharing, 48 slack, 2, 23, 29, 112 Restructuring, 44, 69, 80, 94, 116, 117

145 Returns on innovation investment decreasing returns, 32 Revolutionary change/learning, 79 Reward allocation mechanisms, 62 Rewards, 3, 4, 44, 58, 74, 75, 93 Risks, 2, 5, 15, 21, 23, 24, 28, 29, 59, 82, 83, 89, 111, 113 Routines, 2, 10, 13, 61, 96, 105, 107 Rule making, 105 Rules, 7, 13, 36, 49, 56, 57, 58, 59, 60, 62, 63, 73, 83, 84, 87, 88, 96, 104–105, 107, 108 Scarce resources, 4, 112 Simultaneous change, 78 Size, 24, 28, 31, 32, 52, 53, 55, 56, 57, 60, 66, 98, 107 Slack resources, 2, 23, 29 Social-contagion effect, 102 Social identity, 90 Social influence, 100 Socialization, 31 Social systems, xviii, 6, 7, 8, 29, 31, 32, 55, 58, 73, 90, 101, 110 Sociology, xiii, xiv, xv, xx, 3, 4–9, 11, 19, 20, 21, 22, 32, 41, 42, 51, 58, 73, 87, 103 contingency theory of sociology, 4–9 Specialization, xx, 24, 55, 61, 109 Sprinkler strategy, 100 Standalone innovations, 63, 108 Standardized systems, 59, 61, 102 Strategic learning, 10, 11 Strategic management, 5 Strategic planning, 37, 47, 55, 106, 111, 118 Stratified, 60 Structural functional (SF) theory, 5, 6–8 Structures, xx, xxi, 2, 6, 7, 9, 14, 15, 16, 17, 20, 23, 24, 27, 29, 36, 41, 42, 43, 44, 45, 49, 51, 52, 53, 54,

146 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 68, 70, 71, 74, 77, 78, 79, 81, 84, 85, 87, 93, 94, 98, 102, 106, 109, 113, 116 mechanistic, 16, 52, 55, 60, 61, 62, 63, 64, 66 organic, xx, 53, 63–64, 65, 66 Subordinates, 60, 63, 100 Success, xiv, xxii, 5, 16, 19, 20, 22, 27, 31, 38, 43, 44, 47, 50, 51, 53, 56, 66, 67, 68, 75, 81, 91, 94, 99, 109, 112, 115 Superordinate, 63 Supervision, 106 Supervisory trust, 64 Survival, 8, 112 Systemic innovations, xix, 37, 38, 39, 42, 46, 48, 49, 51, 72 Systemic learning, 81, 86, 99 Systems view of organizations, 6, 7, 73 Task complexity, 52 Task coordination, 54 Task orientation, 7 Tasks, xviii, xx, 44, 52, 53, 54, 60, 62, 63, 66, 71, 83, 88, 107 Teams, 7, 14, 27, 32, 53, 54, 55, 56, 57, 58, 64, 65, 67, 68, 69, 81, 92 cross functional teams, 54, 58 Technical change, xvii, 41, 42, 85, 117 Technical innovations, xvii, 21, 42– 45, 51, 66, 68, 70, 71, 77, 85, 107 Technical styles, 23, 30, 82 Techniques, xvii, xxi, 2, 34, 43, 54, 77, 80, 81 Technocratic, 57 Technological change, 15, 28, 43, 47, 49, 96 Technological innovations, xviii, xxi, 10, 14, 15, 19, 21, 28, 43, 47, 48, 55, 58, 69, 80

SUBJECT INDEX Technological know how, 17 Tightening, 62 Top-down, 44, 45, 69 Top management, 5, 10, 27, 28, 29, 44, 52, 66, 67, 81, 98, 99, 103, 106 Total quality management (TQM), xvi, 20 Traditional, 38, 39, 54, 55, 61, 62, 67, 76, 108, 109, 118 Training, xviii, 67, 74, 75, 77, 90, 91, 92, 95, 116 formal, 90 less formal (informal), 24, 53, 85 Transactions exchange, 83 Transfer of technology, 102 Transformational change, xvii, xxiii, 3, 35, 44, 80, 82, 109, 110, 119 Transformational leaders, 64, 82 Transformational learning, 36, 38 Trialable, 24, 43 Trial and error strategy, xvii, 2, 16, 34, 35, 37, 96, 103 Trust, 64, 65, 82 Uncertainties, 14, 15, 78, 83, 108 Units, xiv, xx, 3, 6, 24, 32, 35, 37, 38, 39, 41, 42, 46, 47, 48, 50, 51, 53, 54, 55, 56, 62, 63, 65, 66, 72, 73, 75, 80, 84, 86, 94, 96, 97, 103, 107, 108, 109, 116 Unknowns, 5, 12, 78 Value added processes, 82 Values, 5, 17, 31, 35, 48, 49, 56, 64, 67, 68, 73, 74, 78, 80, 82, 94, 100, 102, 105, 107, 110 Vertical, xx, 44, 52, 60, 85 Volatile, 57, 96 Waterfall strategy, 99 Workflow, xx, 52–53, 60, 61 Work functions, 55–56 Work structures, 20, 54, 109