The Future Opportunities and Challenges of Business in Digital Era 4.0 (ICEBE 2019) 9780367425944, 9780367853778

Citation preview

THE FUTURE OPPORTUNITIES

AND CHALLENGES OF BUSINESS

IN DIGITAL ERA 4.0

Edited by

Satria Bangsawan, Mahrinasari MS, Ernie Hendrawaty,

Rindu Gamayuni, Nairobi, Hendrati Dwi Mulyaningsih,

Ani Wahyu Rachmawati and Santi Rahmawati

THE FUTURE OPPORTUNITIES AND CHALLENGES OF BUSINESS IN DIGITAL ERA 4.0

PROCEEDINGS OF THE 2ND INTERNATIONAL CONFERENCE ON ECONOMICS, BUSINESS AND ENTREPRENEURSHIP (ICEBE 2019), BANDAR LAMPUNG, INDONESIA, 1 NOVEMBER, 2019

The Future Opportunities and Challenges of Business in Digital Era 4.0

Edited by Satria Bangsawan, Mahrinasari MS, Ernie Hendrawaty, Rindu Rika Gamayuni & Nairobi Faculty of Economics and Business, University of Lampung, Indonesia

Hendrati Dwi Mulyaningsih Universitas Islam Bandung, Bandung, Indonesia Research Synergy Foundation, Bandung, Indonesia

Ani Wahyu Rachmawati International Women University, Bandung, Indonesia Research Synergy Foundation, Bandung, Indonesia

Santi Rahmawati Research Synergy Foundation, Bandung, Indonesia

Routledge is an imprint of the Taylor & Francis Group, an informa business © 2020 Taylor & Francis Group, London, UK Typeset by Integra Software Services Pvt. Ltd., Pondicherry, India All rights reserved. No part of this publication or the information contained herein may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, by photocopying, recording or otherwise, without written prior permission from the publisher. Although all care is taken to ensure integrity and the quality of this publication and the information herein, no responsibility is assumed by the publishers nor the author for any damage to the property or persons as a result of operation or use of this publication and/or the information contained herein. Library of Congress Cataloging-in-Publication Data Names: International Conference on Economics, Business and Entrepreneurship (2nd : 2019 : Bandar Lampung, Indonesia) | Bangsawan, Satria, editor. Title: The future opportunities and challenges of business in digital era 4.0 : proceedings of the 2nd International Conference on Economics,

Business and Entrepreneurship (ICEBE 2019), Bandar Lampung, Indonesia,

1 November, 2019 / edited by Satria Bangsawan [and seven others].

Other titles: Proceedings of the 2nd International Conference on Economics, Business and Entrepreneurship Description: Leiden, The Netherlands : CRC Press/Balkema, [2020] | Includes bibliographical references and index. Identifiers: LCCN 2020028655 (print) | LCCN 2020028656 (ebook) | ISBN 9780367425944 (hardback) | ISBN 9780367853778 (ebook) Subjects: LCSH: Technological innovations–Economic aspects–Congresses. | Information technology–Economic aspects–Congresses. Classification: LCC HC79.T4 I57745 2019 (print) | LCC HC79.T4 (ebook) | DDC 658.4/063–dc23 LC record available at https://lccn.loc.gov/2020028655 LC ebook record available at https://lccn.loc.gov/2020028656 Published by: CRC Press/Balkema Schipholweg 107C, 2316XC Leiden, The Netherlands e-mail: [email protected] www.crcpress.com – www.taylorandfrancis.com ISBN: 978-0-367-42594-4 (Hbk) ISBN: 978-0-367-85377-8 (eBook) DOI: 10.1201/9780367853778 https://doi.org/10.1201/9780367853778

The Future Opportunities and Challenges of Business in Digital Era 4.0 – Bangsawan et al. (eds) © 2020 Taylor & Francis Group, London, ISBN 978-0-367-42594-4

Table of contents

Foreword

xi

Organizing committee

xiii

Scientific review committee

xv

Role of open innovation in enterprise growth G. Rexhepi

1

Organizational commitment and job satisfaction: The leadership role of leader-member exchange in SMEs H. Jimad & Roslina Towards a framework for tourism entrepreneurship sustainability: Implications for future research G. Anggadwita, A.A. Budi, L. Aldianto, S. Novani, C. Wirawan & W.B. Profityo

7

11

The Enhanced performance strategy of Indonesian small entities R. Septiyanti

16

Marketing strategy of electronic transaction services at an Indonesian retail company Haikal, Mahrinasari MS & E. Herdrawaty

20

Confirmation of contingency theory in the implementation of good governance and its impact on government performance in Indonesia Sudrajat

24

The impact of electronic word of mouth in influencing online product-purchase intentions on e-commerce A. Febrian, S. Bangsawan, Mahrinasari MS & A. Ahadiyat

28

Spiritual wisdom in beach management: Best practice from Bali, Indonesia A.W. Handaru

32

Herding behaviour on the Indonesia Stock Exchange in the period 2013–2017 H. Prayogi

36

Characteristics of politically connected companies in Indonesia K. Syaputra, M. Kufepaksi & E. Hendrawaty

40

The impact of trust, satisfaction, and people’s pride on purchasing intention in the Indonesian batik sector K. Keni, R. Lerbin, R. Aritonang & A.S. Pamungkas

44

Income smoothing on market reaction: Environmental performance as a moderation variable Y. Pietricia, C. Helinawati, Lindrianasari & R. Oktavia

49

Risk-taking model in Indonesian banking companies R.D.Z. Putri, S. Hasnawati & E. Hendrawaty

v

53

The effect of spot exchange rate and forward exchange rate on projection of futures spot of Rupiah on Dollar currencies D.S. Warganegara, A. Zahron, E. Mirfazli & O. Pasko

58

Carbon emissions and corporate social and environmental responsibility R. Majidah, Lindrianasari & A. Komalasari

62

Information technology investment and digitization to improve banking performance M. Trimeranti, R.R. Gamayuni & T.J. Prasetyo

66

Determinant factors of stunting conditions on Indonesian economic growth H. Purnama

70

Carbon emissions disclosure, market reaction, and dividend policy Y. Asmaranti & Lindrianasari

74

“Wonderful Indonesia” positioning branding as a place of interesting tourism H. Fauziah

77

Improving business performance through financial technology and customer relationship management Suradi

81

Consumer characteristics and the effects of social factors on purchasing decisions of Kentucky Fried Chicken (KFC) eco-friendly products M. Ali, S. Bangsawan & D. Rouly

86

Convergency of revenue per capita regional New Autonomy (NAR) in Indonesia Ambya

90

Banking performance and shock response of macroeconomic conditions in Indonesia M.K.I. Febriana, R. Malia & S.N. Herlina

94

Foreign investment (PMA) in the food and beverage industry (KBLI15) in Indonesia period 2000 – 2014 Total Factor Production approach (TFP) L.M. Hamzah

97

The effectiveness of business development for rural agricultural business and its effect on the income of farmers group members in Wates Jaya, Lampung Barat District M. Husaini & M.T. Fani

100

The influence of households and labor in fishery industry on industrial agglomeration in Tanggamus District E. Maimunah, A.D. Pratama & U. Ciptawaty

104

An experimental study of the gender differences in risk aversion portfolio selection in Indonesia I.C. Putri, A. Komalasari, Farichah & R.R. Gamayuni

108

Forecasting tourism demand using the trend models method: Evidence from Indonesia H. Kusumastuti, Novalia & A. Anum

112

The impact of mandatory spending on economic growth in Java and Sumatra A. Ratih Yulihar Taher, H.N. Syahputra & A. Darmawan

116

A comparative analysis of Flow of Funds Account (FFA) presentation in Indonesia and Japan F. Zamzami & D. Oktyawati The effect of ethnocentrism and preference of purchase intention D.E. Laofa

vi

119 124

Influence of quality service and satisfaction imagery higher education on Word of Mouth (WOM) G.A. Pranoto, S. Bangsawan & D.H.R. Pandjaitan Electronic Data Capture (EDC) marketing strategy in an Indonesian state-owned bank E. Weliyanti, Mahrinasari MS & E. Herdrawaty

128 133

The influence of level of service on commitment to implement Islamic tourism with religiosity as a mediating variable K.B. Riyanto, S. Bangsawan, Mahrinasari MS & Ribhan

137

The factors that determine consumer’s intention to use the service of the Amil Zakat institution I. purnomowati, Mahrinasari MS, D.A.I. Budiarty & T. Prasetyo

142

International investment diversification in Asean-5 countries after Asean Economic Community (AEC) Febriyanto, M. Kufepaksi & Marselina

147

An application of rapid agricultural risk assessment to manage citrus nobilis var. microcarpa damage in Indonesia F.D. Rizkina & K.H. Widodo

151

Corporate tax aggressiveness: Antecedents and consequent N.D. Kesumaningrum Investor reaction to earnings announcements moderated by management discussion and analysis (MD&A) M. ayu, Lindrianasari & F. Dharma Gapoktan performance is determined by SCM practices, TQM, and competitive strategy N. Husna, Y. Azis, U. Kaltum & P. Ananta

155

159 163

Digital economy challenge: Innovation of technology and unemployment dilemma in Indonesia E.L. Widarni, Murniati, S.A. Prestianawati & Suryaning

167

Estimation of economic value of mangrove forest in Lampung province using choice modeling approach (case study of Lampung Timur district) T. Gunarto, Z. Emalia, R.M. Putri & M. Ona

171

Consumer behavioral condition shares (Theory of Planned Behavior) L. Yulisa, S. Bangsawan & Ribhan

174

The fish demand at fish auction sites in Lampung: Implementation of the Quadratic Almost Ideal Demand System (QUAIDS) model P. Ananta, D. Jayanti, S. Pandjaitan & U. Ciptawaty

179

The relations of family ownership, characteristics of board of directors, and company performance L. Purnamasari, S. Hasnawati & E. Hendrawaty

183

Government intervention and investment efficiency in indonesian companies D.H. Denta, M. Kufepaksi & E. Hendrawaty

187

Cash holdings estimation model for non-financial companies in Indonesia E. Hendrawaty

191

Adoption of digital finance service in Indonesia: An empirical examination of an extended technological acceptance model E. Hendrawaty & S. Bangsawan

vii

196

Initial public offerings news in social media and investor sentiments E. Hendrawaty, Yuliansyah & E. Pranyoto

200

Moderating role of “consumer characteristics” in the influence of customer satisfaction on loyalty Mahrinasari MS & D.H.R. Pandjaitan

205

Simultaneous relationship between financial decisions, size and value of a company on the Indonesia stock exchange S. Hasnawati

210

The analysis of corporate bond liquidity in the Indonesia secondary market S. Hasnawati

214

The usefulness of accrual-based financial statements at local government R.R. Gamayuni

218

Impact of risk, commitment, and bonus on completion of difficult targets: Carbon emissions case Y. Agustina, D. Sukmasari & T.D.R. Sari

222

The influence of integrated quality management on employee performance and creativity in higher education ISO certified SMM 9001: 2015 F.T.A. Ningtyas, Rr. Erlina & K. Hayati

227

The size and value effect anomalies in Indonesian capital market M. Kufepaksi, S. Hasnawati & E. Hendrawaty Determinants of government financial statements quality with moderating variables in leadership commitment E.N. Septiany, I. Lihan & E. Hendrawati Understanding the business model of social enterprise: Case study of Indonesia Mengajar A.R. Qastharin & G. Vanourek The spatial effect on the provincial wage increasing in Indonesia (data analysis of Sakernas 2008-2010) I. Budiarty A study of village fund management to achieve good governance F. Suffah, R.R. Gamayuni & F.G. Dewi

231

235 239

244 249

Analysis of factors affecting interests in the use of regional financial management information system (SIPKD) N. Kusumawardani

253

E-planning, e-budgeting, and government internal control system as a corruption prevention tools in Indonesia F. Yuliant, W. Setyawan, R.R. Gamayuni & T.J. Prasetyo

257

Exploration of good governance on the minimization of corruption in Asia-Pacific S.N. Fathia, R.R. Gamayuni & T.J. Prasetyo

262

Enhancing the role of higher-education institutions in developing technology-based start-ups for young entrepreneurs at the Institute of Informatics & Business (IIB) Darmajaya M. Agarina, Susanti, H. Kurniawan, Yusminar, E. Pranyoto, S. Rumangkit & M. Ariza

266

The influence of household characteristics on poverty alleviation through tourism development N. Aida

270

viii

Forecasting the performance of volatility of share prices with the application of ARIMA model F.S.D. Kesumah, R. Azhar, E. Russel & F.K. Wisnu

275

Dividend policy of agency cost models in companies listed on the Indonesia Stock Exchange U. Muharramah, M. Kufepaksi & E. Hendrawaty

280

The effect of cellular marketing and consumers’ attitude toward buying dunkin’ donuts in Bandar Lampung D.H.R. Pandjaitan

284

Green marketing’s effect on the decision to purchase body shop cosmetic products in Bandar Lampung D.H.R. Pandjaitan & Mahrinasari MS

287

Effects of educational performance, political competition, and regional financial capacity on incumbents’ votes in Indonesian local elections (a hierarchical regression analysis) F. Dharma, A. Syakhroza & D. Martani

291

Influence of commitment in supporting the innovative work behavior of MSME employees in Bandar Lampung Yuningsih

295

The impact of financial literacy on the performance and sustainability of SMEs in Indonesia Y. Amelia, P. Nauli & N. Desriani

299

Factors affecting financial management behavior in the millennial generation A.S. Gahara, R.R. Gamayuni & U. Syaifudin

303

Measuring the effect of environmental uncertainty on the performance of SME managers with a management accounting system Y. Agustina

307

The role of business group in mitigating agency theory caused by excess cash holdings N.P. Dalimunthe, M.N. Wulan & S. Paujiah Testing of Investment Opportunity Set (IOS), firm size, and risk of investment as variables that affect dividend policy in property and real estate companies listed on the Indonesia Stock Exchange (BEI) during the 2013–2017 period H. Wiweko, I. Febrianto & S.P. Darayani

310

314

Performance analysis of vehicle tax payment system queue Rr. Erlina & F. Shofa

318

Consumers attitudes and environmental knowledge toward friendly products D. Wiryawan & H. Novrian

321

The impact of training, career development, and compensation on employee performance E. Simanjuntak, Rr. Erlina & N. Mardiana

324

The effects of entrepreneurial orientation and competitive advantage on the international market entry through financing I. Sadalia, H. Muharam & A. Mulyana Opportunities and challenges of the protean career concept: A review and future agenda S. Bakhri, Suharnomo & Mahfudz

328 333

The influence of Emotional Quotient (EQ), Intellectual Quotient (IQ), and Spiritual Quotient (SQ) on SME employee work performance at Bandar Lampung City N. Mardiana & D. Safitri

338

Author index

342

ix

The Future Opportunities and Challenges of Business in Digital Era 4.0 – Bangsawan et al. (eds) © 2020 Taylor & Francis Group, London, ISBN 978-0-367-42594-4

Foreword

The Faculty of Economics and Business of Universitas Lampung, in cooperation with the Research Synergy Foundation, organized the 2nd International Conference of Economics, Business and Entrepreneurship (2nd ICEBE). An international conference which had the theme “Future Opportunities and Challenges of Business in Digital Era” was attend by lec­ turers, students, and professionals from various countries, such as Indonesia, Australia, Malaysia, Macedonia, and India. Three invited keynotes speakers were welcomed to give lecture for an audience of a hundred researchers, academics, and professionals. Dr. Muhammad Haseeb (Senior Lecturer at Taylor’s Business School, Taylor’s University Lakeside Campus, Subang Jaya Selangor, Malaysia), Hus­ sain Rammal, Ph.D (Director of the Master of Business Administration (MBA) and coordin­ ator for the Bachelor of Business - International Business programs, UTS Business School) and Gadaf Rexhepi, Ph.D. (Associate Professor at South-East European University, Republic of Macedonia). The conference particularly encouraged the interaction of mostly practitioners and some aca­ demics with the developing academic community in the public sector to present and discuss their current work. Their contributions helped to make the Conference as fruitful as expected. The papers presented the most recent scientific knowledge available in the field of Business Administration, Behavioural Economics, Economic Development, Econometrics, Financial Accounting, Management, Management Accounting, Micro, Small and Medium Entrepre­ neurship, Public Sector Accounting, Social Entrepreneurship and Startup Entrepreneurship Research. These Proceedings will enrich the academic environment with the latest developments in public sector research. I believe that this will be a pathway to collaborate with other researchers from various disciplines and various parts of the world. We hope that knowledge and best practices discussed in the seminar and published in its pro­ ceeding will enrich the reference for all experts in the field of education and accordingly stimu­ late further researches in wider areas. We thank all authors and participants for their contributions. Conference Chair, Dr. Mahrinasari MS

xi

The Future Opportunities and Challenges of Business in Digital Era 4.0 – Bangsawan et al. (eds) © 2020 Taylor & Francis Group, London, ISBN 978-0-367-42594-4

Organizing committee

Conference Chair: Dr. Mahrinasari MS Co-Conference Chair: Dr. Hendrati Dwi Mulyaningsih Conference Coordinator Santi Rahmawati Ani Wahyu Rachmawati Conference Support Diah Kusumastuti Astri Amanda Rifi Wijayanti Dual A. Information and Technology Support by Scholarvein Team

xiii

The Future Opportunities and Challenges of Business in Digital Era 4.0 – Bangsawan et al. (eds) © 2020 Taylor & Francis Group, London, ISBN 978-0-367-42594-4

Scientific review committee

Dr. Mahrinasari MS Universitas Lampung, Indonesia Dr. Ernie Hendrawaty Universitas Lampung, Indonesia Prof Sutinah Made Hasanuddin University, Indonesia Prof Wellem Anselmus Teniwut Tual State Fisheries Polytechnic: Langgur, Maluku, Indonesia Dr Mirwan Surya Perdhana Diponegoro University, Indonesia Dr. Abdusalam Faraj Yahia Oman Chamber of Commerce and Industry, Oman Dr Eric Agullana Matriano Columban College, Inc, Philipines Prof. Thanh Huynh Bournemouth University, England Dr. OmKumar Krishnan IIM Kozhikode India Engr. Dr. Muhammad Mujtaba Asad Universiti Tun Hussein Onn, Malaysia Dr. Farichah Universitas Lampung, Indonesia Dr. Rindu Rika Gamayuni Universitas Lampung, Indonesia Dr. Fajar Gustiawaty Dewi Universitas Lampung, Indonesia Prof. Dr. Satria Bangsawan Universitas Lampung, Indonesia Dr. Ambya Universitas Lampung, Indonesia Dr. Marselina Universitas Lampung, Indonesia Dr. Thariga Pholloke Khon Kaen University, Thailand

xv

Dr. Eric Agullana Matriano Columban College, Inc. – Phillipines Dr. Rakan Fuad Aldomy Multimedia University/ Fom, Malaysia Prof. Li-Jiun Chen Feng Chia University, Taiwan Dr. Abdusalam Faraj Yahia Oman Chamber Of Commerce And Industry, Oman Dr. Thanh Huynh Bournemouth University, Uk Prof. Chia Pin Kao Southern Taiwan University Of Science And Technology, Taiwan Dr. Siti Nur ‘Atikah Zulkiffli Universiti Malaysia Terengganu, Malaysia Prof. Omkumar Krishnan Iim Kozhikode India, India Dr. Jirawat Wongthongchai Khon Kaen University, Thailand Dr. Solomon Nathaniel University of Lagos, Nigeria Prof. Harshit Prakashbhai Bhavsar Gujarat Technological University/ Sal College of Engineering- India Prof. Dr.Rashmi Gujrati Kc Group of Institutions, India Dr. Ranawaka Arachchige Ravin Sachindra De Alwis University of Kelaniya, Srilanka Dr. Wajid Zulqarnain Szabist | Shaheed Zulfikar Ali Bhutto Institute of Science and Technology, Pakistan Dr. Noorlizawati Abd Rahim Universiti Teknologi Malaysia, Malaysia Dr. Supachart Iamratanakul Kasetsart Business School, Thailand Dr. Normia Akmad Salindal Cotabato City State Polytechnic College, Phillipines Prof. Dr Muraina Kamilu Olanrewaju Al-Hikmah University Ilorin, Nigeria Prof. Bhagwan Das Quaid-E-Awam University of Engineering, Science & Technology, Nawabshah, Pakistan Dr. Siti Nur’ Atikah Zulkiffli Faculty of Business, Economics and Social Development, Universiti Malaysia Terengganu, Malaysia

xvi

Prof. Jessie I. Quierrez Polytechnic University of the Philippines, Phillipines Prof. Salina Daud Universiti Tenaga Nasional (UNITEN), Malaysia Engr. Dr. Muhammad Mujtaba Asad Universiti Tun Hussein Onn Malaysia, Pakistan

xvii

The Future Opportunities and Challenges of Business in Digital Era 4.0 – Bangsawan et al. (eds) © 2020 Taylor & Francis Group, London, ISBN 978-0-367-42594-4

Role of open innovation in enterprise growth Gadaf Rexhepi Faculty of Business and Economics, South East European University, Republic of North Macedonia

ABSTRACT: Open innovation tends to be one of the fastest-growing fields lately. Many excellent results from its implementation and the quickly increasing amount of research in the field prove its importance today and in the years to come. This paper deals with open innov­ ation and entrepreneurship from the perspective of how open innovation can help enterprises nurture their businesses. In addition, it discusses challenges and new perspectives open innov­ ation and enterprise face while cultivating and creating a competitive advantage. Keywords:

open innovation, entrepreneurship, innovation, growth, enterprise

1 INTRODUCTION Open innovation concepts enrich the source of innovation. Thus enterprises can exploit new initiatives from customers, competitors, or academia, even in different industries. Enterprises should also use their internal capacity to create innovation, along with utilizing external resources and paths to new, more effective approaches. Open innovation has many advan­ tages: (a) It reflects social and economic changes in working patterns, where professionals seek portfolio careers rather than a job for life with a single employer. (b) Improved market institutions such as intellectual property rights (IPR), venture capital (VC), and technology standards allow for the organization to trade ideas. (c) New technologies allow for new ways to collaborate and coordinate across geographical distances. Chesbrough (2003) inaugurated the popular use of the term open innovation, which describes a phenomenon of organizations making greater use of external ideas and technologies and letting unused internal ideas and technologies go outside for others to use in their organizations. The concept of open innov­ ation gains its place thanks to the increased use of the Internet, and without it, it would be a real challenge to implement, especially in the public sector. Open innovation is defined as “a distributed innovation process that involves purposively managed knowledge flows across the organizational boundary” (Chesbrough and Bogers, 2014). Open innovation helps enterprises grow and create a competitive advantage.

2 ROLE OF OPEN INNOVATION IN ENTERPRISE GROWTH One of the challenges all entrepreneurs face is the need for growth. Growth is part of all organizations, and it implies continuous growth of sales, purchases, number of employees, and profit, and thus the normal growth of the enterprise (Rexhepi and Srhoj, 2018). Innov­ ation is considered one of the main sources for enterprise growth (Rexhepi et al., 2018; Rexhepi, Kurtishi, and Bexheti, 2013), but finding the right strategy to implement this innov­ ation is also crucial (Rexhepi, 2014, 2015). Most of the innovations that are part of organiza­ tions are derived from inside the organizations. Traditionally, innovation is viewed as taking place mostly within a single firm (Lee et al., 2010). However, many types of research have proven that using innovation from inside a company (closed innovation) for entrepreneurial

1

growth has its own limitations (Chesbrough, 2006). Changes in professional surroundings – such as increased labor division due to globalization, improved market institutions for trading ideas, and the rise of new technologies, as well as new trends such as outsourcing, agility, and flexibility – require organizations to leave the closed innovation approach and become net­ work organizations (Huizingh, 2011). Researchers and practitioners therefore need to rethink the design of innovation strategies in a networked world, and they need to seek new sources of innovation, which can be found in the new concept of open innovation. Open innovation recently has become one of the hottest topics in innovation management; it is a rich concept that can be used in many different ways inside organizations. About ten years ago, Google reported only 200 page links related to open innovation, most of which merely had the two words near each other in a sentence, such as “company X opened its innovation once at location Y.” Now there are more than 500 million page links in response to the term open innovation, and job titles like manager or director or vice president of open innovation are becoming more common in many organizations (Bogers, 2019). Quantitative studies have shown that it has been a valuable concept for many firms in many contexts (Hui­ zingh, 2011). Academic research and industry practice have paid most attention to outside-in open innov­ ation, while inside-out and coupled open innovation are less well understood. In a review of 165 articles on open innovation, West and Bogers (2014) found that 118 of them addressed only outside-in open innovation, in contrast to 50 articles addressing inside-out open innov­ ation and 70 articles addressing coupled open innovation. Open innovation models explain that organizations can use many sources of knowledge and new ideas for innovation and invention activities, including customers, rivals, academics, and firms in unrelated industries (West and Gallagher, 2006). Open innovation means that ideas emerge and can be commercialized from inside or outside the firm (Dahlander and Gann, 2010). Openness means that a single organization cannot innovate in isolation; it has to engage with different types of organizations so that it can acquire new ideas and resources. It emphasizes firms’ boundaries where ideas, resources, and individuals flow in and out of organizations (Dahlander and Gann, 2010). This collaboration has produced innovative prod­ ucts such as the Linux operating system, the Firefox web browser, and the Apache webserver (West and Gallagher, 2006). These cooperations are better understood through the models of innovation explained in this book.

3 UNDERSTANDING OPEN INNOVATION In technology-intensive industries, innovation is a central issue for the competitiveness of a firm (Ferrary, 2011). This is why most successful companies invest huge amounts of their resources in research and development (R&D) (for example, in 2008, Microsoft invested $6.4 billion in R&D; Nokia, 5.3 billion; IBM, $4.3 billion; Intel, $4.1 billion; and Motorola, $2.9 billion) (Ferrary, 2011). However, new global challenges require new, smarter solutions such as healthcare, transportation, climate change, youth unemployment, financial stability, prosperity, sustainability, and growth, which can be a great opportunity for generating new shared value (Curley and Salmelin, 2013; Suklev and Rexhepi, 2013). As Joseph Schumpeter (1942) states in his famous creative destruction model, where the failure of old approaches fuels motivation, change will appear (Curley and Salmelin, 2013). Open innovation has proven to be a new model that can help reshape the way organizations use their innovation capacity. Institutional openness is becoming increasingly popular in practice and academia: open innovation, open R&D, and open business models (Gassmann and Chesbrough, 2010). The organization is an open system, and it influences and can be influenced by the society. This means that organizations create benefits for others but also can benefit from others. Creativity and innovation are the first things that organizations should share with others. The new con­ cept introduced by Henry Chesbrough (2003) called open innovation conceptualizes the idea of innovation where ideas pass to and from different organizations for exploitation. The open 2

innovation concept assumes that corporate innovation activities are more like an open system than the traditional (twentieth-century) vertically integrated model (Chesbrough, 2003, 2006). Open innovation concepts suggest that innovation can derive not just from inside the organ­ ization but also from outside the organization. Chesbrough and Vanhaverbeke (2011) suggest companies should find a way to utilize the distributed pools of knowledge possessed by cus­ tomers, suppliers, universities, national labs, consortia, consultants, and even their own com­ petitors. The combination of diverse knowledge increases the chances of finding creative solutions, leading to innovations that are more radical. The open innovation concept has been developed first from a small club of innovation prac­ titioners, mostly active in high-tech industries, into a widely discussed and implemented innov­ ation practice (Gassmann and Chesbrough, 2010). Today, open innovation is cited in strategy, general management, and organization behavior journals (Gassmann and Chesbrough, 2010). The concept of open innovation has penetrated industries such as software, electronics, tele­ communications, pharmaceuticals, and biotech (Chesbrough, 2003), as well as firms in the public sector. Organizations such as SAP and Microsoft have started to build decentralized research labs on university campuses to increase their absorptive capacity for outside-in innovation processes. Apple had to open up its proprietary technology to its addicted hightech users. Philips’s open innovation park, Xerox’s Palo Alto Research Center, Siemens’s open innovation program, IBM’s open-source initiatives, British Telecom’s incubation activ­ ities, Deutsche Telecom, and Swisscom – all of these – drive open innovation on a strategic level (Gassmann and Chesbrough, 2010). It is obvious that the era of open innovation has just begun (Gassmann and Chesbrough, 2010). Open innovation has been defined as “the use of purposive inflows and outflows of know­ ledge to accelerate internal innovation, and expand the markets for external use of innovation, respectively” (Chesbrough, Vanhaverbeke, and West, 2006). Nevertheless, open innovation’s definition, even Chesbrough’s definition, has evolved throughout the years (Parveen, Senin, and Umar, 2015). Open innovation is also seen as a “distributed innovation process based on purposively managed knowledge flows across organizational boundaries, using pecuniary and non-pecuniary mechanisms in line with the organization’s business model” (Chesbrough and Bogers, 2014). Open innovation is also a methodology to design and implement solutions col­ laboratively by engaging all stakeholders in an iterative and inclusive service design process (Carayannis and Campbell, 2011). It is used to address issues for businesses, governments, and many other institutions in order to improve the quality of their innovation activities and of the service that they deliver (Syla and Rexhepi, 2013). Open innovation in risk-laden processes brings several advantages. First, organizations can benefit from early involvement in new technologies or business opportunities. Second, corpor­ ations can profit from delayed financial commitment as they can invest step by step, avoiding investing high up-front costs. Third, businesses can gain from early exits, as corporate ventur­ ing is a flexible investment instrument. Fourth, investing firms can also delay exit in the case of spins-offs (Vanhaverbeke, Van de Vrande, and Chesbrough, 2008).

4 ADVANTAGES AND CHALLENGES OF OPEN INNOVATION Open innovation has many advantages (Dahlander and Gann, 2010). (a) It reflects social and economic changes in working patterns, where professionals seek portfolio careers rather than a job for life with a single employer. Firms therefore need to find new ways of accessing talent that might not wish to be employed exclusively and directly. (b) Globalization has expanded the extent of the market that allows for an increased division of labor. (c) Improved market institutions such as intellectual property rights (IPR), venture capital (VC), and technology standards allow for organizations to trade ideas. (d) New technologies allow for new ways to collaborate and coordinate across geographical distances. Nevertheless, most of the research done related to open innovation has been conducted mainly in high-tech, multinational enterprises, but small and medium-sized enterprises (SMEs) also use the concept (Van de Vrande et al., 2009). However, differences emerge in the 3

potential use of open innovation by big companies and SMEs. Van de Vrande and colleagues (2009) found that medium-sized firms are, on average, more heavily involved in open innov­ ation than their smaller counterparts are. Research has also found that SMEs pursue open innovation primarily for market-related motives such as meeting customer demands or keep­ ing up with competitors. Even though this topic remains under examination, more research is proving the potential of open innovation for SMEs, indicating networking as one of the most effective ways to increase open innovation capacity among SMEs (Lee et al., 2010). The researcher also needs to address issues such as the organizational dynamics of university-firm relationships, which remains under-researched (Perkmann and Walsh, 2007). The success of the use of open innovation depends on the capacity and preparation of an organization. Organizations that tend to use open innovation need to address three fundamental challenges in applying it: finding creative ways to exploit internal innovation, incorporating external innovation into internal development, and motivating outsiders to supply an ongoing stream of external innovation (West and Gallagher, 2006). This paper provides major theoretical and empirical evidence that relates to open innov­ ation and entrepreneurship and how it can help enterprises grow and create a competitive advantage. This analysis is based on the book Open Innovation and Entrepreneurship (Rexhepi et al., 2019).

5 OVERVIEW OF OPEN INNOVATION TRENDS Bogers (2019) analyzed the relationship between the diversity of partners that a start-up cooperates with and its innovation performance. Based on data from the Spanish Innovation Technology Panel (PITEC) from 2004 to 2013, he found that start-ups benefit more than incumbent firms do from cooperation breadth; this effect is stronger for high-tech start-ups in particular. This study is a great contribution to examining the link between open innovation and entrepreneurship. It advances our knowledge on the role of breadth as a mechanism to integrate heterogeneous knowledge and access to complementary assets, and it sheds light on some of the contingencies in terms of which types of start-ups will benefit most (GimenezFernandez, Bogers, and Sandulli, 2019). Davari, Emami, and Seyedi (2019) selected nine indicators for inbound and six indicators for outbound open innovation in eighty-three SMEs that operate in the information technol­ ogy sector. They concluded that only a small number of inbound and outbound open innov­ ation indicators have a positive impact on the discovery and exploitation of entrepreneurial opportunities. Egbetokun and colleagues (2019), based on multiple research streams that include econom­ ics of innovation and development economics, developed and tested several hypotheses on sec­ toral differences and the role of the economic context. They found that a wider range of innovation obstacles implies a broader external search, and more intense obstacles require a deeper search. Mahmutaj and Krasniqi (2019) explored the impact of open innovation on start-up firms’ growth. The empirical findings (based on case studies) in developing countries showed a low level of open innovation. This study discussed the challenges of effective collaboration among entrepreneurs and partners’ commitment to supporting firm growth. Haase (2019) concluded that three main areas are essential for the integration of an open innovation initiative in SMEs – communication, culture, and innovation – which led to the identification of four important factors – technical competence, operational management competence, operational-social management competence, and social-technical management competence – and the factor of “words and deeds.”

4

6 CONCLUSION/CHALLENGES OF OPEN INNOVATION: FUTURE RESEARCH • Further research needs to be done on the role of individual employees in open innovation (evidence only from technology industries) in emerging markets. • More successful case studies need to be examined. • Simple models are needed of how enterprises could use the open innovation concept and gain competitive advantages. • Future research needs to investigate the role of other manager characteristics and might examine the interplay between manager characteristics and employee characteristics. • More in-depth research is needed capturing differences between developing and emerging economies. • Another intriguing line of inquiry might focus on the role of intrafirm relationships, regard­ ing the relationships among colleagues or between subordinates and managers, in facilitat­ ing or hindering employee-level open innovation practices. • The supplementary analysis on the contribution of individual knowledge sources to IWO notably does not find any effect of market-related knowledge sources (customer, competi­ tor) on IWO. REFERENCES Bogers, M., Burcharth, A., and Chesbrough, H. W. (2019). Open innovation in Brazil: Exploring oppor­ tunities and challenges. International Journal of Innovation 7(2), 178–191. Carayannis, E. G., and Campbell, D. F. (2011). Open innovation diplomacy and a 21st-century fractal research, education and innovation (FREIE) ecosystem: Building on the quadruple and quintuple helix innovation concepts and the “mode 3” knowledge production system. Journal of the Knowledge Economy 2(3), 327. Chesbrough, H. (2003). The logic of open innovation: Managing intellectual property. California Man­ agement Review, 33–58. Chesbrough, H. (2006). The era of open innovation. Managing Innovation and Change 127(3), 34–41. Chesbrough, H., Vanhaverbeke, W., and West, J. (eds.). (2006). Open Innovation: Researching a New Paradigm. Oxford: Oxford University Press. Curley, M., and Salmelin, B. (2013). Open Innovation 2.0: A new paradigm. OISPG White Paper, 1–12. Dahlander, L., and Gann, D. M. (2010). How open is innovation? Research Policy 39(6), 699–709. Davari, A., Emami, A., and Seyedi, S. (2019). Investigating the effect of inbound and outbound open innovation on discovery and exploiting of entrepreneurial opportunities. In G. Rexhepi, R. D. Hisrich, and V. Ramadani (eds.), Open Innovation and Entrepreneurship: Impetus of Growth and Competitive Advantages (pp. 51–66). Cham: Springer. Egbetokun, A., Oluwatope, O., Adeyeye, D., and Sanni, M. (2019). The role of industry and eco­ nomic context in open innovation. In G. Rexhepi, R. D. Hisrich, and V. Ramadani (eds.), Open Innovation and Entrepreneurship: Impetus of Growth and Competitive Advantages (pp. 67–87). Cham: Springer. Ferrary, M. (2011). Specialized organizations and ambidextrous clusters in the open innovation paradigm. European Management Journal 29(3), 181–192. Gassmann, O., Enkel, E., and Chesbrough, H. (2010). The future of open innovation. R&D Management 40(3), 213–221. Gimenez-Fernandez, E. M., Bogers, M., and Sandulli, F. (2019). How the diversity of cooperation part­ ners affects startups’ innovation performance: An analysis of the role of cooperation breadth in open innovation. In G. Rexhepi, R. D. Hisrich, and V. Ramadani (eds.), Open Innovation and Entrepreneur­ ship: Impetus of Growth and Competitive Advantages (pp. 9–35). Cham: Springer. Haase, I. (2019). Open innovation: Challenges of integrating new forms of innovation in SMEs. In G. Rexhepi, R. D. Hisrich, and V. Ramadani (eds.), Open Innovation and Entrepreneurship: Impetus of Growth and Competitive Advantages (pp. 89–107). Cham: Springer. Huizingh, E. K. (2011). Open innovation: State of the art and future perspectives. Technovation 31(1), 2–9. Lee, S., Park, G., Yoon, B., and Park, J. (2010). Open innovation in SMEs: An intermediated network model. Research Policy 39(2), 290–300.

5

Mahmutaj, L. R., and Krasniqi, B. (2019). Open innovation in a start-up firm. In G. Rexhepi, R. D. Hisrich, and V. Ramadani (eds.), Open Innovation and Entrepreneurship: Impetus of Growth and Competitive Advantages (pp. 109–126). Cham: Springer. Parveen, S., Senin, A. A., and Umar, A. (2015). Organization culture and open innovation: A quadruple helix open innovation model approach. International Journal of Economics and Financial Issues 5(1S), 335–342. Perkmann, M., and Walsh, K. (2007). University-industry relationships and open innovation: Towards a research agenda. International Journal of Management Reviews 9(4), 259–280. Rexhepi, G. (2014). Use the right strategy and grow. ACRN Journal of Entrepreneurship Perspectives 3(1), 19–29. Rexhepi, G. (2015). Entering new markets: Strategies for internationalization of family businesses. In Family Businesses in Transition Economies (pp. 293–303). Cham: Springer. Rexhepi, G., Bexheti, A., Ibraimi, S., and Kurtishi-Kastrati, S. (2018). The importance of intellectual capital in the selection of global marketing strategies: Evidence from family businesses in Macedonia. International Journal of Transitions and Innovation Systems 6(2), 108–117. Rexhepi, G., Hisrich, R. D., and Ramadani, V. (eds.) (2019). Open Innovation and Entrepreneurship: Impetus of Growth and Competitive Advantages. Cham: Springer. Rexhepi, G., Kurtishi, S., and Bexheti, G. (2013). Corporate social responsibility (CSR) and innovation: The drivers of business growth? Procedia: Social and Behavioral Sciences 75, 532–541. Rexhepi, G., Ramadani, V., Rahdari, A., and Anggadwita, G. (2017). Models and strategies of family businesses’ internationalization: A conceptual framework and future research directions. Review of International Business and Strategy 27(2), 248–260. Rexhepi, G., and Srhoj, S. (2018). Strategy as an ever evolving road to success of growing enterprises. World Review of Entrepreneurship, Management and Sustainable Development 14(3), 333–347. Suklev, B., and Rexhepi, G. (2013). Growth strategies of entrepreneurial businesses: Evidence from Macedonia. In Entrepreneurship in the Balkans (pp. 77–87). Berlin, Heidelberg: Springer. Van de Vrande, V., De Jong, J. P., Vanhaverbeke, W., and De Rochemont, M. (2009). Open innovation in SMEs: Trends, motives and management challenges. Technovation 29(6–7), 423–437. Vanhaverbeke, W., Van de Vrande, V., and Chesbrough, H. (2008). Understanding the advantages of open innovation practices in corporate venturing in terms of real options. Creativity and Innovation Management 17(4), 251–258. West, J., and Gallagher, S. (2006). Challenges of open innovation: The paradox of firm investment in open-source software. R&D Management 36(3), 319–331.

6

The Future Opportunities and Challenges of Business in Digital Era 4.0 – Bangsawan et al. (eds) © 2020 Taylor & Francis Group, London, ISBN 978-0-367-42594-4

Organizational commitment and job satisfaction: The leadership role of leader-member exchange in SMEs H. Jimad & Roslina Universitas Lampung, Lampung, Indonesia

ABSTRACT: Leadership is consistently recognized as a major contributor to an organiza­ tions’ success. A leader’s inconsistency in small businesses creates poor employee performance and a decrease in profits. This study, therefore, aims to examine the effect of leadership style leader-member exchange (LMX) on organizational commitment through job satisfaction on SME employees in Bandar Lampung. The purposive sampling technique was used to obtain data from 325 employees of SMEs using structured questionnaires. The results showed that leadership style leader-member exchange affected the job satisfaction of SMEs employees and organizational commitment. The results also showed that the award provided by leaders, per­ ceived fairness, and clarity of the objectives to be achieved by SMEs were the determining fac­ tors for employee satisfaction at work. Keywords: SMEs, leadership style leader-member exchange, job satisfaction, organizational commitment 1 INTRODUCTION Leadership has consistently been recognized as a major contributor to the success of a business with the capability of influencing employees (Lee, 2005). A leader acts as a motivator, mediator, and communicator in an organization, ad their relationship with employees is generally based on the existence of exchanges beneficial to both parties. Graen and Uhl-Bien (1991) developed a leadership model called leader-member exchange (LMX), which is a variation of social exchange theory used to explain the leader-member relationships. According to the LMX theory, the rela­ tionship between superiors and employees is the result of work exchanges. Furthermore, Elanain (2014) reported that there are two types of relationships, namely, high-quality relationships, which reflect on trust, respect, as well as loyalty, and low-quality relationships. The use of LMX makes employees committed to the organization due to their closeness to their leaders and colleagues. This is also a way to repay the leader of their kindness (Lee, 2005). According to previous studies, there is a significant relationship between LMX, organiza­ tional performance, satisfaction, and commitment (Gerstner and Day, 1997; Lee, 2005; Liao et al., 2017) stated that job satisfaction is determined by the organizational climate, while employee commitment is determined by the leader-follower relationship (Wei, Lee, and Kwan, 2016). In addition, higher performance is shown by subordinates with a high level of satisfactory relationship with their superiors, with decreased turnover, and better quality of tasks (Abu Bakar, Su Mustaffa, and Mohamad, 2009). M. Abu Elanain (2014) stated that leadership is very important for small and medium-sized businesses, and the relationship is dependent on social exchange, as well as the interactions that occur with their subordinates. Bhal (2006) reported that their relationship tends to influences the work output of their subordinates. It is identified that in SMEs, employees have limited access to their superiors and resources. There­ fore, there is a low-quality exchange of information. This leads to the potential cause of work dissatisfaction, low commitment to an organization, and poor turnover (Maslyn and Uhl-Bien, 2001). Relationships that are formed due to obligations create a low level of trust and emotional 7

support, which causes employee dissatisfaction with low impact commitment to the organiza­ tion (Elanain, 2014). The Lampung Province is dominated by Small and Medium Enterprises, which numbered 11,903 units in 2017. According to the Department of Cooperatives and SMEs (2018), SMEs make a significant contribution to the economy, absorb a large workforce, and reduce unemployment. It plays a very important role in moving the wheels of the Lampung economy and requires relatively small capital. In small businesses, consistent leadership is needed to face unpredictable challenges and problems or new ventures (Finlay-Robinson, 2013). This research is important as it aims to obtain information on leadership and the exchange process between leaders and their subordinates at SMEs in Bandar Lampung, Lampung Province.

2 RESEARCH METHODOLOGY This study aims to examine the effect of leader-member exchange (LMX) on organizational commitment through job satisfaction on SMEs employees in Bandar Lampung. The survey method was carried out by distributing structured questionnaires to SMEs employees in Bandar Lampung. Furthermore, it provided opportunities for leaders to convey the roles desired by their employees due to the low-quality relationships which affect their performance. Furthermore, the purposive sampling technique was used to obtain data from 325 employees working at SMEs in Bandar Lampung (Hair et al., 2010).

3 FINDINGS AND DISCUSSION Questionnaires were distributed to 325 SME employees in Bandar Lampung. However, a total of 300 copies were returned and eligible for further processing, thereby leaving the response rate at 92.3%. The respondents were made up of 58% male and 42% female, and based on their years of service, 80% have worked for 1-5 years, 6-10 years (18%), and more than 10 years (2%). However, the profile of respondents used in this study was 52% male and 48% female with working years 1-5 years (80%), where 40.3% worked in food and beverage industries, 34.3% in other services, and 25.4% in sales. Based on several model suitability test criteria, it is stated that the entire research model is fit, with a CMIN/DF value of 2.444, GFI 0.829, AGFI 0.801, RMSEA 0.069, TLI 0.790, and CFI 0.806. Similarly, based on the results of data processing using SEM, the Maximum Likeli­ hood Estimates that the CR value in regression weight is 4.988, greater than ± 1.96 and p-value (1,656). It is also obtained sig. (0.009) < (0.05); thus, there is a significant influence of consumer characteristics on purchasing decisions. The significance of the social factor (X2) on the purchase decision of KFC (Y) explained from tcal (4.047) > (1.656). It is also obtained sig. (0,000) < (0.05), thus there is a significant influence of social factors on purchasing decisions of KFC environmentally friendly products. The results of this study illustrate consumer responses related to consumer characteristics indicated by locus control and collectivism. Locus of control is a translation of personality traits that relate to basic beliefs about a person’s interactions with the environment in terms of KFC’s environmentally friendly products through parameters of work accuracy, planning, luck assumptions, attitudes towards events in their environment, perceived attainment of some­ thing, concern for things to happen, attitudes of others, betting lives, and personal control. Social factors describe the visibility of the environment measured from the activities of others, or friends’ and family’s activities on the environment. Its is described in the form of an assess­ ment of the many people around who care and join activities to protect the environment.

5 CONCLUSION This study concludes that the purchasing decision in regard to KFC environmentally friendly products is formed from the characteristics of consumers from the dimensions of control and collectivism. KFC environment can encourage the intention to consume KFC environmen­ tally friendly products. The decision to buy KFC environmentally friendly products can be formed from social fac­ tors from the dimensions of environmental visibility and subjective norms. This is known from the results of research that proves that social factors can significantly shape purchasing decisions in terms of KFC environmentally friendly products, besides consumer perception of better social factors related to KFC environmentally friendly products will encourage the for­ mation of KFC environmentally friendly product purchasing decisions. REFERENCES Amalia, F. (2011). Analisis pengaruh faktor budaya, sosial, Pribadi dan psikologisterhadap Keputusan pembelian minuman penambah tenaga cair merek 150 di semarang. Skripsi. Semarang. http://eprints. undip.ac.id309411 Diunduh 16 Juni 2014. Chaudhary, R., & Bisai, S. (2018). “Factors influencing green purchase behavior of millennials in India.” Management of Environmental Quality: International Journal, 29(5),798_812 © Emerald Publishing Limited 1477–7835. Diglel, Y. (2014). “Green marketing: its influence on buying behavior and attitudes of the purchasers towards eco-friendly products. Global Journal of Management and Business Research: E Marketing, Vol. 14. Kotler, P. (2018). Manajemen Pemasaran. Indeks Kelompok Gramedia Jakarta. Manongko. (2017). Green marketing and Pengaruhnya Terhadap Keputusan Pembelian Melalui Minat Membeli Produk Organik: Studi Pada Pelanggan Produk Organik Di Kota Manado, Publikasi Ilmiah, Universitas Brawijaya, Malang. Muhidin, S. A. (2017). Panduan Praktis Memahami. Penelitian, Pustaka Setia, Bandung.

88

Rejeki, dkk (2015). Pengaruh Green Marketing pada Keputusan Pembelian dan Implikasinya Terhadap Loyalitas Pelanggan (Studi Pelanggan Produk Ramah Lingkungan KFC Gerai Royal Plaza, Surabaya). Jurnal Administrasi Bisnis (JAB) 26(1 Sept). Setiadi, N. (2015). Perilaku Konsumen Konsep dan Implikasi untuk Strategi dan Penelitian Pemasaran. Prenada Media Jakarta. Suhandang. K. (2015). Periklanan, Manajemen, Kiat dan Strategi. Penerbit Nuansa Bandung. Supranto, J. (2017). Pengukuran Tingkat Kepuasan Pelanggan Untuk Menaikkan Pangsa Pasar, Ceta­ kan keempat, Penerbit PT Rineka Cipta, Jakarta. Supranto & Limakrisna. (2017). Perilaku Konsumen dan Strategi Pemasaran Untuk Memenangkan Per­ saingan Bisnis. Mitra Wacana Media Jakaeta. Tong. (2016). “Green approaches in Hong Kong’s fast-food restaurants and its effects on corporate image.” Journal of Research in Marketing, 5(2 February). Wang. (2013). “Consumer characteristics and social influence factors on green purchasing intentions.” Marketing Intelligence & Planning, 32(7).

89

The Future Opportunities and Challenges of Business in Digital Era 4.0 – Bangsawan et al. (eds) © 2020 Taylor & Francis Group, London, ISBN 978-0-367-42594-4

Convergency of revenue per capita regional New Autonomy (NAR) in Indonesia Ambya Universitas Lampung, Lampung, Indonesia

ABSTRACT: The purpose of this study is to analyze the sigma and absolute beta conver­ gence and measure the speed of per capita income merging occurring in the New Autonomous Region in Western Indonesia. The independent variable used is the Gross Domestic Product (GDP) per capita, while panel data with model fixed effect were the data used. The results showed that sigma convergence did not occur during the study period. Primarily, absolute convergence does not occur as evidenced by the lower level of income per capita NAR, which does not grow as faster as the NAR. The speed of absolute beta convergence is fifteen percent per year, while the time needed to close half of the initial gap between the New Autonomous Region (NAR) in Western Indonesia is four years. Keywords:

panel data, convergence, income per capita

1 INTRODUCTION According to Bucul (2012), convergence occurs in case an impoverished region with low income grows faster than a place with high income. This leads to the same level of convergence in the long run. However, this condition occurs since the economy of a region reaches a steady-state position. The results of the research stated the same assertion by Li and Xianbo (2011), Brandt et al. (2012), and Kaitila (2013). Li’s research (2013) argues that the convergence of ASEAN regional income is faster than in the European Union (EU). Similarly, Jayanthakumaran & Lee (2013) established that there is a convergence of income in the Association of Southeast Asian Nations (ASEAN) and the region South Asian Association of Regional Cooperation (SAARC). This condition is attrib­ uted to the differences in economic potential for several countries, leading to conditional con­ vergence arises (Schmitt & Starke, 2011). According to Fan and Casetti (1994), the inequality of economic development among high-income regions is lower than in the low-income regions, and this constitutes convergence. The western part of Indonesia has the best economic growth conditions compared to the cen­ tral and eastern regions. The formation of the New Autonomous Region is a strategic effort by the government to establish good fiscal and equitable economic decentralization, and economic mobility is expected. Nevertheless, decentralization often does not occur as expected since there are differences in development outcomes, economically and non-economically. This occurs due to differences in regional potential, the role of government, natural resources, and human resources. The difference in conditions leads to economic disparities between new autonomous regions in western Indonesia. There is a need to prove the alleged economic imbalances between regions. The purpose of this study is to prove whether the convergence of sigma and beta occurs. Also, it aims to ana­ lyze the speed of convergence and establish the half-life of convergence of income per capita, especially in western Indonesian NARs.

90

2 LITERATURE REVIEW Barro and Sala-i-Martin (1995) stated that a convergent economy has a lower income. It reduces the gap with regions that have higher incomes each year. Primarily, the concept of convergence is divided into two, sigma and beta convergences. The sigma convergence illus­ trates the decreasing per capita income gap over time. However, beta convergence establishes the effect of factors estimated in determining the degree of convergence. Beta convergence can be divided into two, including absolute and conditional convergences (Lall and Yilmaz, 2000; Paas et al. 2007). Absolute convergence assumes that the economies between countries or regions have similarities in terms of structure, demographic conditions, saving rates, and other economic variables. Conversely, conditional convergence assumes that structural characteris­ tics between countries or regions have inequality. For this reason, the convergence is influ­ enced by the structural characteristics of the country or region. Marques and Soukiazis (1998), Lall and Yilmaz (2000), and Paas et al. (2007) stated that there are currently two approaches used to look at convergence. This includes sigma and beta convergences. In general, sigma convergence illustrates the decreasing per capita income gap over time. Determination of the presence or absence of convergence is often based on the ana­ lysis of the dispersion through the coefficient of variation. According to Barrientos (2007), the term economic convergence is used when two or more economies are almost at the same level of development and prosperity. On the other hand, the study of convergence is debated between three growth models, including the neoclassical, endogenous, and distribution dynamics. The welfare of the community is a development and policy goals to be achieved by a country. Public welfare can be measured by dividing national income by the population. This quotient is referred to as per capita income. Specifically, the national income is divided into the Gross National Product (GNP) and Gross Domestic Product (GDP). Mankiw (2006) stated that GDP per capita is a better tool to measure the living standards of its citizens.

3 METHODS This research was conducted in the entire New Autonomous Region in western Indonesia, which was formed in 2008. The variables used were secondary in the form of data crosssection and time series from 2011-2016. Essentially, the data was obtained from the Central Statistics Agency (BPS) of each NAR. The analyst model used is the Williamson Index. The Continued Beta convergence models through Absolute convergence can be measured using the following equation: Where: Y = GRDP per capita; = GRDP per capita of the previous year (initial income); and = NAR. Measurement speed of convergence to determine the duration of the halftime convergence as follows: ln [y (t)] = (1 - e -βT). Ln (y *) + e -βT; ln [y (0)]. The time t required for ln [y (t)] to eliminate the gap between ln [y (0)] and ln (y *) needs to meet the conditions e ­ βT =, then half-time convergence is: t ¼ - lnβð0;5Þ t ¼ - lnβð0;5Þ t ¼ lnβð2Þ t ¼ lnβð2Þ or The Individual Effect uses the Fixed Effect model, namely: Ci = C + β; Where: Ci = Individual Effect; C = constant; and β = coefficient. 4 RESULTS 4.1 Reporting research results 4.1.1 Williamson Index The results of the Williamson Index calculation for 2011 to 2016 are as follows; 0.4808; 0.4872; 0.5003; 0.5047; 0.4997; 0.5048, giving an average of 0.4963. This figure indicates that 91

the inequality of NAR income in western Indonesia is still low since the value is close to 0. The inequality that occurs every year tends to increase. However, in 2014-2015, it decreased from 0.5047 to 0.4997. 4.1.2 Sigma convergence In this study, sigma convergence analysis measures the disparity by calculating the coefficient of variation in GDP per capita in Western Indonesia NARs. Then the Coefficient Variation (CV) value of sigma convergence is obtained.

Table 2. Coefficient of variation of sigma convergence. Year

2011

2012

2013

2014

2015

2016

Coefficient Variation Keterangan

0.5157 -

0.5217 divergent

0.5327 divergen

0.5883 divergen

0.5279 konvergen

0.5295 divergen

Source: Processed data.

The coefficient of variation of GRDP per capita shows that the NAR in western Indonesia had no convergence over four years, specifically from 2011–2016, except 2015. 4.1.3 Beta convergence analysis The following are the results of the absolute convergence regression NAR in western Indonesia: Yit = 3055954 + 0,950943Yit-1 Po = (0.0002) (0.0000) R2 = 0.998463 DW = 2.896291 The regression equation means that the GDP coefficient per capita per year/initial income NAR in western Indonesia was 0.9509. This means that an increase or decrease in per capita GRDP of 1 percent would increase or decrease GDP per capita by 0.95 percent.

5 DISCUSSION The average inequality shown by the Williamson Index is still relatively low at 0.4963, though the NAR inequality in western Indonesia is increasing every year. This is attributed to several factors, including the lack of government and community efforts to utilize regional resources and potential. Human resources in each region are unique and cannot compete with other regions. The estimated GDP per capita coefficient results indicate a positive value, which means that there is a lack of absolute convergence in NAR throughout western Indonesia in 2011-2016. During this period, the NAR, which had a lower per capita Gross Regional Domestic Product (GRDP), had not grown faster than the NAR, which had better initial conditions. The dispar­ ity can be measured by calculating the coefficient of variation per capita GDP per year. In case the coefficient of variation in a particular year is smaller than the coefficient of variation in the previous year, the convergence of sigma occurs (Barro and Salla-i-martin, 1992). Con­ versely, in case the coefficient of variation in certain years is higher than the previous year, then there is no sigma convergence. Therefore, where the coefficient of variation in certain years is smaller than the previous year, the disparity that occurs in new autonomous regions in western Indonesia decreases in certain years. The speed of convergence explains the time needed to close half the gap from the initial is four years. It takes two years to fill the gap of per capita GRDP that occurs in new autono­ mous regions in western Indonesia. According to Barro and Sala-I-Martin (2004: 56), it is 92

essential to be acquainted with the speed of convergence. In case it happens more quickly, the economy nears the steady-state. Conversely, where the convergence is too slow, the economy increasingly steers clear of steady-state.

6 CONCLUSION From the results, the convergence of sigma in western Indonesia NAR does not occur, with an average CV value of 0.5359. Sigma convergence occurs in case the coefficient of variation in GRDP per capita of a particular year is smaller than its variation in the previous year. This means a decrease in disparity in income per capita. In this study, almost every year, the dispar­ ity increases, meaning sigma convergence does not occur. There is no absolute convergence in western Indonesia NAR since the coefficient of GDP per capita in the previous year shows a positive value. This means that the level of GDP per capita of lower-income NARs does not grow faster than higher-income. Absolute convergence speed is 15% percent per year, and the time needed to close half of the initial gap (the half­ time convergence) is four years. REFERENCES Barrientos, Paola (2007). “Theory, History, and Evidence of Economic Convergence in Latin America.” Institute for Advanced Development Studies. Development Research Working Paper Series. No. 13/2007. Barro. R. J., & Xavier, S., 1992. „Convergence.‟ Journal of Political Economy, Vol. 100 (2), 223–251. Barro, R.J dan X Sala-i-Martin. 1995. Economic Growth. McGraw Hill. Brandt, Loren, et al. (2012). From Divergence to Convergence: Re-evaluating the History Behind China’s Economic Boom. January 2012. Working Papers No. 158/12. Department of Economic His­ tory London School of Economics. Fan, C. C., & Casetti, E. (1994). The Spatial and Temporal Dynamics of US Regional Income Inequality, 1950-1989. Annals of Regional Science, 28(1), 177–196. Fei Chen, Xiangwei Sun. 2013. “Analysis on the changes of convergence of regional economic growth in China: 1984-2010”. Journal of Cambridge Studies Volume 8, No. 1. Kaitila, Ville. (2013). Convergence, Income Distribution, and The Economic Crisis in Europe. ETLA Working Papers No 14. Lall, Somik dan Serdar Yilmaz (2000). “Regional Economic Convergence: Do Policy Instruments Make a Difference?”. IBRD. World Bank Institute. Washington. Li, H. (2013). Convergence or Divergence?-Rethinking Regional Integration of the Past Two Decades. Frontiers of Economics in China, 8(4), 592–607. Li, Kui-Wai., and Xianbo Zhou. (2011). Cross-country Convergence and Growth: Evidence from Nonparametric and Semiparametric Analysis. Submitted paper. September 22 – 23, 2011. SanFran­ cisco, USA. Jayanthakumaran, K., & S. W. Lee. (2013). Evidence on the Convergence of Per Capita Income: A Comparison of Founder Members of the Association of Southeast Asian Nations and the South Asian Association of Regional Cooperation. Pacific Economic Review, 18(1), 108–121. Marques, Alfredo dan Elias Soukiazis. 1998. “Per Capita Income Convergence Across Countries and Across Region in The European Union: Some New Evidence.” Paper 2nd International Meeting of European Economy. CEDIN (ISEG). Lisbon. Schmitt, C., & P. Starke. (2011). Explaining the convergence of OECD welfare states a conditional approach. Journal of European Social Policy, 21(2), 120–135.

93

The Future Opportunities and Challenges of Business in Digital Era 4.0 – Bangsawan et al. (eds) © 2020 Taylor & Francis Group, London, ISBN 978-0-367-42594-4

Banking performance and shock response of macroeconomic conditions in Indonesia Irma Febriana M.K., Rizka Malia & Nurbetty Herlina S. Universitas Lampung, Lampung, Indonesia

ABSTRACT: This research paper presents a discussion on the response performance of banks due to the changes in macro variables represented by Index Industrial Production (IPI), the consumer price index (CPI) and the BI rate, coupled with the performance of banks in Indonesia alternated by Return on Assets (ROA), BOPO, and Loan Deposits Ratio (LDR). IRF (Impulse Response Function) as a method of analysis. Results indicate ROA respond positively to fluctuations instituted by, CPIand IPI. However, it responds negatively to vari­ ations caused by the BI rate. Nevertheless, BOPO and LDR respond positively to the IPI, CPI, and the BI rate deviations. Keywords: banking performance, BI rate, BOPO, CPI, IPI, LDR, macroeconomic conditions, ROA 1 INTRODUCTION The banking industry has an important role in stabilizing the financial situation since it con­ trols 80% of the system in Indonesia (Abusomwan, 2018). The financial system consists of a set of procedures that facilitate payment, deposits, and loans, which enhances the effective exchange of economic resources. Agusman (2010) states, the financial system is an essential prerequisite in ensuring economic life. Additionally, macroeconomic stability cannot be achieved without the constancy of the financial system. Favorable macro conditions provide a positive financial environment for the development of banking. Conversely, macroeconomic and financial conditions, if unstable, affect the market and credit, which impacts the bank’s performance. Typical of the economic cycle, the stability of the banking system is an element of social steadiness that tracks back to the fiscal strength of a country (Mankiw, 2010).

2 LITERATURE According to Mishkin (2013), the bank’s performance is stemmed from its objectives, and that is how they maximize profits. Regarding management, banks are focused on; First, liquidity management to ensure the availability of adequate cash to pay for withdrawals. Second, asset organization, which ensures the acquisition of assets with the least risks and ownership diver­ sification Third, the control of the liabilities paying attention to how to obtain funds at a low cost. Lastly, capital adequacy management in which the bank needs to decide on the amount of capital to be managed and its procurement. Based on Bank Indonesia Regulation No. 13/1/PBI/2011 regarding the rating of commercial banks, bank performance is one of the factors included in assessing the health of the lender in regards to the risk factors. PBI’s factors on the bank’s performance consist of three elements including; the implementation of good corporate governance (GCG), profitability, and capital

94

on eight risk profile risks such as credit, market, liquidity, operational, legal, strategic, compli­ ance, and reputation (Fatimah et al., 2015). In the report of the Indonesian Banking Statistics (SPI) FSA and BI performance of the leading commercial banks, profitability and liquidity ratios contribute to generating real income for budgeting. Indicators of profitability ratios include ROA (Return on Assets) and BOPO (Operating Expenses and Operating Income). These factors contribute to profitability in terms of the net interest income and operating revenue other than overhead, and load backup, where all are variables to total average assets. Liquidity ratio is used in the measurement of a bank’s ability to meet its short-term obliga­ tions or liabilities. LDR (Loan Deposit Ratio) is used as an indicator of the availability of sufficient reserve to shelter its credit demand (Bank Indonesia SPI report.)

3 METHOD IRF (Impulse Response Function) was used as the methodology in the collection and analysis of data in this research. The variables which emerged include ROA, BOPO, LDR, IPI, CPI, and BI rate. Banking records were observed monthly for the period between January 2018 and March 2010.

4 RESULTS Based on the test results of impulse response function (IRF), ROA responded positively to the shocks of the CPI, ROA behaved negatively to the shocks of the IPI and the BI rate. And, for the performance variables, ROA was affirmative due to the shocks of the IPI, CPI and the BI rate. And, banking performance LDR was encouraging due to the jolts of IPI, CPI, and the BI rate.

5 REPORTING RESULTS The results obtained, and the hypothesis developed was found to be similar. From the hypoth­ esis, ROA responded positively to the change of all the macro variables. But, after doing the IRF test, the performance of banks only deviates due to a positive variation of the CPI, and not with IPI and BI rate. This is due to an increase in national income, which is explained by higher economic growth associated with the development of the banking sector. Therefore, competition among banks with others becomes more intense and ultimately could reduce the level of bank profitability.

6 DISCUSSION This paper obtained the test results of IRF ROA to CPI changes. In the period 1 to period 12, CPI responded positively to ROA. Inflation caused by the development of the business cycle causes the economy to boom. Inflation occurs since it usually has a larger impact on the revenue than on the cost side, and leads to a bank’s good performance. The effects of inflation depend on whether it is anticipated by the bank. If inflation is fully anticipated, then the interest rate will increase to cover the hike risk. Consequently, the income rises faster than cost impacting positively on the lender’s performance and the level of profitability. Changes in IPI are positively affected by BOPO. From period to 3, economic boom due to steady capital flow results in IPI increase. BI rate, which experienced shocks, is high in the 4th period, which implies, an increase in the BI rate will improve the interest rate on deposits and changing patterns of saving society as well as other operating interest expenses. Furthermore, BOPO reacts well to the variations of the CPI in the 3rd period, whereby when there is infla­ tion but not fully anticipated by the bank, its process to adjust the interest rate is slow, 95

Chance in IPI occurred at the beginning of period 1. The LDR response was positive since the bank extends its credit precautionary principle. This extension is a result of loss in confi­ dence by the lender in peoples’ ability to pay for financing. The bank’s capacity remains tp stagnate or use the previous inflated values. The response of CPI on LDR is inspired by an increase in inflation, which in turn gives the public consumption freedom due to the increase in peoples’ purchasing power. This, however, affects the saving behavior of consumers, as they would rather borrow for consumption than put away in the bank.

7 CONCLUSION Based on the test results of impulse response function (IRF), ROA responds positively due to the shocks of the CPI, and it further varies negatively due to the changes of the IPI and the BI rate. BOPO response is affirmative from the changes in the IPI, CPI, and the BI rate. LDR tends to behave in a similar way as BOPO. REFERENCES Abusomwan, O. S. (2018) ‘Macroeconomic Performance and Performance Nexus Banking Industry: An Perfectual Evidence From Nigeria’, Global Journal of Management And Business Reasearch E-Market­ ing, 18. Agusman (2010) Kerangka Sistem Pengawasan Perbankan Ideal dalamPerekonomian Indonesia.

Fatimah, E. N. et al. (2015) Strategi Pintar Menyusun POS (Standard Operating Procedure). Yogyakarta:

Pustaka Baru. Mankiw, N. G. (2010) Introduction to Macroeconomic. Jakarta: Salemba Empat. Matthews, K., Giuliodori, M. and Mishkin, F. S. (2013) The economics of money, banking and financial markets. Boston: Pearson Higher Ed.

96

The Future Opportunities and Challenges of Business in Digital Era 4.0 – Bangsawan et al. (eds) © 2020 Taylor & Francis Group, London, ISBN 978-0-367-42594-4

Foreign investment (PMA) in the food and beverage industry (KBLI15) in Indonesia period 2000 – 2014 Total Factor Production approach (TFP) Lies Maria Hamzah Universitas Lampung, Lampung, Indonesia

ABSTRACT: TFP is a measurement of the total qualitative outputs from production inputs, changes in composition, technical progress, and work efficiency. Conversely, PMA benefits from externalities using new technology and proper management strategies capable of improving the technical efficiency of the hosting industry. This study, therefore, aims to meas­ ure the externality of FDI in the food and beverage industry (KBLI15) using the residual TFP approach. Data were obtained from the Indonesian manufacturing industry on KBLI 15 from 2000 to 2014 and the Central Statistics Agency (BPS). The results showed that an increase in productivity is also influenced by technological innovation. The difference in residues in vary­ ing industries is due to the level of technology, labor quality, quality of raw materials, and the management used by MnC. Keywords:

externality, food, beverage industry (KBLI15), PMA, TFP

1 INTRODUCTION The Foreign Investment (PMA), mostly carried out by MnC, leads to additional invest­ ment and externalities obtained by the hosting industry. Furthermore, changes in technol­ ogy and new management increase productivity, which improves technical efficiency to achieve economies of scale. Gorg and Greenway (2004), Wang & Blomstrom (1992) stated that increasing company efficiency leads to TFP growth. It explains all qualitative changes in labor and capital, including composition and intensity of demand, economic restructuring, and technical progress, which work together efficiently. In addition, the Solow residuals tend to measure factors that are sometimes ignored, such as technical effects and organizational innovation and which are undesirable. According to studies, Hicks parameters are empirically used to measure factors that are equal to the level of capital growth which is weighed by externalities (Gorg and Greenway (2004), Suyanto et al., (2010), Findlay (1978), Fosfuri, et al., (2001)). Wang & Blomstrom (1992) stated that PMA increases industrial efficiency in the host country, which leads to TFP growth. Liu (2008) reported that PMA consists of negative and positive effects, which are seen in its ability to reduce and increase TFP, respectively. Furthermore, a rise in TFP increases industrial productivity. The development of PMA ownership in the manufacturing industry sector in Indonesia has continued to increase. For instance, the food and beverage industry (KBLI 15) empirically increased productivity with the externalities of FDI from 2000 to 2012. In Indonesia, the efficiency level of manufacturing industries that uses foreign capital is higher compared to those with domestic capital. This is because the externality of PMA increases the ability of labor and industrial productivity (Hamzah LM, 2015). This research, therefore, aims to determine whether the owner of foreign direct investment in the food and beverage industry (KBLI 15) has the ability to provide posi­ tive domestic externalities. 97

2 LITERATURE REVIEW According to research, technological advances have the ability to affect capital goods and human resources in order to improve efficiency. Paul Krugman proposed the theory of Total Factor Productivity (TFP) as a measure of the efficiency with the ability of output growth to occur due to the accumulation and use of inputs such as capital and labor in technological mas­ tery. Lipsey (1992) stated that changes in technology allow the production process to run more efficiently. The increase in TFP reflects the use of more efficient inputs, and TFP is often used as a measure of long-term or dynamic technological change brought by factors such as technical innovation. It has the ability to explain the technological, human capital, and organizational innovation of intangible inputs and labor. Also, the TFP is calculated as a residual aggregate production function of a simple Cobb-Douglas production function. This residual is a weighted average share of the level of augmentation factor used to measure changes in TFP. It is also a valid measurement of the shift in production function under the Solow assumption. However, because the residual TFP model treats all capital as an exogenous factor, it tends to play down the role of innovation in the growth process. Furthermore, its capital accumulation level needs to be calculated together with the innovation’s impact on economic growth. Conversely, TFP growth includes the effects of both technical progress, which includes a shift in the production function and return of movement to the scale that are not constant (Diewert, 2001).

3 METHODS This study uses panel data of the food and beverage manufacturing industry in Indonesia, and the results of a 2000 BPS survey in 2014 with a three-digit KBLI. Furthermore, the TFP prod­ uctivity measurement using the Cobb-Douglas production function and the Solow residual method was used to decompose the source of output/input growth and changes in TFP (β0), which is obtained through regression. The coefficient value obtained from the estimated pro­ duction function is used to calculate the amount of TFP growth using the following equation:

Note: tfpit = total factor of the company i production in KBLI three-digit year t,

yit = value of company output i in year t (rupiah),

lit = number of company i laborers in KBLI 3 digit year t (person),

kit = total capital companies in KBLI 3 digit year t (rupiah),

pmait = total foreign investment of companies in KBLI 3 digit year t (percentage),

βl, βk, βpma = parameters of productivity, labor, and PMA to domestic companies

μit= error term

4 RESULTS

Table 1.

Estimation result.

Variable

Coefficient

Std. Error

t-Statistic

Prob.

C Y K L PMA R-squared

-4.197497 0.999963 -0.103807 -0.739259 -0.826749 0.999963

3.39E-12 9.40E-14 3.36E-14 1.31E-13 5.21E-13

-1.24E+12 1.06E+13 -3.09E+12 -5.64E+12 -1.59E+12

0.0000 0.0000 0.0000 0.0000 0.0000

Source: data processed, 2018

98

5 DISCUSSION PMA externalities tend to increase productivity through a residual approach, which is nega­ tive at the beginning of the observation period and positive at the end. In the framework asso­ ciated with endogenous growth, it provides adequate time to achieve the right quality of labor, technological innovation, and input. When the input quality of production increases, the efficiency of industrial production rises. TFP is the effect of technological changes in effi­ ciency and shifting frontier production functions. Positive and significant TFP values indicate technological innovations, management, and an increase in labor quality in the industry. It also affects the output of the manufacturing industries and changes the managerial capabilities of human resources. The impact of FDI on TFP growth is an important factor in technology transfer. The heterogeneity that occurs in companies is seen from the value of the industrial intercept. Food and drink industries are examples of negative intercepts, while dairy and rice processing industries are positive intercepts. Most food processed industries (KBLI 151) in Indonesia have been merged, while others are acquired by foreign companies (MnCwhich affects the production process. This is because the production process is carried out using better technology and labor. The dairy industry type (KBLI 152) has so far been largely con­ trolled by MnC, with imported raw materials.

6 CONCLUSION AND RECOMMENDATION In conclusion, the TFP model is an important technical change used to increase industrial productivity and investment. This is because capital accumulation is a direct result of TFP growth under steady-state conditions. Based on the analysis of comparative and competitive advantages, it is aimed at strengthening the food and beverage industry clusters. Therefore, to increase the competitiveness of production, priority is given to promotion in order which encourages innovation, strengthens the position of market share as well as food trade chains, and promote a supportive business environment. REFERENCES Aiyar Shekar & James Feyrer., 2002, “A Contribution to the Empirics of Total Factor Productivity”, IMF, 1–38. Botirjan Baltabaev, 2012, FDI and Total Factor Productivity Growth: New Macro Evidence, Depart­ ment of Economics, Monash University, Clayton, Australia. Baltagi, B.H., 2001, Econometric Analysis of Panel Data, John Wiley and Sons, New York. Blomström, M., A. Kokko, and S. Globerman., 2001, “The Determinants of Host Country Spillovers from Foreign Direct Investment: A Review and Synthesis of the Literature”, in N. Pain(ed.), (London: NIESR), 34–65. Diewert, W.E., And Nakamura, A.O., 2002, “The Measurement of Aggregate Total Factor Productivity Growth”, Elsevier Science Handbook of Econometrics, Volume 6, edited by J. J. Heckman and E. E. Leamer. University of Chicago, Hal 1–65. Gorg, H., and Strobl, E., 2004, “Foreign Direct Investment and Local Economic Development; Beyond Productivity Spillovers”, Research Paper Series, University of Nottingham No. 2004/11. Hamzah, L.M., 2015, Dampak Spillovers Penanaman Modal Asing (PMA) Terhadap Industri Manufak­ tur di Indonesia Tahun 2000-2010. Disertasi. Hulten, R Charles., 2001, “Total Factor Productivity a Short Biography”, National Bureau of Economic Research, 1–35. Javorcik, S. B., 2004, “Does Foreign Direct Investment Increase the Productivity of Domestic Firms? In Search of Spillovers through Backward Linkages”, American economic review, 94, 3.605–27. Romer, D., 1990., “Endogenous Technical Change”, Journal of Political Economy,98(5), 71–102. Shekhar Aiyar, James Feyrer, 2002, A Contribution to the Empirics of Total Factor Productivity, Dartmouth College.

99

The Future Opportunities and Challenges of Business in Digital Era 4.0 – Bangsawan et al. (eds) © 2020 Taylor & Francis Group, London, ISBN 978-0-367-42594-4

The effectiveness of business development for rural agricultural business and its effect on the income of farmers group members in Wates Jaya, Lampung Barat District Muhammad Husaini & Meydi Tia Fani Universitas Lampung, Lampung, Indonesia

ABSTRACT: The purpose of this research was to discuss the effectiveness of a program implemented and its effect on the income of farmers with membership in GAPOKTAN in Wates Kecamatan Balik Bukit, West Lampung. The program was called BLM PUAP, and it was developed to improve agricultural business for the villagers in Wates Village. Quantita­ tive descriptive analysis was used in the research, and the result showed (1) the program was effectively implemented to measure the easiness of the borrowing procedure, punctuality of credit, low-interest rate, and qualified facility for the program and (2) the program has a positive effect on the improvement of farmers income in Kecamatan Balik Bukit. How­ ever, the intensity of monitoring and guidance lacked despite the effective implementation of the program. Keywords:

effectivity, PUAP program, vegetable farming business

1 INTRODUCTION In an effort to overcome agricultural problems in rural areas, the Ministry of Agricul­ ture implemented the Rural Agribusiness Business Development Program (PUAP) in 2008 as part of the National Community Empowerment Program (PNPM) through ven­ ture capital assistance to develop agribusiness businesses according to the potential of the targeted villages. West Lampung Regency, with its capital city Liwa is one of the fifteen districts in the Lam­ pung Province region, and the contributor of the largest GRDP to the agricultural sector, which was recorded to be 53.4% in 2017. Moreover, based on statistical data, Balik Bukit is the sub-district with the largest vegetable production in West Lampung Regency, while Watas Village benefits the most in the PUAP aid funds with 500 people working as horticultural farmers and 158 in Gapoktan. Therefore, this study was conducted to evaluate the effectiveness of the PUAP program implementation and its effect on the income of members of Gapoktan Watas Jaya, Watas Vil­ lage, Balik Bukit District, West Lampung Regency. 2 METHODS The population of this study included farmers with membership in Gapoktan, while a sample of 61 respondents was selected using purposive sampling. The data collection techniques used include the distribution of questionnaires to selected respondents using a Likert scale as an indicator. Moreover, to assess the effectiveness of the

100

implementation of the PUAP program, the rating is divided into five categories of (5) Very Effective (SE), (4) Effective (E), (3) Less Effective (KE), (2) Not effective (TE), and (1) Very Ineffective (STE). For example, there are five indicators for the Effective­ ness of BLM Distribution to farmers, and the score obtained was between 305-1525. The least score of 305 was calculated by multiplying the lowest score of 1 with the number of parameters five and number of respondents (61) or (1 x 5 x 61 = 305) while the highest score of 1525 was obtained from the multiplication of the highest score of 5 with the number of parameters which is 5 and 61 respondents (5 x 5 x 61 = 1525). The interval for each level of assessment was determined by subtracting the lowest score from the highest score, and the result divided by the rating category of 244 depending on the scale of each category. The same process was conducted for all indi­ cators, including the quality of facilities received by farmers, the human resources cap­ acity of program managers, and the income of Gapoktan members.

3 RESULTS The effectiveness of PUAP program implementation was measured using (1) Distribution of BLM-PUAP to Farmers, (2) Quality of Facilities received by the participants, (3) Capability of Human Resources Program Managers, and (4) Income of Gapoktan members. 3.1 Effectiveness of PUAP fund distribution to farmers The indicators are as follows: a. b. c. d. e.

Table 1.

Very effective Effective Effective enough Less effective Not effective

1282 1038 794 550 305

- 1525 - 1281 - 1037 - 793 - 549

Respondents’ answers to the effectiveness of BLM-PUAP distribution to farmers.

Answer Scale

Weight (B)

Frequency (F)

Score (BxF)

Very Good Good Good Enough Poor Not Good

5 4 3 2 1

28 98 137 41 1

140 392 411 82 1

Total

Score 140 392 411 82 1 1026

Sources: Survey result, data calculated.

The table shows the effectiveness of the distribution of BLM-PUAP to farmers, in general, was quite effective as indicated by a score of 1026, which is included in the quite effective cat­ egory. Each question item on the questionnaire, such as timeliness, prerequisite accuracy, the accuracy of the procedure, suitability of the load and the amount of assistance, and loan inter­ est rates were classified under good enough and good categories.

101

3.2 The quality of facility for the participants of PUAP

The Facility Quality indicators received by the BLM-PUAP Participants are as follows:

Table 2.

Respondents’ answers on the quality of facilities received by PUAP participants.

Answer Scale

Weight (B)

Frequency (F)

Score (BxF)

Score

Very Good Good Good Enough Not Good Enough Poor

5 4 3 2 1

6 55 145 139 21

30 220 435 278 21

30 220 435 278 21

Total

984

Sources: Survey result, data calculated.

The table shows the level of counseling received by BLM-PUAP assistance participants was quite effective, as indicated by the value of 984 obtained. The reports from the questionnaire showed the counseling received by participants was averagely between 5 to 8 times a year, and this was considered good enough to help farmers run their busi­ nesses. The material and technical guidance provided by the management were con­ sidered to be quite good, although the participants’ level of understanding of the material provided was relatively poor. 3.3 Capability of human resources program managers The indicators of the quality of human resources managing BLM-PUAP are as follows: Table 3.

Respondents’ answers on program manager human resources capability.

Answer Scale

Weight (B)

Frequency (F)

Score (BxF)

Score

Very Good Good Good Enough Not Good Enough Poor

5 4 3 2 1

20 72 108 44 0

100 288 324 88 0

100 288 324 88 0

Total

800

Survey result, data calculated.

The table shows the program manager’s human resources capability has a score of 800, and this means they are categorized as quite effective in running the program due to the abil­ ity to provide good enough service with a convoluted loan system with repayment and inter­ est in installments. However, the monitoring provided by the management was not good enough.

102

3.4 Income of GAPOKTAN members

The indicators of income received by the BLM-PUAP participants are as follows:

Table 4.

Respondents ‘answers on Gapoktan members’ incomes.

Answer Scale

Weight (B)

Frequency (F)

Score (BxF)

Score

Very Good Good Good Enough Not Good Enough Poor

5 4 3 2 1

20 83 107 33 1

100 332 321 66 1

100 332 321 66 1

Total

820

Survey result, data calculated.

The table shows the PUAP program was quite effective in increasing the income of BLM­ PUAP participants. This is indicated by the value of the respondent’s answer score of 820. This was observed to be due to the good selling value as a result of the capital assistance pro­ vided in accordance with the needs and the value of the loan in accordance with the area of arable land to reduce the arrears of loan payments. Based on the scores above, there was an increase in the farmers’ income from the capital assistance channeled by the PUAP program.

4 CONCLUSION 1. The PUAP program in the Watas Village, Balik Bukit Subdistrict, was implemented effect­ ively as measured by the ease of lending procedures, timeliness of loan funds delivery, and low lending rates. 2. The quality of facilities in the form of counseling, guidance, and technical assistance pro­ vided by PUAP managers was quite effective in helping farmers overcome several problems in the field. 3. The effectiveness of the distribution of funds and the ability of the program manager’s human resources have a positive effect by increasing the income of the farmers.

REFERENCES Badan Pusat Statistika (BPS) Kabupaten Lampung Barat, 2017. Lampung Barat Dalam Angka.

Badan Pusat Statistika (BPS) Povinsi Lampung, 2017. Lampung Dalam Angka.

Budianto, Hilman. 2016. Respon Anggota Gabungan Kelompok Tani Terhadap Program Pengemban­ gan Usaha Agribisnis Pedesaan (PUAP) Kecamatan Tebu Kabupaten Lampung Barat. Lampung: Fakultas Pertanian Universitas Lampung. Dinas BP2KP Kabupaten Lampung Barat, 2016. Program Usaha Pengembangan Agribisnis Pedesaan Kabupaten Lampung Barat. Dinas BP3KP Kabupaten Lampung Barat, 2016. Data Gapoktan Kecamatan Balik Bukit. Harun, Al – Rasyid. 2004. Teknik Penarahajan Sampel Dan Penyusunan Skala. Program Pasca Sarjana UNPAD. Bandung. Kementerian Pertanian. 2011. Pedoman Umum Pengembangan Usaha Agribisnis Perdesaan 2011. http:// PUAP.pertanian.go.id/simPUAP/info/PEDUM 2011.pdf. Setiaji, Haryo. 2013. Dampak Program Pengembangan Usaha Agribisnis Pedesaan Terhadap Pendapa­ tan Anggota Gabungan Kelompok Tani. Semarang: Program Sarjana Fakultas Ekonomika dan Bisnis Universitas Diponegoro. Zahara, Jamhari Hadipurwanta. 2012. Dampak Program PUAP Terhadap Petani Padi Penerima BLM – PUAP di Lampung. Balai Pengkajian Teknologi Pertanian Lampung.

103

The Future Opportunities and Challenges of Business in Digital Era 4.0 – Bangsawan et al. (eds) © 2020 Taylor & Francis Group, London, ISBN 978-0-367-42594-4

The influence of households and labor in fishery industry on industrial agglomeration in Tanggamus District Emi Maimunah, Ahmad Dhea Pratama & Ukhti Ciptawaty Universitas Lampung, Lampung, Indonesia

ABSTRACT: This study aims to explore the effect of fisheries-based industrial agglomer­ ation and demographic features in Tanggamus Regency between 20 subdistricts using the fixed-effect model analysis tool. The Central Statistics Agency (BPS), the Department of Fish­ eries and Maritime Affairs were the secondary sources of data in this research, which was con­ ducted between the years of 2012 and 2016. The results were assessed using the Hoover Balassa Index analysis tool, and they indicated a substantial degree of agglomeration in only six districts. Further analysis reveals the accumulation is significantly related to household fisheries (X1) and fisheries labor (X2). Keywords:

agglomeration, balassa hoover index, fishery industry

1 INTRODUCTION The primary purpose of agglomeration or concentric theory is to integrate business groups for the chosen location to attract and encourage upcoming investment ventures. Clustering and location are linked, which explains the need to analyze a locality when determining the right place to settle companies. One area could be used for the production of goods and services as well as settlement (Richardson, 2001). Lampung possesses a fairly extensive coastal area. It has a land area of 35288.35 km2 (Cen­ tral Bureau of Statistics, 2009). Additionally, its coastline is 1,105 km long (including 69 small islands) to form four seaside areas. Lampung is at the center point of the meeting of the Java Sea and the Indian Ocean, making the area a major marine commodities producer, averaging 128,579 tons per year and processing fishery-related products averaging 11.4238 tons annu­ ally. The province, therefore, accounts for the majority of fisheries due to the presence of the natural resource together with its favored geographical location.

2 LITERATURE REVIEW Agglomeration is the spatial concentration of economic activity in urban areas to save on space (economies of proximity) related to clusters of companies, labor, and consumers (Kun­ coro, 2002). The benefit derived from this centralization as a result of economies of scale is called agglomeration economies. Agglomeration advantages arise if there is a close link between economic activities with output. These linkages will lead to external benefits for employers, in production cost savings, transportation expenses of raw materials, and production utility charges that could be shared. The savings would then be able to lower costs incurred by employers, which in turn increases their competitiveness. Cost reduction plays a significant role in improving produc­ tion efficiency and the growth of economic activities in the subject area. Macro benefits of centralization include; 104

1) Advantages of large scale (large-scale economies) 2) Advantages of localization (localization economies) 3) Advantages of urbanization (urbanization economies)

3 METHOD Agglomeration analysis based on the Balassa index was obtained from the formula below:

Where: i = Sector; j = Region; E = Labor 1. 2. 3. 4.

Human resources in the marine endowment in subdistrict. Staff in the fishing quarter in all districts. The workforce in the agricultural industry. Personnel for all industrial sectors.

The study uses the OLS model and a combined statistics panel of time series and crosssection data by getting a good regression line. Predictions as close as possible to the actual data or the values of β0 and β1, cause the smallest possible residue. The relationship Y and X (the dependent and independent variables, respectively) are linear in the parameter. If more than one independent variable is used in the regression, it is assumed there is no linear rela­ tionship (Widarjono, 2017). Regression first tests classic assumptions: choose the panel model between pooled least square method, fixed, or random effect. Second, do the three trials thattest how Lagrange Multiplier (LM), and Hausman work. And, lastly, check the direction that t-statistics and f-statistics map out.

4 RESULTS Out of 20 districts, 6 showed a strong agglomeration index of >4:Wonosobo, City Court, Eastern City Court, West City, Klumbayan, and Balak subdistrict. The selection panel of data regression estimation technique identified three kinds of approaches, namely, the fixed, random, and common effects. To determine the best tech­ nique to be used for the panel data regression, test chow, Hausman, and LM. This method approaches the ordinary least square (OLS) to estimate the panel data model. Household fishery (X1) and labor (X2) had apositive and significant impact on fisherybased industrial agglomeration. This research seeks to find the areas most concentrated with the fishing industry and the impact it has on the economic activities in the area; and also, how localization contributes to fish output. 4.1 Reporting research results Initial hypothesis found agglomeration level index value of > 4 as follows:

105

Table 1. Balassa index 2012–2016. Subdistrict

Value Balassa Index 2012–2016

Wonosobo City District Eastern City West City Klumbayan CukuBalak

4.43 > 4 6.27 > 4 5.45 > 4 5.60 > 4 5.05 > 4 5.76 > 4

Source: Processed Balassa index calculation, 2019.

The results of the Balassa index in 2012–2016, if greater than 4, have a high level of agglom­ eration. In the hypothesis using the Balassa index, the concentration of industry was witnessed heavily in 6 of the 20 districts under study. Panel data analysis for the total period included 5 crosssections, 6 (balanced) observations, 30 using the fixed model, and assumption tests performed that wereauto-created, heterosce­ dasticity, and multicollinearity if not, there are no problems in the model used. Households (X1) have a positive and significant effect on agglomeration with regression coefficients. Labor (X2) has a positive and significant effecton agglomeration. This second variable is equally influential. Table 2. Variable LN_LBR LN_FHS C

Result panel data regression: Fixed model. Coefficient 1.255124 0.496332 –3.825945

Std. Error 0.155948 0.202410 0.880668

t-Statistic 8.048365 2.452116 -4.344369

Prob. 0.0000 0.0226 0.0003

Source: Processed reviews data, 2019.

The study was using the statistical T-test and F statistic with one-way trial and using indi­ vidual effects and getting the scores from six observation areas.

5 DISCUSSION Based on the regression calculation and testing, household fisheries (X1), and labor (X2), had a significant influence on agglomeration, described as follows: a. Effect of household fisheries (X1) on agglomeration Results of research indicating household fisheries to have a positive and significant effect on agglomeration are in line with a study by Head (2017), which examined the location choices of 751 Japanese manufacturing plants built in the USA since 1980. Conditional logic esti­ mates support the hypothesis; industry-level agglomeration benefits play an important role in location decisions. Recent theories of economic geography suggest that firms in the same industry may be drawn to the same locations since proximity generates positive externalities or agglomeration effects. Under this view, chance events and government inducements can have a lasting influence on the geographical pattern of manufacturing. b. Influence of labor (X2) on agglomeration Research results on labor and agglomeration indicate workforce is one of the factors needed for production. If provided, industrial agglomeration increases productivity. Tang­ gamus has enough manpower to support the fishing industry, as was earlier presented by Rastvortseva (2017). Economic localization in industrial Russia estimated regional dynam­ ics in the number of people involved in the manufacturing industry for 2002 to 2014 total 106

savings at 28.23%, which was linked to the presence of agglomeration, natural resources, and human resources in the industry.

6 CONCLUSION The results of the Balassa index indicates 6 subdistricts with high levels of concentration and contribution to the agglomeration of the fisheries-based industry. The results were calculated from a total of 20 subdistricts included in the study. However, only a few of them scored highly on the localization, indicating Wonosobo, City Attorney, City Attorney West, East Great City, Balak, and Kelumbayan districts were worth including as concentrated centers. Two districts had a mid-level score, while 12 had a low index. (X1) household and (X2) labor had a positive and significant impact on fishery-based industrial agglomeration in Tanggamus. REFERENCES Book Small and Medium Industry Data Tanggamus. (2016). Department of Trade and Industry Tanggamus. Djojodipuro, M. (1992). Theory of Location. Jakarta: Issuing Faculty of Economics, University of Indonesia. Emalia, Z., & Arivina. (2015). Theory and Application Area Concept. Top AnugrahProg (AURA). Henderson, J. V. (2003). The urbanization process and economic growth: The so-what questions. Journal of Economic Growth. Head, K. (2000). “Agglomeration benefits and location Choice: Evidence from Japanese manufacturing investments in the United States.” Journal of International Economics, 38(3–4, May 1995), 223–247. Kuncoro, M. (2002). Spatial Analysis and Regional Studies and the Agglomeration. Mc Donald, J. F. (1997). “Fundamentals of urban economics.” New Jersey: Prentice-Hall, Journal of Urban Economics, 26(3), 361–385. Richardson, H. W. (2001). Fundamentals of Regional Economics. Jakarta. Faculty of Economics, Uni­ versity of Indonesia. SadonoSukirno. (2004). Macroeconomics: Theory Introduction. King GrafindoPersada, Jakarta. Rastvortseva, S. (2017). Agglomeration Economics in Regions: The Casein the Russian Industry. World Economy Department - National Research University Higher School of Economics, Russia. Tarigan, R. (2005). Regional Economics: Theory and Applications. Earth Literacy:Jakarta. The Central Bureau of Statistics Year 2012–2016. Tanggamusin Figures. BPS Tanggamus, Lampung Province. Widarjono, A. (2007). Ekometrika Theory and Aplikasi. Yogyakarta: Ekonisia FE UII. Widarjono, A. (2017). The Introduction and Application of the Econometrics Empat. Yogyakarta edition, UPPSTIMYKPN.

107

The Future Opportunities and Challenges of Business in Digital Era 4.0 – Bangsawan et al. (eds) © 2020 Taylor & Francis Group, London, ISBN 978-0-367-42594-4

An experimental study of the gender differences in risk aversion portfolio selection in Indonesia Intan Crusita Putri, Agrianti Komalasari, Farichah & Rindu Rika Gamayuni Universitas Lampung, Lampung, Indonesia

ABSTRACT: The research aims to test the behavior of portfolio investment risk aversion in making investment decisions with a cross-gender portfolio in Indonesia. Experimental testing was used to measure portfolio investment risk avoidance behavior. Consequently, the purpose of this research is to contribute to accounting studies on portfolio investment risk avoidance behavior when making investment decisions with a cross-gender portfolio, particularly in Indonesia. The study population was all students of Masterx of Accounting Science from the University of Lampung, while part of the population was also sampled from students pursuing the Theory of Financial and Capital Markets. The study is unique in the sense that it employed the use of different measurement variables that are predominantly used in Indo­ nesia. These techniques are referred to as experimental methods. Keywords:

gender, risk, aversion, selection, Indonesia

1 INTRODUCTION Stock trading in capital markets is an activity where uncertainty reigns high enough to war­ rant the manifestation of investor behavior. These investors often exhibit irrational behavior by taking action only under certain considerations. Making investment decisions based on rational decision-making processes confines their cognitive abilities, such as customs, know­ ledge, and external environmental factors. The impact of these factors further complicates the decision. Both psychological and environmental factors play a role in influencing the investor decision-making process so that investors are not always rational in their behavior choice (Pak & Mahmood, 2015). Previous studies provide empirical evidence that men are more courageous in taking invest­ ment risks than women. Research by Baffaur, Mohammed, and Rahaman (2019) explains that women are more risk averse than men: they both differ in their emotional reactions to situations that are uncertain, and this differential emotional reaction elicits diversification in risk-taking. This study is further given a boost by similar claims from other works such as Faff, Hallahan and McKenzie (2011), Barber and Odean (2001), Croson and Gneezy (2009), Charness, and Gneezy (2007) and Borghans et al. (2009). In contrast to the results previously described, a study by Bogan et al. (2013) showed that there exists no difference in risk aversion between men and women. In a portfolio management team, team composition, whether more women or more men, did not affect the financial decisions con­ cerning risk assessment and loss. This study found evidence that men’s presence increases the like­ lihood of choosing a higher-risk investment. However, a team that only contains men is not the most likely to seek risk. Moreover, it also found out that men’s teams can be risk averse too. Research by Maxfield et al. (2010) showed that there is gender neutrality in the trend of risk and decision-making in the context of the special managerial besides the allocation of the portfolio.

108

2 RESEARCH ISSUE The Indonesian capital market can be categorized as an emerging market, and it is a developing market consisting of several market players who are still learning and are largely dominated by men. This was evidenced in the news release 21 Years KSEI dubbed “Innovation for Leisure Capital Market Transactions.” The graph showing the growth of the total number of SID ranged from 2012 to 26th December 2018. The total assets recorded in C-BEST as of December 26, 2018, were dominated by local-investor ownership at 54.71%. This was an increase from the previous year, as of December 2017, in which local ownership stood at 54.50%. The gender demographic data of investors in Indonesia put men on top, occupying 59.13% of the whole. Additionally, the majority of investors (39.72%) are aged between 21 and 30 years. Those who work in the private sector made 58.27%, while Bachelor degree holders formed 51.42%. This data was obtained from www.ksei.co.id in 2018. From the above data, it can be seen that the cap­ ital market in Indonesia is still dominated by men at 59.13% which is proof enough that in the case of uncertainty on the capital markets, a men can be said to be brave and like a risk when compared with women.

3 LITERATURE REVIEW Decision-making by investors, according to Pak and Mahmood (2015), was influenced by both psychological and environmental factors, as well as habits, age, gender, knowledge of the investors, and preferences for risk. When observing risk preferences by investors, their behav­ ior can be grouped into three categories, namely, investors who like risk (risk takers), investors who are neutral to risk (risk neutrality), and investors who avoid risk (risk averse). According to Basyaib (2007), risk is the possibility of undesirable results so that only risk associated with situations that allow for the emergence of negative results are linked to the ability to estimate the occurrence of negative results. Risk differs from uncertainty, in that risk has a clear probability – for instance, a bag con­ taining 10 balls which consists of 5 green balls and 5 yellow balls. Uncertainty, on the other hand, bears the probability of an unknown, a bag containing 10 balls where it is not known how many balls are green and how many balls are yellow (Ellsberg, 1961). This study further found that investors would prefer to invest their money on an investment plan with a greater probability than when the probability is unknown. Risk aversion is a preference for investors who have a low risk tolerance so the allocation of more assets in fixed income instruments or assets is risk free and done in smaller stocks. Investors with risk aversion could still not tolerate small risks. Therefore, risk aversion was the level of unwillingness and inability to take risks. 3.1 Risk aversion and portfolio investment decision making Risk is a factor that is usually feared by everyone, including investors. Differences in the reaction of investors to the risk is an indicator of how everyone can accept risk. There were those who only accepted low risk, while some were able and prepared to bear the risk. Eventually, investor behavior can further be classified as risk seekers, risk neutrality, or risk aversion. Hartono (2010) states that risk is one of the trade-off factors that must be taken into consid­ eration when making an investment. The other factor is the return volume. Research by Ellsberg (1961) found that there is a preference for events whose probabilities are known rather than unknown. It shows that investors are risk averse. Guiso et al. (2018) further explain that after the 2008 crisis, risk aversion measures increased substantially. The following hypothesis is proposed based on the study above: H1 Risk aversion affects decision-making portfolio investments. 109

3.2 Risk aversion and gender portfolio investment decision-making Men and women have different emotional reactions to situations that are uncertain, and this different emotional reaction leads to differences in risk taking. Eckel and Grossman (2008) found no difference in attitudes between men and women in the face of risk. The experiments were done on students with the aim being to prove the existence of a relationship between risk attitude and psychological characteristics in making financial decisions, and that women are significantly more risk averse than men. Research by Charness and Gneezy (2007) examined the psychologically biased determinants of risk aversion, and the results indicate that there are significant differences in treatment experiments. The average total investment in treatment ambiguity by men was higher than women. Baf­ faur et al. (2018) explains that women are more risk averse compared to men: this research is in line with similar findings by scholars (Barber & Odean, 2001; Agnew et al., 2008; Borghans et al., 2009; Croson & Gneezy, 2009; Faff et al., 2011; Zeffane, 2015), all of whom share the similar conviction that women are more risk averse than men. Conversely, the following hypothesis is proposed based on the above findings: H2 There are differences in risk aversion between men and women. Based on the test results of impulse response function (IRF), ROA responded positively to the shocks of the CPI, and ROA behaved negatively to the shocks of the IPI and the BI rate. And, for the performance variables, ROA was affirmative due to the shocks of the IPI, CPI, and the BI rate. And, banking performance LDR was encouraging due to the jolts of IPI, CPI, and the BI rate.

4 REPORTING RESULTS The results obtained, and the hypothesis developed, were found to be similar. From the hypothesis, ROA responded positively to the change of all the macro variables. But, after doing the IRF test, the performance of banks only deviates due to a positive variation of the CPI, and not with IPI and BI rate. This is due to an increase in national income, which is explained by higher economic growth associated with the development of the banking sector. Therefore, competition among banks with others becomes more intense and ultimately could reduce the level of bank profitability.

5 DISCUSSION This study is experimental research whose design focused on an experimental group as well as the control group. Both groups were exposed to different study techniques repeatedly, such that the expected outcome improved the quality of observation, especially in suppressing con­ founding variables that might occur during the study. In experimental testing, the author shows participants two slide shows. The first slide show highlights the negative features of investment options and provides annuities as a solution to avoid shortages of investment. The second slide show, on the other hand, highlights the nega­ tive features of an annuity option and provides investment options as a solution to overcom­ ing annuity shortages. The tool used for the experiment is cash. Next, participants are asked to play the “Retirement Game.” Finally, every investor places their preference respectively against the risk; they differ only in how much each person accepts the risk. The results were as follows; some participants only accepted low risk, while some were prepared to bear the risk. Most investors are risk averse, which means they would avoid any risk that may occur in their portfolio. The decision of investors to take or avoid risks is also based on the investor’s psychological factors, such as age, gender, and habits. Men and women have a difference in their emotional reactions to situations that are uncertain, and this different emotional reaction produces differences in risk-taking. 110

6 CONCLUSION This research contributes to the field of accounting behavior of portfolio investment in risk aversion with respect to the cross-gender portfolio in Indonesia. It is expected to become a reference to various groups; for example, investment advisors, must consider personal char­ acteristics and risk tolerance of investors when giving out investment advice. The uniqueness of this research is that it tries to compare risk-aversion preferences between men and women utilizing the experimental method using student subjects. The results are expected to provide information to practitioners such as managers, company executives, gov­ ernment regulators, and investors about portfolio investment policies. The limitation of this study is that it was limited to students of Masters in Accounting at the University of Lampung, and therefore the results may be difficult to generalize because they are only limited to subjects in experimental research. Future recommendation for this study is to include other variables that might influence portfolio decision-making, such as age, level of education, and investment experience. Similarly, future research should also expand the sample subjects to include not only students but nonstudents. REFERENCES Agnew, J. R., et al. (2008). “Who chooses annuities? An experimental investigation of the role of gender, framing, and defaults.” American Economic Review. American Economic Association, 98(2), 418–422. doi: 10.1257/aer.98.2.418. Baffour, P. T., Mohammed, I., & Rahaman, W. A. (2019). “Personality and gender differences in revealed risk preference: Evidence from Ghana.” International Journal of Social Economics, 46(5), 631–647. doi: 10.1108/IJSE-07-2018-0346. Barber, B. M., & Odean, T. (2001). “Boys will be boys: Gender, overconfidence, and common stock investment.” The Quarterly Journal of Economics. Oxford University Press (OUP), 116(1), 261–292. doi: 10.1162/003355301556400. Basyaib, F. (2007) Manajemen Risiko. Jakarta: Grasindo. Borghans, L., et al. (2009) Gender Differences in Risk Aversion and Ambiguity Aversion. Cambridge, MA: National Bureau of Economic Research. doi: 10.3386/w14713. Charness, G., & Gneezy, U. (2007). “Strong evidence for gender differences in investment.” SSRN Elec­ tronic Journal. Elsevier BV. doi: 10.2139/ssrn.648735. Croson, R., & Gneezy, U. (2009). “Gender differences in preferences.” Journal of Economic Literature, 47(2), 448–474. doi: 10.1257/jel.47.2.448. Eckel, C. C., & Grossman, P. J. (2008). “Forecasting risk attitudes: An experimental study using actual and forecast gamble choices.” Journal of Economic Behavior & Organization, 68(1), 1–17. doi: 10.1016/ j.jebo.2008.04.006. Ellsberg, D. (1961). “Risk, ambiguity, and the Savage Axioms.” The Quarterly Journal of Economics. Oxford University Press (OUP), 75(4), 643. doi: 10.2307/1884324. Faff, R., Hallahan, T., and McKenzie, M. (2011). “Women and risk tolerance in an aging world.” Inter­ national Journal of Accounting & Information Management. Elsevier BV, 19(2), 100–117. doi: 10.1108/ 18347641111136427. Guiso, L., Sapienza, P., & Zingales, L. (2018). “Time varying risk aversion.” Journal of Financial Eco­ nomics, 128(3), 403–421. doi: 10.1016/j.jfineco.2018.02.007. Hartono, J. (2010). Teori Portofolio dan Analisis Investasi. Yogyakarta: BPFE. Maxfield, S. et al. (2010). “Gender and risk: Women, risk taking and risk aversion.” Gender in Manage­ ment: An International Journal. Emerald, 25(7), 586–604. doi: 10.1108/17542411011081383. Pak, O., & Mahmood, M. (2015). “Impact of personality on risk tolerance and investment decisions.” International Journal of Commerce and Management, 25(4), 370–384. doi: 10.1108/IJCoMA-01-2013-0002. Zeffane, R. (2015). “Trust, personality, risk taking and entrepreneurship.” World Journal of Entrepre­ neurship, Management and Sustainable Development. Emerald, 11(3), 191–209. doi: 10.1108/wjemsd­ 08-2014-0025.

111

The Future Opportunities and Challenges of Business in Digital Era 4.0 – Bangsawan et al. (eds) © 2020 Taylor & Francis Group, London, ISBN 978-0-367-42594-4

Forecasting tourism demand using the trend models method: Evidence from Indonesia Henni Kusumastuti, Novalia & Adelina Anum Sang Bumi Ruwa Jurai University, Indonesia

ABSTRACT: This research was conducted to investigate the best trend model and to fore­ cast the number of tourist visits to Indonesia. The data used in this research is secondary data related to the number of tourists visiting Indonesia from January 2017 to July 2019. Forecast­ ing tourism demand, such as tourist visit numbers, was carried out by statistical methods. The statistical method used in this research is the trend model, such as the linear, logarithmic, inverse, quadratic, and cubic trends. It was found that the lowest MSE value is the MSE value of the logarithmic trend of 1.252e10. Hence, the best model to use to forecast the number of tourist visits is the logarithmic trend with Yt = 1018383.999 + 79795.923 in (t). The average forecast number of tourists visiting Indonesia in 2020 is projected to reach 1,317,314. Keywords:

forecasting, tourist visits, trend model

1 INTRODUCTION To show the strength of the foreign exchange economy, countries are considered wealthy if they have significant foreign exchange. The number of tourists visiting Indonesia from various countries in 2018 reached 15,810,305. The average number of tourist visits per month was 1,317,525 tourists. The data found that the highest number of tourists was from Asian coun­ tries while the lowest number was from countries in Africa. According to tourism law, no. 10 in 2009, the tourism industry includes various tourism busi­ nesses that produce goods and/or services to meet the needs of tourists. Companies that work in the tourism sector, such as hotels, restaurants, and others, are greatly dependent on the number of tourist visits. The higher the number of visitors to Indonesia, the more likely these companies are to progress. Developed companies are those that can forecast the future and properly choose to anticipate future circumstances. In addition to companies, non-profit organizations (Govern­ ment) need to forecast to design the state budget the following year. Future conditions are full of uncertainties, however, those uncertainties can be minimized with the right forecast method. Forecasting is a process to predict something that will occur in the future based on past data using particular techniques or methods (Siswanto, 2007). According to Suliyanto (2008), “forecasting is not necessarily correct, but it should be conducted to describe future condi­ tions. The deviation occurs between reality and the results of forecasting errors (mistakes). The good forecasting is predictions that have minor errors.” One forecasting method is a time-series method. Frequently used time series methods are daily, weekly, monthly, quarterly, bi-annually, or annually. Several often-employed forecast­ ing methods are statistical methods, Artificial Neural Network (ANN), and the fuzzy time series model. The statistical forecast method is a forecasting method based on mathematical models and statistics, such as moving averages, exponential smoothing, trends (linear and non-linear) and ARIMA (Autoregressive Integrated Moving Average). Each method has benefits and weaknesses. Several previous studies on forecasting comparisons between simple and complex methods on time-series data have been conducted by Syahriza (2005), Suhartono (2005), Song, Li (2008), and Taylor (2008). Those studies concluded that “complex models do 112

not always produce better forecast than simple statistical models.” Chen (2011) also concluded that “the combination of linear and non-linear methods can improve the accuracy of forecast­ ing results in data series of residential tourism in Taiwan.” This study attempts to examine a suitable model and forecast the number of visitors to Indonesia in the following year using a trend. This research is expected to benefit companies involved in tourism, as well as the government, in making better decisions and planning. 2 RESEARCH METHODS The data used in this study are secondary data about the number of visitors to Indonesia from January 2017 to July 2019. The data were collected from the website of the Center of Statistics at www.bps.go.id. Forecasting the number of tourists visiting Indonesia was conducted by statistical methods by using trend models, which include linear, logarithmic, inverse, quadratic, and cubic. The equation of the five trend models is illustrated in Table 1 below. Table 1. The equation of the five trend models. No.

Trend Model

Equation

1. 2. 3. 4. 5.

Linear Logarithmic Inverse Quadratic Cubic

Yt ¼ β0 þ β1 T Yt ¼ β0 þ β1 lnðT Þ Yt ¼ β0 þ β1 =T Yt ¼ β0 þ β1 T þ β2 T 2 Yt ¼ β0 þ β1 T þ β2 T 2 þ β3 T 3

Yt estimates the number of visitors using t, β_0, β_ (1), β_2, and β_3, the parameters of each trend model. A goodness-of-fit test used is if the value is less than 0.05. Fit models employed its mean square error (MSE) to determine the best model. If the value gets smaller, MSE and trends will be better for forecasting. The steps of this study are as follows: 1. Prepare the analyzed data of service time data. In this case, the data regarding the number of visitors to Indonesia from January 2017 to July 2019. The data of visitors visiting Indonesia is coded 1 for January 2019, code 2 for February 2019, etc.: the data in July 2019 is coded 31. 2. Draw/plot time-series data. 3. Analyze the time-series data using statistical methods of linear, logarithmic, inverse, quad­ ratic, and cubic trends. 4. Determine the current trend methods suitable for time-series data. 5. Forecast with the current suitable trend method.

3 RESULTS AND DISCUSSION The plot of tourist visits and visiting hours can be examined in Figure 1. The x-axis shows the visits from January 2017 to July 2019, while the y-axis depicts the number of tourist visits. From Figure 1, it could be seen that the number of tourist visits fluctuated greatly from one month to another. Generally, an increase occurred at the beginning of the period and declined in the middle of the period before recovering in the end. 3.1 Identification of the best data models for forecasting tourists from countries around the world The tourist data visit model for countries around the world was assessed using linear, logarith­ mic, inverse, quadratic, and cubic trends. Summary of forecasting parameters and the five 113

Figure 1.

Plot of the number of tourist visits and visiting time.

Table 2. Summary and trend models of parameters of linear, logarithmic, inverse, quadratic, cubic to the number of tourist visits. Model Summary

Parameter Estimation

Equation

R Square

F

df1 df2 Sig.

Constant

b1

Linear Logarithmic Inverse Quadratic Cubic Exponential

0.258 0.277 0.180 0.270 0.290 0.271

10.093 11.105 6.368 5.180 3.667 10.806

1 1 1 2 3 1

1,103,706.716 1,018,383.999 1,256,814.491 1,069,493.288 1,012,522.048 1,101,215.635

7,230.719 79,795.923 –288,014.307 13,451.343 –194.394 33,260.527 –1,717.690 31.735 .006

29 29 29 28 27 29

0.004 0.002 0.017 0.012 0.025 0.003

b2

b3

models can be seen from Table 2. Each model is smaller than α = 0.05, which means that the five models can be used to predict tourist visits from countries around the world. Determining the most suitable trend models could be examined from mean square error (MSE). The MSE values for linear, logarithmic, inverse, quadratic, cubic, and exponential trend models are shown in Table 3. Table 3. MSE value and trend models of linear, logarithmic, inverse, quadratic, and cubic values to forecast tourist visits. Group

Linear

Logarithmic

Inverse

Quadratic

Cubic

World

1.285E10

1.252E10

1.420E10

1.322E10

1.322E10

The MSE value is 1.285e10, while the logarithmic linear trend is 1.252e10, inverse trend is 1.420e10, quadratic trend is 1.322e10, and cubic trend is 1.322e10. The smallest MSE value is the logarithmic MSE value of 1.252e10. Hence, the most suitable trend to determine that the number of tourists from ASEAN countries is the logarithmic trend. The Y (estimation number of visitors for the t- month) equals 1,018,383.999 + 79,795.923 in (t is estimated) next to the number of tourists visiting Indonesia in January 2020 to December 2020. Next is the forecast for the number of tourists visiting Indonesia from Jan­ uary 2020 to December 2020. Based on the forecast using the logarithmic model, the trend is that, if conditions in Indonesia are stable, the number of tourists visiting Indonesia in 2020 is projected to increase. The estimated average number of tourist visits to Indonesia in 2020 114

is 1,317,314. The estimated average number of tourists visiting Indonesia in 2020, on aver­ age, is greater than the number of tourist visits in 2018. Increasing the number of tourists in 2020 will increase the economic growth in Indonesia, especially in the tourism industry.

4 CONCLUSION The most suitable method used to forecast the number of tourists visiting Indonesia is the loga­ rithmic method, with y (estimating the number of tourist visits in the following month t-) = 1,018,383.999 (domestic tourists) + 79,795.923 (foreigners). The trends revealed that logarithmic logs are smaller than the other four trends (linear, inverse, quadratic, and cubic). Furthermore, based on the forecast using the logarithmic trend, it was found that the number of tourists visit­ ing Indonesia in 2020 will increase. The estimated average number of tourists visiting this country in 2020 is 1,317,314. Suggestions for further research regarding forecasting are to use data from the same period like the past years and to sort data by various countries over the same periods.

115

The Future Opportunities and Challenges of Business in Digital Era 4.0 – Bangsawan et al. (eds) © 2020 Taylor & Francis Group, London, ISBN 978-0-367-42594-4

The impact of mandatory spending on economic growth in Java and Sumatra A. Ratih Yulihar Taher, Hardiansa Nur Syahputra & Arif Darmawan Universitas Lampung, Lampung, Indonesia

ABSTRACT: The purpose of this study was to obtain a compliance level of expenditure on education, health, infrastructure, village endowment, and its overall impact on the economic prosperity of Java and Sumatra. The study was conducted between 2014-2018, and all Indo­ nesian provinces were included in the purposive sampling method. Multiple linear regression was widely used in conducting the research where the results indicated adherence to manda­ tory spending on education in the province of Jakarta. Compliance in health spending was demonstrated by; West Sumatra, Bengkulu, Lampung, Central, and East Java. Also, South Sumatra, Bengkulu, and Lampung achieved the mandatory expenditure on infrastructure. However, no province implemented the village fund requirement. Keywords: mandatory spending, education, health and infrastructure expenditures, and the allocation of village funds 1 INTRODUCTION Fiscal decentralization aims to create local independence. Significant economic aspects were considered except for; foreign policy, defense, security, justice, finance, and religion. Decen­ tralization is the submission of the authority of the central government to the local adminis­ tration. Therefore, the central government only plays an advisory and guidance role in the implementation of the devolved functions (Ministry of Finance, 2015). The legislative roles include; budgetary allocation and oversight of the government by regulating state expenditure in line with the constitutional act on spending. Mandatory spending in local government according to the Directorate General of Fiscal Balance consists of; i) the education allocation to at least 20% of the budget as per the 1945 fourth amendment, (Article 31, paragraph 4 and Act No. 20 of 2003 on National Education System Article 49, paragraph 1). ii) The health budget is allocated at least 10% under Law No. 36 of 2009 article 171 section 2. iii) General Transfer allotted 25% to infrastructure. iv) Village funds got at least 10% of the budget balance about Law No. 6 of 2014 about the village. Therefore, mandatory spending aims to reduce social and economic inequality (Director General of Fiscal Balance, 2017). Furthermore, essential expenditures could be harmonized to tackle perennial issues affecting an area. These challenges could be social or economic, which creates an imbalance in the welfare of the community. The purpose of this research was to determine the provinces in Java and Sumatra, which comply with mandatory spending requirements. Also, it was seeking to know the effect of necessary expenditures on education, health, village funds, and infrastructure and its impact on economic growth.

116

2 LITERATURE REVIEW According to Fay (Fay, 2014), mandatory spending is a program where the federal govern­ ment is obliged to provide the budget for a particular function with substantive legislation. Furthermore, the Budget (2014) termed it to be the government spending where there is the rule of law, which mandates explicitly allocation of a certain proportion of state revenues to be used on certain expenditure items. While Austin (2015) defines mandatory spending as gov­ ernment expenditure controlled by the laws focusing on programs that grant the rights of soci­ ety, such as social security and health protection. The program aims at reducing social and economic inequality. Economic growth is defined as the development of activities in the economy, which leads to the growth of the country’s produce culminating in the prosperity and success of a society and nation at large. Also, it is the potential GDP expansion that defines the country’s national output. Generally, economic growth occurs when the production possibility frontier (PPF) of a nation shifts out (Samuelson, 2004).

3 METHODS This research was a descriptive quantitative illustrating an object under study. Four independent variables were used; education outlay (MS1), health functions (MS2) allocation of village funds (MS3), and infrastructure spending (MS4). The dependent variable of economic growth was used in data collection from sources ranging from the Central Statistics Agency (BPS), the Dir­ ectorate General of Fiscal Balance (DJPK), and other secondary records. The sample data used was collected from 2014 to 2018 and is comprised of the whole region under Java and Sumatra.

4 RESULTS The results show, Jakarta is compliant with education allotment, West Sumatra, Bengkulu, Lampung, Tengah Java, and East Java adhered to health spending provision, South Sumatra, Bengkulu and Lampung implemented the infrastructure share and none of the provinces com­ plied with the village ration. Based on these results, there are still very few provinces that meet with this mandatory spending. Partial regression analysis reveals that mandatory education spending function had a significant positive effect on economic growth with a coefficient of 0.102835. Additionally, health had a 0.098838 factor; allocation of village funds was ranging at 0.035257, whereas infrastructure-component had a positive score of 6.995877.

5 REPORTING RESEARCH RESULT The results obtained on the education variable are supported by the view of Keynesian Economics on the flow of expenditure. The theory states expenditure is income for others. Government expenditure directly increases revenue for the community, which stimulates economic growth and advancement. Mandatory spending on health has a positive effect on economic growth. This indicates the contribution of this variable to improving the quality of human resources. Therefore, public health becomes better, resulting in an increase in productivity; hence, the demand for labor rises. These chains of changes have a ripple effect on almost all elements of the economy, ultimately result­ ing in economic growth. Village allocation and infrastructure expenditures have a positive impact on economic growth.

117

6 DISCUSSION Following the views of Keynesian economic flow, government spending is income for the community, hence the economic growth. The more the government spends, the higher the growth margin. The flow of Keynesian Economics suggested the public sector to intervene to improve the economy. Keynes found private cannot entirely be given the power to manage the economy, since, the private sector only focuses on how to be more profitable, therefore, if left to run the economy, it would not be conducive. Consequently, the public sector needs to intervene by providing services that do not aim for profits. Education and health are some of the services offered by the government since they cannot be left in the hands of the private sector.

7 CONCLUSION Other than Jakarta, no other province complied with education spending. Also, only West Suma­ tra, Bengkulu, Lampung, Central Java, and East Java provinces implemented the health package, whereas, South Sumatra, Bengkulu and Lampung adhered to the provisions for the infrastructure allocation. However, none of the provinces complied with the village allotment requirement. Mandatory spending educational had a positive effect on economic growth. Additionally, expenditure on health and infrastructure has a similar impact on the economy as education. If implemented, the allocation of village funds would have had a significant encouraging effect on the economics of Java and Sumatra. REFERENCES Austin, S. (2015) ‘Mandatory Spending’,.

Budget, D. G. of (2014) Indonesian national budget. Jakarta.

Director General of Fiscal Balance (2017) ‘What is the Mandatory Spending ?. Ministry of Finance’.

Jakarta. Fay, R. (2014) ‘Appropriations for Mandatory Expenditures.’, in Harvard Law School Federal Budget Policy Seminar. Cambridge. Ministry of Finance (2015) Fiscal Decentralization. Jakarta. Samuelson, P. N. (2004) Macro-Economic Studies. Jakarta.

118

The Future Opportunities and Challenges of Business in Digital Era 4.0 – Bangsawan et al. (eds) © 2020 Taylor & Francis Group, London, ISBN 978-0-367-42594-4

A comparative analysis of Flow of Funds Account (FFA) presentation in Indonesia and Japan Faiz Zamzami Student of Doctoral Program in FEB, Universitas Gadjah Mada, Indonesia

Dianila Oktyawati Vocational College, Universitas Gadjah Mada, Indonesia

ABSTRACT: The aim of this study is to compare the presentation of the flow-of-funds account (FFA) report system analysis in Indonesia and Japan. This article also aims to pro­ vide input to the Indonesian government to prepare better FFA reports since it is one of the instruments to be employed in users’ decision-making in the future. This research is a descriptive study. The analysis method carried out in this study was content analysis, and the data was collected from document observation. It was found that the Japanese FFA report presentation is more complete and detailed, and that its FFA website is also more userfriendly compared to that of Indonesia. Furthermore, this article also provides suggestions for the Indonesian government to establish a standard and consistent FFA database system to be applied to its related institutions. Keywords:

Comparison, presentation, flow-of-funds account, Indonesia, Japan

1 INTRODUCTION Fund flow analysis provides a common framework to examine issues related to the financial sector and its relationships with the real economy. It is used in economy industries for basic tools information, for empirical research in general, and for detailed financial policy ana­ lysis. Based on fund flow research by Diantoro (2009), it was found that the fund flow account is one of the tools applied to support the data of monetary policy retrieval, provi­ sion of data, and information and analysis of fund flow between financial and nonfinancial variables, as a policy impacts by sector. Thus the performance of the policy process can be evaluated. Another study carried out by Indriana (2011) demonstrated that the FFA serves as a supporting means to determine the incidence of economic events, especially crises in a country. However, data available on FFA in Indonesia is limited compared to those of the USA; hence, it is difficult to analyze the crisis in Indonesia. Honohan and Atiyas (1993) stated that, in developing countries, domestic capital market conditions are indeed import­ ant, and net acquisition of each sector’s financial assets is influenced by market clearing requirements. Bezemer (2009) argued that FFA helps to foresee the financial crisis and eco­ nomic downturn. This study discusses the comparison of FFA presentation in Indonesia and Japan. Japan was chosen because it is a developed country, and it has complete preparation of the FFA report. Thus, it is interesting to discuss the differences of FFA reports in devel­ oped and developing countries based on the results of research conducted by Tsujimura and Mizoshita (2003), Kobayakawa and Okuma (2014) and Sakuramoto, Takeshi, and Hagino (2019). The aim of this research is to provide an overview of the flow-of-funds account through an analysis of the presentation by comparing the FFA reporting systems of Indonesia and Japan. 119

This research can provide input to the Indonesian government regarding this matter through the statistical Indonesian board-bank in drafting the fund flow report as one that can be used to make decisions in the future. Furthermore, this study also provides an overview of the importance of FFA as a tool that supports economic decision-making.

2 LITERATURE REVIEW Several studies have highlighted the complexity and difficulty in preparing the FFA report, such as Dimitrijevic (1969), Farman (1964), and Green and Murinde (2003). Garvy (1971) reviewed efforts to develop FFA tables in Eastern European countries – except Yugoslavia, where adequate discussion was available. Diantoro (2009) wrote research entitled “The Need for a Central Government Fund Flow Statement for Economic Decision Making,” and Indi­ ana (2011) examined an analysis of “the American and Indonesian Economic Crisis with the Funds Flow Account in 2005–2007.” Furthermore, Telli and Çavdaroğlu (2011) revealed that the FFA of the Turkish economy was generated with particular emphasis on household accounts. Recent FFA studies discussed the methods used in presenting the FFA, for example, the study by Subba Rao (2018).

3 RESEARCH METHOD This is a descriptive study. The data was collected through document observation. This study used secondary data. The data was collected from the FFA report statistics agency, while the information was obtained from various sources of publication or nonpublication from within and/or outside the Bureau of Statistics. The data used was that presented in the last period of the FFA report in 2017 and in 2018 for Indonesia and Japan, respectively. The method of analysis used in this research was content analysis (Krippendorf, 1991).

4 DISCUSSION In this discussion, the study will focus on comparisons between the presentation of the FFA report in Indonesia and in Japan. Several points to compare are as follows. 4.1 Report format Presentation of FFA reports in Indonesia is published in pdf form on the website of the Cen­ tral Statistics Agency quarterly and annually, for example, the period of 2012–2016, 2013–2017, and subsequent periods. Presentation is not devoted because difficulties occur in tracing development annually, and presentation in pdf form complicates further analysis. The presentation of numbers in FFA is not available in detail and still found as temporary and very temporary figures. On the other hand, the Japanese FFA report is released quarterly. The initial data were released in about three months, and the final and annual data in six months. The presentation on the website of general information is highly informative and userfriendly, including material about FFA policy in pdf form and detailed FFA figures in Excel time series. The presentation on the website was established to facilitate FFA ana­ lysis because the data are easily simulated and available in Excel. In addition, the pres­ entation of FFA numbers in Excel spreadsheets is unraveled in detail and can be traced even to the notes of its numbers. If such details are taken into account, the display pre­ sented by the Japanese government is more comprehensive compared to that of the Indonesian government.

120

4.2 Data sources Based on Indonesia Funds Flow Report on 2013–2017, domestic sectors in their FFA drafting used a calculation according to the balance of transactions issued and accepted by economic sectors. However, the transactions between resident and nonresident incorporated in the for­ eign sector are calculated individually. According to the aforementioned data comparison, fundamentally, FFA in both countries are similar in presenting their data sources. However, the guidelines of Japanese FFA are significantly more informative, detailed, and elaborated than those of Indonesian FFA. 4.3 Data availability Data availability is of significance to provide a real picture of the compiled FFA. According to the FFA Indonesia report year 2013–2017, several issues encountered in the drafting of Indonesian FFA related to data availability. One of the issues was in the clarification process where, at the stage of identifying balance sheet into FFA transaction code, posts in the bal­ ance sheet are poorly supported by accurate information because the FFA data procurement system was not built by consistent and relevant agencies. In Japan, the FFA guide elaborates that total series data exceeded 8,000; therefore, it often depends on estimation. It is also important to regularly revise the compilation method to reflect changes in financial structures and to maintain accuracy. FFA in both Indonesia and Japan experienced issues related to data accuracy. Thus, the Japanese FFA compiled a detailed explanation of the estimation method for each sector and transaction item. On the other hand, the Indonesian FFA did not provide a detailed method for estimation, such as its assessment. 4.4 Data renewal Data usage in numerous sectors and accounts is estimated, reducing the accuracy level of the presented data. In this regard, it is important to update and revise the data to reflect changes in financial structures and to maintain accuracy. While FFA in Indonesia did not specifically display revision of an earlier period, FFA in Japan was revised once a year. 4.5 Drafting method Preparation for each method component in FFA reports both in Indonesia and Japan has been described. However, depth in detailing the method of each account is entirely different. Based on comparative analysis of one sector and one account, the central bank found that the explanation of the method used by the Japanese government is more detailed in terms of its discussion and technical procedures compared to the guideline method proposed by the Indo­ nesian government in its fund flow account. 4.6 Comparison with other countries The comparison of FFA presentation in other countries provides an analysis regarding its position. FFA in Indonesia has not included comparisons with other countries in its presen­ tation, whereas FFA in Japan includes its comparison to FFA in the USA and in European countries. By providing FFA comparisons to other countries, Japanese FFA can position itself in regard to its financial assets and liabilities of financial institutions, financial assets of households, financial liabilities owed by nonfinancial private companies, financial surplus and deficit of key sectors, financial assets held by investment trust, financial assets held by pension funds, etc.

121

5 CONCLUSIONS, CONTRIBUTION, LIMITATION, AND SUGGESTIONS 5.1 Conclusions Based on the above discussion, it can be concluded that presentation of FFA in Japan and Indonesia has several advantages and disadvantages, as follows. First, presentation as illus­ trated by the Japanese government is more detailed since it provided traced numbers com­ pared to the Indonesian one. Based on the benchmarking of data sources, it was found that fundamentally FFA in both countries is similar. However, FFA guidelines in Japan are more informative, detailed, and explained with higher clarification than Indonesian FFA. Both FFA in Indonesia and Japan experienced issues related to data accuracy. Hence, FFA in Japan compiled a detailed explanation of the estimation method for each sector and transac­ tion item. While FFA in Indonesia did not specifically provide earlier-period revisions, FFA in Japan provided them at least once per year. Based on comparative analysis of one sector and one account, the central bank found that the explanation method used by the Japanese government is more detailed in terms of its discussion and technical procedures when com­ pared to method guidelines outlined in Indonesian fund flow. 5.2 Contribution/implication of the findings The contribution of this study is to provide a clear picture of the comparison of FFA presen­ tation in two countries in Asia. Furthermore, it hopes to provide a point of difference in Indo­ nesian and Japanese FFA presentations. Hence, it can improve the preparation of Indonesian FFA in the future. 5.3 Limitation of the study and possible future research The limitation is that this study cannot present the same period FFA data for both countries. Future research is expected to be able to compare FFA data in the same period. Besides, it will also be interesting to analyze and compare FFA between developed and developing coun­ tries, particularly in Europe and Asia. 5.4 Suggestions Based on the conclusion, this finding is important to providing insights to the Indonesian gov­ ernment. Several suggestions are proposed for drafting future Indonesian fund flow balance: First, the FFA manual should be compiled to be more informative, detailed, and in order by rearranging its techniques. Also, the FFA website’s presentation should be more user-friendly to provide specific display or themes regarding FFA; in addition, it is better to provide FFA not only in pdf format but also in Excel spreadsheet by providing quarter, semester, and annual FFA reports as well as revised reports, if any. Then, regarding its presentation, FFA should provide its comparisons to that of other countries, for example, Japan, the USA, and others. REFERENCES Bezemer, D. J. (2009). No one saw this coming. Understanding financial crisis through accounting models, No 09002. Research Report. University of Groningen. Research Institute SOM. Berg, B. L. (2001). Qualitative Research Methods for the Social Sciences. Boston: Allyn and Bacon. Badan Pusat Statistik. 2018. Neraca Arus Dana Indonesia 2013–2017, Indonesia. Downe-Wambolt, B. (1992). “Content analysis: Method, applications and issues.” Health Care for Women International,13, 313–321. Diantoro. (2009). Kebutuhan Laporan Neraca Arus Dana Pemerintah Pusat Untuk Pengambilan Kepu­ tusan. Thesis. Yogyakarta: MAKSI UGM. Farman, W. L. (1964). “National flow-of-funds: An acounting analysis.” Accounting Review, 39(2), 392.

122

Garvy, G. (1971). “Flow-of-funds accounts in Eastern Europe.” Review of Income & Wealth, 17(3), 237–251. Green, C. J., & Murinde, V. (2003). “Flow of funds: Implications for research on financial sector devel­ opment and the real economy.” Journal of International Development, 15(8), 1015–1036. Honohan, P., & Atiyas, I. (1993). “Intersectoral financial flows in developing countries.” Economic Jour­ nal, 103(418), 666–679. Indriana. (2011). Analisis Krisis Ekonomi Amerika dan Indonesia dengan Pendekatan Neraca Arus Dana tahun 2005–2007. Thesis. Yogyakarta: MAKSI UGM. Krippendorff, K. (1991). Content Analysis: An Introduction to Its Methodology. London: SAGE Publications. Kobayakawa S., Okuma R. (2014). Japan’s Flow-of-Funds Accounts: Main Characteristics and Measures for Enhancement. Palgrave Studies in Economics and Banking. London: Palgrave Macmillan. McKinsey. (2009). Global Capital Markets Entering a New Era. McKinsey Global Institute. Research and Statistics Department Bank of Japan. (2018). Compilation Method of Japan’s Flow of Funds Accounts, Japan. Singh, T. (2019). “On the flow of funds accounts and inter-sectoral mobility of capital in India.” Applied Economics, 51 (46), 4993–5011. Subba Rao, K. G. K. (2018). “Discrepancies between flow of funds accounts and national accounts statistics.” Economic and Political Weekly, 53(15), 56–63. Sakuramoto, T., & Hagino, S. (2019). Implementation of 2008 SNA in Japan’s Flow of Funds Accounts. Telli, M. C., & Çavdaroğlu, H. S. (2011). Flow of Funds Analysis: Framework, Compilation and Appli­ cations for Turkey. Directorate for Annual Programs and Conjuctural Evaluations. Tsujimura, K., & Tsujimura, M. (2018). “A flow of funds analysis of the US quantitative easing.” Eco­ nomic Systems Research, 30(2), 137–177. Tsujimura, K., Mizoshita, M. (2003). “Asset-liability-matrix analysis derived from the flow-of-funds accounts.” Economic Systems Research, 15(1), 51–67.

123

The Future Opportunities and Challenges of Business in Digital Era 4.0 – Bangsawan et al. (eds) © 2020 Taylor & Francis Group, London, ISBN 978-0-367-42594-4

The effect of ethnocentrism and preference of purchase intention Desmy Erina Laofa Universitas Lampung, Lampung, Indonesia

ABSTRACT: Beef prices tend to increase due to inadequate domestic production, so that people find it difficult to get protein from beef. The solution to overcome low beef production and reduce domestic meat prices is to import beef. However, the majority of people choose to continue to consume local beef for daily protein sources. This study will examine consumer purchase intentions to find consumer preferences and the influence of ethnocentrism by using conjoint analysis and ANOVA tests. The factor of preference and ethnocentrism will reveal the consumer’s intention to buy beef.

1 INTRODUCTION Beef is one of the preferred sources of nutrition in protein needs. Beef’s contribution to national meat needs is 23 percent and is expected to continue to increase (Pusdatin, 2016). The increasing national demand for beef encourages excess demand, where the demand for beef is greater than the supply. This is due to domestic production that cannot meet people’s demands. Excess demand causes the price of fresh beef sold in the market to increase (Ministry of Agriculture, 2018). The solution to overcome low beef production and reduce domestic meat prices is to import beef. The price of imported beef, which is cheaper than local beef, makes imported beef attractive for consumption. Although the price offered for imported beef is lower, the majority of people choose to continue to consume local beef for daily protein sources. Research on the preferences and effects of consumer ethnocentrism on beef purchases needs to be done to further understand the consumption behavior of these people.

2 LITERATURE REVIEW Kotler (2005) states that consumer preferences are the degree of liking or disliking someone towards a type of product. Preference for food products is a description of one’s attitude towards food, and someone can make a choice from products that have at least two different types of food. According to Kotler (2005), there are three components of preferences that affect food consumers where all these components influence one another and are related to each other, namely: 1. Individual characteristics include age, gender, education, income, and nutritional knowledge. 2. Product characteristics include taste, color, aroma, packaging, and texture. 3. Environmental characteristics include the number of families, social level, season, and mobility. H1: Consumer preferences have a positive effect on consumer purchase intentions Shimp and Sharma (1984) in Wei (2008) found that consumers who have high ethnocen­ trism, tend to prefer domestic products to imported products, whereas consumers who have low ethnocentrism tend to choose imported products. Li et al. (2012) also suggested that 124

consumer ethnocentrism will influence purchasing decisions for local and foreign products. Based on the discussion, the following hypotheses can be proposed: H2: Indonesian consumer ethnocentrism has a significant effect on the purchase intention of local beef. Akram et al. (2011) found that consumers who have high ethnocentrism tend to be less in buying foreign products. In developing countries, consumers assume that foreign brand products have better quality than local brand products. This will certainly reduce consumer purchase intentions for local products (Batra et al., 2000; Bhardwaj et al., 2010 in Akram et al., 2011). Research conducted by Li et al. (2012) also suggests that con­ sumer ethnocentrism will influence the purchase decisions of local and foreign products from consumer preferences indirectly. Based on the discussion, the following hypotheses can be proposed: H3: Consumer preferences mediate the relationship between consumer ethnocentrism and con­ sumer purchase intentions for local beef (Indonesia). Based on the hypothesis above, this study proposes the conceptual framework that can be seen in the figure below.

3 RESEARCH METHODOLOGY The type of data used in this study consisted of primary data and secondary data. Primary data obtained through indirect interviews using tools in the form of a questionnaire containing individual characteristics (age, type of work, level of education, and expenditure), ethnocen­ trism variables, preferences, and purchase intentions in beef purchasing decisions. Secondary data were obtained from various relevant sources, such as the Central Statistics Agency and literature studies.

4 DISCUSSION Preference analysis is conducted to determine the tastes of beef consumers who are targeted by imported beef traders and local beef. This study aims to identify the desires or preferences of prospective beef consumers so that beef traders can provide quality beef in accordance with consumer desires. The ability of traders to meet the desires of consumers will increase sales of beef products. The analysis used to determine the preferences of beef consumers is using conjoint analysis. This analysis will help traders or producers in providing and selling beef in accordance with the wishes and preferences of consumers. This analysis is done by first making a combination of attributes to be tested. This study examines the combination of meat price attributes, meat color, meat texture, and fat content. Consumers will also

125

choose beef by considering the attributes contained in beef. Each attribute will have a different importance value. The results of previous studies conducted by Shimp and Sharma (1984); Li et al., (2012); Qing et al., (2012; Wei, (2008); Aziz et al., (2014); Nguyen et al., (2008); Tabassi et al., (2012); Chang & Cheng, (2011); Huang et al., (2008); Fakharmanesh & Miyandehi, (2013); Erdogan & Uzkurt, (2010); and Akram et al., (2011), which shows that consumer ethnocentrism has a significant effect on the purchase intention of domestic products. If consumer ethnocentrism directly influences purchase intention and indirectly also influ­ ences purchase intention through consumer preferences as a mediating variable, then based on Zhao et al., (2010) this research can be said to be complementary mediation, it can be seen if the β results (a) x β (b) x β (c) the result is positive. Based on this, several conclusions can be drawn, namely: consumer preferences have a significant effect on consumer purchase intentions, then consumer ethnocentrism directly has a positive and significant effect on consumer purchase intentions for local products, and consumer preferences can be complementary mediation in mediating the relationship between ethnocentrism consumers and purchase intentions. REFERENCES Akram, Aneela., Merunka, Dwight., Akram, Muhammad S., (2011), “Perceived brand globalness in emerging markets and the moderating role of consumer ethnocentrism,” International Journal of Emerging Markets, Vol. 6 Iss 4 pp. 291–303. Aziz, Saira,. Bahadur, Waseem., Farooq, Rukhshanda., Arshad, Munaza., (2014), “Investigating the Role of Demographic Characteristics on Consumer Ethnocentrism and Buying Behavior,” Inter­ national Review of Management and Business Research, Vol. 3 Issue.2 Chang, Yu-Hern.,and Cheng, Chien-Hang., (2011), “Exploring the effects of consumer ethnocentrism on preference of choosing foreign airlines: A perspective of Chinese tourists,” African Journal of Business Management, Vol. 5(34), pp. 12966–12971, 28 December 2011. Dano, A. H. 2004. Analisis keputusan lokasi pembelian dan preferensi terhadap atribut daging sapi segar (Kasus di pasar swalayan hero Padjajaran dan pasar Tradisional Citeureup di Bogor) (Doctoral dissertation, IPB (Bogor Agricultural University)). Ditjen PKH. 2018. Statistik Peternakan dan Kesehatan Hewan. Jakarta: Direktorat Jendral Peternakan dan Kesehatan Hewan. Erdogan, B. Zafer., Uzkurt, Cevahir., (2010), “Effects of ethnocentric tendency on consumers perception of product attitudes for foreign and domestic products,” An International Journal, Vol. 17 Iss 4 pp. 393–406. Huang, Yu-An., Phau, Ian dan Lin, Chad., Chung, Hsien-Jui., Lin, Koong Hao-Chiang., (2008), “Allo­ centrism and Consumer Ethnocentrism: The effects of Social Identity on Purchase Intention,” Social Behavior and Personality, Vol. 36(8), 1097–1110. Hellier, P. K., G. M. Geursen, R. A. Carr & J. A. Rickard. 2003. “CustomerRepurchase Intention: A general structural equation model”. EuropeanJournal of Marketing, Vol. 37, No. 11/12, pp.1762–1800. Kotler P. 2005. Manajemen Pemasaran Edisi Milenium Jilid 1 & 2. Jakarta (ID): PT. Prenhanllindo. Li, Xianguo., Yang, Jing., Wang, Xia dan Lei, Da., (2012), “The Impact of Country-of-Origin Image, Consumer Ethnocentrism and Animosity on Purchase Intention,” Journal of Software, Vol. 7, No. 10, October 2012. Mangkunegara,A.A.A.Prabu. 2009. Perilaku konnsumen. Refika Aditama:Bandung. Nguyen, Tho D., Nguyen, Trang T.M., Barrett, Nigel J., (2008), “Consumer ethnocentrism, cultural sen­ sitivity, and intention to purchase local products-evidence from Vietnam,” Joumal of Consumer Behaviour, Jan.-Feb. 2008, Vol. 7: 88-100 (2008). [PUSDATIN] Pusat Data dan Sistem Informasi Pertanian. 2016. Outlook Daging Sapi; Komoditas Per­ tanian Subsektor Peternakan [internet]. [diunduh pada 2018 Januari 1]. Qing, Ping., Lobo, Antonio., Chongguang, Li., (2012), “The impact of lifestyle and ethnocentrism on consumers’ purchase intentions of fresh fruit in China, “Journal of Consumer Marketing, Vol. 29 Iss 1 pp. 43–51. Shiffman, L.G.,Kanuk, L.L., (2008), Perilaku Konsumen (Judul asli: Consumers Behavior).Edisi Ketu­ juh. PT Indeks, Jakarta. Shimp TA, Sharma S. 1987. Consumer Ethnocentrism: Construction and Validation of the CETSCALE. Journal of Marketing Research [Internet]. America (USA): American Marketing Association. 24(3): 280–289.

126

Tabassi, Sadra., Esmaeilzadeh, Pouyan., dan Sambasivan, Murali., (2012), “The role of animosity, religi­ osity and ethnocentrism on consumer purchase intention: A study in Malaysia toward European brands,” African Journal of Business Management, Vol.6 (23), pp. 6890–6902, 13 June, 2012. Teas, R. Kenneth., Agarwal, Sanjeev., (2000), “The Effects of Extrinsic Product Cues on Consumers Per­ ceptions of Quaiity, Sacrifice, and Value,” Joumal of the Academj’ of Marketing Science, Vol. 28, No. 2, p. 278–290. Wei, Yujie, (2008), “Does Consumer Ethnocentrism Affect Purchase Intentions Of Chinese Consumers? Mediating Effect Of Brand Sensitivity And Moderating Effect Of Product Cues” Journal of Asia Busi­ ness Studies, Vol. 3 Iss 1 pp. 54–66. Wijayanti, M. R. 2011. Analisis Preferensi Konsumen Dalam Membeli Daging Sapi di Pasar Tradisional Kabupaten Karanganyar (Doctoral dissertation, Universitas Sebelas Maret). Zhao, Xinshu., Jr. Lynch, John G.,dan Chen, Qimei., (2010), “Reconsidering Baron and Kenny: Myths and Thruths about Mediation Analysis,” Journal of Consumer Reasearch, Inc., Vol.37, August 2010: 197–206.

127

The Future Opportunities and Challenges of Business in Digital Era 4.0 – Bangsawan et al. (eds) © 2020 Taylor & Francis Group, London, ISBN 978-0-367-42594-4

Influence of quality service and satisfaction imagery higher education on Word of Mouth (WOM) Gusti Adi Pranoto, Satria Bangsawan & Dorothy H. Rouly Pandjaitan Universitas Lampung, Lampung, Indonesia

ABSTRACT: STIE Muhammadiyah Pringsewu has some performance issues, and these can be associated with the additional dissatisfaction observed in the facilities provided. The pur­ pose of this study, therefore, was to determine the effect of service quality and image on cus­ tomer satisfaction and word of mouth for the students of the college. This involved the use of questionnaires that were self-administered to 135 students of the college at the beginning of the 2, 4, 6, and 8 semesters. The result of the hypothesis tested showed that the quality of ser­ vice and the image of the college was low. This led to the students’ dissatisfaction over the service and image of STIE Muhammadiyah Pringsewu and unfavorable negative WOM.

1 INTRODUCTION STIE Muhammadiyah Pringsewu has some performance issues, and these can be associated with the additional dissatisfaction observed in the facilities provided as well as the bad percep­ tion of the students about the school. It is, however, important to note that these have nega­ tive effects on the institution, especially through the spread of negative word of Mouth, which may lead to the reduction in patronage (Zeithaml et al., 1996). Some Empirical studies reported that quality of service is the antecedent of satisfaction (Naik et al. 2010; Spreng and Mackoy, 1996). Moreover, Naik et. Al. (2010) revealed that the intention of behavior is influ­ enced by SERVQUAL mediated by customer satisfaction. In other words, when organizations conduct extraordinary SERVQUAL, customers tend to create good behavior in the future because they are satisfied. Therefore, improving the image of STIE Muhammadiyah Pring­ sewu through quality education can directly increase the satisfaction of educational services users. According to Reynolds and Beatty (1999), customer satisfaction translates into positive WOM about the seller and the company. Therefore, this study was conducted to determine the effect of quality of service, the image of the college, and satisfaction of the consumers on WOM intentions. It also attempted to explain whether the students of STIE Muhammadiyah Pringsewu use positive WOM about the college.

2 LITERATURE REVIEW 2.1 Quality of service According to Zeithaml et al. (2001: 92), quality of service is a level of excellence to meet cus­ tomers’ expectations by comparing the ideal and perception of quality performance. 2.2 Citra college Brand image is a set of ideas, beliefs, and impressions of a person about a product, company/ shop, or services (Kotler, 2002: 215). 128

2.3 Satisfaction Kotler (2004: 10) defined customer satisfaction as the degree of customers’ expectations about the notion of performance (perceived performance) of a product is met. 2.4 Word of Mouth (WOM) Word of Mouth is a marketing effort that triggers consumers to continually discuss, pro­ mote, recommend, and sell a product or brand to other consumers (Kotler and Keller, 2007: 204).

3 METHODS 3.1 Sampling A stratified random sampling technique was used with a total population of 587 students. The representative number of samples depended on the number of indicator questions multiplied by 5 to 10 to produce a total sample of 135 students. (27 questions x 5 = 135) 3.2 Data collection A Self-administered survey method was used in this study such that the respondents were allowed to fill the questionnaire on their own. 3.3 Measurement The research instruments used were questionnaires, and the responses were measured using a Likert scale.

4 RESULTS AND DISCUSSION In this study, normality assumption and heteroskedasticity tests were conducted, and the results are presented as shown in the following table.

Table 1.

Normality test results using kolmogorov-smirnov. Residual unstandardized

N Normal Parameters a, b Most Extreme Differences

mean Std. deviation Absolute positive negative

Test Statistic Asymp. Sig. (2-tailed)

135 0.0000000 1.55827769 0,067 0,039 -0.067 0,067 0,200c, d

Source: SPSS output in 2019

Table 1 shows the significance (2-tailed) was 0.200 > 0.05, and this means the data residuals were normally distributed

129

Table 2.

Direct impact test results.

Influence

T-Count

T table

X1 ==> Y1 X2 ==> Y1 X1 ==> Y2 X2 ==> Y2 Y1 ==> Y2

1,705 4,247 1,898 2742 5562

1.656 1.656 1.656 1.656 1.656

Source: SPSS output in 2019

The direct effect was examined using a t-test method such that, if t-count > t-table, then Ho is rejected and Ha accepted at a significance of P-Value < 0.05. This means the independent variables affect the dependent variable and based on data presented in Table 2; there is a partial effect of each variable, and the decision made is as follows: 1. Quality of Service (X1) Satisfaction (Y1) The values obtained for T-count and T-table were 1.705 and 1.656, respectively, and this means T-count > T-table. Therefore, it can be concluded that (X1) affected (Y1), and Ha was accepted while H0 was rejected. This was associated with the provision of inferior services such as dirty classrooms, improperly arranged parking areas, and unfriendly service employ­ ees by STIE Muhammadiyah Pringsewu to the students, which lead to discontentment and dissatisfaction. This is in line with the opinion of Kotler (2007: 57) that customers are satisfied with good service or if it is conducted as expected. 2. Image College (X2) Satisfaction (Y1) A T-count value of 4247 was recorded while the T-table was 1.656, and this means T-count > T-table. Therefore, it can be concluded that (X2) affected (Y1), which means Ha was accepted and H0 rejected. This shows the image of STIE Muhammadiyah Pringsewu has a significant effect on satisfaction. This is associated with the students’ negative perception of the college due to the shortage of highly educated lecturers such as doctors and professors, leading to a lack of optimal quality of education. This is in accordance with the opinion of Dharmmesta (1999) that it is possible to form an image/image of a company based on the level of satisfaction. 3. Quality of Service (X1) On Word of Mouth (Y2) A T-count value of 1.898 was recorded while the T-table was 1.656, and this means T-count > T-table. Therefore, it can be concluded that (X1) affected (Y2), which means Ha was accepted and H0 rejected. This was associated with the provision of inferior services such as dirty class­ rooms, improperly arranged parking areas, and unfriendly service employees by STIE Muham­ madiyah Pringsewu to the students, which lead to discontentment and dissatisfaction and sharing of the situation with more than 9 friends through negative WOM. This is in agreement with the research conducted by Walker (2001: 67), which shows satisfied customers usually tell 4 or 5 people about their experiences while dissatisfied ones tell nine to 10 people. 4. Image College (X2) On Word of Mouth (Y2) A T-count value of 2.742 was recorded while the T-table was 1.656, and this means T-count > T-table. Therefore, it can be concluded that (X2) affected (Y2), which means Ha was accepted and H0 rejected. This shows the image of STIE Muhammadiyah Pringsewu has a significant effect on satisfaction associated with the students’ negative perception of the college due to the shortage of doctors and professors of science, which leads to discontentment and 130

dissatisfaction and sharing of the situation with more than 9 friends (WOM Negative). This is consistent with the findings of Fredi, Akhmad, Muhammad (2017) that brand image has effects on potential visitors through the recommendation of buyers’ Word of Mouth. 5. Satisfaction (Y1) On Word Of Mouth (Y2) A T-count value of 5.165 was recorded while the T-table was 1.656, as shown in Table 4:12, and this means T-count > T-table. Therefore, it can be concluded that Satisfaction (Y1) affected Word of Mouth (Y2), which means Ha was accepted and H0 rejected. This also shows the students’ perception of the quality of service and image of the college was not up to expectation, and the students shared the information about the services of the college to more than 9 friends through negative WOM.

Table 3.

The indirect effect test results.

Influence

T-Count

P-Value

T table

X1 ==> == Y1> Y2 X1 ==> == Y1> Y2

1.892 2,172

0,011 0,029

1.656 1.656

Source: SPSS output in 2019

The examination of indirect effect was conducted using the Sobel test such that a T-count > T-table means the variable has a mediating influence at a significance of P-Value T-table. It shows there is no direct influence of (X1) on (Y2) through (Y1). This also means the increase factor (X1) affects (Y2) with an intermediary (Y1), which indicates Ha was accepted and H0 rejected. This was associated with the provision of inferior services such as dirty classrooms, improperly arranged parking areas, and unfriendly service employees by STIE Muhammadiyah Pringsewu to the students, which lead to discontentment and dissatis­ faction and sharing of the situation with more than 9 friends through negative WOM. This is in line with the opinion of Kotler (2007: 57) that customers are satisfied with good service or if it is conducted as expected. 7. Image College (X2) to Word Of Mouth (Y2) through Student Satisfaction (Y1) A T-count value of 2.172 was recorded while the T-table was 1.656, and this means T-count > T-table. It shows there is an influence of (X2) on (Y2) through (Y1). This also means the increase factor (X2) affects (Y2) with an intermediary (Y1), which indicates Ha was accepted and H0 rejected. This shows the image of STIE Muhammadiyah Pringsewu has a significant effect on satisfaction. This is associated with the students’ negative perception of the college due to the shortage of highly educated lecturers such as doctors and professors, leading to the lack of optimal quality of education. This decreased the level of satisfaction of students study­ ing in these universities, and these situations were shared with more than 9 friends through negative WOM.

131

5 CONCLUSIONS The findings of this research showed the quality of service and the image of STIE Muhamma­ diyah Pringsewu college is low to the dissatisfaction of the students which further led to nega­ tive WOM to more than 9 friends. REFERENCES Dharmmesta, BS (1999), “Customer Loyalty: A Conceptual Study For Free For researchers,” Journal of Economic and Business Indonesia, Vol. 14, No. 3 things. 73–88. Fredi, Akhmad, Muhammad, Influence of Brand Image Of Word Of Mouth and Its Impact On Purchase Decision. Journal of Business Administration (JAB) Vol. 43 1 February 2017. Kotler, Marketing 2002.Management, Vol.1, Issue 12, Jakarta: Faculty of Economics, University of Indonesia. Kotler, Philip, and Kevin Lane Keller. 2007. Marketing Management. Twelfth Edition Volume 1. Jakarta: Index. Kotler, Philips. Marketing Management 2004. Volume 2. Translation Drs. BenyaminMolan.PT Grame­ dia Group Index. CNK ride, Gantasala SB, Prabhakar GV. SERVQUAL, Customer Satisfaction and Behavioral Inten­ tions in Retailing European Journal of Social Sciences - Volume 17: 2010, Number 2. Reynolds KE, SE Beatty. Customer Benefits and Company Consequences of Salesperson Customer Rela­ tionships in Retailing. J Retailing: 1999.75: 11–32. Walker, Harrison, L. Jean, 2001. “The Measurement Of Word Of Mouth Communication And An Inves­ tigation Of Service Quality And Customer Commitment As Potential antecedents,” Journal of Service Research, Volume 4, No. 1, P. 60–75. Zeithaml et.all, 2001. Integrating Customer Service Marketing Firm across the 2nd ed. Boston: Mc Graw Hill.

132

The Future Opportunities and Challenges of Business in Digital Era 4.0 – Bangsawan et al. (eds) © 2020 Taylor & Francis Group, London, ISBN 978-0-367-42594-4

Electronic Data Capture (EDC) marketing strategy in an Indonesian state-owned bank Eva Weliyanti, Mahrinasari MS & Ernie Herdrawaty Universitas Lampung, Lampung, Indonesia

ABSTRACT: Bank Rakyat Indonesia is one of the Indonesian state-owned banks. Its oper­ ations are supported by the use of EDC (Electronic Data Capture) machines, which are con­ sidered ineffective by its customers. The banking marketing strategy was carried out by employing qualitative methods. After observing and collecting data, measurements were con­ ducted to determine appropriate ideas and strategies for banking marketing by applying SWOT analysis. The purpose of this study was to determine the marketing strategy of EDC Merchant at Bank Rakyat Indonesia, which is compiled based on SWOT. This research was conducted using a descriptive qualitative approach and analyzed by SWOT. The data were obtained from questionnaires filled by EDC users of Bank Rakyat Indonesia. It was found that marketing strategies related to the use of the EDC machine at Bank Rakyat Indonesia should follow alternative diversification strategies. This study indicates that managers at this bank are advised to implement several programs, such as the BRIZZI card sales program in offices or agencies, i.e., BRIZZI Goes to Office, 10% merchant discount promos, and EDC swipes prize lottery. Keywords: bank

Electronic Data Capture (EDC), marketing strategy, Indonesian state-owned

1 INTRODUCTION The marketing strategy implementation by Bank Rakyat Indonesia has a great role as a support for the increased profits and corporate competition. Bank Rakyat Indonesia, in 2018 has not been able to meet the annual target set in 2018. The realization of total sales volume during 2018 was 14.50%, which was lower than its target. Furthermore, the number of EDC Merchants in 2018 was only 39.50%. It occurred because shop owners or merchants were frequently reluctant to educate buyers to make transactions with EDC machines. This behavior occurs because of the existence of an MDR (Merchant Discount Rate) or automatic­ ally charged fee incurred to consumers per transaction. For example, if the transaction is pro­ cessed by using cards from other banks, the administrative cost is 1.8%, while by using one from Bank Rakyat Indonesia, it will incur 0.15%. Interestingly, if consumers use a BRIZZI card, no fees will be charged. Previous research conducted by Ungureanu et al. (2012) found that analysis of banking marketing strategies can be carried out using qualitative methods, in which after observ­ ing and collecting data, measurements are taken to determine appropriate ideas and strat­ egies for marketing through SWOT analysis. Ghazinoory, Abdi, and Azadegan-Mehr (2011), also stated that the SWOT method could be used as a reference to search for strategies in handling banking issues. The phenomenon experienced by Bank Rakyat Indonesia illustrates that the use of EDC Merchant machines by consumers has not been effective, whereas starting 2018, EDC merchant sales volume has become an important indicator of BRI’s marketing performance. Based on these issues, Bank Rakyat Indonesia needs to innovate its marketing strategies by using SWOT as an analysis tool. Thus, the 133

authors are interested in examining these issues by conducting the research entitled “Elec­ tronic Data Capture (EDC) Merchant Marketing Strategy Analysis at Bank Rakyat Indonesia” This study aims to analyze marketing strategies by using EDC in 2018 to attain higher BRI’s marketing performance and to provide theoretical contribution for the improvement of BRI’s EDC marketing strategies.

2 LITERATURE REVIEW 2.1 Strategic marketing planning Strategic planning leading to customers’ satisfaction becomes a focus in marketing manage­ ment. Therefore, the use of marketing concepts is the rationale to achieve the goals. Strategic planning, according to Bryson (2011), is a disciplined effort to make important decisions and actions that shape and guide how to become an organization and why organizations do things the way they do. Furthermore, strategic planning requires broad information gathering and emphasizes future information with current decisions. Strategic planning can facilitate com­ munication and participation of different interests and values, and assist in decision making and successful decision implementation. 2.2 Marketing strategy The purpose of the market-oriented company is to satisfy its customers and consumers, which in turn benefits the company. To obtain it, companies need precise marketing strategies that can be used to take advantage of market opportunities and to enhance them. The company uses various strategies to market its products. It is because the current conditions are strict. For instance, if a company does not use the right strategy, then it will lose in market share competition. Marketing strategy is a marketing logic where the company hopes to create cus­ tomers’ value and achieve profitable relationships (Kotler and Armstrong, 2016). Meanwhile, according to Kurtz and Boone (2008), marketing strategy is the company’s overall program to determine the target market and satisfy consumers by building a combination of elements of the marketing, such as product, distribution, promotion, and price. 2.3 Competitive marketing strategy Combination of the goals maintained by a company with tools by which it wants to achieve them (Porter, 2001). The main formulation of a competitive strategy is to connect the com­ pany with its environment, even if the relevant environment is broad, encompassing social and economic forces. The main aspect of the company’s environment is that the company’s indus­ try can compete. The purpose of a competitive strategy for a business unit in an industry is when one of them finds a position in the industry where the company can well protect itself against the pressure (power) of competition or can affect the pressure positively. Rivalry among competitors is in the form of a race to get a position by using tactics, such as price competition, advertising war, giveaway, introducing products, and increasing service or guar­ antees to customers. Competition occurs because one or more competitors sense the pressure or see an opportunity to improve their competitive position.

3 METHODS 3.1 Sampling This study used a purposive sampling method, which was samples’ selection from the popula­ tion with a specific purpose. Thus, the selected sample can represent the entire population, and it should have certain criteria (Hair et al., 2010). Based on the predetermined criteria, the 134

total sample of this study was 32 EDC users in the marketing area of Bank Rakyat Indonesia in the 2018 period. 3.2 Data collection The data used in this study is the primary data. They were collected by closed question type questionnaires to obtain a focused response from the samples. In addition, the data used in this research were obtained through an in-depth interview with the samples. 3.3 Measurement This study used four stages of analysis measurement, namely SWOT identification of Bank Rakyat Indonesia EDC marketing, external and internal factor evaluation, SWOT matrix, and alternative strategies ranking.

4 RESULTS AND DISCUSSION Based on the results of internal factor analysis, it was revealed the total score of 3,707, while the results of external factor processing reached 2,813. Furthermore, the total score of the IFE (Internal Factor Evaluation) and EFE (External Factor Evaluation) matrix depicted the value above 2.5, meaning that the strengths and opportunities of the potential marketing at the PT. Bank Rakyat Indonesia EDC machine could overcome the existing weaknesses and threats. From the results of the IFE and EFE matrix analysis, the quadrant position of the Bank Rakyat Indonesia EDC machine marketing strategy was demonstrated in the SWOT analysis diagram (Figure 1). The quadrant position was obtained by calculating the margin in the total score of opportunities and threats (vertical axis), and the margin in total scores of strengths and weaknesses (horizontal axis). The results of the total score margin calculation were obtained by the ordinate of 1.8728; -0.8490, located in quadrant 2. Quadrant position 2 illustrates that the strengths and threats can be utilized for the develop­ ment of Bank Rakyat Indonesia EDC machine marketing by supporting development policies

Figure 1.

SWOT diagram.

135

with diversification strategies. From the SWOT matrix, the researchers recommend proposal alternatives, as follows: • Improvement in the ease use of EDC BRI, which can be used for all cards and communi­ cated by all sales teams to merchants. • Promo in cash to merchants. • Swipe Lottery with EDC Merchant Prizes. • BRI EDC socialization to the community, especially small and medium business owners. • BRIZZI card sales program in offices/agencies, i.e., Brizzi Goes to Office). • 10% merchant discount promo. • EDC Merchant Racing Sales Volume Program. • Improvement in the number of regular visits from 3 months. • Improvements in networking and communicating with merchants. Based on a ranking analysis and discussion with the BRI`s high-level management, three diversification strategies were chosen and prioritized for its aim at optimizing the marketing strategies of the EDC machine at Bank Rakyat Indonesia. The three strategies proposed to develop the marketing of EDC machines in this bank are: • BRIZZI card sales program in offices or agencies (BRIZZI Goes to Office). • 10% merchant discount promotion of 10%. • Swipe lottery for EDC merchant prizes.

5 CONCLUSION The SWOT analysis in this study found that alternative marketing strategies of the EDC machine at Bank Rakyat Indonesia lie in quadrant 2. This particular quadrant in the SWOT matrix suggests that the marketing strategy of the EDC machine at the Bank Rakyat Indo­ nesia should follow alternative diversification strategies. The results of this study managed to provide answers to the aim of this study. Furthermore, the results offer three prioritized alter­ native strategies which can be used as suggestions in developing marketing strategies of the use of EDC machines at Bank Rakyat Indonesia, such as: • BRIZZI card sales program in offices or agencies at the Bank Rakyat Indonesia sales area (BRIZZI Goes to Office). • 10% merchant discount promotion • Swipe lottery for EDC merchant prizes.

REFERENCES Bryson, J. M. (2011) Strategic Planning for Public and Nonprofit Organizations: A Guide to Strengthen­ ing and Sustaining Organizational Achievement. 4th ed. San Francisco, CA: Jossey-Bass. San Fran­ cisco, CA: Jossey-Bass. Ghazinoory, S., Abdi, M. and Azadegan-Mehr, M. (2011) ‘SWOT METHODOLOGY: A STATE-OF­ THE-ART REVIEW FOR THE PAST, A FRAMEWORK FOR THE FUTURE/SSGG METODO­ LOGIJA: PRAEITIES IR ATEITIES ANALIZĖ’, Journal of Business Economics and Management. Vilnius Gediminas Technical University, 12(1), pp. 24–48. doi: 10.3846/16111699.2011.555358. Hair, J. F. et al. (2010) Multivariate Data Analysis. Sixth Edition. UK: Prentice-Hall International.

Kotler, P. and Armstrong, G. (2016) Principles of Marketing. England: Pearson Education Limited.

Kurtz, D. L. and Boone, L. E. (2008) Contemporary Business. US.

Porter, M. E. (2001) ‘Strategy and the Internet’, Harvard Business Review.

UNGUREANU, M. A. et al. (2012) ‘SWOT Analysis Solutions for Developing the Banking Business

Based on Relationships between the Banks Indicators’, Recent Researches in Tourism and Economic Development, pp. 251–256.

136

The Future Opportunities and Challenges of Business in Digital Era 4.0 – Bangsawan et al. (eds) © 2020 Taylor & Francis Group, London, ISBN 978-0-367-42594-4

The influence of level of service on commitment to implement Islamic tourism with religiosity as a mediating variable Kuncoro Budi Riyanto, Satria Bangsawan, Mahrinasari MS & Ribhan Universitas Lampung, Indonesia

ABSTRACT: This study aims to design a model of tourist imagery for an Islamic tourist destination. One of the particular goals of this study is to investigate the impact of strictness elements and dimensions of Islamic service quality on the tourism image of Islamic purposes and Islamic customer loyalty. Besides, this study examines the intervening impacts of adminis­ tration levels because of Islamic tourism pictures on Islamic customer loyalty. The motive of this research can be revealed by applying the study plan by conducting the PLS test and ana­ lyzing 300 examples of Islamic tourists who had the experience to go to Islamic tourism destinations.

1 INTRODUCTION This study aims to analyze the impact of strictness on the promise to implement Islamic tour­ ism with a certain degree of administration as an interceding variable and the tourism indus­ try, for the most part, treats strict buyers “as a strict homogeneous traveler and advertiser” (Triantafillidou et al., 2010, pp. 382-383). This way, the administrative gap that should be filled, including analyzing such connections, is significant for advertisers and supervisors of strict purposes.

2 THEORETICAL REVIEW The accomplishment of promoting procedures (Flavian, Martinez, and Polo, 2001, cited in Yoon and Uysal, 2005). In promotion, faithfulness estimates the loyalty of customers towards brands (Backman and Crompton, 1991). It depends on buyers’ brand inclination or their expectation to pur­ chase a brand. Consumer loyalty, client experience, honor, administration, execution, cost, and brand can add to their faithfulness (Backman and Crompton, 1991; Oliver, 1999). Fur­ thermore, for the tourism industry, objective steadfastness (DL) refers to the expectation of tourists to visit similar destinations, and their purpose is to determine destinations for their companions or family (Toyama and Yamada, 2012). The idea of objective steadfastness has been generally examined by the tourism industry researchers to create powerful approaches to attract more tourists to their destination (Kim and Brown, 2012; Toyama and Yamada, 2012; Mechinda, Serirat, and Gulid, 2009; Yoon and Uysal, 2005). H 1: Service quality positively affects the commitment to become Islamic tourists. 2.1 Level of religiosity Several studies examined strict general climate, which encompasses breathtaking places, legacy, and craftsmanship (Di Giovine, 2011; Nolan and Nolan, 1992; Reader, 2007; Shuo et al., 2009; Voase, 2007). Also, strictness can emphatically impact rigorous experience. 137

According to Fam, Waller, and Erdogan (2004, p. 538), “religion characterizes the goals of life, which thus are reflected in the qualities . . . of the person”. H2a: The level of religiosity is positively related to the commitment to become Islamic tourists. 2.2 The level of religiosity and quality of service Religion is viewed as one of the significant factors in the basic leadership process concerning the motives of tourism (Collins and Tisdell, 2002; Essoo and Dibb, 2004). In his study of the significance of meeting strict needs to expand consumer loyalty, Weidenfeld (2006) mentioned further research related to the positive impacts of rigorous demands in an inn on the degree of visitors’ satisfaction. In line with the findings of Weidenfeld, Ron (2008) argues that the con­ nection between the tourism industry and religion is legitimate and significant research. Besides, he posits that enjoyable yet strict necessity in Islamic tourism should be considered particularly in a promotion. He believes that rigorous needs should be met in all travel indus­ try organizations and offices, for example, tourist attractions, airports, guest data focus, and food outlets. H2b: Religiosity positively affects administration quality.

3 METHODOLOGY 3.1 Samples and data collection The population of this study was people who experience or are currently on Islamic tours. Sampling units were individuals. The method used distribution and questionnaire collection by giving to several respondents who went to or are presently on an Islamic trip. In this study, the 300 questionnaires were taken for the final data analysis. To eliminate differences in response patterns due to various references, all respondents were asked to answer the survey s by referring to Islamic tourist attractions that they went to or are currently visited. Also, they identified what decisive factors affect their loyalty to Islamic tourist destinations. Finally, they filled out the questionnaire. 3.2 Measurement instruments and questionnaire design The research scale was conducted based on the previous one. Modifications were made to fit the context and objectives of the current research. The measurement of “service quality” used a 26 item measure adopted from Lux (2003). “Destination loyalty” using a nine-item size was taken entirely from Martin (2005). “Religiosity” employed a size of fourteen items that were fully adjusted from Alex Wilde and Stephen Joseph (1997). All measurement items were assessed on a Likert scale, as follows. Service quality employed seven points from 1 = not 138

important to 7 = very important to express the level of agreement. Furthermore, “Destination loyalty” and “Religiosity” used five-points between 1 = strongly disagree, and 5 = strongly agree.

4 ANALYSIS RESULTS OF RESEARCH DATA 4.1 Evaluation of Partial Least Square (PLS) models The use of the PLS model should meet all requirements when used as an analytical tool. These conditions must be evaluated with two evaluation models in Partial Least Square (PLS) ana­ lysis, namely the Outer Model and Inner Model. Table 1 shows that the variables of this study have consistency. Of the three parameters, two parameters (composite reliability, Cronbach’s alpha) was found as reliable because the value was higher than the rule of thumb. Furthermore, the AVE parameter revealed that all its variables did not categorize as good. However, since the two parameters were fulfilled, the authors concluded that the research instrument was quite reliable. Based on Table 2, it was found that in this structural model, the influence of SQ on DL showed in the value of R-squared of 0.581, indicating that the value of SQ variation deter­ mined 58.10% of DL variation. In contrast, the remaining 41.9% was determined by variations of other variables. Furthermore, the effect of religiosity on SQ revealed the R-squared value of 0.365, meaning that 36.50% of the value of SQ variation is was determined by the value of R variation. At the same time, variations in other variables were determined by the remaining 63.50%. Based on the magnitude of the R-squared value, it can be concluded that the model was quite good. 4.2 Hypothesis testing 4.2.1 First hypothesis

Based on the results, the value of t arithmetic = 6,543 was found with the P-Value = 0.000.

The p-value was