Information Technology and Management

International Journal of

Information Technology and Management Volume 8, No 2, 2009

Editor-in-Chief: Dr. M.A. Dorgham Publisher’s website: www.inderscience.com Email: [email protected]

ISSN (Print) 1461-4111 ISSN (Online) 1741-5179

Copyright© Inderscience Enterprises Ltd No part of this publication may be reproduced stored or transmitted in any material form or by any means (including electronic, mechanical, photocopying, recording or otherwise) without the prior written permission of the publisher, except in accordance with the provisions of the Copyright Designs and Patents Act 1988 or under the terms of a licence issued by the Copyright Licensing Agency Ltd or the Copyright Clearance Center Inc. Published and typeset in the UK by Inderscience Enterprises Ltd

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The International Journal of Information Technology and Management is a refereed and highly professional journal covering information technology, its evolution and future prospects. It covers technological, managerial, political, economic and organisational aspects of the application of IT. It aims to provide a forum for professionals and academics in the field to exchange ideas and disseminate knowledge. The Journal publishes: original papers; review papers; technical reports; case studies; conference reports; book reviews and notes; and commentaries and news. Contribution may be by submission or invitation, and suggestions for special issues and publications are welcome. Commentaries on papers and reports published in the Journal are encouraged. Authors will have the opportunity to respond to the commentary on their work before the entire treatment is published. Subject coverage • Managing the rapid changes in information technology • Emerging advances in IT and its new applications • Implications of digital convergence • Managing national information infrastructure • Advances in encryption • Jurisdiction in cyberspace • Managing networks • Intelligent organisations • Digital convergence and growth of IT • Management of corporate networks • IT and network organisations • Organisational barriers to implementing IT • IT and electronic governance • Enterprise resource models • Enterprise knowledge management • Knowledge repositories • Customer relationship management and IT • Knowledge economy • Intelligent agents • Diffusion of IT • Distributed software development • Knowing machines • IT and new forms of organisations • Intellectual property rights in IT • IT and gene mapping revolution • Future of IT • Social informatics

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IT clusters Management and geographic information Geographic Information Systems

IJITM places great emphasis on the quality of the papers it publishes. A full double-blind refereeing process is used. Submission of papers Papers, case studies, etc. in the areas covered by IJITM are invited for submission. Authors may wish to send an abstract of proposed papers in advance. Notes for intending authors can be found at: https://www.inderscience.com/papers All papers must be submitted on line. Authors of accepted papers will receive a PDF file of their published paper. Hardcopies of journal issues may be purchased at a special price for authors from [email protected] All editorial correspondence (but not subscription orders) should be sent via email to the IEL Editorial Office at: Email: [email protected] Fax: (UK) +44 1234-240515 Website: www.inderscience.com Neither the Editor-in-Chief, the Editors, nor the publisher can accept any responsibility for opinions expressed in the International Journal of Information Technology and Management nor in any of its special publications. Subscription orders The International Journal of Information Technology and Management (IJITM) is published in four issues per volume. A Subscription Order Form is provided in this issue. Payment with order should be made to:Inderscience Enterprises Ltd. (Order Dept.), World Trade Center Building 11, 29 Route de Pre-Bois, Case Postale 856, CH-1215 Genève 15, Switzerland. You may also FAX to: (UK) +44 1234 240 515 or Email to [email protected] Electronic PDF files IJITM papers are available to download from the website: www.inderscience.com Online payment by credit card. Advertisements Please address enquiries to the abovementioned Geneva address Email: [email protected]

MAJOR DEVELOPMENT FOR SUPPLY CHAIN MANAGEMENT, INFORMATION SYSTEMS AND LOGISTICS

Guest Editors: Dr. Chien-Ta Bruce Ho

Institute of Electronic Commerce, National Chung Hsing University, 250, Kuo Kuang Road, Taichung 402, Taiwan Fax: +886-4-2285-9497 E-mail: [email protected]

Dr. Tzong-Ru Leo Lee

Department of Marketing, Center for Electronic Commerce and Knowledge Economics Research, National Chung Hsing University, 250, Kuo Kuang Road, Taichung 402, Taiwan Fax: +886-4-2285-9497 E-mail: [email protected]

Published by

Inderscience Enterprises Ltd

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Int. J. Information Technology and Management, Vol. 8, No. 2, 2009

Contents SPECIAL ISSUE: MAJOR DEVELOPMENT FOR SUPPLY CHAIN MANAGEMENT, INFORMATION SYSTEMS AND LOGISTICS Guest Editors: Dr. Chien-Ta Bruce Ho and Dr. Tzong-Ru Leo Lee 127

Editorial Chien-Ta Bruce Ho and Tzong-Ru Leo Lee

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A framework for implementing TISIT model to integrate TQM with software and information technologies N. Gunasekaran, V.P. Arunachalam and S. Arunachalam

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Developing collaborative competencies within supply chains Karine Evrard Samuel and Alain Spalanzani

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Cost benefit sharing-based coordination in logistics networks Iwo V. Riha and Bernd Radermacher

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Implementation and empirical evaluation of voice-enabled web applications Shuchih Ernest Chang

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A study on the effect of work environment perception on user satisfaction in health information systems: HISs quality as mediator Chung-Hung Tsai and Dauw-Song Zhu

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Supply chain quality orientation: Does company profile matter? Roaimah Omar, Suhaiza Zailani and Mohamed Sulaiman

International Journal of Information Technology and Management (IJITM) Editor-in-Chief: Dr. M.A. Dorgham International Centre for Technology and Management, UK Email: [email protected] Co-Editors Professor Dimitris Assimakopoulos Grenoble Ecole de Management, Europole, 12 rue Pierre Sémard, BP 127, 38003 Grenoble cx01 France Email: [email protected] Professor B. Bowonder Director, Tata Management Training Centre, Mangaldas Rd., Pune-411 001, India Email: [email protected] Associate Editor Prof. Dr. Detlef Schoder Chair, Department for Information Systems and Information Management University of Cologne, Pohligstrasse 1, D-50969 Cologne, Germany Email: [email protected] Members of the Editorial Board Professor Hamideh Afsarmanesh Dr. Rafiq Dossani Dept. of Computer Science, Senior Research Scholar, University of Amsterdam South Asia Initiative, Informatics Institute, Kruislaan 403 Asia Pacific Research Center, 1098 SJ Amsterdam, The Netherlands Stanford University, Fax: +31 20 525 7490/7419 E309 Encina Hall, 616 Serra Street, Email: [email protected] Stanford, CA 94305-6055, USA Fax: +1 650/723 6530 Dr. Xavier Boucher Email: [email protected] Assistant Professor Division for Industrial Engineering and Professor Petter Gottschalk Computer Sciences Professor of Information Management, Ecole Nationale Superieure des Mines de Norwegian School of Management, Saint Etienne, 158 Cours Fauriel Box 580, 1302 Sandvika, Norway 42013 Saint Etienne Cedex, France Fax: +47-67-55-76-78 Email: [email protected] Email: [email protected] Professor Luis M. Camarinha-Matos Professor Dr. Lorenz M. Hilty New University of Lisbon, Technology and Society Laboratory Quinta da Torre, Swiss Federal Laboratories for Materials 2829-516 Monte Caparica – Portugal Testing and Research (EMPA), Fax: +351-212941253 Lerchenfeldstr. 5, Email: [email protected] CH-9014 St. Gallen, Switzerland Fax: +41-71-274-7862 Dr. Dimitri Corpakis Email: [email protected] Directorate General for Research Professor Robert Laurini European Commission Director, Laboratory of Information Systems B-1049 Brussels, Belgium Engineering (LISI), Fax: +32-2-29-57729, +32-2-29-94643 INSA de Lyon, Bât. Blaise Pascal Email: [email protected] F - 69621 Villeurbanne Cedex, France Professor Wendy L Currie Email: [email protected] Warwick Business School University of Warwick, Coventry CV4 7AL, UK Fax: + 44 - (0)24 - 7652 4539 Email: [email protected]

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Members of the Editorial Board (continued) Professor Feng Li Chair of E-Business Development Director of Teaching & Learning The Business School University of Newcastle upon Tyne Newcastle upon Tyne NE1 7RU, UK Email: [email protected] Ms. Dan Liang Director, Investment & Technology Promotion Branch Investment Promotion and Institutional Capacity - Building Division, UNIDO, VIC, A-1400 Vienna, Austria Email: [email protected] Professor Stuart Macdonald School of Management, University of Sheffield, 9 Mappin Street, Sheffield S1 4DT,UK Fax: +44 (0)114 222 3348 Email: [email protected] Professor Robin Mansell Dixons Chair in New Media and the Internet, London School of Economics and Political Science, Houghton Street, London WC2 2AE Email: [email protected] Emeritus Prof. Ian Masser Town End House Taddington, Derbys SK17 9UF, UK Professor Ian McLoughlin Head, School of Management, University of Newcastl Armstrong Building, Newcastle upon Tyne, NE1 7RU, UK Fax: +44 (0)191 222 8131 Email: [email protected] Mr. Nandan M. Nilekani CEO, President and Managing Director Infosys Technologies Ltd., Plot No. 44 & 97A, Electronics City, Hosur Road, Bangalore 561 229, India Professor Gregory Prastacos Director of the Graduate Program in Decision Sciences, Athens University of Economics and Business, 76 Patission Str., Athens 104 34, Greece Fax: +30-1-8215.414 Email: [email protected] Dr Angel Salazar Business School Manchester Metropolitan University, Aytoun Street, Manchester M1 3GH UK Fax: +44 161 247 6317 Email: [email protected]

Professor AnnaLee Saxenian Dean and Professor School of Information Management and Systems,University of California 102 South Hall, Berkeley CA 94720-4600, USA Email: [email protected] u Professor John Sillince Strathclyde University Department of Management, Business School 199 Cathedral Street, Glasgow G4 0QU, UK Email: [email protected] Professor W. Andrew Taylor Business Information Systems Research School of Management University of Bradford Emm Lane, Bradford, BD9 4JL, UK Email: [email protected] Professor Morris Teubal Department of Economics, The Hebrew University of Jerusalem, Mount Scopus, Jerusalem 91905, Israel Fax: 972-2-5816071 Email: [email protected] Prof. Dr. S.H. Von Solms Vice President, IFIP and Head, RAU-Standard Bank Academy for Information Technology, Rand Afrikaans University, Johannesburg, South Africa Email: [email protected] Professor Poh-Kam Wong Director, National University of Singapore, Entrepreneurship Centre, 14 Prince George’s Park, 118412 Singapore Email: [email protected] Professor Desheng (Dash) Wu Director, RiskChina Research Center; Affiliated Professor, RiskLab; Research Fellow, University of Toronto Joseph L. Rotman School of Management Toronto, Ontario M5S 3G8, Canada Professor David C. Yen Chair and Professor, Dept. of Decision Sciences and Management Information Systems, Miami University Oxford, Ohio 45056, USA Email: [email protected]

CALL FOR PAPERS International Journal of

Networking and Virtual Organisations (IJNVO) Website www.inderscience.com ISSN (Online): 1741-5225 ISSN (Print): 1470-9503 International Journal of Networking and Virtual Organisations (IJNVO) is a vehicle to provide a refereed source of information in the field of Networking and Virtual Organisations. Its objective is to further the development of this dynamic, innovative and global topic. The aim of IJNVO is to establish channels of communication between relevant academics and research experts, policy makers and executives in industry, commerce and investment institutions. The Journal publishes: original papers; review papers; case studies; conferences reports; relevant technology and management reports and news, book reviews and notes. Commentaries on papers and reports published in the Journal are encouraged. Authors will have the opportunity to respond to the commentary on their work before the entire treatment is published. Subject coverage • Network forms of organisations including inter- and intra-organisational networks • Formal and informal networks including inter-personal networks • Community, social and communication networks • Networks in collaboration and competition • Networks in science and technology studies • Networks between industry and academia • Networks in learning across institutional, disciplinary, and geographical boundaries • Global and local innovation networks • Regional collaborative clusters and inter-firm networks • Virtual networks • Organisations with changing and unclear boundaries • Decentralised and more centrally coordinated networks and virtual organisations • Management of dispersed project teams • Application of network theory to virtual organisations • Network analysis methodology, including social network analysis and graph theory. • Virtual organisation and media use in developing countries • Enterprise integration Specific Notes for Authors All papers are refereed through a double blind process. A guide for authors, sample copies and other relevant information for submitting papers are available at www.inderscience.com/papers Please send the submitted paper and submission letter via e-mail to: Dr. N. Wickramasinghe Stuart Graduate School of Business, IIT, 565 W Adams St Suite 406, Chicago, IL, 60661 USA E-mail: [email protected] Please include in your submission the title of the Journal.


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Editorial Chien-Ta Bruce Ho* Institute of Electronic Commerce, National Chung Hsing University, 250, Kuo Kuang Road, Taichung 402, Taiwan Fax: +886-4-2285-9497 E-mail: [email protected] *Corresponding author

Tzong-Ru Leo Lee Department of Marketing, Center for Electronic Commerce and Knowledge Economics Research, National Chung Hsing University, 250, Kuo Kuang Road, Taichung 402, Taiwan Fax: +886-4-2285-9497 E-mail: [email protected] Biographical notes: Chien-Ta Bruce Ho is an Associate Professor in the Institute of E-Commerce at National Chung Hsing University. He has over 75 publications in the forms of journal papers, books, edited books, edited proceedings, edited special issues and conference papers. Sample of his work could be found in Computers and Operations Research, Journal of the Operational Research Society, International Journal of Production Research, Online Information Review, Industrial Management and Data System and International Journal of Production Economics. He is also the Editor of the International Journal of Value Chain Management and International Journal of Electronic Customer Relationship Management. Tzong-Ru Leo Lee is a Professor of Marketing Department, Chairman of Institute of Electronic Commerce and Chairman of Center for Electronic Commerce and Knowledge Economics Research in National Chung Hsing University in Taiwan. He is a Fulbright Visiting Professor in USA in 2006 and a joint author of four books. His research mainly focuses on SCM, CRM, Marketing and EC. Also, he is the Co-editor of the International Journal of Electronic Customer Relationship Management and the Associate Editor of International Journal of Logistics Economics and Globalisation.

We are pleased to introduce this Special Issue of International Journal of Information and Technology Management on ‘Major Development for SCM, IS and logistics’. This Special Issue is one of the important deliverables from the 4th International Conference on Supply Chain Management and Information Systems (SCMIS, 2006),

Copyright © 2009 Inderscience Enterprises Ltd.

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C-T. Bruce Ho and T-R. Leo Lee

Taiwan, 5–7 July 2006. Suitable papers were invited to submit to this Special Issue, and the journal’s review process was undertaken. This Special Issue contains six papers, discussing major challenges and development for SCM, IS and logistics. Below is a brief overview of the papers that appear in this issue. The first paper by Gunasekaran, Arunachalam and Arunachalam is to propose a framework for implementing a model called TQM Integrated with Software and Information Technologies (TISIT), which integrates the TQM foundations with the software and information technologies. This proposed framework of this paper enables the organisations to reduce or eliminate the gaps which are created due to the customer expectations and the actual deliveries. Samuel and Spalanzani present a new approach to interenterprise collaboration via the concept of collaborative competencies. The authors use empirical evidence based on two case studies. The final result of a four-dimensional framework may help serve to analyse collaboration design and establishment within integrated supply chains. This third paper of Riha and Radermacher presents a comprehensive approach for an incentive system in logistics networks based on network-wide evaluation and reallocation of costs and benefits. This paper shows that alternative allocations of resources based on sharing costs and benefits can give an incentive to the network-partners: Cost Benefit Sharing (CBS). It enables activity dependent reallocation of individual effects that reflect the costs and benefits of each party and systematically considers qualitative factors. The fourth paper by Chang is to describe how a Voice-enabled Web System (VWS) is designed and implemented to provide an interactive voice channel using an Apache web server, a voice server and Java technologies. The findings of this paper may be referenced for the purpose of the design and development of successful business applications to catch the revolutionary opportunity and benefit of VWSs. The fifth paper by Tsai and Zhu is to develop the user satisfaction model of health information systems. A survey of 252 samples of the medical centre in Taiwan shows that the effects of user involvement and supervisor support on user satisfaction are mediated by health information system quality. Besides, service quality has the most influence on user satisfaction in health information system quality. The final paper by Omar, Hanim and Sulaiman examine the Supply Chain Quality Orientation (SCQO) in manufacturing companies and the effect of organisation profile on SCQO. The organisation profile encompasses types of industry, company ownership, market for main product, number of suppliers, company age, company position in supply chain, EDI and supply chain manager. 550 questionnaires were distributed to the manufacturing companies in Malaysia and 142 completed questionnaires were analysed to determine the level of SCQO. The results indicate that SCQO does not vary according to respondents’ organisation profile in Malaysia manufacturing industry. Altogether, the presented papers describe interesting and solutions in SCM, IS and logistic field. The Guest Editors would like to thank all the authors for submitting their papers to this Special Issue and the reviewers for their valuable comments and contribution.


A framework for implementing TISIT model to integrate TQM with software and information technologies N. Gunasekaran* Department of Mechanical Engineering, Angel College of Engineering and Technology, Tirupur 641 665, India E-mail: [email protected] *Corresponding author

V.P. Arunachalam Department of Mechanical Engineering, SNS College of Technology, Coimbatore 641 035, India E-mail: [email protected]

S. Arunachalam School of Computing and Technology, Manufacturing Engineering Division, University of East London, Longbridge Road, Dagenham, Essex RM8 2AS, UK E-mail: [email protected] Abstract: This paper proposes a framework for implementing a model called Total Quality Management (TQM) Integrated with Software and Information Technologies (TISIT), which integrates the TQM foundations with the software and Information Technologies (IT). This framework enables the organisations to reduce or eliminate the gaps which are created due to the customer expectations and the actual deliveries. An algorithm has been designed, developed and validated with a case study on implementing TISIT. A generic framework is found and useful to improve the quality on continual basis in any organisation. The flexibility of this framework is that one could start from any stage as they like and continue the cycle of implementation. Keywords: TQM; total quality management; IT; information technologies; software; quality of people; quality improvement. Reference to this paper should be made as follows: Gunasekaran, N., Arunachalam, V.P. and Arunachalam, S. (2009) ‘A framework for implementing TISIT model to integrate TQM with software and information technologies’, Int. J. Information Technology and Management, Vol. 8, No. 2, pp.129–145.


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N. Gunasekaran, V.P. Arunachalam and S. Arunachalam Biographical notes: N. Gunasekaran is a graduate in Mechanical Engineering and a post-graduate in Industrial Engineering from Thiagarajar College of Engineering, TN, India. He has completed his PhD from Bharathiar University, Coimbatore. He is currently serving as a Professor in the Department of Mechanical Engineering and Principal of Angel College of Engineering and Technology, Tirupur, TN, India. He has published 5 papers in the international journals and 2 papers in the national journals in addition to 32 papers in national and international conferences. V.P. Arunachalam is currently serving as a Professor in the Department of Mechanical Engineering and Principal of SNS College of Technology, Coimbatore, TN, India. He has published 25 papers in the international journals and 6 papers in the national journals in addition to 45 papers in national and international conferences. S. Arunachalam is a Faculty in the Manufacturing Engineering Division of School of Computing and Technology, University of East London, Dagenham, UK.

1

Introduction

A product supply chain is a network of suppliers, factories, warehouses, distribution centres and retailers, through which raw materials are acquired, produced and delivered to the customer. The operations of these elements in a chain of product making have distorted to a large extent due to impact of internet and Information Technologies (IT). IT makes it possible to enhance the involvement of cross-functional teams even without physical integration of various elements of a production system and integration of activities of manufacturing to delight the customers. The advent of software engineering and internet technologies helps to reduce quality gaps, which are classified as perception, understanding, design, process and operation gaps. A model called Total Quality Management (TQM) Integrated with Software and Information Technologies (TISIT) is found to be encouraging the continuous improvement of quality in these organisations. A framework of implementing the TISIT model is described with a case study.

2

Literature review

Global competition has strained the organisations to meet quality gaps as the customers’ expectations are changing with time. The quality gaps are generated or widened in a manufacturing company due to the influence of globalisation, deregulation and technology sophistication (Reis et al., 2002). IT is increasing in importance for companies and its effects on global trading are becoming more widely felt (Lorente et al., 1999) while IT has a key role to play in the process of applying TQM in an organisation (Dewhurst et al., 1999). Many researchers and practitioners believe that TQM integrated with performance measurement systems helps to achieve business excellence (Chin et al., 2003). They have developed a training toolkit based on Malcolm Baldrige National Quality Award model and it is named as ‘Knowledge-based Expert Self-assessment (KES)’. Studies have been made on the need and management implications of Web enabled Performance Measurement Systems (WePMS) to respond proactively to

A framework for implementing TISIT model to integrate TQM

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customer and market needs with a greater number of customer specified products, more flexible processes, suppliers and resources coordinated through a number of factories and warehouses, while reducing costs (Bititci et al., 2002). Synergies could be achieved if Information System (IS) is developed in TQM environment for improved organisational effectiveness (Fok et al., 2001). An Integrated Product Development–Quality Management (IPD–QM) approach motivates the practitioners to concentrate on product development embedded with TQM considering the shortcomings of existing approaches such as focused only on cost and manufacturability (Gunasekaran, 1998). Although the focus remains on computers, the business value lies in business process and that our major emphasis now should be on ‘IT-supported business processes’ (Hoplin, 1995). Studies have been conducted on the role of internet and how it affects the various parts of value chain of firm, integration of supply chain and its performance in manufacturing (Frohlich and Westbrook, 2002; Pant and Hsu, 1996; Thermistocleous and Chen, 2004). It showed that manufacturers and services relying on only web-based demand or supply integration outperformed their low integration counterparts. However, the communication between companies is not integrated fully as it is handled through file exchange. Processes of supporting the new way of working are still under development (Appelqvist et al., 2004). Internet provides a tool in such exercises. It allows maximum supply chain performance by activities to be carried out in a synchronised, instantaneous manner (Lankford, 2004). However, all the quality gaps are not addressed together in literature. While literature is available on service quality, there are not many manufacturing specific models exploit the technology sophistication. There is a need for such a model as quality gaps between producers and customers are high in the post-industrial economy. Gunasekaran (2005) proposed a model called TISIT in his PhD thesis.

3

Quality gaps

Quality is degree of excellence, which depends on the ability of an organisation to bridge quality gaps. TQM and connected models have helped to improve quality in manufacturing. PZB model addresses five quality gaps in a service company (Parasuraman et al., 1985). Candido and Morris (2000) had described a Service Quality Gap (SQG) model to improve quality in an organisation. They had again enhanced their model and suggested models namely, synthesised static model, synthesised dynamic model and a mixed model to bridge quality gaps in a service company (Candido and Morris, 2001). In 2002, two new gaps have been introduced to the PZB model (Luk and Layton, 2002). Today, these models are not enough to attain higher degree of excellence in organisations due to technology sophistication. As mentioned in the previous section, the global competition has created gaps and they are classified as operations gap, process gap, perception gap, understanding gap and design gap (Juran and Godfrey, 1998). This is depicted in Figure 1. Operation gap emanates because of difference between actual delivery and capability to deliver while process gap occurs due to the difference between product design and capability to deliver. Perception gap occurs due to the perception of the customer about actual delivery. The lag in understanding of customer expectations by the design group creates understanding gap. And the design gap exists due to the aberration in converting

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the understanding of customer expectations. Global competitive situation has forced today’s organisations to contribute products with shortened product life cycles with the involvement of multifunctional groups. Anyway, the involvement of multifunctional groups widens these gaps. The time taken to reduce or eliminate these gaps increases with the size of companies. Researchers, practitioners and commercialists have been contributing concepts, models and devices for reducing or eliminating these gaps (Millson and Smith, 1996). Of all, three most powerful enablers have contributed highly worthwhile solutions. These enablers are addressed today under three terminologies namely ‘Total Quality Management (TQM)’, ‘IT’ and ‘Software Engineering’. In fact, these enablers have enhanced the quality of human life and organisational performance to a very great extent. The roles of these three enablers have been favourable, significant and tremendous in a product supply chain. TISIT is a model, which links these three enablers to attain the synergic effect to reduce or eliminate the above gaps to the extent required. Figure 1

4

Types of gaps as existing in today’s product making situation

Research objectives

Literature review appears to conclude that there is a need for a model to link the gaps as identified with application of IT to achieve higher degree of excellence in organisations. This paper discusses the following objectives. 1

to describe the TISIT model

2

to design a framework for implementing the TISIT model

3

to validate it with a case study

4

to discuss the issues that will be encountered in the future.

5

TISIT: a model for enhancing the quality of TQM

5.1 Salient features of TISIT The conceptual features of TISIT are depicted in Figure 2.


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5.1.1 Customer The customer is the heart of TISIT model. A review of the prescriptive, conceptual, practitioner and empirical literature on about 100 papers, and all TQM models identify customer focus as one of the 12 important dimensions of quality management (Sureshchander et al., 2001a,b). Customers have a general understanding that the true cost of a product is not just the price paid to the seller; it also includes the time, effort and expense of acquiring the product at the end of its useful life (Burrill and Ledolter, 1998). The customers are the source of trigger for a company to come out with a product/service improvement each time. Hence, it is imperative to have the customer as the heart of this TISIT model for its implementation. Figure 2

TISIT: TQM Integrated with software and information technologies

5.1.2 Quality of people The quality of an organisation’s products depends fundamentally on its belief in quality and in people who are connected with it namely shareholders, management, employee, supplier and society. Every action of people in the organisation must support their belief in quality. Top management must believe in quality and must clearly articulate this belief to all individuals concerned since they form part of the working culture. The actions of employees are nowadays changed due to the influence of software and IT. Under these circumstances, everyone dealing with the quality function by now has either faced the computer or retired (Juran and Godfrey, 1998). They also have made a statement that the breakthrough technology in communications and data storage has already begun the transition from powerful stand-alone machines back to large, virtual machines of unlimited potential. Internet and its derivatives will spawn this revolution.

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This element, quality of people, has a link with customer on one side while it has links with quality of process and quality of product on the other. Hence, any Human Resource Development (HRD) improvement will improve the relationship of the people with customers and improve the quality of process and quality of product.

5.1.3 Quality of process Next to people, the quality of process decides output quality of the product. The technological advancements have made a lot of influences in the management of processes, which are defined as a set of interrelated resources, and activities that transform inputs into outputs. The resources may include personnel, finance, facilities, equipment, techniques and methods (ANSI/ISO/ASQC A8402-1994, clause 1.2). The quality of process influences two main gaps namely operations gap and process gap, which are shown in the TISIT model. A general lack of knowledge about process concepts is a primary reason for these types of gaps, which lead to inferior quality of product. They can be reduced or eliminated if the quality of processes is ensured either with or without the support of software and IT. Basically, the quality improvement could be achieved by incremental changes or replacing the existing system with a new system. But in each case the role of software and IT cannot be avoided as it is demonstrated through literature. The quality improvement in an organisation is largely a matter of improving production process and their interfaces, which essentially uses the support of software and IT in implementing TQM (Schneider and Marquardt, 2002; Sohal, 1999). Hence, the quality of process is linked with software and IT supported process in the bottom side while there has to be clarity for achieving TQM implementation for either reducing or eliminating the operations and process gaps.

5.1.4 Quality of product The output of any process is called as product. It can be used to refer goods or services. The customer is the real judge of the quality of product because their perception gap forms base for further widening the understanding, design, process and operation gaps. Reliability is the link between quality of product and implementation of TQM. The reliability of product can be achieved by using the following product development tools and techniques: •

Quality Function Deployment (QFD)

•

design of experiments

•

value engineering

•

activity-based costing

•

loss function analysis

•

failure mode and effect analysis

•

fault tree analysis

•

seven QC tools

A framework for implementing TISIT model to integrate TQM •

new seven QC tools

•

poke-Yoke approach

•

vendor development.

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Almost all the tools are nowadays computer-based and aided and result with much better reliability as compared to that of earlier. Indigenously developed software for QFD has been employed in conducting a case study for implementing TISIT model. QFD is the only tool which links the complete cycle of development of a product while it integrates the quality of people, quality of process, and quality of product with the customer (Gunasekaran and Ngai, 2004). Also it can be used to measure the gaps with each of the elements with a competitor and they can be reduced or eliminated.

5.1.5 Quality gaps Global competition has created gaps in attaining higher degree of quality in modern organisations. Quality gaps are classified as operations gap, process gap, perception gap, understanding gap and design gap. All these gaps have already been defined in Section 3 of this paper. The authors have made an attempt to link all these gaps with the elements of TISIT to either reduce or eliminate them in an organisation using advancements in IT.

5.1.6 Software and IT sources Only people learn and the organisations and systems adapt (Bolk et al., 1997). They also said that the newly defined domain of computer supported collaborative work and of team-based architectures, should emphatically take into account the human being. The most important issue facing the management is careful implementation, requiring much planning, retraining and attitudinal change of employee (Aggarwal, 1995). A small company had successfully implemented the Advanced Manufacturing Technologies (AMT) such as CAD/CAM/CIM with the involvement of people at different levels and the management of Human Resources (HR) had helped them to meet the customer requirements (Sohal, 1999). Software and IT play irreversible roles in making the link between TQM and quality of people to be stronger for continuous improvement. The ability to tap into and maximise human potential of an organisation will be a major determinant of continuous improvement (Power and Sohal, 2000). There is a need for understanding of problems by a team of people to come out with the expected quality of products. Studies have been conducted on teams, personality types and QFD to promote clarity and understanding of problems for sound, pragmatic and robust design for quality (Lyman and Richter, 1995). Clauson (1995) had discussed the quality resources on the internet to develop the HR of expected quality. He also explains the TQM and quality assurance policies and its applications in the manufacturing and service industries. The Quality of people is considered to be first among the three and it should have a strong link with the other two elements of TQM model (Mani et. al., 2003a). The communication systems help to implement the software and IT solutions at a much faster rate than that of earlier. The software and IT sources link the planning and implementation while it enhances the quality of people, which is the prime factor for minimising the understanding and operations gaps. A case study reported in this paper also supports this construct to continually improve the involvement and integrity of quality of people, which support the effective implementation of TQM.

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5.1.7 Software and IT supported process Quality of process, which works in the side of process gap and operations gap, is the next important element. The business process improvements depend on documents and their consistency, usage, proper storage and linking (Eloranta et al., 2001). Building a model (applying some of the tools of TQM approach) focusing on the plants, people, technology and products with access available for input and analysis from locations world wide would generate information which would further increase organisations’ effectiveness (Bigwood, 1997). The computer must become more than a data storage and transfer mechanism; the processing and hence reasoning capabilities of computers should be brought to bear in the quality improvement effort. Computer-based visualised quality system will be faster, easier and more interesting to use than a paper system (Blome et al., 2003; Dooley et al., 2000). Firms with intrafirm structural linkages have an enhanced ability to innovate, regardless of type of innovation. When there are substantial interdependencies across parts of a firm, intrafirm linkages cut across projects and product lines, providing a free-flowing exchange and cross pollination of information (Koberg et al., 2003). The quality of process depends on the Quality Information System (QIS), which is the integration of Management Information System (MIS) with TQM (Keith, 1994). These literature in addition to the case study on QFD reveal that improved process of design and control contribute to minimise the operations and process gaps with the support of software and IT.

5.1.8 Software and IT-based tools The buzzword ‘survival of fittest and fastest’ is famous among the companies due to the pace of continuous improvement, which decides the market. The quality of product depends on how quickly the feedback information is provided for planning, implementing and controlling the gaps. The QFD, a versatile tool, helps to measure, analyse and control all the gaps. The QFD has changed dramatically from providing defect-free products to customer driven or desired products (Chang, 1989; Denton, 1990). QFD models are used in software development as well and there are differences between classic QFD and software QFD (Herzwurm and Schockert, 2003). A special QFD variant for e-commerce called continuous QFD (CQFD) is suitable for planning electronic business applications (Herzwurm and Schockert, 2003). The literature and case study reveal that the effectiveness of quality improvement tools with regard to required pace could be possibly accelerated only when they are supported by software and IT.

5.1.9 Perpetual links As already explained, the operations, process and design gaps are directly influenced by quality of people, quality of process and quality of product respectively. The companies need to plan for a system, which would either reduce or eliminate the gaps with the rising technologies. The people should know the sources available with regard to the software and IT-based tools with a view to plan and design to delight the customers. Internet, which is a major outgrowth of IT could be used for this purpose. The planning can be made taking into account the present and future requirements of a company. Sometimes an organisation is faced with evaluating emerging operations technologies that it must develop concurrently with overall business planning. When this is the case, a number of issues arise. These include compatibility of the technology with existing operations,


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difficulties in launching new products, flexibility to accommodate volume and model mix changes, personnel requirements, and of course, the investment required (Scharlacken, 1992). The operations gap, which develops between quality of people and quality of process, could be reduced or eliminated with the help of the implementation strategies. The process gap between quality of process and quality of product could be reduced or eliminated with the help of control mechanisms institutionalised with the manufacturing planning and implementation. The perpetual links between planning, implementation and control with software and IT at the early stage of quality planning would result in the concurrent development of HR, process improvement and product improvement. However, the various elements of TQM including education and training should be addressed wherever required.

5.1.10 Concurrent links The success of TQM implementation depends on the resultant of all the above discussions leading to concurrent links of integrity, clarity and reliability. There are research papers, which demand the inclusion of ethics in working culture with TQM even though the rising technologies can be integrated. While the House of Total Quality provides the height and breadth of total quality, the organisational, ethical working culture provides the depth (Lindsay and Petrick, 1997). The implementation part of TQM would be an impossible task without the ethical working culture. The contemporary literature was almost silent about the integrity and ethics, while Tamil classical scriptures spoke volumes about those human values (Mani et al., 2003b). The clarity of quality of system adopted results in effective implementation of TQM. ISO 9000:2000 defines the need for documentation of quality system and communication, as one of its clauses will be required for building quality into the products. The TQM elements such as involvement of people, education and training and the tools such as quality function deployment enrich clarity of the people, processes and products. The reliability of products would be the result of software and IT-based tools in addition to the software and IT sources, software and IT-supported process. Garvin (1988) included reliability as one of his eight dimensions of quality. Reliability is the ability or capability of a product to perform the specified function in a designated environment for a minimum length of time or minimum number of cycles or events. Hence, the products’ reliability also should be considered in the model for quality improvement since the reliability is the resultant measure of any quality improvement. It also takes care of maintainability, availability and capability of the products. Finally, it strengthens the implementation of TQM, which would ultimately require the support of software and IT in the present and future.

5.1.11 Benchmarking Any improvement by a model should be measured to know its performance. TISIT’s performance could also be measured by using benchmarking methods. Xerox as it is known today, formally developed the benchmarking process in 1979 (Juran and Godfrey, 1998; Rao et al., 1996). Their approaches of benchmarking are classified as follows: 5.1.11.1 Internal benchmarking the similar or identical activities, which are carried out in the same organisation but in another department, could be used for benchmarking. The skills of people in software utility for quality improvement shall be benchmarked within the organisation.

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5.1.11.2 Competitive benchmarking the competitors’ data could be used to benchmark and the performance could be improved. It may be indirect or direct benchmarking. One should be cautious if they use indirect benchmarking then the data should be collected in an ethical and legal manner. Formal benchmarking has been ethically managed since the early 1980s, in part because of the existence of Benchmarking Code of Contact developed by the International Benchmarking Clearing House (Camp, 1989). It would be very successful if it is direct benchmarking. Then cost benchmarking, process benchmarking, and strategic benchmarking could be made by proper tie-up by themselves or by involving third parties. 5.1.11.3 Functional benchmarking a company need not focus only on its competitor to benchmark the processes. This is particularly true when an organisation in a different industry is achieving superior results in a similar function. This source of best practices is where large process gains are possible. The search here is not restricted to a common application but to a method or practice within a process that could be adopted and adapted to a specific process (Barber, 2004). The proposed model has a lot of activities, functions and processes, which could be benchmarked by using any one of the methods listed above. Each area that is operations, processes and design can be separately benchmarked for improving the quality of implementation of TQM.

5.2 A framework for implementing TISIT The implementation of this TQM model starts with motivation for improvement, which in turn results in understanding the customer requirements. The necessary motivation comes from TQM principles. It leads to the identification of perception and understanding gaps. Figure 3 shows the complete framework for implementing TISIT model. As the customers are the source for any improvement, the customers’ needs or requirements form part of inputs to the core element of TISIT that is, quality of people. The integrity of people ensures the quality of people who form part of manufacturing the products and they shall be benchmarked. The TISIT model has the capability to show the perception and understanding gaps as a result of benchmarking. The QFD technique shall be adopted to measure and analyse these two gaps thoroughly with other tools such as questionnaire technique, brainstorming, affinity diagrams, etc (Chan and Wu, 2002; Hales, 1994). At the same time the outputs resulting from benchmarking shall be referred to the TQM foundations. The people in organisations get a lot of inputs from software and IT sources for measuring, analysing and benchmarking the gaps. Benchmarking highlights negative gaps in current performance and recommends appropriate actions to reduce or eliminate them (Zairi, 1992). The gap analysis definitely leads to either reduction or elimination of gaps. The elements, quality of people, quality of process, quality of products and benchmarking get input from this element of TISIT. From the benchmarking stage, a company shall come to know other gaps that emanate from the perception and understanding gaps. Hence, the resulting gaps namely design, process and operations gap shall form part of inputs to the HRD, process improvement and product improvement, respectively. The outputs from the gap analysis, HRD, process improvement and product improvement are linked to the appropriate core elements of TISIT model. Say for example, the quality of process takes input from the gap analysis, HRD, process improvement while the degree of quality of process shall be improved by using appropriate software and IT. It results in improved process with higher clarity,


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which in turn forms part of benchmarking. And the improvement cycle continues further. Similarly, the core element quality of product takes input from gap analysis, HRD, process improvement and product improvement while the degree of quality of product shall be improved by using software and IT capabilities. It results in improved product with higher reliability. Figure 3

Framework for implementing TISIT

The degree of understanding shall be improved with the use of internet, etc. The involvement of people in manufacturing environment shall be enhanced with the input from understanding stage and use of software and IT sources. The required HRD shall be compared to that of the existing and feedback shall be given to the people. Any improvement of HR results in improved process and product. Software and IT-based processes shall be employed with due consideration to investment during process design stage. Next to quality of people, the quality of process forms the basis for quality products. The process improvements shall be compared to that of their benchmarked process and feedback shall be used to decide the degree of software and IT usage. Benchmarking could be used to check the level of implementation of TQM. The next cycle of TQM implementation shall be started with newfound motivation.

6

Validation with a case study

M/s Preetha heaters is a company manufacturing different types of heaters namely Fusing machine, Drying oven, Printing dryer and Automatic sticker printing machine. Even though the company has the design of these heaters, it wants to cater to the needs of the customers by suitably modifying the design capacity. There are subcontractors who need to know the requirements of the customers so that the assembly at a central place

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would serve them. A web page has been designed for the above company and a mechanism of collecting customer requirements have been installed on online. Figure 4 shows the software tree for implementing TISIT model in this case study. The implementation of TISIT is started with a measurement of gap by collecting customer requirements. Their needs are understood and requirements are passed to the subcontractors through a web-enabled system. For this purpose, a questionnaire page and a QFD software have been developed and employed for implementation of this model. On completing the questionnaire page, the data are transferred to a database that the manufacturers and suppliers use to make the quality function deployment charts. The Voices of the Customers (VOC) have been measured for each product and the respective suppliers could access the data to know what the customer wants at present. The manufacturer maintains a server while the suppliers are empowered to access the data through a password provided to them. By this way, they make a QFD chart and get it approved by the manufacturer on online to cater to needs of the customers. As per the framework of implementing TISIT, gap analysis is performed but with help of software and IT. It establishes contact with people concerned and provides information with process and design. The employees of organisations associated with main manufacturer could understand the needs of the end customers’ fully. Further actions are also initiated based on QFD output. Figure 4

Software tree for TISIT implementation

In this case study, automatic sticker printing machine is considered for analysis. On opening the company web page, the customers find an option to choose their product. The following questionnaire appears on screen for automatic sticker printing machine.

A framework for implementing TISIT model to integrate TQM 1

Are you satisfied with the printing accuracy?

2

Does the equipment help you to print the sticker in time?

3

Rate the result of printing in your usage?

4

Rate the provision of height adjustment facility for your printing work?

5

Rate the working environment prevailing when the printing was performed?

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Customers have given their feedback on level of importance, level of quality in a 1 to 5 scale and complaints in numbers against the questionnaire. These data are downloaded through the web at the subcontractor side and quality gap analysis is performed. For this purpose, QFD chart is employed and it is drawn as shown in Figure 5. Figure 5

QFD output for client side (see online version for colours)

The absolute weight is the product of level of importance, improvement ratio and sales point while demanded weight is relative percentage of absolute weight. QFD software generates the output automatically and also plots the graph indicating the relationship of VOC with control parameter. The VOC, result of printing stickers need to be improved based on higher demanded weight, graph and column weight. The perception and understanding gaps are measured through this exercise. It was found that there exists an operation gap related to the above gaps. The surface finish of the bed has been improved to 3 microns by reducing this gap through the integration of VOC into product supply chain. Competitive benchmarking has been used for this purpose. The other stages of QFD take care of remaining gaps. It leads to the HRD and the cycle continues further in

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this line. The TISIT model initiates a step forward to integrate VOC with product supply chain in order to cater to the needs of the customer. This is found to be a new concept and customised designs possibly satisfies the customers. Likewise, process improvements and product improvements could be made with the support of software and IT. One of the pitfalls of this TISIT case study was that company was not convinced with data security even though they were satisfied with the pilot run conducted in about seven minutes. There is no constraint that how much one should invest. But it could be investigated for better return on investment. The cycle could be repeated for ‘n’ times for improving the quality on continual basis.

7

Managerial implications

Managers are trying in all possible ways to improve the quality on continual basis. The rising technologies have had a lot of impact on the activities that are performed in different types of industries. The proposed framework of implementing TISIT model is a viable alternative to improve the products, processes and people continuously. Managers could start their implementation of TISIT from where they wish to start. This flexibility really gives them an option to choose their investment strategy. However, there is a need to study the profit and investment in addition to the payback period. Since the model provides an access of various company data, security and operational issues also need to be studied before its implementation.

8

Conclusion

Companies are adapting new models and concepts to attain higher degree of excellence in quality. Literature reveals that there are three enablers namely, TQM, Software Engineering and IT which help them to reduce or eliminate quality gaps. A model is described in this paper to integrate these three enablers and it is named as TISIT. All 24 elements in TISIT model are linked with software and IT to either reduce or eliminate the gaps. A complete framework has been designed to implement the TISIT model in organisations. TISIT implementation starts with a motivation to improve or else at any stage as it was described in implementation framework. The outputs from one stage could form inputs to other stages while the elements of TISIT are supported by software and IT. The TISIT implementation is validated with a case study involving integration of VOC in a product supply chain. TQM must begin at product conception and continue throughout its supply chain and mechanisms, which are required to allow organisations to integrate TQM into all of their activities. The quality gap between customers, suppliers and manufacturer is measured and analysed in this part of implementation. An online measurement of gap using QFD and actions that are to be initiated at different levels of supply chain are discussed. For this purpose, software engineering and IT capabilities are exploited and the TISIT model is implemented. The quality gaps are possibly reduced through this action. Consequently, this model encourages the degree of excellence in achieving quality on continual basis. However, the TISIT model needs further studies in the light of cost benefit, security and operational issues in the supply chain.


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Acknowledgements The authors acknowledge the comments of the anonymous referees towards improving the presentation quality of this paper.

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Developing collaborative competencies within supply chains Karine Evrard Samuel* and Alain Spalanzani Center of Studies and Research in Management (CERAG), University of Grenoble, UMR CNRS 5820-UPMF, France E-mail: [email protected] E-mail: [email protected] *Corresponding author Abstract: In a context of ever changing markets, developing more and more agile supply chains have become a necessity for most companies evolving in a global environment. The review of the literature on supply chain collaboration shows that the ability to develop an agile and demand-driven supply chain is directly linked to the various partners interacting in a supply chain and their ability to collaborate. This paper presents a new approach to interenterprise collaboration via the concept of collaborative competencies. Through empirical evidence based on two case studies, we put forth a four-dimensional framework which may help serve to analyse collaboration design and establishment within integrated supply chains. Keywords: collaborative competencies; interorganisational collaboration; integrated supply chain; collaborative culture; team-building; pharmaceutical industry. Reference to this paper should be made as follows: Samuel, K.E. and Spalanzani, A. (2009) ‘Developing collaborative competencies within supply chains’, Int. J. Information Technology and Management, Vol. 8, No. 2, pp.146–160. Biographical notes: Karine Evrard Samuel is an Assistant Professor in Supply Chain Management at Pierre Mendès-France University in Grenoble, France. She is the Co-director of the ‘Supply Chain Management and Information Systems’ Master’s degree programme. She has authored several papers in the field of strategic management and her research interests focus on interorganisational relationships and the correlation between supply chains performance and coordination efforts. Alain Spalanzani is a Professor and first Vice President of Pierre Mendès-France University in Grenoble, France. He is in charge of the Master’s degree Programme in ‘Supply Chain Management and Information Systems’ and for the Information Systems Degree in Higher Research. He has co-authored a book on logistics and supply chain management and is the author of several papers in major journals. His areas of interest include operations management, knowledge management and interorganisational collaboration within networks.


Developing collaborative competencies within supply chains

1

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Introduction

A supply chain can be defined as a partnership of organisations sharing a common goal of delivering a set of goods or services to an end customer. To achieve that goal, a coordinated effort is necessary between the organisations belonging to the supply chain. Collaboration thus concerns many processes at different levels (strategic, tactical or operational) and, of course, those people acting within these processes. The use of Information Technology (IT) can be seen as a basis for achieving collaborative relationships, while supply chains evolve in a context of ever changing markets and an increasingly global manufacturing environment. In many cases, the ability to compete is directly linked to the ability to collaborate with other companies. This increased need for collaboration within supply chains has received a considerable amount of interest from both the academic and industrial communities over the past years (Christopher, 1998; Gattorna and Walters, 1996; Hines, 1994; Lamming, 1993). The establishment of long-term partnerships with suppliers and distributors is now seen as a way to develop even more efficient and responsive supply chains in order to deliver exceptional value to customers. However, despite more and more innovative IT systems, collaboration is tricky to achieve, and there are several current issues in supply chain management behind the trend towards more collaboration. The amplification of demand uncertainty up the supply chain, known as the ‘bullwhip effect’, is perhaps the most frequent consequence of an absence of collaboration among the supply chain’s members. Orders to suppliers progressively upstream from the end-customer and are inflated to buffer uncertainty and prevent stockouts, resulting in excess inventories and inefficiencies in the supply chain. A second issue is linked to the absence of reliable demand information. In this situation, vendors have to guess customer needs and push the products, which can create waste. When demand forecasts and orders are not developed jointly by the partners, they often are distorted. It is therefore crucial that partners agree to share information. Collaboration can reduce waste in the supply chain, while simultaneously increasing market responsiveness, customer satisfaction, and competitiveness among all members of the partnership. Collaborative relationships can be analysed at two different levels: internal, external or interorganisational collaboration. Internal collaboration can be seen as a necessary basis prior to building interorganisational cooperation. Enterprise Resource Planning (ERP) systems have been used as a technology enabler to increase operational efficiencies within the four walls of the firm. Additional complementary IT systems such as Business Intelligence (BI), Advance Planning and Scheduling (APS) and technologies like Electronic Data Interchange (EDI) or Web-EDI, are now superimposed onto ERP systems to provide extra business support. A better diffusion of information enables different internal departments like the supply chain, operations and sales and marketing, to work together by sharing information relative to demand creation and forecasting. The ability to share information and to work together with a shared view of the final consumer’s needs is becoming, for most firms, a key competency and therefore effective interorganisational collaboration cannot occur without an internal corporate culture that fosters strong internal collaboration between all departments. In order to go further to improve supply chain performance, this culture of collaboration should also exist between companies accustomed to working together in an antagonistic or aggressive way. In fact, new approaches have been developed in order to

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K.E. Samuel and A. Spalanzani

improve external collaboration. The Collaborative Planning, Forecasting and Replenishment (CPFR)® is one of these approaches that proves that there has been a fundamental change in the way companies interact with trading partners. The CPFR is a business process wherein trading partners use technology and a standard set of business processes for collaboration on forecasts and plans for replenishing product. Its focus is on how organisations can work together to make the supply chain processes better and more efficient by creating a joint ‘go to market’ strategy. CPFR is defined as those collaborative business practices that enable trading partners to have visibility into each other’s critical demand, order forecasts and promotional forecasts through a systematic process of shared brand and category plans, exception identification and resolution. The objective of CPFR is to improve efficiency across the extended supply chain, thereby reducing inventories, improving service levels and increasing sales. The purpose of this paper is to present a new approach to interenterprise collaboration through the concept of collaborative competencies. Adversarial relationships have been recognised as dysfunctional since far too often they lead to mistrust, perpetual disagreements and unreasonable demands. Through two different case studies conducted, we have observed a strategic shift towards more collaborative relationships, and the analysis of collaboration design and establishment within integrated supply chains will allow us to show how supply chains transform themselves by improving internal and external collaboration. This paper is divided into three parts. Firstly, we present a brief review of the literature on the concept of collaboration among supply chain partners. Secondly, part of this paper presents two case studies describing the collaborative project implementation process. Case A analyses an example of external collaboration and Case B is rather concentrated on internal collaboration efforts. Finally, the third part of this paper proposes a new approach to interorganisational collaboration through the concept of collaborative competencies. We propose here to revisit the notion of collaboration and to extend the reflection on this topic to researchers in other disciplines. In addition, directions for future research will be presented as a conclusion.

2

The concept of collaboration within supply chains

Collaboration has recently received greater attention in supply chain literature (Barrat, 2004; Barrat and Oliveira, 2001; Becker et al., 2004; Bowersox et al., 2003; Holweg et al., 2005; Mc Carthy and Golicic, 2002; Simatupang and Sridharan, 2005b), but has already been largely explored in strategic management literature, particularly through the concepts of interorganisational relationships and alliances (Bowersox, 1990; Kumar, 1996; Moss Kanter, 1994; Trienekens and Beulens, 2001). Collaboration within supply chains implies that the different actors involved in the flow of products and information from raw materials to the final consumer (integrated supply chain) coordinate their activities in order to fulfil customer needs. This coordination implies the sharing of information and decisions that determine the intensity of the collaboration. Thus, the intensity level can be determined through two perspectives: the complexity and confidentiality of information shared between trading partners, and the decision-making level. The more the information shared is complex and confidential at a strategic decision level, the more intense collaboration is. The nature of exchanged information can be as

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diversified as planning (forecasting of customer demand and of materials demand), production capacity and scheduling or performance measurement information (Anthony, 2000; Min et al., 2005). A recent survey conducted by Computer Sciences Corp. (CSC) and the Supply Chain Management Review across 18 industries shows that more and more companies are moving beyond the early stages of internal excellence and are beginning to collaborate effectively with their supply chain partners. Currently, only a few leaders have reached the higher stages of full network connectivity. The supply chain can be seen as a system interconnecting different businesses that aim to efficiently and effectively provide raw materials and components to supply chain partners and finished goods to consumers in a reliable and cost-effective manner. This system needs to be coordinated in order to create more value and to increase competitive advantage. The flow of information between the supply chain members can be seen as strategic, and is supported by several IT systems that we briefly describe in Table 1. These IT systems can be considered as drivers for collaborative benefits among supply chain activities. The literature on supply chain collaboration identifies several activities that encompass supply chain design (including procurement, transportation and distribution), collaborative manufacturing (including inventory management, product design and product development, manufacturing planning) and integrated fulfilment (including order processing, sales, customer service and demand management) (Anderson and Lee, 1999, Ellram, 1995; Horvath, 2001; Simatupang and Sridharan, 2005a). We classify the IT systems in three categories that are IS for decision-making, IS for managing and IS for interfacing companies within the supply chain. Table 1

Panorama of the major IT systems within the supply chain

Supply chain activities

IS for decisionmaking

Procurement Inventory management

Data mining

Manufacturing

IS for managing the supply chain

IS for interfacing companies

ERP (MRPII)

e-procurement

ERP (ATP), WMS

VMI, CMI, CRP

ERP (CTP), MES

Order processing

ERP (ATO), AOM

Distribution

ERP, DRP, TMS, WMS

CPFR, RMR

Sales

Data mining

ERP, TMS

CPFR, e-commerce

Demand planning

APS

ERP (ATO)

CPFR

Customer service

Data mining, SCEM

SCEM

e-billing

The IT systems of the third category can be considered as drivers for collaboration among supply chain activities because they allow firms to get connected through the exchange of information. The review of the literature equally reveals that other elements play an influential role in company decisions to collaborate, and these need to be taken into account by the partners if they want to increase their chances for success. In fact, firms enter into collaborative arrangements with suppliers or retailers in order to share risks and rewards. The objective of collaboration is to secure a higher performance than would be achieved

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by operating individually (Lambert et al., 1999). Interorganisational coordination mechanisms are recognised in the literature as fundamental, key dimensions characterising supply chain management (Christopher, 1998; Lee and Ng, 1997; Stock et al., 1998). CPFR can be considered as a new step in the development of interorganisational relationships because it is a way to exchange information between manufacturers and distributors at a strategic decision level. This process developed in year 2000 by the Voluntary Interindustry Commerce Standards (VICS) committee is an interorganisational business process that encompass nine steps formalised in a guideline that helps to its implementation within firms (VICS, 2001) (see Figure 1). Figure 1

The nine steps of the CPFR process

CPFR process requires trading partners to have a synchronous collaborative vision, the required technology, and the resources to implement and execute successfully (Ireland and Bruce, 2000). According to the VICS committee, the expected outcomes include improved efficiencies, increased sales, reduced assets and working capital, reduced inventory and the potential for reducing a company’s infrastructure. CPFR has to be seen as a tool that will facilitate collaborative forecasting between supply chain partners. Nevertheless, it will not be successfully implemented if the internal forecasting processes have not been established and if the relationships among partners are antagonistic or self-serving. The actual implementation of a CPFR program implies that partnering companies are to share electronic business information. At the moment, it seems that one of the greatest obstacles to achieving an efficient collaborative supply chain has been the lack of accurate business data. Costly supply chain bottlenecks occur when trading partners cannot exchange information quickly and accurately (Andraski and Di Yeso, 2005). Even if companies recognise the cost of inaccurate data, they still use manual means of managing and updating trading information. A recent Morgan Stanley survey estimates than 30 to 60% of information at the retail level is inaccurate, when US firms threw away $130 billion on unnecessary software and other technology over the past two years. To date, the literature on collaboration has not focused sufficiently on the importance of technology investment bent on improving the efficient exchange of accurate and up-to-date information. In fact, the lack of coordination occurs when decision-makers have incomplete or false information (Sahin and Robinson, 2002). It seems that the first step towards developing collaborative relationships within a supply chain is to organise the flow of information in order to instantaneously access product location, specifications, price and availability, and to ensure a high quality of data. The two case studies which will be presented in the following section aims to show how companies adjust their information flows in order to build efficient CPFR relationships.


3

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Research methodology

There remains much work to do in understanding how a CPFR programme may lead to creating value within supply chains. Answering this ‘how to’ question has driven us to design our qualitative research so as to optimally conduct our exploratory process. According to Yin, a multiple case study approach is particularly appropriate to exploring a contemporary phenomenon within its real-life context, particularly when there is no control over the behavioural events (Yin, 1994). The supply chain relationship context seems especially well-adapted to a multiple-case design since it is more robust for result replication. The unit of analysis is the organisation. The choice of the research sample is based on theoretical sampling (not random) to pursue the research objective. We selected and analysed two firms in the same industry – the pharmaceutical sector – in order to explore similarities and differences in their decision-making mechanisms and implementation steps in the CPFR process. Both firms have a central position in the supply network and operate at a worldwide level. The data was collected throughout 2005 in different ways, including company visits, recorded interviews, company documents and public presentations in order to ensure research reliability (triangulation). While conducting the interviews, we collected the opinions of a variety of actors to avoid data distortion. Each interview lasted at least 3 hrs, and it was often necessary to meet the same person several times in order to obtain complete information. Data analysis will be presented in two ways: firstly, we present a within-case analysis in order to explain the stakes in CPFR implementation for each firm; finally, a cross-case analysis will allow us to compare the coordination mechanisms through the CPFR process in both cases.

4

Analysis of case studies and results

4.1 Case A The first case study presents the development of a CPFR project between a French laboratory and its distributors, mainly represented by the European subsidiaries. This case can be analysed as external collaboration, in the sense that subsidiaries are financially independent from the parent firm and can be considered as the customers. The company has three manufacturing plants in France and a logistics hub that dispatches the products to the subsidiaries. Each subsidiary has its own distribution centre (see Figure 2). Before CPFR was implemented, the firm had to deal with a number of problems: a low rate of product rotation, a high failure rate, and a risk of inventory obsolescence. Supply chain bottlenecks frequently occurred simply because the different partners in the chain could not exchange information rapidly and accurately. The information systems were unable to communicate with each other, and the subsidiaries did not cooperate in order to organise the replenishment. There was a high need for improving customer service and for better controlling the demand. Inventories and manufacturing planning equally were in need of greater optimisation. These four points constituted the primary objectives of the project which was called ‘Kheops’.

152 Figure 2

K.E. Samuel and A. Spalanzani Description of the information flow prior to CPFR implementation (Case A) (see online version for colours)

To begin with, an evaluation of the current IT systems used to elaborate the forecasts was carried out. Forecasts were made once a month by the subsidiaries and information was transmitted to the parent company’s ERP in order to be processed in the APS system. It quickly became clear that there was in fact no collaboration between those who elaborated the forecasts within the subsidiaries and those who processed the data from the parent company’s APS. Following that first step, the need for greater collaboration at different levels of the supply chain appeared as a necessity. On the basis of existing information systems, the company developed a collaborative plan through the implementation of three different processes: forecasting, Distribution Requirement Planning (DRP) and Available To Promise (ATP), this latter being a module of ERP (Figure 3). The new system uses web technology to develop a continuous feedback that checks if the information flow matches the product flow. The monthly forecasts are transformed into daily forecasts which are automatically transmitted to the DRP system that elaborates a three month supply plan. This plan is communicated weekly to the ATP system which validates the information or replaces the forecasts according to plant capacity. Figure 3

The processes of the collaboration plan (Case A) (see online version for colours)

The Kheops project took two years to be implemented in all of the company’s subsidiaries. It was very difficult to drive change within the subsidiaries, particularly because they had to reengineer the entire forecasting process. The marketing department of the subsidiaries had to get involved in the forecasting design process by entering the data and analysing the sales reviews. We were able to observe an internal cultural problem between two departments of the company which were not used to working together (marketing and logistics). The communication problems were also tough to


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solve, since from the project’s outset, the daily forecasts were permanently inspected by the parent company in order to understand the variations. The sales departments of the subsidiaries were not accustomed of being controlled and refused to play the game once the project had begun. A ‘forecasting culture’ in the subsidiaries had to be developed in order to achieve the project objectives. Moreover, the benefits of the project were greatly shared both by the parent firm and the subsidiaries as shown in Table 2. Table 2

The results of the CPFR programme (Case A)

Benefits for the subsidiaries

Benefits for the parent company

Reduced levels of inventories

Improved delivery times

Improved communication between the parent company and its subsidiaries

Lower rates of disruptions

Better reporting on inventory levels and on delivery times

Optimisation and stabilisation of production plans

Enhanced use of production capacities

Possibility of special events simulation (unexpected order)

Better communication between the subsidiaries (delivery confirmations, etc.)

The CPFR program implemented in this particular company improved both planning and forecasting, and the exchange of information radically transformed its internal culture. The project allowed for the implementation of a new information system that enabled the subsidiaries to be replenished automatically on a daily basis. CPFR holds enormous global potential as a process that drives and commits trading partners towards a closer collaboration. That process leads to redesigning the structure and generates organisational density through increased trust between partners and through a decrease of uncertainty thanks to better planning and forecasting; for example, reduction of the ‘bullwhip effect’ (Lee et al., 1997). In the case studied here, CPFR is a decentralised system but all of the system parameters are centrally set by the parent firm. The subsidiaries elaborate the forecasts and deem themselves to be managing the whole system, while in fact the major decisions belong to the parent company. The partners were the authors of their own balanced system, therefore dramatically improving collaboration across the network. The most important thing to be observed in this case study is that their customer approach was significantly altered after project implementation. The parent company transformed its organisation from a supplier-oriented supply chain into a customeroriented supply chain by including the subsidiaries and their forecasts. Collaboration promoted these changes in the processes (from an organisational point of view) and contributed to a change in mentality (from an individual point of view).

4.2 Case B As we know, the second case study also is taken from the pharmaceutical industry. This particular French laboratory produces several products such as drugs and soft medicines that can be bought in over the counter in drugstores. The market is increasingly complex due to French regulations which significantly restrict the supply chain and push for greater inventory needs and cost reduction. To pursue the growth objectives, it is necessary to enlarge the range of products and to sell to developing markets. The supply chain has to become more agile in order to better respond to

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customer needs. The decision to enhance collaborative relationships was made in 2004, and the project began when the company chose to implement an APS system to improve its internal forecasting process and to better control its inventory levels. Up until then, the different manufacturing sites and subsidiaries did not exchange any information. Each site went about its own manufacturing and selling processes, using inventories as buffers for possible market variations. The forecasting process was conducted by the different subsidiaries that gave information on inventory levels, orders and forecasts to the manufacturing plants that produced and delivered the products. The aim of this project was to improve collaboration between the distributors (located on different markets around the world) and the manufacturing plants. The project was conceived to lead to a common management of sales forecasts, inventories, production and of the plants’ distribution capacities. To target that goal, an inventory policy was developed in the spirit of a level agreement. This means that the information exchanged was structured around the complex network of distributors. Plants received the forecasts elaborated by the different sales departments, but before launching the production, manufacturing plants had to agree or disagree with the forecasts. If they agreed, a delivery agreement would be sent and delivery was carried out as before. If they disagreed, discussion would ensue in order to find a compromise on the quantities to be delivered. The same process was implemented for the different sites’ inventory replenishment (see Figure 4). Figure 4

The collaborative project (Case B) (see online version for colours)

In this case, collaboration between markets and plants are effective through a collaborative platform that allows for information exchange in both synchronous and asynchronous ways. Virtual meetings are organised monthly with the distributors who are located in many different countries. One coordinator is in charge of the meeting preparation so that decisions can be made rapidly and with all the necessary elements. Forecasts are elaborated for a three month period and information is transmitted through the platform with web technology (webEx). The distributors and the plants can then work together and exchange data directly in real time through the platform, thereby replacing e-mail exchanges and reducing the risk of errors.


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The collaborative platform and the netmeeting tools (LiveMeeting + SharePoint Services) allow for better use of the APS system, while the forecasting accuracy was quickly improved. The chief executive of the distribution subsidiary is in charge of the forecasts, which must reflect coherency with the inventory policy set by the supply chain department. It seems worthy to note that collaboration is relevant above and beyond the APS system itself: it also ensures greater supply chain efficiency. This case study therefore reveals that the capability of implementing and using information systems is crucial to the positive realisation of the project, furthering even more the initial goal of enhanced collaboration.

4.3 Cross-case analysis Both case studies inquired into the nature of a collaborative project in two different companies belonging to the same industry. In Case A, collaboration was rather external between parent firm and subsidiaries (which in fact are both the customers and distributors). In Case B, we could clearly observe the first step of a collaboration project consisting in developing internal collaboration prior to implementation, and in a second step, in developing the same communication tools with trading partners (suppliers). We were able to notice that the projects developed in those companies allowed them to increase their supply chain efficiency, whereas our results show that the approaches developed for interfirm collaboration did not follow the different steps of the CPFR process (as exposed in Figure 1). In fact, the planning, forecasting, and replenishment processes were implemented in a collaborative way, and yet it seems that the information systems implemented through the different projects were more important to increase collaboration than the process itself. Hence, it becomes clear that a necessary first step in a CPFR programme is making Information and Communication Technologies (ICT) available so as to allow for information exchange. However, in both cases, the collaboration projects changed the internal culture by bringing partners together through new information sharing practices. In Case A, the most important issue to observe is that the CPFR project altered the informationexchanging processes and led to a reorganisation of the supply chain in favour of a more customer-oriented one. The role of asynchronous information exchange is particularly significant in Case B, because it contributed to improving collaboration within teams and to managing the forecasts, the inventories, and the production and distribution capacities in a new, collaborative way. The collaborative platform allows the partners to exchange information and to work together in real time thanks to the APS system, and ensures that decisions are made on a consensus basis through virtual meetings.

5

Conclusions

The cases we have studied explore how improving collaborative relationships may contribute to the realisation of benefits throughout the value chain. This is done by creating truly productive and profitable partnerships. Companies engaged in such a process share significant savings, due to the reduction in inventory levels and the elimination of out-of-stock situations. Less frequent business trips (up to 60% fewer) were necessary between the parent firm and the subsidiaries, which was also a factor for savings. In both cases, we may note that collaboration mechanisms should be

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well-controlled within the company before enlarging those same collaboration tools upstream and downstream. Information systems like ERP and APS enable firms to optimise the planning of material flows while continuing to work under the normal constraints, but these same systems are not effective for coordinating information exchange. These systems need to be complemented with a process that creates and fosters more dialogue between the various partners along the supply chain. This process improves planning, thanks to a better knowledge of the supply chain’s execution processes. Through a collaborative platform, suppliers can be integrated to elaborate the sourcing requirement planning and distributors are then able to draw up the manufacturing and distribution plans. The forecasts are usually given to the various parties by the subsidiaries (usually sales departments), but they are subject to discussion and control by the supply chain department. We observe here that the information systems developed within companies are not actually collaborative tools that permit interaction and exchange of information. In order to improve collaborative ways of managing the supply chain, an interactive process with suppliers and distributors has to be implemented. A collaborative platform seems to be the right answer, because it grants access to inter operable files which can be directly interfaced without requiring multiple keyboardings. Collaboration within a supply chain also transforms individual behaviours towards more collaborative ones, and it therefore possible to discern an interorganisational learning process occurring between the trading partners (Holmqvist, 2003; Scott, 2000). Sharing confidential information contributes to a trust-building process that transforms the supply chain from an internally focused supply chain to a customer-driven network. Trading partners, by the acceptance and the appropriation of a global system, share business information and develop a common language, aided by standardised electronic information (Lee et al., 2007). Collaboration becomes a real source of competitive advantage, critical to successful supply chain strategies. The purpose behind any collaborative activity in a supply chain is to leverage each trading partner’s competencies in a manner which would be beneficial to the entire supply chain. These competencies, which we call collaborative competencies, are essential to the relationship that unleashes the value-creating potential of the integrated supply chain, and can be considered as a specific asset. In both case studies, we can witness a decrease in transaction costs between trading partners through the dismantling of their mutually opportunistic behaviours (Williamson, 1975, 1985). In conclusion, we put forth here a theoretical framework which goes towards explaining the design and establishment of interorganisational relationships in an integrated supply chain (Figure 5). This framework is built on the basis of a theoretical analysis (Spalanzani, 2003; Spalanzani and Ballaz, 2002). Our model emphasises three dimensions in the management of integrated supply chains that will lead to the development of collaborative competencies. There is a combination of an organisational dimension, a technological dimension and an individual, human-centred dimension. Firstly, the organisational dimension implies managing coordination mechanisms through collaborative platforms which enable supply chain-wide solutions like CPFR programmes. The collaboration process should lead organisations to overcome organisational boundaries and constraints in order to jointly manage business processes and key supply chain activities, from the delivery of raw materials to delivering final products to end customers.


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The technological dimension involves some projects based on ICT that will enable greater information flow to all partners in the supply chain, and should ensure that the right information is shared across company boundaries. Developing ICT is a necessary step before going further in the improvement of collaborative relationships. Figure 5

Proposed framework for integrated supply chain collaboration (see online version for colours)

At last, the human dimension is the key element to making the process work. A collaborative interaction between supply chain partners is impossible without trust and balanced relationships. Trust is the glue that holds the extended enterprise together, but trust is extremely fragile, especially in the case of relationships between buyers and sellers. Supply chain partners usually do not share the same objectives and, very often, one partner has more power than the other. Power is identified as playing an influential role in company decision to collaborate and in the way they share risks and profits along the supply chain. Nevertheless, power can be considered as one of the greatest deterrents to trust. This is why this dimension is directly linked to individuals. The existence of trusting relationships between partners will help manage power and dependency relationships. Our model aims to show that these three dimensions interact with each other and need the existence of competencies that determine the partners’ collaborative capabilities. People remain at the core of supply chains. Increasing collaborative competencies will enable participation throughout the supply chain. These competencies are organisational, that is, developed by an organisation, as well as individual, that is, credited to one person in particular. Some of these competencies are teachable (or learnable) and others are linked to the individual him or herself. Further work is required in order to define these competencies, which a supply chain manager working in an extended enterprise should possess, and therefore naturally foster collaboration. One of our findings is that companies can collaborate closely through virtual and asynchronous communication systems, which is a novel concept in an environment, where trust is a critical element affecting the degree of the collaboration’s intensity. In fact, technology can be used to lessen the differences between trading partners and can help to share information and processes, for example, thanks to a collaborative platform. ICT can contribute to educating and to transferring knowledge across the supply chain, as well as to facilitating the creation of collaborative competencies.

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The concept of collaborative competencies developed in this paper offers a broad scope for further testing and development at two different levels: organisational and individual. However, there are a number of limitations to our inquiry. Our case studies are limited to a small sample of companies belonging only to one industrial sector. It therefore becomes difficult to extend our conclusions to other areas of activity. In addition, we feel that the concept of collaborative competencies requires further evaluation through a wider sample of companies and industries via case-based and/or survey-based research designs. This would then open up this concept towards practical implementation as a managerial tool, which we sense could prove useful to a broad range of industries.

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Available at: www.vics.org. Global Survey of Supply Chain Progress (2007).


Cost benefit sharing-based coordination in logistics networks Iwo V. Riha* Fraunhofer Institute of Material Flow and Logistics, Joseph-von-Fraunhofer-Street 2-4, Dortmund 44227, Germany E-mail: [email protected] *Corresponding author

Bernd Radermacher University of Dortmund, Dortmund 44221, Germany E-mail: [email protected] Abstract: We present a comprehensive approach for an incentive system in logistics networks based on network-wide evaluation and reallocation of costs and benefits. We show that alternative allocations of resources based on sharing costs and benefits can give an incentive to the network-partners: Cost Benefit Sharing (CBS). It enables activity dependent reallocation of individual effects that reflect the costs and benefits of each party and systematically considers qualitative factors. A case study of a sourcing process concludes this paper. Keywords: supply chain collaboration; profit sharing; network management; incentives. Reference to this paper should be made as follows: Riha, I.V. and Radermacher, B. (2009) ‘Cost benefit sharing-based coordination in logistics networks’, Int. J. Information Technology and Management, Vol. 8, No. 2, pp.161–177. Biographical notes: Iwo V. Riha holds a Diploma in Logistics from the University of Dortmund and a Master’s in Industrial Engineering from the Georgia Institute of Technology, Atlanta, USA. He has been working at the Fraunhofer Institute since 2003. His main areas of expertise are material flow planning, process redesign, inventory management and operations research. Among his main research interests are process optimisation, collaboration management and inventory management. Bernd Radermacher is a Research Associate at the University of Dortmund, Chair of Factory Organisation. He holds a Diploma degree in Business Administration from the University of Dortmund. He has been a Visiting Scholar at the University of California and Harvard University.


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I.V. Riha and B. Radermacher

Introduction

A wind of change blows through the automotive industry. Original Equipment Manufacturers (OEMs) focus their effort on assembly and marketing of the final product. Suppliers take the responsibility for research and development. Already, major 1st tier suppliers create a large share of the value in the automotive supply chain. Studies suggest that this shift is just beginning. In the future, suppliers will create even more components, modules and designs (FAST, 2004). The OEMs are encouraging this shift: they procure components at a lower cost due to lower wages and economies of scale. Both reduce the OEMs’ financial risks. The concentration on core-competencies seem beneficial to both the OEMs and the suppliers (Kulmala, 2004). As a result of shifting value creation downstream, the OEM increasingly depends on the performance of the supply chain. The dependency dramatically reduces the OEMs’ power to control the network according to their own goals (Figure 1). Figure 1

Today’s and tomorrow’s state of automotive networks (see online version for colours)

The methods used by OEMs to control the supply chain have not kept pace with the erosion of their bargaining power. Here is a typical example: the OEM initiates a project in the supply chain that improves the availability of information by introducing new software. The suppliers and logistics service providers have to invest into new hard ware and software and educate the staff. All benefits affect the OEM only. Because the companies in the supply chain do not see their individual benefit, they will resist the project. In this situation, many OEMs will resort to outdated methods to align the companies towards their strategic and economic goals: pressure, mandatory one-sided cost-reductions, threats of changing to a different supplier (Rinehart et al., 2004). Unfortunately, this development is not limited to the automotive industry but is present in many industries (Jordan and Lowe, 2004). These instruments still work today, but in the future win-win-situations are required to generate greater customer value (Baumgarten and Thomas, 2002). Therefore, new methods that enable and support cooperative coordination in networks have to be developed (Seuring, 2006).

CBS-based coordination in logistics networks

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Literature review

One of the most crucial aspects of managing networks in the future will be to subordinate individual goals for the greater benefit of the network (Christopher, 1998). Supply chains may achieve this goal by building the relationship between the companies on trust and transparency (Akkermans et al., 2003 and the literature cited there). A recent study on Belgian logistics service providers revealed: “It is hard for the partners to determine the benefits or operational savings due to horizontal cooperation beforehand.” (Cruijssen et al., 2007)

It would seem that many researchers address this problem in their work. Instead, literature reviews discover a wide gap in research concerning the area of benefit sharing (Cruijssen et al., 2007; Harland et al., 2003), even though “[…] a fair allocation of benefits to all the partners is essential for a successful cooperation.” (Cruijssen et al., 2007)

Modifying the allocation of cost and benefits is mostly a domain of game-theoretic approaches (Tijs and Driessen, 1986). Most publications analyse the impact of large-scale public infrastructure-projects like reservoirs (Aretino et al., 2001; Ransmeier, 1942). As for investments in conservation-projects, Lu describes a way of distributing one period investment in networks (Lu, 2001). This approach concentrates on the quantitative benefits of cooperation but does not consider the qualitative aspects. Other authors scrutinise cooperative and non-cooperative business relations in a principal/agent-setting and describe management structures that support cooperative behaviour (Kaluza et al., 2003). More recent publications analyse benefit-sharing in conservation projects (Breton et al., 2006), biology (Perru, 2006) and among power utilities (Jia and Yokohama, 2003). A combination of experimental and graph-theoretic approaches identify successful cooperation strategies (Cassar, 2007). The domain of cost-benefit-analysis is concerned with comparing the costs and benefits of alternative investment decisions. Investments are evaluated by analysing the allocation of resources (Campbell and Brown, 2003). The individual decision-maker can then evaluate the result with the investment relative to the result without. These decisions may influence the network’s objectives (Petersen, 1989). In many cases however, individual objectives contradict or disagree with those of the majority, the network (Laux and Liebermann, 1993). Incentives may resolve these conflicting interests. The incentives given by the CBS-approach combine both the evaluation of costs and benefits by modifying the allocation in order to achieve a win-win-situation (Keller et al., 2006). It is necessary to evaluate costs and benefits within the network before they are reallocated. The evaluation of costs by accounting methods is a mature scientific area, and costs are well defined (Weber, 2002; Young, 1994). A significant contribution is the total costs concept (Stock and Lambert, 2001). This approach applies systems thinking towards cost accounting in networks. Each cost therefore directly or indirectly affects other costs. For example, reducing transportation costs by shipping full truckloads may increase inventory costs or even offset the savings if all other factors remain constant. The total cost must be calculated in order to decide whether a measure is economical. Authors frequently describe benefits by the notion of utility (Varian, 2003). In value-based approaches, such as the shareholder value approach or the Economic

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Value Added-method (EVA) (Urban and Seiter, 2005), benefits are the qualitative counterpart to costs. Benefits are usually evaluated financially. In networks, the widespread use of products creates a new type of benefit, the ‘network effect’. This effect describes how the extensive use of the same product can create larger positive effects for certain players in the network (Hardenacke, 2005; Wald, 2003). Until now, the literatures known to the authors do not contain practically applicable models that explain benefit sharing. The research project ‘NutzLog’ (Wildemann, 2005) intents to develop cost-benefit-valuation models for networks, but substantial results have not yet been published. However, there is demand for such models from industry (FAST, 2004; Riha and Hirthammer, 2005; Riha and Weidt, 2005) and the scientific community (Baumgarten and Thomas, 2002; Cruijssen, 2007; Straube et al., 2005).

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Research roadmap

Research in this project is divided into four major steps shown in Figure 2. Research has begun in late 2004, by defining the initial concept of Cost Benefit Sharing (CBS). This step focused on establishing a nomenclature, defining goals and identifying benefits of the concept as well as possible obstacles for the implementation. Step two has been the development of the general framework for CBS, including the structural level and the process level. This framework shows how CBS can be embedded in networks and which processes are required to apply CBS. After determining the framework for CBS (Riha and Hirthammer, 2005), work has begun on detailing the structures and processes. The main tasks in this step are to discuss how the partners achieve transparency about costs and benefits within the network. Furthermore, strategies for the reallocation of costs and benefits in the network are invented. Application and feedback has been the final stage of research. Figure 2

Research roadmap (see online version for colours)


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Paper structure and objectives

Explaining the general idea of CBS and definitions are the basis for any further development. It is topic of the next chapter. Within the CBS framework (Riha and Hirthammer, 2005) this paper focuses only on processes, which calculate and reallocate of effects. The final chapter shows a case study from the automotive-industry. Taken from an anonymised case study, it demonstrates how CBS is applied in a sourcing-process. The main objectives of this paper are: •

Define the most relevant terms in CBS. The aim is to establish a common language for CBS because literature on the topic is scarce and originates in different research areas like institutional economics, controlling and sociology.

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Explain how to derive quantitative and qualitative effects from the underlying process modifications. CBS explains how changes in the process affect each partner in the supply chain individually as well as the supply chain as a whole. Effects can be measured financially as well as by evaluating qualitative impacts. Both types of effects are measured and displayed for the decision makers.

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Give the first ideas how to share costs and benefits. If costs and benefits in a network are not well balanced, some partners do not benefit from the supply chain.

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Definitions and clarification of terms

The authors define CBS as “a comprehensive and system oriented method to motivate companies to participate in supply chain activities although they do not benefit from these activities directly”. Motivation can be financial incentives that are derived from the system effect of cooperating in networks. The CBS-approach and its implementation require definitions of the following terms: •

Basic process: the basic process is the business-process currently used by the companies. A process is an ordered description of the activities that the partners in the supply chain execute. Like every process, the basic process consists of process-elements. They define the activities for each partner in the supply chain. These elements are the most detailed level of description for a process (Kuhn, 1995).

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Cooperative project: a cooperative project (coproject) is a joint project of the supply chain-partners to improve the performance or lower costs within the supply chain by changing the allocation of resources within the supply chain. The key factor for success is to ensure the participation of all relevant partners.

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Process modifications: process modifications are all changes made to the basic process. These modifications can either be changing the content of a process-element, adding or removing process elements. Examples for modifications are shortening the process, upgrading technology or changing the competences and tasks of the participating companies.

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Modified process: the modified process is the goal of the cooperative project. It is defined the basic process plus the process modifications.

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Effects: effects result from applying the process modifications to the basic process. They are evaluated quantitatively as well as qualitatively and have a positive or negative impact on the costs and performance of the supply chain. Effects occur on a company-based, individual level for each partner in the supply chain and as a supply chain-wide result of all modifications taken together.

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Description of the CBS model

Essential to the application of CBS is the concept of Supply Chain Management (SCM). The key concepts of this management philosophy are (Göpfert, 2002; Mentzer, 2001): •

using a systems approach to viewing the supply chain as a whole by taking an interorganisational approach towards managing the flows of goods, information and cash across several stages of production

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strategic orientation towards synchronising and converging intrafirm and interfirm operations and adjusting the strategic capabilities of the companies to best serve the customer

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understand the activities within the supply chain as an output centred process that needs to be aligned internally to achieve best performance at lowest cost.

The widespread conviction in academia is that integrated behaviour, mutual sharing of information, risk and reward are key concepts of a successful SCM (among other Christopher, 1998; Cooper et al., 1997; Hakansson and Lind, 2004; Ihde, 1997). Improving the processes locally will lead to suboptimal results for the entire supply chain. Using fewer resources to generate equal amounts of customer-satisfaction is the final goal of SCM. Discussions with industry-partners and practical experience show that companies implement SCM to: •

Improve the information-structure: better quality and more information relevant to the processes need support by a fluent exchange of information along the supply chain. Improving the information structure enhances planning and controlling and reduces the costs of gathering information.

•

Reduce direct labour-expenditures: all means to reduce the labour required to execute the processes. The reduction of labour-expenditures can be measured as time-savings per process-element.

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Improve process-quality: positive effects of this category ensure a higher process-quality and smoother operations. Typical examples are: reduced quality-costs and rework that can be expressed in time savings or reductions of the production costs.

SCM is the prerequisite for implementing CBS After successfully laying the ground for CBS, the following part describes the six-step approach for CBS shown in Figure 3. The first step for CBS is to understand, visualise and validate the currently used processes that create value in the supply chain. All partners in the supply chain have to agree upon the basic process. In workshops, the partners discuss all relevant details of the process. In the workshop, the moderator has to derive and visualise the input data, resources and processes as well as output of the process. The process ownership is used


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to structure the process along a time-axis. This paper uses the process chain model as a method to describe all processes (Kuhn, 1995). This intuitive method to describe logistics processes disassembles processes into the following entities: the process-elements, connectors and properties of logistics processes, such as different types of resources. The properties of the process-elements are tailor-made to focus on the special requirements of logistics processes, such as the participation of many different parties within one process and predefined logistics resources. Figure 4 shows the properties of the process chain model (Kuhn, 1995). Figure 3

Six-step cost-benefit-sharing approach (see online version for colours)

Figure 4

Properties of logistics processes (see online version for colours)

Source: Kuhn (1995).

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The process chain model describes processes by four categories: control, processes, structure and resources. The properties are a library, which describes the parameters that can be changed to improve the process. In step two, the partners jointly modify the existing process. The modified process achieves better operational performance, shorter cycle time, lower process costs, more stable process results or a similarly improved result of the process. All modifications aim at improving operational performance while lowering or keeping operating costs constant. Three operators for the modification are available: adding, removing or changing an individual process element or its properties. The properties of the process chain identify possible process-modifications. For example, a transport operation may be done with a different type of transport. After the partners have agreed upon the modifications, the modified process is visualised. The process-modifications defined earlier are applied to the basic process and create the modified process. Evaluating the modifications quantitatively and qualitatively leads calculates the effects. Process elements that remain unchanged from the basic process are not evaluated because their effects in the process remain unchanged. Figure 5 shows that five dimensions are required to rate effects: category, monetary valuation, sphere of influence, periodicity and effectiveness. If to some extent an effect cannot be assigned exactly to one category we suggest the application of an allocation ratio to enable an appropriate assignment, for example the step-ladder method also used in accountancy. Figure 5

Dimensions to evaluate effects

The category of effects determines whether the effect is positive for the network or partner and hence desirable or negative and undesirable. Positive effects increase cash-flows or improve performance and quality while negative effects do not. Quantitative and qualitative effects are categorised according to the process chain method (Kuhn, 1995). This is shown in Figure 6. Quantitative effects are evaluated periodically, depending on the time they occur. Permanent and initial effects are distinguished. Incorporating the time in the consideration is recommended for projects running for more than one period. It increases transparency when the effects are assigned to the partners and the allocation is interpreted. As Figure 6 shows, quantitative effects occur mostly in the resources-category.

CBS-based coordination in logistics networks Figure 6

Categories for qualitative and quantitative effects (see online version for colours)

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For the qualitative effects, it is not necessary to differentiate between periods. They occur at all times while the project is active. It is still possible to reevaluate qualitative factors periodically. This would be part of the controlling and feedback-loops, which accompany any supply chain life cycle. Each partner in the supply chain considers qualitative factors individually but does not evaluate them in monetary terms. We propose that instead each partner uses an identical, standardised questionnaire. The questions characterising the qualitative effects of the process modifications are those given in Figure 6. Most qualitative effects occur in the categories partners and coordination. Depending on the nature of the cooperation different questions may be asked. Although qualitative data does not seem to influence rational investment decisions, its impact is generally underestimated. Consider an allocation where one participant has negative individual effects. This partner might still be willing to support the project because of significant strategic qualitative benefits, such as an improved image in public. The authors have observed this fact in many discussions with company-owners. In terms of monetary valuation, all effects that can directly be measured in financial terms are quantitative effects while all effects that are hard to measure financially are qualitative effects. In this paper, we propose not to convert qualitative effects into monetary terms. Our industrial experience shows that the conversion will cause much trouble and discussion among the partners. Instead, we propose that each partner rates the qualitative factors internally using a standardised questionnaire. The questionnaire’s results can be included in the evaluation of the effects without rating them monetarily (Hanusch, 1994). The sphere of influence determines at which partner the effect occurs. An effect may affect an individual partner only, it may only affect the network or in many cases it affects both. An individual effect will increase or decrease costs at one partner in the supply chain but will not affect another partner. On the other hand, an effect at Company A may lead to a significant reduction or increase in costs at a Company B. We call this the system effect. This effect exists only because the partners cooperate. Thus, maximising the system effect may lead to the significant reductions of cost that SCM has promised. Effects may have cascaded impacts, they may occur in second and third degrees. For example, reducing the processing-time (first degree) in turn also decreases stock levels (second degree). The total cost concept justifies these cascaded effects. A strategic project will not lead to changes in performance quickly. Time must be taken into account and effects must be discounted to make them comparable. For the evaluation, it is very important to determine the amount of periods analysed. Typically, the number of periods depends on the duration of the contract or the length of the supply chain partnership. At the end of the evaluation process effects are assigned to partners according to process-ownership. The main result of the assignment is to show how the effects are distributed throughout the network. The question is whether the project will lead to a win-win-situation for all partners. In step five, the allocation of effects is shown and interpreted for all partners. Two different views on the effects are necessary: a company-centred view (individual) and a network-centred view (network). For the individual view, the direct effects of the process modifications are totalled for each partner in the supply chain. The sum of all positive direct effects per company minus the sum of all negative direct effects per company results in the individual effect


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per company. Additionally, qualitative effects are considered at this stage. This point of view reflects the individual outlook of each partner. If the result is positive and positive effects offset the negative ones the company already has an incentive to participate in the project. This result would be the sufficient condition for the company. However, the individual perspective neglects the effect of the process modifications on the entire supply chain. In the CBS-context, it is absolutely necessary to broaden the horizon towards a network-centred perspective. The network-centred perspective totals the individual effects of all parties plus the system effect of the project and leads to the total effect. The total effect shows how much value is gained by the project overall for the network. It measures how much value the modified process creates compared to the basic process. Only the total effect should be used to decide whether to implement the project. The system effect is the benefit that the partners receive through the cooperation. It is the sum of all positive indirect effects minus all negative indirect effects. There is only one system effect for a supply chain. By distinguishing between the total, system – and the individual effects, we can show the benefit of SCM. This is the extra benefit Aristotle referred to in the Metaphysica when he stated: “The whole is more than the sum of its parts”. Some individual effects might be low positive or even negative but the implementation of process modifications is still feasible for the network because the total effect is positive. Collective rationality is prioritised before individual rationality. In order to achieve the projected outcome of the project, some partners need to invest but will gain much less than the investment. Their individual effect is negative. Unfortunately, the project looses support when this effect-allocation occurs. The idea of CBS is then to let those companies that benefit more than their own investment take over a larger share from the costs of the others. In the sixth step, the effects are reallocated if necessary. Individual partners may feel the need to be compensated for their efforts to improve overall supply chain performance because their individual effect is negative. No objective criterion states that reallocation is mandatory. After all, most networks today run without any idea of CBS. However, practice shows that in many networks do not lead to win-win-situations. If one company is extensively disadvantaged, it may try to receive compensation from the other companies in the network whose benefits are higher than their costs. This compensation may occur through direct payments or through acceptance of a larger share of their cost by other companies in the network. Today, this possibility is not available in practice because the allocation of costs and benefits is not transparent. The case study gives a reason. In the past, the power of the focal company within most networks would still have pushed the project towards implementation. But as the power of smaller network participants grows, it is more likely that companies refuse to participate in a project that provides an individual loss to them. These companies need incentive to participate other than pressure. Here, CBS offers an alternative approach.

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CBS and the reallocation of effects

Any discussion about reallocation requires a high degree of cooperative transparency. If one of the partners reaches significantly higher returns on its invested capital it is likely that other partners may consider the outcome unfair. Making costs and benefits

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transparent and communicating them allows most partners in the network to see and compare the results of the project. A ‘fair’ allocation should be the aim of any method that redistributes costs and benefits. Unfortunately, no universally valid definition of fairness is known to derive a universal distribution concept. Instead, we propose a performance-oriented approach. Applying the CBS-concept of reallocation does not change the total effect. Prorating the costs to the benefits is probably the most intuitive way of sharing costs and benefits. Each participant pays a share of costs proportional to the amount of his received benefits. For all partners in the network all costs and benefits are made visible. This transparency is crucial for CBS to succeed. Following this method, the reallocation will lead to equal rates of return on the capital employed for the project.

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Case study: automotive sourcing processes

The approach is now applied to a practical sourcing process to demonstrate its potential of practical application. The basic sourcing process consists of different elements assigning the activities and tasks to each participants. The OEM orders the required materials from the proper supplier. The process ends with the arrival of these materials at the OEM’s production facility. The modified process also organises the material flow from the 1st tier supplier to the production plant of the OEM. Process elements optimise certain activities by using electronic information provided by a special software and hardware. Figure 7 gives an impression of the process chain. Figure 7

Case study procurement process (see online version for colours)

The positive and negative effects can be derived and structured as mentioned earlier. Categorised by participants, they are displayed in Figure 8. To achieve simplicity, within the example, the presented case covers only one period of time. Furthermore, for demonstration purposes we neglect charges for capital interest, the system effect and qualitative factors. Aside from the three presented categories that structure the positive effects, we found positive effects for the OEM, which cannot completely be assigned to one category. To consider them we partially positioned them to each of the three categories by the use of an allocation-rate following the step-ladder method in accountancy. The allocation-rate equals category value divided by the sum of all category values. Figure 8 shows the initial allocation of costs and benefits in the modified process. It indicates a positive total effect of 258,000 €. Therefore, the project should be implemented. On the individual side, the OEM 296,400 € and the logistics service provider gains 37,600 €. Considering the individual effects the supplier might not be willing to participate since his individual effect is –76,000 €. There might also be


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positive effects of qualitative nature that could balance these losses but this seems unlikely to be in the extent of 76,000 €. We assume that the supplier does not want to participate in the project under these conditions. Hence, the project cannot be implemented and no benefits are gained at all unless the supplier is given an adequate incentive to cooperate. This incentive can be provided by the application of the CBS concept to the allocation. The corresponding reallocation is displayed in Figure 9. Figure 8

Initial allocation of effects (see online version for colours)

Figure 9

CBS-reallocation of effects (see online version for colours)

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Results, analysis and discussions

By applying the CBS the total amounts of positive and negative effects, and therefore the total effect remains unchanged. The allocation concerning the negative effects is modified. It is a cost-participation. Figure 9 shows that all companies gain now have positive individual effects and thereby have an incentive to support the implementation

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of the project. The individual effect of the OEM has been reduced compared to the initial allocation but it is still positive. He would pay compensation to both the supplier and the logistics service provider. This compromise allows all partners to equally participate from the gains even in a long-term perspective. It is important to give incentives to companies that invest to improve the supply chain performance but do not benefit from their investments. Economic incentives replace the commonplace ‘power-play’ and will lead to better cooperation and higher efficiency. This is a distinct advantage for tomorrow’s supply chains. CBS is a systematic method of giving incentives to those companies in a network that do not profit directly from cooperative projects, but whose participation is vital for the project to succeed. This system-oriented way motivates companies to achieve a common goal. The idea is to view the network as a system with interrelated parts that can achieve near optimal levels of operational efficiency when they work together cooperatively. The underlying principles of the new management methods – transparency and incentives – are not new.

10 Conclusions, limitations and future research We have discussed the need for a method to give incentives for the network participation. A comprehensive concept of the CBS-model and its application on a case study has been presented in this paper. We have defined relevant terms in the context of CBS and showed an approach to achieving transparency for positive and negative effects in supply chains. This approach aims at a system-oriented improvement of a supply chain. This requires the participation of all partners. The CBS-model provides incentives for the participation. It ensures that all participants are rewarded for their investments. In the case study, we showed an anonymised example of applying CBS in the automotive industry. Even this simplified example shows that win-win-situations can be achieved through transparency. Considering the increasing bargaining power of suppliers, we show that the project might have failed due to the financial loss of the supplier. In this scenario, where the project generates a positive total effect, the CBS-model offers participation incentives to all network companies. The CBS-reallocation reduces the individual effects by certain companies while the effect of others is increased. The total effect remains unchanged by the reallocation. This fact leads to a win-win-situation, but it comes at the expense of the companies that have to give up a share of their individual effect. Their individual effect is still positive after the reallocation but lower than without considering supply chain-wide fairness. Companies that are not strategically oriented might regard this as win-loose situation. A discussion of pareto-optimality has not been included. We argue that compared to the basic process the OEM still benefits in spite of the compensation payments. Only a comparison between the initial allocation and the CBS-reallocation would reveal a financial loss. This is one of the downsides of this approach but it leads to long-term savings. Furthermore, the CBS-approach is based on valid cost information and truthful calculation of the effects. This precondition is difficult to achieve in practice, because it may result in diminishing returns or lower cash-flows. Ways have to be invented to lower the probability of cheating by a methodological approach, for example, an organisational structure that will minimise the incentives for cheating (see Riha and Hirthammer, 2005).


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With these results we have satisfied the goals set in the paper objectives. Further interdisciplinary research needs to be undertaken in refining the model and maturing it towards practical application. Later models must include the system effect and new ways to give incentives. Another goal is to use a simulation model to validate the cost structure and distribution of effects. This may lead to higher acceptance in industry and would account for the dynamics in the supply chain. We have argued that it is important to introduce CBS in the light of major changes in the relationship between the OEM and suppliers in the automotive industry. Apart from the methodological perspective, one should keep in mind that it will not be easy to bring about the mental change needed for the transparency that CBS strictly requires. We therefore encourage the implementation of this method by a network oriented delegation authority. CBS seems to be a way of preparing our networks for future competition and can be applied wherever companies interact in supply chains: in the automotive-, semiconductor- and logistics industries.

Acknowledgements This research was funded by a research grant from the Deutsche Forschungsgemeinschaft as part of the Collaborative Research Center 559 ‘Large Networks in Logistics’ at the University of Dortmund, Germany. The authors are working on the project A2 ‘Supply Networks’.

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Stock, J.R. and Lambert, D.M. (2001) Strategic Logistics Management, Mc Graw-Hill. Straube, F., Dangelmaier, W., Günther, W. and Pfohl, H-C. (2005) Trends und Strategien in der Logistik – Ein Blick auf die Agenda des Logistik-Managements 2010, Bundesvereinigung Logistik, Berlin. Tijs, S.H. and Driessen, T.S.H. (1986) ‘Game theory and cost allocation problems’, Management Science, Vol. 32, pp.1015–1028. Urban, G. and Seiter, M. (2005) ‘What gets measured, gets done!–Nutzenbewertung in der Supply Chain’, International Performance Research Institute GmbH. Varian, H. (2003) Intermediate Microeconomics: A Modern Approach,Norton. Wald, A. (2003) Netzwerkstrukturen und–effekte in Organisationen–Eine Netzwerkanalyse internationalen Unternehmen, Gabler. Weber, J. (2002) Logistik–und Supply Chain Controlling, Stuttgart. Wildemann, H. (2005) ‘Die Quantifizierung des logistischen Nutzens–Kostenausgleich und Nutzenverteilung in Supply Chains’, Zukunft im Brennpunkt, abayfor, Vol. 4, pp.19–24. Young, H.P. (1994) Cost Allocation, Handbook of Game Theory, North Holland: R. Aumann et al., pp.1193–1235.

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Implementation and empirical evaluation of voice-enabled web applications Shuchih Ernest Chang Institute of Electronic Commerce, National Chung Hsing University, 250 Kuo Kuang Road, Taichung City 402, Taiwan, ROC Fax: +886-4-2285-9497 E-mail: [email protected] Abstract: While most users currently receive web services from web browser interfaces, pervasive computing is emerging and offering new ways of accessing internet applications from any device at any location. As a result, there is a growing demand for technology that will allow users to connect to the internet from anywhere through devices that are not suitable for the use of traditional keyboard, mouse and monitor. In this research, cellular phone was chosen as the pervasive device for accessing a multimodal internet application prototype, a voice-enabled web system, through voice user interface technology. The impacts of the forthcoming pervasive computing technology on consumer attitude and the acceptance rate of consumers on new pervasive interface were studied using the Theory of Planned Behaviour (TPB), a widely used technology acceptance theory. The research findings may be referenced for the purpose of the design and development of successful business applications to catch the revolutionary opportunity and benefit of Voice-enabled Web Systems (VWS). Keywords: pervasive computing; human factors; consumer attitude; TPB: theory of planned behaviour; voice applications; web technologies; electronic commerce. Reference to this paper should be made as follows: Chang, S.E. (2009) ‘Implementation and empirical evaluation of voice-enabled web applications’, Int. J. Information Technology and Management, Vol. 8, No. 2, pp.178–195. Biographical notes: Shuchih Ernest Chang is an Associate Professor at the Institute of Electronic Commerce, National Chung Hsing University (NCHU) in Taiwan. He received his MSCS and PhD from the University of Texas at Austin. Before joining the faculty at NCHU, he worked at UBS Financial Services Inc. in USA as a Divisional Vice President for about five years. He has 15 years of working experience in major computer and financial service firms in USA, including: Unisys, IBM, Sun Microsystems, JP Morgan, Bear Stearns and UBS. His research interests are in internet technologies, electronic commerce, enterprise application architecture, information security management and voice-enabled web systems. His publications have appeared in IEEE Pervasive Computing, Information and Software Technology, Expert Systems with Applications, Industrial Management and Data Systems, International Journal of Production Research and International Journal of Technology Management.


Implementation and empirical evaluation of voice-enabled web applications 179

1

Introduction

Just as the e-commerce became a business phenomenon due to the popularity of PCs and the internet, the rapid development of modern wireless technology, accompanied with increasingly high penetration rate of the internet, is making mobile commerce (m-commerce) an important application for both enterprises and consumers (Dholakia and Dholakia, 2004; Gunasekaran and Ngai, 2003). With the explosive growth of the cellular phone users, together with the development of wireless technologies, the pervasive computing technology is bringing the internet to anyone anywhere (Estrin et al., 2002; Roussos et al., 2005). The best example of internet use via cellular phone is in Japan, where 65% of the populations enjoy this access and NTT DoCoMo’s i-mode is the most successful mobile internet service (Ishii, 2004). However, the use of mobile internet is not popular in Taiwan because the penetration rate of mobile internet service in Taiwan, compared with other Asian countries, still tends to be low (Institute for Information Industry, 2004). As pervasive computing technology brings the internet to anyone anywhere with an explosive growth of portable devices such as cellular phones and PDAs, there is a growing demand for technology that will allow users to connect to the internet from anywhere through devices that are not suitable for the use of traditional keyboard, mouse and monitor (Zhai et al., 2005). Currently, the constraints of a typical mobile device, such as small screen size, slow speed and inconvenient keyboard, make it cumbersome to access lengthy textual information (Anerousis and Panagos, 2002); however, voice interface does not have these limitations (Rebman et al., 2003). Using voice as a medium to operate mobile devices also enables user’s hands to engage in some other activities without losing the ability to browse the internet through voice command. Due to the above-mentioned findings, a Voice-enabled Web System (VWS) utilising voice user interface technology was designed and implemented in this research. Cellular phone is chosen as the pervasive device for accessing our internet application prototype, which is a VWS-based service, in this research for two reasons. Firstly, the penetration rate of cellular phone (100.31%) is much higher than the ones of local telephone (59.63%) and internet (40.96%) in Taiwan (Directorate General of Telecommunications, 2005), and cellular phone is connected tightly with people’s everyday life. Secondly, the use of speech for input and output is inherent for the user of a cellular telephone. The system implemented in this research has several advantages over other systems with mobile devices such as Palm PDA, BlackBerry and Pocket PC. For example, VWS users are not restricted to a visual representation of the data. Actually, users can obtain information through voice instead of looking at the monitor. Moreover, through the voice user interface, the system eliminates the requirement of keyboard or mouse. Indeed, voice interface technology can be viewed as one of the most profound technologies, which disappear and weave themselves into the fabric of everyday life until they are indistinguishable from it (Weiser, 1991). This paper describes how VWS was designed and implemented to provide an interactive voice channel using an Apache web server, a voice server and Java technologies. We also showed through our project that multimodal user interface pages could be generated by using technologies including: eXtensible Markup Language (XML), eXtensible Stylesheet Language for Transformations (XSLT) (Burke, 2001), VoiceXML (Larson, 2003) and Java Servlet (Sun Microsystems, 2004). In addition, a VWS prototype was built to provide meal order service as a sample application for users

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to understand and evaluate the voice-enabled system, and through this sample application the impacts of the VWS on the attitude and the acceptance rate of consumers on new pervasive interfaces were studied using the Theory of Planned Behaviour (TPB) (Ajzen, 1991). Our findings may be referenced for the purpose of the design and development of successful business applications to catch the revolutionary opportunity and benefit of VWSs.

2

Literature review

2.1 Pervasive computing The term of pervasive computing was coined by Weiser (1991). In his words, “Our preliminary approach: Activate the world. Provide hundreds of wireless computing devices per person per office, of all scales. This has required new work in operating systems, user interfaces, networks, wireless, displays, and many other areas. This is different from PDAs, dynabooks or information at your fingertips. It is invisible; everywhere computing that does not live on a personal device of any sort, but is in the woodwork everywhere.”

The technological potential for pervasive computing became apparent to researchers from the early 1990s (Bacon, 2002). The fundamental principles that guide pervasive computing design evolved with distributed systems, local area networks and World Wide Web. The vision of pervasive computing is to create for people an environment augmented with computational resources that provided information and services when and where desired (Abowd et al., 2002). Pervasive computing enhanced computer use by making many computers available and effectively invisible to the user throughout the physical environment. It was proposed that pervasive computation would be embodied in things, instead of computers (Mark, 1999). Advances in data networking and wireless communications, digital-system miniaturisation and novel user interfaces were driving the development of pervasive computing, which in turn enabled a broad range of end-user devices to access data and applications on remote servers (Hild et al., 2001). With the development of pervasive computing and its related technologies, users can take advantage of a global connectivity of a wide range of services anywhere. It was also mentioned that new technologies bring new ways to conduct business, and ideas of pervasive commerce opportunities abound (Kourouthanassis and Roussos, 2003).

2.2 Voice application Call routing is a task that human agents handle very well since the early days when the telephone was invented (Lee et al., 2000). For the time being, human operators in call centres and touch-tone dialling systems are still used in many fields. Human operator handling is more flexible and friendly than the self-served touch-tone dialling system, but it involves high costs of personnel expenses. Touch tone interfaces are usually difficult to use especially in cases when the number of menu items is large and difficult to remember although users can follow the directions step by step (Lee et al., 2000).

Implementation and empirical evaluation of voice-enabled web applications 181 Interactive Voice Response (IVR) services have been developed during the past decade to provide a more satisfactory alternative to touch-tone system (Turner, 2004). These IVR services proposed a menu-based dialogue, where the user interacted with the server by uttering isolated words (Sorin et al., 1995). Communication through speech recognition system can be much faster and more reliable than communication with a human telephone operator or a touch-tone system (Rebman et al., 2003). Nowadays IVR is used in value-added service of mobile communication, such as making friends, chatting room, calling taxis and other entertainment activities. In Computer Telephony Integration (CTI), the digital signals in computers and modern digital telephone systems come together for mutual benefit (Lynch, 1995). CTI applications automatically retrieve caller information from the Automatic Call Distributor and capture the caller’s interactions with the Voice Response Unit and associated database (Hernick, 2003). CTI improves the access to information in a timelier manner with more effective actions and response. CTI reduces the hold time waiting for information, and therefore, increases the overall systems performance and improves the level of customer satisfaction. According to a study from Telecom Trends International, the number of m-commerce users world wide will grow from 94.9 million in 2003 to 1.67 billion in 2008, and the global revenues generated from m-commerce are expected to expand from $6.86 billion in 2003 to $554.37 billion in 2008 (de Grimaldo, 2004). A report from ZDNetAsia also mentions that more than half of 3G traffic would be voice and voice is still the platform on which our business is run (Tan, 2005). A study reported by the Kelsey Group claims that expenditures for speech-related services worldwide are expected to reach $41 billion by 2005 (The Kelsey Group, 2001). This report also estimates a 60–65% average annual growth rate by 2005, for voice services globally. A recent example to the continuation of this trend can be illustrated by an outstanding growth (350% increase in quarterly revenue) of speech self-service marketplace reported by Voxify, Inc. (Market Wire, 2006). Based on the above-mentioned fact and analysis, it seems that the demand for m-commerce may have created a market for voice-enabled applications accessible by pervasive devices such as cellular phone. We may therefore assume that applications provided through our proposed VWS are valuable to the consumers, but is our assumption correct? Will consumers adopt the services provided through such VWS? A user study to answer these questions is therefore needed for looking into what the consumers really need and want, so that we can design the VWS-based services and applications to meet consumers’ expectations. For this specific purpose, the TPB was used in our research to conduct a user study. More details of this theory are presented in Section 2.3.

2.3 Theory of planned behaviour In consumer and marketing researches, it is important to understand consumers’ attitudes, that is, thoughts and feelings, by eliciting and extracting directly from consumers the key factors explaining why consumers are adopting or rejecting product or service innovations. For this particular purpose, the Theory of Reasoned Action (TRA), which suggests that an individual’s performance in a specific behaviour is determined by his/her behavioural intention and such behavioural intention is jointly determined by individual attitude and subjective norm (SN), has been widely used in previous studies

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(Ajzen and Fishbein, 1980). As an extension of TRA, the TPB extends TRA by incorporating an additional construct, namely Perceived Behavioural Control (PBC), for reflecting situations in which an individual lacks substantial control over the targeted behaviour (Ajzen, 1991). Figure 1 illustrates the constructs and their relationships in the TPB model. Figure 1

The TPB (see online version for colours)

According to TPB, an individual’s behaviour can be explained by his or her behavioural intention, which is jointly influenced by attitude, SN and PBC. PBC also has a direct effect on actual behaviour. Attitude refers to an individual’s positive or negative evaluative affect about performing a particular behaviour. SN refers to an individual’s perception of relevant others’ opinions on whether or not the individual should perform a particular behaviour. PBC is a construct unique to TPB and refers to an individual’s perceptions of the presences or absence of requisite resources or opportunities necessary for performing a behaviour. In summary, TPB has the following feature: 1

the potential impact of PBC on behavioural intention and actual behaviour is considered in TPB

2

behavioural intention and PBC may directly affect behaviour in TPB

3

behavioural intention is directly influenced by both attitude and PBC

4

SN is important for users with limited direct experience in the early Information Technology (IT) implantation phase.

Both TRA and TPB have been widely used for predicting or explaining cognitive and affective behaviour using the attitude–intention–behaviour relationship in social psychology. TPB in particular has been applied and validated for a great amount of studies in different areas to understand why consumers adopt or reject technological innovations. Some examples of such previous TPB studies are listed in Table 1. In our research, a VWS was designed and implemented to provide users an alternative voice channel for accessing web applications via voice cellular phones. In order to understand the cellular phone users’ attitudes towards the adoption of VWS-based services, TPB model was used in our research to design a research framework. The details of our research framework and its corresponding empirical study approach are described in Section 4.

Implementation and empirical evaluation of voice-enabled web applications 183 Table 1

Previous TPB studies

Author

Context

Hung and Chang (2005)

Wireless Application Protocol (WAP) services

Chau and Hu (2002)

Healthcare

Taylor and Todd (1995)

Information technology

Mathieson (1991)

User intention

3

The voice-enabled web system

3.1 A multimodal approach To conduct an empirical study on the emerging technologies of pervasive computing, we adopted a multimodal application architecture, which offers new ways of accessing web applications from any device at any location (Abowd et al., 2002), by utilising various modes of interfaces to interact with end users. Its back-end servers remain important and intact in this approach, and the technology could involve new ways of interfacing with various types of gateways to back-end servers. This multimodal application approach for supporting our voice-enabled web applications is illustrated in Figure 2. In our research, the voice cellular phone was chosen as the pervasive device for accessing a multimodal web application prototype, the VWS, through voice user interface technology (Anerousis and Panagos, 2002). Figure 2

The multimodal approach for supporting voice-enabled web applications (see online version for colours)

Traditionally, IVR systems are based on proprietary hardware and software technology, with development and deployment tightly integrated on the same hardware platform (Turner, 2004). This has resulted in high development costs. Non-portable proprietary software cannot be deployed on different platforms and it is inherently difficult to upgrade or modify. A multimodal language is needed to support

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human–computer dialogue via spoken input and audio output. As an optimum solution, VoiceXML, a markup language for creating voice user interfaces, bridges the gap between the web and the speech world (Larson, 2003), by utilising speech and telephone touchtone recognition for input and prerecorded audio and Text-To-Speech synthesis (TTS) for output. It is based on the World Wide Web Consortium’s (W3C’s) XML and leverages the web paradigm for application development and deployment (Luttenberger et al., 2004). By having a common language, application developers, platform vendors and tool providers can all benefit from code portability and reuse. Furthermore, to reduce the cost of building and delivery of new capabilities to telephone customers, providing voice access to web-based applications is an attractive option. VoiceXML, together with XML and XSLT, makes it possible for companies to write shared business logic once and focus their resources on developing only the specific user interface for each device they support.

3.2 System description A voice server was used as the platform that enables the creation of voice applications through industry standards, XML, VoiceXML and Java (Larson, 2003). XML facilitates the concept of application integration and data sharing, and enables the exchange of self-describing information elements between computers. In our proposed and implemented VWS system, XML-based data would be created and transformed into two different types of information. The first type includes the information in various data formats supported by HTTP servers, such as texts, pictures, audios, etc. The other information type is in the form of VoiceXML speech. The voice server is set up between the phone and the web server, to interpret the VoiceXML documents and acts as a middleware processor. The VoiceXML interpreter, as a key component in the voice server, contains the voice recognition and the synthesis engines used to automate the conversation between the site and the caller. Any website can be a VoiceXML content server. Services provided by this system can give subscribers access to contents offered by different sources of internet applications and services through Public Switched Telephone Network (PSTN) telephone, wired or wireless. Figure 3 shows the system architecture of the VWS system. A specialised 4-port Dialogic D/41JCT-LS telephony card is used in our study for enabling telephony hardware to integrate with the voice server. When a cellular phone user places a call to a designated phone number, a computer on the voice server answers the call and retrieves the initial VoiceXML script from a VoiceXML content server, which can be a web server located anywhere on the web. An interpreter on the voice server parses and executes the script by playing voice prompts, capturing responses and passing the responses to a speech recognition engine on the voice server. Just as a web browser renders HyperText Markup Language (HTML) documents visually, a VoiceXML interpreter on the voice server renders VoiceXML documents audibly and allows telephone users to access services that are typically available to web users. Once the voice server gets all the necessary information from the caller, the interpreter translates them into a text-based request to the VoiceXML content server. When the server receives the request, it returns a VoiceXML page with either a canned response or dynamically generated VoiceXML script, containing the information requested by the caller. Responses are passed from the VoiceXML content server to the voice server via HyperText Transfer Protocol (HTTP), and then the voice server renders

Implementation and empirical evaluation of voice-enabled web applications 185 VoiceXML documents audibly through voice channel to the cellular phone user. The process can continue, simulating a natural language conversation between the caller and the voice server. Figure 3

The system architecture of the VWS system (see online version for colours)

When voice server starts, VoiceXML browsers start up and wait for calls. Each browser works for one telephone call. The browser gets VoiceXML text from application server through the HTTP protocol, and translates the information from VoiceXML text to the speech for voice users on the telephone. When users dial in the voice system, the telephone and media component of voice server processes the calls. We used Java servlets and Java Database Connectivity (JDBC) to access and connect to a relational database, MySQL. Both the MySQL database and the JDBC driver (mysql-connector-java-3.1.1-alpha-bin.jar) that we used were available for free download at http://dev.mysql.com. Java servlets were used for validating login, constructing user request, processing the request and generating XML output. Afterwards, we use XSLT to convert XML documents into eXtensible HyperText Markup Language (XHTML), VoiceXML and Wireless Markup Language (WML) to suit different browsers. XSLT can be used to perform additional tasks within an application that uses XML as its main data representation model.

3.3 Applications The application to the proposed system is illustrated with food services. Currently, counter ordering (e.g. McDonalds) and online ordering (e.g. Pizza Hut) are two popular methods of requesting fast food services in Taiwan. Therefore, a voice-enabled system prototype was built to provide meal order service as a sample application for users to understand and evaluate the voice-enabled system. The current implementation of our VWS has two interfaces. The first one is the two dimensional (plane) web browser interface, which can present photographs of meal, text descriptions and so on. Voice channel is a one dimensional (linear) interface which cannot include much information. Designing voice user interfaces for providing effective interactions and dialogue is an extremely important task. The voice interface was

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designed following some guidelines. For example, it was adopted in the voice interface to use simple words or single character to increase the recognition rate and the satisfaction level of customers.

4

Empirical study method

The use of mobile internet is not popular in Taiwan, and the success of m-commerce hinges on consumer’s willingness to adopt new technology (Bruner and Kumar, 2005). In this research, we built a VWS with cellular phones as the pervasive devices to access the system and evaluate the concept of pervasive computing. In order to understand user’s acceptance of the proposed system, in this research a sample survey methodology was used to test research hypotheses. As shown in Figure 4, the TPB was applied to examine the individual acceptance of the new VWS-based services. A theoretically grounded questionnaire was developed to call for responses from the users of the VWS system, and subsequently, the online questionnaire was sent out to collect data from users with experience in accessing web applications and our sample VWS application. Figure 4

The TPB-based research framework

Based on TPB, we postulated that a person’s intention to adopt a voice-enabled internet device was determined by three factors. They are attitude (which describes a person’s perception towards a voice-enabled internet device), SN (which describes the social influence that may affect a person’s intention to adopt a voice-enabled internet device) and PBC (which describes the beliefs about having the necessary resources and opportunities to adopt the voice-enabled internet device). In the context of the framework, intention to adopt voice-enabled internet device is thus the dependent variable, while the independent variables comprise attitude, SN and PBC. Hence, the direct effects of attitude, SN and PBC on behavioural intention would be tested by the following hypotheses: H1: Attitude has a significant influence on behavioural intention. H2: SN has a significant influence on behavioural intention. H3: PBC has a significant influence on behavioural intention.

Implementation and empirical evaluation of voice-enabled web applications 187 Empirical data were collected by conducting a field survey through online questionnaire. Subjects were supposed to have the experience about using cellular phones and webs. To insure that the scale used in this research achieved content validity, the measures used to operationalise the constructs included in the research models were mainly adapted from relevant prior studies, with validation and wording changes as necessary. Items for measuring SN, PBC and attitude were taken from Taylor and Todd (1995). Each item was measured on a seven-point Likert scale, ranging from ‘strongly disagree’ (extremely unimportant) to ‘strongly agree’ (extremely important). To achieve the desired balance and randomness in the questionnaire, half of the items were worded with proper negation and all items in the questionnaire were randomly sequenced to reduce the potential ceiling (or floor) effect, which would induce monotonous responses to the measures of a particular construct. To ensure that the question items could be understood and measured validly, pretest was conducted with small group. From the pretest feedback and the subsequent discussion with experts, the questionnaire was modified and refined. Our sample voice-enabled web application provided a virtual foodservice scenario with a phone number and a website address. After experiencing the use of the system, respondents were requested to answer the questionnaire. SPSS 11 and AMOS 5.0 were used to analyse collected samples. The characteristics of respondents were described using descriptive statistics methods, while reliability analysis was used to ensure the consistency of measurement, and validity analysis was used to assess the measurement validity. Afterwards, factor analysis was used to find out the correlated variables and display relevant correlated components. Finally, Structural Equation Modelling (SEM) was used to verify the theoretical model which had latent variables (Schumacker and Lomax, 2004).

5

Empirical study result

A total of 194 respondents were gathered. JavaScript logics were designed and exercised in the online questionnaires for this research to avoid missing values and to validate the quality of the survey results. Invalid survey results were also identified by discovering illogical answer patterns such as the pattern with all the same answers from beginning to end, and using the reverse question which is inconsistent with other items. Overall, 147 usable questionnaires were collected and used for analysis. Among 147 usable respondents, 57.9% were male and 42.1% were female. The majority was from 21 to 30 years old and its response rate was 81.1%. The levels of education tended to university (college) and graduate school with an aggregated response rate amounted to 94.6%. Students formed the major group, which attributed to a response rate of 57.8% and 59.2% responded individuals were with monthly incomes less than 20,000 Taiwan dollars. More details of the descriptive statistics are listed in Table 2. The constructs used in this research were assessed in terms of reliability and convergent validity. The statistics of the collected valid survey results are detailed in Table 3. Reliability was examined using Cronbach’s α values. As summarised in Table 3, all components had acceptable reliability since their Cronbach’s α measures were between 0.63 and 0.91. According to the guideline indicated by Nunnally and Bernstein (1994), the value of 0.7 or above is an acceptable reliability coefficient, but sometimes slightly lower thresholds are used in the literature (García-Morales et al., 2006; Koch et al., 2005). Next, convergent validity is considered to be satisfactory when

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items load high on their respective constructs. As given in Table 3, results showed that all items loaded high on the expected constructs. All items exhibited loading higher than 0.60 on their respective factors, signifying desirable measurement convergent validity. In summary, the measurement model demonstrated adequate reliability and convergent validity. Table 2

Descriptive profile of respondents

Measure Gender Age

Education

Industry

Items

Percentage(%)

Male

85

57.9

Female

62

42.1

Under 21

13

8.8

21–30

127

86.4

31–40

7

4.8

41–0

0

0

Over 51

0

0

Junior high school or under

0

0

Senior/Vocational high school

8

5.4

University/College

78

53.1

Graduate school or beyond

61

41.5

Manufacturing

2

1.4

Agriculture

0

0

Service

4

2.7

Army/Police/Civil servant

0

0

Education/Academic

14

9.5

6

4.1

26

17.7

Freedom

1

0.7

Home maker

2

1.4

Student

85

57.8

Others

7

4.7

Less than $20,000

87

59.2

$20,001–40,000

51

34.7

$40,001–60,000

9

6.1

$60,001–80,000

0

0

$80,001–100,000

0

0

More than $100,000

0

0

Information science/Technology Business/Financial

Individual monthly income

Frequency

Implementation and empirical evaluation of voice-enabled web applications 189 Table 3

Summary of measurement scales

Construct

Measure

Attitude (ATT) ATT1 ATT2

Using a VWS is a good idea Using a VWS is a wise idea

Subjective Norm (SN) SN1

People (peers and experts) important to me supported my use of VWS SN2 People who influenced my behaviour wanted me to use VWS instead of any alternative means. SN3 People whose opinion I valued preferred that I use VWS Perceived Behavioural Control (PBC) PBC1 I would be able to use a VWS PBC2 I have the knowledge and the ability to make use of the VWS Behavioural Intention (BI) BI1 I found using the VWS to be enjoyable BI2 It is likely that I will use VWS in the near future (i.e. next three months) BI3 I intend to use VWS in the near future (i.e. next three months). Table 4

Mean

SD

Factor loading

5.20

1.03

0.89

5.17

1.12

0.90

4.78

1.07

0.77

4.70

1.03

0.87

4.82

0.92

0.72

5.59

1.11

0.62

5.42

1.06

0.70

5.36

1.02

0.90

5.33

1.09

0.88

5.46

1.00

0.79

Cronbach’s alpha (α)

0.91

0.82

0.63

0.91

Goodness-of-fit measures of the research model

Goodness-of-fit measure Chi-square/degree of freedom

Recommended value / 3.00

Model statistic 1.787

Goodness-of-Fit Index (GFI)

0 0.9

0.923

Adjusted Goodness-of-Fit Index (AGFI)

0 0.8

0.868

Normalised Fit Index (NFI)

0 0.9

0.934

Comparative Fit Index (CFI)

0 0.9

0.969

Root Mean Square Residual (RMSE)

/ 0.08

0.073

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TPB model was tested using SPSS 11 and AMOS 5.0, 147 valid questionnaires were used for analysis. Model fitness was examined by six commonly used goodness-of-fit measures including: Chi-square/d.f., GFI, AGFI, NFI, CFI and RMSEA. As given in Table 4, all six indices respectively exceeded their recommended acceptance levels, indicating that the TPB model provided a reasonably good fit to the data. The significance of individual paths was also examined and shown in Figure 5, and the hypotheses testing results are summarised in Table 5. The paths from attitude, SN and PBC to behavioural intention were significant. Furthermore, attitude appeared to have a stronger direct effect on behavioural intention than PBC and PBC had a stronger effect on behavioural intention than SN. As a whole, the three constructs in our TPB-based model altogether explained 62% of the variance (R2BI = 0.62) in users’ behavioural intention towards adopting VWS-based services. Figure 5

The research result

Table 5

Results of hypotheses tests

Hypothesis

Effects a

Structural coefficient 0.72***

Test result

H1

ATT→BI

Supported

H2

SN→BI

0.17*

Supported

H3

PBC→BI

0.27**

Supported

a

ATT: Attitude; SN: Subjective Norm; PBC: Perceived Behavioural Control; BI: Behavioural Intention. *p < 0.05, **p < 0.01, ***p < 0.001.

6

Discussion

The findings of our empirical study show that the intention to adopt a VWS is positively associated with attitude, PBC and SN. Attitude appeared to be the most important determinant of a user’s intention toward accepting VWS. This highlights the important role of attitude in technology acceptance behaviour, and it is also important for us to

Implementation and empirical evaluation of voice-enabled web applications 191 focus on the antecedents of attitude in future studies. Our findings are consistent with the study result from Hung and Chang (2005) about that attitude and SN are positively associated with behavioural intention to using WAP services. However, our study result also shows an important finding regarding that PBC is positively associated with behavioural intention towards using cellular phone for accessing VWS applications. This finding is inconsistent with Hung and Chang’s study result indicating that PBC suppresses actual WAP services use. In this study, voice cellular phone was used as the only pervasive device for accessing an internet application prototype, and in our daily life people already have enough knowledge of cellular phone and the ability to use it. As far as cellular phone users’ concerns, they already have the necessary resources (i.e. hardware – the voice cellular phone) and they are quite familiar with the opportunities and the operation details (i.e. software – the skill and experience) to properly use their cellular phones for the purpose of adopting VWS services. This situation is different from that of Hung and Chang’s study which required users to use WAP devices for services, but their users might not have the necessary hardware (WAP devices) and software (experience) to smoothly use WAP services. Therefore, we suggest that VWS applications can be introduced into people’s life, as long as the system can be accessed through popular devices. Assuming that users could get the desired outcome by using the system, the system would be more acceptable for the users if they can use familiar, existing and available devices to access the system.

7

Conclusions

7.1 Concluding remarks To support various types of pervasive devices in a conventional way, multiple applications have to be independently developed with each to satisfy one type of devices. This practice will exponentially increase the cost, complexity and instability of a system when new devices or changes are introduced. To resolve this issue, we adopted a new software application architecture (see Figure 2) that enables one single application simultaneously interfacing with various types of access devices such as PC’s, handheld computers, PDA’s, WAP enabled wireless devices, phones and others. This multimodal application architecture overcomes the difficulties by singularising the business and application logic while expanding device interfaces. Since common business and application logic is centralised, the maintenance is much easier. Our multimodal web system, VWS was designed and implemented based on this architecture to serve as a ‘proof of concept’ example of this new e-commerce application paradigm. Nowadays, mobile and wireless technologies are becoming increasingly prevalent, and there is a growing demand for technology that will allow users to connect to the internet from anywhere through devices that are not suitable for the use of traditional keyboard, mouse and monitor. In the near future, human–computer voice interfaces will become important tools for solving the accessibility limitations of conventional human–computer interfaces. PBC is found to have a significant effect on behavioural intention to adopt VWS. Since we are using voice to operate the system, it is important to design efficient dialogue menus. Unduly designed voice user interface will be inefficient and fail to serve users’ needs for promptness. More issues regarding interaction and dialogue design should be concerned to avoid users’ dissatisfaction. Using TPB model as

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a theoretical framework, this study helps system developers and researchers predict how users will respond to VWS, and increase the rate of user acceptance by improving the adopting process and accessing techniques of VWS. Despite less information available through voice channel, there are still opportunities to replace internet channel with voice channel (using cellular phone), especially in some situations, such as in an emergency, in an on-the-go situation or in outdoors environment. So, we also suggest a VWS could be initially deployed in such special situations to increase the odds of success. VWS could also be applied to different products or services. Since there would be different, extracted and important attributes on perception of the system, our empirical research framework could be expanded in the future to evaluate more criteria such as costs or feasibility. The future study may also discuss individual difference traits to identify the attitude and acceptance from different groups of users. System hardware factors affect users’ perception on VWS as well. The future studies would conduct laboratory experiments to manipulate variables, such as environment, device, recognition rate and so on. Another avenue of future study is to compare our proposed scheme (i.e. the voice-enabled multimodal web approach) with other related schemes to make our research better and practical. The main limitation of this study is that use of online survey restricts us to a pool of internet users as respondents. Hence, the results obtained may not be suitable for non-internet users and the general public. However, the sample of internet users may be a better representation of potential VWS adopters than non-internet users. This assumption is made on the basis that a person will be more ready to adopt mobile internet (through VWS) when he/she has experienced the benefits of the internet. Another limitation of this study is that we have not considered the influence of the surrounding noise which will influence the quality of speech. Furthermore, the recognition rate of the system is beyond our research scope. Most of the respondents answered the questionnaires based on the experience and impression acquired from one time use of the system. That is, if the system did not recognise some respondents’ speech very well because of surrounding noise or their accents, they would be very frustrated and have bad impression on voice recognition, and then, on the VWS as well.

7.2 Recap of our VWS project In summary, the following are the key items and important points presented by this paper: •

This paper demonstrates how multimodal application architecture was designed and implemented so that one application can simultaneously interface with various types of access devices (such as handheld computers, PDA’s, WAP devices, cell phones and others) by singularising the business and application logic while expanding device interfaces.

•

Comparatively speaking, to support various types of pervasive devices in a conventional way, multiple applications have to be independently developed with each to satisfy one type of devices, and such approach will exponentially increase the cost, complexity and instability of a system when new devices or changes are introduced.

•

Based on the multimodal architecture, this paper describes how a VWS prototype could be implemented to provide an interactive voice channel using an Apache web server, a voice server and Java technologies.

Implementation and empirical evaluation of voice-enabled web applications 193 •

Through the implementation efforts, we confirmed that multimodal user interface pages could be generated by using technologies including XML, XSLT, VoiceXML and Java Servlet.

•

This paper showed that voice interfaces may not only help solve the accessibility limitations of conventional human–computer interfaces, but enable mobile device users’ hands to engage in some other activities without losing the ability to browse the internet through voice command.

•

Based on literature review, we found that while the number of users and the revenues related to m-commerce grow significantly every year, voice is still the mainstream of 3G traffic and the expenditures for voice applications worldwide also grow dramatically. Indeed, the demand for m-commerce may have created a market for voice-enabled web applications accessible by pervasive devices such as cellular phone.

•

The actual adoption of VWS from the consumption side may be different from our expectation, and therefore we attempted to investigate what important factors would affect users’ attitude to the adoption of VWS applications.

•

Based on the TPB, we designed a user study framework together with three hypotheses, and then conducted an empirical study by developing and administrating a questionnaire survey to assess users’ perceptions of VWS. Survey participants were asked to experience the implemented VWS application, and then fill out the questionnaire.

•

Our empirical study result shows that a user’s intention to adopt VWS is positively associated with his/her attitude, PBC and SN. As a whole, our empirical findings support the hypotheses postulated by the underlying premise of TPB, and suggest to enhance the adoption of VWS through perspectives on users’ attitude, PBC and SN.

•

Attitude, that is, the user’s positive or negative feeling towards adopting VWS, appears to be the most important determinant of a user’s intention towards accepting VWS. This highlights the important role of attitude in technology acceptance behaviour, and it also sheds light on investigating the antecedents of attitude in our future studies.

•

SN, which has great influence on behavioural intention especially in the early stages of the innovation diffusion cycle (Hartwick and Barki, 1994), appears to be the least important determinant of a user’s adoption of VWS. Since cellular phone is the only device in this study for accessing VWS and the use of cellular phone has been mixed into people’s daily life, the potential adopters’ needs for seeking advices from trusted reference groups or opinion leaders become less important in making adoption decision than attitude and PBC.

•

In terms of PBC, it is suggested that VWS would be more acceptable to the users if they can use familiar, existing and available devices to access VWS, and it is essential to design efficient dialogue menus for operating VWS via voice channel since inefficient voice user interfaces will fail to serve users’ needs for promptness. Service providers should pay attentions to the voice user interface in terms of the interaction design and dialogue flow of VWS to avoid users’ dissatisfaction.

•

Improving the adopting process and accessing techniques of VWS is the key to success. Despite less information available through voice channel, there are still opportunities to replace internet channel with voice channel. It is suggested that

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S.E. Chang VWS applications may be initially applied to special situations (e.g. in an emergency, in an on-the-go situation or in outdoors environment) to increase the odds of success.

•

Finally, the limitations of this study and the suggested directions for future research are described in this paper.

References Abowd, G., Mynatt, E. and Rodden, T. (2002) ‘The human experience’, IEEE Pervasive Computing, Vol. 1, No. 1, pp.48–57. Ajzen, I. (1991) ‘The theory of planned behavior’, Organizational Behavior and Human Decision Processes, Vol. 50, pp.179–211. Ajzen, I. and Fishbein, M. (1980) Understanding Attitudes and Predicting Social Behavior, New Jersey: Prentice-Hall. Anerousis, N. and Panagos, E. (2002) ‘Making voice knowledge pervasive’, IEEE Pervasive Computing, Vol. 1, No. 2, pp.42–48. Bacon, J. (2002) ‘Toward pervasive computing’, IEEE Pervasive Computing, Vol. 1, No. 2, p.84. Bruner, G.C. and Kumar, A. (2005) ‘Explaining consumer acceptance of handheld internet devices’, Journal of Business Research, Vol. 58, No. 5, pp.553–558. Burke, E. (2001) JAVA and XSLT, California: O'Reilly & Associates. de Grimaldo, S.W. (2004) Mobile Commerce Takes off, Virginia: Telecom Trends International, Inc. Retrieved on 15 November 2005, Available at: http:// www.telecomtrends.net. Chau, P.Y.K. and Hu, P.J.H. (2002) ‘Investigating healthcare professionals’ decisions to accept telemedicine technology: an empirical test of competing theories’, Information and Management, Vol. 39, No. 4, pp.297–311. Directorate General of Telecommunications (2005) Penetration Rates of Major Telecom Services, Annual Report 2004, Taiwan: Ministry of Transportation and Communications. Retrieved on 15 November 2005, Available at: http://www.dgt.gov.tw/chinese/About-dgt/Publication/94/. Dholakia, R.R. and Dholakia, N. (2004) ‘Mobility and markets: emerging outlines of m-commerce’, Journal of Business Research, Vol. 57, No. 12, pp.1391–1396. Estrin, D., Culler, D., Pister, K. and Sukhatme, G. (2002) ‘Connecting the physical world with pervasive networks’, IEEE Pervasive Computing, Vol. 1, No. 1, pp.59–69. García-Morales, V.J., Llorens-Montes, F.J. and Verdú-Jover, A.J. (2006) ‘Antecedents and consequences of organizational innovation and organizational learning in entrepreneurship’, Industrial Management and Data Systems, Vol. 106, No. 1, pp.21–42. Gunasekaran, A. and Ngai, E. (2003) ‘Special issue on mobile commerce: strategies, technologies and applications’, Decision Support Systems, Vol. 35, No. 1, pp.187–188. Hartwick, J. and Barki, H. (1994) ‘Explaining the role of user participation in information system use’, Management Science, Vol. 40, No. 4, pp.440–65. Hernick, J. (2003) ‘Telephony 101: giving voice to your network’, Network Computing, Vol. 14, No. 20, pp.75–77. Hild, S.G., Binding, C. Bourges-Waldegg, D. and Steenkeste, C. (2001) ‘Application hosting for pervasive computing’, IBM Systems Journal, Vol. 40, No. 1, pp.193–219. Hung, S.Y. and Chang, C.M. (2005) ‘User acceptance of WAP services: test of competing theories’, Computer Standards and Interfaces, Vol. 27, No. 4, pp.359–370. Institute for Information Industry (2004) ACI-FIND, Focus on Internet News and Data, Accessed on 15 November 2005, from Advanced Commerce Institute website: Available at: http://www.find.org.tw/. Ishii, K. (2004) ‘Internet use via mobile phone in Japan’, Telecommunications Policy, Vol. 28, No. 1, pp.43–58.

Implementation and empirical evaluation of voice-enabled web applications 195 Koch, A.L., Arfken, C.L., Dickson, M.W., Agius, E. and Mitchelson, J.K. (2005) ‘Variables associated with environmental scanning among clinicians at substance abuse treatment clinics’, Information Research, Vol. 11, No. 1, Retrieved on 15 February 2006, Available at: http://InformationR.net/ir/11-1/paper244.html. Kourouthanassis, P. and Roussos, G. (2003) ‘Developing consumer-friendly pervasive retail systems’, IEEE Pervasive Computing, Vol. 2, No. 2, pp.32–39. Larson, J.A. (2003) ‘VoiceXML and the W3C speech interface framework’, IEEE Multimedia, Vol. 10, No. 4, pp.91–93. Lee, C-H., Carpenter, B., Chou, W., Chu-Carroll, J., Reichl, W., Saad, A. and Zhou, Q. (2000) ‘On natural language call routing’, Speech Communication, Vol. 31, No. 4, pp.309–320. Luttenberger, N., Reuter, F. and Koberstein, J. (2004) ‘XML language binding support for pervasive communication in distributed virtual shared information spaces’, Proceedings of Second IEEE Annual Conference on Pervasive Computing and Communications Workshops, pp.181–186, Orland, FL. Lynch, J. (1995) ‘Computer-telephony integration’, Work Study, Vol. 44, No. 7, pp.8–9. Mark, W. (1999) ‘Turning pervasive computing into mediated spaces’, IBM Systems Journal, Vol. 38, No. 4, pp.677–692. Market Wire (2006) Voxify Reports Outstanding Growth, Increased Momentum in the Speech SelfService Marketplace, Los Angeles: Market Wire Press Releases Retrieved on 10 August 2006 Available at: http://www.findarticles.com/p/articles/mi_pwwi/is_200605/ai_n16136434. Roussos, G., Marsh, A.J. and Maglavera, S. (2005) ‘Enabling pervasive computing with smart phones’, IEEE Pervasive Computing, Vol. 4, No. 2, pp.20–27. Mathieson, K. (1991) ‘Predicting user intentions: comparing the technology acceptance model with the theory of planned behavior’, Information Systems Research, Vol. 2, No. 3, pp.173–191. Nunnally, J.C. and Bernstein, I.H. (1994) Psychometric Theory, 3rd edition, New York: McGraw-Hill. Rebman Jr., C.M., Aiken, M.W. and Cegielski, C.G. (2003) ‘Speech recognition in the human-computer interface’, Information and Management, Vol. 40, No. 6, pp.509–519. Schumacker, R. and Lomax, R. (2004) A Beginner’s Guide to Structural Equation Modeling, 2nd edition, Lawence Erlbaum Associates. Sorin, C., Jouvet, D., Gagnoulet, C., Dubois, D., Sadek, D. and Toularhoat, M. (1995) ‘Operational and experimental French telecommunication services using CNET speech recognition and text-to-speech synthesis’, Speech communication, Vol. 17, Nos. 3–4, pp.273–286. Sun Microsystems (2004) On-line information on J2EE, Retrieved on 2 September 2005, Available at: http://java.sun.com/j2ee/. Tan, A. (2005) Voice to Dominate 3G Traffic, Says Expert. Hong Kong: ZDFNetAsia. Retrieved on 15 November 2005, Available at: http://www.zdnetasia.com/news/communications/ 0,3904 4192,39231956,00.htm. Taylor, S. and Todd, P.A. (1995) ‘Understanding information technology usage: a test of competing models’, Information Systems Research, Vol. 6, No. 2, pp.144–176. The Kelsey Group (2001) ‘The global voice ecosystem’, Analyst Report, The Kelsey Group, March 2001. Turner, K.J. (2004) ‘Analysing interactive voice services’, Computer Networks, Vol. 45, No. 5, pp.665–685. Weiser, M. (1991) ‘The computer for the 21st century’, Scientific American, Vol. 265, No. 3, pp.94–104. Zhai, S., Kristensson, P-O. and Smith, B.A. (2005) ‘In search of effective text input interfaces for off the desktop computing’, Interacting with Computers, Vol. 17, No. 3, pp.229–250.

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A study on the effect of work environment perception on user satisfaction in health information systems: HISs quality as mediator Chung-Hung Tsai* Department of Health Administration, Tzu Chi College of Technology, 880, Sec 2, Chien-Kuo Road, Hualien, Taiwan 97005, ROC E-mail: [email protected] *Corresponding author

Dauw-Song Zhu Department of Business Administration and Accounting, National Dong Hwa University, No. 1, Sec 2, Du Hsuch Road, Hualien, Taiwan 97401, ROC E-mail: [email protected] Abstract: This purpose of this study is to develop the user satisfaction model of Health Information Systems (HISs). A survey of 252 samples of the medical centre in Taiwan shows that the effects of user involvement and supervisor support on user satisfaction are mediated by HISs quality. Besides, service quality has the most influence on user satisfaction in HISs quality. This research can provide managers of the hospital with the implication that we must focus not only on the Information System (IS) quality aspect (system quality, information quality), but also on the social interaction aspect (user involvement, supervisor support) and technical support aspect (service quality). Keywords: user involvement; supervisor support; system quality; information quality; service quality; HISs; Health Information Systems. Reference to this paper should be made as follows: Tsai, C-H. and Zhu, D-S. (2009) ‘A study on the effect of work environment perception on user satisfaction in health information systems: HISs quality as mediator’, Int. J. Information Technology and Management, Vol. 8, No. 2, pp.196–213. Biographical notes: Chung-Hung Tsai is an Assistant Professor and the Director of Department of Health Administration at Tzu Chi College of Technology. He received his PhD from National Dong-Hwa University. His current research areas are knowledge management system, health information system, e-commerce and health management. His academic papers have been published in Journal of Technology Management, MIS Review, Journal of American Academy of Business, Electronic Commerce Studies, Journal of Business Administration, Journal of Customer Satisfaction and Journal of Health Management.


A study on the effect of work environment

197

Dauw-Song Zhu is a Professor and Chairperson of Department of Accounting at National Dong-Hwa University. He received his PhD from National Sun Yat-Sen University. As a Consultant and Scholar, he has been involved in management practices for a long time. His current research interests include management control systems, behavioural accounting and consumer behaviour. He has published 28 refereed journal articles in behavioural accounting, consumer behaviour and healthcare field. He has ever served as Guest Editor of International Journal of Management and Decision Making (IJMDM) and host Supply Chain Management and Information Systems Conference (SCMIS 2006) as Co-chairperson.

1

Introduction

Since the National Health Insurance (NHI) started in 1995, Taiwan government began to be in charge of the matters of public health insurance. In order to fit the new medical environment and to solve the problems caused by the insufficient subsidies, the hospitals in Taiwan were managed by business administration. In this way, managers or the hospitals tried to make the best use of limited resources, decrease the cost and improve the quality. Therefore, Information System (IS) replaced a large amount of manpower as the main instrument to carry out daily medical statistic affairs. According to Dowling (1980), Computer-Based Medical Information System (CBMIS) refers to any kind of interactive computer system, which is used to help medical staffs to accomplish their work. When using CBMIS, most users put emphasis on its technological influence, such as cost, speed and data processing. Its influences on the users and the consequent effect of the users after using it were totally ignored. Henry and Stone (1994) also argued that a computer system can be assessed to be very well, but users refuse to use it. Nowadays, the medical records of patients are quite complicated and take up much space; however, these important information costs a large amount of money and manpower. If we can find out the user satisfaction degree of the Health Information Systems (HISs), we cannot only shorten the complicated procedure, but also save or avoid unnecessary expenditure of money. The medical characteristics and environment leads to the complication and variation of the need of HISs. To carry on the hospitals and to reinforce the marketing competitiveness, managers try their best to modify their original systems by enhancing system processing capabilities and users’ satisfaction. The purpose of this study is to investigate the factors that affect users’ satisfaction in HISs, and to find out the important antecedents of user satisfaction of HISs so as to offer an empirical reference to the managers of hospitals.

2

Literature review

2.1 Development and application of HISs HISs was started in 1960 and was applied in some administration aspects, such as financial declaration, cost statistics, insurance report, etc. The systems almost are stand

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alone and single user version, because hardware was expensive and often break down at that time. Therefore, computer science was not adequate for exploiting HISs. It was not until 1970 that some hospitals began to set up their own information department, and the computer systems were also advanced. Since 1981, many medical centres have expanded their computer system into medical management affairs, and then into clinical treatment. In the US, the so-called HISs was only applied to some patient-centred affairs, such as hospitalisation and registration. Differently, HISs in Taiwan integrated various applications, including charge and account systems, Radioactivity Information System (RIS), Pharmacy Information System (PIS), Logistics Information System (LIS), Nursing Information System (NIS) and so on. To the present, HISs has technologically advanced to two aspects: 1

the Picture Archiving and Communication Systems (PACS)

2

Electronic Medical Record (EMR).

However, it consumes a lot of time and money to develop the software. The managers of hospitals should possess suitable tools to evaluate the value of HISs in Hospitals.

2.2 Evaluation of IS and IS success model DeLone and McLean (1992) consulted over 180 researches and suggested a IS Success model (see Figure 1). They found that success of an IS can be represented by the quality characteristics of the IS itself (system quality); the quality of the output of the IS (information quality); consumption of the output of the IS (use); the IS user’s response to the IS (user satisfaction); the effect of the IS on the behaviour of the user (individual impact); and the effect of the IS on organisation performance (organisational impact) (McGill et al., 2003). System quality is defined as the evaluation of IS itself, including validity of the programme, consistency of the operation interface, simplicity of maintenance, etc. Information quality is defined as the evaluation of the IS output, including relevant, timeliness and correctness of the information. System use means the condition that the receiver uses the information output. It is evaluated by the frequency and the diversity aspects of using the system. User’s satisfaction represents the response of the user after outputting the information, which involves satisfactions in the decision, the hardware, the software, the entirety, the information and the interface. Individual impact means the effect of IS on the behaviour of the recipient. Organisational impact refers to the effect of IS on organisational performance. The model made many important contributions to IS success measurement: 1

it provided a scheme for categorising the multitude of IS success measures

2

it provided a model of temporal and causal interdependencies between the measures

3

it imposed some order on IS researchers’ choices of success measures (McGill et al., 2003; Seddon et al., 1999).

Pitt et al. (1995) suggested that the base of DeLone and McLean categorisation is product-oriented. They argued that the quality of the IS department’s service is a key indicator of IS success. Kettinger and Lee (1994) adapted the SERVQUAL measures from marketing to provide more specific information about user satisfaction with the


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information service function. Based on previous studies as discussed above, DeLone and McLean (2003) updated their original success model as Figure 2. They added service quality to the original success model and combine ‘individual’ and ‘organisational impacts’ into a single variable, ‘net benefits’. Service quality involves the relationship between the IS department and the users. User’s satisfaction to the IS employees represents the evaluation of the attitude, efficiency and profession of the IS employees. Figure 1

D&M IS success model

Figure 2

Updated D&M IS success model

Owing to user satisfaction is the most commonly used as the dependent variable of IS success model and whether system usage is suitable to be a measure of system success while use is mandatory that is still a open question (see DeLone and McLean, 2003; Seddon, 1997), this study will use user satisfaction to be the dependent variable of the HISs system success.

2.3 Work environment perception and the dimensions: user involvement and supervisor support Work environment perception refers to the evaluation of the staffs toward their work environment (Babin and Boles, 1996; James and James, 1989; Lazarus, 1984). Babin and Boles (1996) argued that there were four constructs of work environment perceptions: 1

the internal motivation of the staffs

2

the promotion of the support from the supervisors

3

the friendship and warmth of the work team

4

character pressure.

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Moos (1981) suggested that a supportive work environment should be the one in which the staffs feel themselves involved and supported and promoted by the supervisors. User involvement has been referred to as participation in the system development process measured as a set of activities that users or their representatives have performed (Terry and Standing, 2004). Saleem (1996) cited the model of Participative Decision Making (PDM) and suggested that the key element of a successful IS model is user’s participation in the development of IS. Especially, when the designer lacks professional skill, user involvement is necessary. Kram (1985) defined supervisor support as the relationship between subordinate and supervisor, which is viewed by subordinate as having a positive contribution to career development. Jiang and Klein (2000) argued that supervisor support is defined as the degree of supervisor provision of information on employees’ career opportunities and helpful feedback on performance. Laudon and Laudon (1991) suggested that a successful IS can be judged by the various degrees of user involvement, supervisor support, system complexity and risk and online management. When users were involved, they will know better about the system and become easier to accept the reformation of the system. The supervisor support, on the other hand, will make the users and designers to be more involved in the system. Besides, the supervisor support stands for sufficient budget and resources which influence directly on the success or failure of the system. Ein-Dor and Segev (1986) contended that if the system was supported and promised by various ranks of managers, users and designers will feel positively. Both users and designers will believe that they will be highly valued by the managers and supervisors and win the priority of sufficient financial support. Lucas (1981) held that by the leadership of supervisors, sufficient resources will be promised and adequate reformation will also be created. Weill (1992) contended that the supervisor’s promise will make the system more efficient and significant. Yap et al. (1992) thought that without the supervisor support, the construction of the system will not go smoothly. Davenport (1998) viewed the supervisor as the main mediator between information technology and processing who will make the construction of the system easier. Bingi et al. (1999) also pointed out that the supervisor support is the key to a successful professional information technology. Concerning the whole medical environment, HISs is combined with medical profession and information complexity. In the context, the supervisor support and user involvement are the key elements to decide whether the system is successful. According to the researchers mentioned above, the supervisor support and user involvement are the perceptions and evaluation of users, but present researches seldom investigate the two social context factors.

2.4 Service quality, system quality and information quality Gefen and Keil (1998) argued that the development and implementation of IS as a social exchange means users’ assessment of the behaviours of their social exchange partners – the developers should influence the benefits from the IS. That is, owing to the incurred cost from the development of IS (e.g. the investment of time, effort, emotion and the promise of many future rewards), so user-developer interaction during IS development and implementation can be viewed as a social exchange. From the social exchange views, the expected outcome of the party involved in the social exchange


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interaction will be affected by the actions of each other. Accordingly, user perceptions of the developers’ service quality should influence their rewards from the social exchange actions, that is system quality and information quality of IS. The end users of HISs do not just want a machine, rather they seek a system that assistant them to finish the medical jobs. Thus, the IS department’s ability to provide technological support, product knowledge, software training and consultation will be crucial to system-related quality, namely system quality and information quality.

2.5 Work environment perceptions, system quality, information quality, service quality and user satisfaction Lazarus (1984) argued that work environment perceptions positively affect work satisfaction because of the affective nature of work satisfaction. Simply, the affective assessment of work environment is the base of the affective reaction. The other research also suggested that the supervisor support influence work satisfaction (Kirmeyer and Lin, 1987). Blanton et al. (1998) examined factors affecting professional competence of information technology professionals, and the results suggested that factors of organisation updating climate (supervisor support is one of five facets) did affect professional competency level. That is, if supervisors provide enough feedback information, relevant training, available resources, meaningful incentives and remove barriers to assistant IS professionals to develop the system, then the overall IS quality (system quality, information quality and service quality) will have more chances to be better. User involvement in IS development is generally considered an important mechanism for improving system quality and ensuring successful system implementation (Baroudi et al., 1986). During the research of IS project, Jiang et al. (2002) argued that lack of user involvement incline to decrease the performance of project. Baroudi and Orlikowski (1988) validated the measure of user satisfaction with the IS function, which identified the level of user’s knowledge and involvement is one of three major dimensions. Baroudi et al. (1986) demonstrated that user involvement in the development of IS enhance both system usage and the user’s satisfaction with the system. Barki and Hariwick (1989) used the path analysis of data from 102 individual users of university accounting system to show the effect of user involvement on user satisfaction is significantly positive. Zeffane et al. (1998) examined the impact of end-user participation during IS development on the perceived quality of the data produced from the resultant systems. The results showed that degree of end-user involvement was found to have a significant effect upon the managers’ perception of data quality. Besides, Rondeau et al. (2006) results also indicated that firms with high levels of organisational involvement in IS related activities have higher levels of IS department’s service quality. Although user involvement in ISs development is considered to be important to system-related quality (system quality and information quality), however the empirical evidence is divergent. Using the methods of controlled laboratory experiment and a field survey, Saleem (1996) found that users’ system-related functional expertise is contingent factors of the system-related outcome (system quality and information quality). In this study, we argue that the relationship between user involvement and the system-related outcome is indirect, rather than direct. The involvement of user can be expected to result

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in a better-quality system, through IS staffs integrate employee expertise, better understanding of users’ information requirement and supervisor evaluation of the system. In other words, the effects of user involvement on system-related outcome are mediated by service quality. The foregoing discussion suggests the relation model depicted in Figure 3. To test the model, this paper proposes the following testable hypotheses as Table 1. Figure 3

Table 1

The research model

Hypotheses of the research model

H1: User Involvement of HISs will positively affect service quality and user satisfaction H1a: User Involvement of HISs will positively affect service quality H1b: User Involvement of HISs will positively affect user satisfaction H2: Supervisor support of HISs will positively affect system quality, service quality, information quality and user satisfaction H2a: Supervisor support of HISs will positively affect system quality H2b: Supervisor support of HISs will positively affect service quality H2c: Supervisor support of HISs will positively affect information quality H2d: Supervisor support of HISs will positively affect user satisfaction H3: Service quality of HISs will positively affect and information quality H3a: Service quality of HISs will positively affect system quality H3b: Service quality of HISs will positively affect information quality H4: System quality of HISs will positively affect user satisfaction H5: Service quality of HISs will positively affect user satisfaction H6: Information quality of HISs will positively affect user satisfaction


3

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Research method

To examine the effect of the work environment perceptions on HISs quality (system quality, information quality and service quality) and user satisfaction, we adopted the questionnaire survey for data collection and examined our hypotheses by applying the Structural Equation Modelling (SEM) method to validate the model. The measurement instruments for variables in the questionnaire were developed from previous studies to enhance the variability and reliability. Responses to the various variables related to the perceptions of the individual subjects were measured using Likert-type scale.

3.1 Measurement and data collection The items of the questionnaire in the study either by adapting measures that had been validated by others researchers or by converting the definitions of constructs into a questionnaire format. All items were rated on 5-point Likert-type scales, ranging from 1 (strongly disagree) to 5 (strongly agree).

3.1.1 System quality System quality is defined as “The desired characteristics of the system itself, measured in term of ease-of-use, functionality and reliability, etc”. The construct was measured by the adjustment of DeLone and McLean’s (2003). The 7 items for the three system quality dimensions included in the study, robust (3 items), security (2 items) and ease-of-use (2 items) were generated from in-depth interviews with hospital end users and a review of relevant literature (Table 4 includes the items used to measure each dimension of the construct).

3.1.2 Information quality Information quality is defined as “The information product for desired characteristics such as accuracy, completeness, relevance, understandability and personalization”. The construct was measured by the adjustment of DeLone and McLean’s (2003). The 4 items for the two information quality dimensions included in the study, accuracy (2 items) and completeness (2 items) were generated from in-depth interviews with hospital end users, and a review of relevant literature (Table 5 includes the items used to measure each dimension of the construct).

3.1.3 Service quality Service quality is defined as “Discrepancy between users’ perceptions and expectation, measured in term of tangibles, reliability, responsiveness, assurance and empathy”. The construct was measured by the adjustment of Kettinger and Lee (1994) and Pitt et al. (1995). The 11 items for the five service quality dimensions included in the study, tangible (3 items), reliability (2 items), responsiveness (2 items), assurance (2 items) and empathy (2 items) were generated from in-depth interviews with hospital end users, and a review of relevant literature (Table 6 includes the items used to measure each dimension of the construct).

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3.1.4 User satisfaction User satisfaction is defined as “User response to the use of the output of ISs, measure in term of information quality and system performance”. The construct was measured by the adjustment of DeLone and McLean’s (2003). The 3 items for the user satisfaction included in the study were generated from in-depth interviews with hospital end users and a review of relevant literature (Table 7 includes the items used to measure each dimension of the construct).

31.5 User involvement User involvement is defined as “The extent of users’ participation in the system design”. The construct was measured by the adjustment of Saleem (1996). The 3 items for the user involvement included in the study were generated from in-depth interviews with hospital end users, and a review of relevant literature (Table 7 includes the items used to measure each dimension of the construct).

3.1.6 Supervisor support Supervisor support is defined as “The degree of supervisor provision of resource and helpful feedback on employees’ system usage”. The construct was measured by the adjustment of Jiang and Klein (2000). The 3 items for the supervisor support included in the study were generated from in-depth interviews with hospital end users, and a review of relevant literature (Table 7 includes the items used to measure each dimension of the construct). We used a self-report questionnaire to empirically validate the proposed research model. The data analysis proceeds according to the two-step approach recommended by Anderson and Gerbing (1988). Firstly, we assess the measurement model which consists of the six latent factors, includes the assessment of reliability, discriminant validity and convergent validity of the scales. Finally, we validate the structural model which represents the series of path relationships linking the six constructs. The subjects of the questionnaire were the employees of a medical centre in Taiwan who were the end users of HISs. There were 500 users who were randomising selected. A pretest of the questionnaire was conducted with 60 employees of this hospital. As they filled out the scale, respondents provided verbal and written feedback on the individual items. The items of the scale were adjusted by the feedback of respondents in order to make the meanings of the items clearer and easier. Of the 500 surveys distributed to the system users, a total of 252 usable surveys (50.4%) were returned. Of these respondents, 71% are women, 50% are age 30 and below, 21.8% are nurses and 48.4% of the length of using time is 3 hr. Table 2 presents descriptive statistics for the six constructs in the study. The mean scores for six constructs are all almost on the middle point of 5-point Likert-type scales, and show a reasonable dispersion in their distributions across the ranges.

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A study on the effect of work environment Table 2

Descriptive statistics

Construct

4

Mean

Standard deviation

System quality

3.07

0.57

Information quality

3.25

0.60

Service quality

3.11

0.67

User involvement

3.01

0.98

Supervisor support

3.50

0.71

User satisfaction

3.03

0.68

Empirical results

4.1 Measurement model results To validate the measurement model, three types of validity were assessed: content validity, convergent validity and discriminant validity. Content validity was done by interviewing senior system users and pilot-testing the instrument. And the convergent validity was validated by examining Cronbach’s α composite reliability and average variance extracted from the measures (Hair et al., 1998). As given in Table 3, the Cronbach’s α of every subscales range from 0.84 to 0.95, which are above the acceptability value 0.7 (Nunnally, 1978). Besides, the composite reliability values range from 0.80 to 0.95, and the average variances extracted by our measures range from 0.58 to 0.79, are all within the commonly accepted range greater than 0.5 (Hair et al., 1998). In addition, Tables 4–7 exhibit the factor loadings of the measures in our research model. As expected, all measures are significant on their path loadings at the level of 0.001. Discriminant validity of the constructs was validated by comparing the χ 2 values of the CFA with original subdimensions of every construct against other CFAs, which every possible combination of two dimensions (the correlation coefficient of two dimensions assigned to be one was examined. The χ 2 values of the CFA with original subdimensions of every construct were significantly better than any possible union of any two dimensions. Table 3

Results of confirmatory factor analysis Cronbach α

Composite reliability

Average variance extracted

System quality

0.84

0.80

0.58

Information quality

0.86

0.85

0.74

Construct

Service quality

0.95

0.95

0.79

User involvement

0.91

0.91

0.77

Supervisor support

0.92

0.92

0.78

User satisfaction

0.89

0.89

0.73

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Table 4

Factor loading of system quality subscale

Construct and scale items

Standardised loading (standard error)

System quality (GFI = 0.974, RMR = 0.020, NFI = 0.968, CFI = 0.982) Robust The speed of intranet is quick

0.842 (0.320)***

The reliability of the HISs is high

0.832 (0.308)***

The data accessible speed of the HISs is quick

0.735 (0.459)***

Security HISs provides the necessary user privilege to work

0.866 (0.344)***

HISs provides the suitable user privilege, so that database is secure

0.830 (0.525)***

Ease-of-Use HISs is easy to use

0.810 (0.311)***

HISs is convenient to use

0.689 (0.250)***

Robust

0.746 (0.443)***

Security

0.743 (0.360)***

Ease-of-Use

0.800 (0.448)***

***Path is significant at the 0.001 level. Table 5

Factor loading of information quality subscale



Information quality (GFI = 1.000, RMR = 0.001, NFI = 1.000, CFI = 1.000) Accuracy HISs can provide accuracy information

0.832 (0.308)***

HISs can provide precision information

0.880 (0.226)***

Completeness HISs can provide sufficient information to finish your jobs

0.872 (0.240)***

HISs can provide relevant information to finish your jobs

0.848 (0.281)***

Accuracy

0.859 (0.262)***

Completeness

0.854 (0.271)***

***Path is significant at the 0.001 level.

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A study on the effect of work environment Table 6

Factor loading of service quality subscale



Tangible (GFI = 0.929, RMR = 0.022, NFI = 0.952, CFI = 0.971) IS department has up-to-date hardware and software IS employees’ service attitude is nice

0.772 (0.403)*** 0.841 (0.292)***

Reliability IS employees are dependable IS employees provide reliable service IS employees provide trust service

0.869 (0.184)*** 0.903 (0.244)*** 0.869 (0.245)***

Responsiveness IS employees give prompt service to me IS employees provide timeliness service

0.790 (0.376)*** 0.927 (0.141)***

Assurance IS employees have the professional knowledge and technology I satisfy with IS employees’ professional knowledge

0.873 (0.238)*** 0.877 (0.230)***

Empathy IS employees have users’ best interests at heart IS employees care about my system requirements Tangible Reliability Responsiveness Assurance Empathy

0.894 (0.201)*** 0.790 (0.376)*** 0.853 (0.272)*** 0.861 (0.258)*** 0.873 (0.239)*** 0.912 (0.168)*** 0.953 (0.092)***

***Path is significant at the 0.001 level. Table 7 Factor loading of user involvement, supervisor support and user satisfaction subscales Construct and scale items User involvement (GFI = 1, RMR = 0.000, NFI = 1, CFI = 1) I join the design process of HISs I join the functional maintaining process of HISs I join the functional testing process of HISs Supervisor support (GFI = 1, RMR = 0.000, NFI = 1, CFI = 1) My supervisor promotes the usage of HISs My supervisor thinks HISs can enhance our jobs’ efficiency My supervisor thinks HISs can decrease the medical errors User satisfaction (GFI = 1, RMR = 0.000, NFI = 1, CFI = 1) I satisfy with the hardware of HISs I satisfy with the software of HISs Overall, I satisfy with HISs ***Path is significant at the 0.001 level.

Standardised loading (Standard error) 0.877 (0.231)*** 0.945 (0.106)*** 0.813 (0.339)*** 0.891 (0.206)*** 0.863 (0.256)*** 0.905 (0.181)*** 0.747 (0.442)*** 0.911 (0.170)*** 0.896 (0.198)***

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4.2 Structural model results To validate the measurement model, we used AMOS 6.0 to assess the analysis. As given in Table 8, the goodness-of-fit indices are almost within accepted thresholds, except for GFI, AGFI, NFI and RFI, which are all slightly lower than the commonly cited threshold. The goodness-of-fit indices suggest a suitable fit of the model to the data in the medical centre sample. Figure 4 and Table 9 shows the standardised LISREL path coefficients. All the paths are significant except the two paths: 1

the path linking user involvement and user satisfaction

2

the path linking information quality and user satisfaction.

We will discuss the non-significant paths in further detail in the conclusion. Table 8

Overall model fit

Structural model statistic

Fit indexes Recommended threshold

Reference

χ2

966.315

–

Degrees of freedom (d.f.)

440

–

χ 2 /d.f.

2.20

Below 5

Bollen (1989)

GFI

0.81

Above 0.9

Gefen et al. (2000) and Hair et al. (1998)

RMR

0.042

Below 0.08

Hair et al. (1998)

RMSEA

0.069

Below 0.08

Jarvenpaa et al. (2000)

AGFI

0.77

Above 0.8


NFI

0.86

Above 0.9


RFI

0.85

Above 0.9


IFI

0.92

Above 0.9


TLI

0.91

Above 0.9

Kline (1998)

CFI

0.92

Above 0.9


PNFI

0.76

Above 0.5

Byrne (2001)

PCFI

0.81

Above 0.5

Byrne (2001)

PGFI

0.68

Above 0.5

Byrne (2001)

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A study on the effect of work environment Figure 4

Table 9

LISREL significant paths (the dot lines represent the path is not significant, and the solid lines represent the path is significant)

Hypotheses validated results

Path H1a: User involvementÆ Service quality H1b: User involvementÆ User satisfaction H2a: Supervisor supportÆ System quality H2b: Supervisor supportÆ Service quality H2c: Supervisor supportÆ Information quality H2d: Supervisor supportÆ User satisfaction H3a: Service qualityÆ System quality H3b: Service qualityÆ Information quality H4: System qualityÆ User satisfaction H5: Service qualityÆ User satisfaction H6: Information qualityÆ User satisfaction

Results Supported Not supported Supported Supported Supported Supported Supported Supported Supported Supported Not supported

Standardised path estimate 0.302*** 0.035 0.341*** 0.461*** 0.408*** 0.155* 0.495*** 0.423*** 0.249** 0.446*** 0.071

*Path is significant at the 0.05 level, **Path is significant at the 0.01 level, ***Path is significant at the 0.001 level.

5

Conclusions

Using SEM, the proposed hypotheses are to validate the fit of empirical data and model. The conclusions are as follows: 1

according to the statistical results, the proposed model fits very well for the 252 samples of the medical centre

2

work environment perceptions (user involvement, supervisor support) are indeed the important antecedents of IS quality (system quality, information quality and service quality). Supervisor support has more important influence on IS quality than user involvement

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3

the effects of work environment perceptions on user satisfaction are mediated by service quality

4

service quality of IS departments has positive significant influences on system quality and information quality

5

according to the comparison of path coefficients, service quality has the most influence on user satisfaction.

In contrast to our predictions, the paths between user involvement and user satisfaction were not significant. One interpretation is that, the effect of user involvement on user satisfaction was fully mediated by service quality. In other words, it is possible that user involvement did not directly influence user satisfaction, rather indirectly influence user satisfaction via service quality. The findings confirm the need for further research on how user involvement affects user satisfaction, with the mediation of service quality. The lack of relationship between information quality and user satisfaction might be due to two factors. Firstly, the effect of end users’ perception of information quality on user satisfaction might be decline if they take it for granted. Secondly, the output information of HISs is almost routine and stable, because the health information is uniform among the hospitals in Taiwan. Due to the special context factor, the end users pay more attention to service quality, system quality and supervisor support rather information quality. Our findings suggest that work environment perceptions (user involvement, supervisor support) are two constructs worthy of inclusion in future studies in HISs contexts. There are some implications as follow to provide the managers of the hospitals: 1

User involvement is crucial to IS success. Empirical evidence on whether it has significant influence on IS quality, however, has been largely an open question. Using laboratory experiment design method, Saleem (1996) finds users’ systemrelated functional expertise moderating the outcome of participation. That is, whether user involvement has significant influence on IS quality is depending on end user possess relevant knowledge. Our results also reveal that the effects of user involvement on system-related quality (system quality and information quality) are mediated by service quality. The implication is that, at least in hospital context, if end users of HISs could join more actively the system development processes, IS employees would pay more attention on users’ requirements, which in turn would improve HISs system-related quality.

2

Our findings reveal that supervisor support has significant influence on system quality, information quality and service quality. In other words, end users’ social support is critical to HISs system success. On one hand, supervisor support has not only impact on their subordinates’ motivation to use HISs, but also promote well rapport between IS personnel and end users. On the other hand, supervisor support presents an important implication to IS personnel to monitor and improve the relationship quality of end users and system designers.

3

The research findings also posit that service quality is an important mediator between work environment perceptions (user involvement, supervisor support) and user satisfaction. Besides, service quality has significant influence on system quality and information quality. Owing to knowledge intense feature, it is necessary to provide reliable and relevant medical information to knowledge workers of hospitals to finish their jobs. Accordingly, the study shows that if IS


211

personnel possess patient attitude to fulfil end users’ requirements, the vision of improved operation performance of HISs and high degree of users’ satisfaction would be realised. Given the importance of HISs in today’s hospitals, we hope that our findings will be useful to the managers of hospitals aimed at enriching the practices regarding the enhancement of supervisor support, user involvement and service quality.

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Supply chain quality orientation: Does company profile matter? Roaimah Omar* Universiti Teknologi MARA (UiTM), Kampus Bandaraya, Malacca, Malaysia E-mail: [email protected] *Corresponding author

Suhaiza Zailani School of Management, University Sains Malaysia (USM), Minden 11800, Pulau Pinang, Malaysia E-mail: [email protected]

Mohamed Sulaiman Department of Business Administration, International Islamic University (IIU), Jalan Gombak, Malaysia E-mail: [email protected] Abstract: This study examines the Supply Chain Quality Orientation (SCQO) in Malaysian manufacturing organisations. About 550 questionnaires were distributed to the manufacturing organisations in Malaysia and 142 completed questionnaires were analysed to determine the level of SCQO. One-way ANOVA was applied to determine if significant difference exists between organisation profile and SCQO. The study found that the SCQO is quite substantial in the Malaysian manufacturing industry. In addition, it was found that there is no significant difference between organisation profile and SCQO. However, there is a significant difference in the SCQO between organisations that have EDI linkages with supply chain partners and organisations that are not EDI linked. Consequently, quality needs to be continuously managed from the supply chain standpoint. This study provides empirical evidence of SCQO in the manufacturing industry in Malaysia. Having an end-to-end supply chain manager and adoption of EDI are deemed vital in enhancing SCQO. Keywords: SCQO; supply chain quality orientation; end-to-end supply chain manager; EDI; electronic data interchange; manufacturing; Malaysia. Reference to this paper should be made as follows: Roaimah, O., Zailani, S. and Sulaiman, M. (2009) ‘Supply chain quality orientation: Does company profile matter?’ Int. J. Information Technology and Management, Vol. 8, No. 2, pp.214–230. Biographical notes: Roaimah Omar is an Associate Professor at the Faculty of Business Management, Universiti Teknologi MARA (UiTM), Malacca, Malaysia. Copyright © 2009 Inderscience Enterprises Ltd.

SCQO: Does company profile matter?

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Suhaiza Zailani is an Associate Professor of Operations Management in the School of Management, Universiti Sains Malaysia. Her primary research interests are in the areas of operations and production management, product and service quality management and productivity. Mohamed Sulaiman is a Professor of Operations Management, at the Department of Business Administration, Faculty of Economics and Management Science, International Islamic University, Malaysia. He received his MBA from Catholic University of Leuven, Belgium and a PhD from the University of Wales, Cardiff. He has written more than 50 academic papers, which have appeared in books and international journals.

1

Introduction

Market globalisation and competitive pressure has transformed today’s business environment from being merely inter company competition to inter supply chain competition (e.g. Tan et al., 1998; Vickery et al., 1999). Consequently, there is an increasing need to manage the company’s supply chain into an effective and efficient supply chain. Supply Chain Management (SCM) involves transforming a company’s supply chain into an efficient supply chain in meeting the customer requirements and satisfaction. SCM also enables organisations connected to the supply chain to improve its performance. The profound effect of SCM on the overall performance as opposed to the effectiveness of an individual organisation has prompted many organisations around the world to adopt SCM. In Malaysia, SCM has emerged as an essential strategy for manufacturing companies to improve performance and competitiveness. However, companies practicing SCM may not necessarily lead to supply chain excellence unless organisations involve suppliers in their quality management practices (Wong, 2002). The quality level delivered to the final customer is the result of quality management practices of each link in the supply chain. Since the quality of the final product is being influenced by the members in the supply chain (Sila et al., 2006), the efficiency of the supply chain can be affected, if it is interrupted due to product defects or late delivery of supplies. Besides, focusing on quality management solely at company level could still lead to potential problems such as defects, late delivery and failure to fulfil customer demand in the supply chain. To ensure that customer requirements are met, all members in the supply chain must be responsible for ensuring quality along the chain. Recognising that interdependencies exist between firms in the supply chain, SCQO among the supply chain partners is deemed pertinent. Therefore, this paper examines SCQO in Malaysia manufacturing companies and whether company profile has an effect on SCQO.

2

Supply chain quality orientation

The changes in the business landscape have seen SCM as one of the important business strategies (Morgan, 1997) and becoming the most powerful management practice (Theodorakioglou et al., 2006). This has driven many organisations to implement SCM as a source of competitive advantage. SCM is defined as the integration of key business processes from end user through original suppliers that provides products, services and

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R. Omar, S. Zailani and M. Sulaiman

information that add value for customers and other stakeholders (Lambert, 2004). It involves the flows of material, information and finance in a network consisting of customers, suppliers, manufacturers and distributors (Lee, 2000). The purpose of SCM is to make the whole supply chain more competitive rather than making profits at the expense of other supply chain partners. To achieve benefit from SCM the entire process or activities in the supply chain must be properly managed (McAdam and McCormack, 2001; Sahay et al., 2006; Tracey et al., 2005). It is implied that management of supply chain would be affected unless quality is managed along the supply chain (Kuei and Madu, 2001; Robinson and Malhotra, 2005). Besides, quality management has long been recognised to have an association with improvement in firm business performance and competitive edge (e.g. Bandyopadhay et al., 2003; Flynn et al., 1995; Roethlein et al., 2002) as well as continued survival in the global market place (Yeung et al., 2003). According to Tan et al. (2002), quality management is being emphasised in the firm strategic planning. A survey conducted in manufacturing companies in Turkey found that strategies supporting quality is fundamental requirement to sustain in the existing competitive market (Ulusoy, 2003). Therefore, in the context of supply chain, quality is an important component of supply chain strategy and top management priority in achieving supply chain objectives. It is viewed as a critical focus in SCM (Sahay et al., 2006) and has become a top strategic target in enhancing customer satisfaction (Theodorou and Florou, 2006). Recognizing the importance of quality in supply chain, Wong (2002) suggested that firms should involve their suppliers in their quality management practices. Consequently this would lead to an efficient supply chain. Besides, the supply network must be effectively managed in order to improve the quality of supplies and optimize the supply chain performance (Bititchi et al., 2005; Lummus et al., 1998). Supply network can be established by developing strategic partnership with critical suppliers (Lo and Yeung, 2004, 2006). Their study emphasised supplier quality management; encompassed supplier selection, supplier development and supplier integration which focused on upstream supply chain. However, supply chain quality should also involve the downstream supply chain members. It was found that quality performance and on time delivery performance improved by focusing on the downstream supply chain (Moedas, 2006). In addition, a supply chain performance can be enhanced if supply chain processes are coordinated between the upstream and downstream supply chain partners (Romano and Vinelli, 2001). This point out that supply chain quality should focus not only on the upstream supply chain members but also the downstream members (customers). This reiterates the point that achieving quality in the supply chain is the responsibility of every member of the supply chain (Kuei and Madu, 2001). It includes the manufacturing companies as well other entities in the supply chain such as the suppliers, subsuppliers and end-product manufacturers (Roethlein et al., 2002). In supply chain quality, quality management practices of individual firm must be extended beyond the company wide perspective to include suppliers, customers and other supply chain members (Lin et al., 2005; Robinson and Malhotra, 2005). To realise the full benefits from SCM, organisations should manage its quality with a supply chain perspective (e.g. Flynn and Flynn, 2005, Kannan and Tan, 2007). Then only quality problems throughout the supply chain can be alleviated or avoided. Hence, it is important for all firms to be coordinated in a strategic orientation (Mentzer et al., 2001). Supply chain orientation requires commitment of multiple firms to implement company strategic objectives (Mentzer et al., 2001). It is also essential for supply chain members to complement and mutually support an overall shared supply chain objectives. Besides


217

commitment among supply chain partners, interfirm coordination is the mechanism for the companies to achieve their supply chain strategy. In addition, having similar or compatible goals would also facilitate the supply chain strategy achievement (Defee and Stank, 2005). Likewise, coordination and integration of business process is imperative to improve the quality of the process, products and services in the supply chain (Robinson and Malhotra, 2005). They found that operations in the supply chain can be coordinated if the partners collaborate on quality issues. In addition it also requires effective communication between the supply chain partners regarding quality related events. Effective supply chain quality should enable firms to identify source of quality related risks and unwanted events and identify trends, subsequently to allow firms to response accordingly (Anonymous, 2005). Supply chain quality emphasise on achieving total achieving supply chain optimisation. The main goal of supply chain quality management is to achieve customer satisfaction, by enabling the condition and to enhance trust for total quality along the supply chain (Kuei and Madu, 2001). It requires joint short- and long-term goals and commitment of the entire supply chain members in meeting customer requirements (Kuei and Madu, 2001; Sila et al., 2006; Robinson and Malhotra, 2005). To minimise quality related problems at production start-up a strategic supply chain quality planning should be established with supply chain partners to minimise quality related problems at production startup (Batson and Mcgough, 2006). Strategic supply chain quality and documentations of quality requirements must be done in parallel with other supply chain planning activities. Customer needs must be first documented in planning for quality in supply chain. Quality requirement for each part must be predetermined and source from selected suppliers that met the quality criteria in ensuring product quality in supply chain. Commitment and cooperation among supply chain members allows process and activities to be coordinated from the source of materials to the manufacturing and products delivery. In addition, integration and coordination of participating organisations processes will permit continuous process and product improvements in the supply chain (Robinson and Malhotra, 2005). The use of IT can facilitate collaborating and coordinating information sharing, reduction in cycle time, inventories reduction and enhancing interorganisation relationship (Auramo et al., 2005; Bhatt and Troutt, 2005; Cross, 2000; Hsu, 2005; Levary, 2000; Olhager and Selldin, 2004). Higher usage of EDI is related to lowering of costs and organisational difficulties, reducing external pressure and supplier dependence in the supply chain (Sanchez and Perez, 2003). It is also recognised that supply chain manager plays significant role towards effective SCM (Dischinger et al., 2006). Improved communication between organisations at different levels in the supply chain is essential in supply chain quality. If there is effective communication between firms and its external partners, the quality practices across different levels in the supply chain should be in sync. The rank order of quality practices was found to be similar at different level in the supply chain (Roethlein et al., 2002). However, significant differences across the company position in the supply chain were found in terms of how responding company relates with its customers and supplier, the way its customers relates with the responding company, and product design process. Multidirectional quality awareness between customer and supplier would minimise misalignment of quality goals due to unidirectional communication (Roethlein and Ackerson, 2004). However, increasing complexity in the supply chain network and that quality management in supply chain requires it to be extended beyond the organisational boundary could affect the quality management practices at different levels in the supply

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chain and the overall level of quality orientation in supply chain. In this study, SCQO describes the organisation emphasis towards interorganisational quality efforts in supply chain involving supply chain partners. It involves, optimising the supply chain efficiency, joint quality planning and decision making, multidirectional quality awareness, joint development of business process aligning customer requirements, used of IT, establishment of quality performance and measurement and compatible quality goals and objectives.

3

Research objectives

Increasing complexity of today’s supply chain could deter organisations to develop effective SCQO as it requires the involvement of external organisations. As such the study was undertaken to determine the state of SCQO in the Malaysian manufacturing industry. In addition, the study examines if the organisation profile have a significant differences at the level of SCQO. The organisation profile includes, types of industry, company ownership, supply chain position, years in operation, market for main product, number of suppliers, product category, number of employees, EDI link with supply chain partners and end-to-end supply chain manager.

4

Research methodology

The selection of respondents for this study is based on the Federation of Malaysian Manufacturers (FMM) Directory 2005. The unit of analysis for this study is manufacturing organisation. Manufacturing industry is one of the most important sectors in Malaysia contributing significantly to the country’s economic growth and development. The manufacturing sector contributed 31.5% of the GDP an accounted for approximately 77.4% of the Malaysia’s total export in 2005 (MIDA, 2005). The responding organisations were selected based on a proportionate stratified random sampling. The manufacturing companies are stratified into six different industries. The industries comprised food and beverages products, plastics, chemical products, electrical and electronics, fabricated and basic metals and other manufacturing activities. These industries are considered as fast growing sectors in Malaysia (FMM Directory, 2005). The selection of company is randomly selected and questionnaire is the instrument used for this study. The questionnaires were sent by post and e-mail to the selected organisations. The respondents were given six weeks to answer the questions, after which reminders by post and e-mails are sent to respondents to request for their participation in the survey. The respondents comprised General Managers, Senior Managers, Heads of Department, Purchasing Managers, Quality Managers who were knowledgeable and experienced in the area of quality management and SCM. A total of 550 questionnaires were sent to the respondents of which 147 questionnaires were returned. However, only 142 questionnaires completed and considered usable for analysis whereas the other five questionnaires were not usable as certain sections were not answered by the respondents. The measurement items for SCQO are established based on related literature on supply chain quality (e.g. Kuei and Madu, 2001; Robinson and Malhotra, 2005; Roethlein and Ackerson, 2004) and interviews with practitioners in the


219

manufacturing organisation. Review of the existing literature on supply chain quality provides insight and understanding on the concepts and the important principles of supply chain quality. Since the literature were mainly based on studies conducted in USA, Italy, Hong Kong and Taiwan, discussions with five practitioners involved in supply chain and quality management were held to determine the validity of the items to ensure that the items proposed reflect the supply chain quality activities practiced in the Malaysian manufacturing context. Prior to the main survey, a pilot study was also conducted on eight companies to determine the suitability of the questionnaire items. The pilot study also helped to ensure that the target respondents equally understand the questions developed for this study. After the pilot study, the questionnaires were refined before embarking on the actual study which was carried out in October 2006. The respondents were asked to evaluate their SCQO with their major supply chain partners with respect to a main product. The items for SCQO are measured from 1 = ‘none’ to 5 = ‘very substantial’. The profile of the organisations is measured based on nominal scale. One way between groups ANOVA analysis is also performed to determine whether there is any significance difference in the SCQO mean scores with respect to the profile of the responding organisations. If significant difference exists among the profile, post-hoc test with Tukey HSD is applied to determine where the differences lie in the groups.

5

Factor analysis and Cronbach’s coefficient of reliability

Factor analysis was conducted via principal component analysis on all the ten items for SCQO. As shown in Table 1 all the items fall under one factor. The KMO result is 0.943 and Bartlett’s test which is significant at 0.000. The measure for sampling adequacy is above 0.50 which ranges from 0.926 to 0.966. The total variance explained is 69.6%, which is considered sufficient to explain the variance in the dependent variable. The items in the factorial group were also tested for reliability and the coefficient alpha (Cronbach’s) is 0.95 is high. Alpha values equal to or greater than 0.70 are deemed sufficient to measure reliability of items used in a construct (Nunnally, 1978). Table 1 No.

Factor analysis for SCQO Items

Factor 1

1

Optimising supply chain efficiency rather than maximising own firm performance

0.748

2

Joint establishment of short- and long-term quality planning with supply chain partners

0.848

3

Joint decision making with supply chain members/partners about ways to improve quality

0.835

4

Establishment of sharing responsibility for quality with supply chain partners

0.837

5

Multidirectional quality awareness between supply chain partners/members

0.848

6

Joint development of business process, which enables firm to be responsive to customers’ needs

0.852

7

Aligning customer requirements with supply chain partners/members

0.845

220


Table 1

Factor analysis for SCQO (continued)

No.

Items

Factor 1

8

Use information technology to enhance collaboration and trust with supply chain partners

0.806

9

Joint establishment of quality performance and measurement with supply chain partners

0.854

10

Quality goals and objectives are compatible with supply chain partners/members

0.867

Eigen values

6.963

Percentage of variance (2 decimal)

69.63

Reliability (Cronbach’s alpha)

0.95

Mean

3.35

SD

0.85

Note: Extraction method: principal component analysis with one component extracted.

6

Results

Table 2 shows that 50% of the respondents were from other manufacturing activities such as automobile industry, wood based, textile and apparel. Electrical and electronics accounts for 18.3% while food product and beverage industry is the smallest group with 9.2% of the total respondents. 51.4% of the respondents are the final product manufacturer, while 32.6% and 15.9% were 1st tier and 2nd tier suppliers respectively. Majority of the responding companies (62.1%) market their products to both domestic and international markets, 24% of the manufacturing companies exported 100% of the products produced and only 13.6% manufactured the products for domestic market. About 80.3% of the manufacturing companies had been in business for more than 15 years and less than 1% had been operating less than five years. Since the unit of analysis is organisation, it is appropriate to source information from the right person who are experienced and knowledgeable in the quality and SCM issues. Therefore for this study, the respondents comprised those in the top management positions. This includes, Director, General Manager, Senior Manager, Purchasing Manager, Quality Assurance Manager and Executive position (Table 3). The mean age of the respondents is 39 years old and they have been with the company on average more than ten years (Table 4). The overall mean score for SCQO is 3.35 and SD is 0.85 (Table 5). Item statistics were also conducted on each of the items used to measure SCQO. Table 6 indicates the variance among the items is quite high with the SD for most items except for item 1 and 5 exceeding more than 1 SD. Optimising supply chain efficiency rather than maximising own firm performance has the lowest mean of 3.10 and most of the organisations responded ‘moderately substantial’ or ‘3’with respect to item 1. For all other items (items 2–10) the majority of the respondents answered ‘4’ or ‘substantial’. As indicated in Table 6, ‘joint decision making with supply chain members/partners about ways to improve quality has the highest mean of 3.46.

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SCQO: Does company profile matter? Table 2

Profile of the responding companies

Variable Industry type

Company ownership

Years in operations

Average annual sales (millions of Ringgit)

No. of employees

Position in supply chain Market

Number of suppliers

Product category

EDI linked with supply chain members/partner End-to-end supply chain manager

Companies’ profile Food products and beverages Rubber and plastic products Chemical and chemical products Electrical and electronics Fabricated metals, basic metals and other non-metallic product Other manufacturing activities Malaysian (100%) Majority Malaysia-owned Majority non-Malaysia owned Non-Malaysian (100%) Non-response Less than or equal to five years 6–10 years 11–15 years More than 15 years 26–100 101–200 201–300 301–400 401–500 More than 500 65–200 201–400 401–600 601–800 More than 800 Final product manufacturer 1st tier/direct supplier Tertiary/2nd tier indirect supplier Domestic International Both domestic and international Single supplier 2–5 suppliers 6–10 suppliers 11 or more suppliers Consumer products Industrial products Others (e.g. IT products) Yes Developing No Yes Plan to have one No

Frequency 13 24 10 26 19

Percentage 9.2 16.9 7.0 18.3 13.4

50 51 20 36 34 1 1 11 16 114 40 13 11 5 2 15 23 52 15 8 31 71 45 22 19 34 87 3 78 10 50 57 57 26 19 19 99 33 16 90

35.2 35.9 14.1 25.4 23.9 0.7 0.7 7.7 11.3 80.3 46.5 15.1 12.8 5.8 2.3 17.4 17.8 40.3 11.6 6.2 24.0 51.4 32.6 15.9 13.6 24.3 62.1 2.1 55.3 7.1 35.5 40.7 40.7 18.6 13.9 13.9 72.3 23.7 11.5 64.7

222 Table 3

R. Omar, S. Zailani and M. Sulaiman Respondents’ personnel profile

Designation

Frequency

%

Director/General Manager/Senior Manager

20

14.4

Procurement/Purchasing/Materials/Supply Chain Manager/Manager

53

38.1

Quality Assurance Manager/Quality Control Manager/Quality Engineer

39

28.1

Senior Executive/Executive

26

18.7

1

0.7

Others (technical buyer) Table 4

Respondents’ age and number of years with company

Age Years with company Table 5

No. 1

2

3

4

5

6

SD

38.99 10.41

8.03 7.46

Descriptive statistics for SCQO

SCQO Table 6

Mean

N

Mean

SD

142

3.35

0.85

Items statistics for SCQO Items Optimising supply chain efficiency rather than maximising own firm performance Joint establishment of short- and long-term quality planning with supply chain partners Joint decision making with supply chain members/partners about ways to improve quality Establishment of sharing responsibility for quality with supply chain partners Multidirectional quality awareness between supply chain partners/members Joint development of business process which enables firm to be responsive to customers’ needs

1

2

4

5

Total

Mean

SD

N

10

20

68

3

34

10

142

3.10

0.97

%

7

14.1

47.9

23.9

7

100

N

8

16

47

53

18

142

3.40

1.03

%

5.6

11.3

33.1

37.3

12.7

100

N

6

20

38

58

20

142

3.46

1.04

%

4.2

14.1

26.8

40.8

14.1

100

N

7

22

36

63

14

142

3.39

1.02

%

4.9

15.5

25.4

44.4

9.9

100

N

8

12

52

60

10

142

3.37

0.94

%

5.6

8.5

36.6

42.3

7

100

N

14

12

46

56

14

142

3.31

1.09

%

9.9

8.5

32.4

39.4

9.9

100

223

SCQO: Does company profile matter? Table 6 No. 7

8

9

10

Items statistics for SCQO (continued) Items Aligning customer requirements with supply chain partners/members Use information technology to enhance collaboration and trust with supply chain partners Joint establishment of quality performance and measurement with supply chain partners Quality goals and objectives are compatible with supply chain partners/members

N

1 10

2 14

3 47

4 52

5 19

Total 142

%

7

9.9

33.1

36.6

13.4

100

N

10

18

48

52

14

142

%

7

12.7

33.8

36.6

9.9

100

N

8

17

48

54

15

142

%

5.6

12

33.8

38.0

10.6

100

N

7

18

39

60

18

142

%

4.9

12.7

27.5

42.3

12.7

100

Mean 3.39

SD 1.07

3.30

1.04

3.36

1.01

3.45

1.03

The detailed breakdown for each item based on frequency tabulations for different level of SCQO is shown in Table 6. The highest percentage/or highest number of responses for each item is highlighted in italics. The percentage of respondents indicated ‘very substantial’ for item 1 is only 7% which is considerably low with most of the respondents answered ‘moderately substantial’ which accounted for almost 50% of the respondents. This shows that generally manufacturing companies in Malaysia are realising the importance of optimising supply chain efficiency than firm own performance. For items 2–10, most of the respondents answered ‘substantial’ which ranged from 36.6% for ‘aligning customer requirements with supply chain partners’ and ‘using IT to enhance collaborate and enhance trust with supply chain partners’ to 44.4% for ‘sharing of quality responsibility with supply chain partners’. Results of one-way ANOVA between groups indicates the significance values (Sig.) for all the groups were greater than 0.05. Therefore, the mean score for SCQO does not vary for each group of the company profile except for ‘EDI’ and ‘end-to-end supply chain manager’. The one way-ANOVA (Table 7) indicates that the significance values for between and within groups were greater than 0.05 for most of company profile. Therefore, there is no significant difference in the mean scores of SCQO in each of the different groups with respect to company profile (industry type, company ownership, supply chain position, company age, market for main product, number of suppliers and product category). However, there is significant difference at p < 0.05 in the SCQO mean scores for the EDI groups, and ‘end-to-end supply chain manager’. One way between groups ANOVA with post-hoc tests indicates there is significant difference in SCQO amongst the EDI group that is group 1 = ‘have EDI’, group 2 = ‘Developing EDI’ and group 3 = ‘No EDI’ with supply chain partners with F-value of 5.038 and an overall significant value of 0.008. The post-hoc comparison using Tukey HSD revealed (Table 8) that the statistical significant difference in SCQO means score is between group 1 (M = 3.82, SD = 0.81) and group 3 (M = 3.20, SD = 0.89). Group 2 (M = 3.52, SD = 0.45) did not show any significant difference from group 1 to 3.

224 Table 7

R. Omar, S. Zailani and M. Sulaiman SCQO: one-way ANOVA Mean

SD

3.19 3.10 3.38 3.56 3.35

1.11 0.79 0.77 0.81 0.91

Company ownership

Food products and beverages Rubber and plastic products Chemical and chemical products Electrical and electronics Fabricated metals, basic metals and other non-metallic product Other manufacturing activities Malaysian owned (100%)

3.40 3.13

Supply chain position

Majority Malaysian-owned Majority non-Malaysian owned Non-Malaysian (100%) Final product manufacturer

Years in operation

Industry type

Market for main product

Number of suppliers

Product category

Number of employees

EDI linked with supply chain partners

End-to-end supply chain manager

F

Sig.

0.837

0.526

0.85 0.90

1.895

0.133

3.38 3.53 3.45 3.22

0.68 0.72 0.85 0.83

1.617

0.202

1st tier/direct supplier 2nd tier /indirect supplier Less than or equal to five years

3.45 3.54 2.70

0.89 0.86 0.248

0.863

6–10 years 11–15 years More than 15 years Domestic

3.36 3.28 3.37 3.53

0.63 1.00 0.86 0.70

0.731

0.483

International Domestic and international Single supplier

3.43 3.37 2.48

0.90 0.84 1.33

1.536

0.208

2–5 suppliers 6–10 suppliers 11 or more suppliers Consumer products Industrial products Others (IT products) Less than 200

3.30 3.49 3.46 3.31 3.49 3.36 3.22

0.86 0.69 0.86 0.91 0.79 0.85 0.93

1.359

0.260

0.362

0.836

201–400 401–600 601–800 More than 800 Have EDI

3.35 3.28 3.31 3.48 3.82

0.74 0.91 1.04 0.91 0.81

5.038

0.008

Developing EDI No EDI Yes

3.52 3.20 3.96

0.45 0.89 0.56

13.640

0.000

Plan to have one No

3.31 3.12

0.71 0.87

225

SCQO: Does company profile matter? Table 8

Post-hoc test – multiple comparisons

Variable

Groups

EDI

1. Have EDI

Developing EDI No EDI

2. Developing EDI

Have EDI No EDI

3. No EDI End-to-end supply chain manager

1. Yes 2. Plan to have one 3. No

Mean difference

Sig.

0.31

0.496

0.62* –0.31

0.009 0.496

0.32

0.282

Have EDI

–0.62*

0.009

Developing EDI

–0.32

Plan to have one

0.65*

0.282 0.021

No

0.84*

0.000

Yes

–0.65*

0.021

No

0.19

0.653

Yes

–0.84*

0.000

Plan to have one

–0.19

0.653

*The mean difference is significant at the 0.05 level.

In addition, there is a significance difference in SCQO amongst the end-to end supply chain manager group that is group 1 = ‘have end-to-end supply chain manager’, group 2 = ‘No end-to-end supply chain manager’ and group 3 = ‘plan to have end-to-end supply chain manager’ with F-value of 13.64 and an overall significant value of 0.000. Post-hoc comparison using Turkey HSD show that there is statistical significant difference between groups 1 (M = 3.96, SD = 0.56) and 2 (M = 3.31, SD = 0.71) and groups 1 and 3 (M = 3.12, SD = 0.87).

7

Discussion and conclusion

The study attempted to determine the level of SCQO in manufacturing companies in Malaysia and whether it varies according to the organisations profile. The company profile includes industry type, company ownership, supply chain position, company age and market for main product, number of suppliers and number of employees. In addition, the study also investigates whether EDI linked companies and companies with end-to-end supply chain managers have an effect on SCQO. This study found that SCQO in Malaysia range from moderately substantial to substantial with overall mean score of 3.35 (Table 5). The results suggest that manufacturing companies in Malaysia are inclined towards supply chain quality perspective although it is not fully comprehensive. Thus in order for supply chain members to reap benefits from the improvements in supply chain quality, SCQO in Malaysian manufacturing organisations should be further developed. The results of one-way ANOVA show that there is no statistical significant difference on SCQO with respect to company profile except for ‘EDI’ and ‘end-to-end supply chain manager’. Although Electronics and Electrical industry has the highest mean (3.56) for SCQO and rubber and plastics industry has the lowest SCQO mean score (3.10) the level of SCQO generally does not vary across the manufacturing industry in Malaysia. Similarly, SCQO with respect to company position in the supply chain in Malaysia also

226


indicate no statistical significant difference. The level of SCQO between final product manufacturer, 1st tier supplier and 2nd tier suppliers also indicates no significant variation. The reason could be attributed to the existence of compatible quality goals, joint establishment of short- and long-term quality planning, and joint establishment of quality performance with supply chain partners across the different levels in the supply chain. Common objectives and communication of quality performance set by the manufacturer on its first tier suppliers ensure that customer expectation are fulfilled (Robinson and Malhotra, 2005). The role and responsibility of 1st tier suppliers is to communicate with 2nd tier suppliers to ensure that quality requirements are met. As a result, the quality across the different tiers in the supply chain is consistent. It is the responsibility of the manufacturer to communicate to the suppliers its quality goals, which is based on customer requirements. SCQO is consistent as there is no significant variation across the different tiers in the supply chain. This shows the supply chain members may have clear understanding of the quality requirements of its customers. Although companies in the supply chain are concerned about their customer satisfaction, communication of quality goals is not consistent throughout the supply chain (Roethlein and Ackerson, 2004). Companies at different levels in the supply chain have different goals. Unidirectional of quality goals could result in misalignment and misinterpretation of quality goals. This is not the case for manufacturing companies in Malaysia as multidirectional quality awareness among the supply chain partners is quite substantial. Multidirectional communications enable suppliers and customers to understand each others requirements and ensure quality in supply chain. Joint establishment of quality planning and compatible quality goals with supply chain partners are also substantial. Majority of the responding companies (55.3%) have between 2 and 5 suppliers. This is in agreement with literature (Carter et al., 1998; Cox, 2001; Kannan and Tan, 2002, 2004; Wong and Fung, 1999), which established that companies strived to develop strategic partnership with few suppliers to improve quality of their products. Only 2.1% relies on single suppliers. Relying on single supplier could pose risk to the manufacturers in case of supplier failing to meet the expected quality requirement or on time delivery. The efficiency in the supply chain is affected (Hoske, 2001) if there are defects in products. However, organisations that sourced from a single supplier were found to be more successful in implementing quality management programmes (Carter et al., 1998). Nonetheless, in this study number of suppliers shows no significant effect on SCQO. The study also found that there is no significance difference in SCQO between older companies and newer companies. SCQO is also similar in companies that have been operating longer than 15 years and in companies that were established less than 15 years. Therefore, older companies are not necessarily better off in SCQO in relation to younger companies. Similarly, market for main product, whether for local or international market has no effect on the level of SCQO. In general, SCQO is similar irrespective of the market for the main product. Hence, the SCQO in Malaysia can be regarded as similar regardless of differences in company profile. On the other hand, the firms with EDI shows a significant difference on SCQO from those companies that do not have EDI link with their supply chain partners. This is consistent with Ang (2000) who established that IT facilitates quality management processes. IT enables firms in the supply chain to supply products to customer in the right place and time (Kuei and Madu, 2001; Kuei et al., 2002, 2005). The use of Information Technology (IT) such as Electronic Data Interchange (EDI) and extranets


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facilitate the necessary interactions and coordinate transactions. Information sharing across internal functions and inter-organisations can be supported by technologies such as e-mail, video-conferencing and computer-to-computer links such as EDI, intranet, internet and extranet (Bhatt and Troutt, 2005). Although EDI results in significant variation in SCQO, the percentage of companies that actually have EDI linked with supply chain partners are very low. Most of the responding organisations do not have EDI. IT capabilities are needed to capture and analyse enterprise wide data, communicate and facilitate information sharing throughout the organisation (Bhatt and Troutt, 2005) and across the supply chain (Fawcett and Cooper, 2001). In fact, IT is vital for effective management of supply chain as integration of one supply chain with another or process integration across firm boundaries rely on the capability of IT (Gunasekaran and Ngai, 2004). A significant difference in SCQO also exists in companies that have end-to-end supply chain manager. Companies with end-to-end supply chain manager indicates a higher mean score of 3.92 compare to those companies without end-to-end supply chain manager which shows a lower mean score of 3.12. Having end-to-end supply chain manager is essential in today’s complex and overlapping supply chain environment. Mapping and tracking the physical flows or movement of goods from sourcing of raw materials to point of consumption (customer) is essential. These points out that the success of supply chain quality requires the effective and professional supply chain manager. Therefore, it is essential for supply chain managers to identify who their key supply chain partners, what and type/level of business process to integrate, knowing the supply chain network structure (Lambert et al., 1998). Supply chain manager must be able to develop, implement integrated supply chain solutions, and possess skills and capabilities in functional, technical, leadership, global management, experience and credibility (Dischinger et al., 2006). Although organisation profile seems not to have an impact on SCQO, this study has however, managed to explore the SCQO in the context of manufacturing companies in Malaysia. Quality needs to be continuously managed from the supply chain standpoint rather than from the individual firm perspective. This requires joint effort on quality related matters within the firm and across the external organisations in the supply chain. The industry should realise the importance of end-to-end SCM, the role and responsibilities of supply chain manager and EDI link with supply chain partners. Future study can investigate the reasons for low EDI in manufacturing companies or determinant factors of EDI acceptance. Although it is frequently mentioned in the literature that SCM technology facilitates information exchange (Moberg et al., 2002) through collaboration (Mentzer et al., 2000), the adoption for EDI is low in Malaysian manufacturing industries. There could possibility be a lack of trust amongst the supply chain partners. It is rather difficult to use or implement SCM applications if there is a lack of trust between organisations and its suppliers (Rupple, 2004). Lack of resources and weak relationship with supply chain members could deter implementation of supply chain initiatives (Mentzer et al., 2000). In the future, in depth study could be conducted in a specific company or industry to determine how manufacturer implements quality management in the supply chain. In addition as the service industry is growing in its importance in terms of its role in the Malaysian economy, it might be interesting to investigate the SCQO in the service sector.

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