Healthcare Operations Management Through Use of Simulation 9781781906125, 9781781906118

Citation preview

jeim cover (i).qxd

02/02/2012

10:07

Page 1

ISSN 1741-0398

Volume 25 Numbers 1 and 2 2012

Journal of

Enterprise Information Management

www.emeraldinsight.com

Journal of

ISSN 1741-0398

Enterprise Information Management

Volume 25 Number 1 2012

Editor Professor Zahir Irani

Access this journal online _______________________________

2

Editorial review board____________________________________

3

Editorial ___________________________________________________

4

CONTENTS

The adoption of ICT in project-based and traditional organizations: evidence from Finnish and Swedish companies Maqsood Sandhu and Mian Ajmal _________________________________

7

Deciding the level of information systems outsourcing: proposing a framework and validation with three Indian banks Umesh Gulla and M.P. Gupta _____________________________________

28

Factors affecting ERP system implementation effectiveness Dimitrios Maditinos, Dimitrios Chatzoudes and Charalampos Tsairidis ____

60

Retrieving relevant information: traditional file systems versus tagging Thomas W. Jackson and Stephen Smith _____________________________

79

This journal is a member of and subscribes to the principles of the Committee on Publication Ethics

www.emeraldinsight.com/jeim.htm As a subscriber to this journal, you can benefit from instant, electronic access to this title via Emerald Management eJournals. Your access includes a variety of features that increase the value of your journal subscription.

Structured abstracts Emerald structured abstracts provide consistent, clear and informative summaries of the content of the articles, allowing faster evaluation of papers.

How to access this journal electronically

Additional complementary services available

Our liberal institution-wide licence allows everyone within your institution to access your journal electronically, making your subscription more cost-effective. Our web site has been designed to provide you with a comprehensive, simple system that needs only minimum administration. Access is available via IP authentication or username and password.

When you register your journal subscription online you will gain access to additional resources for Authors and Librarians, offering key information and support to subscribers. In addition, our dedicated Research, Teaching and Learning Zones provide specialist ‘‘How to guides’’, case studies, book reviews, management interviews and key readings.

To benefit from electronic access to this journal, please contact [email protected] A set of login details will then be provided to you. Should you wish to access via IP, please provide these details in your e-mail. Once registration is completed, your institution will have instant access to all articles through the journal’s Table of Contents page at www.emeraldinsight.com/ 1741-0398.htm More information about the journal is also available at www.emeraldinsight.com/jeim.htm

E-mail alert services These services allow you to be kept up to date with the latest additions to the journal via e-mail, as soon as new material enters the database. Further information about the services available can be found at www.emeraldinsight.com/alerts

Emerald online training services Visit www.emeraldinsight.com/help and take an Emerald online tour to help you get the most from your subscription.

Emerald Research Connections An online meeting place for the world-wide research community, offering an opportunity for researchers to present their own work and find others to participate in future projects, or simply share ideas. Register yourself or search our database of researchers at www.emeraldinsight.com/connections

Key features of Emerald electronic journals

Choice of access

Automatic permission to make up to 25 copies of individual articles This facility can be used for training purposes, course notes, seminars etc. within the institution only. This only applies to articles of which Emerald owns copyright. For further details visit www.emeraldinsight.com/copyright Online publishing and archiving As well as current volumes of the journal, you can also gain access to past volumes on the internet via Emerald Management eJournals. You can browse or search these databases for relevant articles. Key readings This feature provides abstracts of related articles chosen by the journal editor, selected to provide readers with current awareness of interesting articles from other publications in the field. Non-article content Material in our journals such as product information, industry trends, company news, conferences, etc. is available online and can be accessed by users. Reference linking Direct links from the journal article references to abstracts of the most influential articles cited. Where possible, this link is to the full text of the article. E-mail an article Allows users to e-mail links only to relevant and interesting articles to another computer for later use, reference or printing purposes.

Electronic access to this journal is available via a number of channels. Our web site www.emeraldinsight.com is the recommended means of electronic access, as it provides fully searchable and value added access to the complete content of the journal. However, you can also access and search the article content of this journal through the following journal delivery services: EBSCOHost Electronic Journals Service ejournals.ebsco.com Informatics J-Gate www.j-gate.informindia.co.in Ingenta www.ingenta.com Minerva Electronic Online Services www.minerva.at OCLC FirstSearch www.oclc.org/firstsearch SilverLinker www.ovid.com SwetsWise www.swetswise.com

Emerald Customer Support For customer support and technical help contact: E-mail [email protected] Web http://info.emeraldinsight.com/products/ subs/customercharter.htm Tel +44 (0) 1274 785278 Fax +44 (0) 1274 785201

Editorial review board

EDITORIAL REVIEW BOARD

Professor Majed Al-Mashari King Saud University, Saudi Arabia Professor Mustafa Alshawi University of Salford, UK Professor Norm Archer McMaster University, Canada Dr Frank Bannister Trinity College, Dublin, Ireland Professor France Belanger Virginia Tech, USA Professor Izak Benbasat University of British Columbia, Canada Dr Gu¨lc¸in Bu¨yu¨ko¨zkan Galatasaray University, Turkey Professor Steven I-Jy Chien New Jersey Institute of Technology, USA Dr King-Lun Choy The Hong Kong Polytechnic University, Hong Kong Professor Gail Corbitt California State University, Chico, USA Professor Wendy Currie Warwick University, UK Professor Tom Davenport Babson College, USA Dr Yogesh K. Dwivedi School of Business & Economics, Swansea University, UK Dr Amany Elbanna Royal Holloway University of London, UK Dr Tony Elliman Brunel University, UK Professor Galal H. Galal-Edeen Cairo University, Egypt Professor Robert D. Galliers Bentley University, USA Dr George M. Giaglis Athens University of Economics and Business, Greece Dr Reyes Gonza´lez University of Alicante, Spain Professor A. Gunasekaran University of Massachusetts, Dartmouth, USA Professor Ray Hackney Brunel Business School, Brunel University, UK John F. Hill University of Warwick, UK Professor Paul Hong University of Toledo, USA Dr Jimmy Huang Warwick Business School, UK

Dr Stephen Jones Conwy County Borough Council, UK Professor Cengiz Kahraman Istanbul Technical University, Turkey Professor Rongbin W.B. Lee The Hong Kong Polytechnic University, Hong Kong Professor Ben Light University of Salford, UK Professor Juan Llopis University of Alicante, Spain Dr Andrew C. Lyons University of Liverpool, UK Dr Amelia A. Maurizio SAP Global Communications, USA Dr Ulf Melin Linkoping University, Sweden Dr Navonil Mustafee Swansea University, UK Professor Nelson Oly Ndubisi Nottingham University Business School, Malaysia Professor Shan Ling Pan National University of Singapore, Singapore Professor Rob Procter University of Manchester, UK Professor Antonio Rizzi University of Parma, Italy Dr Nicholas C. Romano Jr Oklahoma State University, Tulsa, USA Professor Da Ruan Belgian Nuclear Research Centre (SCK*CEN), Belgium Professor Joseph Sarkis Clark University, USA Professor Amir M. Sharif Brunel Business School, UK Dr Markus Strohmaier Graz University of Technology, Austria Professor Glenn Stewart Queensland University of Technology, Australia Dr Marinos Themistocleous University of Piraeus, Greece Dr Edward F. Watson Louisiana State University, USA Dr Frithjof Weber Airbus Deutschland GmbH, Germany Professor Tim Weitzel Bamberg University, Germany Professor Michael Williams Swansea University, UK

3

Journal of Enterprise Information Management Vol. 25 No. 1, 2012 p. 3 # Emerald Group Publishing Limited 1741-0398

JEIM 25,1

4

Journal of Enterprise Information Management Vol. 25 No. 1, 2012 pp. 4-6 q Emerald Group Publishing Limited 1741-0398

Editorial It gives us great pleasure to welcome our readers to the first issue of the volume 25 of Journal Enterprise Information Management ( JEIM), and express our appreciation to them for their continuous support and acknowledgment during the preceding years. The continuous update of the journal’s scope to promote theory and practice has led to an increase in regular research paper submissions. These two issues incorporate quality submissions focusing on providing a mixture of conjectural and practical contributions. The first issue of volume 25 commences with a research paper by Maqsood Sandhu and Mian Ajmal, entitled “The adoption of ICT in project-based and traditional organisations: evidence from Finnish and Swedish companies’. Their research investigates the adoption of electronic communication tools and seeks to shed more light on diffusion. A challenging task for project-based (PBO) and traditional business organisations (TBO). The authors collected data through three surveys, one total population survey in the Finnish and Swedish house building industries representing traditional business organisations, together with a focused and a total population survey in project-based organisations. The empirical findings illustrate a difference in attitude between the employees of TBOs and PBOs. In addition to these findings, the authors also reported that electronic document management and scheduling were more prominent among PBOs, because these firms exhibit more inter-organisational communication. Despite these results, the findings are limited to the context of project-based and traditional business organisations. The authors in this research emphasise that PBOs make more inter-firm collaboration efforts and thus, require more extensive communication systems for inter-organisational links. Based on this argument, the authors assert that further research is needed in other industries to validate the present research findings. In analysing the use of ICT in organisations, the authors identified the type of e-communication tools that are more tightly coupled with the management and the ways in which firms can benefit from these tools for organisational governance. The authors claim that this research is one of the few studies to examine the uses of ICT in a PBO and TBO context and especially in Finnish and Swedish background. The above research paper is followed by Umesh Gulla and M. P. Gupta, entitled “Deciding the level of information systems outsourcing: proposing a framework and validation with three Indian banks”. The authors in this paper recommend a framework that would guide the practicing manager to decide the degree of IS outsourcing. This framework is derived from the findings of a previous empirical study and qualitative inputs. Thereafter, the authors employ the analytical hierarchy process (AHP) technique to apply the framework. The framework has been validated in three India-based banks. This framework supports the strategic alignment between the business strategy and information system strategy. The authors claim that the application of framework illustrates managers’ preferences towards high IS outsourcing. From their empirical findings, the authors accentuate that strategic alignment and medium term impact emerged as the key factors in IS outsourcing. The

authors further claim the validity of their proposed framework by testing their framework in three local Indian banks. However, there are some limitations in this research i.e. the validation exercise was based on a small sample due to resources constraints, thus a study involving a larger sample is desired. The authors also recommend reconsidering the framework on regular intervals and making appropriate changes in decision factors. Despite the limitations, the authors assert that the framework will prove helpful to managers in identifying the critical factors in the IS outsourcing process, which can act as useful inputs in taking informed decisions on the degree of IS outsourcing to adopt. With regards to novelty in this research paper, the authors allege that this research fills a gap by suggesting a practice-oriented framework that will guide the decision-makers to undertake a systematic and structured approach in arriving at outsourcing decision. Then we have a research paper by Maditinos et al., entitled “Factors affecting ERP system implementation effectiveness”. The authors propose a conceptual framework that investigates the way that human inputs are associated with communication effectiveness, conflict resolution and knowledge transfer in the ERP consulting process including the effects of these factors on ERP system effective implementation. The authors validated the proposed conceptual framework through a questionnaire base survey, distributed to a group of Greek companies that have implemented an ERP system. The empirical data were analysed using the “structural equation modelling” technique. The main findings illustrate that the assistance provided by external consultants during the ERP implementation process is more essential than from the top management. Knowledge transfer is an extremely significant factor for ERP system success, knowledge transfer concerning technical aspects of ERP systems is more important than effective handling of communication, and conflict resolution among organisational members. Lastly, the role of top management support seems to be of less importance that the one provided by users. Despite the results, the present study is limited to poor definition of its population and the relatively smaller sample size. The paper illustrates that adopting companies should emphasize in order to successfully implement an ERP system and, therefore, harvest its potential benefits. The authors claim that their conceptual framework examines vital issues concerning ERP system effective implementation, thus, providing valuable outcomes for decision makers and academics. Additionally, the authors thoroughly examined the contribution of “people” in ERP implementation, arguing that people decide the success and/or failure of the ERP system. The last paper of this issue is by Jackson and Smith, entitled “Retrieving relevant information: traditional file systems versus tagging”. In a business context, the authors investigate and clarify whether tagging is a more effective method of discovering relevant information when compared to traditional hierarchical filing systems. In so doing, a five-step interpretive hybrid approach of using a focus group, questionnaires and SWOT analysis was used to test the proof of concept of tagging files compared to a traditional hierarchical filing system. The participants were encouraged to use the questionnaires and the SWOT analysis to record their thoughts anonymously whilst the focus groups allowed elaboration and discussion to help understand the true feelings and thoughts of the group collaboratively. The authors empirically illustrate that the traditional hierarchical filing systems can lead to the retrieval of irrelevant information or to none at all, even though the information exists. This study has shown

Editorial

5

JEIM 25,1

6

that tagging could provide a cost-effective solution by providing a better structured filing system that can help reduce duplication and the retrieval of irrelevant information. This research work is limited by the lesser number of participants from just one organisation. Thus, generalisation from this study to the wider population must be done with great care. With regards to consequences on practice, the organisations should evaluate the functionality of their chosen operating system and Information Store software in light of the potential benefits offered by tagging, and costly limitations of traditional file stores. The authors claim to contribute to the information retrieval and information overload literature by studying the affect tagging files has on an organisation. It provides an insight to the future of filing systems for management and triggers future empirical work into reducing information overload in the workplace. Zahir Irani Editor, and Yogesh Dwivedi Assistant Editor

The current issue and full text archive of this journal is available at www.emeraldinsight.com/1741-0398.htm

The adoption of ICT in project-based and traditional organizations Evidence from Finnish and Swedish companies Maqsood Sandhu Faculty of Business and Economics, United Arab Emirates University, Al Ain, United Arab Emirates

Mian Ajmal

The adoption of ICT in organizations 7 Received 30 October 2010 Revised 11 January 2011 23 February 2011 9 March 2011 Accepted 24 March 2011

College of Business Administration, Abu Dhabi University, Abu Dhabi, United Arab Emirates Abstract Purpose – This research aims to investigate the adoption of electronic communication tools and seeks to shed more light on their diffusion process, a challenging task for project-based (PBO) and traditional business organizations (TBO). Design/methodology/approach – The data for the study were collected through three surveys, one total population survey in the Finnish and Swedish house building industries representing traditional business organizations, together with a focused and a total population survey in project-based organizations. Findings – The main findings from the survey indicate a difference in attitude between the employees of TBOs and PBOs. Moreover, electronic document management and scheduling were more prominent among PBOs, because these firms exhibit more inter-organizational communication. Research limitations/implications – The findings are limited to project-based and traditional business organizations. The research emphasises the fact that PBOs make more inter-firm collaboration efforts and thus require more extensive communication systems for inter-organizational links. Further research is needed in other industries to validate the present findings. Practical implications – By looking at the use of ICT, the aim was to determine which e-communication tools are more tightly coupled to management and how firms can benefit most from these tools for organizational governance. Originality/value – This is one of the few studies to have examined the uses of ICT in a PBO and TBO context and especially in Finnish and Swedish background. Keywords Project-based organization, Traditional business organization, E-communication, Communication tools, Communication technologies, Sweden, Finland, Organizations, Organizational structures Paper type Research paper

The authors are most grateful to the anonymous referees for their constructive and helpful comments that helped to improve the presentation of the paper considerably. Further, the authors also acknowledge the data collection support for TBOs from Mr Mats Engsbo at Hanken, Swedish School of Economics and Business Administration, Vaasa.

Journal of Enterprise Information Management Vol. 25 No. 1, 2012 pp. 7-27 q Emerald Group Publishing Limited 1741-0398 DOI 10.1108/17410391211192143

JEIM 25,1

8

1. Introduction Electronic communication (e-communication) plays a fundamental role in any organizational activity. Today this includes a multitude of communication tools, ranging from simple forms such as e-mails to more complex forms, e.g. electronic document management (EDM) systems, electronic data interchange (EDI), enterprise resource planning (ERP) systems and project planning systems. The introduction of different e-communication tools may alter the operations of firms, providing them with innovative venues to enhance their management processes. E-communication can be divided according to intra-organizational or inter-organizational context, each with its own challenges and opportunities. Depending on the forms and types of complexity in their interaction, project-based organizations and traditional organizations face different communication needs and barriers to require different applications of e-communication. Project business involves the interaction of inter-organizational and intra-organizational activities and their structures with respect to marketing, procuring and executing project activities. Davies and Hobday (2005) refer to it by the term “project-based business” (PBO) when they mean “organizations – which may be entire firms or units within firms – that deploy projects to achieve major business objectives, including all firms which design and produce complex products and systems (CoPS)”. For the purpose of this study, project business is defined broadly to encompass all business functions in the process of which many stakeholders are involved. These functions running through the life cycle of a project can be described as: “management”, “customer interface” (or “concept development”), “engineering”, “supply and procurement”, “transportation and logistics”, “construction” and “operation”. In all these activities, intra-organizational processes interact with inter-organizational processes throughout the project life cycle and, hence, communication plays a vital role in organizations. Earlier research on improving communication focused mainly on internal organizational communication and most of this attention concentrated on the availability of communication for intra-organizational communication of traditional business organizations (TBO) (Amaratunga et al., 2002; Greasley, 2003). It was hoped that some research on the perceived usefulness (an outcome expectancy) would produce key predictors of intention/behaviour for adoption. Since the current research builds on the technology acceptance model (TAM), there is an implicit assumption incorporating an outcome-process perspective (Venkatesh, 2000). However, the distinctive characteristics of project-based business (uniqueness, uncertainty and complexity), with its distinctive communication needs, mean that any attempt to improve communication on the basis of traditional organizations is unlikely to fulfil the special requirements of project business. In particular, a focus on the company’s internal communication fails to recognise in the conduct of project business the importance of communication with external networks, partners and other stakeholders. Indeed, researchers in the area of project management have largely neglected such inter-organizational communication as can be supported by the adoption of available technologies or developing new technologies. Therefore, the driving force for this study is the lack of research on firms engaged in e-communication covering project-based organizations and the way in which traditional business organization e-communication differs from these organizations. An attempt should be made to elaborate some thoughts and views on e-communication

which interrelate the firms’ inter- and intra-organizational communication use. In line with the integrated communication and available technologies, we discuss its uses in PBO. In short, this research has been undertaken to answer the following questions: . How do project-based organizations use e-communication in the form of available technologies and . How does this differ from the use made by traditional business organizations?

The adoption of ICT in organizations 9

The first step in addressing the above research questions is to establish the difference between PBOs and TBOs. The organizations involved in project business are always formed around the tasks involved with its stakeholders. Therefore, it is appropriate to establish a framework for their intra- and inter-communication applying the emerging technologies. Establishing such a framework will provide a better understanding of the way in which firms communicate with their internal and external partners. The communication needs to specify what sets of available technologies can be implemented by the firms, thus leading to the actual use of them by the two groups of organizations. We will also determine whether there are any differences in the actual use of e-communication between the two different forms of organization. 2. Project-based and traditional organizations The major characteristics of PBOs along with others are uniqueness, complexity, and discontinuity. A project is unique in the sense that every project differs from the others in size, type, customers, suppliers, volume, price and so on. It is complex in terms of the technical, financial, political and social factors involved. Finally, it is discontinuous in terms of a high degree of discontinuity in economic relations between suppliers and the customers. These changing external dynamics offer new challenges to project-based organizations. Moreover, growing organizations have a variety of problems and putting those problems in a project framework is a very effective and efficient way of handling the turbulence. In Table I we list the most prominent features of project-based and of traditional organizations. The emphasis on differences in time-frame (temporary vs continuous arrangements), environment (dynamic vs stable) and decision making (decentralised vs centralised) enforce the distinction between the two forms of organization (Sandhu, 2005; Artto and Wickstro¨m, 2005; Sandhu and Naaranoja, 2009). Project-based organizations

Traditional business organizations

Uniqueness Complexity High degree of uncertainty Discontinuity Temporary arrangement Emphasis on goals Dynamic Flexible Non-hierarchical organization Decentralised decision- making Adhocratic

Continuous operations Emphasis on working processes Low degree of uncertainty Stable processes Permanent arrangement Inflexible Hierarchical organization Centralised decision-making Bureaucratic

Table I. Characteristics of project-based organizations and traditional organizations

JEIM 25,1

10

In many ways, a project is, in itself, an organization – a “new” organization which links to other organizations, externally and internally. Therefore, it needs to take into account the unique characteristics of this “new” organization. However, the problematic issue in use is that a particular organization may have difficulty in adapting to a new situation. In spite of the increasing adoption of the project approach, project managers are still perplexed, for two reasons. First of all, the goals of the project are likely to change and become more demanding with changing external circumstances which are beyond the company’s control. Second, in more recent times the traditional techniques of handling the project have not always been a proper fit. The nature of project business means that organizations involved in project management must be specialised in communication if they are to offer a full range of services to their customers, cope with demand fluctuations and shorten response times. Past research (Sandhu, 2005) has emphasised the importance of communication and improving communication processes, in particular on internal organizational capabilities, and most of this attention has been focused on communication and process development. However, some industry-driven research has been done in this area in Finland, mostly on the technological development of producing applications and agreeing on standards, e.g. the VERA programme during 1997-2002 (The VERA programme, n.d.) and the KITARA programme started in 2005 (The KITARA programme, n.d.). Inside the TBOs, there are constant and well-known institutions; for example, functional groups, departments, plants and branches, where knowledge and experience are acquired, stored and disseminated. These institutions can be consulted and their knowledge and experience can be retrieved, whatever the specific source from which they were collected, e.g. in documentation, records, competent employees or hidden within the working process. However, in PBOs the established methods and tools of communication for sharing knowledge require further investigation and development to cope with contingencies (Sandhu and Naaranoja, 2009; Ajmal et al., 2010). In general, there are no methods of capturing the knowledge and experience obtained and collected during projects. Projects are as distinct as temporary organizations with particular objectives, detailed tasks and restricted time and budget. When a project is finished, normally there is no institution or group left from which to access the stored knowledge. Meeting points, such as groups, departments, plants, branches in the regular organizations, are dispersed after the ending of a project. In many cases, even the place where the records of a specific project are accumulated will be unidentified. It is even hard to discover which employees have worked on a recently finished project, who were accountable for specific tasks and where these employees are working now within the company. Difficulties of this kind will increase with the number of projects running in parallel and therefore the organized securing of knowledge and experiences is even more important in multi-project management. Companies that do not systematically capture for later use the knowledge gained in projects before they end risk the loss of some certain knowledge and some useful experiences. Communication is a key issue in the storing of such knowledge. This study presents a framework which is elaborated on the basis of the reciprocal interactions of activities within and outside the organization – thus providing a coherent basis for continuous improvement in e-communications. Therefore, though the differences in characteristics

and communication needs are great, the similarities are even bigger, implying that technologies for supporting PBO and TBO can be cross-productive. 3. Intra- and inter-organizational communication Communication is most often described along three dimensions: content, form and direction. Content and form together make up the messages which are sent (directed) through a channel to its receiver. Any of the three dimensions can get disturbed by “noise” which distorts the message or direction of the message. There are many barriers to impede communication, ranging from language-barriers to lack of understanding of the context. Adriaanse and Voordijk (2005) state that the contract, the frames of reference of the parties involved and the interests of the parties involved (together with a lack of trust) are three major factors influencing inter-organizational communication (i.e. communication between client and contractor) during different project phases. Here we argue that in projects the initial phases are extremely important because the need for pre-contractual communication is crucial and so is the need for early risk analysis, implying that much communication takes place before an actual contract is drawn up. In the early phase of the project, the communication could be of many forms: oral, written (e.g. textual, drawings, graphics) or non-verbal (e.g. gestures). The project management literature has focused mainly on intra-organizational communication aspects (Almeida et al., 2002; Tsai, 2001) how a project is planned, controlled and delivered. But communicating in a project is conceptually different in the traditional stable manufacturing organizations. This focus seeks to develop a greater understanding of the contextual aspects of communication in an inter-organizational and intra-organizational context. Communication tools have been revolutionised with the explosion in information technology, as a multitude of methods and software programs has become available for business. Sophisticated software programs are available and procured, but many are left on the hard disk without being used by the senior managers who commissioned the software. A project business involves intra-organizational and inter-organizational networks that require different types of knowledge and communication. One of the difficulties is that the available communication methods are not easy to use or are deemed unnecessary in project-based organizations. A framework which combines intra-organizational networks with inter-organizational networks is required to communicate efficiently and effectively throughout a project’s life cycle. Otherwise the project manager cannot learn how to communicate in various situations in order to manage the project-based organization. A variety of intra-organizations can exist – for example, matrix organizations, projectised organizations and coordinating organizations. Moreover, several structures of intra-organization can exist to perform project activities. These arrangements depend on the proportion of the business involved in a project, the scope of the project and the duration of the projects involved. All these issues are connected to the communication needs of the organization. Earlier research on intra-organizations has focused mainly on environments that could impede the development of corporations, rather than those from which benefits may be derived (Brady and Davies, 2004; Collyer, 2000). However, most organizations are in an “intermediate context” which allows processes to be developed and benefits to

The adoption of ICT in organizations 11

JEIM 25,1

12

be mutually derived. The important organizational characteristics for successful project development include openness in communication, adequate environmental scanning, management support and established organizational values. Developing communication methods with an inter-organizational as well as an intra-organizational perspective requires a precise understanding of what kinds of communication practice foster business development. According to Amabile (2005), managers often destroy creativity in project-business development by failing to make good connections between people and activities. It is therefore important to identify the interdependencies between actors and activities and to identify the resources which they require to perform their tasks. The communication needs are tightly coupled with the characteristics of the actors, activities and resources. Thus, in order to provide sufficient support and ease of communication in project-based as well as traditional organizations the communication needs should be investigated and developed. In Table II, we categorise the communication diversity between PBOs and TBOs, by looking at the focus and the tools used. Table II presents the notion that, because project-based organizations are more involved in collaborative communication over organizational borders, the tools should support the features associated with inter-organizational communication as the electronic data management (EDM), enterprise resource planning (ERP) and three-dimensional visualisation (3D visualisation) are being commonly used. The emphasis in traditional organizations is on the efficiency of internal communication and on the functional level this is why organizations use MRP I-II, groupware, 2D/3D and CAD/CAM. 4. Adoption of e-communication technologies E-communication facilitates the information flows of the firm, within and across firm boundaries (Wu and Lee, 2005). E-communication in an industry setting can be roughly divided into two forms: (1) intra-organizational communication (within an organization); and (2) inter-organizational communication (e.g. customer communication, supplier communication and partners, i.e. multiple organizations working together on a project). Each of these communication modes requires its own data sets, communication channels and tools to facilitate the communication. Using e-communication, organizations today have added tools for their communication needs, whether the communication takes place between organizations (with customers, suppliers, partners) or inside their own organization.

Form of organization

Table II. Communication diversity

Project-based (PBO) Traditional (TBO)

Main focus of e- communication

Communication tools utilised

Collaborative, inter-organizational emphasis Functional, intra-organizational emphasis

EDM, ERP, 3D visualisation MRP I-II, groupware, 2D/3D, CAD/ CAM

The cost of communication has declined compared to traditional means (e.g. attaching a file to an e-mail vs distribution of paper copies), the speed of communication has increased rapidly (e.g. time for an electronic message to arrive compared to snail mail delivery) and the technologies involved in bringing e-communications are becoming ever the more versatile (e.g. both video-conferencing and textual communication simultaneously). There are still some disadvantages with e-communication, e.g. lack of interpersonal exchange and legal implications (e.g. the validity of signed paper compared to e-mails). These areas are remedied over time as technologies evolve and as digital signatures, for example, are standardised. Still, the study of barriers to adoption is important for recognising why technologies are rejected, in this case, the use of e-communication. Firms should take stock of the adoption barriers they retain and how they can manage them, what can be done internally and what should be placed in the hands of outside partners. The distinction between adoption and use is that adoption is the decision to implement whereas use is what happens after the implementation has been carried out. The adoption decision is a precursor to use, but use is not a definitive consequence of adoption since implementation can be stalled or cancelled even after the actual adoption decision has been taken. During use, there is often some form of adaptation of the technology as the firm or individual learn more it. Often a technology is implemented and tested, but in a simpler mode or partial way. As the organization or individual gets comfortable with the technology, the functionality can be incrementally extended. Barriers to adoption can be classified on the level of general e-business and specific applications. When considering such barriers in firms, it may be necessary to investigate whether the barriers are generic or time/firm-specific. Generic barriers do not change rapidly as they are inherent to the industry or the market. Firm-specific barriers are associated with the organizational schemas and resource constraints affecting the decisions to be made. Time-specific barriers might become obsolete with the introduction of new infrastructure support technologies or lower internal requirements of technical competence to the adopting firm, for example. Depending on the type of barriers, adoption may be slow or even brought to a standstill, leading to patterns of early or late adoption. Central to the problem under discussion is that the barriers may be considered to occur on three different levels: (1) individual level (e.g. project team member, procurement manager); (2) firm level; and (3) network level. The notion of adoption at different levels is nothing new, for these levels are dealt with in the literature on innovation diffusion in the form of optional, collective and authoritative decisions (Rogers, 2004). What is novel here is the view that the barriers (and benefits) are located at different levels and that conflicts between levels create situations more complex and multifaceted than previously conceived. Adoption barriers at the firm level are mostly identified as resource issues, e.g. technological and monetary restrictions. The network level consists of connected firms co-operating on projects or in the form of supply-chains. Barriers at the network level may consist of

The adoption of ICT in organizations 13

JEIM 25,1

14

Figure 1. Links between levels and adoption barriers

social norms, risks of non-established standards or legal issues. This is illustrated in Figure 1. Further, ICT implementation barriers exist and can be identified and handled from different perspectives, e.g. the top-down effects on multi-level IT implementation barriers with links to implementation coping strategies (Stewart et al., 2004). At the industry level, the nature of the industry in the areas of competitiveness, cost sensitivity, resource limitations and fragmentation, may raise barriers that inhibit IT implementation. At the organizational level, the lack of IT investment justifications and available resources may discourage implementation, and so may problems with strategic foresight. At the project level, the nature of the projects themselves (uniqueness, complexity and discontinuity) creates barriers to IT implementation. In a study (Stewart et al., 2004) of the Australian construction industry, the most significant barrier on project-level was tight project time-frames which inhibit training and experimenting with IT, followed by limitations in IT funding, lack of IT leadership and low levels of technological literacy. Evaluating IT costs when developing an IT infrastructure which can be economically justified is n issue which needs more focus and development, especially regarding indirect human costs (e.g. management time on planning and integrating new systems, internal system support) and indirect organizational costs (e.g. productivity losses, resistance to change) (Love and Irani, 2001). The concept of the IT lifecycle is providing firms with further complexity in the investment situation, but also a more realistic picture of what can be expected from investment in IT. Communication processes (i.e. the exchange of information) for firms can occur either internally or externally. Intra-organizational e-communication is in its simplest mode merely electronic mails (or faxes), while more enhanced e-communications over intranet or local networks can be streamed in different forms: text, audio and/or visual. An intranet is a network based on transfer control protocol/internet protocol (TCP/IP) protocols and available only to the members of the organization and is often protected by a firewall (Horton et al., 2001). Inter-organizational e-communication can be focused on customers, suppliers, partners or other parties. The interface with external parties provides support for order taking, procurement, collaboration or other processes. Applications exist for constructing and managing these relations, in the forms of extranets, EDI, e-commerce, EDM and so on.

The spread of e-communication varies across industries, networks and even organizations. The rate, extent and frequency of adopting of e-communication all quantify the adoption of technology, from the economic-rationalistic perspective (Fichman, 2004). The critique against the so-called dominant paradigm of ICT innovation coupled with economic and rationalistic behaviour is that the focus on quantity of adoption and the inherent perceptions of innovation as beneficial may not paint a totally realistic picture. The adoption of transient technologies, the affluent results of early adoption and “more is not always better” are factors which contradict the quantity approach to IT adoption. When a firm decides whether or not to adopt e-communication, the complexity of the decision should be apparent. The decision is based not only on internal perceptions but also on the business milieu of the firm. The determinants of e-communication adoption can be divided in several different groupings: incremental vs. revolutionary, internal vs. external stimuli, key drivers (technological, economic, social, organizational drivers and barriers). In a study (Wu and Lee, 2005) on e-communication in four different industries, two sets of factors are recognised which affect the adoption of e-communication: internal push factors and external pull factors. Both sets of factors are influenced by the environmental turbulence, whether the changes are in technological or market turbulence. Internal push factors consist of customer orientation and competitor orientation. In communicating on a project, the modes and tools of communication may be set from the beginning. For example, in big construction projects, the use or non-use of an electronic document management system can be enforced by the head contractor and the systems may vary according to what collaborators the organization communicates with. To analyse which e-communication solution is or could be adopted by an organization, we have first to understand the network structure that the company is part of and maybe consider where in the network the organization wants to position itself. The locus of control among partners in the network affects the choice of solution, implying that a hierarchical network structure indicates a narrow locus of control and less need of completely open solutions (Marchewka and Towell, 2000). For example, in a network situation where the relative power of one or a few participants is very high, one could expect partner-specific solutions, as the larger organization(s) may dominate their smaller partners and can therefore enforce solutions more suitable or compatible with their existing internal systems (Ratnasingam, 2000). In a network with a more evenly distributed power structure, no single participant can be expected to enforce an individual solution, as this could limit the options to connect to potential partners. As pointed out earlier, the ability of the e-communication solution to integrate with existing systems in the organization is of the utmost importance. Therefore, an investment in an e-communication solution may require further development or even re-invention of the business information systems which are the backbone of the firm (Engsbo and Sandhu, 2007). 4.1 Challenges associated with the use of ICT Wixom and Watson (2001) identify three broad factors regarding the success of ICT related projects; these are project, organizational and technical factors. Each of these critical success factors is discussed below:

The adoption of ICT in organizations 15

JEIM 25,1

.

16 .

.

Project considerations. It is well known that a project proponent is important but if an enterprise system project is spread over a long period of time, the leader may change. Similarly way, the original members of his team may also be replaced. The newly joined members may not be as “sold” on the project concept as the initial team members, for example, the “vanilla implementation.” Usually projects take off with a good deal of excitement and fanfare and the team members have a clearer common vision of the goal than someone who joins at a later stage. Technical considerations. A project can start with a plan which contains technical details about the data format, update, use and testing, but it may not be possible to have a completely accurate plan at the outset. One example is “data-cleaning” in the HR system of a university. The cleaning process would ensure that there is only one data set on every student across the institution. This may be a daunting and lengthy task because it may not be easy to predict the quality of existing records maintained in multiple locations. So the development of a clean, integrated database can take longer than originally anticipated. Organizational considerations. Commonly, the implementation plans do include the resources required for an organizational restructuring program which is critical for getting people to adopt the new practices, for example, training, workflow control and communication. But the resources allocated for organizational changes are often diverted to other areas, such as addressing the pressing technical issues which may have exceeded their original budget.

4.2 Participation of users A requisite of a successful ICT project is the participation of users. They are not only involved in defining users’ requirements, but also in the implementation and adoption phases, which would ensure that changes in organizational level do take place. Although the research shows that even when the users have been “bought-in” during the definition phase, they may still not adopt the technology due to the following reasons: . The users may be reluctant to change to the ways of working required by the new system. Not fully understanding the technological aspects may be a contributor to the “legacy” frame of mind. . If the users did contribute to the design phase, but their suggestions were not included in the implemented version of the project, the users could be resistant to adapting. . It may be hard to get the users to start using the new technology because they may already be busy with their previous work or may not be convinced that the technology brings them an advantage. 4.3 Literature synthesis Many studies have been conducted to address the ICT adoption issues in MNCs and SMEs. Research synthesis of these is listed in Table III. However, so far very few studies have addressed particularly the ICT adoption process in project-based organizations and compared it with that in traditional organizations. Hence the present study aims to closely look into ICT adoption in such organizations by providing evidence from two Scandinavian countries.

“Potential benefits, current supply, utilisation and barriers to adoption: an exploratory study on German SMEs and innovation software” “Adoption of information and communication technology: impact of technology types, organization resources and management style”

“A firm-level analysis of determinants of ICT adoption in Spain”

“Adoption of ICT in a government organization in a developing country: an empirical study”

Kohna and Husig (2006)

Bayo-Moriones and Lera-Lopez (2007)

Gupta et al. (2008)

Yang et al. (2007)

Title

Author and year

A survey questionnaire was used to collect data regarding use of internet technologies among employees in an e-government setting

The data were collected in a survey with a sample of 337 Spanish workplaces

The findings are that software tools are rarely used to support the innovation process in German SMEs

A survey with a uniform questionnaire was sent out to marketing and IT executives of manufacturing oriented SMEs in Germany An empirical method was employed in this study about ICT diffusion process between the early and late adopters Due to management characteristics there is significant dissimilarity between early and late ICT adoption in organizations. However, no significant differences were found in organization resources or corporate strategy factors. Also, there are significant differences in organizational characteristics such as sales volume and rewards The need for reviewing the traditional public support for ICT implementation on small workplaces arises, together with the existence of complementarities with policies aimed to attract foreign investments and to increase the workforce education level as a way to spread ICT implementation. Results also show that managers need to align ICT adoption and the strategic focus of the firm more consistently Study found that performance and effort expectancy, social influence and facilitating conditions all positively impact the use of the ICT in government organizations (continued)

Findings

Methodology

The adoption of ICT in organizations 17

Table III. Previous studies

“Internet-based ICT adoption among SMEs: demographic versus benefits, barriers and adoption intention”

Tan et al. (2010)

Ahuja et al.(2009)

“KM and enterprise systems adoption by SMEs: predicting SMEs’ adoption of enterprise systems” “Study of ICT adoption for building project management in the Indian construction industry”

A questionnaire-based survey was used to collect data from 406 managers or owners of SMEs in Malaysia

A questionnaire survey was conducted and through quantitative data analysis the extent of adoption of formal project management processes, ICT adoption for these processes and factors including perception-based factors affecting ICT adoption were studied

Interviews were made to collect the data

Attitudes towards ERP systems implementation could be a critical point for non-adoption. Having positive intentions is an important step towards realism, i.e. really implementing ERP systems SMEs appear to be more influenced by technological and organizational factors than environmental factors IT infrastructure at site has been perceived as an important enabler for effective ICT adoption by building project management. Rate of increase of ICT adoption in last five years has been found significant. But most of the respondent organizations did not have a communication management strategy SMEs would adopt internet-based ICT regardless of years of business start-up and internet experience. Some significant differences are spotted between manufacturing and service SMEs in terms of their demographic characteristics and internet-based ICT benefits, barriers and adoption intention (continued)

Findings

18

Ramdani et al. (2009)

“Enterprise resource-planning systems A survey method was employed adoption in Bahrain: motives, benefits and barriers”

Kamhawi (2008)

Methodology

Title

Table III.

Author and year

JEIM 25,1

Adriaanse et al. (2010)

A structured questionnaire consisting of close-ended questions was developed to conduct face-to-face surveys with the key informant person in each company in May 2005. Studied companies were SMEs and most interviewees were CEOs

The results indicate that ICT has a significant positive influence on the, four processes for creating knowledge. ICT oriented to communication and workflow is found, to produce a significant positive impact on knowledge creation processes, except for socialisation process, while ICT use for information does not influence any of the processes for creating knowledge and organizational learning The study found that personal “The use of interorganizational ICT in Interviews were conducted with motivation is required to use ICT along United States construction projects” experts from the US construction industry. In total 20 experts from ten with the external motivation to use this companies were involved in this study technology and facilitating conditions in terms of knowledge and skills and acting opportunities to use ICT “Analysing ICT adoption and use effects on knowledge creation: an empirical investigation in SMEs”

Findings

Lopez-Nicolas and SotoAcosta (2010)

Methodology

Title

Author and year

The adoption of ICT in organizations 19

Table III.

JEIM 25,1

20

5. Methodology and surveys 5.1 Background A variety of research methodologies has been used in the study of project-based organizations – including both qualitative and quantitative methods. The objective of the present study is to emphasise theory development, rather than theory generation. It thus adopts a survey approach which builds on the refinement of existing theories, rather than attempting to invent new ones. The present study proposed to describe the electronic communication in the organizations and compare PBOs with TBOs regarding their use and adoption of key IT tools in communication. The aim is to facilitate the discovery of new relations and variables in existing models by developing a comprehensive comparison between existing theoretical approaches and observations taken from the survey under consideration. The data for the study were collected through three surveys, one total population survey in the Finnish and Swedish pre-fabricated house building industries among representatives of traditional business organizations (TBOs) and interviews to clarify some of the answers given in survey. The other two focused surveys in project-based industries. In the second survey on PBOs, no house building companies were involved. The respondents were project-management personnel at both the strategic and the operational levels. Both surveys with similar questions were combined to investigate the plausibility of our assumptions. In total, 114 questionnaires were sent out and 46 answers to our surveys were received. A graphical representation of surveys can be seen in Figure 2. The data we used were a subset of questions from two surveys conducted in a TBO and a PBO environment, in turn. In this study we compare the answers from ten questions specifically focused on e-communication from both surveys. The questions asked concerned the e-communication tools to be found in the organizations. These tools were design and planning with 3D modelling, internal communication networks in the form of intranet and scheduling software, EDM, electronic procurement and communication platforms. 5.2 Data collection The TBO survey was conducted among employees of house building companies as a total population survey for Finland (conducted October-November, 2007 and again at the same time in 2009) and Sweden (conducted in March-April, 2008), where the firms

Figure 2. Graphical representation of methodology

were selected according to the following criteria: they should belong to the SNI-classification 20301 which denotes producers of pre-fabricated wooden houses and should have more than nine employees. In the study, micro firms with fewer than ten employees were excluded. We excluded this category of firms from our study because their smallness restricts the firms’ capability in the field of IT investment. These restrictions are due to shortages of financial and technical resources and to the fact that internal communication technologies in such firms are less needed as the likelihood of face-to-face communication increases. The firms in the study were mainly small and medium-sized enterprises (SMEs). According to the EU definition (European Commission, 2003) of SMEs, small firms have between ten and 49 employees and medium-sized firms are larger but have a maximum of 249 employees. There is also a condition about the turnover and balance sheet related to each category. We sent the survey to 55 house-building companies in Finland and 41 companies in Sweden. The response rate from Finland was 38 per cent (21 answers) and from Sweden 39 per cent (16 answers), 37 responses in total. The second survey, the PBO survey, was conducted in September-October, 2006, among SMEs as well as multi-national companies (MNCs) located in Finland. The operations of the SMEs were mostly local while the MNCs had offices all over the world. The respondents represented companies involved in projects in the construction industry (excluding house building companies), electronics industry and power-plant industry. The selection criterion for the PBO study was that the PBOs belonged to a project management club because these companies allowed the researchers better access to the required information. We distributed the questionnaire survey to 18 chief executive officers (CEOs), directors and general managers of PBOs. We received nine replies and one reply which stated that the recipient had retired from the project-based organization. Three out of the nine responding PBOs were MNCs with between 750 and 14,000 employees in some 80 countries, including Finland and Sweden. From one of the MNCs we received two responses from its two different divisions, raising the number of responses from MNCs to four. The remaining five companies were SMEs, largely operational in Finland and having some links with MNCs as a supplier. A detail of the respondents from each category is listed in Table IV. The third survey with PBO was conducted in March-April 2009 in Finland with 46 organizations involved in different types of project (see Table V). The involved in this Type of firm

Firms

Responses

SMEs 50-249 MNC 250 þ Total

5 3 8

5 4 9

Type of firm

Firms

Responses

12 34 46

11 30 41

SMEs 50-249 MNC 250 to 12,000 Total

The adoption of ICT in organizations 21

Table IV. Responses from the project-based study (2nd survey)

Table V. Responses from the project-based study (3rd survey)

JEIM 25,1

22

survey were service and manufacturing companies working in engineering, power plants, telecommunications, networks and stainless-steel SMEs and MNCs with between 50 to 250 and 250 to 112,000 employees respectively all over the world. The research sample comprised vice presidents, general managers, a program manager, project managers and project assistant managers working in Finnish project-based organizations. The questionnaire was sent to 400 respondents, randomly selected from the list published by the Project Management Association of Finland on its website as well as from the Project Management Club at Vaasa, Finland. A description explaining the study objectives was also included on the first page of the questionnaire. Moreover, three follow-up e-mails were sent approximately one, two and three weeks after the first e-mail. However, most of the respondents gave an answer in the first e-mail. A total of 41 questionnaires were answered with a response rate of 11 per cent percent only. Among these responses in this survey there were 11 participants from SME and the remaining 30 managers were from MNC. Table VI shows the actual use of ICT tools in TBO and PBO. In the PBO survey, the respondents were general managers of projects and project managers. In the TBO survey the respondents were either the CEO of the organization or the IT manager. The difference between the groups of respondents is due to the focus on projects in the first group and the fact that the TBOs do not hold project managers. The customer focus between the two survey groups differs since the customers of the TBO are mostly private persons building a small house or a developer producing row houses. The customer group of the PBOs are mostly large organizations whose projects are high in value. 5.3 Findings and analysis The TBO study provided some interesting details. In their communication to the customers, the house building firms all had homepages and 35 per cent of the firms used 3D visualisation i.e. CAD/CAM, while nine firms (24 per cent) were in the process of implementing this kind of technology. It was more common among the Finnish firms Technology Intra-organizational communication Intranets Design and planning Scheduling Inter-organizational communication Extranets E-procurement

Table VI. Actual use of ICT tools in the two kinds of organization

Collaborative platforms Document management Customer relationship management

TBO

PBO

60% implemented, 13% rejected. 2D CAD 70%, 3D CAD 60%, CAD/CAM 43 % 40% implemented, simple or home-made software

95% 2D CAD 100%, 3D CAD 80% 100%

24% implemented, 21% rejected 43% implemented, 40% feel need for it. Advanced use low No data available Internal mostly, 19% 37%

50% 45% and will increase in future 50% 100% 70%

than Swedish to have 3D visualisation for their customers. 3D visualisation is used to display a model of what the finished product will look like and as a basis for planning or selecting different options, such as colours, porches, etc. Further, 37 per cent of the firms used some form of customer relationship management (CRM) software or database to keep track of customers during the process of delivering the finished house to them. In total 16 per cent of the firms recognised a need for this kind of software while 26 per cent were in the process of implementing such software in their business processes. This was also relevant to the size of the firm; the bigger the firm, the more likely it is the firm is to have implemented 3D visualisation and CRM systems. Regarding internal communication, the use of intranets was prevalent. Almost 60 per cent of the firms had implemented intranet solutions, but, interestingly, four Swedish firms had chosen not to adopt intranets at all. Moreover, these firms were not the smallest in their group, but three out of the four without intranets were smaller than average for the respondents. The extension of intranet with partner access into what can be labelled as extranets was much less commonly used – only 26 per cent allowed partners access through extranets. It is obvious but worth saying that in order to allow partners access through an extranet, be an intranet should be implemented as a prerequisite for extranet communication. EDM systems or project banks were used by 21 per cent of the firms, which was unexpectedly high. Then again, this may point to what the respondent considers to be an EDM system or a project bank. A third of the respondents did not know what this term denoted. Once again, size mattered, as six of the seven firms which had implemented EDM were larger than the average firm in their turnover. Time-scheduling systems were used by close to 40 per cent of the firms; once again, a close correlation between firms which have implemented EDM systems and time-scheduling software. On the procurement side, half of the firms reported using electronic procurement and of these 60 per cent had integrated their procurement to some extent with their suppliers. When asked directly which their connection method for procurement was, the firms revealed that traditional fax or telephone still constituted on average 48 percent of their connection method to the suppliers, while e-mail made up on average. A total of 38 per cent of proprietary systems were used by 11 firms in their procurement process but only made up about 3 per cent on average. EDI communication was used by only three firms, but had high percentages for two of these: 30 per cent and 20 per cent of total procurements conducted on EDI systems. This is a typical trend, as once a firm chooses this method; it will use it as extensively as possible. The PBO questionnaire survey consisted of PBOs using ICT tools and their communications to customers and sub-suppliers, including other stakeholders. The PBO questionnaire was divided into three parts: A, B and C, in addition to background information on the survey participant. Part A gathered information about project-based organization: which types of project, the sizes of the project teams and the technical engineering function involved. The second part focused on other issues that are not part of this study. Part C is the focus of this study, where we asked questions regarding e-communication technology and ICT tools. This part consists of similar questions to those for the ten main questions of the TBO survey; in this part i we make comparisons and draw conclusions for our study.

The adoption of ICT in organizations 23

JEIM 25,1

24

All the firms in the study had homepages and the MNCs used a very high level of e-communications in inter-organizational and intra-organizational context. For example, to integrate and coordinate resources across projects they were using project management tools such as time-planning, cost-planning and control, quality management, risk management, deviation management systems, system designs and CRM. As 3D CAD tools are considered important to design in the projects, almost every organization was using 2D and 3D CAD tools and some platform to communicate with their customers. Two out of the nine responding firms did not use 3D and both were among the smallest of the SMEs responding. About 90 per cent of PBO used CRM as their customers required to register complaints etc. about the products. Customers also keep such databases to analyse the performance of their suppliers. The use of intranets was common; almost all MNCs and SMEs were using Intranet solutions. All the MNC and SME used electronic procurements and had integrated their system with their suppliers. The main results from the questionnaire survey are summarised in Tables IV and V. An important finding from the survey was a difference in attitude between the employees of TBOs and PBOs. According to the respondents from TBOs their employees were more committed to the company strategy than to projects, whereas the respondents from PBOs reported that their employees were more committed to the projects than to the company. It was found that all respondents believed in written contracts as being essential to project business. Of the use of 3D design software, the Finnish house building firms which used 3D software tended to chose Vertex BD (ten out of 16). The use of e-procurement is confusing, as 43 per cent acknowledged they used it but not mostly in the form of true e-procurement, such as e-mail documents or attachments. The most common form of e-procurement was the proprietary software provided by the supplier, which accounted for 4 per cent of the procurement of materials. 6. Conclusions This study has addressed the research questions set for investigating the use of e-communication in the form of the available technologies and their adoption, through three questionnaire-based surveys and interviews intended to clarify some of the answers given in the survey. It is anticipated that the findings will provide the SMEs and MNCs with an opportunity to undertake a self-check for the various issues influencing their adoption decisions. Our conclusions, derived from the study, can be summarised as follows: . For PBOs which conduct several projects with multiple partners, the inter-organizational communication requirements are higher than they are for traditional organizations, where inter-organizational communication is carried out vertically. . In SMEs, employees have easy communication access with the head of the company; however, in the MNCs, there is some “distance” between the CEO and project managers. . The communication needs of TBOs and PBOs are connected to the inter-organizational and intra-organizational relationships exhibited, where

.

. .

more dynamic and different external relationships might provide firms with differing communication needs. The adoption of ICT is restricted to the available technologies, communication needs and organizational characteristics of the organizations, giving different actual use of ICT from PBO and TBO. ICT is used in projects and line organizations mainly for governance purposes. The use of these tools may help in governance, which is at present developing from the classic hierarchical and market-driven community.

The contribution of this paper is to increase understanding of the differences in nature and communication of the TBO and PBO. We emphasise the fact that project-based organizations make more inter-firm collaboration efforts, thus requiring more extensive communication systems for inter-organizational links. The time is a crucial factor in PBO, because of heavy penalties on delays. However, the ever-changing collaborations in PBO also impair the full efficiency of using the same system each time because the project team, if composed of several organizations, is of a different aspect. Our findings are in line with Kotelnikov (2007) that not all SMEs need to adopt ICT tools to the same degree of sophistication and that there need be no “one-size fits-all” ICT policy across different industries, given those different sectors use ICT differently and thus will adopt them at a different pace. This study is highly context-oriented and localised; hence generalisation of the result is questionable. There is a need for further studies from other countries to raise the validity of the results. The study makes a contribution to a better understanding of the actual use and adoption of e-communication in SMEs and MNCs. Further research is needed to measure the wider aspects of differences in e-communication adoption, as our sample of PBO as well as TBO is rather small and we cannot claim high statistical accuracy. The barrier aspect is a further issue to incorporate in future research as to whether PBOs and TBOs exhibit different forms of barriers and the ability to surmount them. We believe the study would also benefit significantly from making more extensive qualitative investigations of the reasons for adopting different forms of e-communication in organization of either form.

References Adriaanse, A. and Voordijk, H. (2005), “Inter-organizational communication and ICT in construction projects: a review using metatriangulation”, Construction Innovation, Vol. 5 No. 3, pp. 159-77. Adriaanse, A., Voordijk, H. and Dewulf, G. (2010), “The use of interorganizational ICT in United States construction projects”, Automation in Construction, Vol. 19, pp. 73-83. Ahuja, V., Yang, J. and Shankar, R. (2009), “Study of ICT adoption for building project management in the Indian construction industry”, Automation in Construction, Vol. 18, pp. 415-23. Ajmal, M.M., Helo, P. and Keka¨le, T. (2010), “Critical factors for knowledge management in project business”, Journal of Knowledge Management, Vol. 14 No. 1, pp. 156-68.

The adoption of ICT in organizations 25

JEIM 25,1

26

Almeida, P., Song, J. and Grant, R.M. (2002), “Are firms superior to alliances and markets? An empirical test of cross-border knowledge building”, Organization Science: A Journal of the Institute of Management Sciences, Vol. 13 No. 2, pp. 147-62. Amabile, T. (2005), How to Kill Creativity. Harvard Business Review on Managing Projects, Harvard Business School Publishing, Cambridge, MA. Amaratunga, D., Sarshar, M. and Baldry, D. (2002), “Process improvement in facilities management: the SPICE approach”, Business Process Management Journal., Vol. 8 No. 4, pp. 318-37. Artto, K. and Wickstro¨m, K. (2005), “What is project business?”, International Journal of Project Management, Vol. 23 No. 5, pp. 343-53. Bayo-Moriones, A. and Lera-Lopez, F. (2007), “A firm-level analysis of determinants of ICT adoption in Spain”, Technovation, Vol. 27, pp. 352-66. Brady, T. and Davies, A. (2004), “Building project capabilities: from exploratory to exploitative learning”, Organization Studies, Vol. 25 No. 9, pp. 1601-21. Collyer, M. (2000), “Communication – the route to successful change management: lessons from the Guinness integrated business programme”, Supply Chain Management: An International Journal, Vol. 5 No. 5, pp. 222-5. Davies, A. and Hobday, M. (2005), The Business of Projects: Managing Innovation in Complex Product and Systems, Cambridge University Press, Cambridge. Engsbo, M. and Sandhu, M. (2007), “Emerging e-communication technologies and their use in project-based organizations”, Management, Vol. 2 No. 4, pp. 285-301. European Commission (2003), Official Journal of the European Union L124/36, EU Recommendation 2003/361/EC. Fichman, R.G. (2004), “Going beyond the dominant paradigm for information technology innovation research: emerging concepts and methods”, Journal of the Association for Information Systems, Vol. 5 No. 8, pp. 314-55. Greasley, A. (2003), “Using business-process simulation within a business-process reengineering approach”, Business Process Management Journal, Vol. 9 No. 4, pp. 408-21. Gupta, B., Dasgupta, S. and Gupta, A. (2008), “Adoption of ICT in a government organization in a developing country: an empirical study”, Journal of Strategic Information Systems, Vol. 17, pp. 140-54. Horton, R.P., Buck, T., Waterson, P.E. and Clegg, C.W. (2001), “Explaining intranet use with the technology acceptance model”, Journal of Information Technology, Vol. 16 No. 4, pp. 237-49. Kamhawi, E.M. (2008), “Enterprise resource-planning systems adoption in Bahrain: motives, benefits and barriers”, Journal of Enterprise Information Management, Vol. 21 No. 3, pp. 310-34. (The) KITARA programme (n.d.), homepages of the Academy of Finland, available at: www.aka. fi/index.asp?id¼e9026bca4a9c46f3ae8d44a4e24f7231 Kohna, S. and Husig, S. (2006), “Potential benefits, current supply, utilization and barriers to adoption: an exploratory study on German SMEs and innovation software”, Technovation, Vol. 26, pp. 988-98. Kotelnikov, V. (2007), “Small and medium enterprises and ICT”, in Haksu, K. (Ed.), Asia-Pacific Development Information Programme (UNDP-APDIP) E-primers for the Information Economy, Society and Polity, UNDP Regional Centre, Bangkok. Lopez-Nicolas, C. and Soto-Acosta, P. (2010), “Analyzing ICT adoption and use effects on knowledge creation: an empirical investigation in SMEs”, International Journal of Information Management, Vol. 30, pp. 521-8.

Love, P.E.D. and Irani, Z. (2001), “Evaluation of IT costs in construction”, Automation in Construction, Vol. 10 No. 6, pp. 649-58. Marchewka, J.T. and Towell, E.R. (2000), “A comparison of structure and strategy in electronic commerce”, Information Technology & People, Vol. 13 No. 2, pp. 137-49. Ramdani, B., Kawalek, P. and Lorenzo, O. (2009), “Knowledge management and enterprise systems adoption by SMES: predicting SMEs’ adoption of enterprise systems”, Journal of Enterprise Information Management, Vol. 22 Nos 1/2, pp. 10-24. Ratnasingam, P. (2000), “The influence of power on trading partner trust in electronic commerce”, Internet Research: Electronic Networking Applications and Policy, Vol. 10 No. 1, pp. 56-62. Rogers, E.M. (2004), Diffusion of Innovation, 5th ed., Free Press, New York, NY. Sandhu, M. (2005), “Managing project business development: an inter-organizational and intra-organizational perspective”, doctoral dissertation, Swedish School of Economics and Business Administration, Vaasa. Sandhu, M. and Naaranoja, M. (2009), “Knowledge management practices in project-based organizations”, International Journal of Business Excellence, Vol. 2 No. 2, pp. 140-56. Stewart, R.A., Mohamed, S. and Marosszeky, M. (2004), “An empirical investigation into the link between information technology implementation barriers and coping strategies in the Australian construction industry”, Construction Innovation, Vol. 4 No. 3, pp. 155-71. Tan, K.S., Chong, S.C., Lin, B. and Eze, U.C. (2010), “Internet-based ICT adoption among SMEs: demographic versus benefits, barriers and adoption intention”, Journal of Enterprise Information Management, Vol. 23 No. 1, pp. 27-55. Tsai, W. (2001), “Knowledge transfer in intra-organizational networks: effects of network position and absorptive capacity on business unit innovation and performance”, Academy of Management Journal, Vol. 44 No. 5, pp. 996-1005. Venkatesh, V. (2000), “Determinants of perceived ease of use: integrating control, intrinsic motivation, and emotion into the technology acceptance model”, Information Systems Research, Vol. 11 No. 4, pp. 342-65. (The) VERA programme (n.d.), homepages of the Finnish Funding Agency for technology and innovation, available at: http://akseli.tekes.fi/opencms/opencms/OhjelmaPortaali/ ohjelmat/Vera/en/etusivu.html Wixom, B. and Watson, H. (2001), “An empirical investigation of the factors affecting data warehousing success”, MIS Quarterly, Vol. 25 No. 1, pp. 17-41. Wu, F. and Lee, Y. (2005), “Determinants of e-communication adoption: the internal push versus external pull factors”, Marketing Theory, Vol. 5 No. 1, pp. 7-31. Yang, K.H., Lee, S.M. and Sang-Gun, L. (2007), “Adoption of information and communication technology: impact of technology types, organization resources and management style”, Industrial Management & Data Systems, Vol. 107 No. 9, pp. 1257-75. Corresponding author Maqsood Sandhu can be contacted at: [email protected]

To purchase reprints of this article please e-mail: [email protected] Or visit our web site for further details: www.emeraldinsight.com/reprints

The adoption of ICT in organizations 27

The current issue and full text archive of this journal is available at www.emeraldinsight.com/1741-0398.htm

JEIM 25,1

28 Received 28 December 2009 Revised 1 April 2010 10 August 2010 6 April 2011 Accepted 27 April 2011

Deciding the level of information systems outsourcing Proposing a framework and validation with three Indian banks Umesh Gulla TERI University, New Delhi, India, and

M.P. Gupta Department of Management Studies, Indian Institute of Technology Delhi, New Delhi, India Abstract Purpose – The purpose of this paper is to suggest a framework that would guide the practicing manager to decide the degree of information systems (IS) outsourcing. Design/methodology/approach – The proposed framework has been derived from the findings of a previous empirical study and qualitative inputs. Analytical hierarchy process (AHP) is then used to apply the framework. The framework is finally validated in three India-based banks. Findings – The proposed framework helps in creating a strategic alignment between the business strategy and information system strategy. The application of the framework shows the preference of managers towards high IS outsourcing. Strategic alignment and medium term impact emerge the important factors in IS outsourcing. The validity of the framework is proved in three banks. Research limitations/implications – The validation exercise has been done on a small sample due to resources constraints and a study involving a larger sample is desired. Further, it is advised to review the framework on regular intervals and make suitable changes in decision factors. Practical implications – The framework is helpful to managers in identifying the critical factors which can act as useful inputs in taking informed decisions on the degree of IS outsourcing. Originality/value – The paper fills some of the gaps in IS outsourcing by suggesting a practiceoriented framework that guides the decision maker to undertake a systematic and structured approach in arriving at an outsourcing decision. The framework has evolved from the practices of banks in India for which there does not exist any similar research. Keywords Information systems, Outsourcing, Framework, Impact, IS outsourcing framework, Strategy, Strategic alignment, Banks, India, Banking Paper type Research paper

Journal of Enterprise Information Management Vol. 25 No. 1, 2012 pp. 28-59 q Emerald Group Publishing Limited 1741-0398 DOI 10.1108/17410391211192152

Introduction The need to focus on core capabilities has become increasingly critical for business in today’s competitive environment. This requires the best resources to be devoted across enterprise as it grows. With information technology (IT) infrastructure emerging as an important factor in achieving business objectives, firms need to be technologically ready to take on strategic challenges that can fuel growth. The rapid growth of IT across the industries has offered competitive advantages, efficiencies and effectiveness in operations as well as helped to realize the so sought-after customer orientation to organizations. However, it has also brought problems to the organizations by way of

increasing complexities in the management of information systems (IS), changing IS application tools and high investments required in its IS infrastructure (Udo, 2000; Han et al., 2008; Zhengzhong, 2010). In such situations, technology requirements put burden on the scarce resources of these firms. One of the routes taken by IS managers is to explore the different options in sourcing IS-related services to use IS productively while allowing firms to concentrate on core business competencies and at the same time avail of the latest technologies and practices in their IS domain. Outsourcing has been seen as an effective solution to such problems by various authors (Palvia, 1995; Lacity et al., 1996; Willcocks et al., 2000; Aubert et al., 2004; Gonzalez et al., 2005; Walden and Hoffman, 2007). Over the years IS outsourcing has taken the shape from IS hardware maintenance in the 1960s to contract programming in the 1970s and in the 1990s to total outsourcing (Yang and Huang, 2000). Outsourcing practice has proliferated to developing countries as well such as Korea, Nigeria, Kuwait, India, China (Lee and Kim, 1997; Khalfan, 2004; Adeleye et al., 2004; Miozzo and Grimshaw, 2008; Mao et al., 2008). This trend has been attested by different research studies (Alsudairi and Dwivedi, 2010) as well as by various research agencies and predicting high growth in IS outsourcing (source: IDC surveys, PA Consulting group surveys, web site of the Institute of Outsourcing). While there is high enthusiasm on IS outsourcing, there have been many horror stories in outsourcing too. Several surveys over a period of past 15 years have revealed the concerns. In the earliest study, Lacity et al. (1995) has found that 70 percent of total outsourcing deals were unsuccessful. Another survey by Schier estimated that about 70 percent of the IS outsourcing contracts would be restructured and 15 percent would be terminated (Allen and Chandershekar, 2000). There are various issues in preparedness of the organizations to accept outsourcing (Aydin et al. 2010) and these needs to be taken into consideration for desired success. Various risks emerging from IS outsourcing have been reported by authors (Adeleye et al., 2004; Bahli and Rivard, 2005; Park and Kim, 2005,Whitten and Wakefield, 2006; Chou and Chou, 2009; Aundhe and Mathew, 2009) which included security issues, loss of innovation, long-term degradation in IS efficiency, overdependence on IS outsourcing vendor, switching costs etc. It emerges from the literature review that currently there is evidence of high interest in the outsourcing of information system services, which was further endorsed by the personal discussion undertaken with industry professionals during this study. It appears that IS managers are currently passing through a learning phase and grappling with various issues, including keenness to know what it takes to make outsourcing successful. Given the high interest being shown by companies in IS outsourcing and the varied experiences with IS outsourcing as reported, it becomes very critical for the decision makers to initiate the outsourcing process with sufficient clarity about how much to outsource that would provide maximum benefit to the organization. The success of IS outsourcing would depend upon the systematic approach to undertake the IS outsourcing process. The framework brought out in this paper is intended to guide the practicing managers to take effective IS outsourcing decisions. Limitations of existing frameworks for IS outsourcing In spite of the criticality of the nature of IS outsourcing decisions, it still remains in the nascent stages about how to execute the IS outsourcing process. While the existing

Information systems outsourcing 29

JEIM 25,1

30

literature has studied issues on outsourcing primarily from academic purposes, there is dearth of appropriate knowledge on planning IS outsourcing decisions, which would be valuable to the practicing managers in industry. According to McIvor (2000, 2008), companies have no firm basis for evaluating the make or buy decision. Lonsdale and Cox (1997) have found that most of the firms make outsourcing decisions primarily on the basis of reducing headcount and costs, which is highly inadequate for such kind of decisions. Recognizing the need for a formal approach for outsourcing decision, many researchers have paid attention to filling the void. There are quite a few outsourcing approaches suggested by various researchers (Table I). While certain factors such as cost analysis, supplier influences, changes in efficiency and effectiveness and core competency, etc., have been considered by all of them, they vary in specificity of approach and impact. Most of them suffer from some or the other limitations as described in the table. The earliest work is of Quinn and Hilmer (1994), who advocated issues such as costs, core and peripheral activities, supplier relationships and technologies to be considered in any outsourcing decision. This, however, does not provide any approach to guide users regarding the factors in an outsourcing decision. Of all, the most interesting work is of McIvor (2000), who suggested a four-stage analysis to assist companies in the formulation of an outsourcing decision. It incorporates the core competency, value-chain and supply base influence issues in outsourcing decisions. However, it fails to provide any insight on the interplays of factors relevant to each stage of decision-making that may be important for such decision situations. The choice of what part of business to outsource is made by ascertaining what will save most on overhead costs, rather than what makes the most long-term business sense. Similarly other frameworks lack in other dimensions. Given some or the other limitations attached to the earlier works as discussed in Table I, it is desirable to look for a framework overcoming most of the limitations. This paper attempts to formulate an IS outsourcing framework that is simple to understand, easy to use and yet flexible and exhaustive in covering all the influencing factors in IS outsourcing decisions. It should be able to guide managers in analyzing the need for outsourcing keeping in view the technology as well as management factors – internal as well as external to the organization. It is with this purpose, a framework is suggested here. Towards a framework for IS outsourcing A framework is a basic conceptual structure used to solve or address complex issues. A conceptual framework is used in research to outline possible courses of action or to present a preferred approach to an idea or thought. It may help IS managers with making recommendations of what to do, when and how to do, and contains prescriptive elements as it suggests that IS managers should carry out the outsourcing process in a certain defined way. Towards achieving our goal of such a framework, we conducted an extensive exercise of consultation with Bank executives in India. Choice of banking sector is based on simple facts that this sector is information intensive sector, has been most receptive to complex web of IT applications, management of which has remained a big challenge till today. Outsourcing of IT in the banking sector, hence, is a critical decision. The framework evolves from the experiences of banking, but will have

The authors proposed a three-phased IS outsourcing life cycle and its associated risk factors that affect the success of outsourcing projects A conceptual model was suggested by the authors to examine the causal structure of capability, process, and relationship in IT outsourcing. It used the responses from 267 IT outsourcing project teams in Korea The authors developed a statistical analysis framework to model client behavior at three stages of the outsourcing lifecycle: for client targeting and selection – opportunity identification, for client risk assessment and project portfolio management – client tracking, and a systematic analysis of outsourcing results, impact analysis, to gain insights into potential benefits of IT outsourcing as a part of a successful management strategy This study suggests a decision model for business process outsourcing adoption for management, and shows how it may be applied in a real decision process for BPO. It used AHP to apply the decision model This paper proposes and tests an explanatory model of information technology (IT) outsourcing behavior. Explored the ASP route to acquire the IS services with distinct advantages but also highlighted a set of risks

Chou and Chou (2009)

Kern et al.(2002)

Aubert et al. (2004)

Yang et al. (2006)

Mojsilovi et al. (2007)

Han et al. (2008)

Main features of the framework

Author

The results obtained supported the transaction costs model which has been the basis for many such earlier research work. The framework simply suggests ASP as one option for IS sourcing without providing the factors internal as well as external that should be considered by the managers while deciding upon this option (continued)

The model is developed for the BPO which cannot be applied as it is in the IS outsourcing process

Here the model is inclined towards the vendors and gives guidelines for the vendor and is not always from the client’s perspective

The model is weighted towards the relationship issues in outsourcing relationship

The focus of framework is on risks at different stages

Limitations of the framework

Information systems outsourcing 31

Table I. Brief of few important IS outsourcing frameworks

Framework considering the factors primarily internal to the organization as level of in-house IS expertise, the degree of business uncertainty reflected through changing requirements, the degree of systems interconnectedness and complexity, the role of IS as a business differentiator, and the relationship between IS and corporate strategy Proposed an outsourcing framework having fourstage analysis: defining core activities; evaluate value chain activities; cost analysis; and, finally, relationship analysis The framework is based on making a comparative assessment of the strengths and limitations of IS outsourcing and of the internal markets approach in terms of operational, tactical, and strategic impacts of the choice among the alternatives The framework considered the core dimensions of the relationship with the vendors as context, contract, structure, interactions and behavior in an outsourcing arrangement Outsourcing framework is based on product/asset complexity and asset specificity of information systems

Willcocks et al. (2000)

Vinning and Globerman (1999)

Kern and Willcocks (2000)

King and Malhotra (2000)

This framework guides only in post outsourcing decision management of outsourcing relationships

This model guides post-outsourcing decision making and does not answer why outsourcing should be undertaken.

Framework is inclined towards the internal market approach by comparing external bids with internal costs which may be difficult to compare. Besides it banks heavily on post-decision impact

Framework is general in nature and talks of stages only in the outsourcing process

Framework does not lay sufficient weight to the external environmental factors

Limitations of the framework

32

McIvor (2000)

Main features of the framework

Table I.

Author

JEIM 25,1

general scope as well. Outsourcing decision will be influenced by several internal and environmental factors which were first identified through a questionnaire survey and select interviews conducted with the business executives and IT managers of a large number of banks in India. The banks chosen represented public sector, private and foreign banks. A synthesis of the questionnaire survey and expert opinion blends the business and IS strategy issues with the impact of outsourcing (short, medium and long term) according to the degree of outsourcing along with the outsourcing reasons and risks as obtained from the questionnaire survey (Figure 1). Finally based on the syntheses, a framework has been evolved to undertake the outsourcing of information systems and the degree to which outsourcing should be undertaken in banking sector in India. The process of this exercise to arrive at the framework is described in brief and is given below: The questionnaire instrument used a Likert scale with “Very low” to “Very high”, “Strongly disagree” to “Strongly agree”, “ Not important” to “Very important” as two extremes of continua. The continua are divided into five intervals for measurements. The data obtained through this had been tested statistically to support (or not support) the propositions, that led to identify important decision factors in IS outsourcing. Interviews, using a checklist, and observation techniques are used to obtain the qualitative inputs. Data obtained from interview and observations are further supplemented by secondary sources such as annual reports, press release and articles published in business magazines and newspapers. Table II illustrates the methodology used to measure the identified variables. A synthesis of learning from qualitative and quantitative inputs is used to develop a framework for information systems outsourcing. The questionnaire was mailed to all heads (Information Systems Department) of the commercial banks operating in India to conduct a survey of information systems managers. For obtaining qualitative input, purposive sampling was done to choose banks. Three banks in each sector i.e. public sector, private sector and foreign banks were chosen to get the qualitative insight into issues relating to information systems outsourcing through interviews and observation. On administrating the questionnaire, 162 responses were received from 43 banks. Out of these, three questionnaires were half filled and efforts were made to get them completed, but with no success, and therefore were not considered for further processing. Hence a total of 159 responses were found valid and included in the study. Table III presents the statistics of banks that participated and number of valid

Information systems outsourcing 33

Figure 1. Synthesis of questionnaire survey and interview

JEIM 25,1

34 Table II. Variables and techniques used for measurement of variables

Table III. Statistics of obtained responses

Variables

Questionnaire

Interview and observation

Reasons of IS applications Extent of information systems penetration Sourcing pattern of IS services Degree of IS services outsourced Efficiency of information systems Service level of information systems Cost savings Performance IS controls Core competence Learning competence Reasons of IS outsourcing

U U U U U U U U U U U U

Category

Responses obtained

No. of banks participated

Percentage of total banks participated

66 51 42 159

17 14 12 43

39.54 32.55 27.91 100

Public sector Private sector Foreign banks Total

U U U

U U U U U

responses obtained. The respondents are fairly well distributed across banking sectors, thereby providing greater generalizability of the results. Internal consistency of the instrument is judged by reliability measures using Cronbach’s alpha, which is found more than the cut-off value of 0.6, which is recommended as acceptable for empirical research of similar nature. Details of this result are not given here because of want of space. The relationship among the eight impact variables has been examined. Correlation analysis is used to determine the measure of the strength of relationship of these eight impact variables. The correlation coefficients of these impact variables have been found and are given in Table IV. The correlation matrix given in Table IV shows that IS efficiency and Service level variables have a significant relationship with all other impact variables. This implies that as the IS efficiency and service level increases, the banks may observe improvement in other impact variables as performance, cost savings, IS controls, core competence and learning competence. Cost has no significant relationship with the IS control variable (with a correlation coefficient of 0.08), meaning thereby that higher IS controls may not lead to significant cost savings. Similarly IS control variable has no significant relationship with core competence (with a correlation coefficient of 0.11). Performance is significantly related to all the impact variables. Core competence is found to be significantly related to learning competence. It has the strategic interpretation for banks that when a bank focuses on developing its core skills, it is also helping such bank in creating conducive environment for developing new skills. Further results of ANOVA indicate that there are significant differences among

Correlation

Service Efficiency level

IS efficiency Service level IS cost Outcome-based performance IS control Core competence Learning competence

Core Cost Performance Control competence

1 0.65 * 0.53 *

1 0.42 *

1

0.63 * 0.28 * 0.65 *

0.49 * 0.27 * 0.47 *

0.39 * 0.08 0.53 *

1 0.41 * 0.53 *

1 0.11

1

0.44 *

0.4 *

0.32 *

0.41 *

0.42 *

0.43 *

Learning competence

Information systems outsourcing 35 Table IV. Relationship (correlation coefficient) among impact variables

1

Note: * significant at 0.05 level

banking sector on research variables such as efficiency, service level, costs, control, core competence. The findings from the study showed a significant improvement in the short-term impact in terms of efficiency, service level, and cost savings with the increase in the degree of IS outsourcing. However, at a very high degree of outsourcing, though there was improvement reported in these impact variables, it was significant. The results are shown in Table V. A similar trend was reported for the medium-term impact in the form of outcome-based performance. For long-term effects, the results showed that outsourcing promotes building of core competence in banks. Banks that have outsourced more have reported higher core-competence skills than those banks that have outsourced lesser of their information systems. However, in the long-term, outsourcing may not facilitate learning competence in banks. In the case of limited outsourcing, learning competence tends to increase in banks as outsourcing increases, but at high outsourcing levels, it showed a declining trend. The extent of IT penetration among the four categories of banks according to the degree of IS outsourcing was determined. Penetration of IT in a bank has been measured in terms of usage of the IT tools by the bank for functions like branch and bank computerization, IT-enabled delivery channels like ATM, internet banking, phone banking, mobile banking, call-centers, e-CRM, data-warehouses, MIS and DSS

Impact variables Efficiency Service level Cost savings Performance IS control Core competence Learning competences

Low Mean SD 3.64 3.73 3.19 3.91 3.54 3.65 3.70

0.60 0.59 0.43 0.53 0.61 0.67 0.53

Note: SD stands for standard deviation

Medium Mean SD 4.26 4.02 3.42 3.99 3.63 4.17 3.87

0.40 0.45 0.37 0.30 0.23 0.38 0.32

High Mean SD 4.46 4.27 3.93 4.24 3.56 4.42 4.04

0.22 0.34 0.29 0.22 0.30 0.27 0.35

Very high Mean SD 4.47 4.34 4.09 4.28 3.72 4.52 3.91

0.37 0.38 0.34 0.26 0.65 0.25 0.54

Table V. Mean score of impact variables of four categories of banks according to degree of IS outsourcing

JEIM 25,1

36

Figure 2. Extent of IT penetration in four categories of banks according to the degree of IS outsourcing

tools, software for financial management, etc. Figure 2 shows that banks with low IS outsourcing have recorded lowest IT penetration (mean of 3.05) while banks in the high IS outsourcing have recorded highest use of IT tools (mean of 4.52). It is further noted that usage of IT tools decreases in banks that practice very high IS outsourcing (mean of 4.40) compared with banks in high IS outsourcing category (mean of 4.52). Thus it emerges from the results that while outsourcing information systems increases the usage of information systems in banks, however at very high degree of outsourcing it may show decline. One reason for this could be that when banks outsource extensively their information systems, real costs of information systems come out more visibly in these banks and the banks then exercise the optimum level of information systems usage keeping in consideration the costs involved as well as the benefits derived. Further an attempt was made to check whether there is significant difference in the extent of IT penetration among the banks pair-wise, falling in four categories based on their degree of IS outsourcing. For this multi range analysis using Duncan’s test for multiple range was used. The results showed that banks that outsource more of their IS functions use significantly increased IT tools in banking process than those banks that outsource lesser of their IS functions. It may be interpreted that there is significant increase in usage of IT tools in banks as the degree of IS outsourcing increases from low to high IS outsourcing but at very high IS outsourcing the difference is not significant. Hence it can be extrapolated that outsourcing can increase the IT acquisition capability up to a limit but at very high outsourcing it starts to show decline. Extent of IT penetration clearly gives an edge to foreign banks (mean score of 4.53) over public sector banks which are found having the lowest usage of IT tools (mean score of 2.99). Further it is found in pair wise comparison that public sector banks have significantly lower IT penetration than private sector and foreign banks. The foreign banks have recorded higher IT penetration (mean score of 4.53) than private banks (mean score of 4.36) but the increase is not significant at the 0.05 level. An outcome derived from this is that public sector banks need to increase the usage of IT tools in their operations to compete with foreign and private sector banks in India. Having found useful information on IS outsourcing from the questionnaire survey, additional qualitative insights were sought in the form of expert opinion on these decision factors and to develop confidence on the results derived from the survey. For this, three experts representing outsourcing vendors, one outsourcing consultant, and 18 senior bank managers who were handling IS outsourcing in their respective banks, were identified and interviewed on issues such as customer requirements and offerings, competition, market forces in banking sector, IT issues, outsourcing of IS services, and outcome of IS outsourcing for the bank. The synthesis led us to believe

that business strategies of banks are driven by various factors such as customer, competition, technology, internal dynamics, and strengths and weaknesses of the bank. The business strategies then should guide the IS strategies which further lead to developing the IS outsourcing strategy including the extent of outsourcing. Finally, outsourcing is related to the business outcome, which may be categorized into three groups according to time span: short-term, medium-term, and long-term.

Information systems outsourcing 37

The framework The above results act as the starting inputs for the framework. The results of questionnaire survey led us to identify some decision factors important for Indian managers in handling the outsourcing dilemma. The following factors were identified as playing a major role in outsourcing decisions as derived from the study: . IS strategic alignment, which is governed by business strategic orientation, IS strategic orientation. . IS outsourcing degree (low, selective and high). . Impact of IS outsourcing (short, medium, and long term). . IS outsourcing drivers. Synthesis of the findings from the questionnaire survey, interviews and experts suggest strong relationships of business strategy, IS strategy, degree of outsourcing and impact of IS outsourcing. It is desired now to bind these factors in a framework that facilitate the manager to take informed decisions in IS outsourcing. The starting point here is a scenario that a decision maker is facing, wherein he/she has to decide how much to outsource IS services to be most productive. Associated with this would be problems and opportunities, such as implementation of a new internet access linked security policy, the use of new technology, choosing a concept for further evaluations, etc. Having identified the main decision points, adequate decision alternatives need to be generated and evaluated, relating to whether or not to execute an activity, alternative concepts, design configurations, risk reducing measures, etc. Our focus is on situations characterized by a potential of rather large consequences, large associated uncertainties and/or high probabilities of what will be the consequences. The proposed framework is based on the idea that IS outsourcing addresses the concerns of the companies as discussed earlier. However the IS outsourcing is a complex decision process and needs elaborate understanding of the company’s strengths, its core business, capabilities in the IS domain. This means that business as well as technological aspects and attributes primarily related to IS be included in the key decision-making processes in IS outsourcing that determine the choice of outsourcing concept, the design configurations, etc. The proposed framework recognizes the fact that different decision problems may be very different when it comes to potential consequences and associated uncertainties of what will be the consequences. The differences in management and decision level could also be large, ranging from the lower level to top management, also from outside the company. The result is a need for different type of decision support and decision-making processes. The framework introduces a classification system structuring the different situations, to select among alternative methods and approaches for the informed decision making on IS outsourcing.

JEIM 25,1

38

Figure 3. Framework for IS outsourcing

What emerges out from the previous discussion is that there are several important considerations that need to be taken care off towards reaching a decision on the degree of IS outsourcing in a given scenario. These include having clarity of business strategic vs IS strategy orientation which provides an insight into the level of IS strategic alignment. This, along with the expectations from an IS outsourcing decision, would help in arriving at some understanding on the degree of IS outsourcing that a firm should go to. As in any business decision, there are certain driving or facilitating factors and certain opposing factors, and is valid in the case of an IS outsourcing decision, which finally influences a tradeoff between continuum of high-low degree of IS outsourcing. The managerial approach in the decision process is described in Figure 3. The proposed framework (Figure 3) guides a manager on deciding the appropriate level of IS outsourcing. The framework emphasizes creating a strategic IS alignment between the business strategy and IS strategy, and accordingly aims at suitable IS outsourcing structure. It considers the likely impact of outsourcing on the strategic interests of the business organization as well as its effect on the routine operations of the organization in the form of short, medium and long-term effects. The degree to which the organization would outsource would also be decided by the outsourcing drivers in that particular organization where IS outsourcing is planned. The IS outsourcing framework consists of a series of logically sequential stages that guide the managers in outsourcing decisions. It is essentially a multi-criteria decision model as depicted in Figure 4. A limited validation exercise is undertaken in the select banks in India. The methodology that would be followed for the validation is as: (1) A multi-criteria-decision model (MCDM) is proposed. Since, it is a managerial decision involving consideration of several qualitative judgmental variables, AHP is found most suitable to respond to this kind of decision scenario. (2) In the above approach, AHP is used at two levels. First, AHP is used to determine the magnitude of importance of various factors considered in the

Information systems outsourcing 39

Figure 4. Hierarchical model for choosing degree of IS outsourcing

decision process based on general perceptions that exist in the banking industry at the prevailing period. In the second stage these weights are now usable in specific banking scenario in deciding the degree of outsourcing. (3) To illustrate its applicability, in the next stage, three banks are chosen that followed different outsourcing practice (low, selective and high outsourcing levels; i.e. one bank practiced low, second practiced selective and third bank practiced high outsourcing). Using the weights of the framework factors obtained earlier, weighted scores of different factors are calculated. These are added for each bank to obtain the overall score. The different stages of the framework are explained as below. Business strategic orientation Core competence movement as propounded by Prahlad and Hamel (1990), emphasizes on maintaining the focus on core business and shell out non-core activities to others through outsourcing. IS functions are found prime target to remain focus on core competence (Loh and Venkatraman, 1992; DiRomuldo and Gurbaxani, 1998). However, caution is desired since overdose of outsourcing may lead to loss of innovation skills (Hoecht and Trott, 2006). Companies need to identify their core competence skills and formulate their products and services around these skills in order to differentiate from the competitors by offering better products and services at lower costs/inputs (McIvor, 2008). As the organizations aim to improve the efficiencies in its existing processes,

JEIM 25,1

40

their dependence on IS tools increases. Hence the business processes begin to be driven strongly by the IT tools. The banking sector is one of such example. However, it is important for organizations to keep in sight its core business focus, lest the organization gets over-occupied with management of its IS infrastructure. It is for this reason the organization finds IS outsourcing an option for sourcing complex IS capabilities. Some of the major factors that represent business strategic orientation for outsourcing decisions are business focus, learning competencies: to keep track of changes in customer requirements and market trends, devising performance metrics spanning resulting from outsourcing over short, medium and long term, and change management. IS strategic orientation The right technology is an outcome of appropriate IS strategy. IT tools have increasingly become complex, and costly and there are lots of options available leading to confusion in many IS-related decision situations. The technology life cycle for IS solutions have shrunk considerably leading to high rate of obsolescence of IS solutions (Grover et al., 1994; Clark et al., 1995) resulting in the technology risks and uncertainness on success of IS solution before the companies. Companies, small as well as big, are resorting to IS outsourcing to deal with the increasing burden of IS maintenance (Rohde, 2004; Gonzalez et al., 2005). Further unavailability of skilled manpower and difficulties in upgrading the skills of the existing IT employees in the IS domain have become serious concerns for many organizations (Aubert et al., 2004, Gonzalez et al., 2005). Thus the companies have to look for an IS structure that utilizes the internal resources and also look for external resources that together are able to meet its users’ requirements. IS outsourcing has emerged as an effective solution in such a scenario. The factors that represent IS strategic orientation are: . selection of technology and IS tools; . procurement of IS solutions; . implementation of IS solutions; . aligning IT tools with the business processes; . IS performance metrics; . hiring and retaining effective and skilled IS manpower; . upgrading continuously the technical skill sets to prepare for future requirements; and . control over IS setup (operational as well as strategic control). IS strategic alignment Strategic alignment of business strategy and IS strategy may result in a structure where synergies between the organization’s internal capabilities and the external IS outsourcing vendor’s strengths are created (Aubert et al., 2004; Paisittanand and Olson, 2006; Goo and Huang, 2008; Palanisamy et al., 2010). Blending the business strategy with IS strategy lead to the strategic alignment of the IS and provides a roadmap to the organization. This is an iterative process and is performed till an optimum level is arrived. The factors that constitute IS alignment are management of IS capabilities, extent of IS penetration, core competence skills, project management capabilities for

different stages of software project management, and vendor management for outsourcing. Figure 5 provides a list of statements that helps clarity on IS alignment in a bank and similar approach may be taken for any company in any industry: Expected impact of IS outsourcing Outsourcing has a direct impact on the way in which a company manages its short-term as well as long-term resources. Outsourcing impact may be reflected in reduction in employment costs, reduction in investment in assets, and reduction in research development expenditures (Juma’h and Wood, 2000). The benefits may accrue in form of cost savings (Martinsons, 1993; Beasley et al., 2009), technology acquisition, improved flexibility for dynamic business environments, positive effects on stock valuations (Agrawal et al., 2006) as the likely benefits. A few authors have reported neutral impact, neither significantly positive nor negative (Florin et al., 2005; Oh et al., 2006). Others have listed the negative effects which range from over reliance on IS vendors (Barthelemy and Geyer, 2001), loss of strategic flexibility, lack of maturity and experience on part of company and vendor (Willcocks et al., 1995), loss of innovative capabilities and technological indivisibility (Earl, 1996), intangible costs of outsourcing, switching costs (Whitten and Wakefield, 2006), technological captivity to vendor, etc. (Palvia, 1995; Kern et al., 2002). Thus it becomes very important to consider the impact of outsourcing considering not only the benefits that would be roped in by the IS outsourcing vendor, but it should also include all the likely risks associated with the outsourcing relationship. Expected impact of outsourcing may be divided into three categories depending on the time period as short-term impact, mid-term impact and long-term impact:

Information systems outsourcing 41

Figure 5. Constituents of IS alignment

JEIM 25,1

.

.

42 .

Short term impact. This category would include the effects of outsourcing that are usually felt in six months to one year from the start of outsourcing. These may be concerning the IS efficiency, service levels of the IS operations, cost savings on IS and productivity improvements. Medium term impact. This impact would result over a time span of one to three years from the initiation of outsourcing. It usually deals with the tactical business concerning the bank profitability, change in overall performance levels of whole systems and processes, IS controls and experiences with the outsourcing vendor including the associated risks of outsourcing. Long tem impact. Long-term impact of outsourcing would be felt usually after three years and onwards and deals with subjects usually strategic to the company. It would consist of the changes in the organization culture, impact of the new organization structure after outsourcing, increase/decrease in core strengths of the company and development of new skills and competencies by the company.

Outsourcing drivers Various authors have provided varying reasons on which IS managers justify IS outsourcing decision. DiRomuldo and Gurbaxani (1998) have identified three reasons for IS outsourcing as: IS improvement; commercial exploitation and to improve business impact. Grover et al. (1994) have identified various reasons for IS outsourcing under three categories of strategic, economic and technological factors. The reasons for outsourcing may be as varied as cost control, suppliers hard pitching for outsourcing, an organization’s structural and cultural factors (McFarlan and Nolan, 1995), influence of media (Loh and Venkatraman, 1992), local cultural factors (Barthelemy and Geyer, 2001), and politics of affiliates in the company’s structure (Lee and Kim, 1997). It is likely that the outsourcing is influenced by the combined effects of external media, vendor pressure and internal communications at the personal level among managers of companies (Hu et al., 1997). A company may be driven to outsourcing due to different reasons particular to that company like the market segment it is operating in, level of competition, ownership nature of the company, management focus, etc. and these drivers may be many, such as business focus on core banking functions, low cost of ownership, shortage of skilled IS manpower, low setup time, and like. Some of the drivers may be very strong and visible, while others may have to be understood through serious deliberation and treated accordingly by the deciding manager. Degree of IS outsourcing With the increasing complexities and costs of IS tools, IS managers are experimenting with different sourcing options of IS services, from “total outsourcing” to a “limited involvement” by vendors in select areas by providing certain specialized skills which the company does not possess. This we refer to as “total insourcing”. In between there is a band where there is varying degree of involvement of an IS vendor. This is referred to as the “selective outsourcing”. Depending on the various parameters of ownership as title of the assets, proportion of IS budget spent on outsourcing vendor or any other parameter, different sourcing options may be:

.

.

.

Total outsourcing. In this sourcing option the organization has very low amount of ownership of IS assets. However the outsourcing vendor commits an agreed level of IS service to the customer. Hence in this, organization owns the IS service without bothering about nuts and bolts of the IS infrastructure that produce the IS service. As an example, Lacity et al. (1996) have defined total outsourcing as the case wherein the organization spends more than 80 percent of its IS budget towards the outsourcing vendor. Total insourcing. This refers to the sourcing option in which the organization owns the IS infrastructure and is responsible to provide the services to its users. The organization has all the employees who are responsible to provide IS services on its payroll. There is very little involvement of external party. The employees of the organization are involved in most of the activities starting from the system design to system development and maintenance stages. Selective outsourcing. This provides for a IS setup in which organization has overall control of IS infrastructure and is responsible for the service deliverables to its user for IS services. However the organization would contract out some IS activities to external vendor that would produce the defined deliverables corresponding to that specific IS activity. In such cases vendors complement the organization’s IS capabilities.

The degree to which an organization outsources its IS functions has important implications for the organization. While a high degree of outsourcing rids the organization of the IS complexities, it brings with it certain risks of overdependence on an outsourcing vendor, loss of IS expertise, security concerns, etc. On the other hand, low outsourcing leads to situations where limited resources of the organization are spread over too many areas, leading to poor utilization of these resources and finally resulting in low performance levels, outdated products/services, difficulties in sustaining existing market shares, etc. In between the two extremes, some managers try to make a trade-off between the gains and risks of outsourcing by following selective outsourcing approach. Illustrating the framework The proposed framework comprises a chain of hierarchy of factors, and each factor contributes towards the decision to choose the degree of IS outsourcing. Illustration of the framework presented in this section is intended to establish confidence in the soundness and usefulness of the framework. The framework involves multi-criteria decision factors and consideration of several qualitative judgmental variables; analytical hierarchy process (AHP) is found most suitable to implement the framework in such a decision scenario. The validation exercise is done in two stages. In the first stage, AHP is used to determine the magnitude of importance of various factors of the proposed framework. AHP has also been used to determine the best outsourcing strategy based on general perceptions that exist in the banking industry at the prevailing time. In second stage the weights of the factors that were obtained in stage I are used to guide the level of IS outsourcing in banking scenario. This is done by evaluating the effects of its application in practice, which is illustrated in its application in three Indian banks (A, B, C), that practiced different degrees of IS outsourcing (bank A practiced low, bank B

Information systems outsourcing 43

JEIM 25,1

44

practiced selective and bank C practiced high IS outsourcing). In this stage, a limited survey using a questionnaire is done to calculate the overall scores of each bank using the weights for the framework factors that were derived from the stage I. An analysis of the overall score gives valuable results on the applicability of the proposed framework. Outsourcing practices in each of the bank that are studied are endorsed by the results of the framework, and hence valid for application in decision situations. The details of the process of validation is explained at the beginning of each stage. While different authors have given different definitions of classification of outsourcing degree most widely used being given by Lacity et al. (1996), who have defined high outsourcing as the cases where company may be spending upwards of 80 percent of its IS expenditure on the outsourcing vendors. However, in this study, based on the inputs obtained from the literature survey and understanding of the actual practices in Indian banks, degree of outsourcing would be measured on the proportion of IS expenditure going to the third party IS vendor for the IS services. There are three categories of outsourcing that are relevant and are defined as: (1) Low IS outsourcing (L) , 30 percent of IS expenditure. (2) Medium IS outsourcing (M) 30-50 percent of IS expediture. (3) High IS outsourcing (H) . 50 percent of IS expenditure. Stage I The IS outsourcing decision comprises of a chain of hierarchy of the factors as mentioned in the outsourcing framework and each factor contributes towards the final decision of choosing the degree of IS outsourcing. AHP was selected to guide us in choosing the right degree of IS outsourcing. The AHP, developed by Thomas Saaty, allows decision makers to model a complex problem in a hierarchical structure showing the relationships of the goal, objective (criteria), sub objectives, and alternatives. AHP can be used to tackle the complex problems of choice and prioritization. It has been used in various situations of decision making including environment impact assessment (Ramanathan, 2001); choosing best irrigation methods (Karami, 2006) in group decision-making situations with non-equivalent importance of individuals in the group (Beynon, 2005). Vaidya and Kumar (2006) have reported 150 application papers using AHP in different decision situations that provide the confidence in using it in our framework. AHP employs both quantitative and qualitative approaches to solve a decision problem. Qualitatively, a complex problem is decomposed into a hierarchical structure. Quantitatively, it adopts pair-wise comparisons to rate the decision elements. Further, AHP employs redundant comparisons to ensure the validity of judgments. It also provides a measure of inconsistency for discarding inconsistent judgments (Lam and Chin, 2005). AHP is used here to guide the managers in choosing the degree of IS outsourcing while considering the major decision factors of the outsourcing framework that have been suggested earlier. The decision factors were derived from the outsourcing framework that is suggested. To apply AHP, eight IS experts were involved. Six of these experts held senior positions in different banks and two were IS consultants who had experience in implementing IS in banks. Table VI gives the details of the experiences of these experts.

These experts were involved to obtain the data about relative importance of the decision factors of framework towards the goal to choose the degree of IS outsourcing. Further AHP is used here to prioritize the major decision factors of the above-mentioned outsourcing framework to arrive at the weights of these decision factors. To undertake these objectives, AHP process is performed and it can be explained in four steps: (1) Structuring the hierarchy of decision factors. The complex problem of selecting the best option among the three levels/ degree of IS outsourcing is decomposed into a multilevel hierarchical structure as shown in Figure 4. The first level is the goal: to select degree of IS outsourcing. The second level is the category of factors: IS strategic alignment, Short-, Medium- and Long-term impact and IS outsourcing drivers. The third level further decomposes these factors into sub-factors as shown in Figure 4. (2) Data collection by pair-wise comparison of the decision elements. Using the nine-point scale, relative importance of experts for the factors at the same level with respect to factors of their preceding level is recorded. The scale for relative importance is given in Table VII. (3) Measuring consistency of judgments. Consistency ratio (CR) is calculated to evaluate the consistency of the judgments. It has been suggested that CR value of 0.1 or below is acceptable. It is observed that CR value of all observations is either below or equal to 0.10 as desired (Table VIII). (4) Calculating the relative weights of factors. To calculate the relative weights of the factors expert choice software is used. It is used to calculate the local weight, which is the priority of an element with respect to its preceding element. The Number of years of experience

1 2-3 4-5 6-7 8-9

45

Number of experts

. 25 21-25 16-20 10-15

Intensity of importance

Information systems outsourcing

2 1 3 2

Definition

Explanations

Equal importance Weak-moderate importance Moderate plus- strong importance Strong plus-very strong importance Very, very strongextreme importance

Two activities contribute equally to the objective Experience and judgment slightly favor one activity over another Experience and judgment strongly favor one activity over another An activity is favored very strongly over another; its dominance demonstrated in practice The evidence favoring one activity over another is of highest possible order of affirmation

Table VI. Experience of respondents

Table VII. Scale of importance for AHP

Table VIII. Weights of decision factors derived from AHP process 0.00

0.00

0.00

0.00

IS strategic alignment

Short-term impact

Medium-term impact

Long-term impact

0.154

0.248

0.190

0.352

Weight

0.05 0.10

0.02

Intellectual assets Learning competence Cost reductions

0.00

IS controls

0.05

Cost savings 0.01

0.01

IS efficiency

Profitability

0.09

0.08

IS strategic orientation

Business strategic orientation

Subfactor

Level 2 Value of inconsistency

0.179

0.200

0.800

0.250

0.750

0.667

0.333

0.333

0.667

Weight

0.057 0.128 0.012 0.064 0.043 0.004 0.019 0.035 0.014 0.044 0.069 0.022 0.102 0.094 0.017 0.034 0.008 0.027 0.067 0.042 0.004 0.017 0.006 0.001 0.006 (continued)

Selective outsourcing High outsourcing Low outsourcing Selective outsourcing High outsourcing Low outsourcing Selective outsourcing High outsourcing Low outsourcing Selective outsourcing High outsourcing Low outsourcing Selective outsourcing High outsourcing Low outsourcing Selective outsourcing High outsourcing Low outsourcing Selective outsourcing High outsourcing Low outsourcing Selective outsourcing High outsourcing Low outsourcing Selective outsourcing

Global weight 0.019

Level 3 Low outsourcing

Alternative

46

Factor

Level 1 Value of inconsistency

JEIM 25,1

Outsourcing drivers

Factor 0.05

Level 1 Value of inconsistency 0.056

Weight 0.05

0.08

Lack of IS skills

Business focus

Subfactor

Level 2 Value of inconsistency

0.709

0.113

Weight

Level 3

Selective outsourcing High outsourcing Low outsourcing Selective outsourcing High outsourcing

High outsourcing Low outsourcing

Alternative

0.002 0.003 0.003 0.010 0.022

0.003 0.001

Global weight

Information systems outsourcing 47

Table VIII.

JEIM 25,1

48

global weight with respect to the goal of choosing the degree of IS outsourcing i.e. the three options of IS outsourcing degree is then calculated by multiplying the local weight of an element by the weight of its preceding element. The judgments are finally synthesized using the geometric mean approach as suggested by Saaty. Table VIII gives the details of the local weight of the factors and global weights of the factors with respect to the three alternatives (low, selective and high is outsourcing) of the goal of choosing the IS outsourcing degree. Results and analysis of AHP Results of AHP process can be analyzed for two purposes. First AHP is analyzed to help in choosing the degree of IS outsourcing. Further, AHP is used in prioritizing the decision factors of the IS outsourcing framework. To choose the degree of IS outsourcing The results (output of Expert Choice software based on AHP) from the AHP process in terms of the syntheses of observations with respect to the goal of choosing the degree of IS outsourcing is shown in Figure 6. The results show that high IS outsourcing emerges as the best option with weight of 0.455. Selective outsourcing emerges the next best option with weight of 0.422 while low outsourcing comes out to be least preferred (weight of 0.123). Hence it emerges that high IS outsourcing is the best advised choice for managers as per the respondents in stage 1. The results also show that low outsourcing is the least fruitful option. This is in line with the popular trend of IS outsourcing as is being observed in industry. However, it is important to mention here that selective outsourcing option is close in terms of preference. This is in line with many authors who have advocated a balanced approach to degree of IS outsourcing (Hoecht and Trott, 2006; Walden and Hoffman, 2007; Bhalla et al., 2008). This gives us the confidence on the suitability and applicability of the framework. Further the AHP exercise has met the inconsistency requirements (overall value of 0.08), which is within the maximum limit of 0.10. Prioritization of decision factors of IS outsourcing The AHP process also has led to prioritizing the decision factors of IS outsourcing. Table VIII gives the weights of the five decision factors and their sub factors. It also shows the global weight in respect to goal of choosing the degree of IS outsourcing.

Figure 6. Decision output of AHP process

The results indicate that IS alignment has emerged as the most important factor in choosing the degree of IS outsourcing (weight of 0.352). Thus it may be inferred that managers value the importance of business strategies and IS strategic orientation of their banks while deciding on outsourcing decisions. Among the three categories of impact according to the time period, which are short-term, medium-term and long-term impact, it is observed that medium-term impact emerges as the most important impact factor (weight of 0.248) in selecting IS outsourcing degree followed by short term impact (weight of 0.190) and lastly long-term impact (0.154). It may be inferred that managers consider IS outsourcing decisions as strategic decision and are concerned about medium term effects. Another interpretation of this could be that managers consider the middle of path approach- they are not swayed by short-term gains of IS outsourcing and also are not sure of long-term concerns or gains of IS outsourcing. Outsourcing drivers also have definite role in outsourcing decisions. The findings can be stretched further to analyze the importance of sub factors of the decision factors of IS outsourcing. Weights of these sub factors that give the relative importance with respect to their parent factors are given in Table VIII. It emerges that business strategic orientation is the most important sub factor (weight of 0.667) for IS alignment followed by IS strategic orientation (weight of 0.333). It shows that banks lay high importance to business strategy while deciding IS outsourcing. Similarly, in the short-term impact factor, it is seen from table that cost reduction assumes higher importance than IS efficiency. Profitability represents higher (0.750) to medium-term impact as compared to IS controls (0.250). Similarly in case of long-term impact intellectual assets are more important than learning competence. Analyzing the outsourcing drivers, it emerges that business focus is the most important (0.709) sub factor of outsourcing drivers followed by cost savings (weight of 0.179) and lack of IS skills (weight of 0.113). Analyzing the global weights of the decision elements of IS outsourcing factors (sub factors) as given in Table VIII, it is seen that business strategic orientation in high IS outsourcing has the highest global weight (0.128). Thus it implies that business strategy is the most important factor in deciding the IS outsourcing degree, and its role is maximum in high IS outsourcing. Second most important decision element emerges to be profitability and it occurs in the selective IS outsourcing alternative. It shows that profitability is one of the most important criteria in selecting IS outsourcing degree. Thus it is observed that high IS outsourcing is the optimal IS outsourcing strategy and this strategy takes care of the short-term, medium-term and long-term interests of banks and gives overall best results for Indian banks. However, it is important to mention that this decision has been arrived based on the overall opinion of the eight experts that comprised bankers and IS consultants. While the prudence of the above outcome decision cannot be doubted, there may be variation in different banks leading to varied opinion on outsourcing decisions. To have a better understanding about the applicability of this framework in individual cases, it is decided to apply the framework in three banks (A, B and C). This is explained in stage II. Stage II. Having obtained the weights of the different factors in framework in stage I, it is now desired to apply these weights to framework factors individually in three banks which are referred to as (banks A, B and C). These banks are chosen on the criteria of degree of IS outsourcing being practiced. These three banks practiced different degrees of IS outsourcing i.e. low outsourcing (Bank A), selective outsourcing

Information systems outsourcing 49

JEIM 25,1

50

(Bank B) and high IS outsourcing (Bank C). It was desired to analyze these three banks on the lines of the decision factors of the IS outsourcing framework. To carry out this exercise, questionnaire having questions related to decision factors of the framework was sent by courier and e-mail to head of the IS department in these three banks to take response from senior-most managers in their IS department. Respondents were asked to indicate the focus and rating of these decision factors in context of the bank they represented on a five-point Likert scale. After one week, they were reminded through email and phone. Finally, twenty responses were received from these three banks. Table IX presents the summary of number of responses, designation and length of experience of the respondents from each of the bank that participated in the survey. Mean scores and aggregate mean scores are calculated for the responses of these three banks. Further mean scores of these factors/subfactors of the framework are multiplied with the weight of these factors/subfactors as obtained from AHP exercise (Table VIII) to arrive at the weighted averages. These are analyzed in the three scenarios according to the degree of IS outsourcing practiced in these three banks. The three scenario provide a comparative analysis of these banks associating the IS outsourcing to their business strategy and IS strategy. Further these three banks are analyzed in terms of the impact of IS outsourcing in these banks in short, medium and long term. It also analyzes the drivers of IS outsourcing in these three scenarios of IS outsourcing. Table X gives the weighted mean scores of the decision factors/subfactors of IS outsourcing in the three scenarios of low, selective and high IS outsourcing. Revisiting the framework in three banks Outcome of the responses are analyzed in case of the three banks and scores (weighted averages) of the decision factors of the framework as given in Table X. There are three scenarios of IS outsourcing: low, selective and high outsourcing. These three banks, representing the three scenarios, are analyzed in the context of the proposed outsourcing framework. Results of overall score are shown in Table X. The decision factors of the framework that have aggregated mean score less than 3.00 has been classified as “low” desirability while in case if aggregate score exceeds 4.00 value, it is Experience (years)

Number of respondents

Designation

Number of respondents

a

Table IX. Summary of designation and experience of respondents

Bank A 26-30 21-25 15-20 Bank B b . 30 26-30 21-25 15-20 Bank C b 26-30 21- 25 15-20

2 4 2

Deputy general manager Assistant general manager Chief manager

2 3 3

1 2 2 1

General manager Deputy general manager Assistant general manager

1 2 3

2 2 2

General manager Deputy general manager Assistant general manager Chief manager

2 2 1 1

Notes: aNo. of respondents ¼ 8; bNo. of respondents ¼ 6

Overall score

Outsourcing drivers

Long-term impact

Medium-term impact

Short-term impact

IS alignment

Framework factor

Business focus Cost reductions Lack of IS skills

Intellectual assets Learning competence

Profitability IS controls

IS efficiency Cost savings

Business strategic orientation IS strategic orientation

Framework subfactor 0.352 0.667 0.333 0.190 0.333 0.667 0.248 0.750 0.250 0.154 0.800 0.200 0.056 0.709 0.179 0.133

Weight 0.861 1.571 0.874 0.427 0.749 1.501 0.705 1.969 0.875 0.450 2.300 0.625 0.150 1.861 0.515 0.311 2.593

Bank A (Low IS outsourcing) (n ¼ 8) Weighted average 1.271 2.112 1.498 0.559 1.055 1.890 1.085 3.250 1.125 0.672 3.466 0.900 0.216 2.717 0.686 0.452 3.803

Bank B (Selective IS outsourcing) (n ¼ 6) Weighted average

1.604 3.113 1.443 0.880 1.543 3.090 1.059 3.187 1.083 0.643 3.466 0.777 0.263 3.426 0.835 0.439 4.459

Bank C (High IS outsourcing) (n ¼ 6) Weighted average

Information systems outsourcing 51

Table X. Weighted mean scores of the framework factors

JEIM 25,1

52

assumed to achieve “high” desirability. The three classifications based on the overall aggregate scores in these three scenarios are categorized as: (1) Overall aggregate weighted score , 3.00 – low outsourcing. (2) Overall aggregate weighted score 3.00-4.00 – selective outsourcing. (3) Overall aggregate weighted score . 4.00 – high outsourcing. Comparative analysis of the framework factors in these three banks can lead to generalization of the utility of the framework and formulation of the appropriate strategies for IS outsourcing in Indian context. Based on the above-mentioned classification, it is clear that bank A is suggested to adopt “low” IS outsourcing given its focus and score on various decision factors of the outsourcing framework as given by Table X. It is important to note that this bank is actually practicing “low IS outsourcing” strategy. Hence this framework is validated. On the similar lines, it is observed that bank B and bank C are suggested to adopt “selective” and “high” IS outsourcing respectively which is actually being practiced by these banks. This validates our framework. However, it is pertinent to mention here that the validation exercise has been done on a small sample due to constraints of time and resources and a study involving a larger sample is desired. Further outsourcing is a complex decision process, which is the interplay of various factors: internal as well as external environmental factors. While the above-mentioned framework tries to cover broad factors, it gives flexibility to practitioners to account for different subfactors under these factors. The application of AHP using these broad array of subfactors would lead to an appropriate decision model and customized solutions for the IS outsourcing in such situations. For example outsourcing barriers may be considered as decision factors, wherein such barriers strongly affect the outsourcing decisions. Further business environment is undergoing continuous changes and hence correspondingly different factors influence the IS outsourcing decisions. While the proposed framework may be applicable in the current environment, it is advised to review the framework on regular intervals and make suitable changes as well as introducing the new relevant factors and omit the factors are not relevant. The above issues may be taken by future researchers to further the research in this area. Synthesis and discussion Over the last few years there has been increasing interest shown in outsourcing of IS. While proponents of IS outsourcing refer to a number of advantages, there are critics who list a number of risks emerging from IS outsourcing. Some of these may be of long-term nature and hence demand careful inspection. In fact if a balanced view is taken, IS outsourcing combine both advantages as well as disadvantages. Outsourcing has led to different results in different companies. However, the managers find it difficult to find, if IS outsourcing can address their problems. Further there is no “one solution applies everywhere” since companies differ in the environment in which they operate. It is up to the manager to find out his/her limitations in the area of information systems versus the strategic importance of the processes facilitated by these IS, and then to design an outsourcing structure that would fill those gaps. Hence managers require to develop the IS outsourcing roadmap that is uniquely suitable for their company. This paper has suggested a framework that would help the company to

design a IS outsourcing structure by providing a structured and systematic approach to undertake the IS outsourcing decision. The proposed framework advocates that IS strategy is related to business strategy and hence managers need to identify the business goals, understand its customer and competition, its strengths and weaknesses, and foresee future trends to evolve suitable business strategies. Keeping in view these strategic business orientation, IS goals should be evolved considering the organization’s capabilities in IS domain, skilled manpower, investment factors. The business strategies and IS strategies need to be synthesized to give IS strategic alignment that would give the IS roadmap for the organization. Outcome of this strategic alignment would lead to deciding on the acquisition, implementation and maintenance of the IS infrastructure in form of IS outsourcing strategy including the degree of outsourcing. This addresses the issue of incorporating the importance of strategy as the basis for initiating the process of IS outsourcing (Loh and Venkatraman, 1992; McIvor, 2008). Hence the manager when using the framework is forced to address the issues of “alignment of business strategy with its IT capability” and also keeping in view the core competence of the organization. The framework is able to not only bring out the driving factors in its strategy making, but also tries to quantify them. This would help the practitioners and researchers to understand the relative importance of the constituent factors in the strategy formula. For example in the illustration that has been used to validate the framework, it emerged that IS strategic alignment is most important factors in the strategy followed by medium-term impact as observed through the results. This also addresses the limitations of the frameworks which tend to guide the post-outsourcing situations (Kern and Willcocks, 2000). While there have been efforts to suggest the framework in guidance of the direction of IS outsourcing, these are constrained by already having defined fixed factors as in the framework suggested by researchers (McFarlan and Nolan, 1995; Han et al., 2008). The proposed framework gives practitioners the freedom to choose the factors first by suitable brainstorming and then by measuring the comparative strength of these factors using the AHP technique. It also scores advantages over some of the frameworks which are inclined to some form of outsourcing model which makes these frameworks biased towards certain formats of IS outsourcing as evidenced by the framework proposed by King and Malhotra (2000) and Mojsilovi et al. (2007). There is limited understanding among the practitioners about the impact of IS outsourcing with progress of duration of outsourcing. While King and Malhotra (2000) did bring about the importance of effects of outsourcing depending on the time period, the framework proposed by them is applicable only in certain conditions. IS outsourcing is seen as a means to cut costs, which is not always true, as reported in many failed cases of IS outsourcing. There is much more to IS outsourcing than simply saving costs in short term. The outsourcing should form as part of the strategy. Hence it is important to identify the possible impact of IS outsourcing rather than only the cost savings. This brings the necessity for identifying all possible areas of impact. The framework has categorized the impact into three subparts in form of time duration, which are short-, medium- and long-term impact. This gives the practitioners of framework the advantage of factoring all possible effects rather than relying only on cost savings. Increasingly the managers have realized considering the effects of outsourcing in long term. This also helps to factor the different risks which may not be immediate but may occur over a medium to longer time span. Further, managers are

Information systems outsourcing 53

JEIM 25,1

54

advised to assess the impact of the adopted outsourcing approach in the short-, medium- as well as long-term on the IS performance, business performance, security, core competence, learning environment and other specific parameters that are in line with the organization’s business goals. This framework provides for developing the right outsourcing structure, keeping in view the long-term focus while addressing the short to medium priorities. To this extent this framework is useful especially to the practitioners. The IS outsourcing degree is further influenced by certain outsourcing drivers. The manager needs to identify these and then manage these drivers to attain the level of outsourcing that is best suited to the organization. This framework is able to capture these drivers which would influence the outsourcing process. As stated earlier, we have realized that there are two categories of frameworks – one that can be applied in specific situations as provided by Chou and Chou (2009), Sherwood (1997) and many more. These frameworks are difficult to apply in an as-is form and would need customization as per the situations in which they are applied. The other category of frameworks that can be applied is generally the staged model (Mojsilovi et al., 2007; McIvor, 2000). While this may be useful to understand the outsourcing process, they are of limited relevance to many practitioners. Practitioners would find the proposed model here more convenient and easy to apply and yet the framework can be flexibly adapted. The practitioners simply need to fill the factors, which would emerge after their discussions and deliberation, in the framework and they would be given comparison of the choice of action. This framework is also easily programmed and ca be converted into a software application. Hence this becomes a very useful tool for the practitioners in decision making in the outsourcing decisions. However, it is important to emphasize that outsourcing is a complex decision process, which is the interplay of various factors: internal as well as external environmental factors. While the above-mentioned framework tries to cover broad factors, it gives flexibility to practitioners in accounting for different sub factors under these factors. There needs to be some care taken while implementing an outsourcing decision. These refer to some risks involved in outsourcing the IS referred to as IS outsourcing barriers, which would discourage outsourcing these IS services. The manager, while deciding on outsourcing his/her IS should determine the reasons which drive the company for outsourcing IS, and, at the same time, should also consider the likely potential risks associated with the outsourcing decision. This helps company to prepare for such contingent situations and incorporate the suitable countermeasures for such risks. Conclusion Over the last few years there has been increasing interest shown in outsourcing of IS. While proponents of IS outsourcing refer to a number of advantages, there are critics who list a number of risks emerging from IS outsourcing. Some of these may be of long-term nature and hence demand careful inspection. In fact if a balanced view is taken, IS outsourcing combines both advantages as well as disadvantages. Outsourcing has led to different results in different companies. However, managers find it difficult to discover if IS outsourcing can address their problems. Further there is no “one solution applies everywhere” since companies differ in the environment in which they operate. It is up to the manager to find out his/her limitations in the area of IS versus the strategic importance of the processes facilitated by these IS and then designs an outsourcing structure that would fill those gaps. Hence managers require to develop the IS outsourcing roadmap that is uniquely suitable for their company.

We started with exploring the available frameworks through literature review and found that while there are few frameworks available, these are constrained in having limited applicability for the practicing managers. Further we were also interested in important issues of creating the strategic alignment of technology and business issues. It was also felt that managers needed some guidance in determining the right degree of outsourcing. This paper has suggested a framework that would help the company to design a IS outsourcing structure by providing a structured and systematic approach to undertake the right IS outsourcing decision. The proposed framework advocates that IS strategy is related to business strategy and hence managers need to identify the business goals, understand its customer and competition, its strengths and weaknesses, and foresee future trends to evolve suitable business strategies. Keeping in view these strategic business orientation, IS goals should be evolved considering the organization’s capabilities in IS domain, skilled manpower, investment factors. The business strategies and IS strategies need to be synthesized to give IS strategic alignment that would give the IS roadmap for the organization. Outcome of this strategic alignment would lead to deciding on the acquisition, implementation and maintenance of the IS infrastructure in form of IS outsourcing strategy including the degree of outsourcing. The IS outsourcing degree is further influenced by certain outsourcing drivers. The manager needs to identify these and then manage these drivers to attain the level of outsourcing that is best suited to the organization. Further managers are advised to assess the impact of the adopted outsourcing approach in short, medium as well as in long term on the IS performance, business performance, security, core competence, learning environment and other specific parameters that are in line with the organization’s business goals. The proposed framework has made use of AHP to arrive at the best option. Illustration of the framework is made considering select banks in India. Invariably, high IS outsourcing emerges as the best option with selective outsourcing as next best choice. The AHP process also has also helped in prioritizing the decision factors of IS outsourcing. Most noticeable is IS alignment that is regarded as the most important factor in choosing the degree of IS outsourcing. Impact of IS outsourcing is examined over short-, medium- and long-term impact. In this study, medium-term impact is found to be the most important impact factor in selecting IS outsourcing degree followed by short-term impact. The proposed framework benefits the managers who are faced with decisions regarding the IS outsourcing and has certain strengths which may be stated as: . This framework gives a multi-paradigm approach to develop information systems outsourcing strategy for any company. It provides the management a systematic approach to design the information systems structure considering the various activities related to IS processes and the form of outsourcing including the extent of outsourcing. . The framework provides for creating a strategic fit between the business goals and the IS capabilities and orientation of any company. It helps the managers to create the desired IS infrastructure through outsourcing strategy where in a optimum level of benefits of outsourcing are generated while keeping the risks of outsourcing at the minimum. . The framework is flexible and modular. It considers various factors internal as well as external that prompt for IS outsourcing.

Information systems outsourcing 55

JEIM 25,1

56

.

The framework provides a combination of analytical and creative techniques. The framework takes a structured analysis route by systematically probing and decomposing the business requirements, positioning the strategic role of the company with respect to its information systems to arrive at innovative solution.

The framework is a step towards in meeting the call of practitioners who now can choose the best option in IS outsourcing and trust over the decision taken. This opens up an opportunity to create a decision support system (DSS) aimed at facilitating the decision process in IS outsourcing. We suggest scope for a more detailed study in future on this framework to have more confidence on this framework. For the researchers, it is would be useful to attempt validation in different industry sectors as in manufacturing, government as well as in different countries to ensure wider acceptability of the same. References Adeleye, B.C., Annansingh, F. and Nunes, M.B. (2004), “Risk management practices in IS outsourcing: an investigation into commercial banks in Nigeria”, International Journal of Information Management, Vol. 24 No. 2, pp. 167-80. Agrawal, M., Kishore, R. and Rao, H.R. (2006), “Market reactions to e-business outsourcing announcements: an event study”, Information and Management, Vol. 43 No. 7, pp. 861-73. Allen, A. and Chandershekar, A. (2000), “Outsourcing services: the contract is just the beginning”, Business Horizons, March-April, pp. 25-34. Alsudairi, M. and Dwivedi, Y.K. (2010), “A multi-disciplinary profile of IS/IT outsourcing research”, Journal of Enterprise Information Management, Vol. 23 No. 2, pp. 215-58. Aubert, B.A., Rivard, S. and Patry, M. (2004), “A transaction cost approach of IT outsourcing”, Information and Management, Vol. 41, pp. 921-32. Aundhe, M.D. and Mathew, S.K. (2009), “Risks in offshore IT outsourcing: a service provider perspective”, European Management Journal, Vol. 27 No. 6, pp. 418-28. Aydin, M.N., Groot, J.D. and Hillegersberg, J. (2010), “Action readiness and mindset for IT offshoring”, Journal of Enterprise Information Management, Vol. 23 No. 3, pp. 326-49. Bahli, B. and Rivard, S. (2005), “Validating measures of information technology outsourcing risk factors”, Omega, Vol. 33, pp. 175-87. Barthelemy, J. and Geyer, D. (2001), “IT outsourcing: evidence from France and Germany”, European Management Journal, Vol. 19 No. 2, pp. 195-202. Beasley, M., Bradford, M. and Dehning, B. (2009), “The value impact of strategic intent on firms engaged in information systems outsourcing”, International Journal of Accounting Information Systems, Vol. 10, pp. 79-96. Beynon, M.J. (2005), “A method of aggregation in DS/AHP decision-making with the non-equivalent importance of individuals in the group”, Computers & Operations Research, Vol. 32, pp. 1881-96. Bhalla, A., Sodhi, M.S. and Son, B. (2008), “Is more IT offshoring better? An exploratory study of western companies offshoring to South East Asia”, Journal of Operations Management, Vol. 26, pp. 322-35. Chou, D.C. and Chou, A.Y. (2009), “Information systems outsourcing life cycle and risks analysis”, Computer Standards & Interfaces, Vol. 31, pp. 1036-43. Clark, T.D., Zmud, R.A. and McCray, G.E. (1995), “The outsourcing of information services: transforming the nature of business in the information industry”, Journal of Information Technology, Vol. 10 No. 4, pp. 221-37.

DiRomuldo, A. and Gurbaxani, V. (1998), “Strategic intent for IT outsourcing”, Sloan Management Review, Summer, pp. 67-80. Earl, M.J. (1996), “The risks of outsourcing IT”, Sloan Management Review, Spring, pp. 26-33. Florin, J., Bradford, M. and Pagach, D. (2005), “Information technology outsourcing and organizational restructuring: an explanation of their effects on firm value”, Journal of High Technology Management Research, Vol. 16 No. 2, pp. 241-53. Gonzalez, R., Gasco, J. and Llopis, J. (2005), “Information systems outsourcing reasons in the largest Spanish firms”, International Journal of Information Management, Vol. 25, pp. 117-36. Goo, J. and Huang, C.D. (2008), “Facilitating relational governance through service level agreements in IT outsourcing: an application of the commitment-trust theory”, Decision Support Systems, Vol. 46, pp. 216-32. Grover, V., Cheon, M.J. and Teng, J.T.C. (1994), “A descriptive study on the outsourcing of information systems functions”, Information and Management, Vol. 27, pp. 33-44. Han, H.S., Lee, J.N. and Seo, Y.W. (2008), “Analyzing the impact of a firm’s capability on outsourcing success: a process perspective”, Information & Management, Vol. 45, pp. 31-42. Hoecht, A. and Trott, P. (2006), “Innovation risks of strategic outsourcing”, Technovation, Vol. 26, pp. 672-81. Hu, Q., Saunders, C. and Gebelt, G. (1997), “Research report: diffusion of information systems outsourcing: a reevaluation of influence sources”, Information Systems Research, Vol. 8 No. 3, pp. 288-301. Juma’h, A. and Wood, W. (2000), “Outsourcing implications on companies’ profitability: a sample of UK companies”, Work Study, Vol. 49 No. 7, pp. 265-74. Karami, E. (2006), “Appropriateness of farmers’ adoption of irrigation methods: the application of AHP method”, Agricultural Systems, Vol. 87, pp. 101-19. Kern, T. and Willcocks, L. (2000), Cooperative Relationship Strategy in Global IT Outsourcing: The Case of Xerox Corporation, Perspectives on Cooperation, Oxford University Press, Oxford. Kern, T., Kreijger, J. and Willcocks, L. (2002), “Exploring ASP as sourcing strategy: theoretical perspectives: propositions for practices”, Journal of Strategic Information Systems, Vol. 11, pp. 153-77. Khalfan, A.M. (2004), “Information security considerations in IS/IT outsourcing projects: a descriptive case study of two sectors”, International Journal of Information Management, Vol. 24 No. 1, pp. 29-42. King, W.R. and Malhotra, Y. (2000), “Developing a framework for analyzing IS sourcing”, Information and Management, Vol. 37, pp. 323-34. Lacity, M.C., Willcocks, L.P. and Feeny, D.F. (1995), “IT outsourcing: maximize flexibility and control”, Harvard Business Review, Vol. 73 No. 3, pp. 84-93. Lacity, M.C., Willcocks, L.P. and Feeny, D.F. (1996), “The value of selective IT outsourcing”, Sloan Management Review, Spring, pp. 13-25. Lam, P.K. and Chin, K.S. (2005), “Identifying and prioritizing critical success factors for conflict management in collaborative new product development”, Industrial Marketing Management, Vol. 34, pp. 761-72. Lee, J.N. and Kim, Y.G. (1997), “Information systems outsourcing strategies for affiliated firms of the Korean conglomerate groups”, Journal of Strategic Information Systems, Vol. 6, pp. 203-29.

Information systems outsourcing 57

JEIM 25,1

58

Loh, L. and Venkatraman, N. (1992), “Determinants of information technology outsourcing: a cross-sectional analysis”, Journal of Management Information Systems, Vol. 9 No. 1, pp. 7-24. Lonsdale, C. and Cox, A. (1997), “Outsourcing: risks and rewards”, Supply Chain Management, July, pp. 32-4. McFarlan, F.W. and Nolan, R.L. (1995), “How to manage an IT outsourcing alliance”, Sloan Management Review, Winter, pp. 9-23. McIvor, R. (2000), “A practical framework for understanding the outsourcing process”, Supply Chain Management, Vol. 5 No. 1, pp. 22-36. McIvor, R. (2008), “What is the right outsourcing strategy for your process?”, European Management Journal, Vol. 26 No. 1, pp. 24-34. Mao, J.Y., Lee, J.N. and Deng, C.P. (2008), “Vendors’ perspectives on trust and control in offshore information systems outsourcing”, Information & Management, Vol. 45, pp. 482-92. Martinsons, M.G. (1993), “Outsourcing information systems: a strategic partnership with risks”, Long Range Planning, Vol. 26 No. 3, pp. 18-25. Miozzo, M. and Grimshaw, D. (2008), “Service multinationals and forward linkages with client firms: the case of IT outsourcing in Argentina and Brazil”, International Business Review, Vol. 17, pp. 8-27. Mojsilovi, A., Ray, B., Lawrence, R. and Takriti, S. (2007), “A logistic regression framework for information technology outsourcing lifecycle management”, Computers & Operations Research, Vol. 34, pp. 3609-27. Oh, W., Gallivan, M. and Kim, J. (2006), “The market’s perception of the transactional risks of information technology outsourcing announcements”, Journal of Management Information Systems, Vol. 22 No. 4, pp. 271-303. Paisittanand, S. and Olson, D.L. (2006), “A simulation study of IT outsourcing in the credit card business”, European Journal of Operational Research, Vol. 175, pp. 1248-61. Palanisamy, R., Verville, J., Bernadas, C. and Taskin, N. (2010), “An empirical study on the influences on the acquisition of enterprise software decisions: a practitioner’s perspective”, Journal of Enterprise Information Management, Vol. 23 No. 5, pp. 610-39. Palvia, P.C. (1995), “A dialectic view of information systems outsourcing: pros and cons”, Information and Management, Vol. 29, pp. 265-75. Park, J.Y. and Kim, J.S. (2005), “The impact of IS sourcing type on service quality and maintenance efforts”, Information and Management, Vol. 42, pp. 261-74. Prahlad, C. and Hamel, G. (1990), “The core competence of the corporation”, Harvard Business Review, Vol. 68, pp. 79-91. Quinn, J.B. and Hilmer, F.B. (1994), “Strategic outsourcing”, Sloan Management Review, Vol. 35 No. 4, pp. 43-55. Ramanathan, R. (2001), “A note on the use of the analytical hierarchy process for environment impact assessment”, Journal of Environment Management, Vol. 63, pp. 27-35. Rohde, F.H. (2004), “IS/IT outsourcing practices of small- and medium- sized manufacturers”, International Journal of Accounting Information Systems, Vol. 5, pp. 429-51. Sherwood, J. (1997), “Managing security for outsourcing contracts”, Computers & Security, Vol. 16, pp. 603-9. Udo, G.G. (2000), “Using analytical hierarchy process to analyze the information technology outsourcing decision”, Industrial Management & Data Systems, Vol. 100 No. 9, pp. 421-9. Vaidya, O.S. and Kumar, S. (2006), “Analytical hierarchy process: an overview of applications”, European Journal of Operations Research, Vol. 169, pp. 1-29.

Vinning, A. and Globerman, S. (1999), “A conceptual framework for understanding the outsourcing decision”, European Management Journal, Vol. 17 No. 6, pp. 645-54. Walden, E.A. and Hoffman, J.J. (2007), “Organizational form, incentives and the management of information technology: opening the black box of outsourcing”, Computers & Operations Research, Vol. 34, pp. 3575-91. Whitten, D. and Wakefield, R.L. (2006), “Measuring switching costs in IT outsourcing services”, Journal of Strategic Information Systems, Vol. 15, pp. 219-48. Willcocks, L., Lacity, M.C. and Fitzgerald, G. (1995), “Information technology outsourcing in Europe and the USA: assessment issues”, International Journal of Information Management, Vol. 15 No. 5, pp. 333-51. Willcocks, L.P., Lacity, M.C. and Kern, T. (2000), “Risk mitigation in IT outsourcing strategy revisited: longitudinal case research at LISA”, Journal of Strategic Information Systems, Vol. 8, pp. 285-314. Yang, C. and Huang, J. (2000), “A decision model for IS outsourcing”, International Journal of Information Management, Vol. 20, pp. 225-39. Yang, D.H., Kim, S., Nam, C. and Min, J.W. (2006), “Developing a decision model for business process outsourcing”, Computers & Operations Research, Vol. 34, pp. 3769-78. Zhengzhong, S. (2010), “The role of IS architecture planning in enhancing IS outsourcing’s impact on IS performance: its antecedents and an empirical test”, Journal of Enterprise Information Management, Vol. 23 No. 4, pp. 439-65. Further reading Loh, L. (1994), “An organizational-economic blueprint for information technology outsourcing: concepts and evidence”, Proceedings of 1994 International Conference on Information Systems, pp. 73-89. Ramaraj, P., Jacques, V., Christine, B. and Nazim, T. (2010), “An empirical study on the influences on the acquisition of enterprise software decisions: a practitioner’s perspective”, Journal of Enterprise Information Management, Vol. 23 No. 5, pp. 610-39. About the authors Umesh Gulla is Associate Professor with TERI University, New Delhi, India. He has published papers in reputed national and international journals/conference proceedings. His research interests are in information systems outsourcing, information systems management, e-commerce/e-business, e-governance, enterprise applications. Umesh Gulla is the corresponding author and can be contacted at: [email protected]. M.P. Gupta is Group Chair of IT and Coordinator of the Center for Excellence in E-governance at IIT Delhi. His research interest lies in the areas of IS/IT planning, e-business and e-government. Professor Gupta has authored the acclaimed book Government Online and edited two others, entitled Towards E-government and Promise of E-government, published by Tata McGraw-Hill, 2004. His research papers have appeared in national and international journals/conference proceedings. He has coordinated several national and international seminars/ conferences and also part of their international program committees. He is on the jury of Computer Society of India (CSI) National E-gov Awards.

To purchase reprints of this article please e-mail: [email protected] Or visit our web site for further details: www.emeraldinsight.com/reprints

Information systems outsourcing 59

The current issue and full text archive of this journal is available at www.emeraldinsight.com/1741-0398.htm

JEIM 25,1

Factors affecting ERP system implementation effectiveness Dimitrios Maditinos

60

Department of Business Administration, Technological Educational Institute of Kavala, Kavala, Greece

Dimitrios Chatzoudes

Received 27 August 2010 Revised 27 September 2010 Accepted 23 March 2011

Department of Production and Management Engineering, Democritus University of Thrace, Xanthi, Greece, and

Charalampos Tsairidis Department of Social Administration, Democritus University of Thrace, Komotini, Greece

Abstract

Journal of Enterprise Information Management Vol. 25 No. 1, 2012 pp. 60-78 q Emerald Group Publishing Limited 1741-0398 DOI 10.1108/17410391211192161

Purpose – Enterprise resource planning (ERP) systems enhance productivity and working quality by offering integration, standardization and simplification of multiple business transactions. The present study seeks to introduce a conceptual framework that investigates the way that human inputs (top management, users, external consultants) are linked to communication effectiveness, conflict resolution and knowledge transfer in the ERP consulting process, as well as the effects of these factors on ERP system effective implementation. Design/methodology/approach – The examination of the proposed conceptual framework was made with the use of a newly developed questionnaire. The questionnaire was distributed to a group of 361 Greek companies that have implemented an ERP system. Information technology (IT) managers were selected as the key respondents of the questionnaire. After the completion of the four month research period (September to December 2008), 108 usable questionnaires were returned (response rate ¼ 31 percent approximately). The empirical data were analyzed using the structural equation modelling technique (Lisrel 8.74). Findings – The main findings of the empirical study can be summarized in the following categories: the assistance provided by external consultants during the ERP implementation process is essential; knowledge transfer is an extremely significant factor for ERP system success; knowledge transfer concerning technical aspects of ERP systems is more important than effective handling of communication, as well as conflict resolution among organizational members; the role of top management support seems to be of less importance that the one provided by users. Research limitations/implications – The present study is limited by the poor definition of its population (due to lack of available data) and the relatively small size of the sample. Practical implications – The paper points out areas that adopting companies should emphasize in order to successfully implement an ERP system and, therefore, harvest its potential benefits. Originality/value – The paper proposes an enhanced conceptual framework that examines vital issues concerning ERP system effective implementation, thus, providing valuable outcomes for decision makers and academics. The originality of the paper lies in its three dimensional approach. Keywords Enterprise resource planning, Internal support, External support, ERP system effective implementation, Linear structure equation modelling, Cost effectiveness, Resource efficiency Paper type Research paper

1. Introduction Individuals, companies and managers often face difficulties in comprehending the full spectrum of capabilities and attributes of ERP systems, due to the system’s complicated nature (Finney and Corbett, 2007; Markus and Tanis, 2000; Somers and Nelson, 2004). Marnewick and Labuschagne (2005) argue that an ERP system should not only be regarded as an information system (IS), but also, in order to be effectively implemented should be regarded as an integrated business system that surrounds all business functions. The same scientists define ERP as a software package that combines both business processes and information technology (IT) features. Nowadays, ERP systems are being increasingly adopted by organizations of any kind and size, in order to avoid technical obsolesce and create sustainable competitive advantages (Al-Mashari et al., 2003; Willis and Willis-Brown, 2002). Dillard and Yuthas (2006) note that most multinational firms are using ERP software packages and even more small and midsize companies are on the route of adopting them. ERP system acquisition and implementation generally enhance productivity and working quality, since the system offers standardization and simplification in multiple, complicated operational procedures across the company (Nah et al., 2001). Moreover, information can easily be transferred, shared and exchanged among users who are working at different business divisions (Amoako-Gyampah, 2007; Kemp and Low, 2008). In general, the literature has identified the following potential benefits of ERP system implementation (Al-Mashari et al., 2003; Amoako-Gyampah, 2007; Chang, 2004; King, 2005; Scott and Kaindl, 2000; Umble et al., 2003): . improved coordination across functional departments; . increased efficiency in doing business; . reduced operating costs (lower inventory control cost, lower production costs, lower marketing costs, lower help desk support costs); . facilitation of day-to-day management; . rapid access to information for decision making and managerial control; and . support of strategic planning (through the planning of available resources). Despite the attributes and major advantages provided by ERP systems, the implementation of such systems is not always effective. Most enterprises are not able to fully justify their investments in ERP software, since the bulk of ERP benefits remain hidden. In their survey, Marnewick and Labuschagne (2005) reported that 25 percent of ERP installations exceed the initial cost and about 20 percent cannot be completed. Moreover, ERP systems often fail to meet organizational goals soon after their implementation. The cause of the general disappointment regarding ERP system effectiveness lies in a number of reasons, including a misconception about the system’s potential (Bradford and Florin, 2003; Hong and Kim, 2002; Marnewick and Labuschagne, 2005; Motwani et al., 2005). The present study aims to develop a conceptual framework that incorporates the main factors leading in the effective implementation of an ERP system. Motivated by the theoretical importance of ERP systems and the empirical failure in fully harvesting their potential, the proposed conceptual framework includes variables that, according to the best of our knowledge, have never been collectively examined before.

Factors affecting effectiveness

61

JEIM 25,1

62

Figure 1. ERP implementation process model

Built on the argument that the success of most ERP systems is decided during the initial steps of their implementation (Gargeya and Brady, 2005; Hong and Kim, 2002) and significantly depends on the cooperation with an external consulting group (Akkermans and van Helden, 2002), the present study develops an “ERP implementation process model” that investigates the impact of internal and external human inputs on ERP implementation effectiveness (see Figure 1). The need to fully incorporate the role of external consulting support in the proposed conceptual framework is imposed by its wide accepted significance in the ERP implementation process (Wang and Chen, 2006). On the other hand, the influence of internal stakeholders (top management and users) in the ERP consulting process is equally important, since they are the ones that must understand and learn to use what

is embedded in the system. By including both internal and external support, the present paper takes account of all the critical entities that could significantly impact the process and outcome of an ERP system implementation (Reimers, 2003). More analytically, the proposed “ERP implementation process model” investigates whether external and internal human inputs affect the consulting implementation process related to effective communication, conflict resolution and knowledge transfer and whether these factors lead to ERP system effective implementation. Such an integrative approach has never been attempted in the literature before and is expected to yield significant findings for companies that are about to adopt ERP systems. In general, it is argued that the proposed conceptual framework adopts a holistic approach to ERP system implementation, sheds light in areas rarely investigated and leads to interesting practical implications. The present study makes two contributions to the ERP implementation literature. First, it develops a conceptual framework that places the centre of attention on the ERP consulting process, arguing that the success of most ERP systems is decided upon their initial implementation and depends significantly on external consultation. Second, the study highlights the contribution of “people” (top management, users, external consultants) to the process of ERP implementation, based on the concept that most ERP systems, however how intelligent, need to be thoroughly adjusted to every business environment in order to be crystallized into workable ERP solutions. The following section includes the presentation of the proposed conceptual framework of the study. In the third and fourth section, the research methodology and the results are being presented. The conclusions and the impact of the research are discussed in sections 5 and 6 respectively and, finally, section 7 includes study limitations and proposals for future research. 2. The conceptual framework of the study The present study introduces a newly developed conceptual framework that places the ERP consulting process on the center of attention. According to Wang and Chen (2006, p. 1031), “one key to a successful ERP implementation is to maintain an effective and smooth consulting process”. The proposed “ERP implementation process model” consists of three dimensions (see Figure 1): human inputs; ERP consulting process; and consequence. The human input dimension includes variables about internal and external support; the ERP consulting process dimension includes variables that are likely to affect the ERP consulting process; while the consequence is the effectiveness of the implemented ERP, as it is perceived by its actual users. The aim of the study is to examine the causal relationships between seven research variables that belong to these three dimensions: (1) top management support (human input . internal support); (2) user support (human input . internal support); (3) consultant support (human input . external support); (4) communication effectiveness (ERP consulting process); (5) conflict resolution (ERP consulting process); (6) knowledge transfer (ERP consulting process); and (7) ERP system effective implementation (consequence).

Factors affecting effectiveness

63

JEIM 25,1

64

The proposed conceptual framework is based on previous studies by Wang and Chen (2006), Wang et al. (2007) and Thong (2001). The hypotheses of the study are presented below. 2.1 ERP consulting process The consulting process that takes place during and after the implementation of an ERP system is of vital significance for every company (Wang and Chen, 2006). The following paragraphs discuss the three main factors that relate to the ERP consulting process: communication effectiveness (Bloomfield and Danieli, 1995; Wang and Chen, 2006); conflict resolution (King, 2005; Robey et al., 1993; Wang and Chen, 2006); and knowledge transfer (Wang et al., 2007), as well as their effect on ERP system effective implementation. 2.1.1 Communication effectiveness. Effective communication is a strong foundation of a trustworthy relationship between external consultants and organizational members (Attewell, 1992). The more consultants and users understand each other, the more effective the communication becomes during the consulting process. Insufficient communication of users’ needs, goals and aspirations to the consultants may undermine the implementation of the ERP system (Fleck, 1993; Wang and Chen, 2006). Thus, we hypothesize that: H1. A positive relationship exists between communication effectiveness and ERP system effective implementation. The consulting process is an undertaking that, in order to be effective, constant communication with the client is needed (Lee and Kim, 1999). With effective communication, information can be transferred and exchanged easier between both parties who realize, in that way, that sustaining this relationship is at their best interest. Such relationship, accordingly, generates trust between the client company and the consultant company. As a result, the two companies become allies in a common effort to minimize conflicts that may arise in their cooperation (Lee and Kim, 1999; Morgan and Hunt, 1994; Wang and Chen, 2006). Thus, we hypothesize that: H2. A positive relationship exists between communication effectiveness and conflict resolution. 2.1.2 Conflict resolution. The implementation of an ERP system is a time-consuming process. During that process certain conflicts may occur between users and consultants (King, 2005). Such conflicts will possibly affect in an adverse way the output of the consultant-client relationship (McGivern, 1983). However, the emergence of disagreements during the implementation period should not be considered as a negative turn in the cooperation, but rather as a common incident during a long-lasting collaboration (Green, 1998). Effective management of conflicts may lead in an enhanced level of information exchange and group work, thus, improving the implementation of the ERP system (Scott and Kaindl, 2000). Thus, we hypothesize that: H3. A positive relationship exists between conflict resolution and ERP system effective implementation. 2.1.3 Knowledge transfer. Knowledge transfer in the ERP consulting process can be described as a gradual procedure in which knowledge is being transferred from

external consultants and vendors to the internal environment of the company (Wang et al., 2007). An increased level of knowledge concerning the ERP system will enable the company to exploit the new technology to its full potential and continue to achieve benefits from the use of the system in the future. Thus, we hypothesize that: H4. A positive relationship exists between knowledge transfer and ERP system effective implementation. 2.2 External consultant support Consultants play a major part in the ERP implementation challenge, since they have the technical knowledge and expertise to assist users in filling the unavoidable knowledge gab that derives from implementing a new ERP system. Under that logic, the consulting process becomes a necessity for any company that is willing to implement an ERP system (Freeman and Dart, 1993; Wang and Chen, 2006). The solutions that consultants offer during and after the configuration of the ERP system directly influence the effectiveness of the implemented ERP, independent of their interactions with their client (Wang and Chen, 2006). Thus, we hypothesize that: H5. A positive relationship exists between consultant support and ERP system effective implementation. In order to achieve high-level communication with each client and be able to resolve conflicts that may probably arise, a consultant should be particularly skilled (McLachlin, 1999). A successful consultant possesses both sufficient technical background, as well as the ability to communicate knowledge and experience, in a way that he gains the client’s trust (McGivern, 1983; Wang and Chen, 2006). Only in such a case, the client feels safe and, as a consequence, a good level of communication and an effective negotiation procedure during the whole implementation process is achieved (Wang and Chen, 2006). Therefore, we hypothesize that: H6. A positive relationship exists between consultant support and communication effectiveness. H7. A positive relationship exists between consultant support and conflict resolution. ERP systems are complex in their nature, as well as in their implementation. Therefore, each company must acquire the adequate know-how and understanding of the system in order to fully exploit its potential. Consultant support from specialists who know in detail the ERP system and have the experience of how the system operates is crucial in order to achieve the required knowledge transfer to the company. The more extended the consultant support is, the more successful the transfer of knowledge to the adopting company will be (Bessant and Rush, 1995; Wang et al., 2007). Therefore, we hypothesize that: H8. A positive relationship exists between consultant support and knowledge transfer. 2.3 Internal consultant support However competent a consultant may be, ERP implementation will not run smoothly unless the members of the client organization (top management and users) are committed to the adoption and the use of the ERP system (Wang and Chen, 2006).

Factors affecting effectiveness

65

JEIM 25,1

66

2.3.1 Top management support. Top management support describes the extent to which executive managers of the adopting firm provide the attention, resources, and authority required for ERP implementation (Wang and Chen, 2006). Top management support is a prerequisite for the successful ERP system implementation. Top managers supervise the whole implementation procedure, enable resource distribution, and support conflict management (Wang and Chen, 2006). Moreover, top management has the responsibility to align the new ERP system with the current business practices and prepare the employees for the change brought by the new technology. When top management works closely with various ERP users in the direction of the successful implementation of the ERP system, the communication between business groups is being enhanced and conflict resolution becomes attainable (Thong et al., 1996; Thong, 2001). Thus, we hypothesize that: H9. A positive relationship exists between top management support and communication effectiveness. H10. A positive relationship exists between top management support and conflict resolution. Moreover, we hypothesize that a strong support from the top management towards the implemented ERP system will lead to enhanced knowledge transfer inside the adopting organization (Boynton et al., 1994; Cohen and Levinthal, 1990): H11. A positive relationship exists between top management support and knowledge transfer. 2.3.2 User support. User support refers to the psychological state of business users toward the changes caused by the implemented ERP system, as well as toward the use of the system for performing their tasks (Wang and Chen, 2006). The users of an ERP system are usually the ones required to adjust their daily working practices to the new system’s requirements. Apparently, becoming familiar with a new ERP system is not an easy task and involves hard working and patience from the part of users (McLachlin, 1999; Soh et al., 2000; Wang and Chen, 2006). In order to favorably affect users’ perceptions about new technology, the real benefits and advantages of using the ERP system need to be continuously reminded (Umble et al., 2003). Otherwise, users are not motivated to support the ERP system in that they are not willing to cooperate with the consultants and assimilate the knowledge transferred to them. This situation provokes conflicts in the consultant-client relationship and hinders communication (Wang and Chen, 2006). Therefore, we hypothesize that a high degree of user support will strengthen communication effectiveness and conflict resolution: H12. A positive relationship exists between user support and communication effectiveness. H13. A positive relationship exists between user support and conflict resolution. Finally, we hypothesize, with alignment to H11, that a strong user support towards the implemented ERP system will lead to enhanced knowledge transfer inside the adopting organization (Boynton et al., 1994; Cohen and Levinthal, 1990): H14. A positive relationship exists between user support and knowledge transfer.

Figure 1 summarizes all the above hypotheses, thus, presenting the proposed conceptual framework of the study. 3. Research methodology 3.1 Sample of the study The conceptual framework of the present study was tested with the use of a newly developed questionnaire on a sample of Greek companies that have implemented an ERP system. Data concerning companies that could possibly be included in the sample of the study were obtained via the web sites of the leading ERP system providers that operate in Greece (e.g. Sap Hellas, Oracle Hellas, Synergy Hellas). Since no other database including companies using ERP systems exists, the use of the certain method was the only one able to provide usable information. Totally, 517 companies that have implemented an ERP system were identified.

Factors affecting effectiveness

67

3.2 Measures The questionnaire of the present study is based on items (questions) that have been used by various previous researchers (Davison, 1997; Freeman and Dart, 1993; Jiang et al., 2000; Lee and Kim, 1992; Shin and Lee, 1996; Simonin, 1999; Sussman and Guinan, 1999; Wang and Chen, 2006; Wang et al., 2007). All questions were translated to Greek and then back to English by another person, so the detection and consequent improvement of any discrepancies was possible. The five-point Likert scale was used for the measurement of all variables (1 ¼ “strongly disagree” to 5 ¼ “strongly agree”). Table I demonstrates the seven research variables, the number of items used for their measurement and the studies from which they where adapted. 3.3 Data collection The final questionnaire and a cover letter including all necessary clarifications, was sent to the IT managers of the companies of the sample. IT managers were selected as the key respondents, due to their experience and expertise. Questionnaires were sent only after telephonic contact with the IT manager in each company has been established. In order to send the questionnaire and the necessary clarifications to the person contacted by telephone, fax, traditional mail, or electronic mail services were utilized. After making all necessary telephone calls, 361 questionnaires were distributed to 361 companies that agreed to participate in the survey. The research period lasted four

Variables Top management support User support Consultant support Communication effectiveness Conflict resolution Knowledge transfer ERP effective implementation Total

Number of items 7 6 10 4 4 4 5 40

Adapted from Lee and Kim (1992) Jiang et al. (2000) Freeman and Dart (1993) Davison (1997) Sussman and Guinan (1999) Simonin (1999), Wang et al. (2007) Shin and Lee (1996)

Table I. The measurement of the variables of the study

JEIM 25,1

68

months (September to December 2008). Totally, 112 questionnaires were returned, and after realizing all necessary controls 108 were used for data analysis (data analysis was conducted with the use of the statistical packages SPSS 14.0 and Lisrel 8.74). The 112 returned questionnaires represent a very satisfactory response rate of 31 percent. The majority (24.7 percent) of the companies of the sample belong to the “Informatics” industry (sector), while 14.8 percent to the “Electronic” and 12.3 percent to the “Food” industry. Moreover, the 37 percent of the companies of the sample employ 101 to 500 employees, 30.9 percent employ 51 to 100 employees, while only 6.2 percent and 12.3 percent of the companies employ less that 50 and more that 1,000 employees respectively. Accordingly, the results indicate that the annual sales of the 32.1 percent of the companies of the sample are between 10,000,000 and 50,000,000 Euros, while the second larger category (29.6 percent) includes companies that have annual sales between 1,000,000 and 10,000,000 Euros. The majority of the respondent companies (34.6 percent) have been using an ERP system for more than two years, 29.6 percent less than two years and 35.8 percent less that one year. Finally, about half of the Greek companies of the sample (49.6 percent) have chosen “SAP Ltd” as their ERP system provider, 26.7 percent “Oracle Ltd” and 23,7 percent have chosen another supplier. 3.4 Reliability and validity The instrument (questionnaire) that was used in the present study was tested for both its content and construct validity. The control for the content validity was conducted prior to the beginning of the survey and included consultation with academics of the field, consultation with experienced practitioners, and pilot testing. The control for the construct validity was conducted in two steps. Each of the seven research variables was evaluated for its unidimensionality and reliability, for the goodness of fit to the proposed research model. The estimation of the unidimensionality of each of the seven variables was conducted using explanatory factor analysis with the method of principal component analysis. Moreover, for the estimation of the reliability of the research variables, the statistical measure Cronbach’s alpha was used (the statistical package SPSS was used in both cases). All tests concluded that all the scales used, after minor amendments (extraction of items), are valid and reliable (see Table II for the main results). Furthermore, the evaluation of the goodness of fit of each of the seven research variables to the proposed model was conducted using confirmatory factor analysis, with the use of the statistical package LISREL 8.71. All tests conducted produced satisfactory results (see Table III for the main results concerning the estimation of the goodness of fit). Finally, after the successful completion of the control for the construct validity of the questionnaire, the final score of each variable was calculated using the mean of the items used in each case. 4. Results The conceptual framework of the present study suggests that top management support, user support and consultant support are positively related with ERP system effective implementation, through communication effectiveness, conflict resolution and knowledge transfer (see Figure 1). The examination of the conceptual framework and the verification of the 14 hypotheses were conducted with the use of the “structural

Variables Top management support User support Consultant support Communication effectiveness Conflict resolution Knowledge transfer ERP system effective implementation

KaiserMayer-Olkin

Bartlett’s test of sphericity

Eigenvalue

Variance

Cronbach alpha

0.691 0.716 0.663

144.9 * 169.5 * 91.9 *

2.656 3.003 2.013

77.31% 79.63% 66.34%

0.846 0.894 0.736

0.763 0.712 0.836

163.2 * 96.3 * 23.3 *

2.520 2.112 2.963

63.85% 58.58 75.09

0.766 0.736 0.891

0.779

163.3 *

2.367

76.84

0.821

Note: *p , 0:01

Variables Top management support User support Consultant support Communication effectiveness Conflict resolution Knowledge transfer ERP system effective implementation

X2

CR

VE (%)

RMSEA

CFI

GFI

37.71 * 13.58 * 21.66 * 13.23 * 19.49 * 9.69 * 25.32 *

0.81 0.83 0.73 0.89 0.91 0.87 0.86

63 68 56 64 78 64 73

0.0967 0.097 0.095 0.096 0.097 0.086 0.099

0.97 0.99 0.96 0.99 0.96 0.96 0.97

0.98 0.99 0.99 0.97 0.99 0.99 0.97

Note: *p , 0:05

equation modeling technique”. the certain multivariate technique was used because of its ability to simultaneously examine a number of depended linear relations, where one or more construct (variable) is both dependent and independent according to the relation it belongs (Hair et al., 1995; Kelloway, 1998). For the conduction of the appropriate analysis the statistical package LISREL 8.74 was used. The estimation of the structural model was conducted with the maximum likelihood estimation method, which is the most widespread method of estimation (Anderson and Gerbing, 1988; Kelloway, 1998). The covariance matrix was used as the table of entry, because the control of the hypotheses in the structural equation modeling technique is based on the hypothesis that the matrix that will be analyzed is the covariance matrix. Thus, even though the use of the correlation matrix has widespread use in a lot of applications, the use of the covariance matrix is recommended (Kelloway, 1996). Finally, the extraction of the standardized completely solution was requested. To evaluate the fit of the overall model the chi-square value (X 2 ¼ 712:69 with 447 degrees of freedom) and the p-value (p ¼ 0:05060) were estimated. These values indicate a good fit of the data to the overall model. However, the sensitivity of the X 2 statistic to the sample size enforces to control other supplementary measures of evaluating the overall model, such as the “Normed-X 2” index (1.59), the RSMEA index (0.087) the CFI (0.95) and the GFI (0.93), that all indicate a very good fit. For the control

Factors affecting effectiveness

69 Table II. Estimation of unidimensionality and reliability

Table III. Estimation of the goodness of fit

JEIM 25,1

70

of the measurement model the significance of the factor loadings, the construct reliability and the variance extracted were estimated. Results indicated that all loadings are significant at the p , 0:05 level. Additionally, the construct reliability and the variance extracted measures for all constructs are satisfactory. Table IV illustrates all relations between research variables, as they have been determined by the hypotheses of the study (see paragraph 2). For the verification (or the rejection) of every research hypothesis, two controls have been conducted: the value and the direction of the relation between the two latent variables; and the significance of the relation, indicated by the t-value, were examined. According to Hair et al. (1995), when the t-value is above 1.96 and below 2 1.96, the hypothesis is significant at the significance level of 5 percent. Otherwise, the hypothesis is statistically insignificant. Results offer support to 8 research hypotheses (H2, H4, H5, H7, H8, H10, H12, H14), while six hypotheses are not verified by the empirical data (H1, H3, H6, H9, H11, H13). The analysis of the results gives room for interesting observations and offers guidelines to ERP implementing companies. 4.1 General observations In general, it should be highlighted that the empirical results suggest that only knowledge transfer and consultant support can directly and positively influence ERP effective implementation (H4 and H5), while the postulated effect of communication effectiveness and conflict resolution is insignificant (H1 and H3). Between these two significant paths, consultant support seems to be of greater importance that knowledge transfer (0.41 and 0.25 respectively). 4.2 “ERP consulting process” dimension The only variable of the “ERP consulting process” dimension that has a direct positive impact on ERP effective implementation is knowledge transfer (H4). Results failed to Hypothesis

Path

Effect

t-value

Result

H1

Communication effectiveness ! ERP system effective implementation Communication effectiveness ! conflict resolution Conflict resolution ! ERP system effective implementation Knowledge transfer ! ERP system effective implementation Consultant support ! ERP system effective implementation Consultant support ! communication effectiveness Consultant support ! conflict resolution Consultant support ! knowledge transfer Top management support ! communication effectiveness Top management support ! conflict resolution Top management support ! knowledge transfer User support ! communication effectiveness User support ! conflict resolution User support ! knowledge transfer

2 0.76

21.46

Rejected

0.73 1.20

3.09 1.90

Accepted Rejected

0.25

2.36

Accepted

0.41

2.46

Accepted

2 0.09 0.49 0.22 2 0.28

20.71 3.26 2.35 22.00

Rejected Accepted Accepted Rejected

0.19 0.01 0.53 0.04 0.22

1.99 0.14 3.53 0.29 2.46

Accepted Rejected Accepted Rejected Accepted

H2 H3 H4 H5 H6 H7 H8 H9 Table IV. Direct effects between research variables (test of hypotheses)

H10 H11 H12 H13 H14

establish a significant relationship between communication effectiveness and conflict resolution, on the one hand and ERP system effective implementation on the other (H1 and H3). It seems that these two variables do not have the capacity to directly influence the outcome of the ERP implementation process, mostly because they are not as equally significant as knowledge transfer and consultant support. They may be necessary for maintaining a good working environment while the implementation process takes place, but they fail to directly influence the overall success of this process. Moreover, communication effectiveness has a quite large effect (0.73) on conflict resolution (H2). This is quite logical, since the higher the communication between business entities, the better the possibility to resolve the problems that occur during the implementation of an ERP system. 4.3 “Human input” dimension User support is the only variable of the “human input” dimension that has an influence on communication effectiveness (H12). This finding indicates that the willingness of users to support the project and accept the corresponding organizational changes motivates them to openly express themselves regarding their thoughts and requirements during the implementation process. Moreover, both consultant support and top management support are positively associated with conflict resolution (H7, H10). Consultants can enhance the ERP implementation process by facilitating conflict resolution, thus, reducing the occurrence of persistent conflicts. Top management support is also critical to inter-unit conflict resolution, since top managers are responsible for coordinating the various business departments and provide compulsory guidelines and instructions. Finally, it is found that user and consultant support influence knowledge transfer (H8, H14) with the same intensity (0.22). The support of users and consultants during the implementation period leads in higher levels of knowledge transfer, meaning that the organization absorbs more knowledge about the use of the system, the knowledge gap between users and consultants is eliminated and, thus, the ERP implementation better satisfies the requirements of the company. This finding is very important, since knowledge transfer is one of the two research variables that have a direct impact on effective ERP implementation. Hence, it is supported that user and consultant support have an indirect impact on ERP system effective implementation, an impact that is mediated through knowledge transfer. Figure 2 presents the revised form of the proposed conceptual framework, in which only the significant paths are shown. 5. Conclusions The present study has proposed a conceptual framework that investigates the main factors leading in the effective implementation of an ERP system. To the best of our knowledge, it is the first empirical evidence that demonstrates the relationship between human inputs, variables that are connected with the ERP implementation process and the final outcome of this process. The examination of the conceptual framework was made with the use of a newly developed structured questionnaire and the results offer interesting implications to ERP adopting companies. The presentation of the

Factors affecting effectiveness

71

JEIM 25,1

72

Figure 2. ERP implementation process model – results

conclusions follows a structured path, so as to enhance their clarity and avoid any possible misinterpretation. 5.1. Consultant support The study empirically shows that the support of external consultants is crucial for the effective implementation of ERP systems. The assistance provided by external consultants is essential, even more important than that provided by top managers. The contribution of the consultants’ involvement and support in the implementation process has also been verified in the studies of Wang and Chen (2006), Chang (2004) and Finney and Corbett (2007). Since consultant support is a factor with such a significant influence on ERP system effective implementation, companies should focus on hiring the right consultant group for the specific business environment. Efforts towards consultant selection should not be viewed as a time wasting procedure, since the experience of consultants in similar business contexts, the commitment towards achieving mutual goals and the shared mentality of the two contactors are of crucial importance for successful implementation. Consultants should not only acquire technical skills, but should also have a broad understanding of the individual business practices and a genuine commitment towards resolving every-day issues considering ERP system implementation. It would be

advisable for adopting companies to make a contractual connection between the fees paid to the consultant team and the improvement in certain areas of business activity. In general, the consultant group should be viewed as a valuable “ally” in the ERP implementation process: consultants need the support and the acceptance of the company personnel in order to be able to fully integrate their valuable expertise and make a substantial difference in the implementation of ERPs. If system users adopt a negative attitude towards working together with a professional team of consultants, the implementation procedure will surely produce poor results. 5.2 Knowledge transfer The present survey has statistically indicated that knowledge transfer is a significant factor for ERP system success. On the same vain, the study of Wang et al. (2007) has produced the same results. On the other hand, no significant relationship was found between communication effectiveness, conflict resolution and ERP system effective implementation. Wang and Chen (2006), also found no relationship between communication effectiveness and ERP system success, but established a relationship between conflict resolution and ERP system success. Apparently, the incorporation of knowledge concerning technical aspects of ERP systems is more important than effective handling of communication, as well as conflict resolution among organizational members of Greek companies. From the above, it is apparent that ERP adopting companies should build the necessary structures in order to facilitate the procedure of knowledge transfer. System users not only need to be taught the newly implemented ERP technology, but they, furthermore, need to learn more about their new organizational responsibilities. Moreover, they should actively try to acquire maximum results from the use of the ERP system, since passive attitude is not a path that leads to successful ERP implementation. In order to do so, the adopting company should, firstly, understand that with the use of an ERP system every employee is being continuously trained. Therefore, companies should provide opportunities for employees to enhance their skills by providing training opportunities on a continuous basis, in order to meet the changing and complex needs of the business environment (Bingi et al., 1999). Moreover, the adopting company should make sure that the knowledge transfer procedure is not short or inconclusive, since the literature recognizes the limited consultation period as a factor that undermines possible positive effects (Nah et al., 2001). Furthermore, since it is difficult for consultants to pass the knowledge to computer illiterate employees, the adopting company should organize computer seminars prior to the implementation of the new ERP system. Finally, the adopting company should appoint its most prominent employees (from all functional business areas) to follow the implementation procedure step by step, so as to be able to play the role of the “internal consultant” after the withdrawal of the professionals. 5.3 Top management support According to the statistical analysis, the role of top management support seems to be of less important that the one provided by users, since top managers assist only in the resolution of conflicts (a factor that has no relationship with ERP system effective implementation), while user support influences both communication effectiveness and,

Factors affecting effectiveness

73

JEIM 25,1

74

more importantly, knowledge transfer (a factor that is related with ERP system effective implementation). These findings are in line with the corresponding ones in the studies of Wang and Chen (2006) and Wang et al. (2007). On a practical level, the above imply that a company needs to ensure user support in order to be led into a successful ERP implementation. This can be achieved by allowing future users to: . report their views on the necessity of the implementation; . contribute to the specifications of the system; . participate in the implementation process; and . collect various rewards upon successful use of the implemented ERP system. Without the active participation and the overall acceptance of its users, every ERP system, no matter how expensive and elegant, is destined to produce less positive results that the ones anticipated, or even fail miserably. 5.4 Overall conclusions In general, the present study argues that consultant support and knowledge transfer are the two key factors for ERP system success. The consultants may improve the performance of ERP systems directly, through their experience and technical expertise and indirectly through the effective transfer and sharing of ERP system knowledge among various inter-organizational members. In other words, the transfer of knowledge from the consultants may raise the level of user know-how, then users subsequently should be able to successfully maintain and further modify the ERP system without consultant engagement. Therefore, practical efforts in hiring the right consultants are essential, especially since the consulting fees are quite significant. Moreover, ERP adopting companies should improve their knowledge management capabilities in order to successfully facilitate the transfer of knowledge from consultants. In order to pursue a successful ERP implementation and gain sustainable competitive advantage, companies need to develop their internal knowledge capabilities before implementing an ERP system. The building of these capabilities will ensure that the knowledge offered by consultants is properly disseminated throughout the organization. Organizational practices, culture, and structure should be reinforced to address this necessity (Nonaka and Takeuchi, 1995). 6. Impact of the research The empirical research included in the present paper has a dual impact. On the one hand, offers important guidelines to companies implementing an ERP system and on the other, develops a coherent conceptual framework that thoroughly investigates the process of the effective implementation of an ERP system, thus, broadening the understanding on the issue. Given the influence of ERP systems on business success, such a dual contribution seems rather significant for both practitioners and academics. 7. Limitations and future research A limitation of the present study is the relatively small size of the sample. This may be attributed to the nature of the population of the study (Greek companies that have

implemented an ERP system), which is rather small and difficult to be defined due to lack of available data. In addition, IT managers were often hesitant to reveal inside information about the company’s policies, as well as information regarding the ERP system performance. Given that companies in Greece are mostly small and medium-sized, most of them do not have an autonomous IT department and are using external IT specialists to assist with the system’s implementation and operation. As a result, it was not always possible to contact the internal staff of each company, and, therefore, gather an overall and consistent evaluation of the ERP system implementation. The present study has emphasized the vital role of the consultants in enhancing the performance of the ERP system, by means of their experience and the transfer of their knowledge and technical expertise to the ones that have acquired and are using the ERP system. Further research on the effective implementation of the ERP systems is suggested with larger samples that would, probably, offer more information and strengthen the initial outputs of the present research. Moreover, it would be interesting to include additional variables to the proposed conceptual framework of the present study (e.g. change management, team morale and motivation, training, job redesign) and finally, gather empirical data from all company personnel, so as to achieve a rounder view of the subject under investigation. References Akkermans, H. and van Helden, K. (2002), “Vicious and virtuous cycles in ERP implementation: a case study of interrelations between critical success factors”, European Journal of Information Systems, Vol. 11 No. 1, pp. 35-46. Al-Mashari, M., Al-Mudimigh, A. and Zairi, M. (2003), “Enterprise resource planning: a taxonomy of critical factors”, European Journal of Operational Research, Vol. 146, pp. 352-64. Amoako-Gyampah, K. (2007), “Perceived usefulness, user involvement and behavioral intention: an empirical study of ERP implementation”, Computers in Human Behavior, Vol. 23, pp. 1232-48. Anderson, J.C. and Gerbing, D.W. (1988), “Structural equation modeling in practice: a review and recommended two- step approach”, Psychological Bulletin, Vol. 103, pp. 411-23. Attewell, P. (1992), “Technology diffusion and organizational learning: the case of business computing”, Organization Science, Vol. 3 No. 1, pp. 1-19. Bessant, J. and Rush, H. (1995), “Building bridges for innovation: the role of consultants in technology transfer”, Research Policy, Vol. 24, pp. 97-114. Bingi, P., Sharma, M.K. and Godla, J.K. (1999), “Critical issues affecting an ERP implementation”, Information Systems Management, Summer, pp. 7-14. Bloomfield, B.P. and Danieli, A. (1995), “The role of management consultants in the development of information technology: the indissoluble nature of socio-political and technical skills”, Journal of Management Studies, Vol. 32 No. 1, pp. 23-46. Boynton, A.C., Zmud, R.W. and Jacobs, G.C. (1994), “The influence of IT management practice on IT use in large organizations”, MIS Quarterly, Vol. 18 No. 3, pp. 299-318. Bradford, M. and Florin, J. (2003), “Examining the role of innovation diffusion factors on the implementation success of enterprise resource planning systems”, International Journal of Accounting Information Systems, Vol. 4 No. 3, pp. 205-25. Chang, S.-I. (2004), “ERP life cycle implementation, management and support: implications for practice and research”, The Proceedings of the 37th Hawaii International Conference on System Sciences (HICSS-37), Hawaii, US, 05-08 January.

Factors affecting effectiveness

75

JEIM 25,1

76

Cohen, W.M. and Levinthal, D.A. (1990), “Absorptive capacity: a new perspective on learning and innovation”, Administrative Science Quarterly, Vol. 35, pp. 128-52. Davison, R. (1997), “A measurement for measuring meeting success”, Information and Management, Vol. 32 No. 4, pp. 163-76. Dillard, J. and Yuthas, K. (2006), “Enterprise resource planning systems and communicative action”, Critical Perspectives on Accounting, Vol. 17, pp. 202-23. Finney, S. and Corbett, M. (2007), “ERP implementation: a compilation and analysis of critical success factors”, Business Process Management Journal, Vol. 13 No. 3, pp. 329-47. Fleck, J. (1993), “Configurations: crystallizing contingency”, International Journal of Human Factors in Manufacturing, Vol. 3 No. 1, pp. 15-36. Freeman, K.D. and Dart, J. (1993), “Measuring the perceived quality of professional business services”, Journal of Professional Services Marketing, Vol. 9 No. 1, pp. 27-47. Gargeya, V.B. and Brady, C. (2005), “Success and failure factors of adopting SAP in ERP system implementation”, Business Process Management Journal, Vol. 11 No. 5, pp. 501-16. Green, B. (1998), “Managerial intervention in organizational disputes: testing a prescriptive model of strategy selection”, International Journal of Conflict Management, Vol. 9 No. 4, pp. 301-35. Hair, F., Anderson, R., Tatham, R. and Black, W. (1995), Multivariate Data Analysis with Readings, 4th ed., Prentice Hall International, London. Hong, K. and Kim, Y. (2002), “The critical success factors for ERP implementation: an organizational fit perspective”, Information and Management, Vol. 40, pp. 25-40. Jiang, J.J., Gary, K. and Means, T.L. (2000), “Project risk impact on software development team performance”, Project Management Journal, Vol. 31 No. 4, pp. 19-26. Kelloway, E.K. (1996), “Common practices in structural equation modelling”, in Cooper, C.L. and Robertson, I.T. (Eds), International Review of Industrial and Organizational Psychology, John Wiley and Sons, London, pp. 141-80. Kelloway, K. (1998), Using LISREL for Structural Equation Modeling: A Researcher’s Guide, Sage Publications, London. Kemp, M.J. and Low, G.C. (2008), “ERP innovation implementation model incorporating change management”, Business Process Management Journal, Vol. 14 No. 2, pp. 228-42. King, W. (2005), “Ensuring ERP implementation success”, Information System Management, Vol. 22 No. 3, pp. 83-4. Lee, J.N. and Kim, S. (1992), “The relationship between procedural formalization in MIS development and MIS success”, Information and Management, Vol. 22 No. 2, pp. 89-111. Lee, J.N. and Kim, Y.G. (1999), “Effect of partnership quality on IS outsourcing success: conceptual framework and empirical validation”, Journal of Management Information Systems, Vol. 15 No. 4, pp. 29-61. McGivern, C. (1983), “Some facets of the relationship between consultants and clients in organizations”, Journal of Management Studies, Vol. 20 No. 3, pp. 367-86. McLachlin, R.D. (1999), “Factors for consulting engagement success”, Management Decision, Vol. 37 No. 5, pp. 394-402. Markus, M.L. and Tanis, C. (2000), “The enterprise system experience – from adoption to success”, in Zmud, R.W. (Ed.), Framing the Domains of IT Management: Projecting the Future through the Past, Pinnaflex Educational Resources, Cincinnati, OH, pp. 173-208. Marnewick, C. and Labuschagne, L. (2005), “A conceptual model for enterprise resource planning (ERP)”, Information Management & Computer Security, Vol. 13 No. 2, pp. 144-55.

Morgan, R.M. and Hunt, S.D. (1994), “The commitment-trust theory of relationship marketing”, Journal of Marketing, Vol. 58 No. 3, pp. 20-38. Motwani, J., Subramanian, R. and Gopalakrishna, P. (2005), “Critical factors for successful ERP implementation: exploratory findings from four case studies”, Computers in Industry, Vol. 56, pp. 529-44. Nah, F., Lau, J. and Kuang, J. (2001), “Critical factors for successful implementation of enterprise systems”, Business Process Management Journal, Vol. 7 No. 3, pp. 285-96. Nonaka, I. and Takeuchi, H. (1995), The Knowledge-creating Company: How Japanese Companies Create the Dynamics of Innovation, Oxford University Press, New York, NY. Reimers, K. (2003), “International examples of large-scale systems: theory and practice II: implementing ERP systems in China”, Communications of AIS, Vol. 11, pp. 11-33. Robey, D., Smith, L.A. and Vijayasarathy, L.J. (1993), “Perceptions of conflict and success in information systems development projects”, Journal of Management Information Systems, Vol. 10 No. 1, pp. 123-39. Scott, J.E. and Kaindl, L. (2000), “Enhancing functionality in an enterprise software package”, Information and Management, Vol. 37 No. 3, pp. 111-222. Shin, H. and Lee, J. (1996), “A process model of application software package acquisition and implementation”, Journal of System Software, Vol. 32 No. 1, pp. 57-64. Simonin, B.L. (1999), “Ambiguity and the process of knowledge transfer in strategic alliances”, Strategic Management Journal, Vol. 20, pp. 595-623. Soh, C., Sia, S.K. and Tay-Yap, J. (2000), “Cultural fits and misfits: is ERP a universal solution”, Communications of the ACM, Vol. 43 No. 4, pp. 47-51. Somers, T. and Nelson, K. (2004), “A taxonomy of players and activities across the ERP project life cycle”, Information and Management, Vol. 41, pp. 257-78. Sussman, S.W. and Guinan, P.J. (1999), “Antidotes for high complexity and ambiguity in software development”, Information and Management, Vol. 36 No. 1, pp. 23-35. Thong, J.Y.L. (2001), “Resource constraints and information systems implementation in Singaporean small businesses”, Omega, Vol. 29 No. 2, pp. 143-56. Thong, J.Y.L., Chee-Sing, Y. and Raman, K.S. (1996), “Top management support, external expertise and information systems implementation in small businesses”, Information Systems Research, Vol. 7 No. 2, pp. 248-67. Umble, E.J., Haft, R.R. and Umble, M.M. (2003), “Enterprise resource planning: implementation procedures and critical success factors”, European Journal of Operational Research, Vol. 146 No. 2, pp. 241-57. Wang, E. and Chen, J. (2006), “Effects of internal support and consultant quality on the consulting process and ERP system quality”, Decision Support Systems, Vol. 42, pp. 1029-41. Wang, E., Lin, C., Jiang, J. and Klein, G. (2007), “Improving enterprise resource planning (ERP) fit to organizational process through knowledge transfer”, International Journal of Information Management, Vol. 27, pp. 200-12. Willis, T. and Willis-Brown, A. (2002), “Extending the value of ERP”, Industrial Management & Data Systems, Vol. 102 No. 1, pp. 35-8.

Factors affecting effectiveness

77

JEIM 25,1

78

Further reading Law, C.C.H. and Ngai, E.W.T. (2007), “An investigation of the relationships between organizational factors, business process improvement, and ERP success”, Benchmarking: An International Journal, Vol. 14 No. 3, pp. 387-406. About the authors Dimitrios Maditinos is Assistant Professor of Information Technology, Finance and Financial Modeling in Kavala Institute of Technology, School of Business and Economics, Greece. He holds degrees in Business Administration with specialization in Information Technology from Lund University, Sweden, and a PhD from the Business School, Greenwich University, UK. Before becoming a full academic he worked in a senior position for the Greek Productivity Center, responsible for professional training in Information Technology and Management. His research interests are in financial modeling, performance measurement systems, investors’ behavior in stock exchanges, financial information systems and electronic commerce. Dimitrios Maditinos is the corresponding author and can be contacted at: [email protected] Dimitrios Chatzoudes is a PhD Candidate in the Department of Production and Management Engineering of Democritus University of Thrace, Xanthi, Greece. His bachelor degree is on business administration and his postgraduate degree on international economics. His academic interests include research methods, international relations and production management. Dr Charalampos Tsairidis is an Assistant Professor in the Department of Social Administration of Democritus University of Thrace, Komotini, Greece. He studied Mathematics and completed his PhD thesis at the University of Ioannina, Ioannina, Greece. Topic of thesis: statistical information theory and censoring. His main research interests are in the area of statistical information theory, statistical data analysis and social statistics.

To purchase reprints of this article please e-mail: [email protected] Or visit our web site for further details: www.emeraldinsight.com/reprints

The current issue and full text archive of this journal is available at www.emeraldinsight.com/1741-0398.htm

Retrieving relevant information: traditional file systems versus tagging Thomas W. Jackson and Stephen Smith Department of Information Science, Loughborough University, Loughborough, UK

Retrieving relevant information 79 Received 21 January 2011 Revised 21 March 2011 10 May 2011 Accepted 10 May 2011

Abstract Purpose – The aim is to determine, in a business context, if tagging is a more effective method of discovering relevant information when compared to traditional hierarchical filing systems. Design/methodology/approach – A five-step interpretive hybrid approach of using both a focus group, questionnaires and SWOT analysis was used to test the proof of concept of tagging files compared to a traditional hierarchical filing system. The approach taken was chosen because of the difficulties and tradeoffs that had to be made between the number of champions and people available to take part in the research; the time that they could allow; and because transcription or recording of the participants was not permitted. The participants were encouraged to use the questionnaires and the SWOT analysis to record their thoughts anonymously whilst the focus groups allowed elaboration and discussion to help understand the true feelings and thoughts of the group collaboratively. Findings – Traditional hierarchical filing systems can lead to the retrieval of irrelevant information, or to none at all, even though the information exists. The study shows that tagging could provide a cost-effective solution by providing a better structured filing system that can help reduce duplication and the retrieval of irrelevant information. Research limitations/implications – One limitation of the study was the limited number of participants from just one organisation. Thus, generalisation of the results of this study to the wider population must be done with great care. Practical implications – Organisations should evaluate the functionality of their chosen operating system and information store software in light of the potential benefits offered by tagging, and costly limitations of traditional file stores. Originality/value – The paper contributes to the information retrieval and information overload literature by studying the effect tagging files has on an organisation. It provides an insight to the future of filing systems for management and triggers future empirical work into reducing information overload in the workplace. Keywords Tagging, Information overload, Information storage, Information retrieval, Semantics, Information management, Classification schemes Paper type Research paper

1. Introduction Searching for relevant files within an organisation has been a source of problems for employees for a number of years (Kelly et al., 2010; Kobayashi et al., 2006). For this reason many companies invest substantial amounts of money in searchable portals and document storage facilities. Ineffective searches and wasting time looking for information has been said to cost up to 10 per cent of an employee’s time (Dubie, 2006). Many organisations employ highly sophisticated search engines to search the full text of all of the files stored within their systems (Smith, 2010). However, many search

Journal of Enterprise Information Management Vol. 25 No. 1, 2012 pp. 79-93 q Emerald Group Publishing Limited 1741-0398 DOI 10.1108/17410391211192170

JEIM 25,1

80

systems cannot retrieve documents that have not already been indexed by that search system such as those within a user’s corporate network profile. In addition, web-based search systems, such as Google or even a corporate intranet search engine do not help users locate files stored on their local computers. The user can resort to using their operating systems search facility but this suffers from the same problems as the web based search systems (Smith, 2010). Using such search engines also requires users to visit the search page and wait for results to be returned. Further to this, if the user wishes to browse for a file whilst continuously narrowing down their search as they go, they are restricted to a traditional hierarchical file structure. Ultimately there are a number of barriers for users to overcome when attempting to find information using traditional search approaches (Smith, 2010). This increases the difficulty in discovering relevant information and can lead to an inability to find what the user is looking for, which can also be compounded by task uncertainty (Nunez and Giachetti, 2009). To illustrate the severity of this problem Nelson (1994) references Naisbitt, arguing that: “Inundated with technical data, some scientists claim it takes less time to do an experiment than to find out whether or not it has been done before.” It is not surprising that in a world that is increasingly dominated by computer-mediated communication systems, it appears that the volume and pace of information can become overwhelming as shown by even earlier studies in the 1980s (Hiltz and Turoff, 1985; Kerr and Hiltz, 1982). Further studies have gone on to define information overload and the impact it has. For example in the 1990s Meglio and Kleiner looked at ways of managing information overload. They looked at time management, communication and the idea that individuals can reduce information overload as they are part of the problem (Meglio and Kleiner, 1990). The research showed that users of information all contribute towards information overload and if these issues can be realised a conscious effort can be made to reduce the overload, thus improving the effectiveness of communication. A decade later both Farhoomand and Drury showed that information overload is still a problem and it affects managers in organisations on a daily basis and can have dramatic effects within an organisation (Farhoomand and Drury, 2002; Kirsh, 2000). Continuing the journey on the timeline, a decade later in 2010, Soucek and Moser reported that information overload causes problems in email communication within the workplace and that the issue of information overload still needs to be addressed and training might provide a potential solution (Soucek and Moser, 2010). Other research has taken more of a holistic view in identifying the factors surrounding information overload, and in particular the main factors contributing to technology-based productivity losses through information overload, communication overload, and system feature overload (Karr-Wisniewski and Lu, 2010). To help visualise the sources of information and potential overload an employee might encounter, the authors have created a conceptual map of the sources of information that an employee can access to retrieve information and knowledge as shown by Figure 1. This study investigates a solution to reducing the information overload problem in organisations by focusing on improving the filing and retrieving of electronic documents (denoted by the red). In the problem domain of information storage and retrieval, the main research question of this research is, can tagging files save employees time retrieving information compared to a traditional hierarchical file system. An enterprising innovation to aid in the storage and retrieval of business information is critical in

Retrieving relevant information 81

Figure 1. How an employee locates information/knowledge sources

generating greater cost effectiveness and increased performance of organisations. It will also provide organisations with the “best practice” when it comes to information storage and retrieval. As highlighted by Rosacker and Rosacker (2010) it is becoming critically important for managers to understand “best business practices” so that these successful techniques can be applied appropriately to enhance and refine operational practices. The paper starts by looking at the traditional use of tagging and investigates its potential benefits in the retrieval of relevant information within an organisation. It then outlines the methodology used to evaluate tagging as an alternative to the traditional filing and retrieval systems. The next section describes of the proof of concept called TagDav, which is a tag based system developed by the authors to enable a comparison to be made against traditional storage and retrieval systems. The results and research synthesis form the next section of the paper, and the paper finishes with a conclusion and limitations of the research. 2. Discovering relevant information The current directory structure found on many computers, along with those used by shared document systems, require a user to place a file into a folder, the file is then retrieved by navigating to the same folder. Placing files into a system whereby the user was guaranteed to retrieve the file that they wished to find would be extremely difficult. The user may even have to add the file a number of different times in different directories to ensure that it was found. Whilst one possible solution is to make use of one of the existing corporate search systems, another possible solution is to replace the file system with one that makes use of tagging. The task of discovering relevant information has seen specific attention within the field of the internet where the corpus of information available is massive (De Kunder,

JEIM 25,1

82

2011). Over time the internet has moved from its traditional text and hyperlink driven state to a frenzy of media rich web sites containing masses of information for, often, millions of users. Within this transition some interesting sites and approaches to discovering information have emerged. Flickr and Delicious provide two interesting case studies. Flickr is an online photo sharing web site. It allows users to upload their photographs for other people to see. Delicious allows users to bookmark web pages and then find their own and other users’ bookmarks when needed. To quantify the volume of information that is stored in these systems, the Flickr web site receives thousands of new photos per minute (Flickr, 2006) and a more recent statistic shows that on average 4,602 images are uploaded every minute (Lux, 2010). All of these photos are stored and retrievable by its members. Delicious is also a high traffic site; it received 150,000 posts per day in June 2008 (Keller, 2008). Instead of using traditional methods and categories to allow users to find photos or bookmarks, they make use of tagging. Tagging offers a strong alternative to traditional hierarchical structures and has allowed many web-based systems to dispense with manually created categories for users to place their content into. Tagging has proven extremely popular, but the literature has also shown that there are a number of in use issues that need to be considered. These have been summarised with some examples: . Single use tags – or tags which have not been used before should be avoided unless necessary. Delicious offer a number of recommended tags as this helps to re-use tags that have already been used before. Some systems also show the user how many times they have used a tag before, as they are adding a tag to an item. . Pluralised or singularised versions of words – The unstructured nature of tagging can lead to issues when items are tagged with either singular or plural versions of a tag (Mathes, 2004). In some cases a user may use the tag “apple” and in others “apples”. It is clear that whilst “apple” could describe both the fruit and the computer manufacturer, the word “apples“ would not describe the company. A decision should be taken on whether to allow both or just one, if only one is used then the singular form is recommended. . Spelling mistakes – can cause the creation of a new tag, but unnecessary one, and make a tag of no benefit. . Personal tags – users freely choose the tags and tagging can be seen as “subject indexing without a controlled vocabulary” (Hayman and Lothian, 2007). In addition, when items are tagged by multiple parties, during collaborative tagging there is a higher likelihood that different tags may be chosen (Golder and Huberman, 2006). This should be avoided and could be prevented by prefixing to allow for a period of distinction. . Spacing and capitalisation should also be considered. Delicious makes the recommendation that users do not use spaces at all within tags to ensure optimised efficiency and effectiveness. . Synonyms – words used may also be synonyms of one another, for example, whilst one person describes a resource with the word “person”, another may use the word “human” (Golder and Huberman, 2006). Including as many synonyms as possible can help to reduce the issues associated with only entering one.

More tags – entering a larger number of tags may help to improve search efficiency and actually allow more focused searches if necessary, preventing the problems caused by differing granularities of search.

Retrieving relevant information

For an organisation aiming to implement tagging as a potential solution to aid in the discovery of information, these issues highlighted by the literature should be considered. The next section details the methodology that will be used to determine if a tag based system is more effective for storing and retrieving information than a traditional hierarchical filing system.

83

.

3. Methods An interpretive philosophy was chosen as the underlying framework and the research adopted a systems development methodology that recognises three main stages: concept development, system building, and system evaluation (Burstein, 2002). In terms of system evaluation a system-centred approach was taken. Wang and Forgionne’s (2008) comprehensive approach was considered but rejected due to the time constraints of the research project. The authors developed a proof of concept, called TagDav, to enable users to tag the files they use. Details of the system are described in the “Proof of Concept – TagDav” section. A number of different methods were used to test TagDav at SoftwareCo, which are detailed later in this section. SoftwareCo, is one of the largest software organisations in the world and is in the top ten of all of the major software rankings including the Forbes 2000 and Research Foundation’s top 100. The organisation employs over 50,000 people in over 50 countries. The company develops a range of software solutions in house and its products are used globally. The SoftwareCo department that participated in this work was one of the rapid development and value prototyping divisions. The department’s employees are highly skilled within their respective field and the department has a very unique structure. The department has attempted to create an environment specifically suited to rapid application development, testing and deployment. The department aims to have only a limited hierarchical structure, with all members of the department seen as equals and interacting with each other to take advantage of their respective skills. The nine participants for this research study were selected by one of the champions within the organisation, who selected on the criteria of someone who would give valuable input, and their knowledge of tagging (experienced and inexperienced). The nine participants were also chosen to include the most varied views including those who would be expected to be advocates of such a system and those expected to be against it. Figure 2 shows the approaches used to determine the effectiveness of a tag-based filing system:

Figure 2. The assessment of tag based file storage

JEIM 25,1

.

.

84

.

.

.

Step one – an eight question questionnaire was given to the nine participants to assess the barriers to tagging, before they were given a demonstration of TagDav. Step two – a demonstration of TagDav was given to the employees at SoftwareCo within the focus group environment. Step three – the second questionnaire contained 16 questions and focused on the way that users currently store and retrieve files and questions about the TagDav system. For example, how easy it is to use and whether they felt that training would be necessary in order to use the system effectively. The aim of these questions was to establish if the participants had a common system, or method of working, or if they all used different filing schemes. Step four – the focus group consisted of nine members from the SoftwareCo. A focus group was chosen to enable an open discussion to enable participants to cover a large range of aspects that are relevant to them as a group. Step five – participants were provided with a matrix on which they could record their thoughts within four key areas, strengths, weaknesses, opportunities and potential risks that might be introduced by the use of the tag based approach to document retrieval.

The study took a hybrid approach using both focus groups and questionnaires, which is similar to, but did not follow, a Delphi style approach. The approach taken was chosen because of the difficulties and tradeoffs that had to be made: . between the number of champions and people available to take part in the research; . between the time that they could allow; and . because transcription or recording of the participants was not permitted by SoftwareCo. The participants were allowed to use the questionnaires and the SWOT analysis to record their thoughts anonymously whilst the focus groups allowed elaboration and discussion to help understand the true feelings and thoughts of the group collaboratively. Although transcription or recording was not allowed by the organisation a number of notes and “sound bites” were taken that were approved by the participants. 4. Proof of concept – TagDav TagDav is short for Tag-based Distributed Authoring and Versioning. It was developed using Ruby on Rails by the authors. A server was developed that would allow users to mount the folders of the server as if they were folders within the computer, as traditional network attached storage (NAS) devices would, but used a tag-oriented navigation method rather than the traditional hierarchical approach. The benefit of integrating with the operating system is that the files will appear as if they are stored on the local computer. This removes the need for the user to open a web browser and perform a search. It would also allow the user to access these files from inside any application that was running on the computer instead of having to download the file first. The ultimate benefit is that the files would appear to be stored

on the computer like any other file in an attempt to allow users to improve their ability to find relevant information whilst remaining in a familiar environment. The server was developed in Ruby on Rails, due to the familiarity of the authors with this programming framework. The server was used to create a virtual file system. The server would not retrieve files directly from a given directory but would work in conjunction with a database. Storing the files in conjunction with a database allows additional information to be stored with each file such as the tags that were used to tag that file. As the tags were also all stored in a database, it would be a very quick process to create a list of all of the tags used by files stored within the system making the system extremely responsive and prevent the delays that are associated with alternative systems such as searching the full text of a document. The system would also have a much lower storage requirement than traditional search based approaches as indexes would not be required in this method. The server would not store multiple versions of the files but would simply store one version of the file and make use of the database to allow the server to generate a virtual structure that is sent to the client. The database would maintain a list of files and the tags associated with that file. Each of the tags would then appear as a “virtual directory” within the root folder. When the user chose that directory, the tag would be used to find all files that contained that tag and display those files. Along with those files, all of the other tags that were used by the files shown would also be present as directories to allow the user to further refine their search and narrow the list of files. This enables the user to choose as many tags as they like until the files that have all of these tags are listed within the directory. The files would be refined based upon the tags that are associated with those files rather than where they had been stored. Although to the user it would appear they were navigating a list of files they were actually just communicating with the server that was dynamically creating the folders they would see. An additional benefit of this method is that users may browse for the files that they wish to find, refining their search by clicking on directories, or tags, as they went. This is a strong contrast to search-based approaches where search terms must be entered before any results are displayed. The system also allows the user to quickly narrow down their search using the directories to represent tags when they are searching for something specific. Instead of using a pre-defined directory structure the directory structure is automatically created based upon the tags of the file. Although the user is essentially browsing a directory structure, the directory structure is continually narrowing down the list of files that contain those tags to allow the user to search for the file. Table I shows the three files that were uploaded into the system and the tags that were applied. The files in Table I provide an example of how the files would appear with their respective tags to the user. Figure 3 shows the TagDav system in the root folder. All of the tags used are listed so that the user may begin their search. Although it may seem like there would be an Name

Tags

File_Tagged_One_and_Both File_Tagged_Two_and_Both File_Tagged_One_Only

tag_one, tag_both tag_two, tag_both tag_one

Retrieving relevant information 85

Table I. Example files in the TagDav system

JEIM 25,1

86

Figure 3. TagDav with close folders

issue if there were thousands of tags entered into the system this would not be the case. The tags would be ordered alphabetically and could quickly be found. In many operating systems simply beginning to type the directory name would highlight that directory and in this case the tag. Once one tag had been chosen, the list of remaining tags would be significantly reduced. The process could continue until the desired file was found. This root folder also has the option to show all of the files that exist in the system but for simplicity it is not shown in Figure 3. The tags from Table I can be seen as directories within the file system that contain the files. It is then possible to expand and navigate within the folders to see the files that are tagged by that content. Figure 4 shows the tag “tag_both” expanded as a folder

Figure 4. TagDav with one folder or tag expanded

showing the two files within this folder and also the two tags that those files are also tagged with. The tags may be combined to further refine the search within the folders. Figure 5 shows the full expansion of the example files and their folders. Although in Figure 5 there are nine files listed there only actually three physical files stored within the system. Each file is only stored within the system once and each of the files shown in Figure 5 is actually a virtual reference to a file that will be retrieved at run time should the user wish to actually download or open this file. In order to work with this file, the user simply has to click the file as they would if the file were in any traditional file system.

Retrieving relevant information 87

5. Results and analysis 5.1 Knowledge of tagging The results from step one showed a large variance when it came to tagging. Four out of the nine employees had never tagged content before. Of the five members of the group that had tagged content before, there was a wide variance in the answers given to the initial questionnaire regarding how they use tags. This section is based upon the five users that had previously tagged content. When asked how many tags they use on average to tag content, the employees were quite close to the average found in the study by Smith (2010). His research showed an average of 3.3 tags used per user. This study showed that one participant (20 per cent) used just one to two tags and only three to four tags were used by the other four participants (80 per cent). This highlights many users who do not use as many tags as they perhaps should. Two (40 per cent) re-used them always and two (40 per cent) sometimes, with one participant (20 per cent) rarely re-using existing tags. The figures were worse when the tags were created by another person. One participant (20 per cent) always re-used tags used by others, one (20 per cent) sometimes re-used them, and the other three (60 per cent) rarely re-used the tags, one (20 per cent) used a mixture and one (20 per cent) used plural. Again, there was no consensus over spaces, with two

Figure 5. Fully expanded view

JEIM 25,1

88

users (40 per cent) stating that they used them, three (60 per cent) stating that they did not and the other using them and some not. Only one participant (20 per cent) used synonyms of a word when creating tags in order to help them to retrieve the content in future. During the focus group participants said that they were not aware of the issues associated with tagging. Many of the participants had only thought of tagging as being of use for them personally and not considered that other people would be using these tags to retrieve content. The participants also commented that many different systems ask users to tag differently or do not give any guidelines as to how tags should be entered into the system. All participants agreed that with the correct training and if all participants were to make use of the same tagging scheme, then the benefits of tagging would be far greater. The questionnaire helped to identify the way that users were currently tagging and through discussions during the focus group it was possible to expand upon the potential issues with tagging. One of the group members stated “although there are barriers towards tagging if they can be overcome then this could actually lead to increased consistency, ease of finding docs/data” with another user stating that “after training tagging might present a powerful option but that they were not aware of all of the potential problems”. These issues highlight the need for training but also for a system to remind users of the benefits of considering these options when tagging systems are in place. 5.2 Assessing TagDav To assess the potential of the TagDav system to help users obtain relevant information, the second questionnaire (step three) was given to the group of nine SoftwareCo employees. Some questions were left blank by some participants, and in these cases only the completed questions were used in the results. This explains the odd percentages for some of the results as the total number might not have been out of nine participants. Once the members had answered the questions in the questionnaire, a group discussion was held centred around the benefits and weaknesses of the system and any potential it may have (step four) to reduce information overload. When asked if they had difficulty finding files they have created because they did not know which directory they have been placed in, 33 per cent of participants stated often, 44 per cent sometimes had a problem but 22 per cent of participants rarely experienced a problem. On locating documents, 22 per cent stated that they always resorted to using the search facility of a file system, 22 per cent often did and 44 per cent sometimes resorted to using the search facility, with 11 per cent never using it. Of the eight participants that did use the search facility only one felt that it was rarely sufficient to find the files they required. One of the participants always placed the same file in more than one location or created symbolic links in order to make it easier to find. Three of the participants sometimes did and one rarely did, with four participants never doing this. This does highlight that 55 per cent of the participants, have at some point, created a duplicate file in order to ensure it can be found in the future. Copying a file to another location does carry a high level of unnecessary risk, if for example, the file is updated in only one place. When participants were asked how they store their files every response was different. Some stored files by project, some by topic, some by year and some used completely different schemes entirely. With all of these different

storage methods, a collaborative file store could easily become quite difficult to use. There would be duplication of files and it could be difficult to find a file if it is not where it is expected to be stored. The responses confirm that there are a number of issues associated with traditional file systems and storage of documents. The following responses relate to the TagDav system and its potential to improve upon these issues. After using the system, participants were asked whether they felt that tagging files would help them to find the files and prevent the need for them to have to resort to using search engines. The majority said (67 per cent) that they definitely felt the system would help them find files they were looking for without the use of a search engine and 11 per cent stated that it often would. Two of the participants felt that the system could help sometimes. When asked whether tagging files would save time when it came to the retrieval of files, 78 per cent felt that it definitely could and 22 per cent of the participants felt that it would often be possible. The participants indicated that they would use this system to replace their current way of filling and retrieval with two of the participants (22 per cent) saying they would definitely use the system, 44 per cent stated that they would make the switch and 22 per cent stated that they would use the system sometimes. All of the participants felt that the system had benefits over traditional directory based systems and all but one (11 per cent) of the participants felt that browsing a file structure was harder than uploading a file and tagging it. Participants were also asked whether they felt they could save time using this system and all participants agreed they could. When asked how long they could save each day using this system, participants were allowed to enter any value of their choice, as no pre-defined options were offered. Answers ranged from ten minutes to 120 minutes, but on average participants felt that they could save 40 minutes per day through using the TagDav. One important factor to note is all of the participants felt training would be required before it was used. Although most of the participants (56 per cent) felt it would only be necessary sometimes, three (33 per cent) of the participants felt training would always be required and one (11 per cent) felt that it would often be required before the system could be used. In step five, the participants were asked to record their thoughts about the strengths, weaknesses, opportunities and threats of TagDav. Most of the participants were impressed by the way the system allowed them to find a document. The system was said to be very easy to use and was praised for its ability to allow participants to find files from any number of approaches or viewpoints “files can be found from a number of different approaches and multiple file representations will appear making it easier to drill down and find documents”. One participant also stated that it would allow users to “reach consensus about file system structure” the users also appreciated the ability to create a “reduction in storage space required” as files would not need to be saved in multiple locations. A number of interesting weaknesses and worries were also raised. One of the worries was that a file with no tags would be “lost in the system” and that if enough tags were not used then the file may be difficult to find. The key thought from participants was that the system would have to be used with a lot of care and “taken seriously” from the start and if it were not, there would be a risk of losing files or having an “unstructured mess”. The participants felt training would certainly help, but they still had concerns about the consistency that would occur if everyone using the system did not fully understand the potential of the system and how to correctly tag

Retrieving relevant information 89

JEIM 25,1

90

the files. The other worry was that some form of consistency would be required in order to ensure that the tags used by some users would be retrievable by others. Some participants also felt that once there were too many tags it might be difficult to drill down and find the files that were required. However, as a group it was felt that this was “more of a benefit then a disadvantage, normally you would not have the option of drilling down further”. One of the participants also raised the issue of the time it would take to store the documents, however, as a group they were not concerned about the amount of time it would take to store the documents as in many cases “it takes ages to find the directory to save something in now”. 5.3 Research synthesis Documents stored on a computer can often be extremely difficult to find using traditional systems and users filing documents are forced to consider where they place files in order to be able to retrieve them in future. Nowadays, in some organisations the consideration given to storing documents seems to be increasing, for example, users having to determine how a document should be classified, categorised, named, expiry date, and storage location. The problem is further compounded by the lack of training provided to employees on how to store and retrieve information or the lack of communication of potential best practices to improve operational practices (Rosacker and Rosacker, 2010). Meglio and Kleiner’s (1990) research showed users of information all contribute towards information overload. The results in this paper confirm this finding by the wide variety of different filing methods users use to store their files, which leads to issues retrieving relevant information. However, if training is provided to overcome these issues, research has shown that the positive effects that training might have had are considerable reduced 30 days after the training was provided ( Jackson and Culjak, 2006). Therefore any system that is introduced to replace the current facility to store and retrieval information, needs to be proven to be more efficient so users can see the benefit of change; easy to use with a small amount of training; and have computer assisted structured rules base to ensure filing is completed correctly. The research in this paper provided the basis from which the rules can be constructed, namely, no single use tags – or tags which have not been used before should be avoided unless necessary; decision should be made on if pluralised or singularised versions of words; inclusion of a spell checker; removal of personal tags; provide guidelines on spacing and capitalisation; inclusion of synonyms; and promote the use of multiple tags. These rules can also help overcome some of the employees concerns raised in step five of this research, regarding creating an unstructured filing system using only tags, by introducing a computer assisted rules base helper at the point of storing or retrieving information. In terms of information retrieval performance, Dubie’s (2006) research showed ineffective searches and wasting time looking for information costs up to 10 per cent of an employee’s time. The results from this study confirm Dubie’s findings that there is inefficiency in the system. By introducing a new way of storing and retrieving information employees could save on average 40 minutes per day using TagDav. This amount of time also includes the increased time employees would have to spend tagging files to be stored. Therefore TagDav could save up to 8 per cent of an employee’s time by effective searchers based on an 8 hour working day, providing an 80 per cent efficiency improvement based on Dubie’s research figures.

Overall, as a proof of concept, this research has shown that tagging is more effective than a traditional filing system, and it has both added to and confirmed the wider findings found in the literature surrounding effective searching. In particular, this research has added to Meglio and Kleiner’s (1990) research by showing that the wide variety of different filing methods users use to store their files leads to issues retrieving relevant information. In addition, information retrieval performance can be enhanced by using tagging system and this alternative approach capitalises on the deficiencies of a traditional filing system (Dubie, 2006), which leads to a more cost-effective approach to filing and retrieving relevant information. 6. Conclusions and limitations The study examines the role of tagging, in a business context, on discovering relevant information when compared to traditional hierarchical filing systems. Within the broad problem domain of information storage and retrieval, the main research question of this research was: “Can tagging files save employees time retrieving information compared to a traditional hierarchical file system?”. An interpretive philosophy was chosen as the underlying research framework with focus on literature from information retrieval and information overload theory. The study has shown that users use a wide variety of different filing methods to store their files, with every participant providing a different answer, for example, storing them by content type, project, date customer and many others. In trying to improve information storage and retrieval this study introduced TagDAV, a proof of concept tag-based file system, to replace traditional hierarchical file structures that could be used by both individuals and groups. The results were very positive towards the new method of filing information as: . 67 per cent of the participants said the system would definitely help them find files they were looking for without the use of a search engine; . 78 per cent of the participants said it definitely could save time when retrieving files; . on average they would save 40 minutes per day using the TagDav, even though more time would have to be spent upfront tagging files to be stored; and . a system such as TagDav could make up to an 80 per cent efficiency saving in employees efforts to store and retrieve information. The practical implications of this research are that information rich enterprises, similar to the one studied in this research, should evaluate the functionality of their chosen operating system and information store software in light of the potential benefits offered by tagging, and costly limitations of traditional file stores. The evaluation will provide information rich enterprises with the “best practice” when it comes to information storage and retrieval. It can be concluded that the TagDav approach provides a mechanism to aid in the storage and retrieval of business information which can lead to generating greater cost effectiveness and increased performance of information rich enterprises. A limitation of the study is TagDav was a proof of concept and the employees were not able to use it on a daily basis to see if it really made a difference to their information capabilities. A further limitation is the number of participants and any further research in this area would benefit from a larger group of participants. Overall, the study has

Retrieving relevant information 91

JEIM 25,1

92

shown that traditional filing systems should be reviewed in the light of the potential benefits offered by tagging and the costly limitations of traditional file stores. References Burstein, F. (2002), “System development in information systems research”, in Williamson, K. (Ed.), Research Methods for Students, Academics and Professionals: Information Management and Systems, 2nd ed., Centre for Information Studies, Charles Sturt University, Wagga Wagga, pp. 147-58. De Kunder, M. (2011), “The size of the world wide web”, available at: www.WorldWideWebSize. com (accessed 10 May 2011). Dubie, D. (2006), “Time spent searching cuts into company productivity”, Network World, available at: http://www.networkworld.com/news/2006/102006-search-cuts-productivity. html (accessed 10 May 2010). Farhoomand, A.F. and Drury, D.H. (2002), “Managerial information overload”, Communications of the ACM, Vol. 45 No. 10, p. 127. Flickr (2006), available at:www.flickr.com/photos/tags/ (accessed April 2006) Golder, S.A. and Huberman, B.A. (2006), “Usage patterns of collaborative tagging systems”, Journal of Information Science, Vol. 32 No. 2, p. 198. Hayman, S. and Lothian, N. (2007), “Taxonomy directed folksonomies”, available at: http:// archive.ifla.org/IV/ifla73/papers/157-Hayman_Lothian-en.pdf (accessed January 2011). Hiltz, S.R. and Turoff, M. (1985), “Structuring computer-mediated communication systems to avoid information overload”, Communications of the ACM, Vol. 28 No. 7, pp. 680-9. Jackson, T.W. and Culjak, G. (2006), “Can seminar and computer-based training improve the effectiveness of electronic mail communication within the workplace?”, in Spencer, S. and Jenkins, A. (Eds), Proceedings of the 17th Australasian Conference on Information Systems. Karr-Wisniewski, P. and Lu, Y. (2010), “When more is too much: operationalizing technology overload and exploring its impact on knowledge worker productivity”, Computers in Human Behavior, Vol. 26 No. 5, pp. 1061-72. Keller, P. (2008), “deli.ckoma.net Del.icio.us stats”, available at: http://deli.ckoma.net/stats#tab_ tags (accessed December 2008). Kelly, D., Fu, X. and Shah, C. (2010), “Effects of position and number of relevant documents retrieved on users evaluations of system performance”, ACM Transactions on Information Systems (TOIS), Vol. 28 No. 2, pp. 1-29. Kerr, E. and Hiltz, S. (1982), Computer-mediated Communication Systems: Status and Evaluation, Academic Press, New York, NY. Kirsh, D. (2000), “A few thoughts on cognitive overload”, Intellectica, Vol. 1 No. 30, pp. 19-51. Kobayashi, T., Misue, K., Shizuki, B. and Tanaka, J. (2006), “Information gathering support interface by the overview presentation of web search results”, Proceedings of the Asia Pacific Symposium on Information Visualisation, Vol. 60, pp. 103-8. Lux, M. (2010), “Flickr uploads per minute – mean uploads per hour”, available at: www. semanticmetadata.net/2010/03/12/flickr-uploads-per-minute-mean-uploads-per-hour/ (accessed 10 April 2011). Mathes, A. (2004), “Folksonomies-cooperative classification and communication through shared metadata”, paper presented at Computer Mediated Communication, LIS590CMC (Doctoral Seminar), Graduate School of Library and Information Science, University of Illinois Urbana-Champaign, Urbana, IL, December.

Meglio, C. and Kleiner, B. (1990), “Managing information overload”, Industrial Management & Data Systems, Vol. 90 No. 1, pp. 23-5. Nelson, M.R. (1994), “We have the information you want, but getting it will cost you!: held hostage by information overload”, Crossroads, Vol. 1 No. 1, pp. 11-15. Nunez, A.N. and Giachetti, R.E. (2009), “Quantifying coordination work as a function of the task uncertainty and interdependence”, Journal of Enterprise Information Management, Vol. 22 No. 3, pp. 361-76. Rosacker, K. and Rosacker, R. (2010), “Information technology project management within public sector organizations”, Journal of Enterprise Information Management, Vol. 23 No. 5, pp. 587-94. Smith, S. (2010), “Reducing information overload by optimising information retrieval approaches”, PhD thesis, Loughborough University, Loughborough. Soucek, R. and Moser, K. (2010), “Coping with information overload in email communication: evaluation of a training intervention”, Computers in Human Behavior, Vol. 26 No. 6, pp. 1458-66. Wang, Y. and Forgionne, G. (2008), “Testing a decision-theoretic approach to the evaluation of information retrieval systems”, Journal of Information Science, Vol. 34 No. 6, pp. 861-76. Corresponding author Thomas W. Jackson can be contacted at: [email protected]

To purchase reprints of this article please e-mail: [email protected] Or visit our web site for further details: www.emeraldinsight.com/reprints

Retrieving relevant information 93

Journal of

ISSN 1741-0398

Enterprise Information Management

Volume 25 Number 2 2012

Editor Professor Zahir Irani

Editorial ___________________________________________________

96

CONTENTS

Interoperability adoption among government and corporate portals in India: a study Rakhi Tripathi, M.P. Gupta and Jaijit Bhattacharya ___________________

98

A process approach to distribution channel re-engineering Ales Groznik and Marinko Maslaric ________________________________

123

The intellectual structure of the supply chain management discipline: a citation and social network analysis Mihalis Giannakis _______________________________________________

136

Organizing for post-implementation ERP: a contingency theory perspective Kevin P. Gallagher and Vickie Coleman Gallagher _____________________

170

Enablers and inhibitors of advanced information technologies adoption by SMEs: an empirical study of auto ancillaries in India G. Kannabiran _________________________________________________

186

This journal is a member of and subscribes to the principles of the Committee on Publication Ethics

JEIM 25,2

96

Journal of Enterprise Information Management Vol. 25 No. 2, 2012 pp. 96-97 q Emerald Group Publishing Limited 1741-0398

Editorial The second issue commences with the research paper by Tripathi et al., entitled “Interoperability adoption among government and corporate portals in India: a study”. The authors in this paper examined the position of interoperability of Government and Corporate portals in technological adoption space in India in terms of three critical dimensions: data integration, process integration and communication integration. The authors conducted this exploratory study through a survey questionnaire from 300 portals of Government departments and Public Sector Undertakings (PSUs) in India. In addition to this survey, the authors collected data from the portals of Indian companies and compared the results to those of the Government portals. These results illustrate that the majority of Government portals in India have initiated integration. Second, the portals of Indian companies are performing better than the portals of Government and PSUs for achieving an interoperable position. Third, there is high dispersion in level of integration of Government portals in India. The portals with the lowest level of integration in Government in India will determine when Government will actually attain full horizontal integration and hence achieve an interoperable portal as there is high dispersion in level of integration of Government portals in India. The authors claim that this research is the first of its kind to examine the position of interoperability in technological adoption space in India. The results lead to a number of recommendations for achieving interoperability for Government portals in India. The above research paper is followed by another paper by Groznik and Maslaric, entitled “A process approach to distribution channel re-engineering”. The authors proposed a methodology for distribution network re-engineering, as for the last few decades there has been a growing interest in making more integrated business decisions across larger segments of the logistics and distribution networks. Moreover, the authors developed a research methodology to assist distribution networks reengineering, due integrating logistic processes within the distribution supply chain. The emphasis of this methodology is on business processes modeling and reengineering in distribution network. The empirical findings substantiate that distribution network reengineering needs to be balanced, methodological process that integrates business process reengineering in combination with information technology. In addition, the case study findings presented illustrate that the proposed methodology has resulted in considerable cost savings and enhancing effectiveness of distribution networks. The authors claim to have extended the reengineering theory and information technology into a supply chain context. Moreover, this research is among the first empirical papers that specifically investigates the relationship between reengineering, information technology and distribution channel management practices; thus, filling an important gap in the supply chain literature. Then we have Giannakis focusing on the “The intellectual structure of the supply chain management discipline: a citation and social network analysis”. This research employs a combination of a Social Network Analysis and Citation Analysis among ten academic journals related to supply chain phenomena. Furthermore, it examines the structure of their network and the role that each of the journals performs, to explore the way that the supply chain management (SCM) discipline has evolved over the last 20 years, to identify the forms of sources used by SCM researchers and the changes that took place. Citations between and within journals are analysed using social network

analysis metrics, in order to examine how the field of SCM has been shaped over time, by describing how communication patterns between and among members of its social network have changed. The analysis of the empirical findings reveals the current structure of the network, the level of cohesion of the discipline and the similarities and differences amongst the journals. However, this is limited to the last 20 years to reflect the growth of the academic discipline of supply chain management, but can be extended beyond this period to examine its extended problem domain. The study confirms the inter-disciplinary nature of supply chain phenomena and the opportunity for research in SCM to acquire central role in the study of inter-organisational systems. Thereafter, we have Gallagher and Gallagher presenting their research work entitled “Organizing for post-implementation ERP – a contingency theory perspective”. The authors in this paper present their understanding of post-implementation organizational choices – when subject matter experts (SMEs) were retained and returned. The authors aim to understand these choices relative to the goals of their project. This research conceptually builds upon prior qualitative research, but is still exploratory in nature. The authors report on findings from an on-line survey conducted with 65 organisations i.e. sample of small, medium and large firms. The authors identified that the hybrid structure was utilised most often. This research is exploratory in nature; hence, it may not be projectable to a larger population, thus, future research should supplement this study with more industry user groups, expand the sample size, and utilise more advanced statistical methods. The authors highlight that previous research studies have focused on successfully implementing ERP, nevertheless, neglecting the post-implementation design. Based in this argument, the authors claim to contribute to a growing body of work with regard to post-implementation design, taking into consideration SMEs and reporting structure, goals, and measures of success utilising contingency theory as our backdrop. Finally, Kannabiran presents his research work entitled “Enablers and inhibitors of advanced information technologies adoption by SMEs: an empirical study of auto ancillaries in India”. This paper explores and evaluates the influential factors enabling or inhibiting adoption of advanced IT in the Indian auto ancillary SMEs. In order to identify and evaluate the enabling and inhibiting factors, the author carried out a detailed survey among registered Indian auto ancillary SMEs during 2010. The data collected were analyzed using confirmatory factor analysis and multivariate regression to evaluate the influence of enablers and inhibitors of advanced IT adoption by the auto ancillary SMEs. Their findings highlighted that the level of advanced IT adoption in auto ancillaries is low with only 17 per cent of SMEs have adopted technologies. A number of enabling and inhibiting factors were identified from the empirical findings. Despite the positive external IT environment and recognition of benefits, advanced IT adoption by SMEs in the auto ancillaries is limited by lack of financial capabilities and in-house IT human resources. For advanced IT adoption in this sector, the author stresses the need for a new approach such as “software as service” or “cloud computing” that eliminates the need for high investments as well as in-house IT manpower. The author asserts that the findings will be useful to SMEs in general but also to policy-makers to bring about effective policies and support strategies for SMEs. The author also accentuates that this is one of the early papers that brings out the enablers and inhibitors of advanced IT adoption by auto ancillaries in India. Zahir Irani and Yogesh Dwivedi Editors

Editorial

97

The current issue and full text archive of this journal is available at www.emeraldinsight.com/1741-0398.htm

JEIM 25,2

Interoperability adoption among government and corporate portals in India: a study

98 Received 2 October 2010 Revised 2 December 2010 12 March 2011 28 March 2011 Accepted 29 March 2011

Rakhi Tripathi and M.P. Gupta School of Information Technology, Indian Institute of Technology, New Delhi, India, and

Jaijit Bhattacharya Government Affairs, HP India, New Delhi, India Abstract Purpose – The purpose of this study is to examine the position of interoperability of government and corporate portals in technological adoption space in India in terms of three critical dimensions: data integration, process integration and communication integration. Design/methodology/approach – This exploratory study was conducted through a survey questionnaire from 300 portals of government departments and public sector undertakings (PSUs) in India. Data were also collected from portals of Indian companies and the results have been compared with those of the government portals. Findings – The results show that the majority of government portals in India have initiated integration. Second, the portals of Indian companies are performing better than the portals of government and PSUs for achieving an interoperable position. Third, there is high dispersion in level of integration of government portals in India. Practical implications – The portals with the lowest level of integration in government in India will determine when government will actually attain full horizontal integration and hence achieve an interoperable portal as there is high dispersion in level of integration of government portals in India. Also, for achieving an interoperable government portal, an organization needs to focus on the weakest factors of each dimension. Originality/value – This study is the first to examine the position of interoperability in technological adoption space in India. The results lead to a number of recommendations for achieving interoperability for government portals in India. The study also highlights the weakest factors of each dimension that require more improvement than other factors. Keywords Integration, Interoperability, One-stop portal, E-government, Open systems Paper type Research paper

Journal of Enterprise Information Management Vol. 25 No. 2, 2012 pp. 98-122 q Emerald Group Publishing Limited 1741-0398 DOI 10.1108/17410391211204374

1. Introduction Interoperability among government organizations has been identified as a central issue and a critical prerequisite for achieving a one-stop government portal (Tripathi et al., 2011; Peristeras et al., 2007). The European Commission (2003) has defined interoperability as “the means by which the inter-linking of systems, information and ways of working, whether within or between administrations, nationally or across Europe, or with the enterprise sector, occurs”. Interoperability is the ability of ICT systems to work together. As identified by Vogel et al. (2008) and Traunmu¨ller (2005), the benefits of interoperability become clear in the following settings: more effectiveness (interconnection instead of isolated solutions), efficiency (reduction of

the transaction costs and increase of the involved agents’ participation), and responsiveness (better access to more information, making possible the fastest resolution of the problems). Economic benefits of interoperability result in lower transaction costs typically utilizing standardized processes. To achieve an interoperable government, the integration of government information resources and processes, and the interoperation of independent information systems, are essential. According to Gouscos et al. (2007), most integration and interoperation efforts face serious challenges and limitations as exchanges of information and services are fragmented and complex, plagued by technical and organizational problems. Stated by Vernadat (2010), the barriers to interoperability comprise political, organizational, economical and technical issues. Problem in government compounded due to multiple diverse sources of data, most of these are unstructured that lies in the form of rules, procedures and concepts, guidelines etc. Data referring to facts and figures treated as operational idea are structured that can be stored in computerized form of database and further used for decision-making (Gupta et al., 2005). Integration is an act or instance of combining an organization’s processes and information into an integral whole (IBM, 2004). A distinction should be made between interoperability and integration. As stated by Klischewski and Scholl (2006), integration is the forming of a larger unit of government entities, temporary or permanent, for the purpose of merging processes and/or sharing information. Interoperation in e-government occurs whenever independent or heterogeneous information systems or their components controlled by different jurisdictions, administrations, or external partners work together (efficiently and effectively) in a predefined and agreed-on fashion. E-government interoperability is the technical capability for e-Government interoperation (Scholl and Klischewski, 2007). Integration forms the basis for a complete interoperable government. In the government’s perspective integration is a process of making the information and processes of two government organizations as a whole (Virili and Sorrentino, 2009). According to the e-GIF (Government Interoperability Framework) if the coherent exchange of information and services between systems is achieved then the systems can be regarded as truly interoperable. Therefore, through integration of information and processes of two organizations, it will be easy to achieve interoperability. The adoption of a new technology such as interoperability involves a proper assessment of the status of integration (process integration, data integration and communication integration) within the government. Higher the level of integration of an organization, lesser the resources needed to adopt the interoperability technology. Integration can happen in two ways: vertical and horizontal. Vertical integration refers to local, state and federal governments connected for different functions or services of government. An example would be the business licensing process. In an ideal situation where systems are vertically integrated, once a citizen filed for a business license at the city government, this information would be propagated to the state’s business licensing system and to the federal government to obtain an employer identification number (FEIN). In contrast horizontal integration refers to integration across different functions and services (Layne and Lee, 2001). An example would be a business being able to pay its unemployment insurance to one state department and its state business taxes to another state department at the same time because systems in both departments talk to each other or work from the same database. The need of

Interoperability adoption

99

JEIM 25,2

100

interoperability arises both within the departments as well as between the departments of government. In India most of the e-government or e-governance initiatives have brought big promise but are facing huge challenge due to islands of information, difficulties in data interchange, and inefficient communication among the government, the businesses and the citizens. Technology incompatibility is only a piece of this “Interoperability Issues Puzzle” in e-governance initiatives in India. Incompatibilities in government processes, diverse and distributed working groups, people, teams, multiple interest perspectives, and interest groups, all create much larger issues for interoperability than the technology alone. Though scope of term “e-governance” is much wider as compared to “e-government”, “e-governance” is preferred term in common parlance in Indian and appear in all the related government reports and proceedings, hence we will also use e-governance throughout rest of the paper as the research confines to Indian settings. Status of E-government in India India is federal union of states comprising 28 states and seven union territories. India’s central government has 49 ministries and two independent departments. There are 18 independent offices in Indian government. In the last decade the growth of e-government has been exceptional. E-government has acquired a special attention in India to facilitate organizational change programs. In India e-governance has steadily evolved from computerization of government departments to initiatives that encapsulate the finer points of Governance, such as citizen centricity, service orientation and transparency. As per West’s (2007) report India’s rank in e-government has improved from 77 in 2006 to 47 in 2007. Also, per the Economist Intelligence Unit’s e-readiness ranking for the year 2009 (EIU, 2009), India ranks 58 among the countries of the world. Over the years, a large number of initiatives have been undertaken by various State Governments and Central Ministries of India to usher in an era of e-Government. Sustained efforts have been made at multiple levels to improve the delivery of public services and simplify the process of accessing them. Nearly all Indian government bodies now have some presence on the web, including fully-fledged e-Government web portals, albeit in small numbers. Government of India has approved a policy of allocating two to 3 per cent of the IT budget in each government ministry. The “Eleventh five year plan” (2007-2012), has allocated $3.2 billion towards e-government applications in the country. Following to that, a national level e-governance plan (NEGP) was announced on 2006, with an outlay of 33000 crores rupees with the aim of creating the right governance and institutional mechanisms, setting up the core infrastructure and policies and implementing 26 Mission Mode Projects and eight support components at the center, state and integrated service levels in order to create a citizen-centric and business-centric environment for governance (Gupta, 2010). Apart from mission mode projects, three other major components of NeGP include the creation of a State Wide Area Network; a State Data Centre (SDC) and 100,000 Community Service Centres (CSC) to serve a cluster of six villages in the country and provide a range of more than eighty services. One of the key objectives under the e-government agenda in many countries is to achieve a one-stop government portal (Gupta et al., 2005). In India, agenda of one stop India portal was laid down with the allocation of Rs. 100 crores in the tenth Indian five-year plan (2002-2007) much before NEGP. The plan also conceived the launch of

National Institute of e-governance, Central Repository of Data, Citizen Service Centres for one-stop non-stop delivery of public services, dissemination of information relating to best practices/innovations in e-Governance (including a documentary series entitled “IT in the Service of People”), and awards for best web sites and innovative use of IT in the delivery of public services[1]. India portal is supposed to serve as a one-stop non-stop destination for public access to information on various aspects of government functioning. It is also to serve as a single window for delivery of government services. An Expert Group was set up to conceptualize its draft report, which inter alia it envisages setting up of a National Information Services Board and implementing the portal with the support of various stakeholders including industry associations, academic institutions, etc. The first version of “India Portal” was launched 10 November 2005 by National Informatics Centre (NIC). Subsequently “india.gov.in” was included as one of the mission mode projects under the National E-governance Plan approved in 2006. The objective behind the portal is to provide a single window access to the information and services of the Indian government at all levels from central government to state government to district administration and Panchayats for the Citizens, Business and Overseas Indians. This portal aims to provide comprehensive, accurate, and reliable and one stop source of information about India and its various facets (Gupta, 2010). Success of such comprehensive portal would necessarily require development of information management plans, standards, data architecture, reference data, initial data collection and conversion to digital form, forms, deliverables, migration plan, sustainable strategy and maintenance. Today, nearly all of the government organizations in India have a web presence with over more than 6500 web sites maintained by various government organisation to render information, services, etc. electronically. These portals often face challenge of presenting a significant variety of features, complexity of structure and plurality of services to be offered. India being country of diverse culture, language poses a major hindrance. Without multilingual facility, there is hardly any use of portals for common men. Since the knowledge divide is quite pronounced in the country, people from backward/rural areas would require easy access but also need online help to navigate through the portals[2]. Hence it is often found that these portals are portal in namesake and often struggle to go beyond a web site in terms of contents and features primarily due to lack of backend integration. The mapping over stage models, show only few departments having achieved some type of integration (Gupta, 2010). Portal maturity will depend on degree of integration among disparate systems, which is achievable only if the backend systems are interoperable. In this paper, attempt is made to identify the position of interoperability of these portals in technological adoption space. It takes help of a three dimensional adoption space model proposed by Chen et al. (2005) to measure the level of integration. Prior research work of the authors (Tripathi et al., 2011) is dovetailed into adoption space model in ascertaining the level of interoperability and degree of integration. This includes an understanding of critical factors necessary for the successful adoption of interoperability technology along three dimensions of integration – process integration, communication integration and data integration. All the dimensions and organizational factors are inter-related. By measuring the position of interoperability an organization can focus on improving the factors to achieve interoperability.

Interoperability adoption

101

JEIM 25,2

102

The structure of the paper is as follows. In the following section, adoption space model for interoperability has been explained. Section 3, discusses the research methodology used in this research. Next, section 4 presents and analyzes the results of the data surveyed. Section 5 discusses the insights of the study and points out the relevant factors. Finally, in section 6 the article offers some conclusions that include limitations of the paper along with future work.

2. Adoption space To determine portal maturity would require assessment of integration from multiple dimensions. In our previous study, we identified three dimensions of integration (Tripathi et al., 2011): (1) Data integration: Data integration is an issue of combining data residing at different sources and providing the user with a unified view of this data (Halevy, 2001; Srivastava et al., 1996). (2) Process integration: For inter-organizational integration the necessity for process integration increases. Different processes are developed for every level of government organizations (Tripathi et al., 2011). (3) Communication integration: Communication integration comprises the use of electronic computers, computer software and computer networks to convert, store, protect, process, transmit and securely retrieve information (Vernadat, 2010). The details are given in Table I. Each dimension has further been mapped to sub-dimensions (13 for Data integration, 7 for Process integration and 8 for Communication integration) for an appropriate estimation of the position of respective organizations. Adoption space refers to a continuum of positions in a three dimensional space over which evolution or progression towards maturity in adoption of technology can be located. Portal maturity, may also assessed, over continua of adoption space, primarily from the integration considerations based on the previous three dimensions (see Figure 1). Adoption space model as proposed in Figure 1 is logically sound as it measures the Euclidean distance for a particular location. This idea found interesting use by Chen (2003) who explained XML adoption in a technology project. In the present case, integration for portal maturity is measured in absolute value of the integration vector that corresponds to the Euclidean Distance of integration point (in a three dimensional space) from the origin. This model plots the level of integration of a portal in a three-dimensional Cartesian coordinate system. Each of the three dimensions of integration vector ranges from 0 (nil) to 5 (complete). The highest level of integration is at the point (5, 5, 5) in this three dimensional space, which implies that the organization is completely interoperable. At this position the portals are vertically and horizontally integrated. Euclidean distance is calculated as the square root of the sum of the squares of the arithmetical differences of the corresponding coordinates of the two points,

Literature referred

Expert consulted (2007-2009)

Data integration Gupta et al., 2005

Neeta Verma (2007), Senior Technical Director, NIC, India; Mirulesh (2009), Public Works Department (Delhi), India; Navin Mittal (2008), Collector, Andhra Pradesh, India IEEE, 2006 Neeta Verma, Senior Technical Director, NIC, India; Anurag Srivastava (2009), IT Director, Madhya Pradesh India K.N. Narayankar (2008), Senior Research Executive, Central Water & Power Research Station, India; Shefali Dash (2008), Deputy Director General, NIC-HQ, India Ajay K. Singh (2009), Director, CRIS, India; Santos and Reinhard, 2007; Rao et al., 2008; Layne and Lee, Ahmed, Software Programmer, Finance Commission of India 2001 Mach et al., 2006; Hiller and Dibakar Ray (2007), Scientist, NIC, India; Huzur Be´langer, 2001 Saran, Professor, Department of Computer Science and Engineering, I.I.T. Delhi, India; U.C. Nangia, Director, Ministry of Petroleum & Natural Gas, India Eckerson, 1999 Anurag Srivastava, IT Director, Madhya Pradesh India; Navin Mittal, Collector, Andhra Pradesh, India; Jacob Victor (2008), Joint Director (E-governance), Andhra Pradesh, India Weng et al., 2006; Ding et al., Dibakar Ray, Scientist, NIC, India; Jacob Victor, 2002 Joint Director (E-governance), Andhra Pradesh, India Coyle, 2002; The Open Group, Anurag Srivastava, IT Director, Madhya 2005 Pradesh India; Dibakar Ray, Scientist, NIC, India; Jacob Victor, Joint Director (E-governance), Andhra Pradesh, India IFEG Version 2.4 Report Janmejay, Principal System Analyst, Indian (2006) Government Tenders, India Janmejay, Principal System Analyst, Indian Government Tenders, India Janmejay, Principal System Analyst, Indian Government Tenders, India Janmejay, Principal System Analyst, Indian Government Tenders, India Janmejay, Principal System Analyst, Indian Government Tenders, India; D.C. Mishra (2009), Senior Technical Director, NIC, India, Process integration Liu et al., 2005

Ahmed (2009), Software Programmer, Finance Commission of India; Huzur Saran, Professor, Department of Computer Science and Engineering, IITD, India; Ajay K. Singh, Director, CRIS, India

Factor identified

Interoperability adoption

Data centre

Data architecture

103

Data update

Compatible standards Back office integration

Data security

Ontology Open standards

Message Formatting Language Data Replication Data Transformation Data Modelling Data Resource Description

Process codification

(continued)

Table I. Factors for measuring the “Integration sophistication” of an organization

JEIM 25,2

Literature referred

Expert consulted (2007-2009)

Ghattas and Soffer, 2008; Wittenburg et al., 2007

104

Anurag Srivastava, IT Director, Madhya Pradesh, India; Hardeep S. Hora (2009), NIC, India; Huzur Saran, Professor, Department of Computer Science and Engineering, IITD, India; Ajay K. Singh, Director, CRIS, India Ceravolo et al., 2008; Ahmed (2009), Software Programmer, Finance Wittenburg et al., 2007 Commission of India; Navin Mittal, Collector, Andhra Pradesh, India Department of Defense, 1996 Shefali Dash, Deputy Director General, NIC-HQ, India; Jacob Victor, Joint Director (E-governance), Andhra Pradesh, India Gugliotta et al., 2005; Liu et al., Neeta Verma, Senior Technical Director, NIC, 2005 India; Janmejay, Principal System Analyst, Indian Government Tenders, India Hardeep S. Hora, technical director of NIC, India; D. C. Mishra, Senior Technical Director, NIC, India

Factor identified Formulation of processes

Process update Reuse Middleware Open standards

Communication integration Ronald Noronha (2009), Chief Manager, BPCL, India; Mirulesh, Web Developer, Public Works Department (Delhi), India Strover, 2001 R. Vijaya Chakraboraty (2009), Senior Manager (Systems), National Aluminium Corporation Limited, India Huang et al., 2006; Ardagna Naveen Agrawal, Technical Director (IT), and Pernici, 2006; CISCO, 2006 Department of Land Resources, India; U.C. Nangia, Director, Ministry of Petroleum & Natural Gas, India Jacob Victor, Joint Director (E-governance), Layne and Lee, 2001; Bertot Andhra Pradesh, India; Janmejay, Principal and Jaeger, 2006; Evans and System Analyst, Indian Government Tenders, Yen, 2006 India Lin and Lin, 2008 Anurag Srivastava, IT Director, Madhya Pradesh India; Shefali Dash, Deputy Director General, NIC-HQ, India; Dibakar Ray, Scientist, NIC, India Straub and Nance, 1990; Vinay K. Chaudhary (2009), Engineer, Power Rainer et al., 1991 Grid Corporation, India; Mittal, Collector, Andhra Pradesh, India IFEG Version 2.4 Report Naveen Agrawal, Technical Director (IT), (2005) Department of Land Resources, India; U.C. Nangia, Director, Ministry of Petroleum & Natural Gas, India IFEG Version 2.4 Report Jacob Victor, Joint Director (E-governance), (2005) Andhra Pradesh, India; Janmejay, Principal System Analyst, Indian Government Tenders, India Table I.

Source: Tripathi et al. (2011)

Networking Connectivity Quality of services

Web and internet technologies Interoperability of technologies Security Intelligent design

Network Layer Security

Interoperability adoption

105

Figure 1. Adoption space model

vffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi u n uX dðx; yÞ ¼ t xi 2 yi Þ2 i¼1

x ¼, x1 ; x2 ; :::; xn .

y ¼, y1 ; y2 ; :::; yn . p The Euclidean Distance (from origin) of “completely interoperable” point will be 5 3. This lies outside the scale of 0 to 5 and needs to be normalized (to 5) in order to make comparison meaningful. Therefore, Normalized Euclidean Distance has been used for all our analysis. pffiffiffi Normalized Euclidean Distance ¼ ðEuclidean DistanceÞ= 3 Considering the position of each organization’s portal in the three dimensional space, t-test has been applied for significance of the result. This test has been conducted at 95 per cent confidence interval i.e. p value , 0.05. We have applied the test as follows:

JEIM 25,2

.

.

106

Normalized Euclidean Distance (NED): Comparing the NED of Government Departments, PSU and Indian companies’ portals. Individual dimensions: Comparing each of the three dimensions, for three types of portals (government, PSU and corporate).

Therefore, we have compared the results in four ways: Normalized Euclidean Distance, Data Integration, Process Integration and Communication Integration. 3. Research methodology To assess portal maturity over three-dimension adoption space model, a questionnaire survey is conducted. Success of the research objectives is dependent on the analysis of a large number of responses. The questionnaires based approach is a well-established technique in obtaining data in social sciences research. A number of Information Technology (IT) research projects with the objective of getting data from user groups have been successfully conducted using this method. Precise, structured multiple-choice questionnaires were designed keeping in mind the need for eliciting the requisite information. It must be noted that the questionnaire went through a pretesting process before it was administered. The pretesting was carried out with a panel comprising of four high-ranking government officials involved with e-government initiatives in India and an eminent academician. The questionnaire was refined according to the comments and suggestions made by this panel. The modifications that were made were primarily related to the instructions in the survey and rephrasing of some measurement items. Since there were no major comments received, the questionnaire was considered ready for data collection. Three separate sections were developed for each dimension of integration as to find the current situation of the organization’s portal on integration. The section on data integration comprised 13 questions. Six questions were included in the section of Process integration and section on Communication integration had eight questions. Table I show the factors of the three dimensions and how they were identified through literature review and interviewing the experts. One question each was asked for every factor of the respective dimension (see the Appendix, Table AI). Five-point Lickert scale was used where 1 is interpreted as ‘not initiated’; 2 – being initiated; 3 – partially initiated; 4 – advance stage of integration and 5 – complete implementation. The answers of the categories are mutually exclusive so that respondent had to select not more than one choice against an item. Apart from this, the respondents were given the opportunity to offer their comments on any issue related to e-government development. ‘Zero’ (0) was also used in the scale to capture the non-familiarity of the respondents with the terminology and is not aware of the value of factor. Difference between 0 (unfamiliar) and 1 (not initiated) is that if any portal is on scale 1 then it signifies that the organization is aware of the factor and its usefulness but has not initiated yet. Organizational factors can be one of the reasons for not initiating a factor. For example, an organization is aware of the importance of a factor that can help in achieve interoperability. But without the support of top level management (Kambil et al., 2000; Eder and Igbaria, 2001) it is difficult to initiate any factor in any organization whether they are technology related or not. This survey was done to note how many respondents are not even aware of the factors that help in achieving interoperability.

The survey was conducted in August-September, 2010. The questionnaire along with a covering letter mentioning the objective of the study was sent to approximately 400 officials of government departments of India (central ministry, states and union territories), Indian public sector undertakings (government owned and controlled corporations) and Indian companies portals. A large number of government portals are developed and maintained by National Informatics Centre (NIC), India. Regular visits to NIC were made. Only those PSUs and Indian companies were selected that tend to have their corporate/head office in National Capital Region (NCR). The officials were selected on the basis of their involvement with e-government initiatives within departments in central and state governments in India. The questionnaires got hand delivered to the respondents by volunteer students and for this prior appointments were taken.

Interoperability adoption

107

4. Results and analysis Responses were received from 273 officials in India (see Table II). Break up include 93 government organizations (including states, central ministries and their departments), 90 Indian public sector undertakings and 90 Indian corporations. Profiles of respondents Work experience of the respondents that are involved in e-government initiatives and in field of IT are presented as frequency distribution in Table III. Most of them participated on the condition that their identity is not disclosed. In total, 74 respondents had less than five years experience. There were 54 interviewees with an experience more 15 years. These were mostly the officers at director level and have been working on e-government projects in India for several years. Table II summarizes the profiles of the usable respondents. Data were collected from 19 states of India. Majority of the state portals are maintained by National Informatics Centre, India. A total of 43 central ministry officials responded to the

Profile States Central ministries Independent offices Government departments Public Sector Undertakings (PSU) Indian companies Total

Experience (in years) NA Up to 5 5 to 10 10 to 15 15 and higher Total

Number of respondents 19 43 14 17 90 90 273

Table II. Profiles of respondents

Number of respondents 72 74 51 22 54 273

Table III. Experience of respondents in E-government and IT

JEIM 25,2

108

questionnaire and gave information about the portal of their department. Data were also collected from 14 independent offices and 17 departments in India. A total of 90 usable responses were received from the public sector undertakings and Indian companies. Frequency distribution Table IV gives a breakdown of Integration maturity on the Lickert scale for 93 portals of government organizations in India. Data revealed that 63 per cent (59 out of 93) of these government portals have initiated some efforts for integration. This signifies that government departments are either connected or, at least, communicating to each other. Table IV further elaborates the situation of portals with regard to integration maturity. Most of the portals that have started working on integration are some where between the levels of initiated and partially initiated (2 and 3 on Lickert scale). This implies majority of the portals are at a lower level of integration. Examining the development of each dimension individually shows that most of the government portals have initiated Communication Integration (83 per cent). Only 52 and 57 per cent of government portals have initiated process and data integration. Moreover, there are very few government portals that have achieved significant levels of integration on any of the dimensions. It has been noted that only one government portal (www.tenders.gov) has completely implemented process integration and is also at significant levels of the other two dimensions. Adoption space Results of integration adoption are presented and the coordinates of the three dimensions of all the portals of organization (Government Departments, PSU and Indian companies) are presented (up to two decimal places) in Table V. The coordinates of the sample average of each dimension of government portals, is at the initiation

Integration Maturity (Lickert Scale)

Table IV. Frequency distribution of government portals on integration maturity

Table V. Positions of the surveyed organizations in interoperability adoption space along three dimensions

Not initiated Initiated Partially initiated Advance stage of implementation Complete implementation Total

Indian portals Government Public sector undertakings Indian companies

Normalized Euclidean Distance

Data integration

Process integration

Communication integration

34 43 15 1

40 33 16 4

45 33 13 1

16 45 29 3

None 93

None 93

1 93

None 93

Normalized Euclidean Distance

Data integration

Process integration

Communication integration

2.34 2.2

2.23 2.09

2.00 2.18

2.61 2.28

2.89

2.85

2.51

3.23

level. It should be noted that every dimension of each of the organization portals is far from the position of (5, 5, 5) i.e. position of complete interoperability. The position of Indian company portals is higher than the position of government and PSU portals in interoperability adoption space in India. Also, it should be mentioned that except for process integration, government portals are performing better than PSU portals in all the dimensions. The sample average of PSU portals at each dimension is at the “Initiated” level. Comparing the dimensions vertically shows that the position of process integration is the farthest from the final destination (5, 5, 5) in all the three types of organizations. In adoption space, the position of the organization is measured by the Euclidean Distance, and it shows that in India the position of Indian company portals is slightly better than positions of government and PSU portals in India in the adoption space. Sample average gives the central position of all organizations. However, the collected data has shown significant variations. For meticulous study, Table VI shows the averages of top ten portals of all the organizations that have highest level of integration as compared to the rest of the surveyed portals. Similarly, the bottom ten portals that have lowest level of integration have been computed. This result help us compare the performances between the organizations and with in the organizations as well. As seen earlier in Table V, position of government portal in adoption space is 2.34. But the best ten government portals have higher integration maturity. The Euclidean distance of the best ten average government portals is 3.63, which imply that most of the government portals are close to advanced stage of implementation of integration. On the other hand, average of bottom ten of government portals is very low and shows that these portals have not yet initiated integration. The average of process integration of bottom ten portals is below 1, which implies that process integration has not been initiated and also there are few government departments that are not even familiar with the factors of this dimension. Comparing the averages of top ten portals of government and PSU, indicate that few government portals have

Dimensions

Top ten portals

Bottom ten portals

Government portals Normalized Euclidean Distance Data integration Process integration Communication integration

3.63 3.66 3.56 3.68

1.32 1.22 0.77 1.76

Public sector undertaking portals Normalized Euclidean Distance Data integration Process integration Communication integration

2.97 2.92 3.06 2.94

1.45 1.51 1.24 1.58

Indian company portals Normalized Euclidean Distance Data integration Process integration Communication integration

3.81 3.72 3.67 4.04

1.80 1.70 0.99 2.43

Interoperability adoption

109

Table VI. Comparing the averages of best performing portals (top ten) and the portals at the lowest position (bottom ten) in interoperability adoption space of the surveyed organizations

JEIM 25,2

110

achieved higher level of integration than the PSU portals. On the contrary, bottom ten portals of PSU have higher averages than government portals. This signifies that integration maturity of government portals is varied. The position of Indian companies is better than the position of government portals when comparing the best ten and the bottom ten portals. In a three-dimension adoption space, the positions of three types of organizations are plotted in MATLAB shown in Figure 2. The adoption space is a three-dimensional Cartesian coordinate system with the origin labelled as O. The x-axis represents the degree of sophistication of data integration. The y-axis represents the degree of sophistication of process integration. The z-axis represents the degree of sophistication of communication integration. Figure 2 has three clusters: Averages of Sample, Top ten and Bottom ten. Each cluster contains the position of surveyed organizations. As discussed earlier, the position of Indian company portals is slightly better than the position of government and PSU portals. Moreover, the development of government portals is varied. Significance . Government portals and portals of Indian companies: In Figure 2, the sample average position of Indian company portals (2.85, 2.51, 2.32) in the adoption space model is higher than the position of government portals (2.23, 2.00, 2.61). In Table VII, results are given for the comparison of level of integration of Indian companies and government departments and ministries. Comparison has been done with Euclidean Distance and with the average of each dimension. Each average of Indian company portal is significantly higher than the average of government department and ministries. Significance has been computed and given in the Table VIII.

Figure 2. Three-dimensional adoption space

Government portals

Indian company portals

Average Normalized Euclidean Distance Data integration Process integration Communication integration

2.34 2.23 2.00 2.61

2.9 2.85 2.51 3.23

Variance Normalized Euclidean Distance Data integration Process integration Communication integration

0.69 0.83 0.93 0.72

0.56 0.61 0.82 0.54

Normalized Euclidean Distance Data integration Process integration Communication integration

t-test ( p-value) 0.00 0.00 0.00 0.00

Indian Indian Indian Indian

Interoperability adoption

111

Remarks Company portals . Company portals . Company portals . Company portals .

Govt. Govt. Govt. Govt.

portal portal portal portal

Government portals

Indian PSU portals

Average Normalized Euclidean Distance Data integration Process integration Communication integration

2.34 2.23 2.00 2.61

2.21 2.09 2.18 2.28

Variance Normalized Euclidean Distance Data integration Process integration Communication integration

0.69 0.83 0.93 0.72

0.45 0.52 0.6 0.5

Normalized Euclidean Distance Data integration Process integration Communication integration

t-test ( p-value) 0.00 0.09 0.06 0.00

Remarks Govt. . PSU Govt. ¼ PSU Govt. ¼ PSU Govt. . PSU

.

T-test: p-value of t-test of the two organizations with Normalized Euclidean Distance, Data Integration, Process Integration and Communication Integration is less than 0.05, which proves that the level of Integration in portals of Indian companies is significantly higher than in government portals. Government portals and public sector undertakings portals: Position of sample average of government portals (2.23, 2.00, 2.61) in the adoption space models is higher than that of PSU portals (2.09, 2.18, 2.28) (see Figure 2). Like Table VII, Table VIII shows the results for the comparison of level of integration of government portals and public sector undertakings portals. The averages of

Table VII. VI. Comparing level of integration – government portals and portals of companies in India

Table VIII. Comparing level of integration – government portals and PSU portals in India

JEIM 25,2

112

government portals are higher than the average of PSU portals except at the level of Process Integration. The sample average of process integration of PSU portals is 2.18 as compared to the process integration average of government portals, which is 2. Significance has been computed and given in the table. T-test: p-value of t-test of the two organizations with Data Integration and Process Integration is not less than 0.05, which proves that the level of Integration in portals of PSU is not significantly higher than in government portals. Also, the p-value of t-test for Normalized Euclidean Distance and Communication Integration of government and PSU is less than 0.05 but with government . PSU, which shows that at level of Communication Integration and overall (NED) government portals are at a higher level than PSU. 5. Discussion The previous results are depicted through candlestick chart of each dimension and normalized Euclidean distance for three types of organizations (government, PSU and company) and are presented in Figure 3. Furthermore, the results of each organization have been divided into three different categories: averages of best performing portals (top ten) for integration maturity; averages of the portals at the lowest level of integration (bottom ten) and sample average. The position of each organization is evaluated on a five-point Lickert scale and the data has been provided in the previous section. The findings of survey and analysis of the government portals in India yielded certain insights. The portals of Indian companies are performing better than the portals of government and PSUs for achieving an interoperable position. In Figure 3, it can be

Figure 3. Candlestick charts of all the averages in interoperability adoption space of each organization

observed that the position of Indian company portals is clearly better than the position of government and PSU portals in India. A comparison of the averages of best performing portals, lowest level portals and sample; reveals that, the position of Indian company portals is consistently higher than position of government and PSU portals except for the average of bottom ten portals of process integration of PSU portals. This is not unexpected as it has always been stated (Scholl, 2006; Escher and Margetts, 2007; Morgeson and Mithas, 2009) that the growth of government is far behind the growth of companies’, reasons being legislative barriers, administrative barriers, technological barriers, social barriers etc. This has also been seen that portals of Indian companies have achieved higher level of integration as compared to government portals in India. Figure 3 also shows that the best ten government portals have achieved higher position of integration as compared to the best ten performing portals of PSUs in India. On the contrary, level of integration of the weakest government portals (bottom ten) is lower than that of weakest PSU portals, except for communication integration. This implies that dispersion of government portals is significantly higher than Public Sector Undertaking portals, i.e. the development of Public Sector Undertaking portals seems to be more consistent. Therefore, we cannot make a conclusive statement on the performance of government and PSU portals for achieving interoperability as the portals with high level of integration and portals at the lowest level in government are moving in opposite directions. This has also been proved through t-tests in the previous section. One may say that because of high dispersion in government portals the mean value is not very significant. High dispersion in level of integration of government portals in India for achieving interoperability shows that some progressive departments in government have taken lead, yet there are also significant laggards. Except for communication integration, the position of bottom ten government portals is at the lowest level of integration among the three types of organizations in India. For achieving a one-stop government portal, both vertical and horizontal integrations are essential. This signifies that all the portals of government must be integrated and for this each portal should attain a high level of integration. The portals with the lowest level of integration in government in India will determine when government will actually attain full horizontal integration and hence achieve an interoperable portal.

Weakest factors of all dimensions of integration in government portals in India The results of adoption space highlight factors of every dimension that are comparatively weaker than the other factors and require relatively more improvement than the other factors in government portals. These factors have either not been initiated or are at a relatively low scale. Focusing on these factors will help in increase the level of Integration and thus help in achieving interoperability. We have discussed lowest quartile of each dimension. Also, as mentioned earlier that the data has been collected for scale 0 which implies that the respondent is unfamiliar with the terminology of the factor and does not understand its importance for an interoperable portal. One of the major reasons of these factors being low on Lickert scale is that organizations are not aware of the factor.

Interoperability adoption

113

JEIM 25,2

114

Data integration: Factors that are the weakest in this dimension are the specialized technologies for supporting metadata (data of data) that are required to accomplish data integration. (1) Ontology: Ontology is categorizing things that exist in same domain. The need for ontology arises for development of portals as government has enormous data from different sources. These data are required to be managed and categorized for an efficient portal. For vertical and horizontal integration, Ontology will effectively combine the data and information coming from multiple heterogeneous sources. Moreover, with the help of ontology the issue of semantics, which is an upcoming problem, can be controlled. The average of this factor is 1.47 on five-point scale among 93 portals of government organizations, which implies that in most of the government organizations ontology has not been initiated. One of the major reasons behind this slackness is that a significant number (31 out of 93) of government officials are ignorant about ontology and therefore, are not making any effort for its use. (2) Adoption of open standards: According to Coyle (2002), features of open standards are that: . anyone can use the standards to develop software; . anyone can acquire the standards for free or without a significant cost; and . the standard has been developed in a way in which anyone can participate. Apart from being inexpensive, the use of open standards reduces the risk of vendor lock-in and to guarantee data preservation. The position of this factor is 1.62 on a five-point scale i.e. in most of the organization portals this factor has not been initiated. One of the main reasons behind this low average of the factor is same as above that 29 out of 93 government portals are not aware of the importance of the factor. (3) Message Formatting Language implementation: The Message Formatting Language will help in defining the format of data messages and documents that can be exchanged between applications. This includes defining the standards for the data exchange between the organizations. The involved organizations can be the internal government organizations as well as outside agencies (IFEG Version 2.4 Report). Average of this factor is 1.51 out of 5. In more than 50 per cent of the government portals show lack of any initiative on this though majority of government officials (80 per cent) are aware of its importance. Therefore, the reason for low scale may be varied. (4) Resource description framework: Data Resource Description defines the language for representing metadata. Metadata commonly defined as data about data, relates to a set of attributes that will capture the semantics of individual data items (IFEG Version 2.4 Report). Achieving interoperability for enormous data of government requires metadata and therefore data resource description. Like the previous factor, this one also has not been initiated in 50 per cent of the government portals and so its average is 1.52 out of 5. But unlike the factor of Message Formatting Language, the 33 per cent of the government officials are not familiar with the terminology and hence do not understand the significance of the factor.

Process integration: In government portals, Process integration is the farthest dimension from the position of interoperability out of the three dimensions of Integration. Most of the factors in the dimension are weak. But weakest factors that has either not been initiated or have a very slow progress are the following: . Adoption of open standards: As discussed previously, this factor is essential for the development of an interoperable government portal. In the dimension of process integration, adoption of open standards has not been initiated in majority (54 per cent) of the government portals. Few government portals have adopted open standards for combining the processes in some less important sections hence there has been no improvement. As a result, approximately 60 per cent of the government portals are very low at this factor. The same is in data integration, 33 per cent of the government officials working on portal development are not aware of the significance of the factor. Therefore, because if this is the overall position of the factor is effected. . Reuse: Software reuse is the process of implementing or updating software systems using existing software assets (Department of Defense, 1996). This factor has an average of 1.56 out of 5. Sizeable government officials (27 out of 93) are ignorant about potential software reuse. Promoting software reuse will have great bearing on productivity, quality, and reliability, and the decrease of costs and implementation time in e-government projects. An initial investment in starting software reuse will pays for itself after few phases. The development of a reuse process and repository produces a base of knowledge that improves in quality after every reuse, minimizing the amount of development work required for future projects, and ultimately reducing the risk of new projects that are based on repository knowledge. Communication integration: Communication integration deals with the use of electronic computers, computer software, and computer networks to convert, store, protect, process, and transmit and securely retrieve information. This dimension forms the platform for integration. By improving the weakest factors of this dimension the position of Communication Integration will improve that will further help achieve the position of interoperability. These are explained as following: .

Web and internet technologies: Governments worldwide are increasingly using the internet to provide public services to their constituents (Layne and Lee, 2001). Much of the research has focused on practical and technical dimensions while research on how to improve e-government for users remains scarce (Bertot and Jaeger, 2006). Web-based technologies offer governments more efficient and effective means than traditional physical channels to better serve their citizens (Evans and Yen, 2006; D. Evans and D.C. Yen, E-Government: Evolving relationship of citizens and government, domestic and international development, Government Information Quarterly, Vol. 23 No. 2 (2006), pp. 207-35. Article j PDF (222 K) j View Record in Scopus j Cited By in Scopus (6) Evans and Yen, 2006). This is considered one of the vital factors of the communication integration dimension. Unfortunately, more than one-third of the government officials are unfamiliar with web and related technologies or have

Interoperability adoption

115

JEIM 25,2 .

116

superficial knowledge as is evident from large number of government portals (57 per cent) are lacklustre and disorganised. Intelligent design of supporting applications (mobile, etc.) by users: The devices and channels that access government services and applications can be of multiple types. Therefore, applications that can support all the formats are becoming essential. This will not only make the portal flexible but also reachable to most of the citizens (IFEG Version 2.4 Report). A sizeable government officials (30 per cent) involved with portals development do not have proper knowledge of intelligent design. Only 21 out 93 government portals have initiated intelligent design of supporting applications. The average for this factor is the lowest among all the factors of all dimensions (1.29).

6. Research implications The results from this study provide organizations with a better understanding of factors associated with the adoption of interoperability, which will be useful reference for them to develop appropriate strategies. A high dispersion is found in level of integration of government portals in India. Therefore, for achieving a one-stop government portal, the Government need to focus on those portals with the lowest level of integration. Skilful planning is required for both vertical and horizontal integrations as both are essential for an interoperable portal. Additional efforts are required to offset the weakest factors of each dimension by way of infusing more on capacity building and skill development among government officials and also marking extra resources allocations. This will enable a positive environment for achieving integration and interoperability. It will be helpful to spread the awareness and significance of the factors, which reflect weakness on the part of government and its employees. The critical success factors would be commitment of key contributors, change in work culture, re-engineering of organization processes and e-inventing governments. The adoption model can be used for other technologies such as enterprise architecture and enterprise architecture integration that being adopted these days (Kamal, 2009). Enterprise architecture (EA) is particularly relevant to organizations that have a large portfolio of applications where problems such as functional overlap, duplication and redundancy are common. Enterprise application integration (EAI) refers to “the plans methods, and tools aimed at modernizing, consolidating, integrating and coordinating the computer applications within an enterprise” (McKeen and Smith, 2002). At technology level, EAI involves the development of messaging middleware, an integration broker that serves as a hub for inter-application communication, and adapters that allow applications to interface to the integration broker. 7. Conclusion and future work The present study provides empirical data about interoperability adoption in government portals of India and analyzes the current level of integration sophistication along three dimensions in Indian government portals. The study compares the results with portals of Public Sector Undertakings and Companies in India. An interoperability adoption framework has been used that helps organizations to examine their current status in the e-government environment from the perspective of three domains, namely data integration, process integration and communication

integration. The framework also provides guidelines for government organizations, which need to understand the potential benefits of adopting interoperability technology and then assists them in choosing the appropriate path and proper applications. The contribution of this paper is two-fold. First, it generates insights into interoperability adoption in portals of government organizations, PSUs and companies in India by providing empirical data through survey. Second, the research highlights the weakest factors of each dimension that are at a lower level and require relatively more resources than other factors to achieve the desired position of interoperability. One of the critical reasons for government portals in India not being able to achieve interoperability is the government official’s poor knowledge and appreciation about various issues of interoperability and integration. In general government is not known to have quality people and over this, the lack of technical skills adds up to great inertia governments are infamous far. This study is the first of its kind to have attempted assessment of the position of interoperability in government portals in India. There are some limitations, which hindered this study from proceeding efficiently. First, only the National Capital Region based Public Sector Undertakings were approached, due to travel and time constraints. As future work, targeting other regions may generate additional insights. Second, this study provides a snapshot analysis of current interoperability adoption. However, e-government is a fast-changing phenomenon and the dynamics associated with it can hardly be well understood in one-shot study. A longitudinal study can be used to find out e-government development trends across periods whereas a snapshot observation cannot. Further, in this study, the equal weights are given to each factor. A future work may consider assigning relative significance (weights) for factors along each dimension. Each factor can be given weights and accordingly suitable strategy will be required to achieve the desired level of sophistication. Inspecting the results of the survey reveals that while interoperability is an important precondition for one stop portal, several government organizations in India are far from making any serious efforts for the same. Given the complexity of subject and sheer size and spread government organization, it would be unwise to speculate how much time it will take for government portal to be interoperable and therefore achieve some reasonable level of maturity. Furthermore, the dimensions in this paper are identified primarily based on studies from literature and discussions with experts and experience with e-government initiatives in Indian government portals. The underlying theory of this adoption model shall be applicable to other governments as well. The dimensions and their factors can be further developed according to the requirements for portals. In summary, this study has been helpful in gaining insight into what is coming in a way of government organizations to achieve a one-stop portal. Interoperability is essential. Further, adoption of technology of interoperability will decrease transaction costs and enhance the reliability of government organization. Notes 1. Report of the working group on Convergence and e-governance for The tenth five year plan (2002-2007) Planning Commission, November, 2001. 2. Internal Project by M.P.Gupta submitted to NIC (2011).

Interoperability adoption

117

JEIM 25,2

References Ahmed (2009), Software Programmer, Finance Commission of India, telephone interview, March. Ardagna, D. and Pernici, B. (2006), “Dynamic web service composition with QoS constraints”, International Journal of Business Process Integration and Management, Vol. 1 No. 4, pp. 233-43.

118

Bertot, J.C. and Jaeger, P.T. (2006), “User-centred e-government: challenges and benefits for government web sites”, Government Information Quarterly, Vol. 23 No. 2, pp. 163-9. CISCO (2006), available at: www.cisco.com/en/US/products/ps6558/products_ios_technology_ home.html (accessed October 23, 2006). Ceravolo, P., Corallo, P. and Elia, G. (2008), “Semantic web-based profiled knowledge discovery in community of practice”, International Journal of Business Process Integration and Management, Vol. 3 No. 4, pp. 256-70. Chakraboraty, R.V. (2009), Senior Manager (Systems), National Aluminium Corporation, India, telephone interview, May. Chaudhary, V.K. (2009), Engineer, Power Grid Corporation, India, personal interview, March. Chen, M. (2003), “Factors affecting the adoption and diffusion of XML and web services standards for e-business systems”, International Journal of Human-Computer Studies, Vol. 58, pp. 259-79. Chen, A.N.K., Sen, S. and Shao, B.B.M. (2005), “Strategies for effective web services adoption for dynamic e-businesses”, Decision Support Systems, Vol. 42 No. 2, pp. 789-809. Coyle, K. (2002), “Open source, open standards”, Information Technology and Libraries, Vol. 21 No. 1, pp. 33-6. Dash, S. (2008), Deputy Director General, National Informatics Centre – HQ, India, personal interview, 28 January. Department of Defense (1996), Software Reuse Executive Primer, available at: http://sw-eng.fallschurch.va.us/ReuseIC/policy/primer/primer.htm (accessed April 1996). Ding, Y., Fensel, D., Klein, M. and Omelayenko, B. (2002), “The semantic web: yet another hip?”, Data & Knowledge Engineering, Vol. 41, pp. 205-27. EC: Commission of the European Communities (2003), “Linking-up Europe: the importance of interoperability for e-government services”, Commission of European Communities, Staff Working Document. Eckerson, W. (1999), “15 rules for enterprise portals”, Oracle Magazine, available at: www.oracle. com/oramag/oracle/99-Jul/49ind.html (accessed April 2000). Eder, L.B. and Igbaria, M. (2001), “Determinants of intranet diffusion and infusion”, Omega, Vol. 29 No. 3, pp. 233-42. Escher, T. and Margetts, H. (2007), “Understanding governments and citizens on-line: learning from e-commerce”, paper presented at the annual meeting of the American Political Science Association, August 30. Evans, D. and Yen, D.C. (2006), “E-government: evolving relationship of citizens and government, domestic and international development”, Government Information Quarterly, Vol. 23 No. 2, pp. 207-35. Ghattas, J. and Soffer, P. (2008), “Facilitating flexibility in inter-organisational processes: a conceptual model”, International Journal of Business Process Integration and Management, Vol. 3 No. 1, pp. 5-14.

Gouscos, D., Kalikakis, M., Legal, M. and Papadopoulou, S. (2007), “A general model of performance and quality for one-stop e-government service offerings”, Government Information Quarterly, Vol. 24, pp. 860-85. Gugliotta, A., Cabral, L., Domingue, J., Roberto, V., Rowlatt, M. and Davies, R. (2005), “A semantic web service-based architecture for the interoperability of e-government services”, The International Conference on E-Government (ICEG2005), Ottawa. Gupta, M.P. (2010), “Tracking the evolution of e-governance in India”, International Journal of Electronic Government Research, Vol. 6 No. 1, pp. 46-8. Gupta, M.P., Kumar, P. and Bhattacharya, J. (2005), Government Online: Opportunities and Challenges, Tata McGraw-Hill Publishing Company, New Delhi. Halevy, A.Y. (2001), “Answering queries using views: a survey”, Very Large Database Journal, Vol. 10 No. 4, pp. 270-94. Hiller, J.S. and Be´langer, F. (2001), “Privacy strategies for electronic government”, in Abramson, M.A. and Means, G.E. (Eds), E-Government 2001, Rowman & Littlefield, Lanham, MD, pp. 162-98. Hora, H.S. (2009), Technical Director of NIC, Ministry of Tribal Affairs, India, personal interview, March. Huang, C., Lo, C., Chao, K. and Younas, M. (2006), “Reaching consensus: a moderated fuzzy web services discovery method”, Information and Software Technology, Vol. 48 No. 6, pp. 410-23. IBM (2004), WebSphere Business Integration, available at: http://publib.boulder.ibm.com/ IEEE Standard Computer Dictionary: A Compilation of IEEE Standard Computer Glossaries (2006), IEEE Standard Computer Dictionary: A Compilation of IEEE Standard Computer Glossaries, Institute of Electrical and Electronics Engineers (IEEE 90), New York, NY, available at: www.sei.cmu.edu/str/indexes/glossary/interoperability.html (accessed October 2006). IFEG Version 2.4 Report (2006), NIC, available at: http://egovstandards.gov.in/ (accessed August 2006). Kamal, M.M. (2009), “Investigating the importance of factors influencing integration technologies adoption in local government authorities”, Transforming Government: People, Process and Policy, Vol. 3 No. 3, pp. 302-31. Kambil, A., Kalis, A., Koufaris, M. and Lucas, H.C. (2000), “Influences on the corporate adoption of web technology”, Communications of the ACM, Vol. 43 No. 11, pp. 264-71. Klischewski, R. and Scholl, H.J. (2006), “Information quality as a common ground for key players in e-government integration and interoperability”, Proceedings of the 39th Hawaii International Conference on System Sciences (HICSS), IEEE, Los Alamitos, CA. Layne, K. and Lee, J. (2001), “Developing fully functional e-government: a four stage model”, Government Information Quarterly, Vol. 18, pp. 122-36. Lin, H. and Lin, S. (2008), “Determinants of e-business diffusion: a test of the technology diffusion perspective”, Technovation, Vol. 28 No. 3, pp. 135-45. Liu, T., Dimpsey, R., Behroozi, A. and Kumaran, S. (2005), “Performance modelling of a business process integration middleware”, International Journal of Business Process Integration and Management, Vol. 1 No. 1, pp. 43-52.

Interoperability adoption

119

JEIM 25,2

120

McKeen, J.D. and Smith, H.A. (2002), “New developments in practice II: enterprise application integration”, Communications of the Association for Information Systems, Vol. 8, pp. 451-66. Mach, M., Sabol, T. and Paralic, J. (2006), “Integration of eGov services: back-office versus front-office integration”, Proceedings of the Workshop on Semantic Web for e-Government, workshop at the 3rd European Semantic Web Conference, Budva, Montenegro, June 11-14. Mirulesh (2009), Web Developer, Public Works Department (Delhi), India, personal interview, March. Mishra, D.C. (2009), Senior Technical Director, National Informatics Centre, India, personal interview, March. Mittal, N. (2008), Collector, Andhra Pradesh, India, personal interview, February 12. Morgeson, F.V. and Mithas, S. (2009), “E-government and the promise of performance: comparing end-user perceptions of e-business and US Federal Government web sites”, Public Administration Review, forthcoming. Narayankar, K.N. (2008), Senior Research Executive, Central Water & Power Research Station, India, personal interview, March 17. Noronha, R. (2009), Chief Manager, Bharat Petroleum Corporation, India, personal interview, March. (The) Open Group (2005), Developer Declaration of Independence, available at: www.opengroup. org/declaration/declaration.htm (accessed March 29, 2005). Peristeras, V., Loutas, N., Goudos, S.K. and Tarabanis, K. (2007), “Semantic interoperability conflicts in pan-European public services”, Proceedings of the 15th European Conference on Information Systems (ECIS 2007), St Gallen, pp. 2173-84. Rainer, R.K., Snyderr, C.A. and Carr, H.H. (1991), “Risk analysis for information technology”, Journal of Management Information Systems, Vol. 8 No. 1, pp. 192-7. Rao, R., Tripathi, R. and Gupta, M.P. (2008), “issues of personal information integration in government-employee e-government”, Proceedings of the 2nd International Conference on Theory and Practice of Electronic Governance (ICEGOV2008), Cairo, December 1-4, ACM Press, New York, NY. Ray, D. (2007), Scientist, National Informatics Centre, India, personal interview, October 10. Santos, E.M.D. and Reinhard, N. (2007), “Setting interoperability standards for egovernment: an exploratory case study”, Electronic Government, An International Journal, Vol. 4 No. 4, pp. 379-94. Scholl, H.J. (2006), “What can e-commerce and e-government learn from each other?”, Proceedings of the 7th Annual International Conference On Digital Government Research, May 21-24, San Diego, CA, pp. 454-5. Scholl, H.J. and Klischewski, R. (2007), “E-government integration and interoperability: framing the research agenda”, International Journal of Public Administration, Vol. 30 No. 8, pp. 889-920. Singh, A.K. (2009), Director, Centre for Railway Information Systems, India, personal interview, February 28. Srivastava, A. (2009), IT Director, Madhya Pradesh, India, personal interview, April.

Srivastava, D., Dar, S., Jagadish, H.V. and Levy, A. (1996), “Answering queries with aggregation using views”, Proceedings of the 22nd International Conference on Very Large Data Bases (VLDB’96), September 3-6, Taj Mahal Hotel, Mumbai (Bombay), pp. 318-29.

Interoperability adoption

Straub, D.W. and Nance, W.D. (1990), “Discovering and disciplining computer abuse in organization: a field study”, MIS Quarterly, Vol. 14 No. 1, pp. 45-55. Strover, S. (2001), “Rural internet connectivity”, Telecommunications Policy, Vol. 25 No. 5, pp. 331-47. Traunmu¨ller, R. (2005), Cross-border and Pan-European Services: The Challenges Ahead, Institute for Informatics in Business and Government, available at: www.eisco2005.org/ fileadmin/files/eisco2005/ (accessed November 2006). Tripathi, R., Gupta, M.P. and Bhattacharya, J. (2011), “Identifying factors of integration for an interoperable government portal: a study in Indian context”, International Journal of Electronic Government Research, Vol. 7 No. 1, pp. 64-88. Verma, N. (2007), Senior Technical Director, National Informatics Centre, India, personal interview, August 8. Vernadat, F.B. (2010), “Technical, semantic and organizational issues of enterprise interoperability and networking”, Annual Reviews in Control, Vol. 34 No. 1, pp. 139-44. Victor, J. (2008), Joint Director (E-governance), Andhra Pradesh, India, personal interview, February 15. Virili, F. and Sorrentino, M. (2009), “Value generation in e-government from service-based IT integration”, Transforming Government: People, Process and Policy, Vol. 3 No. 3, pp. 227-47. Vogel, T., Schmidt, A., Lemm, A. and O¨sterle, H. (2008), “Service and document based interoperability for European ecustoms solutions”, Journal of Theoretical and Applied Electronic Commerce Research, Vol. 3 No. 3, pp. 17-38. Weng, S., Tsai, H., Liu, S. and Hsu, C. (2006), “Ontology construction for information classification”, Expert Systems with Applications, Vol. 31, pp. 1-12. Wittenburg, A., Matthes, F., Fischer, F. and Hallermeier, T. (2007), “Building an integrated IT governance platform at the BMW Group”, International Journal of Business Process Integration and Management, Vol. 2 No. 4, pp. 327-37.

Further reading EURIM (2002), “Interoperability – joined up government needs joined up systems”, EURIM (The European Information Society Group), Briefing No. 36, Modernizing Government Theme. Kamal, M.M. (2006), “IT innovation adoption in the government sector: identifying the critical success factors”, Journal of Enterprise Information Management, Vol. 19 No. 2, pp. 192-222. Landsbergen, D.J. and Wolken, G. Jr (2001), “Realizing the promise: government information systems and the fourth generation of information technology”, Public Administration Review, Vol. 61 No. 2, pp. 206-20. Mowbray, T.J. and Zahavi, R. (1995), The Essential CORBA: Systems Integration Using Distributed Objects, John Wiley & Sons, New York, NY. Thakur, J. (2009), Principal System Analyst, Indian Government Tenders, India, personal interview, March 5.

121

JEIM 25,2

Appendix A survey to study the issues of interoperability in developing one-stop portal URL of your portal: www.

122

Table AI. Portal centric

In your opinion how far has your organization’s portal been able to achieve the following dimensions for a one-stop portal: (Please tick U in appropriate column) Data integration (Scale: Not Aware, Not Initiated, Fully Implemented) An appropriate data centre is in place An architecture to combine all relevant data accessible through data A process for updating input of data Adoption of process for testing of compatibility of updated software versions Integration of the services delivery departments (systems) to the portal Ontology for effectively combining the data/information from multiple heterogeneous sources Mechanisms adopted for data security Adoption of open standards to reduce the risk of vendor lock-in and to guarantee data preservation Data replication implementation (automated real time data synchronization enabling locality of access for data access regardless of source implementation) Data transformation implementation (support data cleansing and metadata interchange through leveraging industry standards) Message Formatting Language implementation (format of data messages and business documents that can be exchanged between applications) Data Modeling usage [UML (Unified Modeling Language) to provide the conceptual design primarily for human interpretation] Resource Description Framework in place (representing metadata) [Interoperable character set standards to support the interchange, processing, and display of the written texts of the diverse languages and technical disciplines of the modern world] Process integration (Scale: Not Aware, Not Initiated, Fully Implemented) All the processes for the portal have been codified Processes have been formulated for connecting service delivery departments to the portal The processes are being upgraded regularly and new technology is being applied to do so Open standards are adopted for combining the processes The architecture for combining different processes has a middleware Adoption of standardized reusable software components and processes across departments Communication integration (Scale: Not Aware, Low, High) Level of Networking of the data centers of the services delivery departments Speed of connectivity (bandwidth, response time) Quality of services (delay and loss of packets) is being provided Deployment of web and internet technologies in the relevant departments of the Government Interoperability of the existing technologies Security measures for the main server(s) Adoption of Network Layer Security standards for implementing virtual private network (VPN) and secure remote access Intelligent design of supporting applications (to convert the contents to a format understandable by the multiple access devices/channel, e.g. mobile, etc. by users)

Corresponding author Rakhi Tripathi can be contacted at: [email protected]

To purchase reprints of this article please e-mail: [email protected] Or visit our web site for further details: www.emeraldinsight.com/reprints

The current issue and full text archive of this journal is available at www.emeraldinsight.com/1741-0398.htm

A process approach to distribution channel re-engineering Ales Groznik Faculty of Economics, University of Ljubljana, Ljubljana, Slovenia, and

Marinko Maslaric Faculty of Technical Sciences, University of Novi Sad, Novi Sad, Serbia

Distribution channel re-engineering 123 Received 18 November 2010 Revised 22 December 2010 Accepted 2 March 2011

Abstract Purpose – The aim of the paper is to propose a methodology for distribution network reengineering since for the last few decades there has been growing interest in making more integrated business decisions across larger segments of the logistics and distribution networks. Design/methodology/approach – In this paper, a methodology to assist distribution networks reengineering by integrating logistic processes within the distribution supply chain is developed. The emphasis of methodology is on business processes modeling and reengineering in distribution network. Findings – The results confirm that distribution network reengineering needs to be a balanced, methodological process that integrates business process reengineering in combination with information technology. Case study findings presented illustrate that the recommended methodology has resulted in considerable cost savings and enhancing effectiveness of distribution networks. Originality/value – The paper has extended reengineering theory and information technology into a supply chain context. Moreover, it is among the first empirical papers that specifically investigate the relationship between reengineering, information technology and distribution channel management practices; thus the paper fills an important gap in the supply chain literature. The case study provides important insights for both, academia and practitioners, to understand the importance of broader context of distribution channel management in order to better leverage reengineering context by exploiting information technology. Keywords Distribution process, Business process modeling, Reengineering, Logistics, Distribution management, Business process re-engineering Paper type Research paper

1. Introduction To succeed in the modern global economy, it is critical to build a logistic network that is information rich, highly flexible, cost effective, and defined by both customer needs and internal corporate strategy. Organizations must constantly reinvent logistic network to allow business growth and change. The nature of distribution process is changing from simply holding physical inventory towards a business model that relies on information and inventory linkages with customers and suppliers. Customer expectations now include both traditional activities associated with warehousing and distribution and new activities like technical support, electronic order processing, and customized financial services to name a few. Structural changes in distribution channels are currently taking place which are accelerating deliveries to customers

Journal of Enterprise Information Management Vol. 25 No. 2, 2012 pp. 123-135 q Emerald Group Publishing Limited 1741-0398 DOI 10.1108/17410391211204383

JEIM 25,2

124

(Gunasekaran et al., 2004) These new distribution channel structures, in which logistics management is typically centralized, have proven to be both extremely cost efficient and effective in improving customer services (Persson and Olhager, 2002). Modern information technology (IT) has been a necessary enabler of the move to more centralized distribution structures (Vaculik et al., 2009). High operational efficiency is dependent on quick, accurate, and continuous exchange of information between organizations and also between and within different functions within organizations. Rapid developments in IT have increased the availability of information, and also the opportunities to transfer information between different inter and intra-organizational units (Yang and Su, 2009). However, the simple use of IT applications to improve information transfers between supply chain members is not enough to realize the benefits of information sharing. A mere increase in information transfers does not mean that the efficiency of logistics processes will be improving. The business models of existing distribution processes have to be changed, so as to facilitate the better use of the information transferred (Trkman, 2010). Literature review shows that numerous papers were published describing reengineering methodologies mostly focusing on major phases of redesign (Adesola and Baines, 2005), (Harmon and Davenport, 2007), (Persson and Olhager, 2002), or exquisite detail (Castano et al., 1999), (Stefanovic et al., 2009), (Muffatto and Payaro, 2004). We find a significant lack of research on methodology of distribution channels renovation. The motivation of the research is to define a methodological frame that would allow academia and practitioners to restructure existing distribution channels. The aim of this article is to describe and explain the reengineering of distribution processes from traditional distribution to distribution, applying the logistic principles and involving the centralization of logistics activity in distribution networks through using proposed methodology. The core steps of the methodology are based on business processes modeling and simulation. An explanatory methodology framework is developed and applied to a company case study. In this paper through a case study, we observed the distribution network as a network of one distribution center, multiple retailers and customers. The distribution center’s task is to deliver goods to each retailer so that the customer demands are met to the most desirable levels possible. Proposed methodology assumed an integrated logistic decision making to assist the distribution center in performing their tasks. The next section briefly reviews basic principles about the distribution channel reengineering. Section 3 introduces the term of business process modeling. Section 4 defines the proposed methodology. Section 5 formulates the case study and outlines business process models for the current and proposed state for the distribution network under consideration, and details a simulation study. Section 6 discusses the results and concludes. 2. Applying distribution channel reengineering with business process modelling In reengineering theories, organizational hierarchies and the representation of organizations in terms of different functions are replaced with a process-oriented perspective. Organizational structures are redesigned, by focusing on business processes, and their outcome. According to (Persson, 1995) we can distinguish three different restructuring concepts: total quality management (TQM), time-based

management (TBM) and business process reengineering (BPR), and the most important contribution of these theories has been to extend a process orientation into a strategy paradigm. The process-oriented design for the logistics and distribution systems is based on efficient use of IT (Groznik and Trkman, 2006). Information sharing between members of a distribution supply chain using new IT should be increased to reduce uncertainty and improve the logistic performances. However, companies need to invest large amount of money for redesigning internal organizational and technical processes, changing traditional and fundamental product distribution channels and customer service procedure to achieve IT-enabled supply chain. The main problem when developing an innovative IT-integrated distribution systems is lack of integration between IT and business model (Andersen and Rask, 2003), (Skerlavaj et al., 2010). Hence, formation of a business model is crucial for full utilization of improved information system. Information should be readily available to all companies in distribution channel, and the business processes should be structured, so as to allow the full use of this information. The objective of this paper is to offer insights into distribution channel reengineering using business process modeling and simulation. Business process reengineering is enabled by business process modelling. A business process model is an abstraction of a business that shows how business components are related to each other and how they operate. Its ultimate purpose is to provide a clear picture of the company’s current state and to determine its vision for the future. Modelling a complex business requires the application of multiple views. Each view is a simplified description (an abstraction) of a business from a particular perspective or vantage point, covering particular concerns and omitting entities not relevant to this perspective. To describe a specific business view process mapping is used. It consists of tools that enable us to document, analyze, improve, streamline, and redesign the way the company performs its work. Process mapping provides a critical assessment of what really happens inside a given company (Cull and Eldabi, 2010). The usual goal is to define two process states: AS-IS and TO-BE. The AS-IS state defines how a company’s work is currently being performed. The TO-BE state defines the optimal performance level of AS-IS. In other words, to streamline the existing process and remove all rework, delays, bottlenecks and assignable causes of variation, there is a need to achieve the TO-BE state. Business process modelling and the evaluation of different alternative scenarios (TO-BE models) for improvement by simulation are usually the driving factors of the business renovation process (Bosilj-Vuksic et al., 2002). Business process modeling complexity increases with the number of companies being modeled as shown by Albani and Dietz (Albani and Dietz, 2009). Therefore, we decided to propose a methodology that would integrate distribution channel reengeniring and business process modelling. .

3. The distribution channel reengineering methodology The methodology presented in this section is the outcome of an iterative process from theory, practice, and case studies. There have been a number of papers published describing reengineering methodologies (Adesola and Baines, 2005), (Castano et al., 1999), (Fuente et al., 2010), (Harmon and Davenport, 2007), (Stefanovic et al., 2009). Most focus on major phases of redesign (Adesola and Baines, 2005), (Chuah et al., 2010), (Harmon and Davenport, 2007), (Persson and Olhager, 2002), others go into exquisite

Distribution channel re-engineering 125

JEIM 25,2

126

Figure 1. The proposed methodology for distribution channel reengineering

detail (Castano et al., 1999), (Stefanovic et al., 2009), (Muffatto and Payaro, 2004). Our goal was to propose a methodology that would represent a comprehensive tool for both academia and practitioners to apply it to distribution channel reengineering in order to increase the successful rate of reengineering project. The proposed methodology is a generic six-step approach that guides the actions to assists business process reengineering in logistic/distribution networks. It is a guide, not a procedure or manual. The structure for the methodology is shown in Figure 1. An outline of the content of the proposed methodology is given in the following. . Understanding business needs, goals and objectives: The first step on the road to a reengineering distribution system is to assemble a team of strategic decision makers and influences from a variety of corporate levels. Not only is it important to fostering a universal sense of ownership in the process by these key personnel, but these people will also source the needed data on past and current operations, as well as about future corporate plans. . Collecting relevant data and understanding the business process. Once the goals of the distribution channel reengineering process have been defined, it should be fairly clear what types of data need to be collected for analysis. Also, we need to identify the business process architecture. . Establishing base case. Now that all the date has been collected and process has been defined, it is time to use that information to create an AS-IS model of current distribution channel operations, called a base case. The base case will be used as

.

.

.

a standard against which potential future-state operating scenarios will be compared. Redesign process-analyzing and evaluating potential future-state scenarios. Once the AS-IS model is established, it is time to time to build TO-BE models as potential scenarios of future conditions and compare them with current reality. To do this it is important to first establish and prioritize which variables will present key factors in the analysis. These variables could be inventory costs, transportation costs, required service levels, ordering costs, labor availability etc. Selecting optimal future-state. After all it is time to assess the various future-state scenarios which is developed by manipulating the data that established base case. For this we use simulation. After business process model simulation we compare these options and chose the model that best supports organization’s strategic plans related with distribution process. Review new process. At the end we need to develop strategic view of the new business process, set process targets and performances, and to develop plan to meet targets. Lack of performance measures significantly affects management in a supply chain environment (Sambasivan et al., 2009).

4. Distribution channel reengineering: a case study From the distribution point of view, the oil industry is a specific business, and for many reasons it is still generally based on the traditional model. The product is manufactured, marketed, sold and distributed to customers. In other industries, advanced logistic and distribution operations is becoming increasingly driven by demand-pull requirements from the customer. There is strong vertically integrated nature of oil companies and that may be a potential advantage. In other industries, much attention is focused on value chain integration across multiple manufacturers, suppliers, and customers. In the oil industry, more links in the logistic chain are “in house”, suggesting simpler integration. In practice, there is still a long way to go to achieve full integration of logistic processes in the oil distribution chain. A case study has been used as a research method to underline the theoretical findings set out in previous sections, i.e. to show how the distribution channel reengineering can be adopted with business process modelling. In addition, the purpose of the case study is to show how the benefits of the distribution channel reengineering can be assessed by using the proposed combination of business process modelling and simulation. The case study is used extensively as a research strategy in practice-oriented fields such as management (Yin, 2003). The presented research is only partly of an exploratory nature in researching the possibility of assessing distribution channel renovation and integration benefits. Still, the case study is an appropriate research method as the research questions are of the “how” type in their substance. This type of research questions is likely to lead to the use of case studies, histories, and experiments as the preferred research strategies (Yin, 2003). The case study presented in this paper deals with the fulfilment/procurement process in an SC that contains a petrol company (with multiple petrol stations at different locations) and a supplier which transports the petrol to the petrol stations from a few large warehouses.

Distribution channel re-engineering 127

JEIM 25,2

128

The business process modelling, and renovation project was initiated by the Serbian petrol company in order to reduce operating costs, shorten lead times, and improve stock management. The project started with the formation of a project group, consisting of members of the petrol company, the transport company, and consultants. The researchers were in the role of consultants. The first step of the project was a workshop for the project group in which the members were acquainted with the project goals and methodology. After the workshop, key business process groups were identified by discussion and brainstorming. One of the most crucial processes was the procurement process. The processes were modelled by interviewing people from the companies, which perform the activities. During the interviews, consultants were able to collect the data and prepare the business processes models. Since the models reflect business operations, key personnel from both companies were involved, and the final version of the AS-IS models was validated, by the relevant managers of both companies. Then, the consultants analysed the key business processes on the basis of their models. The results of the analyses became the starting-point for the renovation of the business processes. Apart from business process data, we also used industry-specific data (e.g. oil prices, tank volumes), which is available from the literature (Trkman et al., 2007). According to collected data, organizational model, developed process objectives, identified business process architecture we could develop the model of the current distribution process. The objective of the step 3 (see Figure 1) was to map out in a structured way the distribution processes of the observed petrol company. The modelling tool used in this case study was iGrafx Process. The AS-IS model was initially designed so that the personnel involved in the distribution processes could review them, and after that the final model shown in Figure 2 was developed. The core objective of distribution chains is to deliver the right product at the right time, at the right price and safely. In a highly competitive market, each aims to carry this out more effectively, more efficiently and more profitably than the competitors. Because both the prices and quality of petrol in Europe are regulated, the main quality indicator in petrol distribution is the number of stock-outs. The main cost drivers are therefore: number of stock-outs, stock level at the petrol station and process execution costs. Lead-time is defined as the time between the start (measurement of the stock level) and the end (either the arrival at a petrol station or the decision not to place an order) of the process. The main problems identified when analyzing the AS-IS model relate to the company’s performance according to local optimization instead of global optimization. The silo mentality is identified as prime constraint in the observed case study. Other problems are in inefficient and costly information transfer mainly due to the application of poor IT. There is no optimization of the performance of the distribution chain as a whole. Purchasing, transport and shipping are all run by people managing local, individual operations. They have targets, incentives, and local operational pressures. Everything was being done at the level of the functional silo despite the definition that local optimization leads to global deterioration. Based on the mentioned problems, some improvements were proposed. The main changes lied in improved integration of whole parts of the distribution channel and centralized distribution process management.

Distribution channel re-engineering 129

Figure 2. AS-IS model of the process

The emphasis in business process reengineering is put on changing how information transfers are achieved. A necessary, but no means sufficient condition for this is to implement new IT, which enable efficient and cost effective information transfers. Hence, IT support is not enough as deep structural and organizational changes are needed to fully realize the potential benefits of applying new IT. In this case study we develop two different propositions for business process reengineering (two TO-BE models) to show how the implementation of new IT without business process renovation and the related organizational changes does not mean the full optimization of distribution network performances. The first renewed business model (TO-BE 1) is

JEIM 25,2

130

shown in Figure 3 and represents the case of implementing IT without structural changes to distribution processes. In the TO-BE 1 model, there is no integrated and coordinated activity through the distribution channel. Inventory management at the petrol stations and distribution centre is still not coordinated. The TO-BE 2 model assumes that the processes in the whole distribution channel are full integrated and the distribution centre takes responsibility for the whole procurement process. The TO-BE 2 business model is shown in Figure 4. The main idea is that a new organizational unit within the distribution centre takes on a strategic role in coordinating inventory management and in providing a sufficient inventory level at the petrol stations and distribution centre to fulfill the demand of the end customer. It takes all the important decisions regarding orders in order to realize this goal. Other changes proposed in the TO-BE 2 model are the automatic measurement of petrol levels at petrol stations and the automatic transfer such data to the central unit responsible for petrol replenishment; the predicting of future demand by using progressive tools; and using operations research methods to optimize the transportation paths and times. The role of IT in all of these suggestions is crucial. 5. Discussion Using iGrafx Process, we simulated business process to investigate the impact of business process reengineering on the defined distribution performances: lead times and transactional costs. iGrafx Process uses discrete event simulation to estimate the consequence of possible experiments. For estimating changes in process execution costs and lead times, a three-month simulation of the AS-IS and both TO-BE models was run. In the AS-IS model a new transaction is generated daily (the level of petrol is checked once a day); in the TO-BE it is generated on an hourly basis (the level of stock is checked automatically every hour). The convincing results are summarized in Table I. The label “Yes” refers to those transactions that lead to the order and delivery of petrol, while the label “No” means a transaction where an order was not made since the petrol level was sufficient. The comparison of simulation results (see Table I) show that proposed changes (TO-BE 1 and TO-BE 2) significantly lower the transactional costs as well as average lead times. There is also significant distinction between proposed TO-BE 1 and TO-BE 2 models in regards to transactional costs and average lead times. Implementation of IT without structural changes to distribution processes (TO-BE 1) merely changes the transactional costs and average lead times. These results support our view that mere IT implementation does not bring business outcome, since the implementation alone does not significantly affects costs and lead times. In order to foster business value out of IT implementation, company has to apply distribution channel reengineering with business process modeling. The comparison of our AS-IS and TO-BE 2 model show the average process costs are reduced by almost 50 per cent (Yes (AS-IS) vs Yes (TO-BE 2)), while the average lead times are cut by 62 per cent (Yes (AS-IS) vs Yes (TO-BE 2)). From this it is clear that this renovation project is justifiable from the cost and time perspectives. Furthermore, using case study we clarified that companies reengineering their distribution networks have to adopt systematical approach in order to streamline their processes. The significance of our paper is that it not only clarifies that mere IT implementation will not result in an expected business change, but also provides methodology that systematically assists in distribution network reengineering. The

Distribution channel re-engineering 131

Figure 3. TO-BE 1 model of the process

JEIM 25,2

132

Figure 4. TO-BE 2 model of the process

results in Table I show that a full improvement in logistic performances is only possible in the case of implementing both IT, which enables efficient information sharing and the redesign of business processes. The mere implementing of IT without structural and organizational changes in business processes would not contribute to realizing the full benefit. Changes described in the TO-BE 2 model, have later been adopted, by the petrol company. The validity of the model was tested by ex-post comparison of simulated and real business operations data. The comparison validated the TO-BE 2 model since the data from operations fit simulations. The validation also supports the methodology of distribution network reengineering. Continuous monitoring and improving of the business model is necessary. The visibility of the process in the whole chain and the ability to estimate further changes with a developed methodology will serve as an important enabler of a continuous improvement.

Distribution channel re-engineering 133

6. Conclusions In the paper, we presented a methodology for distribution network reengineering. The goal was to overcome numerous reengineering methodologies that focus either on major phases of redesign or are too detailed. The presented methodology represents a comprehensive tool for both academia and practitioners to apply it to distribution channel reengineering in order to increase the successful rate of reengineering project. The methodology has been tested on a petrol distribution company in order to explore the effect of information sharing with regard to the performance. The business process reengineering in distribution channel, realized through proposed methodology, described in this paper helped achieve significant savings for the case study company by improving effectiveness in distribution network. The conclusions of the simulation experiments are significant savings in cost and time measures. The validity of the model in the case study was tested, by comparing the AS-IS and TO-BE 2 model and simulations to the actual state in the company. Results of the comparison validated the model. The presented case study shows the applicability of the proposed methodology; however further case studies have to be done in the future to prove the validity. The study also has some limitations. In the case study, initiator and the business driver of distribution channel reengineering was the petrol company. The petrol company influenced the importance of the change with their supply chain position power. That limitation is closely related to social, human related issues. Presented changes in the distribution channel significantly twist the focus employees have to follow. Instead of local, company optima, employees have to seek solutions on overall supply chain levels. Companies forming the supply chain have to transform their Transaction

No.

Av. lead time (hrs)

Av. work (hrs)

Av. wait (hrs)

Average costs (e)

Yes (AS-IS) No (AS-IS) Yes (TO-BE 1) No (TO-BE 1) Yes (TO-BE 2) No (TO-BE 2)

46 17 46 1489 46 1489

33.60 8.43 27.22 0.00 12.85 0.00

11.67 2.40 10.26 0.00 4.88 0.00

21.93 6.03 16.96 0.00 7.98 0.00

60.10 8.47 56.74 0.00 32.54 0.00

Table I. Comparison of simulation results for the AS-IS and TO-BE models

JEIM 25,2

134

organisational cultures and leadership styles in order to support the overall supply chain benefits. The proposed approach is applicable to a wide range of supply chains in different industries, regardless of the number of organisations participating. The methodology can be applied to multi-tier supply chains with no major changes. The proposed methodology encompasses six generic steps that bring any supply chain into distribution channel reengineering. Nevertheless, we should be aware that from the business point of view one time application of the methodology would not yield optimum results. Continuous monitoring and improving of the business model is necessary, meaning that the proposed methodology should become the panacea of distribution channel reengineering. Future research will focus on incorporating the proposed methodology for distribution network reengineering into broader change management perspective. This would involve the assurance that the methodology would be applicable as a change management tool. Currently, the proposed methodology focuses on costs and lead times. The methodology should be extended into stock level and resource optimisation. References Adesola, S. and Baines, T. (2005), “Developing and evaluating a methodology for business process improvement”, Business Process Management Journal, Vol. 11 No. 1, pp. 37-46. Albani, A. and Dietz, J.L.G. (2009), “Current trends in modelling inter-organizational cooperation”, Journal of Enterprise Information, Vol. 22 No. 3, pp. 275-86. Andersen, P.H. and Rask, M. (2003), “Supply chain management: new organisational practices for changing procurement realities”, Journal of Purchasing and Supply Management, Vol. 9 No. 2, pp. 83-95. Bosilj-Vuksic, V., Indihar-Stemberger, M., Jaklic, J. and Kovacic, A. (2002), “Assessment of e-business transformation using simulation modeling”, Simulation, Vol. 78 No. 12, pp. 731-44. Castano, S., Antonellis, V.D. and Melchiori, M. (1999), “A methodology and tool environment for process analysis and reengineering”, Data & Knowledge Engineering, Vol. 31 No. 3, pp. 253-78. Chuah, P., Wong, W.P., Ramayah, T. and Jantan, M. (2010), “Organizational context, supplier management practices and supplier performance: a case study of a multinational company in Malaysia”, Journal of Enterprise Information, Vol. 23 No. 6, pp. 724-36. Cull, R. and Eldabi, T. (2010), “A hybrid approach to workflow modelling”, Journal of Enterprise Information, Vol. 23 No. 3, pp. 268-78. Fuente, M.V., Ros, L. and Ortiz, A. (2010), “Enterprise modelling methodology for forward and reverse supply chain flows integration”, Computers in Industry, Vol. 61 No. 7, pp. 702-10. Groznik, A. and Trkman, P. (2006), “Business renovation towards successful supply chain management in oil industry”, E-commerce 2006: Proceedings of the IADIS International Conference, Porto, December 9-11, International Association for Development of the Information Society, Porto, pp. 230-7. Gunasekaran, A., Patel, C. and McGaughey, R. (2004), “A framework for supply chain performance measurement”, International Journal of Production Economics, Vol. 87 No. 3, pp. 333-47. Harmon, P. and Davenport, T. (2007), “The BPTrends process redesign methodology”, Business Process Change, pp. 353-83.

Muffatto, M. and Payaro, A. (2004), “Integration of web-based procurement and fulfillment: a comparison of case studies”, International Journal of Information Management, Vol. 24 No. 4, pp. 295-311. Persson, G. (1995), “Logistics process redesign: some useful insights”, International Journal of Logistics Management, Vol. 6, pp. 13-25. Persson, F. and Olhager, J. (2002), “Performance simulation of supply chain designs”, International Journal of Production Economics, Vol. 77 No. 3, pp. 231-45. Sambasivan, M., Nandan, T. and Mohamed, Z.A. (2009), “Consolidation of performance measures in a supply chain environment”, Journal of Enterprise Information, Vol. 22 No. 6, pp. 660-70. Skerlavaj, M., Song, J.H. and Lee, Y. (2010), “Organizational learning culture, innovative culture and innovations in South Korean firms”, Expert Systems with Applications, Vol. 37 No. 9, pp. 6390-403. Stefanovic, D., Stefanovic, N. and Radenkovic, B. (2009), “Supply network modelling and simulation methodology”, Simulation Modelling Practice and Theory, Vol. 17 No. 4, pp. 743-66. Trkman, P. (2010), “The critical success factors of business process management”, International Journal of Information Management, Vol. 30 No. 2, pp. 125-34. Trkman, P., Stemberger, M.I., Jaklic, J. and Groznik, A. (2007), “Process approach to supply chain integration”, Supply Chain Management: An International Journal, Vol. 12 No. 2, pp. 116-28. Vaculik, J., Michalek, I. and Kolarovszki, P. (2009), “Principles of selection, implementation and utilization of RFID in supply chain management”, Promet-Traffic&TransportationScientific Journal on Traffic and Transportation Research, Vol. 21, pp. 41-8. Yang, C. and Su, Y. (2009), “The relationship between benefits of ERP systems implementation and its impacts on firm performance of SCM”, Journal of Enterprise Information Management, Vol. 22 No. 6, pp. 722-52. Yin, R.K. (2003), Case Study Research: Design and Methods, 3rd ed., Sage Publications, Thousand Oaks, CA, London and New Delhi. Corresponding author Ales Groznik can be contacted at: [email protected]

To purchase reprints of this article please e-mail: [email protected] Or visit our web site for further details: www.emeraldinsight.com/reprints

Distribution channel re-engineering 135

The current issue and full text archive of this journal is available at www.emeraldinsight.com/1741-0398.htm

JEIM 25,2

The intellectual structure of the supply chain management discipline

136

A citation and social network analysis

Received 3 February 2011 Revised 24 March 2011 26 April 2011 Accepted 25 May 2011

Mihalis Giannakis Warwick Business School, University of Warwick, Coventry, UK Abstract Purpose – This paper aims to explore the way that the intellectual structure of the SCM discipline has been shaped over the last 20 years. The discipline is represented by the papers that are published in a network of ten leading academic journals in the field. As the SCM literature has grown, the analysis of the way that the characteristics of this network of journals have changed over time enables the identification of salient challenges facing SCM theory and practice for the new decade. Design/methodology/approach – A combination of social network and citation analyses among the selected journals is applied. Citations between and within journals are collected and analysed using social network analysis metrics, that assess the communication patterns between and among the journals, the cohesion of the network and the role that each of the journals has performed (and is acquiring) in the dissemination of knowledge. Findings – The analysis reveals that the current structure of the network of journals is characterised by an evident shift of focus of operations management journals towards more SCM phenomena, the cohesion of the discipline has improved but is still fragmented due to a lack of reciprocal co-citations among the journals, and the emergence of three distinctive clusters in the network. Research limitations/implications – The study reflects the growth of supply chain management, by studying an eclectic number of academic journals over the past 20 years, but can be extended beyond this period and it can include more academic and practitioner journals to examine its extended problem domain. Practical implications – The study confirms the inter-disciplinary nature of supply chain phenomena and the opportunity for research in SCM to acquire a central role in the study of inter-organisational systems. Originality/value – Bibliographic studies have been conducted in the past in several (more established) disciplines. The study of where knowledge is communicated with co-citations among papers and journals provides concrete evidence of the changing characteristics of an academic discipline. The SCM discipline is maturing as an academic discipline and the analysis of its intellectual structure can assist in establishing its legitimacy and future expansion. Keywords Supply chain management, Social network analysis, Citation analysis, Bibliometric study, Journals Paper type Research paper

Journal of Enterprise Information Management Vol. 25 No. 2, 2012 pp. 136-169 q Emerald Group Publishing Limited 1741-0398 DOI 10.1108/17410391211204392

Introduction Academic disciplines in social sciences emerge because there is the need to satisfy the demand for new knowledge that is necessary to explain phenomena created by the ever-changing political, demographic, economic and technological conditions and because individuals and organisations are interested in funding and doing research to

explain these phenomena (Berry and Parasuraman, 1993; Heineke and Davis, 2007). Collaborations and networks then develop in conferences and through published works in journals and the field gradually takes shape. As an academic field Supply Chain Management (SCM) evolved from the Operations Management Discipline (Harland, 1996). Supply chains always existed in industries, but the term SCM has been introduced in 1980s as a consulting solution to logistics management and its growth in business circles as a new competitive way of forming companies’ strategy and in academia as a new field of study has been reported extensively. This growth was a natural evolution which occurred to fill the academic gap of the externalisation of Operations Management, which was driven by the rapid changes in Information Technology that enabled more effective communication between business and the new competitive globalised environment created by economic, demographic and political developments that brought about the emergence of new forms of inter-organisational relationships (alliances, partnerships) (Giannakis and Croom, 2004). The nature of SCM research has been examined by several scholars (See for example, Harland, 1996; Cooper et al., 1997; Fine, 2000; Croom et al., 2000; Tan, 2001; Chen and Paulraj, 2004; Lawson et al., 2006). It has been described as a multivariate discipline encompassing a large number of different literatures and research areas, spanning from Operations Management, Strategy and Marketing to Sociology and Geography (Giannakis and Croom, 2004), but has been criticised that it lacks clear theoretical and conceptual schema which define its boundaries (Chen and Paulraj, 2004), and that it overlaps with other competing disciplines like Operational Research and Marketing (Ganeshan et al., 1999; Lummus and Vokura, 1999; Lambert and Cooper, 2000; Croom et al., 2000). The SCM field has been expanded over the past 30 years and continues to grow. Many pioneering scholars are still conducting research in the field and an increasing number of UG and PG programmes in SCM are developed and offered in universities around the world. There is a substantial growth of papers that refer to supply chain management phenomena or include the term supply chain in their title. Earlier works (Tan, 2001, Miles and Snow, 2007) examined the stages through which the SCM literature developed by analysing the different contributions to the development of SCM thought. Each of these contributions introduced a new feature to the totality of SCM thought. The research presented in this paper investigates the way in which the academic field of SCM has evolved over time, not through an extensive critical analysis of the literature, but by analysing a network of eminent journals of the discipline. In order to better understand the changing characteristics of the SCM discipline, the citations that are exchanged between and among these journals are analysed. These citations represent the communication patterns between researchers and facilitate the dissemination of ideas between and within journals. By studying and analysing how knowledge has been disseminated in the SCM literature, useful insights will be generated regarding the theory and practice of SCM, the identification of its problem domain and its inter-disciplinary nature as well as helping researchers to identify emerging themes. Traditionally, this can be done through an examination of a large number of contemporary literatures. The bibliometric study that this paper adopts does not analyse the pertinent literature of

Intellectual structure of the SCM discipline 137

JEIM 25,2

138

SCM per se, but the way journals exchange knowledge (in the form of citations). This approach can also provide a clear picture of how the academic field of SCM has evolved but it also gives the opportunity to identify the role that each journal performs and how various streams of research can be combined to face future challenges of SCM phenomena. The study also gives the opportunity to identify the linkages of SCM with other disciplines to investigate if the existence of SCM fulfils a purpose, or performs a role for academics and practitioners. In this direction this paper addresses the following research objectives: RO1. To identify a network of journals that can represent effectively the academic network of SCM discipline. RO2. To collect the number of citations that appear in the published articles of these journals over a period of 20 years. RO3. To identify the connections between journals, and identify the role that they play in the creation and dissemination of knowledge. RO4. To identify how the field has changed over the past 20 years through the role of the journals in the network and point out agendas for future research in SCM. The remainder of the paper is organised in five sections: In the first section, the two research methods that are utilised in this research (citation analysis and social network analysis) are introduced. The analytical steps that have been followed for the selection of the journals to be studied and the data collection procedure are outlined in the second section. The findings of the analysis are presented in the third section and a critical examination of the results in the fourth section. Finally in the last section potential extension of the research in the interested field is discussed. Citation and social network analyses Citation analysis Published work in academic journals plays a critical role in the way that an academic discipline evolves. In their research, social scientists induce ideas by observing phenomena and also by reading articles that they find interesting and aid them in their thinking, which they cite in their work as an acknowledgement of debt to prior research. The knowledge that they then generate by applying those ideas in particular contexts with the use of analytical methods and established theories, is disseminated through the published works to other researchers from the same or different disciplines and more importantly to practitioners that use this it in their business practices. The analysis of connections between and within journals (i.e. the citations) can be seen therefore as a concrete evidence of where knowledge is generated and used (Garfield, 1979). A citation is defined as ‘when one document (A) mentions or refers to another document (B), known as the source document. Citation Analysis has been used extensively to investigate the structure of many social sciences disciplines and natural sciences (Garfield, 1979). It may provide information on the identity of journals which make and receive citations (“directional” data) as well as information on the total number citations those journals make or receive (“valued” or “strength” data). At a micro level analysis it could provide greater information about the citations made and

received from journals, authors, books, etc. The unit of analysis is the citations or references “any source like a journal article, a book, a working paper, or an unpublished dissertation, listed by the authors of the papers analysed” (Garfield, 1979). Social network analysis The flows of communication and exchanges of ideas through citations can be further understood by complimenting the citation analysis with the Social Network Analysis (SNA) technique. A Social Network consists of a finite set of social actors and the relations defined on them (Wasserman and Faust, 1994). SNA is a method that investigates the relationships between the social actors through analysis of the structure of the social network, with the use of relational data (Scott, 2006). These are the contacts, ties, or information that is exchanged between actors, which relate one actor to another. The measures of the relationships could include influence, affinity, patterns of communication, or the cohesion between the actors (Wasserman and Faust, 1994). With this technique a network of actors is defined as individuals within an organisation, organisations within a supply chain, or in the case of a citation analysis, the academic journals within a scholarly discipline. In the case of the network of academic journals, SNA could be utilised to better understand the relationships between and among its actors ( journals), by studying the information that is exchanged between and among the members (citation data) and provide insights into how knowledge is spread throughout the academic community. The Citation Analysis can be therefore combined with the SNA in order to understand the characteristics of the network, by describing how communication patterns between and among journals have shaped it. With the combination of SNA and citation analysis information can be drawn on how SCM as an academic discipline has evolved over the past 20 years, to what extent it reached maturity and how its future will be shaped by the generation of new knowledge through the interaction of the members of its intellectual network (journals). Research design and data collection Journal selection The goal of the study is to include journals that are important in the broad field of SCM. For that reason a “positional approach” in the use of the SNA was followed. A large number of journals that have extensively published works related to SCM were identified first. Previous works that investigated the SCM problem domain were visited (Philips and Philips, 1998; Carter et al., 2007) and the journals that they included in their study were added to those that were found in extensive literature reviews (Croom et al., 2000, Tan, 2001). An initial list of 35 journals was produced which arguably covers a thorough (but not exhaustive) spectrum of the SCM field. Global databases of academic and practitioner journals like ABI/INFORM, Business Source Premier and EBSCO were also consulted in order to select the journals. Table I outlines the initial selection of the journals that are considered to be relevant to SCM. The final selection of the journals that were included in the analysis was made after a filtering of four steps. (1) The journals that do not use refereed publications were not included. (2) The journals that refer solely to practitioners were not included.

Intellectual structure of the SCM discipline 139

JEIM 25,2

140

Table I. Initial selection of Journals

Primary SCM and OM Journals

General management journals

Journal of Supply Chain Management Supply Chain Management: An International Journal Journal of Operations Management International Journal of Operations and Production Management Journal of Purchasing and Supply Management International Journal of Logistics Management Journal of Business Logistics International Journal of Physical Distribution and Logistics Management Journal of Enterprise Information Management Transportation Research Part E (Logistics and Transportation Review) Production and Operations Management Logistics Focus (not refereed) Production and Inventory Management Journal International Journal of Production Research Journal of Purchasing (practitioner) Purchasing (practitioner) Purchasing and Supply Management (practitioner) International Journal of Production Economics Supply Chain Management Review (practitioner) Supply Management (practitioner) Transportation and Distribution (specialises in transportation only)

Academy of Management Journal Academy of Management Review Strategic Management Journal California Management Review Decision Sciences European Journal of Marketing Harvard Business Review Management Science Industrial Marketing Management Journal of Operational Research Society Journal of Marketing Research Journal of Marketing Journal of the Academy of Marketing Science British Journal of Management Sloan Management Review European Journal of Operational Research

(3) Journals that appear on the Association of Business Schools Journal Quality Guide of 2010 were included (Harvey et al., 2010) (4) Only the journals that specialise in SCM phenomena were included. This process enabled a thorough investigation of the expanding SCM problem domain. For the purposes of conducting a reliable analysis and to avoid bias in the collected data, which could have probably skewed the results, the study focused on those journals that have clear theoretical orientation towards SCM issues. Journals that stem from the Operational Research Discipline were excluded (i.e. The Journal of Operational Research Society, European Journal of Operational Research) as well as journals that have fragmentally published papers in SCM, or a few issues related to SCM (i.e. the International Journal of Production Economics, International Journal of Production Research and Industrial Marketing Management), despite the fact that they may be important actors in generating and disseminating knowledge in their field. After the filtering process the journals that were selected are outlined in Table II. It is always very difficult to draw the boundaries of a social network, as this entails the problem of leaving out actors/journals that could influence its behaviour. The main objective of this paper however is to see how the SCM discipline has evolved over time and not to compile a normative and comprehensive list of journals that define its boundaries. These boundaries have changed (and are likely to change) and the inclusion of all the journals that are currently publishing papers related to SCM would

Journal Name

Abbreviation

ABS Rank

Journal of Supply Chain Management Journal of Purchasing and Supply Management Supply Chain Management: An International Journal Journal of Operations Management International Journal of Operations and Production Management International Journal of Logistics Management Journal of Business Logistics International Journal of Physical Distribution and Logistics Management Journal of Enterprise Information Management Transportation Research, Part E: Logistics and Transportation Review

JSCM JPSM SCMIJ JOM IJOPM

1 2 3 4 3

IJLM JBL IJPDLM

2 2 2

JEIM LTR

1 3

not satisfy the main objective of the study. The selected journals are well known and established academic journals in the field of SCM. Data collection The main sources of collecting citation data are the Social Science Citation Index and the Journal Citation Reports that come out every year, as well as an online database, Google scholar (http://scholar.google.com). These sources however do not cover some of the journals under investigation, mainly because they are comparatively new and/or have been criticised of having limitations and reliability problems (Reed, 1995). Google scholar has also been criticised for errors that include missing data and discrepancies between citing and cited data (Falagas et al., 2008). For these reasons citations were collected manually from the journals themselves. All the citations that have been used in all the papers that have been published in the journals of the selected network were collected (using online bibliographic databases such as Business Source Premier, Proquest and Science Direct). Then the number of citations in each of the ten journals was manually counted and the number of times each journal cited the others and itself was calculated. For example, the number of times that papers which were published in a particular journal appear as citations in papers that were published in another journal was calculated. The collected citation data were then used to construct directional valued 10 £ 10 matrices, to investigate the relationship between journals through the calculation of specific SNA metrics. Matrices construction Matrices were constructed for each of the last 20 years 1991-2010 (see Table AI, Appendix 1). The figures in the matrices represent the number of times each journal cited the other journals, as well as the total annual number of citations within each journal. These yearly matrices were then summed up to create four five-year period matrices (1991-1995, 1996-2000, 2001-2004, 2006-2010) and then summed up again to create two ten-year period matrices (1991-2000 and 2001-2010). These combined matrices were used to smooth out any variances in a year, representing thus a better picture of sending and receiving citations between journals. They also facilitated the

Intellectual structure of the SCM discipline 141

Table II. Network of academic journals studied

JEIM 25,2

142

comparison between the periods in terms of the structural characteristics of the network. Some journals had a lot more citations than others because they publish more papers, or because their authors use more citations (e.g. the JOM compared to LTR). The data in these highly citing (and cited) Journals would overwhelm other data in the matrices and skew the relational characteristics of the network. A technique that is used to control this potential source of error is to normalise the data. For that purpose, the rows of the matrices were normalised to account for that fact. Row normalisation refers to changing the scale of numbers in the matrix when we wish the data matrix to have the same mean or standard deviation (Borgatti et al., 2002; Scott, 2006). An eleventh column was added to each matrix including the sums of all the citations made by the network of the ten journals. The rows of the matrices were subsequently normalised using marginal normalisation (Borgatti et al., 2002). By forcing the sum of the elements to be 100, the cell entries were linked to percentages of citations given or received, instead of the actual number of citations. All the analyses for the calculation of the relational indicators between the journals and the characteristics of the network were performed using the normalised 10 £ 10 matrices, leaving the eleventh column out. This procedure resulted to the normalised matrices presented in Appendix 1. The matrices were analysed using the software UCINET 6.2 that handles relational data (Borgatti et al., 2002). Data analysis Social network analysis indicators The analysis of the matrices focused on three areas: the identification of the relationships between the selected journals, the formation of groupings or cliques among journals, the position of each journal in the network and the structure of the network. It also explored how these have changed over the past 20 years. The relationships between the journals of the network, and the role that each journal plays in the network, have been identified by assessing, and analysing several SNA metrics. These metrics include the number of self-citations (the number of citations provided in a paper of one journal to other documents published by the same journal), the level of centrality of each journal (the level to which a particular journal receives citations from other journals), the level of betweenness (the degree to which a particular journal cites many journals and not just a few), and the level of closeness (how close is one journal to another through reciprocal co-citations as well as how close is a journal to all the other journals in the network). For the identification of groupings/cliques in the network analysis, a hierarchical clustering analysis has been conducted to show how groupings of particular journals have formed over the 20-year period. The way that the intellectual field of SCM field evolved has been identified by conducting a multi-dimensional scaling analysis to map how the position of each journal in the network has changed over the past 20 years, and using hierarchical clustering to illustrate how relationships between journals have changed. In addition, the SNA measure of structural equivalence has been used to identify the position of a journal in the network. The structure of the network has been identified through the assessment of the cohesion of the network (how dense is the network by looking at the degree of citations

made by the journals of the network to each other and not to other academic journals) and the position of each journal (the level of similarity between journals). The results of the analysis in terms of the social network analysis indicators that have been used are discussed in the following. Descriptive analysis A correlation between the normalised matrices of the periods 1991-2000 and 2001-2010 was conducted first to reveal if any major differences took place in the network over the past 20 years. The overall correlation between the two matrices was 0.79, indicating that the overall citation network has been rather stable. Further, more refined analysis of differences between the periods, using the measures of centrality, betweenness, the position in the network and the cohesion of the network can reveal particular changes that have taken place. Roles and relationships between journals Self-citations The use of self-citations by a journal implies that the journal is independent and does not exchange knowledge with the rest of the network. As it is illustrated in Appendix 1, the journals with the highest percentage of self-citations for the entire 20-year period are the JOM and IJOPM, followed by the JSCM and IJPDLM. As expected, newer journals such as the JPSM (was introduced in 1996) and SCMIJ (was introduced in 1997) did not cite themselves as much in the first decade. An analysis of the matrices also reveals that self-citations constitute most of the citations in the network of journals, and over the past 20 years there has been an increasing trend in the number of self-citations (but also an increased number of total citations), a fact that indicates that the whole network has become more self-contained. Centrality Centrality in a social network is a concept that illustrates the most important and prominent actors in the network (Wasserman and Faust, 1994). These actors possess a strategic location within the network. There are many ways of measuring the dimensions of prominence in a network. For the purposes of this study, the metrics of degree centrality, the betweenness and the closeness of the network are utilised using the Freeman approach (Borgatti et al., 2002). Degree centrality The actors that are more central and prominent in the network of journals are the most active in terms of the number of citations they received from the other journals (their indegree) than the citations the make (their outdegree). As it can be seen in Table III the most prominent journal in terms of the citations received and made is the JSCM with a difference of 87.7 followed by the JEIM with a difference of 29.2 and the IJPDLM with a difference of 25.6. The two OM journals are relatively central to the network with high levels of outdegree and indegree. Substantial difference appears in the indegree of JEIM over the past ten years, making the journal a more prominent actor in the network. The network centralization (degree to which the entire network is focused around a few central nodes) has slightly increased over the last 20 years. This indicates a relative consolidation of the network around a few journals, a finding that can be

Intellectual structure of the SCM discipline 143

Table III. Degree Centrality 1991-2010 28.80 48.80 76.10 150.30 96.30 52.50 175.00 31.60 3.60 24.60

48.4 30.1 2 20 2 86.3 2 45.2 2 5.3 2 122 10.4 83.6 46.2

85.90 79.10 62.80 67.40 70.00 62.60 63.10 44.80 71.00 79.20

OutDegree 48.30 48.50 91.00 87.50 66.30 97.80 141.30 62.60 95.90 26.80

37.6 30.6 2 28.2 2 20.1 3.7 2 35.2 2 78.2 2 17.8 2 24.9 52.4

Difference

85.20 79.00 60.20 65.70 62.50 58.60 59.90 50.60 71.60 75.60

OutDegree

36.50 43.30 85.80 81.90 80.30 85.20 147.60 79.72 66.30 26.50

1991-2010c InDegree

48.7 35.7 2 25.6 2 16.2 2 17.8 2 26.6 2 87.7 2 29.2 5.3 49.1

Difference

Notes: aNet Centralization (Outdegree) ¼ 5.80 per cent; Net Centralization (Indegree) ¼ 29.53per cent; bNet Centralization (Outdegree) ¼ 6.13 per cent; Net Centralization (Indegree) ¼ 31.74 per cent; cNet Centralization (Outdegree) ¼ 6.72 per cent; Net Centralization (Indegree) ¼ 34.09 per cent

77.20 78.90 56.10 64.00 51.10 47.20 53.00 42.00 87.20 70.80

Difference

2001-2010b InDegree

144

JPSM IJLM IJOPM IJPDLM JBL JOM JSCM JEIM SCMIJ LTR

OutDegree

1991-2000a InDegree

JEIM 25,2

interpreted that the academic field of SCM is maturing and developing around the intellectual focus of the selected journals. Betweenness The concept of betweenness is another way to measure the prominence in a network and refers to the extent to which a particular point lies between the various other points in the graph: a point of a relative low degree may play an important intermediary role and so be very central to the network (Scott, 2006). Thus the journals that are “in between” may act as gatekeepers in the dissemination of knowledge among the network. The betweenness analysis was conducted to confirm and consolidate the results for degree centrality as well as to show which journals act as gatekeepers in the dissemination of knowledge in the network. The relative difference that exist in the scores of the journals (see Table IV) indicate the more or less betweenness of the journals (highest score means higher level of betweenness). Over the past 20 years the more central journals in the sense that they were located between many other Journals were the JSCM, JOM and the JBL. The SMIJ and JEIM underwent a remarkable increase in terms of their betweenness (their are is ranked third and fourth for 2001-2010 respectively), acquiring a prominent liaison in the exchange of citations. Overall, the journal “most between” other journals was the JSCM. By comparing the two-decade periods, the 2001-2010 decade is characterised by the emergence of a fewer centrally located journals that channel the information/knowledge in the network.

Intellectual structure of the SCM discipline 145

Closeness Opposite to degree centrality that shows the “local centrality” (i.e. the centrality in the immediate environment of the journal), the level of closeness indicates how “globally central” a journal is. This measure focuses on how close an actor is to all the other actors in the network (Wasserman and Faust, 1994) and expresses the global centrality of a network, i.e. a journal would be globally central if it lies at short geodesic distances from many other journals (nodes of the network). Journals with high level of closeness centrality therefore, could be very productive in disseminating knowledge to other journals in the network. As it can be seen in the results if analysis of matrices for the

JPSM IJLM IJOPM IJPDLM JBL JOM JSCM JEIM SCMIJ LTR

1991-2000

Flow Betweenness 2001-2010

1991-2010

4.93 7.88 18.64 12.35 6.74 5.75 8.74 5.45 4.07 5.48

5.21 4.47 8.80 6.38 5.57 8.88 15.46 10.21 11.62 4.81

5.11 5.74 10.22 7.80 5.98 7.12 11.26 7.22 8.50 4.71

Note: Network Centralization Index for 1991-2010 ¼ 11.807 per cent

Table IV. Longitudinal Betweenness of each journal

JEIM 25,2

146

level of closeness of each journal, the most globally central journal for the 20 year period were the JSCM, the IJOPM and JOM and more recently the JEIM (see Table V). In the analysis of the relationship between the journals in the network, each journal sends and receives citations from other journals. Those journals with the larger number of citations they receive, compared to the citations they make are perceived to be more central in the network. Centrality in the network is an indication of the prestige that a journal has. This prestige can be assessed by identifying the number of citations made, and received by each journal. Three measures were used in this study: degree betweenness and closeness. Those journals with high levels of indegree than outdegree and/or high betweenness scores are considered to possess prestige in the network, as they have been the most centrally positioned. The analysis over the past two decades revealed that while some journals played an important role in the first decade (e.g. IJPDLM), their role was lessened in the second decade. Conversely, the second decade saw the emergence of two new centrally positioned journals, JEIM and SCMIJ, along with the most prominent two journals for the entire period ( JSCM and JOM). Groupings, cliques and structure of the network An analysis of the development of groupings and cliques was then conducted to identify if certain journals specialise and focus on specific themes/issues. Groupings of journals show that each member ( journal) in a group will be directly linked to every other member in the same group. The technique of hierarchical clustering was utilised first to identify groups in the network. Hierarchical clustering This technique finds a series of nested partitions of the actors in a network. It groups journals into subsets, so that entities within a subgroup are relatively similar to each other (Wasserman and Faust, 1994). The different partitions are ordered according to decreasing levels of similarity. The algorithm begins with the identity partition (in which all items are in different clusters). It then joins the pair of items most similar (least different), which are then considered a single entity. The algorithm continues in this manner until all items are joined into a single cluster (the complete partition) (Borgatti et al., 2002). The similarities between journals are identified in terms of the way they cite (are cited) by other journals. 1991-2000 InCloseness OutCloseness

Table V. Closeness

JPSM IJLM IJOPM IJPDLM JBL JOM JSCM JEIM SCMIJ LTR

60.00 100.00 100.00 100.00 90.00 90.00 100.00 64.28 60.00 75.00

75.00 81.82 100.00 90.00 75.00 69.23 75.00 90.00 81.82 75.00

2001-2010 InCloseness OutCloseness 75.00 75.00 100.00 90.00 75.00 100.00 100.00 64.28 100.00 75.00

90.00 69.23 100.00 90.00 75.00 90.00 90.00 81.82 90.00 75.00

1991-2010 InCloseness OutCloseness 75.00 90.00 00.00 90.00 90.00 100.00 100.00 64.28 90.00 75.00

90.00 81.82 90.00 90.00 75.00 90.00 90.00 90.00 90.00 75.00

The output of the hierarchical clustering analysis is presented in the dendograms of Figures 1 and 2 and illustrates the groups of journals that are similar to each other in the two separate ten-year periods. The level of clustering refers to the degree of similarity among journals in the clusters. When comparing the two ten year periods, the cliques that emerge are quite different. For the first decade (1991-2000) the most central clique is composed by JEIM and IJLM in the first level. At the second level JBL,

Intellectual structure of the SCM discipline 147

Figure 1. Hierarchical Clustering 1991-2000

Figure 2. Hierarchical Clustering 2001-2010

JEIM 25,2

148

LTR, and then the JPSM are added to the original clique forming a grouping, which is distinctive of the cliques of JOM, IJOPM and IJPDLM and JSCM that form another grouping after the second level. SCMIJ is added to the network in the third level. This analysis indicates that the network of the journals was fairly unorganised with several cliques being formed in the first level. For the last ten-year period, the results present the formation of two distinct high-level clusters. On one side lie logistics oriented journals ( JEIM, IJLM, IJPDLM, JBL, and LTR) and on the other side a cluster with the traditional OM journals is formed together with the newly formed SCM journals ( JPSM, JSCM, SCMIJ and JOM, IJOPM). This finding indicates a more direct communication between the journals in the two distinctive cliques in period 2 than in period 1. JEIM has a central position in the network, being added to the logistics oriented grouping only at the second level. This indicates that JEIM is more interdisciplinary in its content when compared to journals that belong to a particular clique from level 1. Multi-dimensional scaling A Multidimensional Scaling (MDS) analysis was also performed to provide a visual depiction of the communication patterns among the journals of the network. Conceptually, the purpose of MDS is to provide a visual representation of the pattern of proximities (i.e. similarities or distances) among a set of objects. It can be interpreted to represent a two-dimensional recreation of the communication patterns between the journals in the network. For the journals that are close to one another on the map it means that they have stronger communication ties. Figure 3 illustrates the results of the metric MDS done by UCINET6 for the period 1991-2010. In Appendix 2 (see Figures A1, A2, A3, A4, A5 and A6), the MDS maps illustrate how the position of the journals has changed over the last 20 years, with the presentation of four consecutive five-year periods. The MDS map shown previously indicates that for the period 1991-2010 three distinctive group of journals have been formed. On the right side the more logistics-oriented journals (IJPDLM, JBL and IJLM). More centrally in the network are

Figure 3. MDS Mapping for 1991-2010

the JSCM and SCMIJ with the JSCM very close to the centre. This could mean that this group ( JSCM and SCMIJ) sends and receives citations from different sources in the network. The JEIM possesses a central role over the past five years, as it can be seen from the shift of its position in the map between 1991-2000 and 2001-2010. To the left side is the third group of the Operations Management related journals IJOPM and JOM. The MDS maps in Appendix 2 demonstrate an interesting finding in the way that the network of journals has evolved over the past 20 years. It can be seen that the traditional OM journals are becoming more central in the network and form closer ties with the SCM journals. The position of the “logistics-oriented” journals (the IJPDLM, JBL, IJLM, JEIM, and LTR) has changed as well. Three journals (IJPDLM, IJLM and JEIM) have got closer to each other and the other journals. The LTR however has maintained peripheral position to the network, focusing mainly on transportation problems of SCM and on quantitative approaches to logistics. These changes show primarily signs of formation of a more cohesive network in the last decade (with the exception of the more quantitative logistics journals). This can be interpreted as an indication of a more established discipline of SCM. Position in the network The identification of the position in the network can identify the journals that are similar to one another and perform similar roles within the network. The measure of the structural equivalence has been utilised for this purpose. Structural equivalence illustrates whether some journals share the same role or perform the same function within a given network. Structurally equivalent journals occupy the same social network positions in that they have similar connections with the “other” journals (Doreian, 1985). The roles performed by these members can be many and varied. For example although two journals may not have strong ties in exchanging citations, they may both act as gatekeepers in their clusters. The CONCOR procedure of UCINET6 has been applied. This technique partitions the data by splitting blocks based on the convergence of iterated correlations of the actors/journals of the network, by performing a factor analysis on the correlations of the matrix. The equivalence characteristics of the network are shown in Appendix 3 (see Table AII), and the dendograms in Figures 4 and 5 exhibit the journals that perform similar roles in the network. The analysis for the first period produces four groups of structurally equivalent journals: G1 ( JSCM, IJLM, JPSM), G2 (SCMIJ, JEIM), G3 ( JBL, IJPDLM, LTR) and G4 (IJOPM, JOM). The analysis for the second decade also produced four structurally similar groups: G1 ( JPSM, SCMIJ, JSCM), G2 (IJOPM, JOM), G3 (IJLM, JEIM) and G4 (IJPDLM, JBL, LTR). For the second period the distinction between purchasing and supply management (G1 journals), Operations Management (G2 journals), logistics and transport management (G4 journals) is more evident. G3 journals provide a motley mix of information systems, logistics and supply chain management topics and form a separate (multi-disciplinary group). As it can be seen in the dendograms, there has been a major change in the role of specific journals. The JSCM for example had a similar role to IJLM in the first ten years, but over the past decade has acquired a different role. Similarly JEIM was similar to SCMIJ in the first decade. As SCMIJ was only introduced in 1995 both

Intellectual structure of the SCM discipline 149

JEIM 25,2

150

Figure 4. Structural Equivalence Cluster Dendograms – Equivalence Cluster Dendogram for 1991-2000

Figure 5. Structural Equivalence Cluster Dendograms – Equivalence Cluster Dendogram for 2001-2010

journals acquired a peripheral role in the network. In the second decade JEIM has evolved into a more inter-disciplinary journal. By taking into account other characteristics such as the centrality and betweenness of the journals and by looking at the dendogram between 2001-2010, a conclusion can be reached that the journals that act as gatekeepers between the two major clusters (SCM vs Logistics journals) of the dengogram for 2001-2010 are the JSCM and IJPDLM. Cohesion A final analysis has been to identify the cohesion of the network of SCM journals. A way of measuring the cohesion of the whole network is by measuring its density.

The density measure of SNA describes the general level of linkage among actors in a network and is defined as the number of ties in the network divided by the number of pairs of actors (Scott, 2006). As it can be seen in Table VI, the density of the network has increased substantially over the 20 years, illustrating that there has not been a significant change in the structure of the network in terms of its cohesion.

Intellectual structure of the SCM discipline 151

Research findings and discussion The findings of the SNA analysis generate useful insights about the objectives of this study. For the selection of a network of journals that represent the intellectual structure of the SCM discipline (Research Objective 1), a large number of journals that increasingly publish articles in the broad field of SCM has been identified. Apart from the seminal disciplines of Logistics, Operations Management and Purchasing, these journals represent a growing interest in SCM phenomena originating in the disciplines of Operational Research, Information Systems, Marketing and General Management. This explosion of interest in supply chain issues provides evidence that the SCM problem domain is being established as an important academic discipline. The selection of the citations from the journals of the selected network also indicated an explosion of interest of the SCM related journal in journals that fall within other disciplines (Research Objective 2). A discipline’s scientific status is enhanced if the knowledge base is widely dispersed and used by other disciplines and researchers (Anderson, 1983). Researchers in the field of SCM draw knowledge on a diverse and very rich body of literature spanning from Operations Management and Logistics to Psychology and Geography. A unique established body of literature regarding supply chain phenomena does not exist and researchers in the field tend to prefer to publish their work in more established general management academic journals. Supply Chain Management related papers are increasingly found in journals such as Harvard Business Review, Strategic Management Journal, and Management Science. These journals in fact are among the most cited journals of the network of journals that have been analysed in this study. Several special issues dedicated to SCM phenomena have been published in these journals with the trend spreading to journals that were traditionally not considered part of the SCM discipline. For the connections between the selected journals and the identification of the role of the journals in the network, their similarities and the way that their exchange of communication (citations) has changed over time (Research objectives 3 and 4), the SNA analysis revealed the following findings. Position in the network: Several studies propose that the prominence in a social network is of paramount importance for the diffusion and dissemination of knowledge (Knoke and Song, 2008; Borgatti and Li, 2009). In the analysed network several journals perform this role: The JSCM, SCMIJ, JOM, IJOPM and JEIM have acquired a central role in the network with a focus that transcends the traditional areas of SCM (logistics, procurement, operations). The transformation of the JEIM in particular from a specialised IS logistics journal (Logistics Information Management) to a journal that incorporates a large number of SCM phenomena (Alsudairi and Dwivedi, 2010; Dwivedi and Mustafee, 2010; Schlichter and Kraemmergaard, 2010) has also been

Table VI. Density/average value within blocks 1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

Density 0.064 0.068 0.053 0.067 0.069 0.070 0.072 0.066 0.071 0.070 0.066 0.071 0.073 0.077 0.078 0.081 0.083 0.086 0.086 0.085

1992

152

1991

JEIM 25,2

substantial. These journals can be considered as gatekeepers of knowledge in the scientific community of SCM. Clusters in the network: The findings show that the network of SCM journals has changed considerably over the past 20 years. The 1991-2000 decade was characterised by distinct clusters of journals (see Figures A1, A2, A3, A4, A5 and A6 in Appendix 1) and by a single journal that acted as gatekeeper. The last decade however shows a convergence of communication between the journals and the emergence of larger clusters (that are closer to each other). The distinction between logistics related journals and operations and process management related journals still exists, but there is evidence of convergence. This provides evidence that the network has become more cohesive over the last ten years. Rather than having a few “powerful journals” in the network, the prestige of journals in network is spread across a large number of journals. The SCM discipline evolved in a way that has been characterised by an increasing need for communication between journals specialising in logistics, transportation, purchasing, operations and process management. Research in Operations Management issues appear to be closer today to SCM as it is evidenced in the analysis. The number of papers that are published in the JOM and IJOPM with a clear focus on SCM phenomena has increased by 400% over the past 20 years. More and more paper related to SCM are presented in the traditional OM conferences (POMS, EUROMA, INFORMS). The advancements in Information and Communication Technology (ICT) tools over the past decade and the implications of ICT tools on the management of supply chain processes have also By comparing the SCM discipline to other business disciplines like marketing, Information Systems, or Accounting it can be seen that the SCM discipline is far less concentrated than those disciplines (Baumgartner and Pieters, 2003; Wakefield, 2008; Polites and Watson, 2009). On one hand this may be interpreted as an ever-increasing acceptance of the value of managing inter-organisational systems, which in effect is what SCM stands for. On the other hand though as Pfeffer (1993) postulates, “without a strong network and lack of consensus a discipline’s ability to compete with adjacent disciplines is jeopardized”. Conclusion In this paper a network of ten academic journals that can be used to represent the academic field of SCM was analysed, with the use of citation data to calculate several SNA metrics (centrality, betweenness, position in the network and network cohesion). The role of each of the journals was identified through the application of SNA in citation data. Based on the findings, several insights have been generated on the way that the SCM has evolved how knowledge and ideas are disseminated in the network. The evolution of the SCM discipline over the last 20 years represents an interesting case study to analyse how the changes in the marco-economic environment influenced academic research. The way that the field will evolve in the next 20 years with the ever-greater emphasis on inter-disciplinary (and even non-disciplinary) research, represents a great opportunity and challenge for the SCM discipline to acquire a central role in the research in the management of organisational systems. As it is by nature a hybrid field of socio-economic and engineering disciplines, it can provide an ideal

Intellectual structure of the SCM discipline 153

JEIM 25,2

154

paradigm for greater theoretical and practical advancements for organisations. Published theoretical and applied research in SCM related journals not only will increase the profile of the SCM discipline, but will also create a fascinating forum in which academics can exchange ideas for a variety of pertinent inter-organisational phenomena. Several implications can be drawn from this study for research in SCM related phenomena. (1) The exponential growth of interest in SCM phenomena and the growing cohesion of the network of journals is a natural consequence as an academic discipline matures. There needs to be however an increased epistemological and methodological clarity of the problem domain of the SCM discipline. (2) The distinctive clusters of journals that represent relatively independent approaches to SCM presents an opportunity for the growth of the discipline. At the same time however, without the use of integrated approaches that bridge the conceptually different perspectives (e.g. logistics and operations management), competing paradigms will emerge. The recent stream of research that promotes the sustainability agenda across the supply chain, as well as the strategic notion of value added across the supply chain may provide the integrating theoretical pillars to promote research in SCM. Limitations and future research The use of citation analysis for the exploration of the structure of an academic discipline may suffer from several problems, such as the motivation for self-citations as well as citations to particular journals and omission of references. The use of co-citations may be considered also as an ex parte measure of similarity between journals. For the analysis of the intellectual structure of the SCM discipline, its representation by a finite and limited number of journals may carry a certain bias in the understanding of the way that knowledge in an academic discipline evolves. The main benefit however in using this combinatory bibliometric approach to deconstruct the structure and evolution of the SCM discipline is that its quantitative nature provides an objective perspective and also allows for the identification of specific roles of the selected journals in the way that knowledge is disseminated (Philips and Philips, 1998; Polites and Watson, 2009). This study can be extended and validated with an extensive (qualitative) longitudinal literature review, or a Delphi study. Further work could use the citation analysis to look at the major academic journals in the general field of management, as well as major practitioner journals, and their relationship with the core journals of SCM. The patterns/importance of the different bodies of literature can be identified through this approach, by measuring the percentages of the citations that refer or come from a journal with a very clear disciplinary orientation. A periodic replication of the study (e.g. every five years) can also be used to reveal any changes in the intellectual structure of the SCM discipline. Future studies can also incorporate newer journals focusing on SCM phenomena.

References Alsudairi, M. and Dwivedi, Y.K. (2010), “A multi-disciplinary profile of IS/IT outsourcing research”, Journal of Enterprise Information Management, Vol. 23 No. 2, pp. 215-58. Anderson, P.F. (1983), “Marketing, scientific progress and scientific method”, Journal of Marketing, Vol. 47, Fall, pp. 18-31. Baumgartner, H. and Pieters, R. (2003), “The structural influence of marketing journals: a citation analysis of the discipline and its sub-areas over time”, Journal of Marketing, Vol. 67, pp. 123-39. Berry, L. and Parasuraman, A. (1993), “Building a new academic field – the case of service marketing”, Journal of Retailing, Vol. 69 No. 1, pp. 13-55. Borgatti, S.P. and Li, X. (2009), “On social network analysis in a supply chain context”, Journal of Supply Chain Management, Vol. 45 No. 2, pp. 5-22. Borgatti, S.P., Everett, M.G. and Freeman, L.C. (2002), UCINET 6.0, Analytic, Natick, MA. Carter, C., Leuschner, R. and Rogers, D.S. (2007), “A social network analysis of the Journal of Supply Chain Management: knowledge generation, knowledge diffusion and thought leadership”, Journal of Supply Chain Management, Vol. 43 No. 2, pp. 15-28. Chen, I.J. and Paulraj, A. (2004), “Towards a theory of supply chain management: the constructs and measurements”, Journal of Operations Management, Vol. 22 No. 2, pp. 119-50. Cooper, M.C., Lambert, D.M. and Pagh, J.D. (1997), “Supply chain management: more than a new name for logistics”, The International Journal of Logistics Management, Vol. 8 No. 1, pp. 1-13. Croom, S., Romano, P. and Giannakis, M. (2000), “Supply chain management: an analytical framework for critical literature review”, European Journal of Purchasing and Supply Management, Vol. 6, pp. 67-83. Doreian, P. (1985), “Structural equivalence in a psychology journal network”, Journal of the American Society for Information Science, Vol. 36 No. 6, pp. 411-7. Dwivedi, Y.K. and Mustafee, N. (2010), “Profiling research published in the Journal of Enterprise Information Management”, Journal of Enterprise Information Management, Vol. 23 No. 1, pp. 8-26. Falagas, M.E., Pitsouni, E.I., Malietzis, G.A. and Pappas, G. (2008), “Comparison of Pub Med, Scopus, Web of Science, and Google Scholar: strengths and weaknesses”, The Journal of the Federation of American Societies for Experimental Biology, Vol. 22, pp. 338-42. Fine, C.H. (2000), “Clockspeed-based strategies for supply chain design”, Production and Operations Management, Vol. 9 No. 3, pp. 213-21. Ganeshan, R., Jack, E., Magazine, M.J. and Stephens, P. (1999), “A taxonomic review of supply chain management research”, in Tayur, S., Ganeshan, R. and Magazine, M. (Eds), Quantitative Models for Supply Chain Management, Kluwer Academic Publishers, Boston, MA, pp. 840-79. Garfield, E. (1979), Citation Indexing: Its Theory and Application in Science, Technology and Humanities, John Wiley, New York, NY. Giannakis, M. and Croom, S. (2004), “Towards the development of a supply chain management paradigm: a conceptual framework”, Journal of Supply Chain Management, Vol. 40 No. 2, pp. 27-37. Harland, C. (1996), “Supply chain management: relationships, chains and networks”, British Journal of Management, Vol. 7, pp. 63-80, special issue.

Intellectual structure of the SCM discipline 155

JEIM 25,2

156

Harvey, C., Kelly, A., Morris, H. and Rowlinson, M. (2010), Academic Journal Quality Guide Version 4, The Association of Business Schools, London. Heineke, H. and Davis, M.M. (2007), “The emergence of service operations management as an academic discipline”, Journal of Operations Management, Vol. 25 No. 2, pp. 364-74. Knoke, D. and Song, Y. (2008), Social Network Analysis, Sage Publications, Los Angeles, CA. Lambert, D.M. and Cooper, M.C. (2000), “Issues in supply chain management”, Industrial Marketing Management, Vol. 29, pp. 65-83. Lawson, B., Squire, B. and Cousins, P.D. (2006), “Supply chain management: theory and practice – the emergence of an academic discipline?”, International Journal of Operations and Production Management, Vol. 26 No. 7, pp. 697-702. Lummus, R.R. and Vokura, R.J. (1999), “Defining supply chain management: a historical perspective and practical guidelines”, Industrial Management & Data Systems, Vol. 99 No. 1, pp. 11-17. Miles, R.E. and Snow, C.C. (2007), “Organisation theory and supply chain management: an evolving research perspective”, Journal of Operations Management, Vol. 25 No. 2, pp. 459-63. Pfeffer, J. (1993), “Barriers to the advance of organisational science: paradigm development as a dependent variable”, The Academy of Management Review, Vol. 18 No. 4, pp. 599-620. Philips, D. and Philips, J.K. (1998), “A social network analysis of business logistics and transportation”, International Journal of Physical Distribution and Logistics Management, Vol. 28 No. 5, pp. 328-48. Polites, G.L. and Watson, R.T. (2009), “Using social network analysis to analyze relationships among IS journals”, Journal of the Association for Information Systems, Vol. 10 No. 8, pp. 535-634. Reed, K.L. (1995), “Citation analysis of faculty publication: beyond Science Citation Index and Social Science Citation Index”, Bulletin of the Medical Library Association, Vol. 83 No. 4, pp. 503-8. Schlichter, B.R. and Kraemmergaard, P. (2010), “A comprehensive literature review of the ERP research field over a decade”, Journal of Enterprise Information Management, Vol. 23 No. 4, pp. 486-520. Scott, J. (2006), Social Network Analysis: A Handbook, Sage, London. Tan, K.C. (2001), “A framework of supply chain management literature”, European Journal of Purchasing and Supply Management, Vol. 7, pp. 39-48. Wakefield, R. (2008), “Networks of accounting research: a citation-based structural and network analysis”, The British Accounting Review, Vol. 40 No. 3, pp. 228-44. Wasserman, S. and Faust, K. (1994), Social Network Analysis: Methods and Applications, Cambridge University Press, Cambridge.

Corresponding author Mihalis Giannakis can be contacted at: [email protected]

1991 JPSM IJLM IJOPM IJPDLM JBL JOM JSCM JEIM SCMIJ LTR 1992 JPSM IJLM IJOPM IJPDLM JBL JOM JSCM JEIM SCMIJ LTR 1993 JPSM IJLM IJOPM IJPDLM JBL JOM JSCM JEIM SCMIJ LTR

0 0 0 0 0 0 0 0 0 0

0 2 0 0 0 0 1 0 0 0

0 6 0 0 0 0 1 0 0 0

0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0

0 6 66 3 1 31 13 0 0 0

0 4 57 5 1 31 9 0 0 0

0 0 64 8 0 27 8 0 0 0

0 37 15 71 27 4 28 8 0 24

0 32 8 63 31 10 24 7 0 19

0 0 10 58 34 4 27 9 0 14

JPSM IJLM IJOPM IJPDLM

0 12 5 37 57 8 18 18 0 27

0 9 9 41 47 4 14 10 0 31

0 0 6 38 51 4 19 14 0 21

0 1 53 7 2 79 19 2 0 1

0 2 47 8 7 67 12 1 0 1

0 0 41 13 6 54 14 2 0 2

0 21 10 26 10 12 67 9 0 9

0 25 12 31 7 16 57 7 0 7

0 0 8 27 9 19 48 3 0 3

0 0 0 0 0 0 0 20 0 0

0 0 0 0 0 0 0 17 0 0

0 0 0 0 0 0 0 16 0 0

0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0

0 0 0 4 8 0 0 0 0 24

0 0 0 12 10 0 0 0 0 31

0 0 0 7 14 0 0 4 0 27

0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

0.00 7.20 0.00 0.00 0.00 0.00 0.70 0.00 0.00 0.00

0.00 2.70 0.00 0.00 0.00 0.00 0.90 0.00 0.00 0.00

0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

0.00 7.20 44.30 2.00 1.00 23.10 8.90 0.00 0.00 0.00

0.00 5.40 42.90 3.10 1.00 24.20 7.70 0.00 0.00 0.00

0.00 0.00 49.6 5.30 0.00 25.00 6.90 0.00 0.00 0.00

0.00 44.60 10.10 48.00 25.70 3.00 19.20 14.00 0.00 28.20

0.00 43.20 6.00 39.40 30.10 7.80 20.50 16.70 0.00 21.30

0.00 0.00 7.80 38.40 29.8 3.70 23.30 18.80 0.00 20.9

0.00 14.50 3.40 25.0 54.30 6.00 12.30 31.60 0.00 31.80

0.00 12.20 6.80 25.60 45.60 3.10 12.00 23.80 0.00 34.80

0.00 0.00 4.70 25.20 44.70 3.70 16.40 29.20 0.00 31.30

0.00 1.20 35.60 4.70 1.90 59.00 13.00 3.500 0.00 1.20

0.00 2.70 35.30 5.00 6.80 52.30 10.30 2.40 0.00 1.10

0.00 0.00 31.80 8.60 5.30 50.00 12.10 4.20 0.00 3.00

0.00 25.30 6.70 17.60 9.50 9.00 45.90 15.80 0.00 10.6

0.00 33.80 9.00 19.40 6.80 12.50 48.70 16.70 0.00 7.90

0.00 0.00 6.20 17.90 7.90 17.60 41.40 6.30 0.00 4.50

Matrix Normalised matrix JBL JOM JSCM JEIM SCMIJ LTR JPSM IJLM IJOPM IJPDLM JBL JOM JSCM

0.00 0.00 0.00 0.00 0.00 0.00 0.00 35.10 0.00 0.00

0.00 0.00 0.00 0.00 0.00 0.00 0.00 40.50 0.00 0.00

0.00 0.00 0.00 0.00 0.00 0.00 0.00 33.30 0.00 0.00

JEIM 0.00 0.00 0.00 4.60 12.30 0.00 0.00 8.30 0.00 40.30 0.00 0.00 0.00 7.50 9.70 0.00 0.00 0.00 0.00 34.8

0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

0.00 0.00 0.00 0.00 0.00 0.00 0.00 2.70 0.00 7.60 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 28.2 (continued)

LTR

SCMIJ

Appendix 1

Intellectual structure of the SCM discipline 157

Table AI. Matrices

Table AI. 0 10 0 1 2 0 1 0 0 0 0 11 0 5 2 0 2 1 0 0 0 19 1 12 8 4 6 1 0 3

0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0

0 5 93 14 2 29 10 4 0 3

0 9 78 9 4 28 12 5 0 1

0 5 71 2 8 27 14 0 0 0

0 34 20 78 30 12 31 22 0 25

0 32 14 71 34 10 23 17 0 29

0 31 19 65 23 8 31 14 0 21

0 16 5 41 71 9 13 10 0 21

0 14 2 38 65 5 9 9 0 18

0 9 4 41 62 7 12 12 0 24

0 7 48 10 7 61 20 4 0 0

0 4 50 12 4 71 17 2 0 1

0 1 48 10 5 64 10 6 0 2

0 18 29 49 23 13 51 11 0 15

0 20 21 37 18 18 67 17 0 21

0 18 14 30 13 20 71 4 0 16

0 0 0 2 0 0 0 23 0 0

0 0 0 4 0 0 1 19 0 0

0 0 0 1 0 0 0 17 0 0

0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0

0 3 0 13 5 0 0 4 0 31

0 1 0 4 2 0 0 3 0 19

0 0 0 1 7 0 0 1 0 24

0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

0.00 18.60 0.50 5.50 5.50 3.10 4.60 1.30 0.00 1.30

0.00 12.10 0.00 2.80 1.60 0.00 1.50 1.40 0.00 0.00

0.00 13.50 0.00 0.70 1.70 0.00 0.70 0.00 0.00 0.00

0.00 4.90 47.40 6.40 1.40 22.70 7.60 5.10 0.00 3.10

0.00 9.90 47.30 5.00 3.10 21.20 9.20 6.80 0.00 1.10

0.00 6.80 45.50 1.30 6.70 21.40 10.10 0.00 0.00 0.00

0.00 33.30 10.20 35.60 20.50 9.40 23.70 27.80 0.00 25.50

0.00 35.20 8.50 39.40 26.40 7.60 17.60 23.30 0.00 32.60

0.00 41.9 12.20 43.00 19.20 6.30 22.30 25.90 0.00 24.10

0.00 15.70 2.60 18.70 48.60 7.00 9.90 12.70 0.00 21.40

0.00 15.40 1.20 21.10 50.40 3.80 6.90 12.30 0.00 20.20

0.00 12.20 2.60 27.20 51.70 5.60 8.60 22.20 0.00 27.60

0.00 6.90 24.50 4.60 4.80 47.70 15.30 5.10 0.00 0.00

0.00 4.40 30.30 6.70 3.10 53.80 13.00 2.70 0.00 1.10

0.00 1.40 30.8 6.60 4.20 50.80 7.20 11.10 0.00 2.30

0.00 17.60 14.80 22.40 15.80 10.20 38.90 13.90 0.00 15.30

0.00 22.00 12.70 20.60 14.00 13.60 51.10 23.30 0.00 23.60

0.00 24.30 9.00 19.90 10.80 15.90 51.10 7.40 0.00 18.4

Matrix Normalised matrix JBL JOM JSCM JEIM SCMIJ LTR JPSM IJLM IJOPM IJPDLM JBL JOM JSCM

158

1994 JPSM IJLM IJOPM IJPDLM JBL JOM JSCM JEIM SCMIJ LTR 1995 JPSM IJLM IJOPM IJPDLM JBL JOM JSCM JEIM SCMIJ LTR 1996 JPSM IJLM IJOPM IJPDLM JBL JOM JSCM JEIM SCMIJ LTR

JPSM IJLM IJOPM IJPDLM

0.00 0.00 0.00 0.90 0.00 0.00 0.00 29.10 0.00 0.00

0.00 0.00 0.00 2.20 0.00 0.00 0.80 26.00 0.00 0.00

0.00 0.00 0.00 0.70 0.00 0.00 0.00 31.50 0.00 0.00

JEIM

0.00 1.10 0.00 2.20 1.60 0.00 0.00 4.10 0.00 21.30

0.00 0.00 0.00 0.70 5.80 0.00 0.00 1.90 0.00 27.60

LTR

0.00 0.00 0.00 2.90 0.00 0.00 0.00 5.90 0.00 3.40 0.00 0.00 0.00 0.00 0.00 5.10 0.00 0.00 0.00 31.60 (continued)

0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

SCMIJ

JEIM 25,2

1997 JPSM IJLM IJOPM IJPDLM JBL JOM JSCM JEIM SCMIJ LTR 1998 JPSM IJLM IJOPM IJPDLM JBL JOM JSCM JEIM SCMIJ LTR 1999 JPSM IJLM IJOPM IJPDLM JBL JOM JSCM JEIM SCMIJ LTR 0 18 4 25 18 2 6 3 0 8 10 24 3 30 27 0 7 5 5 12 3 38 5 23 21 0 8 7 8 7

0 0 0 0 0 0 0 0 0 0

6 0 0 0 0 0 0 0 0 0

14 0 1 5 0 0 0 0 15 0

7 5 103 29 2 34 10 6 8 2

12 3 121 18 6 32 12 3 7 4

0 8 87 13 4 23 7 4 0 5

3 18 38 91 23 3 8 18 2 12

5 28 41 85 21 2 18 23 19 19

0 31 32 61 27 8 27 27 0 28

JPSM IJLM IJOPM IJPDLM

0 17 15 41 62 9 9 1 0 31

0 15 9 38 57 6 9 3 2 27

0 14 7 36 62 7 6 8 0 19

0 1 47 4 3 77 12 0 1 0

0 2 38 6 4 73 29 0 0 1

0 4 54 7 2 67 26 1 0 2

21 0 41 69 3 23 51 16 8 2

27 4 32 71 9 28 61 17 0 8

0 14 27 54 18 18 47 18 0 10

0 0 2 5 0 0 0 18 0 0

0 0 1 2 0 0 0 23 8 0

0 0 0 1 0 0 0 29 0 0

2 0 1 0 0 0 0 1 5 0

0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0

1 8 12 29 2 0 0 9 0 25

0 8 8 23 3 0 0 12 0 21

0 5 3 17 2 0 0 8 0 27

27.50 0.00 0.40 1.70 0.00 0.00 0.00 0.00 31.90 0.00

9.70 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

5.90 43.70 1.90 7.80 18.10 0.00 8.20 9.20 17.00 8.90

16.10 28.60 1.20 11.00 21.30 0.00 5.10 5.80 1.50 13.00

0.00 19.10 1.90 11.70 13.50 1.60 5.00 3.10 0.00 8.10

13.70 5.70 38.90 9.80 1.70 23.30 10.20 7.90 17.00 2.50

19.40 3.60 47.80 6.60 4.70 22.70 8.80 3.50 4.00 4.30

0.00 8.50 40.70 6.10 3.00 18.40 5.90 4.10 0.00 5.10

5.90 20.70 14.30 30.70 19.80 2.10 8.223.70 4.30 15.20

8.10 33.30 16.20 31.10 16.50 1.40 13.20 26.70 0.00 20.70

0.00 33.30 15.00 28.50 20.30 6.40 22.70 27.60 0.00 28.30

0.00 4.30 25.20 3.30 1.50 53.60 21.80 1.00 0.00 2.00

0.00 19.50 5.70 13.90 53.40 6.20 9.20 1.30 0.00 39.20

0.00 1.10 17.70 1.40 2.60 52.70 12.20 0.00 2.10 0.00

0.00 0.00 17.90 2.40 3.60 15.00 13.90 2.20 44.90 3.10 4.30 51.80 6.60 21.30 3.50 0.00 0.00 0.00 29.300 1.10

0.00 14.90 3.30 16.80 46.60 5.60 5.00 8.20 0.00 19.20

41.20 0.00 15.50 23.30 2.60 15.80 52.00 21.10 17.00 2.50

43.50 4.80 12.60 26.00 7.10 19.90 44.90 19.80 0.00 8.70

0.00 14.90 12.60 25.213.50 14.40 39.50 18.40 0.00 10.10

Matrix Normalised matrix JBL JOM JSCM JEIM SCMIJ LTR JPSM IJLM IJOPM IJPDLM JBL JOM JSCM

0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

3.90 2.00 0.00 9.20 0.40 4.50 0.00 9.80 0.00 1.70 0.00 0.00 0.00 0.00 1.30 11.80 10.60 0.00 0.00 31.60 (continued)

0.00 0.00 0.40 0.70 0.00 0.00 0.00 26.70 0.00 0.00 0.00 0.00 0.80 1.70 0.00 0.00 0.00 23.70 0.00 0.00

0.00 9.50 3.20 8.40 2.40 0.00 0.00 14.00 0.00 22.80

0.00 5.30 1.40 7.90 1.50 0.00 0.00 8.20 0.00 27.30

0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

0.00 0.00 0.50 0.00 0.00 0.00 0.00 29.60 0.00 0.00

LTR

SCMIJ

JEIM

Intellectual structure of the SCM discipline 159

Table AI.

Table AI. 1 35 3 19 13 1 4 9 6 2 2 36 8 8 10 4 4 2 3 2 22 17 5 42 9 2 6 2 4 2

22 0 3 9 0 0 0 0 9 0

18 1 10 0 1 1 1 0 0 0

23 0 7 4 0 1 7 1 12 0

10 4 126 10 1 108 6 6 4 1

4 6 105 3 1 21 1 6 1 0

3 4 115 34 1 21 8 10 2 3

23 2 14 64 48 13 17 3 11 9

19 23 11 68 32 11 11 5 8 3

6 23 49 115 29 4 9 14 0 9

7 16 1 29 70 11 15 2 7 10

4 16 6 42 66 10 4 2 3 5

0 15 11 34 54 1 13 3 2 26

1 2 43 5 10 142 6 2 1 0

1 4 46 10 0 94 5 2 2 0

0 1 34 2 1 60 6 1 0 2

55 1 43 15 50 83 87 7 7 14

53 7 9 10 10 38 69 18 5 2

36 0 52 64 8 19 58 22 14 5

2 1 1 4 0 1 0 7 1 0

0 9 5 6 2 1 0 8 0 0

0 1 5 6 0 0 0 9 0 0

9 2 1 7 3 0 1 2 24 0

2 6 0 1 0 0 0 0 5 1

2 0 0 0 0 0 0 1 6 0

5 2 0 11 1 3 1 1 0 18

2 2 0 22 8 0 1 1 0 14

1 6 17 28 4 0 0 1 0 20

14.65 0.00 2.90 2.09 0.00 0.27 4.79 3.03 16.90 0.00

17.14 0.91 5.00 0.00 0.77 0.56 1.04 0.00 0.00 0.00

30.99 0.00 1.04 2.89 0.00 0.00 0.00 0.00 23.08 0.00

14.01 36.17 2.07 21.99 4.69 0.55 4.11 6.06 5.63 3.70

1.90 32.73 4.00 4.71 7.69 2.22 4.17 4.55 11.11 7.41

1.41 41.18 1.04 6.11 11.82 0.94 5.88 12.86 15.38 2.99

6.37 8.51 52.28 5.24 0.52 29.67 4.11 18.18 5.63 1.85

3.81 5.45 52.50 1.76 0.77 11.67 1.04 13.64 3.70 0.00

4.23 4.71 39.79 10.93 0.91 19.81 11.76 14.29 5.13 4.48

14.65 4.26 5.81 33.51 25.00 3.57 11.64 9.09 15.49 16.67

18.10 20.91 5.50 40.00 24.62 6.11 11.46 11.36 29.63 11.11

8.45 27.06 16.96 36.98 26.36 3.77 13.24 20.00 0.00 13.43

4.46 34.04 0.41 15.18 36.46 3.02 10.27 6.06 9.86 18.52

3.81 14.55 3.00 24.71 50.77 5.56 4.17 4.55 11.11 18.52

0.00 17.65 3.81 10.93 49.09 0.94 19.12 4.29 5.13 38.81

0.64 4.26 17.84 2.62 5.21 39.01 4.11 6.06 1.41 0.00

0.95 3.64 23.00 5.88 0.00 52.22 5.21 4.55 7.41 0.00

0.00 1.18 11.76 0.64 0.91 56.60 8.82 1.43 0.00 2.99

35.03 2.13 17.84 7.85 26.04 22.80 59.59 21.21 9.86 25.93

50.48 6.36 4.50 5.88 7.69 21.11 71.88 40.91 18.52 7.41

50.70 0.00 17.99 20.58 7.27 17.92 41.18 31.43 35.90 7.46

Matrix Normalised matrix JBL JOM JSCM JEIM SCMIJ LTR JPSM IJLM IJOPM IJPDLM JBL JOM JSCM

160

2000 JPSM IJLM IJOPM IJPDLM JBL JOM JSCM JEIM SCMIJ LTR 2001 JPSM IJLM IJOPM IJPDLM JBL JOM JSCM JEIM SCMIJ LTR 2002 JPSM IJLM IJOPM IJPDLM JBL JOM JSCM JEIM SCMIJ LTR

JPSM IJLM IJOPM IJPDLM

1.27 2.13 0.41 2.09 0.00 0.27 0.00 21.21 1.41 0.00

0.00 8.18 2.50 3.53 1.54 0.56 0.00 18.18 0.00 0.00

0.00 1.18 1.73 1.93 0.00 0.00 0.00 12.86 0.00 0.00

JEIM

1.90 1.82 0.00 12.94 6.15 0.00 1.04 2.27 0.00 51.85

1.41 7.06 5.88 9.00 3.64 0.00 0.00 1.43 0.00 29.85

LTR

5.73 3.18 4.26 4.26 0.41 0.00 3.66 5.76 1.56 0.52 0.00 0.82 0.68 0.68 6.06 3.03 33.80 0.00 0.00 33.33 (continued)

1.90 5.45 0.00 0.59 0.00 0.00 0.00 0.00 18.52 3.70

2.82 0.00 0.00 0.00 0.00 0.00 0.00 1.43 15.38 0.00

SCMIJ

JEIM 25,2

2003 JPSM IJLM IJOPM IJPDLM JBL JOM JSCM JEIM SCMIJ LTR 2004 JPSM IJLM IJOPM IJPDLM JBL JOM JSCM JEIM SCMIJ LTR 2005 JPSM IJLM IJOPM IJPDLM JBL JOM JSCM JEIM SCMIJ LTR 16 23 5 35 15 1 3 4 2 4 7 18 3 24 12 1 3 7 5 8 4 14 1 16 18 4 5 19 8 5

25 2 12 5 3 7 15 3 21 1

33 4 17 5 5 10 21 1 18 3

28 7 11 3 5 9 19 5 28 1

17 7 127 11 10 93 28 10 18 8

21 5 113 8 5 110 17 8 14 4

8 3 120 6 3 95 11 2 15 1

21 10 14 90 38 8 10 17 4 12

19 11 12 85 42 8 8 11 7 16

32 7 10 77 35 9 13 4 8 12

JPSM IJLM IJOPM IJPDLM

11 17 8 21 59 8 12 21 9 11

10 18 4 12 51 13 6 9 4 12

3 22 3 18 55 6 3 6 3 15

21 4 76 11 20 171 32 11 20 17

17 4 63 9 21 153 19 9 12 8

6 1 55 7 14 161 18 4 9 1

54 9 41 15 15 49 98 12 47 10

61 9 31 7 17 70 81 7 18 7

63 4 38 7 15 77 92 5 22 7

5 5 2 6 6 6 2 28 4 3

3 5 4 5 3 4 3 15 3 3

4 5 2 8 7 3 3 12 1 4

48 7 28 11 15 30 40 11 52 8

36 7 14 8 11 24 47 5 48 5

19 5 17 14 12 10 42 1 39 3

2 4 5 20 5 2 5 9 3 21

3 4 2 25 8 0 3 4 0 18

3 3 0 23 3 0 3 7 1 23

13.30 8.30 3.50 1.50 2.60 2.40 7.60 3.50 14.50 1.00

15.70 4.70 6.50 2.70 2.90 2.50 10.10 1.30 14.00 3.60

14.00 2.70 4.60 2.50 1.90 1.90 7.40 6.30 17.40 1.40

1.90 16.70 0.30 7.80 9.40 1.10 2.00 13.30 4.10 5.20

3.30 21.20 1.10 12.80 6.90 0.30 1.40 9.20 3.90 9.50

8.90 30.70 1.90 17.50 9.30 0.30 1.50 8.30 1.70 5.60

8.10 8.30 40.60 5.40 5.20 24.50 11.20 7.00 9.30 8.30

10.00 5.90 43.00 4.30 2.90 28.00 8.20 10.50 20.90 4.80

4.50 4.00 45.80 3.00 1.90 25.70 5.40 4.20 12.40 1.40

10.00 11.90 4.50 44.10 19.90 2.10 4.00 11.90 2.10 12.50

9.00 12.90 4.60 45.20 24.00 2.00 3.80 14.50 5.40 19.00

17.90 9.30 3.80 38.50 21.60 2.40 6.40 8.30 6.60 16.90

5.20 20.2 2.60 10.30 30.90 2.10 4.80 14.70 4.70 11.50

4.80 21.20 1.50 6.40 29.10 3.30 2.90 11.80 3.10 14.30

1.70 29.30 1.10 9.00 34.00 1.60 1.50 12.50 2.50 21.10

10.00 4.80 24.30 5.30 10.50 45.00 12.70 7.70 10.40 17.70

8.10 4.70 24.00 4.80 12.00 38.90 9.10 11.80 9.30 9.50

3.40 1.30 21.00 3.50 8.60 43.60 8.90 8.30 7.40 1.40

25.60 10.70 13.10 7.40 7.90 12.90 39.00 8.40 24.40 10.40

29.00 10.6 11.8 3.70 9.70 17.8 38.90 9.20 14.00 8.30

35.20 5.30 14.50 3.50 9.30 20.90 45.30 10.40 18.20 9.90

Matrix Normalised matrix JBL JOM JSCM JEIM SCMIJ LTR JPSM IJLM IJOPM IJPDLM JBL JOM JSCM

17.10 8.20 5.30 4.30 6.30 6.10 22.60 6.60 37.20 6.00

22.70 0.90 8.30 4.80 8.90 1.60 5.40 9.80 7.90 2.60 7.90 0.50 15.90 0.20 7.70 6.30 26.90 1.60 8.30 21.90 (continued)

1.40 5.90 1.50 2.70 1.70 1.00 1.40 19.1 2.6.0 3.60 2.40 6.00 0.60 2.90 3.10 1.60 0.80 19.60 2.10 3.10

1.40 4.70 0.80 13.30 4.60 0.00 1.40 5.30 0.00 21.40

1.70 4.00 0.00 11.50 1.90 0.00 1.50 14.60 0.80 32.40

10.6 6.70 6.50 7.00 7.40 2.70 20.70 2.10 32.20 4.20

2.20 6.70 0.80 0.40 4.30 0.80 1.50 25.00 0.80 5.60

LTR

SCMIJ

JEIM

Intellectual structure of the SCM discipline 161

Table AI.

Table AI. 7 16 7 11 15 8 4 21 8 8 8 21 5 17 17 7 7 18 5 6 12 29 3 21 11 3 3 14 3 12

39 5 15 7 2 12 33 3 43 3

42 8 24 9 4 13 41 7 48 9

33 10 22 12 8 18 38 9 36 6

40 10 107 27 18 102 38 21 42 11

41 8 124 17 5 94 29 18 33 12

34 10 118 14 12 115 27 22 37 9

17 28 15 63 17 11 18 32 20 28

24 31 13 79 21 9 21 31 11 31

16 21 11 82 30 5 17 24 18 27

20 17 18 18 47 7 14 35 8 20

14 10 15 21 51 13 11 24 8 22

10 13 10 28 45 6 13 28 11 23

27 20 68 38 23 120 34 24 32 16

32 14 72 28 15 131 32 18 27 12

28 9 67 19 18 148 37 15 31 15

62 19 62 47 33 78 98 18 71 21

58 15 54 32 21 71 101 21 67 20

62 11 48 25 18 64 112 18 51 14

8 7 2 2 8 6 4 18 2 3

7 5 5 7 7 9 7 24 7 5

4 7 3 4 8 6 3 26 7 5

58 17 55 29 24 47 63 26 93 17

51 12 42 24 13 41 68 21 88 13

44 9 32 19 11 32 52 16 74 10

5 2 2 14 14 2 5 8 7 27

5 6 4 18 10 7 4 15 5 25

4 2 7 28 8 4 2 12 2 34

11.70 6.30 6.20 4.40 3.90 4.60 12.10 4.40 11.50 3.70

14.90 6.20 6.70 3.60 2.40 3.30 12.80 3.60 16.10 5.80

15.70 4.90 4.70 3.00 1.20 3.00 11.00 1.60 15.20 2.00

4.30 18.20 0.80 7.70 5.40 0.80 1.00 6.80 1.00 7.50

2.80 16.20 1.40 6.70 10.40 1.80 2.20 9.10 1.70 3.90

2.80 15.50 2.20 4.60 9.00 2.00 1.30 11.40 2.80 5.40

14.20 6.30 30.20 10.00 8.90 25.90 12.10 10.20 13.40 6.80

14.50 6.20 34.60 6.70 3.00 23.80 9.00 9.10 11.00 7.70

13.70 9.70 37.10 5.90 7.20 28.70 9.00 11.90 13.10 6.10

6.00 17.60 4.20 23.20 8.40 2.80 5.70 15.60 6.40 17.40

8.50 23.80 3.60 31.30 12.80 2.30 6.50 15.70 3.70 20.00

6.50 20.40 3.50 34.60 18.00 1.30 5.70 13.00 6.40 18.20

7.10 10.70 5.10 6.60 23.20 1.80 4.40 17.10 2.50 12.40

5.00 7.70 4.20 8.30 31.10 3.30 3.40 12.20 2.70 14.20

4.00 12.60 3.10 11.80 26.90 1.50 4.30 15.10 3.90 15.50

9.60 12.60 19.20 14.00 11.30 30.50 10.80 11.70 10.20 9.90

11.30 10.80 20.10 11.10 9.10 33.20 10.00 9.10 9.00 7.70

11.30 8.70 21.10 8.00 10.80 37.00 12.30 8.10 11.00 10.10

22.00 11.90 17.50 17.30 16.30 19.80 31.10 8.80 22.60 13.00

20.60 11.50 15.10 12.70 12.80 18.00 31.50 10.70 22.40 12.90

25.00 10.70 15.10 10.50 10.80 16.00 37.30 9.70 18.10 9.50

Matrix Normalised matrix JBL JOM JSCM JEIM SCMIJ LTR JPSM IJLM IJOPM IJPDLM JBL JOM JSCM

162

2006 JPSM IJLM IJOPM IJPDLM JBL JOM JSCM JEIM SCMIJ LTR 2007 JPSM IJLM IJOPM IJPDLM JBL JOM JSCM JEIM SCMIJ LTR 2008 JPSM IJLM IJOPM IJPDLM JBL JOM JSCM JEIM SCMIJ LTR

JPSM IJLM IJOPM IJPDLM

2.80 4.40 0.60 0.70 3.90 1.50 1.30 8.80 0.60 1.90

2.50 3.80 1.40 2.80 4.30 2.30 2.20 12.20 2.30 3.20

1.60 6.80 0.90 1.70 4.80 1.50 1.00 14.10 2.50 3.40

JEIM

1.80 4.60 1.10 7.10 6.10 1.80 1.20 7.60 1.70 16.10

1.60 1.90 2.20 11.80 4.80 1.00 0.70 6.50 0.70 23.00

LTR

20.60 1.80 10.70 1.30 15.50 0.60 10.70 5.20 11.80 6.90 11.90 0.50 20.00 1.60 12.70 3.90 29.60 2.20 10.60 16.80 (continued)

18.10 9.20 11.70 9.50 7.90 10.40 21.20 10.70 29.40 8.40

17.70 8.70 10.10 8.00 6.60 8.00 17.30 8.60 26.20 6.80

SCMIJ

JEIM 25,2

2009 JPSM IJLM IJOPM IJPDLM JBL JOM JSCM JEIM SCMIJ LTR 2010 JPSM IJLM IJOPM IJPDLM JBL JOM JSCM JEIM SCMIJ LTR 1991-1995 JPSM IJLM IJOPM IJPDLM JBL JOM JSCM JEIM SCMIJ LTR 15 34 5 23 9 10 18 23 18 14 21 43 19 27 14 12 27 29 24 12 0 29 0 6 4 0 5 1 0 0

44 14 23 14 7 8 47 7 41 8

39 10 24 12 4 10 40 11 51 6

0 0 0 0 0 0 0 0 0 0

0 24 336 27 14 144 56 5 0 1

42 20 109 18 22 78 34 23 62 8

38 17 95 23 21 95 38 17 47 7

0 132 66 328 149 36 133 55 0 107

17 17 9 61 32 12 15 18 17 28

19 20 12 57 24 15 17 23 16 32

JPSM IJLM IJOPM IJPDLM

0 44 26 195 282 28 72 63 0 121

10 13 12 24 57 13 15 15 8 18

12 9 8 16 52 8 12 28 12 27

0 8 239 50 24 335 72 13 0 7

27 27 84 30 27 117 61 34 37 23

32 21 73 41 31 125 41 37 39 16

0 84 65 151 57 85 310 40 0 56

77 38 77 38 35 77 115 32 70 21

67 31 71 44 39 86 121 27 74 23

0 0 0 5 0 0 1 89 0 0

8 10 9 9 8 10 15 43 12 8

4 9 7 7 6 6 13 32 7 5

0 0 0 0 0 0 0 0 0 0

72 34 65 24 20 37 81 34 110 18

68 28 58 26 19 38 75 25 102 19

0 1 0 28 41 0 0 8 0 125

4 7 5 8 14 8 8 8 4 33

1 4 3 10 18 4 7 6 3 26

0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

12.30 4.60 5.80 4.80 1.70 2.70 9.70 4.50 12.90 3.40

14.70 7.50 6.50 5.40 3.10 2.00 12.10 3.10 11.40 4.50

0.00 9.00 0.00 0.80 0.70 0.00 0.80 0.40 0.00 0.00

6.60 19.60 4.60 10.80 0.60 3.20 6.60 11.70 6.10 6.90

5.00 18.20 1.40 8.80 4.00 2.50 4.60 10.20 5.00 7.90

0.00 7.50 45.90 3.40 2.50 22.90 8.60 1.80 0.00 0.20

13.20 9.10 26.40 7.20 9.40 20.90 8.30 9.30 15.70 4.60

12.70 9.10 26.80 8.80 9.30 24.10 9.80 7.60 13.10 4.00

0.00 41.00 9.00 41.50 26.10 5.70 20.50 20.10 0.00 25.70

5.40 7.80 2.20 24.30 13.70 3.20 3.60 7.30 4.30 16.00

6.30 10.70 3.20 21.80 10.60 3.80 4.40 10.20 4.50 18.10

0.00 13.70 3.60 24.70 49.40 4.50 11.10 23.00 0.00 29.00

3.20 5.90 2.90 9.60 24.50 3.50 3.60 6.10 2.00 10.30

4.00 4.80 2.30 6.10 23.00 2.00 3.10 12.40 3.30 15.30

0.00 2.50 32.70 6.30 4.20 53.30 11.10 4.70 0.00 1.70

8.50 12.30 20.30 12.00 11.60 31.10 14.80 13.80 9.40 13.10

10.70 11.20 20.60 15.70 13.70 31.60 10.50 16.40 10.90 9.00

0.00 26.10 8.90 19.10 10.00 13.50 47.80 14.60 0.00 13.40

24.30 17.40 18.60 15.10 15.00 20.60 28.00 13.00 17.70 12.00

22.30 16.60 20.00 16.90 17.30 21.80 31.10 12.00 20.60 13.00

Matrix Normalised matrix JBL JOM JSCM JEIM SCMIJ LTR JPSM IJLM IJOPM IJPDLM JBL JOM JSCM

22.70 15.50 15.70 9.60 8.60 9.90 19.70 13.80 27.80 10.30

0.00 0.00 0.00 0.30 0.00 0.00 0.00 3.50 0.00 7.20 0.00 0.00 0.00 0.00 0.00 2.90 0.00 0.00 0.00 30.00 (continued)

2.50 4.60 2.20 3.60 3.40 2.70 3.60 17.40 3.00 4.60 0.00 0.00 0.00 0.60 0.00 0.00 0.20 32.50 0.00 0.00

1.30 3.20 1.20 3.20 6.00 2.10 1.90 3.20 1.00 18.90

0.30 2.10 0.80 3.80 8.00 1.00 1.80 2.70 0.80 14.70

22.70 15.00 16.30 10.00 8.40 9.60 19.30 11.10 28.40 10.70

1.30 4.80 2.00 2.70 2.70 1.50 3.30 14.20 1.90 2.80

LTR

SCMIJ

JEIM

Intellectual structure of the SCM discipline 163

Table AI.

Table AI.

14 134 16 109 87 7 31 25 14 32

51 108 22 125 64 12 21 34 22 21

63 143 39 99 66 40 59 105 58 52

42 0 4 14 0 0 0 0 24 0

127 14 57 17 14 28 63 10 79 5

197 47 108 54 25 61 199 37 219 32

195 65 553 99 78 484 166 101 221 47

60 25 591 38 20 427 63 32 52 14

22 25 519 108 15 139 47 27 10 17

93 117 60 342 124 52 88 128 82 146

114 53 61 384 195 49 59 40 38 52

14 134 180 430 130 29 93 104 2 93

66 62 63 107 252 47 65 130 47 110

35 89 22 122 301 48 40 40 26 53

0 77 47 190 306 32 50 25 2 124

146 91 364 156 114 641 205 128 166 82

46 15 283 42 65 721 80 28 44 26

0 15 221 29 17 338 93 6 1 5

326 114 312 186 146 376 547 116 333 99

286 30 162 54 107 317 427 49 99 40

84 36 181 307 61 101 268 84 22 40

31 38 26 29 37 37 42 143 35 26

14 25 14 29 18 15 8 70 9 10

0 1 8 16 0 0 0 102 0 0

293 100 252 122 87 195 339 122 467 77

114 27 60 41 41 64 130 19 168 17

6 0 1 0 0 0 0 2 11 0

19 21 21 78 64 25 26 49 21 145

15 15 7 101 25 5 13 22 4 94

2 30 40 110 16 0 0 34 0 124

13.80 5.90 6.00 4.20 2.50 3.10 11.50 3.50 13.30 3.90

14.70 3.50 4.50 1.80 1.60 1.70 7.00 2.90 14.60 1.50

22.80 0.00 0.30 1.10 0.00 0.00 0.00 0.00 27.90 0.00

4.40 17.90 2.20 7.80 6.60 2.00 3.40 9.90 3.50 6.40

5.90 26.90 1.70 13.10 7.50 0.70 2.30 9.90 4.10 6.30

7.60 29.60 1.30 8.30 13.80 1.10 5.30 6.10 16.30 7.40

13.60 8.10 30.80 7.80 7.90 24.70 9.60 9.50 13.40 5.80

7.00 6.20 46.20 4.00 2.40 25.30 7.00 9.30 9.60 4.20

12.00 5.50 42.60 8.20 2.40 21.50 8.10 6.60 11.60 3.90

6.50 14.70 3.30 26.90 12.50 2.70 5.10 12.10 5.00 17.90

13.20 13.20 4. 80 40.30 22.90 2.90 6.50 11.60 7.00 15.70

7.60 29.60 14.80 32.70 20.60 4.50 16.00 25.40 2.30 21.40

4.60 7.80 3.50 8.40 25.40 2.40 3.70 12.30 2.90 13.50

4.10 22.20 1.70 12.80 35.40 2.80 4.40 11.60 4.80 16.00

0.00 17.00 3.90 14.50 48.40 5.00 8.60 6.10 2.30 28.50

10.20 11.40 20.20 12.30 11.50 32.70 11.80 12.10 10.10 10.00

5.30 3.70 22.10 4.40 7.60 42.80 8.80 8.10 8.10 7.80

0.00 3.30 18.20 2.20 2.70 52.30 16.00 1.50 1.20 1.10

22.80 14.30 17.40 14.60 14.70 19.20 31.50 11.00 20.20 12.10

33.20 7.50 12.70 5.70 12.60 18.80 47.20 14.20 18.30 12.00

45.70 8.00 14.90 23.40 9.70 15.60 46.00 20.50 25.60 9.20

Matrix Normalised matrix JBL JOM JSCM JEIM SCMIJ LTR JPSM IJLM IJOPM IJPDLM JBL JOM JSCM

164

1996-2000 JPSM IJLM IJOPM IJPDLM JBL JOM JSCM JEIM SCMIJ LTR 2001-2005 JPSM IJLM * IJOPM IJPDLM JBL JOM JSCM JEIM SCMIJ LTR 2006-2010 JPSM IJLM * IJOPM IJPDLM JBL JOM JSCM JEIM SCMIJ LTR

JPSM IJLM IJOPM IJPDLM

2.20 4.80 1.40 2.30 3.70 1.90 2.40 13.50 2.10 3.20

1.60 6.20 1.10 3.00 2.10 0.90 0.90 20.30 1.70 3.00

0.00 0.20 0.70 1.20 0.00 0.00 0.00 24.90 0.00 0.00

JEIM

1.70 3.70 0.50 10.60 2.90 0.30 1.40 6.40 0.70 28.30

1.10 6.60 3.30 8.40 2.50 0.00 0.00 8.30 0.00 28.50

LTR

20.50 1.30 12.50 2.60 14.00 1.20 9.60 6.10 8.80 6.40 10.00 1.30 19.50 1.50 11.50 4.60 28.30 1.30 9.40 17.80 (continued)

13.20 6.70 4.70 4.30 4.80 3.80 14.40 5.50 31.10 5.10

3.30 0.00 0.10 0.00 0.00 0.00 0.00 0.50 12.80 0.00

SCMIJ

JEIM 25,2

1991-2000 JPSM IJLM * IJOPM IJPDLM JBL JOM JSCM JEIM SCMIJ LTR 2001-2010 JPSM IJLM * IJOPM IJPDLM JBL JOM JSCM JEIM SCMIJ LTR 1991-2010 JPSM IJLM * IJOPM IJPDLM JBL JOM JSCM JEIM SCMIJ LTR

14 163 16 115 91 7 36 26 14 32

114 251 61 224 130 52 80 139 80 73

128 414 77 339 221 59 116 165 94 105

42 0 4 14 0 0 0 0 24 0

324 61 165 71 39 89 262 47 298 37

366 61 169 85 39 89 262 47 322 37

277 139 1999 272 127 1194 332 165 283 79

255 90 1144 137 98 911 229 133 273 61

22 49 855 135 29 283 103 32 10 18

221 436 367 1484 598 166 373 327 122 398

207 170 121 726 319 101 147 168 120 198

14 266 246 758 279 65 226 159 2 200

JPSM IJLM IJOPM IJPDLM 0 23 460 79 41 673 165 19 1 12

101 192 272 129 158 1107 614 277 1141 220 155 2035 227 450 258 175 75 211 408 120

101 192 151 106 85 647 229 198 553 179 95 1362 105 285 170 156 73 210 163 108

0 121 73 385 588 60 122 88 2 245

696 264 720 698 371 879 1552 289 454 235

612 144 474 240 253 693 974 165 432 139

84 120 246 458 118 186 578 124 22 96

45 64 48 79 55 52 51 404 44 36

45 63 40 58 55 52 50 213 44 36

0 1 8 21 0 0 1 191 0 0

413 127 313 163 128 259 469 143 646 94

407 127 312 163 128 259 469 141 635 94

6 0 1 0 0 0 0 2 11 0

36 67 68 317 146 30 39 113 25 488

34 36 28 179 89 30 39 71 25 239

2 31 40 138 57 0 0 42 0 249

14.80 3.10 3.40 2.00 1.30 1.80 6.80 2.30 14.10 1.90

14.80 3.10 3.40 2.00 1.30 1.80 6.80 2.30 14.10 1.90

22.80 0.00 0.20 0.70 0.00 0.00 0.00 0.00 27.90 0.00

5.20 21.00 1.50 7.80 7.30 1.20 3.00 7.90 4.10 5.20

5.20 21.00 1.50 7.80 7.30 1.20 3.00 7.90 4.10 5.20

7.60 21.10 0.80 5.50 7.60 0.50 7.60 0.50 2.90 3.80

11.20 7.00 39.80 6.30 4.20 24.30 8.60 7.90 12.40 4.00

11.20 7.00 39.80 6.30 4.20 24.30 8.60 7.90 12.40 4.00

12.00 6.30 43.90 6.40 2.40 22.20 8.40 4.70 11.60 2.10

8.90 22.10 7.30 34.30 19.60 3.40 9.60 15.70 5.40 19.90

8.90 22.10 7.30 34.30 19.60 3.40 9.60 15.70 5.40 19.90

7.60 34.40 12.60 36.00 23.20 5.10 18.40 23.30 2.30 23.50

4.10 13.80 3.10 14.20 37.50 3.20 5.90 12.40 3.30 20.40

4.10 13.80 3.10 14.20 37.50 3.20 5.90 12.40 3.30 20.40

0.00 15.60 3.70 18.30 48.904.70 9.90 12.90 2.30 28.80

7.80 6.50 22.00 6.40 7.20 41.40 11.60 8.40 9.30 6.00

7.80 6.50 22.00 6.40 7.20 41.40 11.60 8.40 9.30 6.00

0.00 3.00 23.60 3.80 3.40 52.80 13.40 2.80 1.20 1.40

28.10 13.40 14.30 16.10 12.20 17.90 40.10 13.90 19.90 11.70

28.10 13.40 14.30 16.10 12.20 17.90 40.10 13.90 19.90 11.70

45.70 15.50 12.60 21.80 9.80 14.60 47.00 18.20 25.60 11.30

Matrix Normalised matrix JBL JOM JSCM JEIM SCMIJ LTR JPSM IJLM IJOPM IJPDLM JBL JOM JSCM SCMIJ 3.30 0.00 0.10 0.00 0.00 0.00 0.00 0.30 12.80 0.00 16.70 6.40 6.20 3.80 4.20 5.30 12.10 6.90 28.40 4.70 16.70 6.40 6.20 3.80 4.20 5.30 12.10 6.90 28.40 4.70

JEIM 0.00 0.10 0.40 1.00 0.00 0.00 0.10 28.00 0.00 0.00 1.8 3.20 1.00 1.80 1.80 1.10 1.30 19.40 1.90 1.80 1.80 3.20 1.00 1.80 1.80 1.10 1.30 19.40 1.90 1.80

1.50 3.40 1.40 7.30 4.80 0.60 1.00 5.40 1.10 24.40

1.50 3.40 1.40 7.30 4.80 0.60 1.00 5.40 1.10 24.40

1.10 4.00 2.10 6.60 4.70 0.00 0.00 6.10 0.00 29.20

LTR

Intellectual structure of the SCM discipline 165

Table AI.

JEIM 25,2

166

Figure A1. MDS 1991-1995

Figure A2. MDS 2001-2005

Appendix 2 The MDS for 1991-1995 does not include the positions of JPSM and SCMIJ as they were not published before 1996 and thus their inclusion would skew the existing network of that period

Intellectual structure of the SCM discipline 167

Figure A3. MDS 1991-2000

Figure A4. MDS 1996-2000

JEIM 25,2

168

Figure A5. MDS 2006-2010

Figure A6. MDS 2001-2010

1.00 0.51 0.63 0.35 0.50 0.66 0.94 0.43 0.95 0.23

0.51 1.00 0.294 0.69 0.89 0.18 0.26 0.89 0.22 0.97

IJLM

JPSM IJLM 2001-2010 JPSM 1.00 0.35 IJLM 0.35 1.00 IJOPM 0.30 2 0.09 IJPDLM 20.10 0.57 JBL 20.03 0.69 JOM 0.41 2 0.09 JSCM 0.21 2 0.13 JEIM 0.52 0.87 SCMIJ 0.88 0.05 LTR 0.20 0.93

1991-2000 JPSM IJLM IJOPM IJPDLM JBL JOM JSCM JEIM SCMIJ LTR

JPSM 0.35 0.69 0.32 1.00 0.84 0.16 0.06 0.77 0.08 0.85

0.30 2 0.09 1.00 2 0.16 2 0.11 0.86 0.58 2 0.03 0.39 2 0.17 20.10 0.57 0.16 1.00 0.92 0.06 0.12 0.09 20.04 0.42

IJOPM IJPDLM

0.63 0.29 1.00 0.32 0.37 0.95 0.67 0.35 0.69 0.14

20.03 0.69 20.11 0.92 1.00. 20.11 0.04 0.38 20.16 0.82

JBL

0.50 0.89 0.37 0.84 1.00 0.18 0.05 0.80 0.24 0.99

JBL

JSCM

JSCM

JEIM

0.42 0.89 0.35 0.77 0.80 0.28 0.06 1.00 0.04 0.78

JEIM

0.41 0.21 0.52 20.09 20.13 0.88 0.86 0.58 0.03 0.07 0.12 0.09 20.11 0.04 0.38 1.00 0.35 2 0.40 0.35 1.00 2 0.50 20.04 20.50 1.00 0.51 0.53 0.11 20.20 20.32 0.86

JOM

0.66 0.94 0.18 0.26 0.95 0.67 0.16 20.06 0.18 0.05 1.00 0.37 0.37 1.00 0.28 0.06 0.73 0.93 20.03 20.07

JOM

Correlation matrix

IJOPM IJPDLM

0.88 0.05 0.40 2 0.04 2 0.16 0.51 0.53 0.11 1.00 2 0.15

SCMIJ

0.95 0.22 0.69 0.08 0.24 0.73 0.93 0.04 1.00 2 0.04

SCMIJ

0.18 0.93 2 0.17 0.42 0.82 2 0.20 2 0.32 0.86 2 0.15 1.00

LTR

0.23 0.97 0.14 0.85 0.99 2 0.03 2 0.07 0.78 2 0.04 1.00

LTR

0.003

0.001

0.033 0.128

SCMIJ

0.007

0.002

0.228

JPSM

0.148 0.141 0.034 0.018 0.068 0.013 0.020 0.019 0.031 0.023

0.167 0.284 0.062 0.053 0.121 0.042 0.038 0.047 0.064 0.069

0.112 0.124 0.398 0.243 0.086 0.042 0.063 0.040 0.070 0.079

JPSM SCMIJ IJOPM

0.001

0.010 0.280

0.004 0.001

JEIM

Blocked matrix

0.078 0.093 0.220 0.414 0.116 0.072 0.064 0.060 0.065 0.084

JOM

0.076 0.163 0.005 0.008 0.029 0.076 0.055 0.038 0.038 0.211

0.281 0.199 0.143 0.179 0.401 0.122 0.161 0.117 0.134 0.139

JSCM

0.120 0.116 0.222 0.439 0.084 0.024 0.064 0.047 0.021 0.063

0.041 0.033 0.031 0.032 0.059 0.375 0.142 0.204 0.138 0.124

JBL

0.457 0.256 0.146 0.126 0.470 0.098 0.218 0.182 0.113 0.155

IJLM IJOPM JSCM

0.089 0.054 0.073 0.034 0.096 0.196 0.343 0.199 0.221 0.157

IJPDLM

0.012 0.528 0.236 0.134 0.034 0.038 0.028 0.014 0.030

JOM

0.015 0.011 0.014 0.006 0.010 0.048 0.073 0.244 0.034 0.054

LTR

0.023 0.047 0.037 0.099 0.489 0.183 0.129 0.288 0.156

JBL

0.011

0.047 0.066 0.061 0.292 0.040 JEIM 0.018 0.019 0.010 0.011 0.013 0.018 0.018 0.018 0.032 0.194

0.076 0.023 0.051 0.126 0.184 0.232 0.360 0.233 0.235 2 0.344 IJLM 0.052 0.041 0.015 0.012 0.030 0.073 0.078 0.052 0.210 0.079

0.021

LTR

IJPDLM

Appendix 3. Structural equivalence ( journal correlations and blocked matrices)

Intellectual structure of the SCM discipline 169

Table AII. Matrices

The current issue and full text archive of this journal is available at www.emeraldinsight.com/1741-0398.htm

JEIM 25,2

Organizing for post-implementation ERP A contingency theory perspective

170 Received 12 January 2011 Revised 9 February 2011 2 April 2011 Accepted 2 April 2011

Kevin P. Gallagher Department of Business Informatics, Northern Kentucky University, Highland Heights, Kentucky, USA, and

Vickie Coleman Gallagher Nance College of Business, Cleveland State University, Cleveland, Ohio, USA Abstract

Journal of Enterprise Information Management Vol. 25 No. 2, 2012 pp. 170-185 q Emerald Group Publishing Limited 1741-0398 DOI 10.1108/17410391211204400

Purpose – The importance of involving subject matter experts (SMEs) in ERP implementations is well established. SMEs’ knowledge of business and system processes are critical to conducting gap analyses and configuring enterprise systems. But what happens to SMEs on completion of the implementation phase? Prior qualitative research found that some organizations return SMEs to their old department, which can contribute to knowledge transfer; while other organizations retain the services of SMEs, to assist in ongoing efforts with support and enhancement of the systems. The purpose of this study is to understand post-implementation organizational choices – when SMEs are retained and returned. The aim is to understand these choices relative to the goals of their project. Theoretically, organizations that return SMEs move toward a distributed or hybrid model, while organizations that retain SMEs employ a centralized functional-support structure. In accordance with contingency theory, these structural choices should align with an organization’s goals and measures of success. Design/methodology/approach – This research conceptually builds on prior qualitative research, but is still exploratory in nature. The authors report on findings from an online survey conducted with 65 organizations. The sample included small, medium and large firms. Respondents were key decision-makers in their organization’s ERP initiatives (directors and managers) recruited from two user-group associations (higher education and health care), primarily from the USA and Canada. Descriptive statistics and t-tests (when appropriate) were utilized to analyze and report the findings. Findings – The hybrid structure (neither completely centralized nor decentralized) was utilized most often (66 percent of the organizations in the sample). The organization’s original goals and measures of success did not seem to dictate the final organizational structure, as would be predicted by contingency theory. The authors interpret this as an indication that the choice of structural form is not easily explained based on goals and objectives. They conjecture that devising a structural approach to supporting such a complex inter-functional system such as ERP requires solving many complex simultaneous organizational problems. Research limitations/implications – This research involves a small sample of 65 organizations and is exploratory in nature; hence, it may not be projectable to a larger population. Future research should supplement this study with more industry user groups, expand the sample size, and utilize more advanced statistical methods. Originality/value – Previous research has focused on successfully implementing ERP, neglecting post-implementation design. This study contributes to a growing body of work with regard to post-implementation design, taking into consideration SMEs and reporting structure, goals, and measures of success utilizing contingency theory as the backdrop. Keywords Enterprise resource planning (ERP), Post-implementation, Contingency theory, Organizational structures, Subject matter expert (SME), Manufacturing resource planning, Contingency planning Paper type Research paper

1. Introduction How best to organize the IT function is a long-standing question for researchers and practitioners alike (King, 1983; von Simson, 1990). For ERP projects, and for post-implementation support, this issue is critically important, especially with regard to the use of subject matter experts (Worrell et al., 2006). However, until recently (e.g. Worrell et al., 2006; Zhu et al., 2010), research has primarily focused on implementation efforts rather than post-implementation. Subject matter experts (SME) are invaluable contributors to the success of ERP installations, whose knowledge of business practices and system processes are critical to configuring enterprise systems (Volkoff et al., 2004). As a result, project managers often plan carefully and petition strongly to secure the best and the brightest employees from each of the functional business units that will be impacted by an implementation project (Gallagher and Gallagher, 2006). SMEs then become key members of the implementation team. However, as the project moves into post-implementation, organizations must determine how the SMEs will be utilized and managed once the project ends. In this research, we view this question as one of organizational structure, being either centralized, decentralized or a hybrid form. For example, the retention of SMEs in an ongoing support organization is a centralized form, while their working from various functional departments to support ongoing ERP efforts defines a distributed, or hybrid organizational form. Given the critical role SMEs play as members of an implementation team and their potential ability to contribute to post-implementation efforts, a number of steps can take place to secure this talent. First, they can become permanent members of a centralized post-implementation support organization. Or, they can be returned to their functional roles, thereby becoming part of a distributed or hybrid form of the organization. In either situation, SMEs could contribute to future efforts, but the resulting structure could offer differing advantages and disadvantages for both the organizations and the individuals. For example, some suggest that returning SMEs to their original roles and responsibilities, presumably in their original department, would be most favorable to facilitate knowledge transfer (Volkoff et al., 2004) (i.e. a decentralized or hybrid model). Alternatively, retaining SMEs in a formal capacity to work on ERP related projects would facilitate coordination efforts related to system enhancements and reengineering (Worrell et al., 2006) (i.e. a centralized model). To explore these choices, we undertook a study to investigate the types of organizational forms chosen once they moved into the post-implementation phase, and the reasons for these choices. We adopted a contingency theory approach (Brown and Magill, 1994). Contingency theory would predict that post-implementation design would be based on the organization’s goals and objectives (Sambamurthy and Zmud, 1999). For example, if organizations view the goals of ERP as simply an update to technology, or alternatively as an opportunity for process improvements or business process reengineering, then those differing goals may yield different design choices for the support organization. This research reports on findings from survey research conducted with 65 organizations concerning their decisions regarding post-implementation support. We also investigate the implications that various pre- and post-implementation goals and tactics hold for creating a post-implementation structure. First we provide some theoretical background on the role that organizational structure plays in the ongoing

Postimplementation ERP 171

JEIM 25,2

172

management and staffing of the information systems function. The utilization of SMEs in ongoing post-implementation efforts is an important consideration. Next, we outline the research method and sampling, followed by its findings, analysis and discussion. The conclusions, limitations and opportunities for future research are then discussed. 2. Theoretical background The research we undertake is exploratory, given that our research seeks to understand what firms are doing (and is not meant to be predictive in nature). We chose to undertake an organizational structure approach in this research. This approach is well established in the IT literature (King, 1983; Brown and Magill, 1994; Simon et al., 1954; Sambamurthy and Zmud, 1999) and easily comprehended by IT practitioners for who we hope to inform with this research (Boynton et al., 1993). We apply the concepts of structural contingency theory to understand how ERP organizations are structured in terms of their positioning of human resources (e.g. SMEs). Thus, we build on a well-established organization theory in order to explore how support functions for ERP systems are organized post-implementation. We also build on existing work in other functional areas, such as accounting (Simon et al., 1954) and preliminary work in this emerging research area (Worrell et al., 2006). The staffing of cross-functional activities, such as information systems implementations, often relies on personnel from various functional or operational departments who serve as SMEs and act as horizontal mechanisms in organizations (Brown, 1999; Galbraith, 1994). These arrangements commonly occur during the configuration and implementation of ERP systems (Brown and Vessey, 2003) such that SMEs come together (either permanently or temporarily) to inform and guide the design of the system. That is, these and other information systems efforts rely on structural mechanisms, such as cross-functional teams and liaisons, to support the multi-functional nature of the work processes they are automating (Markus et al., 2000). This allows the implementation project to benefit from the knowledge and experience of personnel who understand the existing design and function of the systems that the ERP software is intended to replace. These SMEs are also in a position to inform the configuration of the new system being implemented. Not surprisingly, many ERP efforts try to recruit the most knowledgeable and talented SMEs they can (Gallagher and Gallagher, 2006; Worrell et al., 2006). Organizations also try to retain these personnel, sometimes on a full time basis, for the duration of the project. Furthermore, projects often try to co-locate or centralize the personnel working on an implementation project, and may offer incentives to SMEs to work on the project. They also may provide funding to their functional departments to back-fill for the personnel on-loan so that work can be completed while the SME is committed to the ERP project (Worrell et al., 2006). As an ERP project concludes, and the post-implementation structure is contemplated, the ongoing role of the SMEs also becomes an issue. 2.1 Organizing IT Organizational designs within the IS function is a well-established area of research (Boynton et al., 1993; Brown and Magill, 1994; King, 1983). The question is motivated by the desire for organizations to align the IT function with overarching organizational goals (Brown and Magill, 1994). From a contingency theory approach, different ways of

organizing promote different organizational capabilities (Brown and Magill, 1994; Galbraith, 1994). A department that manages and supports information systems can more effectively support the organization if it is structured in a way that aligns with the overall organization’s priorities (Brown and Magill, 1994). Structural theories identify three general models; centralized, decentralized, and the hybrid design (Brown and Magill, 1994; Sambamurthy and Zmud, 1999). Each of these offer advantages and disadvantages for an IS function, or in this case, an ERP support organization. The literature defines each of these structures according to the degree of control over the management of resources (Sambamurthy and Zmud, 1999). While in the centralized model an IT department controls all aspects of the system, the decentralized model generally allocates a significant amount of control over IT resources to different functional or operational units in a business. The hybrid approach tries to gain benefits of both models by sharing control of resources, for example allocating control of software functionality to various departments where needs may differ (Brown and Magill, 1994; Sambamurthy and Zmud, 1999). For each of these structural models and reporting relationships, we see an application to the role of SMEs in a post-implementation support organization. In a centralized model we find the retention of personnel (including but not limited to SMEs) within a post-implementation organization. As contingency theory would predict, this option will offer the advantages of increased economies of scale (von Simson, 1990), the ability to minimize conflicts between organizational and departmental goals (King, 1983), increased organizational learning (von Simson, 1990), and the ability to establish and promote career paths for personnel (von Simson, 1990). Alternatively, a decentralized model would distribute both technical and subject matter personnel across their respective functional or operational departments. The advantages of a decentralized structure are that it puts decision-making authority directly in the hands of line managers (Brown and Magill, 1994), thereby aligning system design and departmental needs (von Simson, 1990). It also increases absorptive capacity, given that those who work on ERP solutions continue to acquire and retain knowledge of their respective department’s requirements (Sambamurthy and Zmud, 2000). However, this decentralized structure undermines many benefits inherent in the centralized design of an ERP system (Markus and Tanis, 2000). It may also undermine the strong sense of unity and identity developed during the implementation project that can foster productivity (Gallagher and Gallagher, 2006). Thus, we would not expect to find the occurrence of the decentralized structure in many ERP organizations, with the exception of very large organizations that share a common system across multiple sites (Markus et al., 2000). We would expect to find many organizations with hybrid structures. Such structures are found in ERP organizations when an organization retains only a small technical team of personnel, but then continues to depend on SMEs positioned in various functional or operational departments. The benefits of this structure are increased alignment of technology and business (Brown and Magill, 1994) and greater opportunities to exploit the advantages of centralization without losing the flexibility of decentralization (von Simson, 1990). The advantage of a hybrid or distributed model is that these structures generally place greater control and thus greater decision-making authority in the business units (Sambamurthy and Zmud, 2000).

Postimplementation ERP 173

JEIM 25,2

174

As a result, this model can help to align departmental needs with IT efforts. Working more closely with users in a functional department, SMEs in a distributed model can promote IT-business innovation, identify new opportunities, and enable knowledge transfer (Volkoff et al., 2004). Research has shown that SMEs facilitate knowledge transfer by taking ideas from the initial implementation (and subsequent enhancement projects) back to the business units through both formal and informal mechanisms ( Jones et al., 2008). In essence, they become project liaisons and advocates given that they were representatives and the “voice” of the functional department. We assume that post-implementation design decisions are made rationally with the expectation of achieving intended performance outcomes. Ultimately, we expect many of the benefits of various structural models to also apply to the structures we define for post-implementation ERP organizations. Since this research is exploratory, we do not formulate hypothesis for the purpose of testing relationships, but instead examine the existence of relationships between organizational goals and organization design to understand if relationships exist and how they may be related (Brown and Magill, 1994). 3. Method Initial qualitative research was conducted to explore the question of how ERP projects organized for post-implementation and how they positioned the role of SMEs within their organizing structures, as explained previously (Worrell et al., 2006). In that study a review of the literature was conducted to identify relevant content areas and to determine a theoretical framework for examining these questions. Justification for a second more quantitative study was based on the nature of the findings in the initial qualitative research, as that research found that managers had extensively examined the questions of post-implementation structure and had arrived at different decisions. Approximately half the organizations in the initial qualitative study choose a centralized structure and half choose a distributed structure. Examination of the initial goals of the ERP implementation showed some promise as an explanation for the different choices made by the organizations. The current follow-up study using survey methods offered the ability to examine a larger population of organizations and to understand structural choices and the relationship of project goals to post-implementation structure. Construct development was based on both the earlier qualitative research and on an ongoing review of pertinent literature. The preliminary design of the survey was piloted with both academic experts and key informants who were experienced project leaders for ERP implementations and ongoing support efforts. The final validated survey was structured around eight different areas of inquiry as follows: (1) Organizational demographics (organization size, industry, region, etc.). (2) Modules purchased and implemented (phases of implementation). (3) Original goals and measures of success on a 1-7 scale. (4) Incentives and promises made to achieve goals. (5) Implementation staffing and structure. (6) Post-implementation staffing and structure. (7) Current goals (after implementation phase) on a 1-7 scale. (8) Individual demographics (education, degree, etc.).

Specific details about the wording of each question, and the scales and anchors used, are addressed in the detailed findings, which follow. Participation in the survey was facilitated by relationships with two ERP software user groups. These relationships were established after the findings from the initial qualitative research (Worrell et al., 2006) were presented at one of the user group’s national meeting. The lead author was solicited to conduct a quantitative study. After this initial contact, another organization also requested that the data collection be replicated among their user group. As such, two user group associations were utilized in order to recruit key decision makers to respond to the survey. The organizations in the user groups were from higher education organizations and health care organizations. Within the education user group, a total of the 544 invitations to participate were emailed to members designated as “key contacts”. The invitation was sent via the president and a link to the survey was provided to the main contacts from 520 member organizations. A total of 49 organizations participated from the higher education user group (e.g. having complete data for purposes of this paper) for a response rate of 9.4 percent. Among the health care user group members, all 2,785 individual members were emailed and invited by the president to participate. However, they were screened and asked to forward the survey link on to a “key decision maker”. A total of 17 responded with complete data out of the 184 member organizations, for a response rate of 9.2 percent (Note that among the health care user group respondents, participants were asked to provide their contact information – so that we could screen for duplicate organizations. However, of the four cases that were missing this information, the data were sorted to determine if perhaps someone else from their organization had also answered the survey. None of the key demographics was similar and all four cases were retained.) Respondents were involved at high levels within their organizations such that 9.7 percent were project executives or sponsors of the ERP system, 72.6 percent were project directors or managers, and 17.7 percent stated themselves as “Other” (e.g. business systems analysts, functional experts, specialists, etc.). A mix of organizations responded. For example, 66 percent were public and 34 percent were private. By region, the largest representation was from the Northeast (22.6 percent) and the West (22.6 percent), followed by the Midwest (17.7 percent), the Southwest (12.9 percent), and the Southeast (9.7 percent). A small portion were international (6.5 percent Canada, 3.2 percent Africa, 3.2 percent Asia, and 1.6 percent Western Europe), actually representing nine out of the total number respondents who reported their institution’s primary location. Respondents were also asked to report on the number of employees at their institution (as measured in full-time equivalents – FTEs). Again, our sample includes a mix, with 18.5 percent having fewer than 1,000 employees, 18.5 percent with 1,000 to 2,499 employees, 21.5 percent with 2,500 to 4,999, 20.0 percent with 5,000 to 9,999, and 21.5 percent with 10,000 or more employees. Institutions were primarily using PeopleSoft (87.3 percent), yet a few others were using Oracle (4.8 percent), SAP (4.8 percent) and Siebel (3.2 percent). As highlighted in Figure 1, the phases of their implementation were varied by module; however, the majority had gone live with their financial management modules (46 institutions) and their human capital management modules (44 institutions). (Note that campus

Postimplementation ERP 175

JEIM 25,2

176

Figure 1. Status of ERP system models organizations

solutions did not apply to health care institutions yet it has been implemented by a large part of our sample, which is, as noted previously, skewed toward educational institutions). Data were downloaded from the on-line survey software and analyzed in Excel and SPSS when relevant. 4. Findings Our survey included questions regarding the structure and goals of each of the ERP post-implementation support organizations. The first section discusses findings related to structure of the post-implementation organization. The next section examines the goals and measures of success for each project, both for the organization’s initial implementation project and its ongoing post-implementation support efforts. In the final section, we analyze the relationship between the various goals and measures of success relative to the structural forms chosen for post-implementation. 4.1 Structure of the post-implementation organization We found that the post-implementation support structures fell primarily into two dominant forms: a centralized cross-functional team structure (27 percent) and a distributed ad hoc/hybrid structure (66 percent). Only 5 percent described their organization as decentralized. Specifically, we asked “How would you generally describe the organizational structure for Post-Implementation ERP?” Our data included completed questions by 62 of our 65 respondents (see Table I). When analyzing organizational structure within industry, we find that educational institutions from our sample tend to be more centralized, whereas health care institutions tend to be hybrid compared to education. Yet, the structure in both

industry sectors skews toward a Hybrid model. (see Table II for breakdown by industry sample). In addition, we analyzed organizational structure by the overall size of the organization. Company size did not appear to be related to organizational structure (table available on request). We also asked the question of structure in another way, using a scale of 1 ¼ centralized to 7 ¼ decentralized, intended to understand the degree of centralization. This format acknowledges that structure, especially in the hybrid form, is often viewed along a continuum between centralization and decentralization. Specifically, we asked, “In reference to your previous answer, please indicate the degree to which control of ERP in your organization is centralized or decentralized”. In addition, we asked, “In your opinion, what would be the most effective Post-Implementation design for your organization?”. We call the later the respondent’s “most effective” or ideal structure versus their “current”. Figure 2 shows the results from these two questions. Results for each response are shown side by side. In general, the results indicate that our respondents see a centralized structure as ideal. However, there also appears to be a “grass is always greener” mentality. Although the general trend is towards preference for a more centralized model, there also appears to be a preference for less ambiguity in the middle of the 1-7 scale and a tendency to want more in terms of centralization if they skew centralized, and prefer more decentralized if they are only somewhat decentralized. We also asked respondents to identify who had executive responsibility for the ERP project. Interestingly, when structure is cross-tabulated by titles of those with overall executive responsibility for the ERP project, even those describing their institution as a “hybrid” show that the VP of Information Technology or the CIO is primarily responsible Organizational structure

n

Percent

Centralized – application, development, support controlled by ERP department Decentralized – application, development, support controlled by functional BU’s Hybrid – application, development, and support controlled and shared by both the ERP dept. and functional BU’s Other Total

17

27.4

3

4.8

41

66.1

1 62

1.6 100.0

Structure Centralized Decentralized Hybrid Other Total

Healthcare (n ¼ 16) (%)

Education (n ¼ 46) (%)

Total (n ¼ 62) (%)

12.5 6.3 81.3 0.0 100.0

32.6 4.3 60.9 2.2 100.0

27.4 4.8 66.1 1.6 100.0

Postimplementation ERP 177

Table I. Structure for post-implementation ERP

Table II. Structure by industry sector

JEIM 25,2

178

Figure 2. Current versus most effective structure

(as shown in Table III). This would seem to indicate that a hybrid model still relies primarily on control by IT management, despite its reliance on resources distributed across many other functional areas. 4.2 Project goals and measures of success Respondents were asked to identify their original goals for the ERP project based on six pre-determined criteria, allowing room for “other” goals, if necessary. Specifically, they were asked, “Thinking about your original goals for the ERP project, please rate the following with regard to importance”. Respondents used a scale of 1 to 7, with 1 representing “not at all important”, 7 representing “very important”, and 4 anchored as “neutral”. Mean calculations for the responses are shown in Table IV. Replacement of old technology was the most important original goal, followed by process improvement and business process reengineering. All three are reported with a mean of above 4 (a neutral response) on the 1 to 7 scale. Alternatively, cost and staff

Structure by overall executive responsibility for ERP in organization

Table III. Structure by overall executive responsibility for ERP in organization

President/Chancellor/CEO Provost/VP Academic Affairs/COO VP Finance/VP Administration/CFO VP Information Technology/CIO Other Total

Total Centralized Decentralized Hybrid (n ¼ 41) (n ¼ 61) (n ¼ 3) (n ¼ 17) (%) (%) (%) (%) 5.9 17.6 23.5 52.9 0.0 100.0

0.0 0.0 33.3 66.7 0.0 100.0

4.9 7.3 26.8 56.1 4.9 100.0

4.8 9.7 27.4 54.8 3.2 100.0

reduction, reorganization or change, and Y2K all averaged below the “neutral” point of 4 on the scale. In addition, thinking about their original ERP project in the implementation phase, respondents were asked to rate six variables on a 1-7 scale with regard to importance to their project’s measurement of success. Specifically, we asked, “Please rate the following with regard to importance to your measurement of success in the original ERP project”. Mean scores are outlined in Table V. In this question, all the items outlined in the following have mean scores above the “neutral” point of 4 on the scale. Time, cost, quality and perceived performance (user satisfaction) are well-established measures of success in the IS literature (Atkinson, 1999). Since many ERP projects focus on minimizing customization to stay on time and within budget, and to lower long-term maintenance costs, we also included this as an option (i.e. often referred to “vanilla” in ERP). We also included automation of processes, since a new system would offer new opportunities for applying information technology. As shown in Table V, completion within budget and on time were rated the highest in importance on a 1-7 scale. Next, we shifted focus slightly and asked respondents to consider their ongoing post-implementation support of the modules currently in production. A total of four variables were rated with regard to their current goals. Specifically, we asked, “Now thinking about those modules that are implemented, please rate the following in order of importance of current goals”. Respondents used a scale of 1 to 7, with 1 representing “not at all important” and 7 representing “very important” to their current goals. Process improvements had the highest mean. Means are outlined in Table VI. Next, we asked respondents to report about the measures of success and again rate them on a scale of 1 to 7, as reported in Table VII. Specifically, we asked, “Thinking about the Post Implementation project, please rate the following in order of importance with regard to measures of success of your ERP project”. In this question, timely Original goals for ERP Project

n

Mean

SD

Replace old technology Process improvement Business process reengineering Cost reduction/staff reduction Structural reorganization/change (merger, acquisition, etc.) Resolve Y2K

63 64 63 61 62

6.17 5.77 5.27 3.79 3.03

1.144 1.231 1.405 1.450 1.967

60

2.83

2.395

Measurement of success

n

Mean

SD

Complete within budget Complete on-time Maximize user satisfaction Maximize quality assurance Minimize customization Automation of processes

64 64 64 64 64 63

6.09 5.91 5.42 5.31 5.27 5.25

1.137 1.050 1.257 1.489 1.417 1.379

Postimplementation ERP 179

Table IV. Original goals for ERP project – during/ pre-implementation

Table V. Measurement of success – during/ pre-implementation

JEIM 25,2

180

response to support issues was the most important measure of success. Budgeting issues had the lowest mean score. The change in goals and measures of success are notable. Improvements in business processes and reporting become important goals as organizations enter a post-implementation phase (whereas completing on time and within budget were most important during implementation). In addition, user needs become more important measures for success in post-implementation, while budget and customization issues become less important. 4.3 Structure by project goals and measures of success In addition, we conducted t-tests to determine if the importance of goals were different for those respondents who identified their organization as primarily centralized versus hybrid. Although the rank order of original goals are the same for centralized and hybrid organizations, it appears that Business Process Reengineering and Resolving Y2K were rated as somewhat more important in Hybrid organizations (e.g. see t-tests in Table VIII). When considering current goals (post-implementation), process improvements are most important for both centralized and hybrid organizations. (Note that t-tests were

Table VI. Current goals for the ERP project – post-implementation

Table VII. Measures of success – post-implementation

Current goals for the ERP Project

n

Mean

SD

Process improvements Improve reporting Business process reengineering Cost reduction

64 64 64 64

5.98 5.78 5.16 4.92

1.000 1.201 1.405 1.384

Measures of success

n

Mean

SD

Timely response to support issues User satisfaction Automation of processes Manage to a fixed budget

64 64 64 64

6.16 6.08 5.81 5.44

0.912 0.948 1.067 1.207

Centralized (n ¼ 16-17)

Hybrid (n ¼ 39-40)

6.29 5.47 4.94 * 3.56 3.53

6.18 5.73 5.42 * 3.90 2.95

2.25 * *

3.10 * *

Original goals for ERP Project – during/pre-implementation

Table VIII. T-test – mean differences in original goals for ERP project – during/ pre-implementation (centralized vs hybrid)

Replace old technology Process improvement Business process reengineering Cost reduction/staff reduction Structural reorganization/change (merger, acquisition, etc.) Resolve Y2K Notes: *p , 0.05; * *p , 0.01

conducted and there were no differences between means for hybrid versus centralized on the goals listed in Table IX). Mean scores of original (pre-implementation) measures of success (for those describing their company as centralized versus hybrid) are listed in Table X. T-tests did not indicate significant differences between mean scores based on type of organizing structure. However, please note that the rank is very similar for both types of organizations. In addition, we examined mean scores of current (post-implementation) measures of success (by centralized versus hybrid organizations). T-tests did not indicate differences in means based on type of organization and the rank order of mean scores is virtually the same for both types of organizing structures (as highlighted in Table XI).

Postimplementation ERP 181

5. Analysis and discussion The implementation of an ERP project is a costly, complex task (Saatcioglu, 2009) riddled with high failure rates. Despite the challenges, the allure of the benefits have left the ERP market nearly saturated. Hence, researchers have recently begun to explore the post-implementation design, structure, and relevant measures of success (e.g. Worrell et al., 2006; Zhu et al., 2010). The objectives of this research were exploratory in nature. We set out to understand how post-implementation ERP support organizations are structured. We approached Current goals for the ERP Project – post-implementation Process improvements Improve reporting Business process reengineering Cost reduction

Measurement of success project – during/pre-implementation

Centralized (n ¼ 17)

Rank order

Hybrid (n ¼ 41)

Rank order

6.06 5.88 5.06 5.06

1 2 3 3

5.95 5.71 5.27 4.80

1 2 3 4

Centralized (n ¼ 16-17)

Rank order

Hybrid (n ¼ 41)

Rank order

5.88 5.71 5.18 5.06 4.88 4.88

1 2 3 4 5 5

6.17 6.05 5.49 5.39 5.41 5.34

1 2 3 5 4 6

Current measurement of success – post-implementation

Centralized (n ¼ 16-17)

Rank order

Hybrid (n ¼ 41)

Rank order

Timely response to support issues User satisfaction Automation of processes Manage to a fixed budget

6.18 5.82 5.76 5.41

1 2 3 4

6.17 6.12 5.78 5.44

1 2 3 4

Complete within budget Complete on-time Maximize user satisfaction Maximize quality assurance Minimize customization Automation of processes

Table IX. Rank order – mean scores of current goals for the ERP project – post-implementation (centralized vs hybrid)

Table X. Rank order – means scores of original measurements of success – during/ pre-implementation (centralized vs hybrid)

Table XI. Rank order – means scores of current measurements of success – post-implementation (centralized vs hybrid)

JEIM 25,2

182

this topic applying guidance from prior IS literature and a well-established theoretical framework. Using structural contingency framework, we asked respondents to identify the original goals and measures of success for their organization’s ERP project, as well as their current goals and measures for success (now that they had moved into the post-implementation phase). First we examined the question of structure by asking respondents to indicate if their support organization was centralized, decentralized, or a hybrid form. As expected, we found few instances of decentralization. Given the nature of ERP as a highly integrated system with a centralized database design, it would seem likely that we would only see a decentralized organizing form in the largest of organizations. We found that the hybrid structure was utilized most often among the organizations in our sample. We did not presuppose any expectations, given that prior research in this area revealed no dominant form, although that study sample was quite small (Sambamurthy and Zmud, 1999). In fact, the nature of ERP as a technology that integrates work processes across functional areas of the organization offers arguments for both the centralized and distributed forms. We believe that finding greater than 66 percent with hybrid structures emphasizes that involvement of users (e.g. SMEs) and their subsequent knowledge of the business contributes greatly to the alignment of ERP with an organization’s objectives. However, once recruited onto an ERP project, retention of SMEs at the end of a project can also offer the ability to align goals, while simultaneously coordinating efforts to become more highly effective. Thus, the centralized form was found in 27 percent of organizations. The results found some differences across the two industries, with healthcare organizations in our sample employing the hybrid form more often than educational institutions. Nevertheless, both industries in our sample skewed toward the hybrid form. This finding demonstrates opportunities for future research to examine the relationship between industry and IT structures. On average, organizations in our sample would like to be more centralized, but a surprising number indicated they would also like to be more decentralized. This raises questions as to a general desire in ERP organizations to be structured differently, which may not be too surprising given the existing benefits of both forms and the inevitable compromise that either choice presents. In our sample, the executive who was responsible for ERP had no relationship to the structural form adopted, although we did find that IT managers were in control of the projects in decentralized organizations (i.e. took charge in these complex situations). In examining how organizations prioritized goals, we found that goals did not change much as organizations moved from implementation into the post-implementation phase; however, the measures of success were reordered to emphasis responsiveness and user needs. Specifically, with regard to goals, we found that process improvements ranked highest among original goals and cost reductions ranked lowest. Again, these findings did not change much from pre- to post-implementation. We also examined the relationship between goals and structure and found that only “business process reengineering” and “resolving Y2K issues” showed statistically significant differences between those adopting different organizing forms. Those with the hybrid form gave a higher prioritization to these two issues. On one hand, this finding is in line with what one might expect, such that resolving Y2K, for example is a

temporary condition. Once this issue is resolved, SMEs can be returned to their functional roles or to that of a hybrid design rather than a centralized design. On the other hand, a reengineering effort would potentially benefit from creating a dedicated (centralized) organization to focus on continued efforts with process redesign, independent of the varying priorities of the different functional areas. However, our findings indicate that organizations still resulted in a hybrid even when reengineering was a priority. When considering their original measures of success, we found that project management issues were at the top of the list in priorities (e.g. being on-time and within budget). User issues and quality assurance were not as high in importance. However, post-implementation success measures were somewhat different, such that responding to users and user satisfaction topped the list of success measures. The changes in success measures seemingly fits with the urgency in organizations to make sure the implementation is a success as measured in terms of time and cost. However, quality becomes the higher priority as the organization begins to utilize the system daily. Perhaps of primary importance, particularly in light of contingency theory, is the fact that the organization’s original goals and measures of success did not seem to dictate the final organizational structure. We interpret this finding as an indication that the choice of structural form is not easily explained based on goals and objectives, as contingency theory might predict. We conjecture that devising a structural approach to supporting such a complex inter-functional system such as ERP is one that requires solving many complex simultaneous organizational problems. 6. Limitations, conclusions and future research This research undertook an exploratory methodology to understand the objectives, structure and staffing of post-implementation ERP organizations. We surveyed key contacts in 65 organizations (contacted through the software user group). The sample represents two industry sectors, higher education and healthcare. This study has several limitations. Only two industries were examined and the responses of just 65 organizations were reported on in this paper. This limitation affected our ability to apply more advanced statistical methods in our analysis, and perhaps our ability to find statistical significance in some of the methods we did apply. The findings reported in this paper do, however, establish the basis for additional analysis and help to set an agenda for future research in this important area. The question of what influences the choice of organizational structure in post-implementation remains open, as too does the question of what form offers the best performance given the goals of the organization. Each of the organizational design models discussed has inherent strengths and weaknesses for an ERP support organization. By retaining key functional personnel, the centralized model leverages organizational knowledge developed during the implementation, improving the organization’s capabilities to undertake future initiatives, such as upgrades, business process improvements and other enhancements. This model can also aid perceptions of legitimacy of the ERP unit and provide enhanced access to organizational resources. One might have expected that original goals of reengineering and reorganizing would lead to a more centralized model; however, our data does not support this notion. Alternatively, the distributed model returned functional SMEs to the home units after the implementation. However, the SMEs may still be expected to be involved in

Postimplementation ERP 183

JEIM 25,2

184

future initiatives on an ad hoc basis. This lower cost approach offers the advantage of designating a liaison between the ERP project and a functional unit, thus enhancing knowledge transfer. Additionally, this model ensures that business process knowledge remains current. It also provides functional units with a greater ability to influence future decisions in enhancements and process improvements. While the majority of the organizations we surveyed described their post-implementation ERP support organization structure as hybrid, they were, when reported along a continuum, more centralized than decentralized. Furthermore, respondents reported on average that the ideal structure for their organization would be more centralized than the current structure. We also found that the organizations we surveyed reported a shift in both goals and how they measure success as they moved from their implementation projects into the post-implementation phase. Further analysis will be required to see if a relationship exists between an organization’s response and support for user needs and automation of processes and the existence and desire for more centralized structures. Furthermore, future research should explore other contingencies, as well as how the degree of customization and degree of centralization may or may not contribute to success factors. Although one may assume that strategic goals would dictate structural design, driving forces are indeed more complicated. As is the case with knowledge management systems, post-implementation designs are likely influenced by other factors such as culture, market characteristics, size of the institution (Supyuenyong et al., 2009) and political dynamics within the institution. Future research should continue to explore the mechanisms that determine post-implementation organizational design, beyond educational and health care institutions, to also include a spectrum of sizes of organizations including small, medium (Esteves, 2009) as well as large institutions. Researchers are just beginning to scratch the surface with this topic (e.g. Worrell et al., 2006; Zhu et al., 2010) and our research contributes to this growing body of work. References Atkinson, R. (1999), “Project management: time, cost and quality, two best guesses and a phenomenon, it’s time to accept other success criteria”, International Journal of Project Management, Vol. 17 No. 6, pp. 377-82. Boynton, A.C., Victor, B. and Pine, J.B. (1993), “New competitive strategies: challenges to organizations and information technologies”, IBM Systems Journal, Vol. 32 No. 1, pp. 40-60. Brown, C. (1999), “Horizontal mechanisms under differing IS organization contexts”, MIS Quarterly, Vol. 23 No. 3, pp. 421-54. Brown, C.V. and Magill, S.L. (1994), “Alignment of the IS functions with the enterprise: toward a model of antecedents”, MIS Quarterly, Vol. 18 No. 4, pp. 371-403. Brown, C. and Vessey, I. (2003), “Managing the next wave of enterprise systems: leveraging lessons from ERP”, MIS Quarterly Executive, Vol. 2 No. 1, pp. 65-77. Esteves, J. (2009), “A benefits realization road-map framework for ERP usage in small and medium-sized enterprises”, Journal of Enterprise Information Management, Vol. 22 Nos 1-2, pp. 25-35. Galbraith, J.R. (1994), Competing with Flexible Lateral Organizations, Addison-Wesley Publishing Company, Reading, MA.

Gallagher, V.C. and Gallagher, K.P. (2006), “Employee perceptions of role changes in ERP projects”, paper presented at the Annual Meeting of the Academy of Management, August, Atlanta, GA. Jones, M.C., Zmud, R.W. and Clark, T.D. Jr (2008), “ERP in practice: a snapshot of post-installation perception and behaviors”, Communications of the Association of Information Systems, Vol. 23 No. 25, pp. 427-62. King, J. (1983), “Centralized versus decentralized computing: organizational considerations and management options”, Computing Surveys, Vol. 15 No. 4, pp. 319-49. Markus, L.M. and Tanis, C. (2000), “The enterprise systems experience – from adoption to success”, in Zmud, R.W. (Ed.), Framing the Domains of IT Research: Glimpsing the Future Through the Past, Pinnaflex Educational Resources, Cincinnati, OH, pp. 173-207. Markus, L.M., Tanis, C. and van Fenema, P.C. (2000), “Multisite ERP implementations”, Communication of the ACM, Vol. 43 No. 4, pp. 42-6. Saatcioglu, O.Y. (2009), “What determines user satisfaction in ERP projects: benefits, barriers or risks?”, Journal of Enterprise Information Management, Vol. 22 No. 6, pp. 690-708. Sambamurthy, V. and Zmud, R.W. (1999), “Arrangements for information technology governance: a theory of multiple contingencies”, MIS Quarterly, Vol. 23 No. 2, pp. 261-91. Sambamurthy, V. and Zmud, R.W. (2000), “Research commentary: the organizing logic for an enterprise’s IT activities in the digital era – a prognosis of practice and a call for research”, Information Systems Research, Vol. 11 No. 2, pp. 105-14. Simon, H.A., Kozmetsky, G., Guetzkow, H. and Tyndall, G. (1954), Centralization vs Decentralization in Organizing the Controller’s Department, Scholars Book Co., Houston, TX. Supyuenyong, V., Islam, N. and Kulkarni, U. (2009), “Influence of SME characteristics on knowledge management processes: the case study of enterprise resource planning service providers”, Journal of Enterprise Information Management, Vol. 22 Nos 1-2, pp. 63-80. Volkoff, O., Elmes, M. and Strong, D. (2004), “Enterprise systems, knowledge transfer and power users”, Journal of Strategic Information Systems, Vol. 13 No. 4, pp. 279-304. von Simson, E. (1990), “The ‘centrally decentralized’ IS organization”, Harvard Business Review, July-August, pp. 2-7. Worrell, J., Gallagher, K. and Mason, R. (2006), “Explaining the structure of post-implementation ERP teams”, Proceedings of the 12th Annual Americas Conference on Information Systems, Acapulco. Zhu, Y., Li, Y., Wang, W. and Chen, J. (2010), “What leads to post-implementation success of ERP? An empirical study of the Chinese retail industry”, International Journal of Information Management, Vol. 30 No. 3, pp. 265-76. Corresponding author Kevin P. Gallagher can be contacted at: [email protected]

To purchase reprints of this article please e-mail: [email protected] Or visit our web site for further details: www.emeraldinsight.com/reprints

Postimplementation ERP 185

The current issue and full text archive of this journal is available at www.emeraldinsight.com/1741-0398.htm

JEIM 25,2

Enablers and inhibitors of advanced information technologies adoption by SMEs

186

An empirical study of auto ancillaries in India

Received 25 November 2010 Revised 5 February 2011 26 April 2011 6 June 2011 Accepted 2 August 2011

G. Kannabiran National Institute of Technology, Tiruchirappalli, India, and

P. Dharmalingam Dr Ambedkar Institute of Productivity, National Productivity Council, Ministry of India, Chennai, India Abstract

Journal of Enterprise Information Management Vol. 25 No. 2, 2012 pp. 186-209 q Emerald Group Publishing Limited 1741-0398 DOI 10.1108/17410391211204419

Purpose – The auto ancillary industry in India has witnessed huge capacity expansion and modernization due to entry of foreign automobile manufacturers in the post liberalization era. In spite of potential benefits, the adoption of advanced IT among small to medium-sized enterprises (SMEs) is low in India. There are several technological, economical and organizational factors that enable or inhibit the adoption of advanced IT. The primary objective of this research is to identify and evaluate the key factors that are enabling or inhibiting adoption of advanced IT in the Indian auto ancillary SMEs. Design/methodology/approach – In order to identify and evaluate the enablers and inhibitors, a detailed survey was carried out among registered Indian auto ancillary SMEs during 2010. Out of 584 registered SMEs, 110 owners/top managers of the SMEs responded to the survey. The data collected through the survey were analyzed using confirmatory factor analysis and multivariate regression to evaluate the influence of enablers and inhibitors of advanced IT adoption by the auto ancillary SMEs. Findings – The survey findings show that the level of advanced IT adoption in auto ancillaries is low with only 17 per cent of SMEs having adopted technologies. This study reveals that “perceived benefits” and “perceived competitive pressure” enable advanced IT adoption among auto ancillary SMEs in India. However, “lack of financial capacity”, “small scale operation and “lack of in-house IT manpower” inhibit the adoption. It is also found that enablers such as “changes in business environment”, “IT experience of CEO/owner” and “increased information linkage with OEM/customer” do not have any influence on the adoption. Similarly in the case of inhibitors, “lack of IT Infrastructure” and “lack of information security” do not have significant association with IT adoption. Despite the positive external IT environment and recognition of benefits, advanced IT adoption by SMEs in the auto ancillaries is limited by lack of financial capabilities and in-house IT human resources. Originality/value – This is one of the early papers that brings out the enablers and inhibitors of advanced IT adoption by auto ancillaries in India. Further, these factors are systematically analyzed to assess the relative importance with reference to the SMEs. The findings contribute to theory of IT adoption among SMEs, but more importantly to the SMEs in the auto ancillary, and policy makers and IT service providers who are likely to facilitate increased adoption. Keywords Advanced IT adoption, Enablers, Inhibitors, Small to medium-sized enterprises, Auto ancillaries, India Paper type Research paper

1. Introduction The auto ancillary industry in India is highly fragmented with about 584 organized and 6,000 unorganized units. Organized sector alone contributes to more than 80 per cent of country’s total production of auto components (ACMA, 2011). The market for auto ancillary components can be classified into original equipment manufacturers (OEMs), replacement market and export market, which account for 40, 50 and 10 per cent respectively, of the total demand for auto components. In terms of geographic mix, 40 per cent of the auto components are exported to Europe, 24 per cent to Asia and 22 per cent to North America. According to Automotive Component Manufacturers’ Association (ACMA, 2011), the compounded annual growth rate (CAGR) of the auto component industry records around 18 per cent in the 2010-2011. Indian auto ancillary SMEs will need to continuously strive to increase their efficiency, quality and productivity to sustain and accelerate the current growth and develop competitiveness (NASSCOM, 2007; Singh et al., 2007). In this regard, Information Technology (IT) will increasingly play a crucial role in enabling the firms to integrate with their global and domestic customers and suppliers. IT can help SMEs to cut cost by improving their internal processes, faster communication with customers and better distributing their products through online. Among the SMEs that have basic IT, adopting more advanced ICT still brings additional benefits. Advanced IT such as ERP/SCM software can help SMEs to increase productivity, improve inventory controls, increase sales through closer relationships and faster delivery times (NMCC and NASSCOM, 2010). Major benefits of advanced IT adoption include reduction in costs and increase in productivity (Lymer, 1997), increased systems integration and higher levels of product and process innovation (Raymond and Bergeron, 2008), providing collaborative environments (Alba et al., 2005) and improve the overall competitiveness (Alberto and Fernando, 2007). Confederation of Indian Industry (CII, 2010) study shows that the penetration of IT in Indian SMEs is quite low and attributed to reasons such as very few employees of a typical SMEs gain relevant expertise in IT during their education; most SME firms do not have a formal IT budgeting process and lack of customization of IT solutions. In spite of many potential advantages of advanced IT, adoption by auto ancillary SMEs remains limited as compared to automobile manufacturers and large firms (Todd and Javalgi, 2007). For example, taking advantage of exponential growth of advanced IT applications such as e-commerce, larger businesses have reaped the benefits (Riquelme, 2002). In contrast, the rate of e-commerce adoption in the SME sector has remained relatively low (Magnusson, 2001; Parker and Castleman, 2007). Historically, advanced technologies are always designed for usage in a large corporation, rather than to suit the SMEs. There is also a general belief about spiraling expenditure towards up gradation, skill building cost and maintenance rather than it being seen as a one-time investment with some tangible return (Yesbank, 2009). Further, large companies have financial as well as technical capacity to identify alternate technologies that would suit their requirements and this capacity is very less in the case of SMEs (Yesbank, 2009). Thus, adoption of advanced IT among the SMEs continues to lag behind compared to similar industries in other countries (NASSCOM, 2009). In order to increase IT penetration, it is important to understand the IT adoption challenges faced by the SMEs.

Advanced IT adoption by SMEs 187

JEIM 25,2

188

Few research studies have been conducted with respect to IT adoption by Indian SMEs in general (Sharma and Bhagwat, 2006; Singh et al., 2007; Todd and Javalgi, 2007; Thakkar et al., 2008). Pillania (2008) has investigated the role of IT for KM in automotive SMEs in Indian context. However, research has not been carried out particularly with respect to enablers or inhibitors of advanced IT adoption in the auto ancillary SMEs (Kumar, 2007; Sarosa, 2005). Therefore, the primary aim of the research is to identify and evaluate the key factors that are enabling or inhibiting successful adoption of advanced IT in the auto ancillary SMEs in India. This is achieved, by systematically collecting, and analyzing the responses, from the owners/managers of auto ancillary SMEs in India. The rest of the paper is organized as follows. A detailed review of previous research on IT adoption in SMEs is presented in the following section. We then present research objectives and methodology followed by detailed analysis and discussion. The paper is concluded with implications for practice and direction for further research.

2. Review of previous research IT adoption has been defined in many ways depending on the research objectives. The auto ancillary firms possess a heterogeneous mix of IT capabilities, ranging from basic to very sophisticated, providing IT related services to its own firms and others (NASSCOM, 2007). For this study, we have taken advanced IT, which includes Intranet, Extranet, ERP, SCM and e-Commerce for internal and external integration business operation (Moodley, 2002). Many research studies have been conducted to identify the various factors that affect the advanced IT adoption in SMEs both in developing and developed countries. For example, in the UK context, Simpson and Docherty (2004) reported that cost savings and external pressure are the key motivating factors for adopting e-commerce and ignorance about the technology and limited resources are the barriers to internet adoption. Lucchetti and Sterlacchini (2001) have emphasized that factors such as financial resources technical skills and security of transactions are important for IT adoption in Italian SMEs. MacGregor and Vrazalic’s, 2005, study findings in Sweden and Australia SMEs shows that lack of technical skills and IT knowledge and high cost of IT implementation are significant barriers for e-commerce adoption. Cavaye and Hussin (2007) have studied the various facilitators to the adoption of these technologies that are rated highly by owner/managers. In the Australian context, Crawford (1998) identified the inhibiting factors such as lack of awareness, lack of skill, lack of realization of the benefits and infrastructure issues. Ahuja et al.’s 2009 research reports that lack of strategic direction and high cost ICT are the most important barriers while perceived benefits and great management control are the main enablers for IT adoption in the Indian context. The primary objective of this research to extend the previous research by identifying and evaluating the enabling or inhibiting factors of advanced IT adoption in auto ancillaries industry in India. Significant factors that influence the adoption of IT as identified from prior research and grouped into two categories, namely enablers and inhibiters. The previous research related to the enablers and inhibiters and presented in the following sections.

2.1 Enablers of advanced IT adoption For this study, five enablers of advanced IT adoption are considered as these factors have been repeatedly found in the pervious research both in developed and developing economies (Voges and Pulakanam, 2011; Ongori and Migiro, 2010; Alshawi, 2010; Raymond and Bergeron, 2008; Mike and Anthony, 2004; Moodley, 2002). They are: perceived benefits, awareness of business environment, IT experience of owner /CEO, increased information linkage with OEM/customer and perceived competitive pressure. The previous research findings relating to the enablers are presented in this section. Perceived benefits. The term “perceived benefits” is defined by a set of anticipated advantages that can benefit the organization (Mehrtens et al., 2001; Seyal et al., 2004). Apulu and Latham (2011) has identified that the key drivers for ICT adoption among SMEs in Nigeria are competitive advantage and reduced cost and time. Voges and Pulakanam (2011) found that perceived benefits of internet use has positively related IT adoption in to the perceived benefits in New Zealand SMEs. According to Alberto and Fernando (2007), the use of IT can improve competitiveness with technologies such as internet providing numerous opportunities for SMEs to compete equally with large corporations. Lymer (1997) stressed that IT implementation in SMEs has the potential to reduce costs and increase productivity. Lai and Hsieh (2007) found that perceived relative advantage is positively related to the adoption of IT. The findings from previous research indicate that “perceived benefits” is a factor influencing the adoption of IT technologies like CRM, ERP and web technologies (Seyal et al., 2007; Alshawi, 2010). Perceived benefits are the most investigated EC technologies that promote the adoption of these technologies (Jeon et al., 2006; Seyal et al., 2004). Electronic commerce will aid SMEs to increase efficiency in day-to-day business operations and increase the flow of information (Ongori and Migiro, 2010). The benefit perceived by SMEs in adopting e-Commerce to conduct business is to reduce the operating cost (Al-Qirim, 2007). Greater manufacturing flexibility, increased systems integration and higher levels of product and process innovation are achieved through e-business implementation (Raymond and Bergeron, 2008). It is also found that the dimensions affecting ERP adoption show that perceived benefits possess positive effects on ERP adoption in SMEs (Shiau et al., 2009). However, Tsao et al. (2004) have found that perceived benefits are insignificant contributor to e-commerce adoption. Changes in business environment. Globalization and liberalization policies have made business resources more mobile and transferable beyond borders (Todd and Javalgi, 2007). Ongori and Migiro (2010), state that the impact of globalization has obliged many SMEs to adopt ICT in order to survive in the present competitive era and, it was necessary have ICT at the forefront of their various organizations in order adapt to new business environments. Globalization also promotes the rapid innovation, easy entry as less government protection and convergence across industries due to less trade barriers within region and liberalization opening up of new economies (Humprey, 2001). It is also evident that globalization has increased the share of developing countries in manufacturing (UNDP, 2005). Several researchers have highlighted various challenges faced by SMEs in a globalized environment (Wang, 2003; Stuti, 2005; Samad, 2007). The globalization of value chains has changed the way production

Advanced IT adoption by SMEs 189

JEIM 25,2

190

is organized and has provoked important modifications in the relationships between partners along the value chain (Decker et al., 2006). Mendo and Fitzgerald (2005) suggest that not considering the broader picture of the changes in the industry is an underlying weakness for internet adoption by SMEs. Implementation of advanced IT, such e-commerce also leads to change within the organization. They have advocated that a growth oriented research model that covered process, content and drivers of change. SMEs need to improve their competitive capability by effectively managing the collaborative environments (Alba et al., 2005). Therefore, SMEs must take advantage of low-cost labor, flexible logistics, new technology, cheaper materials, and of less regulated operating environment. Therefore, the factor “changes in business environment” needs further investigation. IT experience of owner/CEO. CEO/owner involvement is essential for establishing appropriate IT goals, identifying critical business information needs, allocating the requisite financial resources and managing the implementation. Empirical studies by Igbaria et al. (1998) and Premkumar and Roberts (1999) found CEOs took a key role in driving the adoption of internet technologies. Manufacturing SMEs have a positive attitude to ICT, much of which is generated by owner/manager perception that ICT can have a positive impact on operational efficiency (Somuyiwa and Adewoye, 2010). Adoption depends on the CEO/owner’s IT experience and his experience in IT decision making. If the owner does not perceive the technology to be useful, nor understand its potential, then they will be reluctant to adopt (Windrum and de Beranger, 2003). IT knowledge, skills and practices are important determinants of whether IT is adopted or rejected by the SMEs (Wainwright et al., 2005). The level of IT background of the owner and lack of knowledge on how to use the IT will result in low adoption e-commerce (Kirby and Turner, 1993; Bassellier et al., 2003). Hashim (2007) stated that the level of IT knowledge among managers has a leaner relationship with how early (or late) the adoption of new innovations can take place. Many studies have found that the CEO characteristics and CEOs’ IS knowledge and attitude are the most significant factors for IT implementation (Mirchandani and Motwani, 2001; Dholakia and Kshetri, 2004; Sabherwal et al., 2006). This is also supported by Levy and Powell (2003) who found that owner attitude influences IT adoption, particularly in internet related technology. Reynolds and Bopaya (1994) found that small business owner/managers are unlikely to adopt more sophisticated technologies if they are not familiar with the basic ones. It has been found education level of the top management of the SME is a significant predictor of the extent of IT adoption (Chuang et al. 2007; Sanna et al., 2007). Further, it also affects the proactive or reactive approaches adopted towards rapid technological changes (Martin and Matlay, 2001). Additionally, factors such as internet experience determine whether the SMEs have adequate knowledge in assessing the benefits and barriers of IT, which would ultimately determine their adoption intention (Tan et al., 2009). Increased information linkage with OEM/customer. There is considerable literature in information systems research that identifies the influence and information linkage that customers, vendors, and suppliers exert on the SMEs and result in software assimilation. Bharati and Chaudhury (2010) showed that wide use of information Technology among manufacturers’ suppliers and vendors increases the adoption of Information technology adoption. Communicative relationships describe the exchange of actual or planned information and events to other industry partner to coordinate

production activities. Large automobile manufactures can influence the behaviour of other SMEs by threats or sanctions (Hung-Chi Wu, 2001; Jun and Cai, 2003; Chuang et al., 2007). Especially, if there are some dominant OEMs, they can force other small SMEs to follow their suit. It is found that large organizations enforcing partners to adopt EC technologies in a global economy (Hinson and Sorensen, 2006; Sarosa and Underwood, 2005). All these approaches are determined based on the extent of competition and rivalry in the industry and play a crucial role in technology adoption (Wymer and Regan, 2005). It is also found that vertical linkage was found to be an important discriminate factor for online data access and the internet adoption (Elizabeth et al., 2004). When a major supplier or customer adopts IT, the small business owner is more likely to adopt (Kirby and Turner, 1993). Position of the auto ancillary unit in the value chain (i.e. Tier I or Tier II) is important to understand its significance in the value chain (Kumar, 2007). Large businesses will be more willing to enter into the business relationship with SMEs using IT to improve on trust, transparency and communication issues. However, compatibility issues become important when OEM expects SMEs to interact or exchange information on a particular hardware/software requirement (Thakkar et al., 2008). Perceived competitive pressure. A firm may feel pressure when it sees more and more competitors in the industry are adopting advanced technologies and therefore decide to adopt advanced IT in order to remain competitive (Cragg et al., 2002). Competitive pressures in an industry cause an organization to evolve over time and become similar to other organizations. Bharati and Chaudhury (2010), showed that wide use of an IT and innovation, it serves as a proxy indicator of its worth and induces other firms to adopt the same. Julien and Raymond (1994) study also confirmed that SMEs to be interested to adopt technology if competitors and trading partners or a whole industry are adopting IT. Martin and Matlay (2001) also found competitive pressure to be statistically significant. The individual small business is likely to adopt as well. The competitive pressure and the expectations in the market trends in the industry can force companies into adopting ERP, e-commerce technologies and SCM to gain competitive advantages over their rivals (Dholakia and Kshetri, 2004; Zhu et al., 2003). Businesses might adopt e-commerce as a result of their competitors using it, so as not to lose their competitive advantage (Iacovou et al., 1995). It was found that external pressure has significant influence on CRM adoption (Dasgupta, 2000; Scupola, 2003). However, Quayle (2002) found customer pressure to be significant but not the competitive pressure. 2.2 Inhibiters of advanced IT adoption For this study, five inhibiters of advanced IT adoption are considered as these factors are found most significant in pervious research studies (Somuyiwa and Adebayo, 2011; Packale´n, 2010; Seyal et al., 2007; MacGregor, 2004; Dixon et al., 2002; Duncombe and Heeks, 2001) They are: lack of financial capacity, lack of in-house IT manpower, small scale operation, lack of IT infrastructure and lack of information security. The previous research findings relating to the inhibitors are presented in this section. Lack of financial capacity. Previous research shows that the higher the investment, less likely the firms adopts the innovative applications as any advanced technologies might be considered to be expensive by SMEs because of lack of financial resources (Poon and Swatman, 1999).

Advanced IT adoption by SMEs 191

JEIM 25,2

192

The study by Somuyiwa and Adebayo (2011) reveals that key factors that inhibit the widespread adoption and use of ICT are high cost of technology. According to Duncombe and Heeks (2001), lack of finance is one of the two main constraints for organization to adopt advanced IT by SMEs in the USA. The cost factor was studied by various researchers and found direct relationship with adoption of technology (Seyal et al., 2007; Premkumar et al., 1997). Cragg and King (1993) identified the lack of financial resources and inadequate levels of technical expertise as the major inhibitors of IT adoption in small businesses. The SMEs are less likely to adopt IT when its initial set-up cost is high (Dixon et al., 2002). Poon and Swatman (1999) stated that small businesses often have difficulty in obtaining financial resources. Lack of in-house IT manpower. SMEs generally lack the human and technological resources needed for ICT and e-commerce, because they focus on day-to-day operations and lack the time to understand the benefits of new technologies. Even when they are aware of the potential benefits of adopting e-commerce, they require expertise or qualified personnel. Packale´n (2010) found that the workers in small firms ICT-skills are not at a very high level and lack of ICT-skills or access to people with skills is one of the major obstacles for small firms to adopt advanced information Technology. According to MacGregor (2004), small business tends to avoid IT into their business, if it is seen as complex to use. This is not surprising because SMEs always lack of skills among workforce to use IT (Spectrum, 1997). The ability of managers’ IT knowledge or skills is definitely increasing the opportunity of IT use among SMEs. Lack of employee knowledge base might hinder technology adoption if the owner believes that this technology can only be employed using specialist staff (Jones et al., 2003). Lack of suitable technical and managerial staff with sufficient IT expertise have significant influence on the adoption (Levy et al., 2001; Wainwright et al., 2005; Hashim, 2007). Kartiwi and MacGregor’s 2007 study showed that the lack of technical knowledge is the significant barrier for IT adoption in cross-country comparison of developed and developing countries. Dholakia and Kshetri (2004) suggest that technologies already existing in an organization influence the future adoption of a new technology. Reynolds and Bopaya (1994) found that small businesses are unlikely to adopt more sophisticated technologies if they are not familiar with the basic ones. Kotelnikov (2007) stated that lack of technical skill is more prominent for advanced IT such as e-commerce and ERP software than for basic IT. Riemenschneider et al. (2003) and Brown and Lockett (2007) found technology complexity one of the factors significantly influencing adoption, which the employees are not able to understand. With institutional help, SMEs trust that the government will help them face the technical problems of adopting an ERP system (Shiau et al., 2009). In some cases, SMEs are unaware of the financial and technical assistance provided by the government and the private sector, and therefore they perceive these barriers as hindering their adoption intention. Small-scale operation. According to Bharati and Chaudhury (2010), firm size is one of the most critical determinants of IT adoption. It has been well established in the IT diffusion literature that firm size is often a proxy for resource slack and infrastructure. Yulong Li (2011) has identified in research study that Chinese small enterprise’s failed attempt to adopt enterprise resource planning (ERP) due to small scale operation. Dixit and Prakash (2011) stated that SMEs have the perception that ERP is meant only for large firms mainly owing to the high costs of acquisition, implementation and

maintenance as also the complexity. SMEs even feel they do not need ERP. Previous research suggests organization’s size has a strong influence on IT related technologies (Chen and Popovich, 2003). Organizational size was found to be significant discriminators between adopters and non-adopters of online data access technology (Teo and Pian, 2003). In simple organizational structure where a low volume of information to be communicated and stored, there is a less compelling need for advanced IT. Teo and Pian (2003) suggest that smaller firms may be less likely to adopt advanced technologies such as e-commerce. Findings from MacGregor (2004) suggest that SMEs with fewer than 10 employees were less likely to adopt advanced IT than larger SMEs. Firms that low volume business operation and do not have opportunities for exports may not adopt advanced IT (Flint and Herbert, 2000; Ramdani et al., 2009). Based on a study of Thai SMEs in hotel industry, Lertwongsatien and Wongpinunwatana (2003) and Khemthong and Roberts (2006) identified firm size as one of the influential factors on e-commerce adoption decision. It has been found that manufacturing and service SMEs across different sizes need different IT applications and, their internet-based IT practices will also vary (Tan et al., 2009). Firm size is an important determinant of a firm’s involvement and decision process in acquiring IT (Dholakia and Kshetri, 2004; Brown and Kaewkitipong, 2009). According to study (Windrum and de Beranger, 2003) firm size and business activity is found to be a key factor in both the adoption of intranets and extranets. However, Bajwa et al. (2005) and (Levy et al., 2001) suggest that size may not be a significant predictor of adoption of some collaboration tools like email and web-based tools. Lack of IT Infrastructure. This refers to SMEs’ perception about the availability of supporting services in the region/country that promotes the adoption of advanced IT. The technology infrastructure includes the availability of software and hardware vendors and distributors dealing in web servers, databases, telecommunication facilities and ERP software. Johnson (2010) stated that lack of ICT infrastructure (e.g. poor internet connection, software, hardware, etc.) is the barrier for IT adoption. Mpofu and Watkins-Mathys (2011) have confirmed from their research that poor ICTs infrastructure and lack of ICTs technical and managerial capacity are obstacles among SMEs in adopting ICTs to enhance their business processes. Good network infrastructure in the nation and ease of loans are some of the initiatives that government can adopt to encourage more IT usage (Tan and Eze, 2008) SMEs are slower to adopt the new IT compared to their large business counterparts in developing countries, mainly due to lack of telecommunication infrastructure (Sheth and Sharma, 2005; Wood, 2004; Hawk, 2004). Toussea-Oulai (2007) found that lack of basic infrastructures is a barrier to IT adoption in developing nations and stated that over 80 per cent of the SMEs studied did not have access to broadband connection. In this regard, poor telecommunications limit the growth of e-commerce which includes transmission facilities connecting a country’s domestic network to the internet. A number of studies have highlighted the need for availability of capable technology infrastructure and availability of skilled IT manpower and software/hardware vendors as factors that determine the e-commerce adoption in SMEs (Doolin et al., 2003; Srinivasan et al., 2002). SMEs can achieve growth by giving special attention to develop the infrastructure that could enable a more efficient use of resources (Todd and Javalgi, 2007). A large pool of trained human resources in the field

Advanced IT adoption by SMEs 193

JEIM 25,2

194

of IT acts as the propellant for more IT activity. Access to skilful individuals provides the much-needed help to IT adoption especially in small business enterprises (Taylor et al., 2004). Lack of information security. The lack of a legal framework to support e-business (e.g. regulations for online transactions, digital signatures, arbitration, intellectual property rights, exports and imports, etc.) creates a barrier to e-commerce practice (Koshy, 2011). Information security and confidentiality is one of the main factors that determine innovative adoption of IT (Beale, 1999). It is revealed that many organizations are reluctant to embrace e-commerce mainly because of their concerns towards security issues and lack of confidence in the e-commerce set-up (Grandon and Pearson, 2004). SMEs may face security problems in many forms, including payment security, privacy and confidentiality of the information or viruses. Security in the forms of confidentiality, integrity, and availability of information assets is the major barrier to wider adoption of e-commerce (Lowry et al., 1999; Poon and Swatman, 1999; Jeon et al., 2006). Based on a survey Ratnasingam (2001) found that perceived lack of security as one of the main barriers to the adoption of e-commerce. In the Australian context, Crawford (1998) has identified the factors such security and infrastructure issues are the most significant factors for IT adoption. A number of studies have investigated the available legal/regulatory environment, government support and commitment as factors that determine the e-commerce adoption by SMEs (Chang and Cheung, 2001; Jeon et al., 2006). Lowry et al. (1999) in a study of Australia SMEs reported on the concerns about security and reluctance by customers to interact online. 3. Scope and objectives The scope of this study is to build a conceptual framework to systematically study the factors that influence the advanced IT adoption in auto ancillaries in India. Significant factors that influence the adoption of IT are identified from prior research and grouped into two categories namely enablers and inhibiters. The primary objective of this research is to identify and evaluate the enabling or inhibiting factors of adoption of advanced IT in auto ancillaries industry in India. Five enablers considered for conceptual research model are perceived benefits, changes in business environment, IT experience of CEO/owner, increased information linkage with OEM/customer and perceived competitive pressure. Five inhibiters considered for conceptual research model are lack of financial capacity, lack of in-house IT manpower, small-scale operation, lack of IT Infrastructure and information security. While the dependent variable of the study is adoption of advanced IT, independent variables are grouped into enables and inhibitors. A conceptual research model highlighting the previous relationship is presented in Figure 1. The research objectives and the conceptual model are translated into the following set of hypotheses to test the relationship between the enablers and inhibiters and advanced IT adoption among auto ancillary SMEs in India. H1.

Higher the perceived benefits of IT use, higher the advanced IT adoption.

H2.

More the changes in business environment, higher the advanced IT adoption.

Advanced IT adoption by SMEs 195

Figure 1. Conceptual research model

H3.

Higher the levels of IT experience of CEO/owner, higher the advanced IT adoption.

H4.

Increased information linkage with OEM/customers will lead to greater adoption of advanced IT.

H5.

Higher the perceived competitive pressure, higher the advanced IT adoption.

H6.

Higher the lack of financial capacity lower the level of advanced IT adoption.

H7.

Higher the lack of in-house IT manpower lower the level of advanced IT adoption.

H8.

Smaller the scale operation, lower the level of advanced IT adoption.

H9.

Higher the lack of IT infrastructure lower the level of advanced IT adoption.

H10.

Higher the perceived lack of information security, lower the level of advanced IT adoption.

4. Research methodology The population for the research study was auto ancillary SMEs in the organized sector in India. There are 584 registered SMEs with Auto Component Manufacturers Association of India (ACMA). The population included all type of auto ancillaries namely engine parts, mechanical and suspension parts, electrical and electronic parts, rubber and plastic parts, foundry and heat treatment units and other equipment

JEIM 25,2

196

manufacturers. A preliminary questionnaire was developed based on the literature review and feedback from discussion with members of auto ancillary association for pilot study. A pilot survey was carried out in 30 selected auto ancillary units. This was undertaken to test the applicability, content validity and reliability of the survey instrument. The respondents of the study were owners/CEO or senior most manager of the organization. Section-A of the questionnaire with 14 questions dealt with firm characteristics. Section-B had ten questions about the current level of advanced IT adoption in the organization (intranet, extranet, ERP, e-Commerce, SCM, CRM). Section-C was designed with five questions to measure the enabling factors and five questions to measure inhibiting factors that influence the IT adoption. Respondents were asked to indicate their responses using a five-point Likert scale (from strongly disagree to strongly agree) to the questions of section B and C. The items of the questionnaire relating to enablers and inhibiters are presented in the Appendix (see Table AI). The questionnaire was administered over to 584 registered auto ancillaries through postal mail and only 118 members responded. After discarding eight questionnaires due to incomplete information, 110 responses were taken for data analysis. The response rate is 19 per cent. Table I provides the product wise classification of auto ancillary SMEs that participated in the survey. 5. Data analysis and findings The data collected through the survey were analyzed using SPSS 16.0. Prior to undertaking detailed analysis, all the constructs were tested for validity and reliability. Validity and reliability are the tools used to evaluate the characteristics of a good measurement. Confirmatory factor analysis (CFA) was performed for establishing the validity and reliability of IT adoption constructs. The results are shown in Table II. Goodness of Fit Index (GFI) value is the evidence for unidimensionality. According to Chau (1997), scores in the 0.8-0.89 range, are interpreted as reasonable fit whereas scores of 0.9 and above represent good fit. All values of GFI in Table II range from 0.858 to 0.9140, which suggests very good model fit. Each construct of the research model were subjected to reliability test through Cronbach’s alpha which is ranged from 0.80 to 0.90. The scale reliabilities are unusually good compared to the acceptable 0.7 level for field research. Multiple regression analysis was carried out to evaluate the relationship between the enablers and inhibitors of advanced IT adoption in auto ancillary SMEs. Tables III Products manufactured

Table I. Classification of auto ancillary SMEs by product wise

Engine parts Mechanical, suspension and steering parts Electrical and electronic parts Rubber and plastics parts Foundry and heat treatment units Others products Total

Frequency

(%)

39 21 10 13 7 20 110

35.5 19.1 9.1 11.8 6.4 18.1 100.0

and IV present the results of regression analysis on the five independent variables of enablers and five independent variables of inhibiters towards advanced IT adoption. It was found from multiple regression analysis (see Table III) that two out of five enablers are statistically significant to the advanced IT adoption. Perceived benefits

Construct

CMIN

GFI

CFI

RMR

RMSEA

Cronbach’s alpha (a)

Level of advanced IT adoption Enablers for IT adoption Inhibiters for IT adoption

28.57 80.68 191.47

0.873 0.914 0.858

0.875 0.898 0.732

0.117 0.030 0.089

0.109 0.141 0.190

0.8019 0.8130 0.8118

197 a

Items 10 5 5

Notes: GFI ¼ Goodness of Fit Index; CFI ¼ Comparative Increment Fit index. CMIN ¼ Chi-square minimum; RMR ¼ Root Mean square Residual; RMSEA ¼ Root Mean Square Error of Approximation. aRelated items (independent variables) for each construct are given in the Appendix

Predictors coefficients Unstandardized coefficients B Std. error

Model

Ena lers (predictors)

1a

(Constant) Perceived benefits Changes in business environment IT experience of the CEO/owner Increased information linkage with customers/oEM Perceived competitive pressure

Standardized coefficients Beta

t

p (sig.)

0.674 1.938 1.476

3.406 0.818 0.876

0.265 0.201

0.198 2.370 1.685

0.844 0.020 * 0.095

1.355 0.634

0.821 0.788

0.184 0.088

1.651 0.805

0.102 0.422

2.188

0.708

0.335

3.093

0.003 * *

Notes: aRegression model summary on five enablers of advanced IT adoption: R ¼ 0:456 (dependent variable: advanced IT adoption); R-square ¼ 0.208; Adjusted R-square ¼ 0:170; Standard error of the estimate ¼ 4:334; * *denotes significant at 1 per cent level, *denotes significant at 5 per cent level

Model Inhibiters (predictors) 1a

Predictors coefficients Unstandardized coefficients B Std. error

(Constant) 12.659 Lack of financial capacity 2.303 Lack of in-house IT manpower 1.565 Small scale operation 1.792 Lack of IT infrastructure 1.063 Lack of information security 0.034

2.056 0.621 0.602 0.445 0.615 0.619

Standardized coefficients Beta 0.443 0.312 0.408 0.176 0.005

Advanced IT adoption by SMEs

t

p (sig.)

6.157 3.707 2.600 4.024 1.727 0.055

0.000 0.000 * * 0.011 * * 0.000 * * 0.087 0.956

Notes: aModel summary on five inhibiters of advanced IT adoption: R ¼ 0:466 (dependent variable: advanced IT adoption); R-square ¼ 0.217; Adjusted R-square ¼ 0:180; Standard error of the estimate ¼ 4:308; * *denotes significant at 1 per cent level, *denotes significant at 5 per cent level

Table II. Validity and reliability indicators

Table III. Multiple regression results for enablers

Table IV. Multiple regression results for inhibiters

JEIM 25,2

198

and perceived competitor’s pressures found to have positive relation with advanced IT adoption with p-value of 0.020 and 0.003 respectively. Further, out of accepted hypotheses, perceived competitor’s pressure has higher influence with b ¼ 0:335 than perceived benefits with b ¼ 0:265. However the variables, awareness of changes in business environment, IT experience of the CEO/owner and increased information linkage with customers/oEM are not statistically significant because of the p-value is 0.095, 0.102 and 0.422 respectively. As per Table IV, three out of five inhibiters are statistically significant to the advanced IT adoption. Results show that the lacks of financial capacity, lack of in-house IT manpower, small scale operation are statistically significant with p value of 0.000, 0.011 and 0.000 respectively. Out of accepted hypotheses, it is also found that lack of financial capacity and small-scale operation have higher influence with b ¼ 0:443 and 0.408 respectively than lack of in-house IT manpower with b ¼ 0:312. Lack of IT infrastructure and lack of information security are not statistically significant because of the p value is 0.087 and 0.956 respectively. 6. Theoretical implications In this research we have attempted to evaluate the enablers and inhibitors of advanced IT adoption by auto ancillaries in India. Our findings have the following significant implications for theory of advanced IT adoption by SMEs. Out of five enabling factors considered, “perceived benefits” and ‘perceived competitive pressure” were found to be statistically significant for advanced IT adoption. This study confirms that “perceived benefits” is one of the key influencing factors for IT adoption in auto ancillary SMEs. As found by previous researchers small firms expect to derive various benefits, such as improved communications, cost savings, time savings and increased market potential from IT adoption (Voges and Pulakanam, 2011; Alshawi, 2010; Shiau et al., 2009; Seyal et al., 2007; Seyal et al., 2004; Lal, 2002). Our findings differ from the earlier finding by Tsao et al. (2004) that the “perceived benefits” is not a significant contributor to e-commerce adoption. This may be due to the fact that some of the SMEs in developing countries are not sure about the benefits that can be derived from e-commerce, and or knowledge about what technology can provide. Our study supports the earlier findings (Lal, 2002; Lauder and Westall, 1997; Barua et al., 1995) and confirms that both direct and indirect benefits lead to adoption of advanced IT. The automotive market is highly competitive as many global players are operating in India. This leads to competitive environment among SMEs to supply quality products on time. Therefore, greater the use of information technology by competitors, the more likely the advanced IT will be adopted by the SME. Our findings are inline with previous researchers (Bharati and Chaudhury, 2010; Martin and Matlay, 2001; Kuan and Chau, 2001; Iacovou et al., 1995; Cragg and King, 1993) that competitive environment is the significant factor for IT adoption. However, the findings differ from Quayle (2002), which identified competitive environment not to be an important factor. Our study shows that the competitive pressure is a most significant factor for advanced IT adoption decision in SMEs. Our study further shows that perceived competitive pressure (b ¼ 0:335) influence the advanced IT adoption than perceived benefits (b ¼ 0:265). This shows that more than the general benefits such as cost

reduction and efficiency improvement, the competition among the SMEs is highly influencing factor (Dholakia and Kshetri, 2004; Scupola, 2003). This study shows that the “changes in business environment” is not an influencing factor for advanced IT adoption. Our findings differ from previous researchers (Alba et al., 2005; Mendo and Fitzgerald, 2005) who have highlighted the importance of understanding of changing business environment. This is mainly due to the fact that most of the SMEs have already adopted the basic IT for functional level computerization. In addition many global automotive manufacturers have entered into India due to policies such as globalization and liberalization. Although awareness exists, adoption of advanced IT is low due to other economic and technical factors. Our study findings contradict earlier studies (Dixon et al., 2002; Taylor et al., 2004), SMEs do not realize the huge potential mainly due to lack of full awareness. It may be concluded that a simple awareness of changes in business environment is not sufficient for advanced IT adoption. Our results reveal that IT experience of CEO/owner is not a significant factor influencing IT adoption. Our study differs from the earlier findings (Reynolds and Bopaya, 1994; Mirchandani and Motwani, 2001; Dholakia and Kshetri, 2004; Sabherwal et al., 2006; Hashim, 2007; Tan et al., 2009) that CEO/owner knowledge of IT is important for IT adoption. Thus, our study shows that the IT experience of CEO/owner is not a differentiating factor for IT adoption in SMEs. This may be due to the fact that many of these SMEs have adopted basic IT. Further, the overall awareness of IT and its benefits are improving in the industrial sector. Similarly, increased information linkage with OEM/customer is also not found to be significant influencer of advanced IT adoption. Kumar (2007) ascertained that position of the auto ancillary unit in the value chain (Tier I or Tier II) is important and IT use enables the organization for collaborative efforts. However, according to our findings, increased information linkages with OEM/customers, by auto ancillary SMEs is not a significant factor. The auto ancillaries are able to set up IT support for such exchange of data/information. It is also understood that some auto majors have supported ancillary units through subsidy for acquiring resources and capabilities. Our study also differs from the earlier findings (Hinson and Sorensen, 2006; Jun and Cai, 2003; Chuang et al., 2007) that multinational companies have created pressures on their subsidiaries and suppliers to use IT to global networking. Many SMEs are located in and around the large customers with connectivity to ancillary SMEs. Therefore, increased linkage with OEM/customers is not found as significant influencing factor for advanced IT adoption. Three out of five inhibiting factors were statistically significant in the context of advanced IT adoption. Lack of financial capacity is one of the factors that negatively influence the advanced IT adoption among SMEs. Few CEOs/owners had indicated that not only the initial investment especially for ERP, but also the up-gradation cost is high. Our findings confirm the earlier findings (Cragg and King, 1993; Premkumar et al., 1997) that although the cost of technology adoption can vary widely, limited financial resources inhibit uptake, especially for small firms. Our study found that the lack of financial capacity is a main influencing factor for IT adoption in auto ancillary SMEs. As suggested by previous studies either adequate financial resources or lower cost of software would lead IT adoption (Duncombe and Heeks, 2001; Dixon et al., 2002). This study found that lack of in-house IT manpower is another inhibiter after lack of financial capacity. Our study findings is supports the previous findings (Packale´n, 2010; Hashim, 2007; Kartiwi and MacGregor, 2007; Levy et al., 2001; Reynolds and

Advanced IT adoption by SMEs 199

JEIM 25,2

200

Bopaya, 1994) that lack of IT skill is more prominent for advanced IT such as e-commerce and ERP software than for basic IT). It may be noted that IT personnel are leaving after gaining experience for better jobs in the IT industry. Therefore, SMEs are not able to attract and develop required in-house human resources. Thus our research confirms that the lack of in-house IT manpower is significant influencing factors for advanced IT adoption (Shiau et al. 2009). It is found that small-scale operation is another inhibiter for advanced IT adoption. Li (2011), Bharati and Chaudhury (2010), Brown and Kaewkitipong (2009) and Dholakia and Kshetri (2004) stated that smaller the firm size lesser the information interaction. Further, Flint and Herbert (2000) stated that small firms found difficulty in advanced IT adoption although basic IT is used already. Our finding also shows that, though many SMEs have already implemented basic IT capabilities for office productivity, adoption of advanced IT is limited by small scale of operation of the SMEs. It may be concluded that that small firms with local markets may not need an advanced IT. Alternatively, the small firms do not have other opportunities for exploiting the power of advanced IT. However, our study results differ from Bajwa et al. (2005) and (Levy et al., 2001) which suggested that size may not be a significant predictor of adoption of some collaboration tools like email and web-based tools. Further, our study shows “lack of financial capacity” (b ¼ 0:443) and “small scale operation” (b ¼ 0:408), inhibit more on advanced IT adoption than lack of in-house IT manpower, (b ¼ 0:312). IT shows that given the financial capacity organizations are likely to use external services for the IT requirements. Lack of IT infrastructure is not significantly influencing the advanced IT adoption. Previous studies (Chinyanyu and Lorraine, 2011; Srinivasan et al., 2002; Sheth and Sharma, 2005; Wood, 2004) emphasized that lack of IT infrastructure such as poor communication infrastructure, support of IT vendors and skilled manpower are some of the factors that affect adoption of advanced IT. Todd and Javalgi (2007) found that Indian SMEs can achieve international growth by specifically utilizing IT and special attention has to be given to develop the infrastructure that could enable a more efficient use of resources. However our results show that lack of IT infrastructure is not significantly affecting it. Since most of the auto ancillaries are located in around the large organizations and major cities, the adequate infrastructure provided by government already exists. Similarly, perceived risk of information security is not found as a significant inhibitor because the latest technology such as intranet/extranet protocol has many provisions to take care of the risk factors. We differ from the previous finding (Grandon and Pearson, 2004; Beale, 1999) that revealed that many consumers are reluctant to embrace e-commerce mainly because of their concerns towards security issues and lack of confidence in the current e-commerce set-up. The very growth of IT sector in India and the level of IT adoption by large companies have given confidence to SMEs. 7. Practical implications According to our study relating to advanced IT adoption shows that perceived benefits and perceived competitive pressure are the major enabling factors. On the other hand, lack of financial capacity and lack of in-house IT manpower are inhibiting the IT adoption in auto ancillary SMEs. Even if significant enablers helping auto ancillary SMEs to go far advanced IT, they will only adopt if they can overcome the significant inhibiters.

The “perceived benefits” is one of the key influencing factors for IT adoption in auto ancillary SMEs. SMEs in developing countries are not sure about the benefits that can be derived from e-commerce, and or knowledge about what technology can provide. Efforts may be taken to showcase some of the best practices of deriving high order benefits from advanced IT adoption. As found in other countries such efforts may be spearheaded by government agencies and by automobile manufacturers. Due to policies such as globalization and liberalization, it is important that business resources mobile and transferable beyond borders. The Indian auto ancillary SMEs are part of the global supply chain. It is interesting to note that changes in the business environment are understood by the SMEs. In the time to come, SMEs will improve their IT adoption by adequately managing the other factors such as lack of financial resources and IT human resources. It is also found that IT experience of CEO/owner is not a significant factor influencing IT adoption. It may be due to the fact that many of these SMEs have adopted basic IT and the overall awareness of IT and its benefits are improving in the industrial sector. Similarly, increased information linkage with OEM/customer is also not found to be significant influencer of advanced IT adoption. The auto ancillaries are able to set up IT support for exchange of information. It is also understood that some auto majors have supported ancillary units through subsidy for acquiring resources and capabilities. Further, many SMEs are located in and around the large customers and therefore increased linkage with OEM/customers is not found as significant influencing factor for advanced IT adoption. Lack of financial capacity is one of the factors that negatively influence the advanced IT adoption among SMEs. Few CEOs/owners had indicated that not only the initial investment especially for ERP, but also the up-gradation cost is high. As suggested by previous studies either adequate financial resources or lower cost of IT would lead to adoption of adopt IT. To overcome the inhibiters, government can provide support by grants, incentives, subsidies, tax incentives and low interest rate loans for increasing the affordability of advanced IT. Similarly, it is found that lack of in-house IT manpower is another inhibiter after lack of financial capacity. More than the resources required for having adequate human resources, SMEs face the problem of high employee turnover due to employment opportunities in the IT industry. Industrial associations with government support can host training and workshops that are aimed at specialized training to existing employees so that the need for exclusive IT human resource may be eliminated. Added to these inhibitors, small scale operations make it difficult for advanced IT adoption due to high investments (both capital and recurring) and inability to have specialized human resource for managing IT infrastructure and systems. To address these three major inhibitors, IT service providers may offer shared services in order to enable more and more SMEs to embrace advanced IT. Alternatively, SMEs may come together to promote a cloud computing based common infrastructure and capability to overcome these inhibitors. It is found that lack of IT infrastructure and lack of information security are not significant inhibitor of advanced IT adoption. The overall infrastructure has significantly improved in countries like India. Further, as most of the auto ancillaries are located in around the large organizations and major cities, the adequate infrastructure provided by government already exists. Similarly, lack of information security is not found as technologies have improved. Moreover, the some of these platforms are managed by the large automobile companies to link the SMEs and necessary provisions are present to take care of the risk factors.

Advanced IT adoption by SMEs 201

JEIM 25,2

202

8. Conclusion In this research, we investigated the current level of IT adoption and its degree of use by auto ancillary SMEs in the organized sector and empirically evaluated the enablers and inhibitors of advanced IT adoption in India. Our study finds that auto ancillaries in India are yet to grasp the full potential of advanced information technology. This research study confirms that though 100 per cent of all respondents have adopted basic IT such as PCs, internet and e-mail, only 17 per cent of respondents have adopted advanced IT adoption such as SCM, CRM and Extranet Technology for B2B business. It is found that while perceived competitive pressure and perceived benefits enable the IT adoption, lack of financial capacity, small scale operation and lack of in-house IT manpower inhibit the advanced IT adoption. Other enablers, awareness of business environment, IT experience of owner/CEO and increased information linkage with OEM/customer were found to be not significant. Similarly, lack of IT Infrastructure and lack of information security are found not impacting the advanced IT adoption, although many previous researchers have highlighted the importance. An awareness of perceived benefits of advanced IT use and competitive pressure in the global auto market is not alone enough to enhance advanced IT adoption unless inhibiters are overcome. In order to overcome the inhibitors such as lack of financial capacity, government can provide support through subsidies, tax incentives, and low interest rate loans for increasing the affordability of advanced IT such as ERP. Further, outsourcing and other models of sourcing technologies will help SMEs to overcome the issue of non-availability of skilled IT human recourses. IT service providers may offer shared services in order to enable more and more SMEs to embrace advanced IT. Alternatively, SMEs may come together to promote a cloud computing based common infrastructure and capability to overcome these inhibitors. The results of the study recognize the need for more training facilities in advanced IT for SMEs and measures to provide IT products and services at an affordable cost to SMEs. This study is conducted only in the organized sector of auto ancillaries in India. Therefore, the general applicability of the results across all unorganized sector in India and other manufacturing and service sector should be taken cautiously. 8.1 Future research directions The present study also opens new areas for further research. There may have been some other characteristics from the perspective of SMEs that affect the rate of advanced IT adoption. For example, owners’ academic qualifications, age, company’s policy, firm innovativeness etc. Future studies may investigate types of IT applications and their respective impacts on businesses. Further research may also focus on comparing the findings of this study with SMEs in other sectors for cross learning. The study findings may also be compared with adoption of advanced IT by auto ancillary SMEs in developed countries to derive lessons for SMEs in developing countries. In conclusion, proper involvement of stakeholders will result in advanced IT adoption SMEs, which would eventually lead to growth of developing nations. References ACMA (2011), “Indian automotive aftermarket study book”, White Paper on Legislative Improvements to Combat Counterfeiting, press conference, New Delhi, February. Ahuja, V., Yang, J. and Shankar, R. (2009), “Study of ICT adoption for building project management in the Indian construction industry”, Automation in Construction, Vol. 18 No. 4, pp. 415-23.

Al-Qirim, N. (2007), “The adoption of e-commerce communications and applications technologies in small businesses in New Zealand”, Electronic Commerce Research and Applications: Intelligent Agents in E-services, Vol. 6, pp. 462-73. Alba, M., Diez, L., Olmos, E. and Rodriguez, R. (2005), Global Performance Management for Small and Medium-sized Enterprises, International Federation for Information Processing Book Series, Springer, Boston, MA, pp. 1-8. Alberto, B.M. and Fernando, L.L. (2007), “A firm-level analysis of determinants of ICT adoption in Spain”, Technovation, Vol. 27, pp. 352-66. Alshawi, S. (2010), “Organisational, technical and data quality factors in CRM adoption: SMEs perspective”, Industrial Marketing Management, Vol. 40 No. 3, pp. 376-83. Apulu, I. and Latham, A. (2011), “Drivers for information and communication technology adoption: a case study of Nigerian small and medium sized enterprises”, International Journal of Business and Management, Vol. 6 No. 5. Bajwa, S.D., Lewis, F.F., Pervan, G. and Lai, S. (2005), “The adoption and use of collaboration information technologies: international comparisons”, Journal of Information Technology, Vol. 20, pp. 130-40. Barua, A., Kriebel, C.H. and Mukhopadhyay, T. (1995), “Information technologies and business value: an analytic and empirical investigation”, Information Systems Research, Vol. 6, pp. 3-23. Bassellier, G., Benbasat, I. and Reich, H. (2003), “The influence of business managers in IT competence on championing IT”, Information Systems Research, Vol. 14, pp. 317-36. Beale, M.W. (1999), “Consumer concern over e-commerce security”, E-Commerce Times, available at: www.ecommercetimes.com Bharati, P. and Chaudhury, A. (2010), “IT adoption in small and medium-sized enterprises: the role of knowledge acquisition”, Paper 141, Proceedings of Americas Conference on Information Systems, Lima, August 12-15. Brown, D.H. and Kaewkitipong, L. (2009), “Relative size and complexity: e-business use in small and medium sized tourism enterprises in Thailand”, Journal of Enterprise Information Management, Vol. 22 Nos 1/2, pp. 212-31. Brown, D.H. and Lockett, N. (2007), “E-business, innovation and SMEs: the significance of hosted services and firm aggregations”, International Journal of Entrepreneurship and Innovation Management, Vol. 7 No. 1, pp. 92-112. Cavaye, M. and Hussin, H. (2007), “IT alignment and performance in small manufacturing firms”, Journal of Strategic Information Systems, Vol. 11, pp. 109-32. Chang, J. and Cheung, L. (2001), “An empirical analysis of the barriers to implementing e-commerce in small-medium sized construction contractors in the state of Victoria”, Construction Innovation, Vol. 1, pp. 31-41. Chau, P.Y.K. (1997), “Re-examining a model for evaluating information centre success using a structural equation modeling approach”, Decision Sciences, Vol. 28, pp. 309-34. Chen, I.J. and Popovich, K. (2003), “Understanding customer relationship management: people, processes and technology”, Business Process Management Journal, Vol. 9, pp. 672-88. Chuang, T., Rutherford, M.W. and Lin, B. (2007), “Owner/manager characteristics, organizational characteristics and IT adoption in small and medium enterprises”, International Journal of Management and Enterprise Development, Vol. 4, pp. 619-34. CII (2010), “Creating competitive SMEs”, Journal of Computing, Vol. 2 No. 5. Cragg, P. and King, M. (1993), “Small-firm computing: motivators and inhibitors”, MIS Quarterly, Vol. 17 No. 1, pp. 47-53. Cragg, P., King, M. and Hussin, H. (2002), “IT alignment and performance in small manufacturing firms”, Journal of Strategic Information Systems, Vol. 11, pp. 109-32.

Advanced IT adoption by SMEs 203

JEIM 25,2

204

Crawford, J. (1998), “NEWS – a project to get smaller enterprises on line”, Department of Industry, Science and Tourism, available at: www.noie.gov.au/publications Dasgupta, S. (2000), “Information technology adoption in the Greek banking industry”, Journal of Global Information Technology Management, Vol. 3, pp. 22-30. Decker, M., Schiefer, G. and Bulander, R. (2006), “Specific challenges for small and medium-sized enterprises in M-business: a SME-suitable framework for mobile services”, Proceedings of the International Conference on E-Business, pp. 169-74. Dholakia, R.R. and Kshetri, N. (2004), “Factors impacting the adoption of the internet among SMEs”, Small Business Economics, Vol. 23 No. 4, pp. 311-22. Dixit, A.K. and Prakash, O. (2011), “A study of issues affecting ERP implementation in SMEs”, International Refereed Research Journal, Vol. 2 No. 2. Dixon, T., Thompson, B. and McAllister, P. (2002), “The value of ICT for SMEs in the UK: a critical review of literature”, Report for the Small Business Service Research Programme, The College of Estate Management, Reading. Doolin, B., McLeod, L., McQueen, B. and Watton, M. (2003), “Internet strategies for establishing retailers: four New Zealand case studies”, Journal of Information Technology Cases and Applications, Vol. 5, pp. 3-19. Duncombe, R.A. and Heeks, R.B. (2001), “Information and communication technologies and small enterprise development in Africa: lessons from Botswana”, Institute for Development Policy and Management, Vol. 16, pp. 66-87. Elizabeth, E., Grandon, J. and Pearson, M. (2004), “Electronic commerce adoption: an empirical study of small and medium US businesses”, Information & Management, Vol. 42, pp. 197-216. Flint, J. and Herbert, R. (2000), “Marketing, the internet & regional small business”, paper presented at ANZMAC 2000 Conference – Visionary Marketing for the Twenty-first Century, Facing the Challenge, Australia. Grandon, E. and Pearson, J. (2004), “Electronic commerce adoption: an empirical study of small and medium US businesses”, Information & Management, Vol. 42 No. 97, p. 216. Hashim, J. (2007), “Information communication technology (ICT) adoption among SME owners in Malaysia”, The International Journal of Business and Information, Vol. 2, pp. 221-40. Hawk, S. (2004), “A comparison of B2C e-commerce in developing countries”, Electronic Commerce Research, Vol. 4, pp. 181-99. Hinson, R. and Sorensen, O. (2006), “E-business and small Ghanaian exporters: preliminary micro firm explorations in the light of a digital divide”, Online Information Review, Vol. 30, pp. 116-38. Humprey, J. (2001), “Opportunities for SMEs in developing countries to upgrade in a global economy”, International Labour Organization (ILO), Geneva, ILO’s In Focus Programme on Small Enterprise Development (IFP-SEED). Hung-Chi Wu, S. (2001), “IT applications in SMEs – impacts of e-commerce and corresponding solutions”, Productivity, Vol. 42 No. 2, pp. 256-64. Iacovou, C., Benbasat, I. and Dexter, A. (1995), “Electronic data interchange and small organisations: adoption and impact of technology”, MIS Quarterly, Vol. 9, pp. 465-85. Igbaria, M., Zinatelli, N. and Cavaye, A.L. (1998), “Analysis of information technology success in small firms in New Zealand”, International Journal of Information Management, Vol. 18, pp. 103-19. Jeon, B.N., Han, K.S. and Lee, M.J. (2006), “Determining factors for the adoption of e-business: the case of SMEs in Korea”, Applied Economics, Vol. 38, pp. 1905-16. Johnson, M. (2010), “Barriers to innovation adoption: a study of e-markets”, Industrial Management & Data Systems, Vol. 110 No. 2, pp. 157-74.

Jones, P., Davies, P.B. and Muir, E. (2003), “E-business barriers to growth within the SME sector”, Journal of Systems and Information Technology, Vol. 7 No. 1, pp. 1-25. Julien, P.A. and Raymond, L. (1994), “Factors of new technology adoption in the retail sector”, Entrepreneurship Theory and Practice, Vol. 8, pp. 79-87. Jun, M. and Cai, S. (2003), “Key obstacles to EDI success: from the US small manufacturing companies’ perspective”, Industrial Management & Data Systems, Vol. 103 No. 3, pp. 192-203. Kartiwi, M. and MacGregor, R.C. (2007), “Electronic commerce adoption barriers in small to medium-sized enterprises in developed and developing countries: a cross-country comparison”, Journal of Electronic Commerce in Organizations, Vol. 5 No. 3. Khemthong, S. and Roberts, L.M. (2006), “Adoption of internet and web technology for hotel marketing: a study of hotels in Thailand”, Journal of Business Systems, Governance and Ethics, Vol. 1 No. 2, pp. 47-60. Kirby, D. and Turner, M. (1993), “IT and the small retail business”, International Journal of Retail and Distribution Management, Vol. 21, pp. 20-7. Koshy, P. (2011), “Adoption of information and communications technology in rural micro and small enterprises (MSEs)”, Paper No. 2, Institute for Development Studies and Enterprise Research, Samadhan Foundation, Kerala. Kotelnikov, V. (2007), “Small and medium enterprises and ICT”, Asia-Pacific Development Information Programme, available at: www.apdip.net Kuan, K. and Chau, P. (2001), “A perception-based model of EDI adoption in small business using technology-organization-environment framework”, Information and Management, Vol. 38, pp. 507-21. Kumar, K. (2007), “SMEs and globalization: auto clusters ICT diagnostic study”, National Institute of Science, Technology & Development Studies (NISTADS), New Delhi. Lai, F. and Hsieh, C.T. (2007), “On network external, e-business adoption and information asymmetry”, Industrial Management & Data Systems, Vol. 107, pp. 728-46. Lal, K. (2002), “E-business and manufacturing sector: a study of small and medium-sized enterprises in India”, Research Policy, Vol. 31, pp. 1199-211. Lauder, G. and Westall, A. (1997), “Small firms on-line”, Commission on Public Policy and British Business, Institute for Public Policy Research (IPPR), London, pp. 51-68, Vol. 6. Lertwongsatien, C. and Wongpinunwatana, N. (2003), “E-commerce adoption in Thailand: an empirical study of small and medium enterprises (SMEs)”, Journal of Global Information Technology Management, Vol. 6 No. 3, pp. 67-83. Levy, M. and Powell, P. (2003), “Exploring SME internet adoption: towards a contingent model”, Electronic Markets, Vol. 3, pp. 173-81. Levy, M., Powell, P. and Yetton, P. (2001), “SMEs: aligning IS and the strategic context”, Journal of Information Technology, Vol. 6, pp. 133-44. Lowry, G., Singh, M. and Scollary, A. (1999), “Electronic commerce initiatives in Australia: identifying opportunity, meeting challenges, and measuring success”, Proceedings of the 10th Australasian Conference on Information Systems, pp. 532-41. Lucchetti, R. and Sterlacchini, A. (2001), “Factors affecting the adoption of ICTs among SMEs: evidence from an Italian survey”, Quaderni Di Ricerca, No. 155. Lymer, A. (1997), “The internet and small businesses: a study of impacts”, Fifth European Conference on Information Systems, Cork Publishing, Cork. MacGregor, R.C. (2004), “Factors associated with formal networking in regional small business: some findings from a study of Swedish SMEs”, Journal of Small Business and Enterprise Development, Vol. 11, pp. 60-74.

Advanced IT adoption by SMEs 205

JEIM 25,2

206

MacGregor, R.C. and Vrazalic, L. (2005), “A basic model of electronic commerce adoption barriers: a study of regional small businesses in Sweden and Australia”, Journal of Small Business and Enterprise Development, Vol. 12 No. 4, pp. 510-27. Magnusson, M. (2001), “E-commerce in small businesses – focusing on adoption and implementation”, Proceedings of the 1st Nordic Workshop on Electronic Commerce, Halmstad. Martin, L.M. and Matlay, H. (2001), “Blanket approaches to promoting ICT in small firms: some lessons from the DTI ladder adoption model in the UK”, Internet Research, Vol. 11, pp. 399-411. Mehrtens, J., Cragg, P.B. and Mills, A.M. (2001), “A model of internet adoption by SMEs”, Information & Management, Vol. 39, pp. 165-76. Mendo, F.A. and Fitzgerald, G. (2005), “A multidimensional framework for SME e-business progression”, Journal of Enterprise Information Management, Vol. 18, pp. 678-96. Mirchandani, A.A. and Motwani, J. (2001), “Understanding small business electronic commerce adoption: an empirical analysis”, Journal of Computer Information Systems, Spring, pp. 70-3. Moodley, S. (2002), “Internet-enabled supply chain integration: prospects and challenges for the South African automotive industry”, Development Southern Africa, Vol. 18, pp. 165-78. Mpofu, C. and Watkins-Mathys, L. (2011), “Understanding ICT adoption in the small firm sector in Southern Africa”, Journal of Systems and Information Technology, Vol. 13 No. 2, pp. 179-99. NASSCOM (2007), “IT adoption in the Indian auto component industry”, NASSCOM Review report, NASSCOM, New Delhi. NASSCOM (2009), “The Indian IT industry: overcoming challenges, harnessing opportunities and embracing innovation”, NASSCOM Strategic Review, NASSCOM, New Delhi. NMCC and NASSCOM (2010), “A roadmap to enhance ICT adoption in the Indian manufacturing sector”, review report, National Manufacturing Competitiveness Council, New Delhi. Ongori, H. and Migiro, S.O. (2010), “Information and communication technology adoption: a literature review”, Journal of Chinese Entrepreneurship, Vol. 2, pp. 93-104. Packale´n, K. (2010), “ICT capabilities and possibilities in micro-firms: a study of micro-firms in ˚ land Islands archipelago”, 23rd Bled e-Conference on e-Trust, Slovenia. the A Parker, C.M. and Castleman, T. (2007), “New directions for research on SME-ebusiness: insights from an analysis of journal articles from 2003 to 2006”, Journal of Information Systems and Small Business, Vol. 1 Nos 1-2, pp. 21-40. Pillania, R.K. (2008), “Information technology strategy for knowledge management in Indian automotive components SMEs”, Knowledge and Process Management, Vol. 15, pp. 203-10. Poon, S. and Swatman, P.M.C. (1999), “A longitudinal study of expectations in small business internet commerce”, International Journal of Electronic Commerce, Vol. 3, pp. 21-33. Premkumar, G. and Roberts, M. (1999), “Adoption of new information technologies in rural small businesses”, The International Journal of Management Science, Vol. 27, pp. 467-84. Premkumar, G., Ramamurthy, K. and Crum, M. (1997), “Determinants of EDI adoption in the transportation industry”, European Journal of Information Systems, pp. 107-21. Quayle, M. (2002), “E-commerce: the challenge for UK SMEs in the twenty-first century”, International Journal of Operations & Production Management, Vol. 22, pp. 1148-61. Ramdani, B., Kawalek, P. and Lorenzo, O. (2009), “Predicting SMEs’ adoption of enterprise systems”, Journal of Enterprise Information Management, Vol. 22, pp. 10-24. Ratnasingam, P. (2001), “Electronic commerce adoption in Australia and New Zealand”, Malaysia Journal of Computer Sciences, Vol. 4, pp. 223-42.

Raymond, L. and Bergeron, F. (2008), “Enabling the business strategy of SMEs through e-business capabilities: a strategic alignment perspective”, Industrial Management & Data Systems, Vol. 108 No. 5, pp. 577-95. Reynolds, A. and Bopaya, B. (1994), “Challenges facing information technology to support world class manufacturing”, Computers in Industry, Vol. 28, pp. 163-5. Riemenschneider, C.K., Harrison, D.A. and Mykytyn, P.P. (2003), “Understanding IT adoption decisions in small business: integrating current theories”, Information and Management, Vol. 40 No. 4, pp. 269-85. Riquelme, H. (2002), “Commercial internet adoption in China: comparing the experiences of small, medium and large businesses”, Internet Research: Electronic Networking Applications and Policy, Vol. 2 No. 3, pp. 276-86. Sabherwal, R., Jeyaraj, A. and Chowa, C. (2006), “Information system success: individual and organizational determinants”, Management Science, Vol. 52 No. 12, pp. 849-64. Samad, N.A. (2007), “Positioning Malaysian SMEs in the global”, Proceedings of Persidangan Kebangsaan IKS 2007, University Utara Malaysia, Kota Kinabalu. Sanna, L., Sami, S. and Petri, H. (2007), “Enterprise size matters: objectives and constraints of ERP adoption”, Journal of Enterprise Information Management, Vol. 20 No. 3, pp. 319-34. Sarosa, S. (2005), “Information technology adoption process within Indonesian SMEs: an empirical study”, Australasian Conference on Information Systems, Sydney. Sarosa, D. and Underwood, J. (2005), “A research framework for the electronic procurement adoption process: drawing from Australian evidence”, Journal of Global Business and Technology, Vol. 1. Scupola, A. (2003), “The adoption of internet commerce by SMEs in the south of Italy: an environmental, technological and organizational perspective”, Journal of Global Information Technology Management, Vol. 6, pp. 3-18. Seyal, A.H., Awais, M.M., Shamail, S. and Abbas, A. (2004), “Determinants of electronic commerce in Pakistan: preliminary evidence from small and medium enterprises”, Electronic Markets, Vol. 14, pp. 372-87. Seyal, A.H., Abd Rahman, M.N. and Hj Awg Mohamad, H.A.Y. (2007), “A quantitative analysis of factors contributing electronic data interchange adoption among Bruneian SMEs”, Business Process Management Journal, Vol. 13 No. 5, pp. 728-46. Sharma, M.K. and Bhagwat, R. (2006), “Practice of information systems: evidence from select Indian SMEs”, Journal of Manufacturing Technology Management, Vol. 17 No. 2, pp. 199-223. Sheth, J.N. and Sharma, A. (2005), “International e-marketing: opportunities and issues’”, International Marketing Review, Vol. 22 No. 6, pp. 611-22. Shiau, W., Hsu, P. and Wang, J. (2009), “Development of measures to assess the ERP adoption of small and medium enterprises”, Journal of Enterprise Information Management, Vol. 22, pp. 99-118. Simpson, M. and Docherty, A.J. (2004), “E-commerce adoption support and advice for UK SMEs”, Journal of Small Business and Enterprise Development, Vol. 11 No. 3, pp. 315-28. Singh, R.K., Garg, S.K. and Deshmukh, S.G. (2007), “Strategy development for competitiveness: a study on Indian auto component sector”, International Journal of Productivity and Performance Management, Vol. 56 No. 4, pp. 285-304. Somuyiwa, A.O. and Adewoye, J. (2010), “O Managing logistics information system: theoretical underpinning”, Asian Journal of Business Management, Maxwell Scientific Organization, Vol. 2, pp. 41-7. Somuyiwa, A. and Adebayo, T. (2011), “Analysis of information and communication technologies (ICT) usage on logistics activities of manufacturing companies in Southwestern Nigeria”, Journal of Emerging Trends in Economics and Management Sciences, Vol. 2, pp. 68-74.

Advanced IT adoption by SMEs 207

JEIM 25,2

208

Spectrum (1997), Moving into the Information Society, HMSO, London. Srinivasan, R., Lilien, G. and Rangaswamy, A. (2002), “Technological opportunism and radical technology adoption: an application to e-business”, Journal of Marketing, Vol. 66, pp. 47-61. Stuti, K.I. (2005), “Overcoming barriers to innovation for Indian SMEs”, Ministry of Small Scale Industries, New Delhi. Tan, K.S. and Eze, U. (2008), “An empirical study of internet-based ICT adoption among Malaysian SMEs”, Communications of the IBIMA Malaysia, Vol. 1. Tan, K., Chong, S., Lin, B. and Eze, U. (2009), “Internet-based ICT adoption: evidence from Malaysian SMEs”, Industrial Management & Data Systems, Vol. 109, pp. 224-44. Taylor, M.J., McWilliam, J., England, D. and Akomode, J. (2004), “Skills required in developing electronic commerce for small and medium enterprises: case based generalization approach”, Electronic Commerce Research and Applications, Vol. 3, pp. 253-65. Teo, T. and Pian, Y.A. (2003), “contingency perspective on internet adoption and competitive advantage”, European Journal of Information Systems, Vol. 2, pp. 78-92. Thakkar, J., Arun, K. and Deshmukh, S.G. (2008), “Interpretive structural modeling (ISM) of IT-enablers for Indian manufacturing SMEs”, Information Management & Computer Security, Vol. 16, pp. 113-36. Todd, P.R. and Javalgi, R. (2007), “Internationalization of SMEs in India. Fostering entrepreneurship by leveraging information technology”, International Journal of Emerging Markets, Vol. 2 No. 2, pp. 160-88. Toussea-Oulai, A. (2007), “Information technology transfer: problems facing African developing nations”, International Journal of Human Computer Interaction, Vol. 3, pp. 79-93. Tsao, H., Lin, K. and Lin, C. (2004), “An investigation of critical success factors in the adoption of B2B EC by Taiwanese companies”, Journal of American Academy of Business, Vol. 5, pp. 198-202. UNDP (2005), “International cooperation at a crossroad: aid, trade and security in an unequal world”, Summary Human Development Report, United Nations Development Programme, New York, NY. Voges, K.E. and Pulakanam, V. (2011), “Enabling factors influencing internet adoption by New Zealand small and medium size retail enterprises”, International Review of Business Research Papers, Vol. 7 No. 1, pp. 106-17. Wainwright, D., Green, G., Mitchell, E. and Yarrow, D. (2005), “Toward a framework for benchmarking ICT practice, competence and performance in small firms”, The International Journal for Library and Information Services, Vol. 6, pp. 39-52. Wang, S.D. (2003), “The implications of e-financing: implications for SMEs”, Bulletin on Asia-Pacific Perspective, United Nations, New York, NY. Windrum, P. and de Berranger, P. (2003), “Factors affecting the adoption of intranets and extranets by SMEs: a UK study”, Research Memoranda, Maastricht Economic Research Institute on Innovation and Technology, Maastricht. Wood, C.M. (2004), “Marketing and e-commerce as tools of development in the Asia-Pacific: a dual path”, International Marketing Review, Vol. 21 No. 3, pp. 301-20. Wymer, S. and Regan, E. (2005), “Factors influencing e-commerce adoption and use by small and medium businesses”, Electronic Markets, Vol. 15, pp. 412-38. Yesbank (2009), “Technology for financial efficiency”, YES BANK’s Knowledge Banking Publication, Vol. 1 No. 1. Yulong Li (2011), “ERP adoption in Chinese small enterprise: an exploratory case study”, Journal of Manufacturing Technology Management, Vol. 22 No. 4, pp. 489-505. Zhu, K., Kraemer, K. and Xu, S. (2003), “Electronic business adoption by European firms: a cross-country assessment of the facilitators and inhibitors”, European Journal of Information Systems, Vol. 12 No. 4, pp. 251-68.

Appendix 1

Construct

Items

Enablers for IT adoption (Independent variable)

Perceived benefits of IT use Changes in business environment IT experience of owner/CEO Increased information linkage with OEM/customer Perceived competitive pressure Lack of financial capacity Lack of in-house IT manpower Small scale operation Lack of IT Infrastructure Lack of information security No. of PCs (computers) currently exists Networking of computers Type of internet connectivity Intranet/extranet facility Do you have own web sites No of portals supported your web site Enterprise Computing Technologies & Software Groupware/Collaborative Computing Software Production supported software No. of IT personnel

Inhibiters for IT adoption (Independent variable)

Level of advanced IT adoption (Dependant variable)

Corresponding author G. Kannabiran can be contacted at: [email protected]

To purchase reprints of this article please e-mail: [email protected] Or visit our web site for further details: www.emeraldinsight.com/reprints

Advanced IT adoption by SMEs 209

Table AI. Table of Construct and its variables