Investigating the Success of ERP Systems:Case Studies in there Taiwanese High Tech Industries

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Investigating the success of ERP systems: Case studies in

three Taiwanese high-tech industries

Shih-Wen Chien

a,

*

, Shu-Ming Tsaur

b

a_{National Pingtung Institute of Commerce, Department of Commerce Automatic & Management,}

51 Min Sheng E. Road, Pingtung 900, Taiwan, ROC

b

Department of Management Information, Ching Yun University, Jhongli, Taiwan 320, ROC Received 7 December 2005; received in revised form 6 December 2006; accepted 5 February 2007

Available online 23 March 2007

Abstract

The measurement of enterprise resource planning (ERP) systems success or effectiveness is critical to our understanding of the value and efficacy of ERP investment and managerial actions. Whether traditional information systems success models can be extended to investigating ERP systems success is yet to be investigated. This paper proposes a partial extension and respecification of the DeLone and MacLean model of IS success to ERP systems. The purpose of the present research is to re-examine the updated DeLone and McLean model [W. DeLone, E. McLean, The DeLone McLean model of information system success: a ten-year update, Journal of Management Information Systems 19 (4) (2003) 3–9] of ERP systems success. The updated DeLone and McLean model was applied to collect data from the questionnaires answered by 204 users of ERP systems at three high-tech firms in Taiwan. Finally, this study suggests that system quality, service quality, and information quality are most important successful factors.

Keywords: ERP success model; DeLone and McLean model; High-tech firms

1. Introduction

Organizations today are constantly in search for ways to achieve better business performance and sustain competitive advantages through effective deployment of resources and business processes. To improve business performance, orga-nizations require an efficient planning and control system that synchronizes planning of all processes across the organization. The key to competitiveness lies in a solid information system (IS) infrastructure seamlessly aligned with core business processes developed for the delivery of high quality products and services to customers within the optimal time. These demands have prompted more firms to shift their IS strategies from developing in-house information systems to purchasing application software, such as ERP systems, to generate synergies and enhance operating efficiency[1].

However, scarce literature has concentrated on measuring success for an ERP system. Although it is very important to evaluate the success of ERP implementation projects since a lot of financial and human resources are invested, Bradford and

Sandy [2] reported that 57% of the interviewed companies

launched no assessments on the performance of ERP systems owing to lack of empirically effective evaluation models.

Information systems (IS) success is one of the most widely used dependent variables in information systems research. Not surprisingly, much attention has been given to how best to measure it (e.g.,[3–6]).

This research accordingly attempts to propose a success model for ERP systems and to empirically investigate the multi-dimensional relationships among the success measures. Addi-tionally, three case firms among the success measures are also empirically tested. In this paper, I do not assess more complex concepts, such as right information needs or users’ interest because it is difficult to get a reliable measure of this kind of attributes just by interviewing. The goal is to obtain the users’ perceptions about the importance of CSF in order to establish a rank among them. It is a valuable effort, since IS users and IS experts have significantly different perceptions on IS success[7].

www.elsevier.com/locate/compind Computers in Industry 58 (2007) 783–793

* Corresponding author. Tel.: +886 8 7238700x2110; fax: +886 8 7235648. E-mail addresses:swchien@npic.edu.tw(S.-W. Chien),tsaur@cyu.edu.tw (S.-M. Tsaur).

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2. Theoretical overview 2.1. Impact of ERP systems

Literature on the impact of ERP systems is growing. However, most studies in the literature are interviews, case studies, and industry surveys[8–10]. Participating companies reported substantial performance improvement in several areas thanks to the ERP systems, such as the ability to provide real-time information to customers, shorter production cycle, and on-time completion rates.

2.2. Information system success model

The success of IS is widely recognized by practitioners and academics as a difficult concept to define even many studies have endeavored to describe and justify the evaluation of IS success[3,4,6,11–13]. An IS has many stakeholders, each with a different definition of system success. IS development projects have been plagued by budget overruns and unmet user

requirements [14]. Thus, from a developer’s perspective, a

successful IS may be one that is completed on time and under budget, with a complete set of features that are consistent with specifications and that function correctly. From an innovator’s perspective, a successful system is one that attracts a large, loyal, and growing community of users. More recently, Jiang et al.[7]identified a set of critical success factors for system development including clearly defined goals, top management support, sufficient resources, competent team members, and adequate communication. So, from a management perspective, a successful system may be one that reduces uncertainty of outcomes and thus lowers risks, and leverages scarce resources. From the end user’s perspective, a successful system may be one that improves the use’s job performance without inflicting

undue annoyance. For example, Saarinen’s paper[15]provided

four metrics of system success. These included (1) the satisfaction with the development process, (2) satisfaction with system use, (3) satisfaction with the quality of the IS product, and (4) impact of the IS on the organization.

Meanwhile, researchers had developed a large number of system success criteria. Many had been empirically tested, including: system quality [16], user information satisfaction (UIS)[17], quality of decision making[18], IS usage[19], and productivity from a cost/benefit standpoint[20]. User percep-tions had become particularly prominent within the IS literature

[18]. The use of these psychometric measures was due to the

difficulty in quantifying and linking costs and benefits to particular IS innovations.

One of the most important and popular works on IS success model is the DeLone and McLean model (D&M IS success

model). DeLone and McLean[3]proposed a taxonomy and an

interactive model as the framework for conceptualizing IS success. But, not all of the researchers have attempted to critique or modify the D&M IS success model. Some have developed and proposed alternate frameworks for measuring IS effectiveness.

After synthesize the previous studies, DeLone and McLean

[3] using the six dimensions of IS success model—‘‘Success

Quality, Information Quality, Information Use, User Satisfac-tion, Individual Impact and Organizational Impact’’ to evaluate the success of IS. Since then, approximately 300 articles in refereed journals have referred to, and made use of, this IS success model. The broad fame of the model is strong evidence of the need for an extended framework in order to integrate IS research findings.

The description and examples of measures for these six dimensions are as follows. First, system quality denotes system performance like data accuracy, system efficiency, response time, etc. Second, information quality refers to the quality of the IS product, such as currency, relevance, reliability, and completeness. Third, use refers to the frequency an information system is used, examining items like the number of functions used, frequency of access, and amount of connecting time. Fourth, user satisfaction records the satisfaction level as reported by system users, including overall satisfaction and interface satisfaction, etc. Fifth, individual impact refers to measuring the impacts brought about by the information system on individual users, such as changes in productivity, decision model, and decision-making. Sixth, organizational impact requires the evaluation of the changes caused by the information system to the organization, such as decreases in operating costs, savings in labor costs, and growth in profits (Fig. 1).

According to the D&M IS success model, both system quality and information quality influence use and user’s satisfaction, which in turn shape the impacts of the system on individual users and the organization. The reason for the existence of different measures for IS success is understandable when one considers ‘‘information’’ as the output of a system that can be measured at different levels – the personnel level, the technical level, the semantic level, and the effectiveness level – and different stakeholders are involved at each level.

However, Seddon and Kiew [84] recommend replacing

use with usefulness, stating that use only affects satisfaction

when use is voluntary. Seddon and Kiew [85] placed use

outside a revised model of system success because it was

Fig. 1. D&M IS success model, DeLone and McLean[3]. S.-W. Chien, S.-M. Tsaur / Computers in Industry 58 (2007) 783–793 784

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deemed more a characteristic of user behavior than a

measure of system success[6].

The primary purpose of the original D&M IS success model was to synthesize previous studies on IS success into a more coherent body of knowledge and to provide guidance to future studies[4]. The role of IS has changed and progressed during the last decade. Similarly, academic inquiry into the measure-ment of IS effectiveness has also advanced over the same period

[4]. DeLone and McLean introduced an updated D&M IS

success model as foundation for positioning and comparing IS empirical research.

Changes have occurred in the past decade. The role of IS has progressed, as well as IS management. ERP systems have become more prevalently adopted for integrated IS services companywide. Since ERP systems are usually complicated IS packages, the service quality of MIS department, ERP vendors and ERP consultants has become more critical than the service quality provided for isolated information systems before.

The quality of MIS service, as perceived by its users, becomes a key indicator of IS success[21]. MIS departments evaluate user satisfaction primarily to improve their service quality [22]. Nowadays, ‘‘service quality’’ as the overall support delivered by the service provider applies no matter this support is delivered by the MIS department or a new organizational unit, or outsourced to an Internet service provider (ISP); poor support, for whatever reason, will result in lost customers and sales recession [4]. However, commonly used measures of IS effectiveness focus on products, rather than services, of the IS function. Thus, there is a risk that IS researchers will misjudge IS effectiveness if they do not include a measure of IS service quality in their assessment package[23]. Pitt et al. [23]propose a model of information system success similar to the DeLone and McLean model, except service quality is included as one of the dimensions that affect use and user satisfaction.

In response to the progresses in IS applications, DeLone and McLean proposed an updated version in 2003. Service quality was added to the success model, and the individual impact and organizational impact were combined into a single variable named ‘‘net benefits’’. To catch up with the advancements of its applications, IS not only needs to provide users with information products but also to meet users’ flexible information require-ments. Service quality is thus added to the updated model to measure the service-level success since system quality focuses more on technology-level measure. Since it is difficult to describe the multi-dimensional aspects of IS use—mandatory or

voluntary use, informed or un-informed use, effective or ineffective use, DeLone and McLean further suggested that ‘‘intention to use’’ may be adopted as an alternative measure for IS use in some contexts. Certain net benefits can occur as results of IS use or intention to use and user satisfaction.

The impact that information has on organizational perfor-mance is difficult to isolate amidst many other factors, both internal and external to the firm. Some researchers have attempted to look at the value of technology investments through quantifiable financial measures such as investment and ROI, market share, cost, productivity analysis, productivity paradox, and profitability.

Other studies have investigated relationships between information systems and qualitative measures, such as organizational structure, change, efficiency, responsiveness, coordination, flexibility, increased quality of decision-making,

and increased quality of work life [11,24–27]. Other

researchers have attempted to measure organizational impact by looking at the result of the IS function, such as measuring the quality of customer service and assessing the amount of resulting competitive advantage[26–31].

Net benefits are the most important success measures as they capture the balance of positive and negative impacts of the ERP system on organizations. Positive net benefits may encourage the use intention of ERP system and increase user satisfaction, while negative net benefits can decrease the intention to use and IS user satisfaction (Fig. 2).

3. Background and hypothesis development

The ‘‘ERP system experience cycle’’ framework[32]which

is based on Soh and Markus’[86]model is adopted to delineate the ERP adoption process in this study. The framework models an organization’s experience with ERP system from adoption to success as moving through four phases characterized by key players, typical activities, characteristic problems, appropriate performance metrics, and a range of possible outcomes. This paper is focused on exploring the project and shakedown phases of the framework, more commonly known as implementation phases.

3.1. Applying the IS success model in the research context Following the logic framework of the updated DeLone and McLean model for IS success, this study proposes a success

Fig. 2. Updated D&M IS success model, DeLone and McLean[4].

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[84] P.B. Seddon, M. Kiew, A partial test and development of the DeLone and McLean’s model of IS success, in: Proceedings of the International Conference on Information System, 1994, pp. 99–110.

[85] P.B. Seddon, M. Kiew, A partial test and development of the DeLone and McLean’s model of IS success, Australian Journal of Information System 4 (1) (1996) 90–109.

[86] C. Soh, M.L. Markus, How IT creates business value: A process theory synthesis, in: J. Degross, G. Ariav, C. Beath, R. Hoyer, C. Kemerer (Eds.), Proceedings of the Sixteenth International Conference on Information Systems, Amsterdam, 1995.

[87] A. Parasuraman, V.A. Zeithaml, L.L. Berry, Reassessment of expectations as a comparison standard in measuring service quality: implications for further research, Journal of Marketing 58 (1994) 111–123.

[88] J.A. Martilla, J.C. James, Importance-performance analysis, Journal of marketing January (1977) 77–79.

[89] J.M. Hawes, C.P. Rao, Using importance-performance analysis to develop health care marketing strategies, Journal of Health Care Marketing 5 (4) (1985) 19–25.

Shih-Wen Chienreceived a PhD of e-Business Man-agement in the Department of Business Administra-tion at NaAdministra-tional Central University. He is an assistant professor in the Department of Commerce Automatic & Management at National Pingtung Institute of Commerce (Taiwan, ROC). His current research inter-ests center on ERP Performance Measurement, Knowledge Management and Financial Information Management. He has published the research paper in International Journal of Production Economics.

Shu-Ming Tsaurreceived his PhD in MIS from the National Chengchi University (Taiwan, ROC), and is an assistant professor in the Department of MIS at Ching Yun University (Taiwan, ROC). His research interests include e-Business, Electronic Commerce, MIS and Financial Information Systems.