An Empirical Investigation of Successful Enterprise Systems Stabilization and Production Support

Transcription

1 An Empirical Investigation of Successful Enterprise Systems Stabilization and Production Support Amin Ahmad Shaqrah Faculty of Economics & Administrative Sciences Al-Zaytoonah University of Jordan-Jordan DOI: /jsi.v6i2.221 Abstract: In this paper is a conceptual framework that examines the antecedents and consequences successful enterprise systems stabilization and production support and test its empirical validity. Top managements support, production strategy, education and training, vendor selection, business process reengineering, project team competence, high cost, change of management, and language barrier were applied as a antecedents and consequences to establish the theoretical foundation. An empirical test of the model is conducted. The results had shown that positive effects of all antecedents and consequences on successful enterprise systems stabilization and production support. Limitations of this paper for future studies and practice are presented at the end. Keywords: Enterprise systems, Stabilization, Production support, SEM, Jordan. 1. Introduction Enterprise systems are made up of a suite of integrated software applications that are designed to support a business core functions (Aldwani, 2001; Amaoko, 2004). Enterprise systems help organizations to reduce operating costs and improve business process management through integration of business functions and information (Aldwani, 2001). Despite the advantages associated with ERP systems, their adoption is often problematic (Amaoko, 2004). Approximately 50% of all ERP implementations fail to meet the adopting organizations expectations (Jasperson et al., 2005; Adam & O Doherty, 2000). This paper contributes to the systems literature by broadening our understanding of antecedents constructs successful enterprise systems stabilization and production support. Since the early 2000, major corporations in the Jordan and other industrialized nations have implemented enterprise systems in order to integrate their functional areas information systems into a coherent, enterprise-wide, web-enabled distributed network. However, few companies reported that their initiatives had achieved significant value and much can be learned to improve their chances of success. The most commonly cited obstacles to enterprise systems stabilization and production support in the Jordan are that it is too expensive and too complicated. This paper examines the role of top managements support, production strategy, education and training, vendor selection, business process reengineering, project team competence, high cost, change of management, and language barrier on successful stabilization and production support. Despite high expectations, many Jordanian executives are still not certain that enterprise systems will in fact add value to their companies. While many of these concerns are consistent with the global stabilization and production support trends, some are unique to Jordan. Indeed, research results covering a variety of technologies implemented in many different kinds of industries have found that changes induced by information technology are often resisted, and that serious modification of intended changes is common practice. Jordan-specific concerns include cultural and language barriers, lack of IT infrastructure, and lack of incentives for enterprises. This paper investigated the early trends of stabilization and production support of enterprise systems in Jordan based on an executive survey of fifteen companies and tries to describe key antecedents affecting the enterprise systems success. Our research methodology includes pilot studies, pretests, and survey questionnaire. Statistical analysis consists of descriptive statistics with hypothesis testing, reliability and validity tests, and structured equation modeling analysis. Managerial insights and policy implications relevant to enterprise systems stabilization and production support concerns are discussed. 32 OURNAL OF SYSTEMS INTEGRATION 2015/2

2 AN EMPIRICAL INVESTIGATION OF SUCCESSFUL ENTERPRISE SYSTEMS STABILIZATION AND PRODUCTION SUPPORT 2. A Conceptual Framework The adoption of enterprise systems has been investigated for decades, and existing models of technology adoption and diffusion have linked a complex network of system, organizational, individual, and social factors to adoption decisions (e.g. Palaniswamy and Frank, 2000; Bingi et al., 1999). Recent research has shown that firms adopt ERP in part because of human and social factors that complement more systematic cost-benefit analyses. Understanding the effects of these factors is important because adoption decisions primarily based on factors would seemingly result in limited understanding of how a system contributes to a specific organization. The most commonly discussed critical success factors (CSFs) of ERP implementation include (Akkermans & Helden, 2002; Bingi et al., 1999): Top management support, implementation strategy, education and training, vendor selection and support, change management and business process reengineering (BPR), project champion, project management, management of expectation, clear goals and objectives, and project team competence. The role of top management in making ERP decisions includes developing an understanding of capabilities and limitations, establishing reasonable goals, exhibiting strong commitment to the successful introduction of enterprise applications, and communicating the strategic objectives and the vision of the organization. ERP, supply chain management (SCM), customer relationship management (CRM), and other enterprise applications are traditionally thought of as independent software applications, but now companies are making all those processes accessible through an integrated information system, network, or extended ERP systems. In fact, project team competence, BPR, and the cost are among the key determinants of ERP decisions for enterprises in Jordan. ERP systems intend to enhance organizational cross-functional efficiency and effectiveness through the seamless integration of all the information flowing through such functional areas as financial and accounting, human resource, supply chain, and customer service (Palaniswamy and Frank, 2000). The key drivers for investing in ERP are identified as increased efficiency, increased revenue, and cost reductions (Everdinggen et al., 2002). Other potential benefits of ERP implementation include improved communications, enhanced operations flexibility, improved customer service, reduced inventory level, and streamlined BPR (Norris et al., 2000). BPR has long been considered one of the key success factors in implementing major IT projects such as ERP, especially in enterprises that have a strong corporate culture and in those that rely heavily on legacy systems (Grover et al., 1995). BPR involves a fundamental rethinking and redesign of business processes to achieve improvement in critical measures of performance, such as cost, quality, customer service, and speed to market (Hammer, 2000). BPR requires a commitment for change not only by top management as a must, but also by everyone else in the firm, which goes hand in hand with ERP (Jacobs & Whybark, 2000). ERP applications might lose favor if companies are scared away by high implementation costs and complicated project management process, by lack of key CSF s, and by lack of an essential BPR and change management. While ERP has a great market potential, its implementation is undoubtedly facing many challenges and obstacles in Jordan. Since the vast majority of Jordanian enterprises would, at best, be classified as large-size companies with annual sales ranging from $4 to $50 million, the high cost of ERP implementation is by far the largest challenge in making ERP decisions in Jordan. Since the top ten multinational ERP vendors, such as Oracle, SAP, and Microsoft, account for 92% of the current ERP market in Jordan. ERP implementation complexity, due to cultural and language barriers in Jordan, is the second largest challenge. Other major challenges to ERP implementation include lack of IT infrastructure and lack of incentives for enterprises. Implementation of ERP influences various practices and processes and has been suggested to be a significant influencing factor in the future direction of organizations including their strategic development for a summary of critical issues in ERP management (Scapens & Jazayeri, 2003), ERP is not a strategy; it is a mechanism for implementing a strategy (Rikhardsson & Kraemmergaard, 2006). In examining the influence of ERP in the quest for integration Dechow & Mouritsen s (2005) suggested that ERP systems do not define what integration is and how it is to be developed. It may seem difficult to decouple the technology from the strategy since technological functions and limitations within ERP systems have large influences on what can and cannot be done within the technology. But an interesting aspect of Dechow and Mouritsen s (2005) study illustrated how technology and strategy are decoupled; they suggested that firms implement boundary objects to overcome systembased blind spots, illustrating the division of the strategy and the technology. In other words, ERP systems facilitate integration, but when the system cannot meet all the organization s needs, other JOURNAL OF SYSTEMS INTEGRATION 2015/2 33

3 AMIN AHMAD SHAQRAH mechanisms are implemented to compensate for the ERP system s shortfalls. Nonetheless, practices embedded in ERP systems tend to spread among organizations that adopt ERP systems (Soh et al., 2000).Figure 1 illustrated the conceptual framework. TMS IS ET VS BPR ESSPS PTC HC CM LB * Figure 1. A Conceptual Framework Model *TMS: Top Management Support, IS: Implementation Strategy, ET: Education and Training, VS: Vendor Selection, BPR: Business Process Reengineering, PTC: Project Team Competence, HC: High Cost, CM: Change of Management, LB: Language Barrier, ESSPS: Enterprise Systems Stabilization and Production Support. 3. Research Methodology The overall approach employed was a field study using a survey methodology for data collection. The data were collected from executives subjects that worked with enterprise systems to perform their tasks. The survey data were gathered using questionnaires administered to the full time employees of the organizations belonging to various industries. Each organization was selected among companies with recent deployment of enterprise systems, based on the client list provided by ERP vendors. A total of seventy two questionnaires were distributed and sixty two were returned. The returned questionnaires were initially screened for usability and reliability. Finally, forty four responses were found to be complete and usable, rendering a net response rate of approximately 62% percent. The respondent characteristics were analyzed in terms of gender, age, educational background, and tenure. Gender distribution indicated an approximate 1.8:1 ratio in favor of male employees. On average, respondents were approximately forty-one years old. About 13.3 percent had a high school education, with the remainder of respondents (86.7% percent) having at least a Bachelor s degree. Respondents had on average about sixteen years of work experience. To ensure the content validity of the scales, items used to operationalize the constructs included in this study were mostly adapted and modified from previous studies, with some changes necessary for the target information system and the organizational context. All question items were measured using a five-point Likert-type scale, with anchors ranging from strongly disagree to strongly agree. 4. Analysis The data were analyzed using EQS based on the structural equation modeling approach. Data analysis was carried out in accordance with a two-stage methodology to avoid the possible interaction between measurement and structural equation models. 34 JOURNAL OF SYSTEMS INTEGRATION 2015/2

4 AN EMPIRICAL INVESTIGATION OF SUCCESSFUL ENTERPRISE SYSTEMS STABILIZATION AND PRODUCTION SUPPORT 4.1 Measurement Model A confirmatory factor analysis (CFA) using EQS was conducted to test the measurement model. The overall goodness-of-fit of the measurement model was examined using the following eight common model fit measures: X 2 /df ratio, GFI, AGFI, NFI, NNFI, CFI, RMSR, and RMSEA. The measurement model in the CFA was revised by removing items, one at a time that had large standardized residuals and/or weak correlations with other items. After removing items, as summarized in Table 1, the measurement model exhibited an overall good model fit, with the data collected from the respondents by meeting the acceptance levels commonly suggested by previous research. The exception was for the GFI level. GFI at was slightly below but closer to the recommended level Although the GFI level could be improved by dropping additional items, it was decided to stop the dropping procedure by considering the content of the measurement. Recognizing the good model fit for the measurement model, further analysis was conducted to assess the psychometric properties of the scales; that is, for the construct validity of the research instruments. The construct validity has two important dimensions: convergent validity and discriminant validity. Table 1. Fit Indices Fit Recommended Measurement Structural index value model model X 2 N/A Df N/A X 2 /df < GFI > AGFI > NFI > NNFI > CFI > RMSR < RMSEA < The convergent validity was assessed by three measures, as shown in Table 2: factor loading, composite construct reliability, and average variance extracted (Fornell & Larcker, 1981). In determining the appropriate minimum factor loadings required for the inclusion of an item within a construct, factor loadings greater than 0.50 were considered to be highly significant (Hair et al., 1998). A stricter recommendation of factor loading greater than 0.70 was also proposed (Fornell & Larcker, 1981). All of the factor loadings of the items in the measurement model were greater than 0.60, with most of them above Each item loaded significantly (p<0.01 in all cases) on its underlying construct. The composite construct reliabilities were also within the commonly accepted range greater than 0.70 (Gefen et al., 2000). As a stricter criterion, the guideline with a minimum of 0.80 applied to determine the adequacy of the reliability coefficients obtained for each construct. Finally, AVE measures the amount of variance captured by the construct in relation to the amount of variance due to measurement error (Fornell & Larcker, 1981). AVE was all above the recommended level of 0.50 (Hair et al., 1998) which meant that more than fifty percent of the variances observed in the items were - explained by their underlying constructs. Therefore, all constructs in the measurement model had adequate convergent validity. JOURNAL OF SYSTEMS INTEGRATION 2015/2 35

5 AMIN AHMAD SHAQRAH Table 2. Convergent Validity Test Constructs* Items Factor loading Composite reliability AVE TMS TMS TMS TMS TMS IS IS IS IS IS ET ET ET ET ET VS VS VS VS BPR BPR BPR BPR BPR PTC PTC HC CM PTC PTC HC1 HC2 HC3 CM1 CM2 CM3 CM LB LB LB LB *TMS: Top Management Support, IS: Implementation Strategy, ET: Education and Training,, VS: Vendor Selection, BPR: Business Process Reengineering, PTC: Project Team Competence, HC: High Cost, CM: Change of Management, LB: Language Barrier The discriminant validity was examined in two ways: comparing the inter-construct variances and average variances extracted and comparing the X 2 statistic of the original model against other models with every possible combination of two constructs. The shared variances between constructs were 36 JOURNAL OF SYSTEMS INTEGRATION 2015/2

6 AN EMPIRICAL INVESTIGATION OF SUCCESSFUL ENTERPRISE SYSTEMS STABILIZATION AND PRODUCTION SUPPORT compared with the average variance extracted of the individual constructs (Fornell & Larcker, 1981). To confirm discriminant validity, the average variance shared between the construct and its indicators should be larger than the variance shared between the construct and other constructs. As shown by comparing the inter-construct variances and average variances extracted in Table 3, all constructs share more variance with their indicators than with other constructs. Discriminant validity of the constructs was further validated by combining the items between various constructs and then reestimating the modified model (Segars, 1997). That is, comparing the X 2 statistic of the original model with its all constructs against other models with every possible combination of two constructs was conducted. Significant differences in the X 2 statistic of the original and alternative models imply high discriminant validity. As reported in Table 4, the X 2 statistic of the original model was significantly better than any possible combination of any two constructs, confirming discriminant validity. As a consequence, these results revealed no violation of the criteria for the discriminant validity of the constructs in the research model. To confirm the multidimensionality for the constructs of organizational commitment and attitude toward change, a second order CFA for these constructs was conducted. All of coefficients and the factor loadings of the items were greater than 0.60, with most of them above 0.80, and all the paths are significant (p<0.01 in all cases). In addition, the second order factor model exhibited an overall good model fit with the data collected from the respondents, by meeting the commonly recommended levels. These results confirmed the multidimensionality of the above two constructs. Table 3. Discriminant Validity Test Using AVE Comparison Constructs TMS IS ET VS BPR PTC HC CM LB TMS IS ET VS BPR PTC HC CM LB Structural model The structural model, including the research hypotheses and the causal paths, was examined using the confirmed measurement model. All constructs were modeled as being reflective, and most of constructs in the model were measured directly using multiple indicators. The only exceptions lie in the organizational commitment and attitude toward change dimensions, which are represented by summated scales based on the measurement model. This was considered reasonable since the first order and second order CFA confirmed their construct validity and multidimensionality. The model s overall fit with the data was evaluated by the same set of fit indices used in the measurement model (refer to Table 1). The structural model exhibited a fit value satisfying the commonly recommended threshold for the respective indices, providing evidence of a good model. The path coefficients and the overall fit indices are shown in Figure 1, along with the portion of the variances explained. As is evident from Figure 1, EQS results provided strong support for all hypotheses which were essentially drawn from the specification and have been empirically validated from previous studies. JOURNAL OF SYSTEMS INTEGRATION 2015/2 37

7 AMIN AHMAD SHAQRAH TMS 0.90 E59* IS 0.98 E60* 0.02* * 0.21* 0.27* ET 0.98 E61* VS 0.96 E62* -0.01* ERP Adoption* 0.62* BPR 0.20 E63* 0.56* 0.66* 0.31* 0.44* PTC 0.99 E64* HC 0.11 E65* -0.09* CM 0.95 E66* LB 1.00 E67* Figure 2. A Conceptual Framework Model Testing Results 5. Discussion and Conclusion Overall, support was found for the research model in this paper. The results showed that all antecedents effect on stabilization and production support phase and most highly significantly affected by cost, the path coefficient was After that BPR, the path coefficient was Then project team competence, the path coefficient was Whereas the remaining path coefficients were 0.44 on top management support and language barriers on change management on vendor selection on implementation strategy and education and training respectively. This paper investigated the enterprise systems stabilization and production support trends and its market potential in Jordan via an executive survey of fifteen companies. Statistical analysis of forty four usable returns confirms that the above antecedents and consequences affecting on enterprise systems stabilization and production support. The cost is ranked number one among the antecedents affecting on stabilization and production support, which is consistent with Akkermans & Helden (2002); Bingi et al., (1999) studies. There were limitations arising from the sample size used in this study. The sample size was relatively small (n = 72). Due to the relatively small sample size, more versatile and powerful statistical techniques such as Structural Equation Model (SEM), which is optimized for large samples of 200 to 400 subjects (Muehling and Laczniak, 1992), couldn t be employed. Instead the present study utilized the conventional ordinary least squares (OLS) regression to analyze data gathered from the respondents. This paper was conducted in the Jordan business environment only. To strengthen the findings of this research internationally, future research should be conducted in a cross-cultural environment. Despite these limitations, the present paper provided valuable insights into the study of enterprise systems success. The limitations acknowledged above therefore provide some suggestions for further research. References Adam, F. and O Doherty, O., 2000: Enterprise Resource Planning: Myth and Reality, 5ème, Colloque de l AIM, Montpellier, France Akkermans, H. and Helden, K., 2002: Vicious and Virtuous Cycles in ERP Implementation: A Case Study of Interrelations between Critical Success Factors, European Journal of Information Systems, 11(1), pp Aldwani, A., 2001: Change Management Strategies for Successful ERP Implementation, Business Process Management Journal, 7(3), pp Bingi, M. Sharma, and Godla, J., 1999: Critical issues affecting an ERP implementation, Information Systems Management, 16(3), pp JOURNAL OF SYSTEMS INTEGRATION 2015/2

8 AN EMPIRICAL INVESTIGATION OF SUCCESSFUL ENTERPRISE SYSTEMS STABILIZATION AND PRODUCTION SUPPORT Dechow, N. and Mouritsen, J., 2005: Enterprise resource planning systems, management control and the quest for integration, Accounting, Organizations and Society, 30(1), pp Everdinggen, Y. Hillegersberg, J. and Waarts, E., 2002: ERP adoption by European midsize companies, Communications of the ACM, 43(4), pp Fornell, C. and Larcker, D, 1981: Evaluating Structural Equation Models with Unobservable Variables and Measurement Error, Management Science, 40(4), pp Gefen, D. Straub, D. and Boudreau, M., 2000: Structural Equation Modeling and Regression: Guidelines for Research Practice, Communications of the Association for Information Systems. 4(7), pp.1-70 (2000) Grover, V. Jeong, S. Kettinger, W. and Teng, J., 1995: The implementation of business process reengineering, Journal of Management Information Systems, 12(1) pp Hair, J., Anderson, R. Tatham, R. and Black, W., 1998: Multivariate Data Analysis, Fifth ed., Prentice Hall, Upper Saddle River, New Jersey Hammer, M., 2000: Reengineer work: Don t automate, obliterate, Harvard Business Review Jacobs, R. and Whybark, C.,2000: Why ERP? A Primer on SAP Implementation. Irwin/McGraw-Hill, Boston, MA Jasperson, J. Carter, P. and Zmud, R., 2005: Conceptualization of Post-Adoptive Behaviors Associated with Information Technology Enabled Work Systems, MIS Quarterly, 29(3), pp Muehling, D. and Laczniak, R. 1992: An examination of factors mediating and moderating advertising's effect on brand attitude formation. Journal of Current Issues and Research in Advertising, 14(1), pp Norris, G. Hurley, J. Hartley, J. Dunleavy, and Balls, J., 2000: E-Business and ERP: Transforming the Enterprise, John Wiley & Sons, New York, NY Palaniswamy, R. and Frank, T., 2000: Enhancing manufacturing performance with ERP systems, Information Systems Management, 17(3), pp Rikhardsson, P. and Kraemmergaard, P., 2006: Identifying the impacts of enterprise system implementation and use: Examples from Denmark, International Journal of Accounting Information Systems. 7(1), pp Scapens, R. and Jazayeri. M., 2003: ERP systems and management accounting change: Opportunities or impacts? A research note, European Accounting Review, 12(1), pp Segars, A., 1997: Assessing the Unidimensionality of Measurement: a Paradigm and Illustration within the Context of Information Systems Research, Omega, 25(1), pp Soh, C. Kien, S. and Tay-Yap J., 2000: Cultural fits and misfits: Is ERP a universal solution, Communications of the ACM, 43(4), pp JEL Classification: L10, M15 JOURNAL OF SYSTEMS INTEGRATION 2015/2 39