The Relationship Between Implementation Variables and Performance Improvement of ERP Systems

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1 The Relationship Between Implementation Variables and Performance Improvement of ERP Systems Wen-Hsien Tsai*, Julian Ming-Sung Cheng*, Jun-Der Leu* Yi-Wen Fan**, Ping-Yu Hsu*, Li-Wen Chou*, Ching-Chien Yang* *Dept. of Business Administration, **Dept. of Information Management, National Central University National Central University Jung-Li, Taiwan Jung-Li, Taiwan Abstract The purpose of this paper is to explore the relationship between some implementation variables and performance improvement of ERP systems. DeLone and McLean (1992) surveyed 180 articles attempting to measure information systems (IS) success and proposed an analysis framework, composed of six dimensions, for assessing the ERP performance in the post-implementation stage. In this paper, DeLone-&- McLean s framework will be used to develop the ERP performance measures fit for ERP adopters of Taiwan. The implementation variables explored in this paper are ERP implementation statuses (all the planned modules having been implemented or not), ERP system sources (packaged ERP systems or nonpackaged ERP systems), and ERP implementation strategies (integral or step-by-step planning; Big Bang or phased approach). Structured questionnaire were sent to those companies listed in the TOP500 The Largest Corporations in Taiwan The research findings indicate that the companies using nonpackaged ERP systems, integral planning and having implemented all the planned ERP modules will have the better performance improvement. Keywords: ERP System Sources, ERP Implementation Strategies, Performance Improvement 1. Introduction In recent years, companies throughout the world gradually adopt Enterprise Resource Planning (ERP) systems to enhance competitiveness, to enhance the ability of responding more quickly to change, to enable easier access to information and faster retrieval of information or reports, to improve information for strategic planning and operational control, and to achieve other benefits (Mirani and Lederer, 1998). The main purpose of ERP proects is the automation and integration of many basic processes in order to integrate information across the enterprise and eliminating complex, expensive interfaces between computer systems (Teltumbde, 2000). Since all business functions are involved in ERP systems, they will be highly complex information systems. And, it is expensive and time consuming to implement an ERP system (Sarkis and Gunasekaran, 2003). Due to the constraints of budget and time, some companies may employ a phased implementation approach, that is, modules are implemented one at a time or in a group of modules, often a single location at a time. Phased implementations require substantial attention and maintenance given to legacy systems in order to facilitate integration with the new ERP system. Moreover, there may not be enough modules implemented to achieve functionality. However, there also are some advantages and disadvantages for a Big Bang implementation approach, where an entire suite of ERP modules is implemented at all locations at the same time (Thanasankit, 2001; Mabert et al., 2003). Generally, so-called ERP systems are the packaged ERP software purchased from vendors. Nevertheless, in our knowledge, some companies in Taiwan employed the non-packaged ERP systems that came from evolution of legacy systems, self-redevelopment, or outsourcing. ERP vendors designed their packaged ERP systems to be the universal package software for various industries and organizations. Also, Packaged ERP systems often offer numerous options representing best practices (Teltumbde, 2000). Even so, it is impossible for any organization to install a packaged ERP system without any tailoring or add-on. Thus, it is not advantageous to adopt an ERP system if it requires considerable modifications. In view of the issues mentioned above, the purpose of this research is to explore the relationship between some implementation variables and performance improvement of ERP systems. The implementation variables explored in this paper are ERP implementation statuses (all the planned modules

2 having been implemented or not), ERP system sources (packaged ERP systems or non-packaged ERP systems), and ERP implementation strategies (integral or step-by-step planning; Big Bang or phased approach). Besides, the Information System (IS) success model of DeLone and McLean (1992) is used to develop the ERP performance measures for measuring the performance improvement levels. 2. ERP Performance Measures In this paper, we utilize DeLone and McLean (1992) IS success model to develop ERP performance measures. DeLone and McLean (1992) divided IS success measure into six dimensions or categories as follows: (1). System Quality: measures of the information processing system itself. (2). Information Quality: measures of the information system output. (3). System Use: measures of recipient use of information system. (4). User Satisfaction: measures of recipient response to the use of information system. (5). Individual Impact: measures of the effect of information on the behavior of the recipient. (6). Organizational Impact: measures of the effect of information on organizational performance. This study selected ERP performance measures from the related literature (DeLone and McLean, 1992; DeLone and McLean, 2003; Saarinen, 1996; Skot et. al., 2001; Mirani and Lederer, 1998; Lee et al., 2002; Liberatore and Miller, 1998; Mabert et al., 2000). As for Organizational Impact, the Balanced Scorecard (BSC) approach is used to divide ERP performance measures of Organization Impact dimension into four categories (Kaplan and Norton, 1992; Roseman and Wiese, 1999; Lipe and Salterio, 2000). Among those authors researching on the DeLone and McLean s IS success model, Li (1997) and Skok et al., (2001) explored the importance of IS success measures using 7-point and 9-point Likert-type scales of survey questionnaires respectively. In this research, we will use 7-point Likert-type scales. 3. Methodology 3.1 Research Hypotheses As mentioned in Section 1, the purpose of this research is to exploring the relationship between some implementation variables and performance improvement of ERP systems. The dependent variables are the performance improvement levels of System Quality, Information Quality, System Use, User Satisfaction, Individual Impact, Organizational Impact, and Composite Performance after having implemented ERP systems. The implementation variables (dependent variables) explored in this paper are: (1) ERP implementation statuses (all the planned modules having been implemented or not), (2) ERP system sources (packaged ERP systems or non-packaged ERP systems), and (3) ERP implementation strategies (integral or step-by-step planning; Big Bang or phased approach). The research hypotheses of this research are as follows: H1: There is no difference in performance improvement levels between the companies that have implemented all the planned modules and that have implemented the partial modules. H2: There is no difference in performance improvement levels between the companies that have implemented ERP systems with different ERP system sources. H3: There is no difference in performance improvement levels between the companies that have implemented ERP systems with different ERP implementation strategies. 3.2 Data Collection There are two stages in this research described as follows: Stage1: Listing ERP Performance Measures and Evaluating their Importance by a Small Sample Survey The list of ERP performance measures is obtained after a literature review. These ERP performance measures are categorized according to the six dimensions of DeLone and McLean s model. Then the importance of these ERP performance measures (83 measures in total) are evaluated by companies that have implemented ERP systems by using 7-point Likert-type scales. In this stage, 260 questionnaires were sent to the companies that had implemented ERP systems. The number of usable responses is 45, and the

3 usable response rate is 17.31%. Stage 2: Redesigning the Survey Questionnaire Concerning ERP Performance Measures and Implementation Variables. Collecting the Data by a Large Sample and Analyzing the Data Collected According to the average importance score rankings obtained from Stage 1, top five important performance measures were chosen for each success dimension of DeLone and McLean s model except the Organizational Impact dimension where 12 measures were chosen. The 37 chosen measures are as shown in Table 3. In this stage, 3597 questionnaires were sent to the companies of manufacturing and services industries, listed in the TOP 5000 The Largest Corporations in Taiwan on Of the 3597 questionnaires mailed, 657 (18.27% of 3597) were usable responses. Among 657 usable responses, 93 (14.16% of 657) were under implementation and there were no module going-live, 137 (20.85% of 657) had implemented partial modules, and 146 (22.22% of 657) had implemented all the planned modules. In this paper, 283 companies, that had implemented all the planned modules or the partial planned modules, will be analyzed. The characteristics of the respondents are shown in Table Measurement of Performance Improvement Levels In the questionnaire of Stage 2, we asked respondents to evaluate the performance improvement level and importance level for each of the 37 chosen ERP performance measures by using 7-point Likert-type scales ranging from 1 (Substantial Deterioration) to 7 (Substantial Improvement) and from 1 (Extremely unimportant) to 7 (Extremely important), respectively. The data of importance levels are used to calculate the relative weights of measures. We used these data and the following equations to determine the performance improvement levels of System Quality, Information Quality, System Use, User Satisfaction, Individual Impact, Organizational Impact, and Composite Performance after implementing ERP systems: 1.The performance improvement level of the th dimension for the i th respondent s company: P i = l k= 1 P ik l W k= 1 k W k, i = 1,2,3,..., N, = 1,2,3,..., 6 where W k = the average importance level score of the th N respondents ik N k measure of the th dimension as perceived by ( W ik ) = i=1, N W = the importance level score (1 to 7) of the k th measure of the th dimension as perceived by ik the th i respondent, P = the performance improvement level score (1 to 7) of the k th measure of the th dimension for thei th respondent s company, l = the number of chosen measures for the th dimension. 2.The composite performance improvement level for the i th respondent s company: l W k 6 k = 1 P i = ( P ), i =1, 2, 3,, N i 6 l = 1 W k where P i, W k = 1 k = 1, and l are defined as above.

4 Table 1. Characteristics of the Respondents Enterprise Employment Freq. Percentage Fewer than 100 employees 10 to 300 More than % 44.88% 40.28% Annual Revenue (NT$ bil.) Fre. Percentage $0.2 or <$0.5 $0.5 to <$1.0 $1.0 to <$5.0 $5.0 to <$10.0 $10.0 to <$30.0 $30.0 & up % 25.09% 42.05% 9.19% 5.65% 6.01% Capital Amount (NT$ mil.) Freq. Percentage $80 or less $80 to <$200 $200 to <$500 $500 to <$1000 $1000 to <$2000 $2000 to <$5000 $5000 to <$10000 $10000 & up % 13.43% 12.72% 26.15% 20.14% 9.54% 4.15% 6.01% ERP Experience Freq. Percentage Less than 2 years 2 to 4 years % 11.66% 4 to 6 years % 6 to 8 years % Above 8 years % Type of Company Freq. Percentage Foreign Domestic-Foreign Joint Venture Domestic % 7.07% 85.16% Industry Freq. Percentage Manufacturing Services % 28.98% Implementation Statuses Freq. Percentage Implemented all the planned modules Implemented the partial planned modules % 48.41% ERP System Sources Fre. Percentage Evolution from legacy systems Self-redevelopment Outsourcing ERP Packaged systems ERP package systems with other systems Missing % 8.83% 14.13% 42.05% 19.08% 1.41% Implementation Strategies (N=173) Freq. Percentage Integral planning & Big Bang approach Integral planning & phased approach Step-by-step planning & phased approach Missing % 43.35% 16.18% 0.58% Table 2. Average Performance Improvement and Importance Levels of Six Dimensions Performance Measure Dimensions Average Performance Improvement Level Rank Average Importance Level System Quality Information Quality System Use User Satisfaction Individual Impact Organizational Impact Rank

5 4. Research Results 4.1 Performance Improvement and Importance Levels of ERP Performance Measures The performance improvement and importance levels of ERP performance evaluation dimensions and measures for all respondents are shown in Table 2 and Table 3. From Table 2, we know that System Quality and Information Quality are the top two important dimensions of ERP performance evaluation as perceived by the respondents. These two dimensions are the fundamental factors of achieving ERP/IS success. Also, System Quality and Information Quality are the top two performance improvement dimensions after having implemented ERP systems. From Table 3, the top five important measures in evaluating ERP performance are: (1) data accuracy, (2) believability of output, (3) system accuracy, usefulness of output, and (5) inventory level; the top five performance improvement levels after having implemented ERP systems are: (1) data accuracy, (2) database contents, (3) data accuracy, (4) timeliness of output, and (5) usefulness of output. 4.2 Implementation Statuses and Performance Improvement Of the 283 companies that have implemented ERP systems, 146 (51.59% of 283) have implemented all the planned modules and 137 (48.41% of 283) have implemented the partial planned modules. From Table 4 and Fig.1, we can see obviously that the average performance improvement levels on each performance evaluation dimension and composite performance are significantly different between these two groups. That is, the companies having implemented all the planned modules will have higher performance improvement levels than the companies having implemented partial planned modules. It may because the companies will achieve the synthetic effect after having implemented all the planned modules. 4.3 ERP System Sources and Performance Improvement Among the 283 companies that have implemented ERP systems, their ERP system sources are: (1) evolution from legacy systems (41, 14.49%), (2) self-redevelopment (25, 8.83), (3) outsourcing (40, 14.13%), (4) ERP package system (119, 42.05%), and (5) ERP package system with other systems. The average performance improvement levels for these five system sources are shown in Table 5. From Table 5, we know that these five sources can be divided into two groups. The first group (106, 37.46%) including evolution from legacy system, self-redevelopment, and outsourcing, has higher performance improvement level than the second group (173, 61.13%), including ERP package systems and ERP package systems with other systems. The first group is non-packaged ERP systems and the second group is packaged ERP systems. Table 6 and Fig. 2 show the research results concerning these two groups. From Table 5, we know that the average performance improvement levels on each performance evaluation dimension and composite performance are significantly different between these two groups. And, the companies with nonpackaged ERP systems will have higher performance improvement levels than the companies with packaged ERP systems. This research result is against our normal expectation. This may because that the companies implemented packaged ERP systems in Taiwan are on the early stage of post-implementation and have not achieve the ERP benefits fully. 4.4 Implementation Strategies and Performance Improvement As explained in Section 4.3, there are 173 companies adopting the packaged ERP systems among the 283 companies that have implemented ERP systems. Of these 173 companies, 69 (39.88% of 173) adopted the Integral planning & Big Bang approach, 75 (43.35% of 173) the Integral planning & phased approach, and 28 (16.18%) the Step-by-step planning & phased approach. Table 7 and Fig.3 show the research results about implementation strategies. We can find that, except the Individual Impact dimension, the decreasing rank order in the performance improvement levels of each dimension for these three approaches is: (1) Integral planning & phased approach, (2) Integral planning & Big Bang approach, and (3) Integral planning & Big Bang approach. We also find that there is no significant difference in performance improvement levels of various performance evaluation dimensions and composite performance except the Information Quality and System Use dimensions between the companies with different ERP implementation strategies. From Table 8, we can see that the significant differences exist between Integral planning & phased approach and Step-by-step planning & phased approach. All these research results indicate that there is almost no significant difference in ERP performance improvement between the various approaches. However, if a company adopts the phased implementation, it should do the integral planning ob for all the ERP implementation phases.

6 Table 3 Performance Improvement and Importance Levels of ERP Performance Measures ERP Performance Measures Performance Rank Importan Rank Improveme Within Overall Within Overall ce nt System Quality (1) Data accuracy (2) Database contents (3) Data currency (4) System accuracy (5) Response time Information Quality (1) Believability of output (2) Timeliness of output (3) Usefulness of output (4) Understandability of output (5) Relevance of output System Use (1) Rate of using ERP to assist in making decision (2) Charge for ERP system use (3) Frequency of report requests (4) Voluntariness of use (5) Amount of connect time User Satisfaction (1) Information satisfaction (2) Software satisfaction (3) Interface satisfaction (4) Overall satisfaction (5) ERP proect satisfaction Individual Impact (1) Job performance (2) Individual productivity (3) Decision quality (4) Information awareness (5) Accurate interpretation Organizational Impact a. Financial (1) Inventory levels (2) Purchasing costs (3) Inventory turnover b. Customer (1) On-time delivery (2) Customer complaint reaction time (3) Frequency of on-time mail c. Internal Business Process (1) Data transmission time between departments (2) Frequency of interaction across the enterprise (3) Ability of forecasting stock requirement d. Learning and Growth (1) Degree of understanding work flow (2) Employees achievement (3) Product development to market time

7 Implementation Statuses Table 4 Implementation Statuses and Performance Improvement System Information System User Individual Organizational Quality Quality Use Satisfaction Impact Impact Composite Performance Implemented all the planned modules (1) Implemented the partial planned modules (2) Difference (1)(2) Significance (ANOVA).011**.002***.055*.011**.062*.011**.002*** ***p-value < 0.01; **p-value < 0.05; *p-value < 0.1 Freq. System Quality Organization Impact Information Quality Implemented all the planned modules Implemented the partial planned modules Individual Impact System Use User Satisfaction Fig.1 Implementation Statuses and Performance Improvement ERP System Sources Table 5 ERP System Sources and Performance Improvement System Information System User Individual Quality Quality Use Satisfaction Impact Organizational Impact Composite Performance Evolution from legacy systems Self-development Outsourcing , ERP package systems ERP package systems with other systems , Freq.

8 Table 6 Non-packaged and Packaged ERP Systems and Performance Improvement Non-packaged and System Information System User Individual Organizational Composite Packaged ERP Systems Quality Quality Use Satisfaction Impact Impact Performance Freq. Non-packaged ERP systems (1) Packaged ERP systems (2) Difference (1)(2) Significance (ANOVA).037**.011**.006***.001***.000***.000***.000*** ***p-value < 0.01; **p-value < 0.05; *p-value < 0.1 Organizational Impact System Quality Information Quality Non-packaged ERP systems Packaged ERP systems Individual Impact System Use User Satisfaction Fig. 2 Non-packaged and Packaged ERP Systems and Performance Improvement Table 7 Implementation Strategies and Performance Improvement Implementation System Information System User Individual Organizational Composite Strategies Quality Quality Use Satisfaction Impact Impact Performance Freq. Integral planning & Big Bang approach Integral planning & phased approach Step-by-step planning & phased approach Significance (ANOVA) *.044** **p-value < 0.05; *p-value < 0.1

9 Table 8 Scheffe Test for Implementation Strategies and Performance Improvement in Information Quality and System Use Information Quality System Use Implementation Strategies IP&BB IP&P IP&BB IP&P Integral planning & Big Bang approach IP&BB - - Integral planning & phased approach IP&P Step-by-step planning & phased approach SP&P * * *p-value < 0.1 System Quality Organizational Impact Information Quality Individual Impact System Use User Satisfaction Integral planning & Big Bang Integral planning & phased Step-by-step planning & phased Fig.3 Implementation Strategies and Performance Improvement 7. Conclusions The purpose of this paper is to explore the relationship between some implementation variables and performance improvement of ERP systems. The implementation variables explored in this paper are ERP implementation statuses (all the planned modules having been implemented or not), ERP system sources (packaged ERP systems or non-packaged ERP systems), and ERP implementation strategies (integral or step-by-step planning; Big Bang or phased approach). The performance improvements are measured according to the six dimensions of Delone and McLean s 1992 success model and by the 7-point Likerttype scales of ERP performance improvement and ERP performance measures importance. We also use the composite performance that integrates all the six dimension s measures into one single composite performance index. In this study, we utilize a two-stage approach: (1) listing ERP performance measure and then evaluating their importance by a small sample survey, and (2) redesigning the survey questionnaire concerning ERP performance measures and implementation variables; collecting the data by a large sample and analyzing the data collected. The research results indicate that: (1) System Quality and Information Quality are the top two important dimensions of ERP performance evaluation as perceived by the respondents. Also, System Quality and Information Quality are the top

10 two performance improvement dimensions after having implemented ERP systems. These two dimensions are the fundamental factors of achieving ERP/IS success. (2) The companies having implemented all the planned modules will have higher performance improvement levels than the companies having implemented partial planned modules. It may because the companies will achieve the synthetic effect after having implemented all the planned modules. (3) The companies with non-packaged ERP systems will have higher performance improvement levels than the companies with packaged ERP systems. (4) There is no significant difference in ERP performance improvement between the various implementation strategies. However, if a company adopts the phased implementation, it should do the integral planning ob for all the ERP implementation phases. Reference DeLone, W.H. and E.R. McLean, Information Systems Success: The Quest for the Dependent Variable, Information Systems Research, 3 (1), 1992, DeLone, W.H. and E.R. McLean, The DeLone and McLean Model of Information Systems Success: A Ten-Year Update, Journal of Management Information Systems, 19 (4), Spring 2003, Kaplan, R.S. and D.P. Norton, The Balanced Scorecard-Measures That Drive Performance, Harvard Business Review, January February 1992, Lee, Y.W., D.M. Strong, B.K. Kahn and R.Y. Wang, AIMQ: A Methodology for Information Quality Assessment, Information & Management, 40, 2002, Li, E.Y., Perceived Importance of Information System Success Factors: A Meta Analysis of Group Differences, Information & Management, 32, 1997, Liberatore, M.J. and T. Miller, A Framework for Integrating Activity-Based Costing and the Balanced Scorecard into the Logistics Strategy Development and Monitoring Process, Journal of Business Logistics, 19 (2), 1998, Lipe, M.G. and S.E. Salterio, The Balanced Scorecard: Judgment Effects of Common and Unique Performance Measures, The Accounting Review, 75(3), July 2000, Mabert, V.A., A. Soni, and M.A. Venkataramanan, Enterprise Resource Planning Survey of U.S. Manufacturing Firms, Production and Inventory Management Journal, 41(2), 2000, Mabert V.A., A. Soni, and M.A. Venkataramanan, Enterprise Resource Planning: Managing the implementation Process, European Journal of Operational Research, 146, 2003, Mirani, R. and A.L. Lederer, An Instrument for Assessing the Organizational Benefit of IS Proects, Decision Sciences, 20 (4), Fall 1998, Rosemann, M., and J. Wiese, Measuring the Performance of ERP Software - A Balanced Scorecard Approach, Proceedings of 10 th Australasian Conference on Information Systems, 1999, Saarinen, T., An Expanded Instrument for Evaluating Information System Success, Information & Management, 31, 1996, Sarkis, J., and A. Gunasekaran, Editorial: Enterprise Resources Planning Modeling and Analysis, European Journal of Operational Research, 146 (2), April 16, 2003, Skok, W., A. Kophmel, and I. Richardson, Diagnosing Information System Success: Importance- Performance Maps in the Health Club Industry, Information & Management, 38, 2001, Teltumbde, A., A Framework for Evaluating ERP Proects, International Journal Production Research, 38 (17), 2000, Thanasankit, T., Implementing ERP Systems Big Bang Versus Phased, 2001, quoted from the website: 01).ppt. Acknowledgement This paper is supported by the MOE Excellence Research Proect: Electronic Commerce Environment, Technology Development, and Application (Proect Number: 91-H-FA08-1-4).