Erp Fit


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Erp Fit

  1. 1. ARTICLE IN PRESS International Journal of Information Management 27 (2007) 200–212 Improving enterprise resource planning (ERP) fit to organizational process through knowledge transfer Eric T.G. Wanga, Cathy Chia-Lin Lina, James J. Jiangb, Gary Kleinc,Ã a Department of Information Management, National Central University, Taiwan, ROC b Department of Management Information Systems, University of Central Florida, Orlando, FL 32816-1400, USA c Department of Management, United States Air Force Academy, 2354 Fairchild Dr. Suite 6H-130, USAF Academy, CO 80840-5099, USA Abstract Critical to enterprise resource planning (ERP) implementation is the fit between the system and the processes in an organization. Knowledge about the ERP system must flow from those implementing the system and those responsible once in production. Effective knowledge transfer is assisted by the absorptive capacity of the learner and the competence of the knowledge holder, as reflected in the client and consultant relationship of this study. A model of transfer is composed from existing theories of learning to explain the roles played by the client through absorptive capacity and the consultant through competence. Survey data of CIOs in Taiwan confirm that transfer is improved with higher levels of capacity and competence, while the transfer process leads to a better fit between ERP systems and organizational processes. Management needs to foster the build-up of their internal knowledge stocks in order to stimulate the flow of knowledge transfer. r 2007 Elsevier Ltd. All rights reserved. Keywords: ERP implementation; Knowledge transfer; Absorptive capacity; Consultant competence; Process fit 1. Introduction Approximately 90 percent of enterprise resource planning (ERP) implementations are late or over budget (Martin 1998) and 70 percent of ERP implementations fail to deliver anticipated benefits (Al-Mashari, 2000). Although the literature describes multiple reasons for this poor record of performance, gaps between the functionality offered by an ERP system and that required by the particular organization are common (Everdingen, Hillegersberg, & Waarts, 2000; Swan, Newell, & Robertson, 1999; Umble & Umble, 2002). The difficulties are expanded by customer organizations requiring unique business solutions and ERP vendors having a generic solution sold to a broad market. Thus, one large factor in the improvement of the success rate is the mutual adaptation between the IS and user environment (Markus & Robey, 1988). Such an adaptation process must align the organization’s existing ÃCorresponding author. Tel: +1 719 333 2731. E-mail addresses: (E.T.G. Wang), (C. Chia-Lin Lin), (J.J. Jiang), (G. Klein). 0268-4012/$ - see front matter r 2007 Elsevier Ltd. All rights reserved. doi:10.1016/j.ijinfomgt.2007.02.002
  2. 2. ARTICLE IN PRESS E.T.G. Wang et al. / International Journal of Information Management 27 (2007) 200–212 201 operating processes and the packaged software’s embedded functionality through a combination of software configuration and organizational change (Hong and Kim, 2002). Such IS-driven initiatives require change of the organization’s socio-technical system, which is intertwined of technology, task, people, structure, and culture (Laughlin, 1999). While these above resolution strategies were employed to tackle the problem of misfits, other researchers found that an existence of significant knowledge gap among the stakeholders which could potentially cause the unsuccessful implementation (Markus & Tanis, 2000; Soh, Sia, & Tay-Uap, 2000). ERP implementation is a knowledge intensive process; it requires a great deal of experience from many different stakeholders, and requires these individuals to interact extensively during the implementation process. The knowledge gap risks configuration errors and unnecessary customization, but also conflicts between the different parties involved (Pan, Newell, Huang, & Cheung, 2001; Sumner, 2000). The need for closing this knowledge gap in the ERP project is therefore important (Huang & Newell, 2003). Studies about ERP implementations focus on identifying critical success (and/or risk) factors associated with ERP implementations, one of which is the impact of knowledge transfer (Chan & Rosemann, 2001; Jones, 2001; Lee & Lee, 2000; Parr, Shanks, & Darke, 1999; Volkoff & Sawyer, 2001; Willcocks & Sykes, 2000). While an organization may lack necessary experience or knowledge for ERP implementation, it could nonetheless transfer this knowledge from external sources such as consulting firms (Timbrell & Gable, 2001). As a result, the members in an ERP implementation team could include representatives from business departments, technical specialists from the IT department, project managers within the organization, and consultants (Davenport, 1998; Roberts, Leigh, Purvis, & Parzinger, 2001). Based upon the knowledge stock-flow theory proposed by Dierickx and Cool (1989), this study proposes that consultant competence and the adopting firm’s absorptive capacity are two critical factors influencing the effectiveness of knowledge transfer during ERP implementation. Effective knowledge transfer from a competent consulting firm to the client will leave the client better positioned to maintain and evolve its system, thus leading to a better fit between the system and the client’s processes (Davenport, 2000). Absorptive capacity refers to the ability to contain the knowledge transferred and is based primarily on existing knowledge stock to frame and retain additional knowledge. Firms should possess a high level of absorptive capacity to effectively value, assimilate, and apply the external knowledge acquired from consultants into their business processes (Cohen & Levinthal, 1990). The purpose of this study then is to understand the environment that enables effective knowledge transfer between consultants and the client and whether more effective knowledge transfer would lead to an ERP system better matched with the client’s process requirements. Specifically, the knowledge stock-flow theory proposed by Dierickx and Cool (1989) is adopted to examine the causal relationships between consultant competence, the client’s absorptive capacity, and knowledge transfer and eventual ERP process fit. In addition, Soh et al. (2000) suggested that the organizational fit of ERP might be worse in Asia, because the reference process model underlying most ERP systems is influenced by European or US industry practices. Thus, Asian organizations provide a rich sample opportunity for possible ill fit. The contribution of this study is to not only confirm the stock-flow model but also add to our understanding of how both internal knowledge transfer capability and external sources of knowledge can impact the eventual organizational fit to ERP. 2. Background and hypotheses Researchers have conceptualized ERP implementation as an organizational learning process (Davenport, 2000). In this study, organizational learning theory was adopted to explain the knowledge transfer between consultants and clients in the ERP implementation process. In this section, we first review the organizational learning theory and then review the constructs relevant to the research model. 2.1. Organizational learning theory Scholars have used different perspectives to investigate organizational learning issues. Recently, many researchers have advocated the ‘‘process-orientation’’ perspective (Crossan, Lane, & White, 1995; Huber, 1991; Lee, Courtney, & O’keefe, 1992). For example, Argyris and Schon (1978) suggested that organizational
  3. 3. ARTICLE IN PRESS E.T.G. Wang et al. / International Journal of Information Management 27 (2007) 200–212 202 learning is a process of detecting and correcting errors. Fiol and Lyles (1985) also pointed out that organizational learning is a process of improving actions through better knowledge and understanding. Consequently, organizational learning is an evolutionary process to improve organizational performance. This process orientation has also served to explain how organizational learning considerations can be applied to improve knowledge creation within an organization and lead research in knowledge management systems (Alavi & Leidner, 2001; Nonaka & Takeuchi, 1995). Crossan, Lane, and Wroderick (1999) posed a dynamic organizational learning process. They used production flow to metaphorically describe the stock-flow relationship in organizational learning. Production flow must insure that the level of work-in-process inventories does not exceed the capacity of any part of the system to absorb and process them. Concepts like throughput, capacity utilization, cycle time, and bottlenecks have aided our understanding of what it takes to balance a production line to ensure smooth flow (Crossan et al., 1999). Gibson, Greenhalgh, and Kerr (1995) argued that in order to make the production line as smooth and coordinated as possible, manufacturing managers must align the stock and flow levels of work-in-process inventory. This concept is similar to organizational learning because organizational managers need to align stock and flow levels of learning so that the overall organizational learning system can operate efficiently and effectively. Misalignment between the stocks and the flows indicates that learning is not being absorbed by the organization (Bontis, Crossan, & Hulland, 2002). Stocks of knowledge are accumulated knowledge assets internal to the firm. Flows of knowledge are represented by knowledge that streams into the firm, which may be assimilated and developed into stocks of knowledge. The basic difference between stocks and flows may be illustrated by the ‘‘bathtub’’ metaphor shown in Fig. 1 (Dierickx & Cool, 1989). At any moment in time, the stock of knowledge is indicated by the level of water in the tub; it is the cumulative result of flows of water into the tub from outside sources and out of it through an overflow or leakage. With respect to implementing ERP systems, knowledge transfer from consultants to a client is represented by the water flowing into the tub, and the amount of water in the tub may represent the stock of the client’s absorptive capacity. Consultant competence is represented by the source of the water that is the knowledge stock of external sources. When stock and flow are sufficient, the organizational learning can operate efficiently and effectively. For effective knowledge transfer during ERP implementation, the consultant must have sufficient knowledge to offer while the client also needs to have enough absorptive capacity to learn from the consultant. Researchers have used absorptive capacity to explain organizational phenomena. But, the definitions and the operationalizations of this concept vary. Cohen and Levinthal (1990) offered the most widely cited definition of absorptive capacity. According to them, absorptive capacity is the firm’s ability to recognize the value of new, external knowledge, assimilate the knowledge, and apply knowledge to commercial ends. In an ERP implementation, knowledge sourced from the consultant must be translated, adapted, and combined with knowledge of the client’s business processes, then internalized into new organizational routines specific to the client’s context. The process is similar to the organizational learning process proposed by Nonaka and Takeuchi (1995). So the client’s absorptive capacity is important during the transfer process. Consultant Competence Overflow Consultants ERP Knowledge Leak Absorptive Capacity of Client Fig. 1. ‘‘Bathtub’’ metaphor of knowledge transfer.
  4. 4. ARTICLE IN PRESS E.T.G. Wang et al. / International Journal of Information Management 27 (2007) 200–212 203 Ideally, consulting is a service, which helps organizations re-engineer and rethink their businesses under the dimensions of technology, strategy, people, and business processes (Basil & Tang, 1997). In return, consultants learn from their clients as well, even selecting organizations that provide an opportunity to exchange knowledge (Sveiby, 1997). Many researchers have used role theory to describe the competence of consultants (Bessant & Rush, 1995; Champion, Kiet, & Mclendon, 1990; Jang & Lee, 1998). These studies thus suggest the critical role consultants play in serving as external knowledge stock as well as in facilitating inter-firm knowledge transfer. Knowledge is considered as a more dynamic matter, a flow of interacting changes taking place in the people involved in a learning process (Garavelli, Gorgoglione, & Scozze, 2002). Davenport & Prusak (1998) stated that knowledge is a fluid mix of framed experience, values, contextual information, and expert insights that provides a framework for evaluating and incorporating new experiences and information. Knowledge is considered as wellsprings continuously being filled with new ideas that affect the organization’s behaviors, values and beliefs (Leonard, 1995; Nonaka, 1990). Many scholars have used this perspective to develop knowledge transfer processes (Gilbert & Cordey-Hayes, 1996; Szulanski, 1996; Trott, Cordey-Hayes, & Seaton, 1995). One of the focuses of this study then is to examine whether knowledge transfer during ERP implementation can mediate the effects of knowledge stocks, i.e., consultant competence and the client’s absorptive capacity, on the outcome of ERP implementation. Organizational process fit of ERP is the outcome variable of this study, defined as the extent to which the implemented ERP system can satisfy the client’s process needs. Swan et al. (1999) indicated that organizational misfits of ERP exist due to the conflicting interests of user organizations and ERP vendors. The team responsible for ERP implementation will be challenged to either match the functionality of the ERP system to the way that the enterprise currently does business or find ways to change current processes and procedures (Laughlin, 1999). Consequently, this study focuses on the degree of fit between the processes offered by the ERP system and those required by the client after implementation. 2.2. Research model and hypotheses According to the above discussion, this study treats absorptive capacity as the client’s knowledge stocks, while consultant competence is conceptualized as the consultant’s knowledge stocks. Based upon the organizational learning theory and the discussion above, the research model shown in Fig. 2 is proposed. 2.2.1. Absorptive capacity and effective knowledge transfer Cohen and Levinthal (1990) defined the term ‘‘absorptive capacity’’ as a firm’s general ability to value, assimilate, and utilize new, external knowledge. They suggested that an organization’s absorptive capacity tends to develop cumulatively and is path dependent. This means that the recipient’s stock of prior related knowledge determines its absorptive capacity for new knowledge and can render the recipient greater Absorptive + Capacity + Organizational Knowledge Process Fit of Transfer ERP + Consultant Competence Fig. 2. Research model.
  5. 5. ARTICLE IN PRESS E.T.G. Wang et al. / International Journal of Information Management 27 (2007) 200–212 204 capability to successfully exploit new knowledge. In general, absorptive capacity can be viewed as an organization’s internal knowledge stock. Examination of transfer in a systems environment is considered a crucial issue for information systems research (Alavi & Leidner, 2001). However, most pertinent work has been in other disciplines. These have supported the existence of the relationship between absorptive capacity and knowledge transfer. For example, Szulanski (1996) found that a major barrier to knowledge transfer is the recipient’s lack of absorptive capacity, leading to the ‘‘stickiness’’ of knowledge transfer. If an organization’s absorptive capacity is higher, it means that knowledge transfer should be more effective (Boynton, Zmud, & Jacobs, 1994). Based upon the organizational learning model and the empirical findings in the literature, we propose the following null and alternate hypothesis: H1o: Absorptive capacity is not related to knowledge transfer. H1a: Absorptive capacity is positively related to knowledge transfer. 2.2.2. Consultant competence and effective knowledge transfer An ERP system is an enterprise-wide and complicated system, requiring a certain level of competence or capabilities to deal with the challenges imposed during the implementation process. As a result, organizations often seek the required expertise from external sources, such as consulting firms. Consultants are both knowledge providers and facilitators during the implementation. They help client organizations configure and derive value from an ERP package, providing both product knowledge and process guidance (Timbrell & Gable, 2001; Volkoff & Sawyer, 2001). Through guided learning, formal training, and knowledge creation activities, consultants can help clients acquire the needed knowledge for a successful implementation. According to Bessant and Rush (1995), there are four ways in which consultants can improve the operation of an innovation process, such as ERP implementations. The first way is the direct transfer of expert knowledge that has already been obtained and assimilated by consultants. Second, consultants help through their role of experience sharing, which is performed either implicitly or explicitly. The third way is ‘‘marriage broker,’’ which provides users with a single point of contact through which a wide range of specialist services are offered. Finally, it is the diagnostic role consultants play in helping users articulate and define their particular needs in innovation. Consultant competence can be viewed as an external knowledge stock; this external stock provides the needed knowledge to the ERP adopting firms. As a result, when a client works with competent consultants, i.e., those with greater external stock, the knowledge required for ERP implementation should be more effectively transferred to the client than when working with less competent consultants. Although there is no empirical evidence regarding the direct relationship between consultant competence and knowledge transfer found in the IS literature, based upon the above discussion, we propose the following null and alternate hypothesis: H2o. Consultant competence is not related to knowledge transfer. H2a: Consultant competence is positively related to knowledge transfer. 2.2.3. Effective knowledge transfer and ERP success Although the extant literature falls short of empirically demonstrating the causal link between effective knowledge transfer and successful ERP implementation, Davenport (2000) stated that knowledge transfer leaves the client organization better positioned to maintain and evolve its system and to generate returns from the ERP investment. Gable, Scott, and Davenport (1998) also suggested that effective knowledge management, knowledge sharing in particular, could offer significant commercial and practical benefits to a system over its lifecycle. Thus, it can be argued that effective knowledge transfer from the consultant to the client is a critical success factor in ERP implementation. If the ERP-related knowledge can be effectively absorbed and utilized by a client, it is more likely to satisfy the client’s needs and meet the expected benefits. Volkoff and Sawyer (2001) argued that consultants can help clients configure and derive value from ERP by providing both product knowledge and process guidance. When such knowledge is transferred more effectively from the consultant to the client, the client should have a
  6. 6. ARTICLE IN PRESS E.T.G. Wang et al. / International Journal of Information Management 27 (2007) 200–212 205 better understanding of the functionality of and process models embedded within the package. This would increase the likelihood of resulting in an implemented system that provides a better fit with its process requirements. Consequently, we propose that more effective knowledge transfer during implementation will lead to a higher degree of organizational process fit of ERP. H3o. Knowledge transfer is not related to organizational process fit. H3a: Knowledge transfer is positively related to organizational process fit. 3. Research method 3.1. Sample To examine the factors that affect the effectiveness of knowledge transfer during ERP implementation, a questionnaire was developed to collect data from a group of manufacturing firms in Taiwan. The sample frame was drawn from Common Wealth’s The Largest Corporations in Taiwan 2001. The top 1000 manufacturing firms were selected as the sample for this study. In order to test the proposed model and hypotheses, the key informant approach was adopted. The key informants were the CIOs in those manufacturing firms as being the most capable of assessing the company’s IT personnel competence and of observing the knowledge transfer conditions during ERP implementation. A modified version of Dillman’s total design method (Dillman, 1978) was used to ensure a higher response rate. The mailing to the subjects included a cover letter explaining the purpose of the study, the questionnaire and a stamped return envelope. Besides, the letter also noted that we would donate 30 NT dollars to a named charity for each effective questionnaire. Ten were returned due to undeliverable address. Three weeks after the first round mailing, follow-up surveys were mailed out. In the second round survey, we mailed a reminder letter and the questionnaire to 377 firms, which were randomly selected from the non-responding firms. We did not mail the follow-up survey to all the non-respondents because of budget constraints. A total of 169 surveys were returned, yielding a response rate of 17%. Excluding cases where no ERP was implemented, or implemented without the use of consultants, or had response omissions in critical data, the remaining sample size used for analysis was 132. The responding firms represent a wide range of manufacturing industries. Three types of manufacturing sectors are predominant: electronic (29.5%), automobile (9.8%), and data communication (9.1%). The firms range widely in size as measured by total assets and number of employees. Close to 50% of the firms have total assets of less than $1 billion and employ fewer than 500 workers. The sample is thought to be representative of medium to large-sized manufacturing firms in Taiwan (see Table 1). The most widespread ERP system used by Taiwan’s manufacturing firms is Data Systems (23.5%), the second Oracle (12.9%), and the third SAP (9.8%). As to the external consulting sources, the majority of the responding firms (71.9%) relied on the ERP vendor for implementation support. Most of the firms (55.3%) had implemented ERP for more than 2 years. More than 43% of the responding firms had implemented five to six ERP modules. Table 2 presents detailed information about the ERP systems implemented. To ensure the representativeness of the sample, t-test was conducted on employee number and total asset value with a sample of non-respondents to check for possible non-response bias. A random sample of 100 non- respondents was compared with the 132 respondents. The findings provided no evidence of the existence of non-response bias. Additionally, two groups of the same size were formed based on the return date of the questionnaire. Then, a comparison between the early respondents group and the late respondents group was conducted (Armstrong & Overton, 1977). The assumption of this analysis is that late respondents share similar characteristics with non-respondents. The results of t-test indicated that no significant differences in these two variables between early and late respondents. 3.2. Measures The measures were largely based on the scales in the literature and were adapted to the ERP implementation context. All the items were measured on a five-point Likert scale, anchored from 1 (strongly disagree) to 5 (strongly agree), and are provided in Table 3. The operationalization of the constructs is discussed below.
  7. 7. ARTICLE IN PRESS E.T.G. Wang et al. / International Journal of Information Management 27 (2007) 200–212 206 Table 1 Profile of the organizations that responded Company characteristics Category Effective data Percentage Industry category Food 7 5.3 Metalwork 8 6.1 Machinery equipment 8 6.1 Plastic goods 5 3.8 Iron and steel 4 3.0 Electronics 39 29.5 Data communication 12 9.1 Textile 7 5.3 Chemicals 3 2.3 Nonmetal mineral 1 0.8 Shoemaking 1 0.8 Chemical product 2 1.5 Paper-making 4 3.0 Automobile 13 9.8 Others 17 12.9 Missing value 1 0.8 Total asset Less than NT$ 80 million 4 3.0 NT$80 million–NT$0.2 billion 12 9.1 NT$0.2 billion–NT$0.5 billion 28 21.2 NT$0.5 billion–NT$1 billion 24 18.2 NT$1 billion–NT$2 billion 22 16.7 NT$2 billion–NT$5 billion 15 11.4 NT$5 billion–NT$10 billion 10 7.6 Over NT$10 billion 16 12.1 Missing value 1 0.8 Number of employees Less than 100 17 12.9 100–500 63 47.7 501–1000 22 16.7 1,001–3000 16 12.1 Over 3000 14 10.6 o2 Number of IT employees 25 18.9 3–5 44 33.3 6–10 22 16.7 11–20 19 14.4 21–50 10 7.6 Over 51 10 7.6 Missing value 2 1.5 3.2.1. Absorptive capacity Absorptive capacity is largely a function of the client’s preexisting stock of knowledge (Dierickx & Cool, 1989) and it becomes manifested in the client’s ability to value, assimilate and apply new knowledge successfully to commercial ends. The operationalization of absorptive capacity was based on Szulanski (1996) with five items, assessing the extent to which the client’s ability to exploit the ERP knowledge transferred from the consultants. 3.2.2. Consultant competence Refers to the consultants’ ability to solve the client’s problems, to offer related and needed knowledge, to mobilize various skills, and to help the client configure and derive value from the ERP package (Timbrell & Gable, 2001; Volkoff & Sawyer, 2001). This study operationalized the construct based on Roberts et al. (2001) with eight items.
  8. 8. ARTICLE IN PRESS E.T.G. Wang et al. / International Journal of Information Management 27 (2007) 200–212 207 Table 2 Profile of the ERP adopting organizations_Toc40694074 ERP-related information Category Effective data Percentage ERP vender SAP 13 9.8 Oracle 17 12.9 IE ERP 6 4.5 Data systems 31 23.5 Proyoung business Information system 8 6.0 J. D. Edwards 2 1.5 Wellan 3 2.3 FAST Tech 5 3.8 Baan 5 3.8 Self-developed 19 14.4 Others 23 17.4 Consulting firm IBM 4 3.3 HP 9 6.8 Andersen TN Soong & Co. 5 3.8 Deloitte 1 0.8 Advanced, Inc. 4 3.3 Provided by ERP vender 95 71.9 Others 14 10.6 ERP online time Less than 6 month 20 15.2 6 month–1 year 5 3.8 1–2 year 32 24.2 Over 2 year 73 55.3 Missing value 2 1.5 Number of modules implemented 1–2 modules 8 6.0 3–4 modules 27 20.5 5–6 modules 58 43.9 7–8 modules 35 26.5 Over 9 modules 3 2.2 Missing value 1 0.8 3.2.3. Effective knowledge transfer Effective knowledge transfer was operationalized based on Simonin (1999) with two items, assessing the extent to which the client absorbs and uses the ERP-related knowledge transferred from the consultants. 3.2.4. Organizational process fit The operationalization of organizational process fit was based on Hong and Kim (2002) with three items, assessing the extent to which the ERP system fits the client’s requirements and processes. 4. Data analysis and hypothesis testing Confirmatory factor analysis (CFA) was conducted to examine the validity of the constructs analyzed in this study. When conducting CFA, if the model provides a reasonably good approximation to reality, it should provide a sufficiently good fit to the data. The CFA for the measurement model resulted in a root mean square residual of .05 (p.10 is recommended), a w2/degree of freedom ratio of 2.31 (p3 is recommended), a Comparative Fit Index of .90 (X.90 recommended), and a Non-normed Fit Index of .90 (X.90 recommended). The measurement model was adequate for the data set. Convergent validity is demonstrated when different instruments are used to measure the same construct, and scores from these different instruments are strongly correlated (Campbell & Fiske, 1959). Convergent validity can be assessed through t-tests on the factor loadings, such that the loadings are greater than twice their standard error (Anderson & Gerbing, 1988). The t-tests for the factor loadings are shown in
  9. 9. ARTICLE IN PRESS E.T.G. Wang et al. / International Journal of Information Management 27 (2007) 200–212 208 Table 3 Measurement model—confirmatory factor analysis results t-value Construct indicators Standardized Alpha loadings Absorptive capacity .91 The adopting firm had information on the state-of-art of the ERP system .72 9.31* The adopting firm had a clear division of roles and responsibilities to implement the ERP .76 10.02* system The adopting firm had the needed skills to learn and understand the ERP system .87 12.26* The adopting firm had the technical competence to absorb the ERP system .88 12.49* The adopting firm had the managerial competence to absorb the ERP system .87 12.41* Consultant competence .92 Providing the message that ERP implementation involves a cultural change .72 11.79* Involved in each of the various techniques used by the ERP system .73 9.55* Providing expertise in executing the transition to the ERP system .77 10.35* Providing evidence of the value of the ERP system .86 12.18* Providing a complete understanding in the ERP system .81 11.19* Contributing expertise and experience in using the ERP system .80 10.90* Providing knowledge on how the ERP system will affect roles and responsibilities for .78 10.45* personnel involved Returning at a later date to insure changes to the implementation process are properly .78 10.50* completed Knowledge transfer .71 Your company has learned a great deal about the ERP technology/process know-how .77 11.79* held by the consultants The ERP technology/process know-how held by the consultant has been assimilated by .72 8.94* your company and has contributed to other projects developed by your company Organizational process fit .86 The processes built in ERP meet all needs required from organizational processes .87 11.90* The processes flow built in ERP corresponds to flow of organizational processes .89 12.32* The processes built in ERP correspond to the business practices of our company .70 8.72* *Significant at .05. RMSEA: .10 (p.10 recommended). Bentler’s CFI: .90 (X.90 recommended). w2/d.f. ratio: 300.07/130 ¼ 2.31 (o3 recommended). Bollen (1988) NNFI: .90 (X.90 recommended). Table 3. The results showed that the constructs demonstrated a high level of convergent validity since all t-values were significant at the .05 level. Discriminant validity is demonstrated when different instruments are used to measure different constructs, and the correlations between the measures of those different constructs are relatively weak. Discriminant validity was assessed by using the confidence interval test (Anderson & Gerbing, 1988). A confidence interval test involves calculating a confidence interval of plus or minus two standard errors around the correlation between factors, and determining whether this interval includes 1.0 (or À1.0). If the interval (for each pair of constructs) does not include 1.0, discriminant validity is demonstrated. The results of the confidence interval tests supported the discriminant validity of the factors. In addition, the reliability of each construct was examined by Cronbach’s alpha. All the values of Cronbach’s alpha exceeded the recommend level of .70 (Nunnally 1978). The means, standard deviations, and intercorrelations are presented for all the variables in Table 4. The theorized model in Fig. 2 fits the data reasonably well, with a root mean square residual of .05, a w2/degree of freedom ratio of 2.37, a Comparative Fit Index of .90, and a Non-normed Fit Index of .90. Fig. 3 shows the results of the structural equation modeling analysis. All three null hypotheses were rejected by the t-tests at the .05 level of statistical significance. The standardized path coefficients are .40, .68, and .61, respectively.
  10. 10. ARTICLE IN PRESS E.T.G. Wang et al. / International Journal of Information Management 27 (2007) 200–212 209 Table 4 Descriptive statistics and correlation Absorptive capacity Consultant competence Technology transfer Organizational Process (AC) (CC) (EKT) fit (FIT) Mean 3.49 3.55 3.55 3.44 Median 3.60 3.63 3.50 3.33 Std deviation 0.73 0.64 0.72 0.73 Kurtosis 1.16 0.12 0.57 À0.01 Skewness 0.03 À0.62 À0.38 À0.38 AC 1.00 CC 0.54 1.00 EKT 0.61 0.75 1.00 FIT 0.58 0.47 0.47 1.00 H1 – rejected t-value: 2.7442 coefficient: 0.40 Absorptive Capacity Organizational Knowledge Process Fit of Transfer ERP H3 - rejected t-value: 5.3264 coefficient: 0.61 H2 - rejected Consultant t-value: 3.028 Competence coefficient: 0.68 Fig. 3. Analysis results. 5. Summary This study, to our best knowledge, is the first empirical evidence that demonstrates the relationships between the client’s absorptive capacity, consultant competence, and the effectiveness of knowledge transfer in ERP implementation. The model derived directly from stock-flow theory was confirmed and demonstrates that fit can be influenced by both internal knowledge capacity and the caliber of the external knowledge sources. Hypothesis 1 tested whether the client’s absorptive capacity is positively associated with effective knowledge transfer during ERP implementation. The finding in the positive direction is consistent with Szulanski’s (1996) study, which argued that the major ‘‘stickiness’’ of knowledge transfer is lack of absorptive capacity. Hypothesis 2 tests found in favor of a positive association between consultant competence and effective knowledge transfer. This result supports arguments that a consultant with essential ERP implementation knowledge repositories serve to meet the client business objectives (Bessant & Rush 1995; Timbrell & Gable, 2001). Thus, ERP consultants act as knowledge links, providing the necessary knowledge to the client when the client’s expertise is scarce and organizational learning around the ERP system is burdensome (Roberts et al., 2001). Hypothesis 3 tests indicate effective knowledge transfer is positively associated with ERP’s organizational process fit. Soh et al. (2000) suggested that a common challenge in successfully adopting ERP has been related to ‘‘misfit’’: the gap between the pre-written functionality offered and that required by the adopting firm. Due to the fact that customization is expensive, most companies installing an ERP package need to adapt or even completely rework their processes to fit the requirements of the package (Davenport, 1998). Under such circumstances, if a consultant can effectively transfer his/her sophisticated knowledge about how to
  11. 11. ARTICLE IN PRESS E.T.G. Wang et al. / International Journal of Information Management 27 (2007) 200–212 210 re-engineer the business processes of the client, the client is more likely to be successful in ERP implementation due to the experienced external help. When the knowledge is effectively transferred between the consultant and the client, i.e., the knowledge gap is eliminated, the ERP implementation will satisfy the client’s requirements better. 6. Implications Several managerial implications can be derived from this study. First, the selection of competent consultants is critical for ERP implementation success. When an ERP adopting firm lacks certain necessary capabilities, consultants can either be a knowledge provider or a facilitator during the implementation. With greater capability to configure and derive value from an ERP package, consultants can provide useful product knowledge as well as process guidance to ERP adopting firms (Timbrell & Gable, 2001; Volkoff & Sawyer, 2001). Through guided learning, formal training, and knowledge creation activities, consultants can help clients acquire the necessary knowledge for a successful ERP implementation. So ERP adopting firms should select the most qualified consultants before the implementation to guarantee the value brought in by the consultants. Second, ERP adopting firms should build up their internal knowledge stocks in order to stimulate the flow of knowledge transfer. Firms differ in their capability to absorb and assimilate new inputs of the ERP system. According to our research findings, a firm with greater internal knowledge stock will have a more successful ERP implementation. Thus, in order to pursue a successful implementation and gain greater competitive advantage, firms need to develop their internal knowledge stocks before implementing an ERP system. The building of knowledge stocks, though a necessary condition, is likely not sufficient without practices to ensure the knowledge is properly disseminated throughout the organization. Organizational practices, culture, and structure should be tailored to address these needs (Nonaka & Takeuchi, 1995). Finally, for a successful ERP implementation, ERP project managers should be able to assess the fit between their organization and the ERP system. Firms should consider the fit between the ERP system and the firm’s business processes as an important ERP selection criterion. As examples, Data systems (23.5%) is the most popular ERP system in Taiwan, where fit is more problematic due to the US and European reference organizations used to develop most ERP products. Although SAP and Oracle are world leading ERP vendors, the business practices they offer are all based on western business environments and do not necessarily provide the best solution for Taiwan’s manufacturing firms. 7. Conclusion This study focused on the implementation of ERP systems in manufacturing firms in Taiwan, the results might not hold with other system types, in other industries, or other countries. Future work might examine the model for other system types or organizational classifications. Studies in other global regions would add to the generalizability of the results, however, detailed demographic information about surveyed organizations was described in this study to allow readers to interpret the application contents. Additionally, organizational process fit of ERP may not be a sufficient indicator to evaluate the degree of the success of an ERP implementation. Other possible factors from the knowledge transfer literature could be tested along side or separately from those in this study, leading to a broader scope for the theoretical model tested. Future research may develop more comprehensive measurement scales, specifically developed to measure ERP success at multiple levels in an organization that accounts for the variety of success measures for more traditional systems. Further expansion of the model would then employ the success scales as a subsequent outcome after fit, providing a model that tracks organizational policies through the mediators of knowledge transfer and fit to eventual success. Acknowledgement This research is in part supported by the National Science Council, Taiwan, under the contract number NSC 95-2752-H-008-003-PAE.
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