Dual Organizational Changes: When BPR meets ERP Implementation

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Dual Organizational Changes: When BPR meets ERP Implementation

Dr. Chin-Yuan Ho

Dept. of Information Management National Central University E-mail: chuckho@mgt.ncu.edu.tw

Mr. Tu-Pei Yueh

Dept. of Information Management National Central University E-mail: s9423007@cc.ncu.edu.tw Abstract

ERP systems have been proven very difficult to implement given the required large technology investments and the fundamental changes in the way the business operates. Moreover, often-accompanying business process reengineering (BPR) creates even greater pressure on the affected functional units and users. However, ERP implementation and BPR are like a double-edge sword in that organizational benefits can be realized if the dual organizational changes can be well managed. We study the ERP project success from the perspective of organizational changes, and identify the effects of contingency variables, such as organizational resistance, adaptation, and actions or capabilities of stakeholders in the implementation project.

A mail survey is conducted over the CommonWealth Top 1000 Manufacturers in Taiwan. Out of 143 respondents, 98 firms that have implemented ERP systems are considered valid empirical data for us to test our hypotheses. The research findings show that a highly fit ERP system can produce better ERP project results when organizational resistance can be controlled or reduced. Adaptation, either process adaptation or ERP adaptation, can help improve the ERP success, even when there are gaps between “as-is” business processes and “to-be” processes. Top management commitment remains a powerful means to make ERP success more viable. But highly capable and committed key users are critical only when process change is great.

Keywords: ERP Implementation, BPR, Customization of ERP, Project Success

1. Introduction

The ERP system is the main information infrastructure of an organization. The system passes the information from one department to another. Correctness and timeliness of information is extremely important to the organization. Each organization has its own business model and processes. The uniqueness of the organization is the source of its competitive advantage. When it comes to choosing an ERP system, the fitness becomes one of the most important criteria (Somers et al., 2001). But ERP systems are packaged software. They are designed to meet the requirements of one or more industries. Only fully customized systems can perfectly meet the organization’s needs. If the organization decides to implement an on-the-shelf ERP system, it would need customize the system, or change the business processes (Bingi et al., 1999;Rolland et al., 2000), or both (Leonard-Barton, 1988). If the organization decided to customize the system, it might cost more and the implementation might last longer. If the organization decided to change the processes, the employees might resist the change (Markus et al., 2000). Either way will delay the implementation project, or even lead the implementation project to a failure.

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McLean’s IS success model (1992) helped the researchers to find a way to measure how successful the information system is. The model has six constructs, which are system quality, information quality, use, user satisfaction, personal impact, and organizational impact. But Hong and Kim (2002) claimed that the ERP implementation is different from the traditional IS implementation project. It is not evaluated by the general users, but by the project team members. The success is defined in terms of the achievement of some predetermined goals, which include parameters such as time, cost, and function. In this study, we measure ERP success in terms of the perception of project goals and system quality. Therefore, the purpose of this study is to characterize the effects of the organizational changes from both BPR and ERP implementation on ERP success, and this serves as our base relationship. More specifically, we want to identify the effects of contingency variables on the base relationship. The first set of contingency variables is adaptation, either process adaptation or ERP adaptation. The second is actions or capabilities of stakeholders in the implementation project, such as implementation consultants, top management, and key users. Also, we want to examine whether organizational resistance is mediating on the base relation.

Our research questions thus include the followings:

(1) What constitutes the organizational change in ERP implementation?

(2) Does the organizational fit of ERP alone determine ERP success? Whether the gaps between the as-is processes and the to-be processes help explain the outcome of ERP project?

(3) Given the organizational fit of ERP and the process gaps, what is the role of organizational resistance in ERP success?

(4) Given the organizational fit of ERP and the process gaps, will process adaptation or ERP adaptation improve ERP success?

(5) Given the organizational fit of ERP and the process gaps, will the key stakeholders affect ERP success?

We will provide a literature review in section 2. In section 3, a research model and the associated hypotheses are proposed. In section 4, we will briefly introduce the research method and the analysis results. Conclusions will be given at the end of this paper.

2. Literature Review

Soh et al. (2000) defined “misfits” problem of adopting package software as the gaps between the functionality offered by the package and that required by the adopting organization. Organizations have to choose among adapting to the new functionality, living with the shortfall, instituting workaround, or customizing the packages. Their findings showed that problems of misfit might be worse in Asia because the business models adopt European or US industry practices from the ERP vendors. Misfits arose from company-specific, public sector-specific, or country-specific requirements that did not match the capabilities of the ERP package. Soh et al. categorized the types of misfits into data misfits, functional misfits, and output misfits.

To deal with the misfits, organizations have a wide variety of choices between changing organizations themselves and customizing the ERP systems. Soh et al. deployed a spectrum of resolution strategies. Light (2001) also developed a continuum of maintenance implications of customizations. Brehm et al. (2001) also built a typology of ERP tailoring types. They identified 9 different types of ERP package tailoring. The typology shows the methods from configuration to package code modification. A particular company may choose to tailor a package by using almost every combination of the tailoring types. The ERP

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package tailoring typology was also used to predict success during each phase of implementation.

Another way to meet the ERP functionalities is to change business processes. Business Process Reengineering (BPR) projects vary widely in terms of their objectives. The primary objective of BPR is to make organizations more competitive by improving quality, reducing costs, and shortening product development cycles (Guimaraes, 1995). However, the potential problems of BPR are numerous and vary widely. Those problems include employees setbacks, communication barriers between functional areas, lack of leadership and inability to handle personal risk and confrontations properly, strategies formed outside the company’s ability to implement term, etc. In turn, the problems result in sinking morale, productivity drops, and distrust of management.

Based on the IS success model developed by DeLone and McLean (1992), Pitt et al., (1995) thought that the service perspective is weighing more in information system vendor. The service quality construct was then added to the ERP success model. Hong and Kim (2002) evaluated ERP implementation success from the negative side. They focused on the project perspective of implementing an ERP system. An instrument was developed to measure the time and money wasted or benefits/performance below the expectation.

Recognizing both the ERP implementation and BPC create tremendous organizational changes, and in turn, affect the outcome of ERP implementation, we want to capture and characterize their effects on the project success and system quality.

3. Research Model and Hypotheses

The purpose of this research is to study the effects of the organizational changes from both BPR and ERP implementation on ERP success. Our research model is depicted in Figure 3.1.

Organizational Change z Organizational Fit of ERP z Business Process Change ERP Success zProject Success zSystem Quality Contingency Variables

zTop Management Commitment

zConsultant’s Service Quality

zKey User’s Competency

zERP Adaptation zProcess Adaptation zOrganizational Resistance Organizational Change z Organizational Fit of ERP z Business Process Change ERP Success zProject Success zSystem Quality Contingency Variables

zTop Management Commitment

zConsultant’s Service Quality

zKey User’s Competency

zERP Adaptation

zProcess Adaptation

zOrganizational Resistance

Figure 3.1 Research Model

The research model is inspired by Hong and Kim’s study in 2002. Hong and Kim explored the high failure rate of ERP projects from an “organizational fit of ERP” perspective, given that fit is recognized as the most important selection criterion for ERP (Everdingen et al., 2000). From a different angle, we took the organizational change as the primary cause of failure for ERP projects. Not only the ERP implementation presents itself a great organizational change to the adopting organizations, tremendous pressure is added onto the affected units and users if business process reengineering (BPR) is pursued while implementing the ERP. BPR could be undertaken before, during, or after ERP implementation, which carries different relative advantages and disadvantages. According to

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Markus and Tanis (2000), there is general consensus that business process change adds considerably to the expense and risk of the implementation of ERP. Accordingly, we add Business Process Change (BPC) as another predictor variable for ERP success. We define BPC as the gap between the business processes before implementing ERP (as-is processes) and the business processes after implementing ERP (to-be processes). This leads to our first hypothesis.

H1aThe organizational fit of ERP is positively related to ERP success. H1bThe business process change is negatively related to ERP success.

Implementing an information system may cause resistance (Krovi, 1993). ERP implementation affects more units and users than the implementation of a conventional information system. In Hong and Kim’s research, organizational resistance was tested as a contingency variable. The results showed that, organizational resistance did not interact with organizational fit of ERP to explain ERP implementation success, but had significantly negative association with ERP implementation success. Their empirical results showed that organizational resistance is not a moderator variable, but an intervening variable between organizational fit of ERP and implementation success. Thus we propose our second hypotheses as follows:

H2aThere is a mediating effect of the organizational resistance on the relationship between organizational fit of ERP and ERP success.

H2bThere is a mediating effect of the organizational resistance on the relationship between business process change and ERP success.

ERP are commercial software packages, and they are designed to support generic business processes that may substantially differ from the way any particular organization conducting its business. Most adopting organizations have to customize ERP system to meet their specific needs. The impact of customizing ERP systems on the business depends on the gap between ERP functionalities and business needs. Customizing ERP systems can be beneficial and risky. The level of adaptation on ERP package was also used to predict success both during the initial implementation phase and post implementation phase of the ERP system life cycle (Brehm, 2001). That leads to our third hypothesis.

H3aThere is a moderating effect of ERP adaptation on the relationship between organizational fit of ERP and ERP success.

H3bThere is a moderating effect of ERP adaptation on the relationship between business process change and ERP success.

ERP vendors usually encourage clients to configure, instead of customize the software. The best practices represent the “proven” way of doing business from the successful implementation cases in a specific industry. If organizations adopt the best practices, they have to adapt their business processes to the embedded system processes in ERP. This leads to our fourth hypothesis.

H4aThere is a moderating effect of process adaptation on the relationship between organizational fit of ERP and ERP success.

H4bThere is a moderating effect of process adaptation on the relationship between business process change and ERP success.

Support from top management is one of the most unequivocally addressed critical success factors in information systems implementation. Top management can provide necessary supports for the project team in incentives, training, and augmented budget, resolve the conflicts during the implementation, and express their concerns for the progress and the system performance. It is reasonably to expect that the commitment from top management can strengthen the positive relationship between organizational fit and ERP success, and

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weaken the negative implications of BPC on ERP success.

H5aThere is a moderating effect of top management commitment on the relationship between organizational fit of ERP and ERP success.

H5bThere is a moderating effect of top management commitment on the relationship between business process change and ERP success.

ERP systems are too complex for most adopting organizations to implement all by themselves. The Implementation requires extensive knowledge not only on business domain and information technologies, but also project management and change management. Most organizations seek for help from implementation consultants. We expect that a good consulting company can provide critical supports to the organizations. That leads to our hypothesis 6.

H6aThere is a moderating effect of the consultant’s service quality on the relationship between organizational fit of ERP and ERP success.

H6bThere is a moderating effect of consultant’s service quality on the relationship between business process change and ERP success.

The implementation project team is composed of the project manager, the consultants, and the key users. Key users are usually the senior employees of each department in an organization. Key users play an important role in the project. They provide the workflows and requirements of his department. When the business process doesn’t fit with the system, they become the media between the organization and the implementing consultants. That leads to the hypothesis 7.

H7aThere is a moderating effect of key user’s competency on the relationship between organizational fit of ERP and ERP success.

H7bThere is a moderating effect of key user’s competency on the relationship between business process change and ERP success.

4. Research Method and Results 4.1 Sample and data collection

We developed a questionnaire with most question items from empirically tested instruments. To summarize, the sources of the instruments are shown in Table 4.1.

Table 4.1 Profiles of the research constructs

Concepts References

Business Process Change Guimaraes, 1985 Organizational Fit of ERP Hong and Kim, 2002 Organizational Resistance Hong and Kim, 2002 Process Adaptation

ERP Adaptation Hong and Kim, 2002 Consultant’s Service Quality Freeman and Dart,

1993 Key User’s Competency This study Top Management

Commitment This study

Project Success Hong and Kim, 2002 System Quality Shin and Lee, 1996

Given that ERP implementation is most popular in manufacturing firms, we selected the top 1,000 manufacturing firms from the “Premier 2001” database in the CommonWealth

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Magazine as the sample for our study. We mailed the questionnaire to the directors of MIS department. Out of the 1,000 mails, 143 were returned. 36 of the respondents haven’t implemented ERP systems, 3 were dropped due to incomplete or inappropriate data entry, 6 developed ERP systems by themselves, and 98 were valid responses.

4.2 Descriptive statistics

Among the 98 valid respondents, we have 40 in electronics, 14 in information and communication, 7 in metalwork, 5 in chemical engineering, 4 in both mechanical engineering and textiles, 3 in chemicals, auto parts, and steel. And the rest scattered among other industries. In terms of the ERP vendors, Data System Consulting (DSC), Oracle, and SAP ranked the top with 31, 13, and 4 cases, respectively. As for the implementation time, only 13 cases completed the project in six months. 32 cases spent from six months to a year. 45 cases spent from a year to two years. And 25 cases spent more than two years.

4.3 Instrument validatoin

In the following analysis, we used SPSS 10.0 as the analyzing tool. In this study, each construct has multiple items to measure a single concept. Those items must have the convergent validity to make sure the total score is valid. Items were eliminated if their item-total correlation was below 0.4 in this study (Kerlinger, 1986). For discriminant validity, we checked the factor loading for each item with exploratory factor analysis (EFA). Items were eliminated if the factor loading was below 0.5. After eliminating those items with low item-total correlation and factor loading, the remaining items were sure to have the required validity.

Reliability is the accuracy of a measuring instrument. The internal consistency reliability was assessed by calculating Cronbach’sαvalues. The reliability analysis result of the constructs is summarized in Table 4.2. The internal consistency (Cronbach’s α) of the concept ranged from 0.7774 (for Project Success) to 0.9399 (for Top Management Commitment). The result shows that the reliability of the instrument is acceptable.

Table 4.2 Internal consistency reliability (Cronbach’s α)

Concept Items Mean S.D. Reliability

Organizational Fits of ERP 10 3.24 0.63 0.9096 Business Process Change 10 2.89 0.71 0.8922 Organizational Resistance 5 3.26 0.73 0.8290

ERP Adaptation 6 3.43 0.70 0.9345

Organization Adaptation 4 3.35 0.80 0.8785 Top Management Commitment 6 3.35 0.75 0.9399 Consultant’s Service Quality 20 3.29 0.55 0.9247

Key User’s Competency 5 3.39 0.73 0.8932

Project Success 4 3.21 0.76 0.7774

System Quality 6 3.47 0.52 0.8252 0.8153

4.4 Testing base relationship

First, we examine the base relationship between organizational fit of ERP and ERP project success and the base relationship between business process change and ERP project success. Second, we examine the role of contingency variables in the base relationship. Table 4.3 displays the correlation matrix of the variables in this study.

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According to the correlation matrix of Table 4.3, we found the base relationship between organizational fit of ERP and ERP success was significant (r = 0.651, p<0.01), and that of business process change was also significant (r = 0.228, p<0.05). However, as we divide the ERP success into project success and system quality, we found that the relationship between business process change and project success was not significant. In other words, the gap between the “as-is” processes and “to-be” processes is not significantly related to the project success, but is significantly related to the system quality. Thus hypothesis H1a is supported and H1b is not. The result of H1a is also consistent with Hong and Kim’s study.

Table 4.3 Correlation matrix of the variables

a ORGFIT, Organizational fit of ERP; BPC, Business process change; ORGRST, Organizational resistance; ERPADPT, ERP adaptation; PRCADPT, Process adaptation; TOPCMT, Top management commitment; CONSERVQ, Consultant’s service quality; KUCOMP, Key user’s competence; PROJSUC, Project success; SYSQUA, System quality; ERPSUC, ERP success ** P < 0.01 * P < 0.05 A B C D E F G H I J ORGFIT (A) 1.000 BPC (B) 0.263** 1.000 ORGRST(C) -0.325** 0.074 1.000 ERPADPT (D) -0.117 0.110 0.416** 1.000 PRCADPT (E) -0.141 0.143 0.302** 0.598** 1.000 CONSERVQ (F) 0.651** 0.235* -0.327** -0.089 -0.055 1.000 KUCOMP (G) 0.407** 0.151 -0.294** 0.008 -0.109 0.355** 1.000 TOPCMT (H) 0.478** 0.211* -0.438** -0.075 0.012 0.496** 0.623** 1.000 PROJSUC (I) 0.439** 0.082 -0.340** -0.202* -0.185 0.500** 0.287** 0.271** 1.000 SYSQUA (J) 0.633** 0.292** -0.344** -0.049 -0.005 0.514** 0.426** 0.413** 0.363** 1.000 ERPSUC (I+J) 0.651** 0.228* -0.414** -0.151 -0.113 0.614** 0.433** 0.416** 0.819** 0.922**

4.5 Testing the contingency relationships

Hong and Kim (2002) found that, both “ERP adaptation” and “Process adaptation” has a moderating effect on ERP implementation success. In this study, we additionally considered “Top management commitment”, “Consultant’s service quality”, and “Key user’s competency”. We also used the typology of moderator variables and the method for identifying moderator variables developed by Sharma et al. (1981). According to Sharma et al., to examine the moderator variable, we first checked the relationship between the predictor and dependent variable with simple regression. Then we checked that if the interaction of the moderator and predictor would influence the dependent variable.

In the following analysis, organizational fit of ERP and business process change are used as the predictor variables in sequence, and ERP success is the criterion variable. First we use organizational fit of ERP as the predictor, the regression results are listed in Table 4.4.

Table 4.4 The moderator test results with Organizational fit of ERP as the predictor

Regression Model β (Interaction) p-value (Interaction) R 2 p-value (model) R 2 ORGFIT 0.424 0.000

ORGFIT + ORGRST +Interaction -0.892 0.066 0.488 0.000 0.064 ORGFIT + ERPADPT +Interaction -0.074 0.883 0.429 0.000 0.005 ORGFIT + PRCADPT + Interaction -0.296 0.523 0.427 0.000 0.003 ORGFIT + CONSERVQ+ Interaction 0.174 0.789 0.487 0.000 0.063 ORGFIT +KUCOMP+ Interaction 1.032 0.056 0.478 0.000 0.054 ORGFIT +TOPCMT+ Interaction 1.260 0.020 0.469 0.000 0.045

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* ORGFIT, Organizational fit of ERP; ORGRST, Organizational resistance; ERPADPT, ERP adaptation; PRCADPT, Process adaptation; TOPCMT, Top management commitment; CONSERVQ, Consultant’s service quality; KUCOMP, Key user’s competence

We found that the relationship of ERP adaptation and Process adaptation with either Organizational fit of ERP or ERP success is not significant. Neither of the adaptation has interaction with Organizational fit of ERP. According to Sharma et al., ERP adaptation and Process adaptation are homologizer variables. That is, ERP adaptation and Process adaptation can affect the relationship between Organizational fit of ERP and ERP success, but has no interaction with Organizational fit of ERP. The result supports hypothesis H3a and H4a. “Top management commitment” is significantly related to both Organizational fit of ERP and ERP success. Its interaction with the predictor is also significant. Thus, Top management commitment is a quasi-moderator. This result supports hypothesis H5a. As for Consultant’s service quality and Key user’s competence, they are significantly related to ERP success, but have no interaction with Organizational fit of ERP. Therefore both Consultant’s service quality and Key user’s competence are not moderator variables. The identification of each variable is displayed in Table 4.5. The hypothesis H6a and H7a are not supported.

Table 4.5 Identification of moderators with Organizational fit of ERP as the predictor

* Predictor variable: Organizational fit of ERP; Criterion variable: ERP success

Related to Criterion and/or Predictor Not Related to Criterion and Predictor No Interaction

With Predictor

Organizational resistance, Consultant’s service quality and Key user’s competence are not moderators

Process adaptation and ERP Adaptation are homologizers Interaction With

Predictor Variable Top management commitment is quasi-moderator

Replicating the regression tests on the contingency variables with Business process change (BPC) as the predictor, we have the test results in Table 4.6.

Table 4.6 The moderator test results with Business process change as the predictor

* BPC, Business process change; ORGRST, Organizational resistance; ERPADPT, ERP adaptation; PRCADPT, Process adaptation; TOPCMT, Top management commitment; CONSERVQ, Consultant’s service quality; KUCOMP, Key user’s competence; Dependent variable=ERP success

Regression Model β (interaction) p-value (interaction) R 2 p-value (model) R 2 BPC 0.052 0.024 BPC+ ORGRST+ Interaction 0.537 0.240 0.250 0.000 0.198 BPC+ ERPADPT +Interaction 1.282 0.023 0.133 0.004 0.081 BPC+ PRCADPT + Interaction 1.035 0.068 0.106 0.014 0.054 BPC+ CONSERVQ+ Interaction -0.427 0.451 0.389 0.000 0.337 BPC+KUCOMP+ Interaction 1.435 0.006 0.275 0.000 0.223 BPC+TOPCMT+ Interaction 1.438 0.006 0.256 0.000 0.204

The results showed that, the ERP adaptation is neither significantly related to BPC nor ERP success, but its interaction with BPC is significant to ERP success. By the criteria of Sharma et al., we found that “ERP adaptation” is a pure moderator in this model. A pure moderator is a variable that can change the form of relationship between predictor variable and criterion variable. This kind of change is caused by the interaction of moderator variable and predictor variable. The result supports hypothesis H3b.

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With regards to “Process adaptation”, it is neither related to BPC nor ERP success. The interaction with BPC is not significant either. Thus, Process adaptation is a homologizer. It affects the relationship between BPC and ERP success, but it has no interaction with BPC. The result supports hypothesis H4b.

“Top management commitment” and “Key user’s competence” are significantly related to both BPC and ERP success, and their interactions with BPC are also significant. Therefore, these two variables are Quasi-moderators. The difference between a quasi-moderator and a pure moderator is the relationship with the predictor. The quasi-moderator is related either to the predictor or the criterion variable. Thus, Top management commitment and Key user’s competence can moderate the effect of BPC on ERP success. The result supports hypothesis H5b and H7b.

As for “Consultant’s service quality”, it is significantly related to both BPC and ERP success, but has no interaction with BPC. It means that the Consultant’s service quality has no moderating effect on the relationship between BPC and ERP success. The result supports hypothesis H6b. The identification of the moderator variables is shown in Table 4.7.

Table 4.7 Identification of moderators with Business process change as the predictor

* Predictor variable: Business process change; Criterion variable: ERP success

Related to Criterion and/or Predictor Not Related to Criterion and Predictor

No Interaction With Predictor

Organizational Resistance and Consultant’s

service quality are not moderators Process adaptation is homologizer Interaction With

Predictor Variable

Top management commitment and Key user’s

competence are quasi-moderators ERP adaptation is pure moderator

According to Hong and Kim’s findings, Organizational resistance has no moderating effect on the relationship between Organizational fit of ERP and Project success, but has an intervening effect. From Table 4.4-4.7, we also replicated Hong and Kim’s results. Therefore, we will examine the mediating effect in this study, with ERP success as the criterion variable and Organizational fit of ERP or BPC the predictor variable.

We followed Baron and Kenny’s method (1986) to examine a mediator variable. First, we used Organizational fit of ERP as the predictor variable. From the test results in Table 4.8, we found that all the necessary conditions held in the predicted direction. Given the beta value of Organizational fit of ERP in the fourth equation is 0.577, which is smaller than the beta value of Organizational fit of ERP in the second equation (0.651), the fourth condition was held too. Therefore, the mediation of Organizational resistance between Organizational fit of ERP and ERP success was established. That means, when the mediator variable exists, the relationship between independent variable and dependent variable is weakened. The results support hypothesis H2a.

Table 4.8 Results of mediation test with Organizational fit of ERP as the predictor

* ORGFIT, Organizational fit of ERP; ORGRST, Organizational resistance; ERPSUC, ERP success

Regression

Equation Selected Variables

Dependent Variable β (Predictor) R 2 p-value 1 ORGFIT ORGRST -0.325 0.106 0.001 2 ORGFIT ERPSUC 0.651 0.424 0.000 3 ORGRST ERPSUC -0.414 0.172 0.000

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Then, we considered Business process change (BPC) as the independent variable. The regression results are listed in Table 4.9. From the results, we found that there is no significant relationship between Organizational resistance and BPC. Therefore, hypothesis H2b was not supported. Organizational resistance has no mediation effect on the base relationship between BPC and ERP Success.

Table 4.9 Results of mediation test with Business process change (BPC) as the predictor

* BPC, Business process change; ORGRST, Organizational resistance; ERPSUC, ERP success

Regression

Equation Selected Variables

Dependent Variable β R 2 p-value 1 BPC ORGRST 0.074 0.005 0.471 2 BPC ERPSUC 0.228 0.052 0.024* 3 ORGRST ERPSUC -0.414 0.172 0.000* 4 BPCORGRST ERPSUC 0.260 0.239 0.005*

To summarize the hypotheses and their testing results, we concluded the results in Table 4.10. In the 14 hypotheses we have proposed, 9 of them are supported by the empirical data.

Table 4.10 Summary of hypotheses testing

Hypotheses H1a H1b H2a H2b H3a H3b H4a H4b H5a H5b H6a H6b H7a H7b

Supported Y N Y N Y Y Y Y Y Y N N N Y

* “Y” = Supported; “N” = Not supported

From the results, the research model can be modified to Figure 4.1 and Figure 4.2.

Organizational Change z Organizational Misfit of ERP ERP Success zProject Success zSystem Quality Mediating Variable zOrganizational Resistance Moderating Variables

zTop Management Commitment

zERP adaptation zProcess Adaptation Organizational Change z Organizational Misfit of ERP ERP Success zProject Success zSystem Quality Mediating Variable zOrganizational Resistance Moderating Variables

zTop Management Commitment

zERP adaptation

zProcess Adaptation

Figure 4.1 Revised Research Model (Organizational fit of ERP as the predictor)

Organizational Change z Business Process Change ERP Success zProject Success zSystem Quality Moderating Variables

zTop Management Commitment

zKey User’s Competency

zERP Adaptation zProcess Adaptation Organizational Change z Business Process Change ERP Success zProject Success zSystem Quality Moderating Variables

zTop Management Commitment

zKey User’s Competency

zERP Adaptation

zProcess Adaptation

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5. Conclusion

Recognizing ERP implementation as a planned organizational change, the adopting organization best identify an ERP system that “fit” the most to the organization’s requirements, such as processes, data, and interfaces, to ensure the project success and best system quality. Both Process adaptation and ERP adaptation can help improve the ERP success, even when there are gaps between “as-is” business processes and “to-be” processes. Top management commitment remains a powerful means to make ERP success more viable. But highly capable and committed key users are critical only when process change is great. Surprisingly, Business process change measured by the gap between as-is processes and to-be processes is positively significantly related to ERP success, but not significantly related to project success. It seems that the desirable outcomes can be realized only when significant changes in processes are pursued and a great effort in adaptation is committed. This is a very good manifestation of the verse in the Bible (Psalm 127:5), “Those who sow in tears shall reap with joyful shouting.”

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Acknowledgement

This study is supported by the MOE Program for Promoting Academic Excellence of Universities: Electronic Commerce Environment, Technology Development, and Application (Project Number: 91-H-FA08-1-4).

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