A Structural Equation Model of Organizational Culture and mediating Factors of ERP System Success
Organizational culture and organizational citizenship behavior (OCB) are two major categories of behavior in the field of organizational behavior management theory. Although many studies on the effect of these two concepts have been done, few address how these concepts affect Enterprise Resource Planning (ERP) systems. The purpose of this paper will be to investigate the relationship between organization culture and the successful factors of ERP via an OCB mediator. ERP success’ factors to be studied in this paper are: information quality, and user satisfaction. The relations between organizational culture, OCB and ERP will be hypothesized during this research using structural equation modeling, and a representation model showing their relationships. The results will indicate that organization culture has a positive impact on OCB. Furthermore, organizational citizenship behavior will also have significant positive impacts on information quality, and user satisfaction.
Enterprise Resource Planning, Critical Factors, Organizational Culture, Organizational Citizenship Behavior
Organizational culture as a component of an effective organization has always been of particular interest to organizations. Different studies on organizational culture and its relationship with other factors such as job satisfaction, performance, and productivity confirm this claim (Ebrahimpour, Zahed, Khaleghkhah, & Sepehri, 2011). Deshpande and Webster Jr (1989) define organizational culture as a “set of shared assumptions and understanding about organization functioning.” Since organizations are made up of individuals with various characteristics, and talents, organizations will have a diverse culture. If personnel change, some aspects of this culture will change. Hence, organizational culture is known to be influential for the success of any project involving organizational changes (Ke & Wei, 2008). In other words, the fit between the information system and organizational culture is critical for organizations to secure future benefits promised by the system (Ke & Wei, 2008).
Organizational citizenship behaviors (OCBs) are extra role behaviors of employees, which go beyond the planned formal roles. Primarily, the topic of OCBs did not even have a great impact on the field of organization behavior study. However, during the past decade, interest in it has increased vividly. Interest in OCBs has not been limited to the field of organizational behavior, it also extended to different fields such as human resource management, marketing, hospital and health administration and education (Yoon, 2009). Various dimensions have been proposed to define an OCB construct. One of the most popular and effective models of OCB is Organ’s model. Organ (1988) proposed ‘altruism’, ‘conscientiousness’, ‘courtesy’, ‘civic virtue’ and ‘sportsmanship’ as OCB dimensions. Thus, Organ’s model is to be used in this paper and will be applied to finding the relationships between organizational culture and ERP systems success factors.
An ERP system is an integrated software system that provides a solution to information-processing needs, enabling executives to manage resources efficiently and effectively. In recent times, many companies have implemented an ERP system not only to survive but also to achieve strategic advantages in an increasingly competitive business environment. The ERP system has subsequently become the backbone of the information system of the company (Yoon, 2009). Understanding and identifying the critical success factors (CSFs) of ERP systems are necessary for a successful ERP implementation. Although many CSFs are enumerated in literature, this paper focuses on the common set of CSFs by reviewing the literature: information quality, and user satisfaction.
Since an ERP is a complex system, difficulties that arise from using an ERP system may cause delay in business transactions. Any act especially above prearranged tasks that helps colleagues who are having difficulty using the ERP system will improve the efficiency of the transaction (Yoon, 2009).
The effective implementation of an ERP system requires change management strategies and understanding of organizational culture (Costa, Ferreira, Bento, & Aparicio, 2016). The literature shows that organizational culture has a significant impact on OCB (Harwiki, 2016). In effect, when organizational culture improves in an organization, OCB will also improve. Therefore, organizational culture and OCB factors have a vital role in an organization’s change management strategies, which lead to the successful implementation of an ERP system. Moreover, despite recent research on OCBs and its impact on the various fields such as sales performance, productivity, product quality, and service quality in marketing; few types of research address the effects of OCBs in information systems and in particular ERP.
In sum, organizational culture and OCB are two major categories of behavior in organizations, hence, investigating their impact on a successful ERP system implementation is important. Some research has been done exploring the impact of OCB on CSFs of an ERP system, however, there is not adequate research that examines the impact of organizational culture on CSFs of ERP via OCB factors. Consequently, finding the relationships between organizational culture and OCB in the success of ERP systems can be beneficial for many organizations. The results of this study would provide a schema for organizations on what factors are vital while they are implementing ERP system.
This research will use a quantitative method for data analysis. In this method, questionnaires are to be distributed, and then the data will be collected and analyzed. The emphasis of quantitative method is on objective measurement and statistical analysis of data collected through questionnaires and surveys (Morgan, 2007). Organizational culture will be employed as an exogenous variable, organizational citizenship behavior and success factors of ERP system as the endogenous variables. To assess these relationships, path analysis using structural equation modeling (SEM) will be conducted. SEM is a general statistical modeling technique used to establish relationships among variables. Also, SEM is considered to be a confirmatory technique that tests models conceptually derived beforehand. Essentially, SEM is a combination of factor analysis and a series of multiple regressions. The software to be used for data analysis in this paper is Statistical Analysis System (SASTM 9.4).
There are many definitions for organizational culture, and most of them are based on the idea that organizational culture helps organizational members with different goals, strength, responsibility and attitude. Since organizational culture values develop through the cooperation between individuals and organizations, people who are involved with an organization have an important role in creating, developing and changing their organizational culture. The members of an organization are presumed to be categorized by the cultural similarity in terms of shared understandings, belief, values, social norms that make them somehow different from other groups outside the organization (Alvesson, 1987).
Organizational culture provides a structure for using theoretical work and knowledge to improve an organization’s effectiveness. It is difficult to find a highly successful company that does not have a unique, recognizable organizational culture. Organizational culture influences the communication skills and employees’ decision-making processes. Researchers have shown that organizational culture has an effect on employees’ commitment and behavior (Mohanty & Rath, 2012).
Organizational culture variables are beliefs and norms, individual autonomy, individual responsibility, conflict tolerance, structure, risk tolerance and support (Mohanty & Rath, 2012). Belief and norms tend to reflect the values of the group and specify those actions that are proper and those that are improper. Individual autonomy defines as the amount of self-determination in job activities, and freedom to control the pace of work. Individual responsibility is a “social phenomenon that is explained as the accumulation of the unintended consequences of individual actions”. Conflict tolerance is the gratefulness of diversity and the ability to live and let others live. A structure is the “distributions along various lines of people among social positions that influence the role relations among people”. Risk tolerance defines as the degree to which people are persuaded to take the initiative, and perform risky and ambitious actions. Support is the activity of contributing to the fulfillment of a need (Mohanty, 2013).
Furthermore, organizational culture provides the employee a frame of reference for changes in an organization. It means that when organizations have different cultures, employee have different perceptions of organizational changes. Therefore, organizational culture is known to be important for the success of any project involving organizational changes (Yoon, 2009).
Organizational citizenship behavior
Since Organ (1988) introduced the concept of organizational citizenship behaviors more than two decades ago, OCB has been one of the most active research areas among organizational scientists. Organ (1988) believed that OCB is positive actions of some of the employees for improving productivity and cohesiveness in the workplace beyond their job and organizational duties.
Katz and Kahn (1978) divided behaviors in organizations into in-role behavior and extra-role behavior. In-role behavior is in accordance with formal role descriptions, and extra-role behavior is beyond formal role requirements. According to their theory, extra-role behavior arises from feelings of ‘‘citizenship” with respect to the organization. These feelings have been perceived as the backbone of behaviors that are not required by an organization, but have positive impacts on organizational function (Yoon, 2009).
Various dimensions have been proposed to define the OCB construct. Organ (1988) proposed ‘altruism’, ‘conscientiousness’, ‘courtesy,’ ‘civic virtue’, and ‘sportsmanship’ as OCB dimensions. The components of Organ’s study have become widely accepted as the dimensions of OCB construct as they comprehensively represent the concepts of extra-role behavior or voluntary behavior (Yoon, 2009).
Organ depicted the dimensions as follows: ‘altruism’ is about when an employee assists another one in completing his task under unusual circumstances; one worker helping another worker catch up after his sick leave is an example of altruism. Conscientiousness refers to an employee performing his assigned tasks in a manner beyond what is expected. Courtesy defines as a behavior such as “helping someone prevents a problem from occurring, or taking steps in advance to mitigate the problem” (Organ, 1988). Civic virtue brings support for the administrative roles in the organization. Sportsmanship refers to emphasizing the positive aspects of the organization instead of the negative and it is a willingness of the employee to endure less than ideal conditions without complaining (Mohanty, 2013).
Nowadays, organizational citizenship behavior has been widely noted in management because of its positive impacts on organizations. The significance and the necessity of OCB on the effectiveness of organizations have been realized by the managers for many years. Batman and Organ (1983) in their empirical studies concluded that there is a positive and significant relationship between job satisfaction and OCB. In marketing literature, Bell and Menguc (2002) explored the direct positive relationship between OCB and customers’ perceptions of service quality. Organizations that hire people showing extra-role behavior are more likely to have effective work groups within the organization. Literature shows that there is a positive and significant relationship between organizational culture and OCB in an organization (Mohanty, 2013).
ERP system success factors
To deal with a rapidly changing environment and overcome the limitations of the current systems, many companies have implemented Enterprise Resource Planning systems.
ERP systems are computer-based information systems for enterprising integration. They supersede manufacturing resource planning (MRPII) systems and material requirements planning (MRP), and its perspective is broader than manufacturing. ERP systems specifically address the need for integration of application programs in different business processes such as sales, accounting, and manufacturing. Different business applications can all use a common database that serves as the integrating mechanism. Enterprise applications are systems that coordinate activities, decisions, and knowledge across many different functions, levels and business entities in a company. ERP systems are accepted to be the most important enterprise applications around the world. However, the implementation of ERP systems as a complex system is a challenging approach. In fact, the high failure rate has been reported due to cancellation, cost and time overruns. Hence, in order to reduce the failure rate of ERP systems implementation, a number of studies have been conducted to identify critical success factors (CSFs) in the implementation of ERP systems (Ngai, Law, & Wat, 2008).
DeLone and McLean (1992) believes that an ERP system is an information system that integrates the enterprise functions. It provides services to entire departments in organizations. It also brings a capacity to organizations to plan and manage its resources based on an integrated approach. A review of literature illustrates different models and CSFs that influence on ERP systems success. This study examines a couple of CSFs of ERP systems based on the Delone and McLean model.
Information system success can be measured in six factors: information quality, system quality, system use, user satisfaction, individual impact, and organizational impact (Delone & McLean, 2003). Information quality and user satisfaction are the two factors to be examined in this research. Although measuring financial performance must be an important variable to measure ERP systems success, it has been argued that financial performance cannot be used as a measurement since it is difficult to measure financial performance affected only by information systems (Yoon, 2009). Therefore, this variable is excluded from this research.
Information quality is characteristics such as accuracy, meaningfulness, and timelines in a product (DeLone & McLean, 1992). System quality has a different meaning from information quality. System quality is defined as “the degree to which the system is easy to use for accomplishing some task” (Costa et al., 2016, pp. 662-663).
In an ERP system environment, user satisfaction refers to the extent to which users perceive the ERP system is accessible to them and meets their needs. Obviously, an ERP system without user satisfaction is less likely to be used by the user and generate valuable outcomes (Dezdar & Ainin, 2011). Prior studies found that system quality has the strongest impact on user satisfaction of the other factors (Tsai, Lee, Shen, & Lin, 2012). Therefore, one factor that affects organizational performance is a user satisfaction. In sum, some organizational changes should be managed for an ERP system to be successfully implemented.
Research model and hypotheses
Some evidence has converged on the finding that organizational culture has a significant impact on OCB (Mohanty & Rath, 2012). Therefore, the first hypothesis is formed as:
Hypothesis 1. There exists a relationship between organizational culture and OCB
Helping behavior (altruism) has a positive impact on productivity and product quality. ERP systems’ data created by employees who are new or has little experience in using an ERP system can be inaccurate and incomplete. Helping behaviors toward them may make the data of an ERP system more accurate. Moreover, conscientious behaviors such as observing company regulations and procedures in using ERP systems, and performing ERP systems transactions in time or even after working time will create information in a timely fashion (Yoon, 2009). Podsakoff, Ahearne, and MacKenzie (1997) also argued that employees, who exhibit sportsmanship, enhance their organizations’ ability to adapt to changes in the environment by demonstrating a willingness to take on new responsibilities or learn new skills. Sportsmanship behavior like willing to accept new information technologies will help ERP systems to be successfully adapted to the organizations; thus, OCB will ultimately have an effect on the information quality of ERP systems. Therefore, the following hypothesis can be established.
Hypothesis 2. There is a relationship between OCB and the information quality of an ERP system.
Nowadays, ERP systems play an important role in completing the business transactions of a company. Consequently, difficulties that arise from using an ERP system may cause business transactions delay. Courtesy may serve as an effective method of coordinating activities among team members and users. Courtesy by touching base with other team members, or members of other groups in the organization, reduces the likelihood of the occurrence of problems that would otherwise take time and effort to resolve. Therefore, it is expected that courtesy behavior prevents problems from occurring. Civic virtue by voluntarily attending and actively participating in work meetings support the cooperation among users; hence, potentially increases the users’ effectiveness and efficiency in using ERP systems. Since these kinds of behavior make ERP systems easier to use for users, result in a user satisfaction of ERP systems. Therefore, the following hypothesis will be established.
Hypothesis 3. There is a relationship between OCB and user satisfaction of ERP systems.
Therefore, the research model can be formed using above hypotheses. The research model for this study is presented in Exhibit 1.
Hypotheses will be verified using Structural Equation Modeling which is a statistical method based on multivariate regression analysis. Since the proposed model consists of more than one endogenous variables also known as dependent variables, simple regression would not be appropriate. In a simple regression, one variable is affected by one independent variable; however, in this model, three variables are affected by one independent variable. In general, when one or more independent variables or one or more dependent variables or causal relationships are hypothesized, then using SEM is required rather than a simple regression analysis (Ullman & Bentler, 2003).
Exhibit 1. Proposed research model
The approach used in this research is a correlational approach. A correlational study is a quantitative method in which the relationship or covariance between two or more variables are investigated (Mitchell, 1985).
Data collection and measures
The target of this research is organizations that has implemented ERP systems. Data will be collected from ERP system users in different companies where ERP systems were implemented. Since all population is available, simple random sampling is adequate method for sampling in this study. Due to the fact that structural equation modeling has the ability to model complex relationships between multivariate data, sample size is an important issue. A larger sample size is always desired for SEM (Ullman & Bentler, 2003).
The measures to be used for this study are adapted to fit the context from prior research (Costa et al., 2016; Yoon, 2009). Each questionnaire includes 23 questions which will be used to study the variables such as organizational citizenship behavior, organizational culture and ERP success implementation indicators. The questionnaire can be found in Appendix A. Respondents will be asked to choose the best answer that is applicable to their organization on the basis of the five-point Likert scale ranging from 1 (least strongly) to 5 (most strongly). In addition, before administering the questionnaires, measures will be reviewed for clarity of items and content validity by experts. To confirm reliability and internal consistency of the questionnaire, Cronbach’s alpha reliability coefficient is measured in SAS 9.4. Cronbach’s alpha coefficient ranges between zero and one. The closer Cronbach coefficient to one, the greater the internal consistency (Ullman & Bentler, 2003).
Structural Equation modeling is a confirmatory technique which tests models that are conceptually derived and tests whether the theory fits the data. SEM is a combination of factor analysis and multiple regression that tests measurement and structural model which specified in a proposed model simultaneously. Other names for SEM are path analysis, casual modeling, and analysis of covariance structures. There are three advantages of SEM over simple regression or even multiple regression. First one is that SEM allows analysis for multiple dependent variables; however, regression allows only a single dependent variable. The second advantage is that SEM allows variables to correlate. The last but not the least, SEM accounts for measurement error, whereas regression assumes that the measurements are perfect. Furthermore, SEM concepts consists of observed variable or indicators, latent variables, measurement model and structural model. Indicators are the variables actually measured in the study. Latent variables are the constructs that are measured by a variety of indicators, such as items in a questionnaire (Ullman & Bentler, 2003). Hence, the reason of using SEM in this study becomes clear with this explanation.
Moreover, in this research, ERP, OCB and organizational culture factors are latent variables and items in the questionnaire are observed variables.
Assessment of Measurement model and Structural Model
For testing the measurement model, confirmatory factor analysis technique and for structural model, path analyses technique are used. The measurement model will be tested before the structural model.
To make sure whether there are causal relationships between variables and to test the fitting of the data with the proposed model, measurement model using confirmatory factor analysis will be conducted in SAS 9.4. To assess measurement model, the goodness-of-fit index will be investigated. When the ratio of χ2 to degree of freedom (df) is less than three, the goodness-of-fit index is acceptable. Another index for goodness-of-fit which is widely used in structural equation modeling is Root Mean Square Error of Approximation (RMSEA), and typically a RMSEA of less than 0.05 is required. (Narimani, Tabaeian, Khanjani, & Soltani, 2013).
A structural model is a part of the entire structural equation modeling diagram that will be completed for every model proposed. It is used to relate all of the variables, both latent and observed, in the model (Costa et al., 2016). For structural model path analysis technique in SAS 9.4 will be used. Path diagram of this research is shown in Exhibit 2.
Exhibit 2. Path Diagram of proposed model.
ERP systems Success Factors
Organizational Citizenship Behavior
To test the hypothesized relationships, confirmatory factor analysis and path analysis, structural equation modeling with PROC CALIS in SAS 9.4 will be employed. PROC CALIS, stands for covariance analysis of linear structural equations, is a software package that was designed to handle all analyses in structural modeling. The code are used for path analysis is as follows:
PROC CALIS date= name of dataset;
Path Organizational culture —> OCB;
Path OCB —> Information Quality;
Path OCB —> User satisfaction;
After conducting path analysis in SAS 9.4, the results of hypothesis analysis will be generated, which is similar to Exhibit 3.
Exhibit 3. Sample of results of hypothesis analysis.
|H1||Organizational culture OCB||Supported Or not supported|
|H2||OCB Information Quality|
|H3||OCB User Satisfaction|
|Note: Significant at:
p < 0.001
A brief summary of method procedure which is used in this study is shown in Exhibit 4.
Exhibit 4. Summary of method procedure.
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ATZ1. I support employees who are unfamiliar with an ERP system
ATZ2. I give my time to help employees with ERP system related problems.
ATZ3. I take time out of my day to help train new employees
ATZ4. I perform ERP system-related work of absent employees if I can.
CST1. I obey company rules, regulations and procedures in using an ERP system.
CST2. I carry out ERP system-related work in a timely manner.
CST3. I complete ERP system-related work even though after business hours
CTS1. I am cautious to avoid problems with coworkers in using an ERP system
CTS2. I do not abuse rights of others in using an ERP system
CTS3. I do not interfere with coworkers with regard to using an ERP system
CVT1. I am willing to follow organizational change.
CVT2. I keep up with the policy and business strategy of the organization.
CVT3. I positively participate in efforts for process improvement.
SPM1. I keep trivial complaints about using an ERP system to myself
SPM2. I do not complain about my ERP system-related work even if the work seems excessive
SPM3. I do not complain about business processes that seem unfair to me.
IFQ1. The ERP system of our company provides us important information.
IFQ2. The ERP system of our company gives us usable information.
IFQ3. The ERP system of our company provides us relevant information.
USS1. The ERP supports adequately my area of work and responsibility
USS2. The ERP is efficient.
USS3. The ERP is effective.
USS4. The ERP satisfies me on the whole.
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