The name of the journal chosen for this article is Business Process Management Journal (BPMJ). Applying a process approach, the magazine's focus is on driving the efficiency, effectiveness and competitiveness of the organization. Given the positive organizational impact that a successful technology project such as an ERP implementation can have, it is fitting that this research should be considered for publication in BPMJ as it adds to the body of knowledge the community needs of this journal.
Research title
Research problem and purpose
Based on the literature review, this research aims to test the two strongest independent variables, both of which are under the control of management, but this time in the context of the developing country of South Africa. Gable, Sedera, and Chan (2008) confirm this view and state that an IS project is a long-term investment that is expected to yield ongoing benefits in the future. 2013) note that organizations tend to neglect the role of the end user of the system. This narrow view of success excludes the perspective of one of the organization's most important stakeholders, the user.
Research motivation
These determinants of IS project success are assumed to be universal across country contexts and IS project contexts. However, very little research has been done to test these success factors in relation to ERP projects in South Africa. Based on the contingent factors consistently found to have a positive impact on IS project outcomes, this research aims to validate these in the South African and ERP project implementation contexts.
Introduction
Enterprise resource planning (ERP)
However, with the proliferation of the digital business in the modern era, ERP has become an important enabler for a digital business. As the system-of-record that cuts across most business functions, ERP systems provide the base layer essential to supporting digital business strategy in the modern era. The underlying technology itself is rarely the primary determinant of ERP system implementation success (Hiebl et al., 2017; Morris & Venkatesh, 2010).
Development of conceptual model
- Top management support and ERP project success
- Top management support and user participation
- User participation and ERP project success
- Conceptual model
Top management has a key role to play in facilitating decision-making across these different groups. Top management support has become an umbrella term covering three closely related categories of top management support: resource provision, management participation and management involvement (Liu et al., 2015). The literature strongly points to the fact that top management must participate and be present throughout the project (Liu et al., 2015).
Top management must act in a way that establishes and clearly communicates the project's priority in the organization. The support shown by top management cascades down the organization through middle management and ultimately to the system users. Through ongoing and publicly visible involvement (in word and deed), top management demonstrates their commitment to the project's success (Liu et al, 2015).
The behavior of top management sets an example that other stakeholders can follow. Having visible top management support and commitment to an ERP implementation significantly increases organizational support for change (Kim & Kankanhalli, 2009). Some studies consider top management to be the CEO along with those who report to the CEO (collectively the c-suite), while other studies consider top managers in the most senior positions to be top management (Liu et al., 2015).
Furthermore, the complexity of ERP projects highlights the need for top management to adjust their behavior and levels of support throughout the project; their actions cannot be static (Dong et al., 2009). 2013) claim that the two most important determinants of user satisfaction, one of their dimensions of IS success, are user involvement and top management support. The long-term value of ERP investments can be eroded by a lack of top management support and insufficient and ineffective user participation.
Conclusion
Introduction
Research design
This research used a single data collection technique, which Saunders, Lewis and Thornhill (2009) define as monomethod. The data collection technique took the form of a self-administered online survey questionnaire, which produced primary data. Since the research objective of this study was to test and validate the relationship between the antecedents of IS project success and not to explain why they occur, descriptive research was conducted.
Due to time constraints and for reasons of pragmatism, this research was a cross-sectional study, meaning that data were collected at one point in time.
Population
Unit of analysis
Sampling method and size
Users of the implemented ERP who were employed in the company when the ERP was implemented. As proven by the central limit theorem, Wegner (2016) explains that the minimum sample size for parametric statistical tests to be performed is 30 responses. 2009) cautions that a 100% response rate is unlikely, so the sample should be large enough to ensure sufficient responses to give the researcher the necessary confidence in the data. To increase the statistical power of the research, a sample size of 100 responses was targeted. 2009) suggest that a response rate of 30% for Internet-administered questionnaires in an organization is a reasonable assumption.
Given a response rate of 30 percent, the questionnaire therefore had to be distributed to a minimum of 334 ERP users. This was calculated by dividing the targeted responses by the response rate using the 'actual sample size required' formula (Saunders et al., 2009). The researcher has experience with the implementation of ERP systems and has an established network to which he has access.
Guided by this experience, the researcher believed that five organizations would provide the required answers from the sample unit of ERP users. Of the five companies that were approached, three companies have agreed to participate in the study. With the help of the management of the participating companies, the survey was sent to 970 ERP users.
Measurement instrument
Apart from the demographic data collected in Section A of the questionnaire, all other questions were answered using a five-point Likert scale. Ensuring that your questionnaire will provide enough data to answer the research question and achieve the research objectives is called content validity, while construct validity ensures that conclusions can be drawn from the research's operationalized variables to the theoretical constructs on which they are based (Yilmaz refers to reliability as the extent to which data collection techniques produce consistent findings. Using the same research technique that was planned for use in the study, the questionnaire was distributed to 10 ERP users within the researcher's own organization.
Since the researchers were only interested in collecting data from ERP users who were employed by the organization at the time of ERP implementation, the reliability of the data to be analyzed was increased through the screening question discussed in a previous section. . The validity and reliability of the data collected along with the response rates achieved depended largely on the design of the questions and the structure of the questionnaire (Saunders et al. 2009). Internal consistency measures the consistency of responses across other questions for the same construct in the same questionnaire.
The most widely used method to test for internal consistency reliability is Cronbach's alpha (Bonett & Wright, 2015; Saunders et al., 2009). To measure the validity of the instruments, a bivariate Pearson's correlation between each item question and the item total score was performed with SPSS software. The Cronbach's alpha scores for all items within all constructs were above 0.7, the generally accepted lower limit for Cronbach's alpha (Hair et al., 2014).
Factor scores were calculated as item means for each construct: user participation (Factor 1), top management support (Factor 2), individual influence (Factor 3a), organizational influence (Factor 3b), and project success (Factor 3). .
Data collection process
These measurements confirmed the reliability of the construct and the data were considered reliable to perform a detailed analysis. To reduce analytical complexity, factor scores were calculated to allow items to load as one factor per construct. Given that the sample size exceeded 50 responses (N = 102), the data are assumed to be approximately normally distributed. 2014) claim that larger sample sizes (more than 50 observations) reduce the negative effects of non-normality.
Deutskens, De Ruyter, Wetzels, and Oosterveld (2004) suggest that early follow-up reminders produce moderately better results than later follow-up examinations. Early follow-up notices should be sent to respondents to take advantage of the fast turnaround of online surveys. Although the cost of sending follow-up reminders for an online survey is negligible, it should be done with caution.
Repeat follow-ups have been shown to have diminishing returns, with the non-financial cost of annoying potential respondents without a corresponding increase in response rates. Because the researcher was dependent on management support to distribute the survey link, the number of reminders was limited to one follow-up. Company representatives who originally distributed the survey link sent a reminder email two weeks after the initial correspondence went out.
Analysis approach
Vicious and virtuous cycles in ERP implementation: a case study of interrelationships among critical success factors. Business intelligence capability: The effect of top management and the mediating roles of user participation and analytical decision-making orientation. Investigating the impact of organizational culture and top management support of knowledge sharing on the success of software process improvement.
How information sharing values influence the use of information systems : a study in the context of business intelligence systems. Critical Deployment Success Factors (CSFs) for ERP: Do they contribute to implementation success and post-deployment performance. Are you a user of the ERP (directly) or of the output of the ERP (indirectly).
Using a five-point scale ranging from (1) strongly disagree to (5) strongly agree, please rate ERP senior management support. Using a five-point scale ranging from (1) strongly disagree to (5) strongly agree, please rate the individual impact and the organizational impact ERP has had. Individual impact is about how ERP has affected your individual skills and effectiveness on behalf of the organization.
Organizational impact refers to the organizational-level impacts of ERP, particularly improved organizational outcomes and capabilities.