Global Journal of Computer Science and Technology, G: Interdisciplinary, Volume 23 Issue 1

obtain a body of quantitative data connected to two or more variables, as well as their association, survey research entails a cross-sectional design (Bryman & Bell, 2011). With the aid of a survey, the authors were able to categorize and describe the population, and test relationships and assumptions (Jackson, 2015). Since the primary goal of this study was to establish a correlation between a predictor variable and several response variables, and because it was descriptive and explanatory, data were collected using both a web-based and paper-based questionnaire, which was then used for statistical analysis. This study adopted a quantitative approach, and in the current research, hypotheses are derived from extensive literature reviews to test the relationships between variables. Users were asked to rate the variables on a Likert scale using a web-based survey. Collected data converted into numerical data, was then further statistically tested using statistical software. As a result of the approach and purpose of this study, a quantitative approach was recommended to answer the research questions and test the hypothesis. For primary data collection, the survey strategy used in this study included a questionnaire. The current study made use of a self-administered questionnaire for primary data collection. The research used both paper- based responses and online questionnaires to increase the number of responses of system users who are widely dispersed geographically. As this study makes use of survey research strategies where one needs to draw inferences from a sample of a population to answer the research question, probability sampling was chosen (Saunders et al., 2009). The current study targeted the system users of ERP systems implemented remotely in Sri Lanka. Since the targeted respondents were a niche group, the chosen respondents were credible since they were the best fit for the intended purpose. The study was aimed the companies in the manufacturing sector where ERP systems have been implemented remotely during the Covid-19 pandemic in Sri Lanka. The population amounted to900 ERP system users of remotely implemented ERP, based on the Krejcie & Morghan (1970), since the population size was 900, the sample size was taken as 269. According to the convenience sampling technique, the sample was selected, and responses were collected both using web-based and paper-based questionnaires. The research extensively made an effort to increase the response rate via e-mails by sending reminders to the respondents and following up the process by reminding them to finish the questionnaire. To address the initial proposition of the study, the statistical analysis consists of examining, coding, tabulating, or otherwise combining the evidence (Yin, 1989). In this section, we analyze the data collected using questionnaires, using descriptive statistics, Pearson correlation, and multiple linear regression using the statistical package for social scientists (SPSS version 21), and presenting the results as tables and graphs. In terms of the original units of the data, regression analysis measures the average relationship between two or more variables. It shows cause-and- effect relationships between variables. Thus, the current study used multiple regression analysis to determine the type of relationship (positive or negative) that exists between the selected independent variables and the dependent variable - the remote ERP implementation success and whether those independent variables significantly impact on the remote ERP implementation success. It is necessary to assess the validity and reliability of the measures for the instrument, according to Hair et al. (2003). This study used Cronbach’s Alpha to assess the instrument's internal consistency and reliability. Effective research should have a Cronbach's Alpha result of at least 0.7. Thus, while the questionnaire is distributed to 33 first respondents, Cronbach's Alpha result has been checked and found to be above 0.7. This indicates the validity of the research. © 2023 Global Journals Global Journal of Computer Science and Technology Volume XXIII Issue I Version I 33 ( )G Year 2023 Table 2: Cronbach’s Alpha Level of Reliability Cronbach’s Alpha Internal consistency α ≥ 0.9 Excellent 0.9 > α ≥ 0.8 Good 0.8 > α ≥ 0.7 Acceptable 0.7 > α ≥ 0.6 Questionable 0.6 > α ≥ 0.5 Poor 0.5 > α Unacceptable Source: Based on (Bonett and Wright, 2015) The scale of reliability of Cronbach's Alpha is shown in Table 2, and there have been various reports of accepted Alpha values above. The most acceptable score Alpha value is above 0.7. Also, a minimal number of questions and poor connections between items or heterogeneous notions could be reasons for a score below 0.7. Critical Success Factors of Remote ERP Implementation: From System Users’ Perspective