Investigating the Impact of E-Learning on Human Resource Productivity at Abadan Oil Refinery Using a Fuzzy Inference System
Subject Areas : روش های نوین آموزش وتوسعه منابع انسانیhabibollah ranaei 1 , Nazanin Kashanizade 2 , Moslem Alimohammadlo 3
1 - Associate Professor, Department of Management, Faculty of Economics, Management and Social Sciences, Shiraz University, Shiraz, Iran
2 - Master's degree, Department of Management, Faculty of Economics, Management and Social Sciences, Shiraz University, Shiraz, Iran
3 - Professor, Department of Management, Faculty of Economics, Management and Social Sciences, Shiraz University, Shiraz, Iran
Keywords: E-learning, human resource productivity, Abadan Oil Refinery, fuzzy inference system.,
Abstract :
With the expansion of knowledge and technology, e-learning has found its way into organizations which allows employees to update their knowledge and improve their productivity and efficiency within the organization. The purpose of this study was to investigate the impact of e-learning on human resource productivity at the Abadan Oil Refinery. In the first part of the study, the method was a systematic review of the scientific texts which was conducted through relevant keywords, searching the national (SID, Google Scholar, IRANDOC) and International data bases (Web of Science, Scopus, and Google Scholar) for the data published between 1998 and 2021. In the second part, the impact of e-learning on human resource productivity was examined using a two-part fuzzy inference system. The statistical corpus in the first part included studies conducted in the field of e-learning, from which samples were selected purposefully and judgmentally. In addition, the statistical population in the second part consisted of two groups: experts and administrative staff (460 individuals). Samples were selected purposefully and judgmentally from the expert group, and 210 individuals were selected from the administrative staff based on the Morgan Table. The findings indicated that the factors influencing e-learning consist of five components: learner-related factors (learner’s knowledge, interaction, interest, ability, trust, and attitude); instructor-related factors (instructor’s expertise and academic credibility, feedback, continuous assessment, and interaction with learners); educational content characteristics (content quality, multimedia usage, goal orientation, appropriate utilization of available resources, and easy accessibility); necessary infrastructure (technology and infrastructure within the organization, financial resources, and technical support services), and organizational factors (management support, organizational culture, and provision of professional certificates). Ultimately, the results from the designed fuzzy inference system revealed that any change (increase or decrease) in the factors influencing e-learning has a corresponding impact on human resource productivity, leading to measurable changes.
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