Effect of Online Training on Employee Engagement During the COVID-19 Era

Mariam Hashem, Elizabeth Sfeir, Hussin J. Hejase, Ale J. Hejase


Employee engagement and training and development (T&D) are widely used terms nowadays, especially in the business world. Researchers and studies show that T&D influences the engagement of the employees. However, amid a dynamic environment full of change, studies need to follow suit and assess the impact of change too. Therefore, as the COVID-19 pandemic has arisen, new studies are needed in this era. Motivated by this reason, this study focuses on the "Effect of Online Training on Employee Engagement during COVID-19 Era (Remote Working)". It aims at exploring and investigating whether there is a link between online training and engagement by using the Towers Perrin-ISR Model of engagement which contains three components cognitive thinking, affective feeling, and behavioral acting components. This research uses a quantitative, deductive, and positivist approach. A structured questionnaire is designed and administered to a sample of 54 administrative employees at five different universities in Lebanon. It consists of 20 questions related to the chosen employee engagement model with five demographic factors. Statistical analysis was performed using the Statistical Product and Service Solutions, SPSS version 25. Descriptive statistics, Cronbach alpha, cross-tabulations, factor analysis, and regression analysis are applied. Results found did not find a statistically significant relationship between employee engagement and online training. However, an alternative model resulted in emphasizing the importance of having well-prepared institutions that foster their values, culture, and respect for the employees leading to a successful relationship and causing the acceptance and success of online training. This study is concluded within certain limitations and recommendations for future work as presented in this paper.

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DOI: https://doi.org/10.20849/abr.v7i5.1294


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Asian Business Research  ISSN 2424-8479 (Print)  ISSN 2424-8983 (Online)

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