Drivers and Constraints of Employee Satisfaction with Remote Work: An Empirical Analysis

Abstract

Background/Purpose: The Covid 19 epidemic has forced many organizations to move to remote work (RW), and this trend is expected to continue even later in the post-epidemic period. Employees of the organization are at the heart of this transi-tion to RW, so identifying the factors that affect employee satisfaction with RW is very important for organizations to increase employee commitment and motivation. Therefore, the main objective of this study was to identify and prioritize the factors affecting employee satisfaction with RW using an innovative method.
Method: In the first phase of this study, a conceptual research model was designed inspired by literature. In the next phase, the proposed conceptual model of this re-search was tested using structural equation modeling (SEM). Then, using the artifi-cial neural network model, the importance of each of the model variables in pre-dicting employee satisfaction with RW was identified.
Results: The findings of this article ultimately disclosed that work-life balance, in-stitutional and technological support, job satisfaction, and perceived limited com-munication are, respectively, are elements that affect employee satisfaction with RW. The first three factors are drivers of employee satisfaction and the last factor (i.e., perceived limited communication) is the constraint of employee satisfaction with RW because it had a statistically significant negative effect on employee satis-faction with RW.
Conclusion: This study revealed that organizations should focus on the processes and strategies to improve employees’ work-life balance, provide institutional and technological support during remote work, and increase job satisfaction in order to increase the satisfaction level of their employees in the remote work. On the other hand, it was found that perceived limited communication is an effective factor that causes a decrease in the level of satisfaction of employees in remote work.

Keywords: Remote work, Employee satisfaction, Structural equation modeling, Multilayer per-ceptron, Artificial intelligence, Artificial neurol network, Covid 19 pandemic