The Relationship between Remote Employee Engagement and Computer-Mediated Communication Indicators

Authors

  • Franklin M. Lartey Lartey Research and Management, 320 Old Orchard Court Marietta, GA 30069, The United States.
  • Phillip M. Randall School of Business, Technology, and Health Care Admininstration Capella University, Minneapolis, MN, The United States.

DOI:

https://doi.org/10.9734/bpi/ctbef/v1/18461D

Keywords:

Employee engagement, remote worker, computer-mediated communications, self-determination theory

Abstract

This study looked at the computer-mediated communication indicators that influence remote knowledge workers' engagement.  The study was conducted  an online survey of 133 remote knowledge workers in the U.S. and  a multiple regression statistical model was used to answer the research question seeking the extent to which empathy, expressiveness, and motivation contributed to remote employee engagement. The findings indicated a statistically significant association between the dependent variable Engagement and the independent variables Empathy, Expressiveness, and Motivation. Since no prior attempt had been made to analyse the relationship between engagement and the items highlighted here, this study filled a knowledge gap in the literature. Our findings may help to direct future research and job design for distant knowledge workers in the digital and pandemic era, which has consequences for both researchers and practitioners. Managers can use this study to pinpoint which remote workers require the most assistance. This is based on the fact that remote workers are separated from their coworkers and managers and the lack of casual discussions that usually serve to instruct them or remind them of tasks could impair their performance in the absence of self-determination. 

Published

2023-02-24

How to Cite

Franklin M. Lartey, & Phillip M. Randall. (2023). The Relationship between Remote Employee Engagement and Computer-Mediated Communication Indicators. Current Topics on Business, Economics and Finance Vol. 1, 132–144. https://doi.org/10.9734/bpi/ctbef/v1/18461D