Title: Examining the Impacts of ESG on Employee Retention: A Study of Generational Differences
Authors: C. Christopher Lee; Joley L. Luppi; Tyler Simmons; BaoTram Tran; Ruoqing Zhang
Addresses: Author address listing can be found in the "About the Authors" section at the end of the article.
Abstract: Purposes - This study examines the relative effects of employees' environment, society, and corporate governance (ESG) perceptions on their intention to stay with the organization during the COVID-19 pandemic. This study also explores whether generational differences moderate the relationships between the three ESG factors and employee retention. Methods - This study uses an online survey to collect data via Amazon Mechanical Turk. Multiple regression analysis is used to analyze data collected from 716 respondents. Findings - The results show that environment-related ESG (E-ESG) and society-related ESG (S-ESG) positively and significantly impact employee retention, and the magnitudes vary across different generations. However, the impact of corporate governance-related ESG (G-ESG) on employee retention is not significant. Limitations - This study only compares two generational cohorts, namely Generation Y and Generation Z. Future research endeavors could expand the sample size, including Generation X, or consider other potential moderating factors such as job type, job location, or firm size. Contributions to literature - This study makes a valuable contribution to the existing literature by empirically investigating the relationships between ESG dimensions and employee retention. Practical implications - Businesses can effectively allocate corporate resources to important ESG factors uncovered by this study, thus, developing effective employee retention strategies. Originality - This study examines the collective effects of three ESG factors on employee retention. Furthermore, it highlights generational differences in the relationships between ESG factors and employee retention.
Keywords: Employee retention; ESG; generations; regression analysis; COVID-19.
Journal of Business and Management, 2023 Vol.29 No.1, pp.1 - 22
Published online: 05 Sep 2024 *