Assessing the Impact of Person-Environment fit on Turnover Intention Through Multiple Linear Regression

Abstract

Focusing on key antecedents of intended turnover may enable organizations to intervene before reaching scenarios where employee turnover is inevitable. The current study aimed to establish which type of fit plays the most prominent role in employees’ turnover intention. To achieve this aim, multiple linear regression was used. By establishing which type of fit influences employees’ thoughts of quitting the most, organizations can adopt better retention strategies as opposed to casting a net and hoping for the best. This cross-sectional study used secondary data from 384 retail employees. Three distinct fit scales and a turnover intention scale were administered. The study’s hypothesis was assessed through multiple linear regression, relative weight analysis, and commonality analysis. Needs-supplies fit was the only variable that had a statistically significant negative association with turnover intention. Needs-supplies fit had the biggest contribution (23.64%) to the multiple R 2 value (34.25%) of the multiple linear regression model. Commonality analysis showed that needs-supplies fit accounted for the highest percentage (16.85%) of unique variance in explaining turnover intention. To enhance the probability of retaining employees, organizations may want to fine-tune their retention strategies based on establishing congruence between what employees need and what can be done to meet these desired needs. The current study stresses the importance of distinguishing between different types of person-environment fit as they may not similarly relate to outcomes.