Pay Volatility and Employee Turnover in the Trucking Industry

Autor: Nina Gupta, Samantha A. Conroy, Dorothea Roumpi, John E. Delery
Rok vydání: 2021
Předmět:
Zdroj: Journal of Management. 48:605-629
ISSN: 1557-1211
0149-2063
DOI: 10.1177/01492063211019651
Popis: Many organizations have turned to “just-in-time” pay systems to manage fluctuations in demand for products and services. For example, the trucking industry commonly pays truck drivers by the mile, and retail organizations fluctuate hours available to work to align with holiday demand. Based on the Unfolding Model of Turnover, we propose that the pay volatility, that is, fluctuations in individual pay over time, created by such systems create shocks that initiate thoughts of leaving the organization. We propose that these thoughts increase turnover likelihood. We also propose that pay level and pay trajectory moderate the pay volatility and turnover relationship. Based on a large dataset containing information on objective pay and turnover for truck drivers over a period of 34 weeks, the results of this study support the role of pay volatility, pay level, and pay trajectory in affecting voluntary turnover. Specifically, the results show that all three factors predict turnover likelihood and that pay volatility and pay level interact to predict turnover likelihood. The findings indicate that pay volatility has organizational downsides due to its effects on employee turnover in addition to its known upsides (i.e., flexibility).
Databáze: OpenAIRE