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Given the considerable visible and hidden costs associated with voluntary job turnover and the fact that independent contract workers (“gig workers”) can change jobs with ease, it is imperative for managers and scholars to understand the reasons why someone joins a company in an effort to hire workers who will stay with the company longer. A commercial research panel company, Dynata, was used to collect data from current and former independent contract workers. After a rigorous screening protocol, data were collected retrospectively from 495 current and 456 former direct sellers, since direct selling is one of the oldest forms and largest categories of gig work. A binary logistic regression analysis enabled prediction of voluntary job turnover based on the number of reasons for joining the company. Findings from statistical analysis of the reasons for joining a company showed that the greater the number of reasons given for joining, the greater the likelihood of staying with the company. Additionally, statistically significant differences were observed between the current and former direct sellers for nine of the 12 reasons investigated. Importantly, from a predictive modeling perspective, it was possible to predict whether a direct seller would stay with the company or quit the company based on the number of reasons for joining the company. The research has implications for both theory and practice. Utilizing theoretical underpinnings from organizational and behavioral management literatures, pre- and post-employment variables establish the framework for pursuing a better understanding of pre-employment motives for joining a company. Despite calls for more research on individual differences in joining a company, past research efforts may have been hindered by the failure to explore new approaches, new agendas, and new methodologies. Theoretically, the research shows that there is a need to ensure the inclusion of pre-employment motive constructs in examining the construct of voluntary job turnover. Managerially, the cost of turnover is significant, and this is particularly true for salesforce turnover. Reducing the rate of voluntary salesforce turnover even by a small percentage could (1) lead to greater effectiveness, efficiency, and profitability for companies, (2) result in less time invested in a job for which an individual is not necessarily motivated to pursue successfully long-term, and (3) ensure consistent product and service delivery for customers. Little is known about gig workers, and this research project focuses on one of the original gig workforce cadres, direct selling. Additionally, this research is unique in its approach to collecting data retrospectively from current and former independent contract workers as well as in the predictive abilities offered by the data and subsequent statistical modeling.

The Importance of Pre-employment Job Motives in Predicting Voluntary Salesforce Turnover in the Gig Economy