Logistic Regression Approach to Predicting Truck Driver Turnover

S. Scott Nadler and John F. Kros
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S. Scott Nadler: Department of Marketing and Management, University of Central Arkansas, Conway, AR, USA
John F. Kros: Department of Marketing and Supply Chain Management, East Carolina University, Greenville, NC, USA

International Journal of Applied Logistics (IJAL), 2014, vol. 5, issue 1, 15-32

Abstract: The purpose of this study is to identify those constructs that lead to driver turnover. The theory of reasoned action (TRA), originating in the social psychology literature is the theoretical approach in this study. Interviews with drivers were conducted using the intercept method to develop a survey instrument. The survey was then administered to drivers at large truck stops. This study makes contributions on two fronts. From a managerial perspective the study results indicate that companies can use a technique such as this model as part of their driver retention efforts in order to create competitive advantage by increasing efficiency and cutting costs. The resulting logistic regression model, based on four factors, accounts for eighty eight percent of the variance and accurately predicts which drivers or driver classes are most at risk of turning over.

Date: 2014
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Persistent link: https://EconPapers.repec.org/RePEc:igg:jal000:v:5:y:2014:i:1:p:15-32

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