Predicting truck driver turnover |
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Authors: | Yoshinori Suzuki Michael R Crum Gregory R Pautsch |
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Institution: | 1. Department of Logistics, Operations, and Management Information Systems, College of Business, Iowa State University, 2340 Gerdin Business Building, Ames, IA 50011-1350, United States;2. Department of Economics, College of Business and Public Administration, Drake University, 344 Aliber Hall, Des Moines, IA 50311-4505, United States |
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Abstract: | We propose a decision tool for truckload carriers that can help control driver turnover rates. Our approach is to use an existing econometric method, along with the drivers’ work data, to predict the quit probability of each driver on a weekly basis, so that carriers can identify a subset of drivers who are “about to quit” in a timely manner. Empirical results from two case studies indicate that our approach does a nice job of predicting driver exits, and that it may become a useful management decision tool. Our method was recently adopted by two US truckload carriers. |
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