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Driver turnover in the trucking industry: What's the cost of reducing driver quit rates?

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  • Trick, Steven
  • Peoples, James
  • Ross, Anthony

Abstract

This paper empirically examines the personal characteristics of truck drivers that are associated with a greater probability of driver turnover. Exploration of this phenomenon is significant in part because knowing who is likely to leave a trucking company helps decision makers in trucking firms identify effective measures needed to reduce driver turnover. Estimation results of a discrete driver quit choice model along with findings from estimating a driver wage equation, are used to predict the driver compensation needed to mitigate high driver turnover. These findings show that at the mean, drivers who stay on the job receive $54.25 (2018 dollars) more per week than drivers who leave, which translates to $2836.20 annually and is 6.02% percent above the mean wage of drivers who leave their job. The value of this annual wage differential is less than the mean value of the conservatively low estimate of $3654.72 (2018 dollars) computed in past research as the per driver cost of truck driver turnover. We interpret these results to suggest that it is cost effective for trucking companies to increase driver compensation. Indeed, truck driver wage trends do show a recent pattern of wage gains.

Suggested Citation

  • Trick, Steven & Peoples, James & Ross, Anthony, 2021. "Driver turnover in the trucking industry: What's the cost of reducing driver quit rates?," Research in Transportation Economics, Elsevier, vol. 89(C).
  • Handle: RePEc:eee:retrec:v:89:y:2021:i:c:s0739885921001013
    DOI: 10.1016/j.retrec.2021.101129
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    References listed on IDEAS

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    1. Michael H. Belzer, 2002. "Technological Innovation and the Trucking Industry: Information Revolution and the Effect on the Work Process," Journal of Labor Research, Transaction Publishers, vol. 23(3), pages 375-395, July.
    2. Michael R Faulkiner & Michael H Belzer, 2019. "Returns to compensation in trucking: Does safety pay?," The Economic and Labour Relations Review, , vol. 30(2), pages 262-284, June.
    3. Suzuki, Yoshinori & Crum, Michael R. & Pautsch, Gregory R., 2009. "Predicting truck driver turnover," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 45(4), pages 538-550, July.
    4. Dale L. Belman & Kristen A. Monaco, 2001. "The Effects of Deregulation, De-Unionization, Technology, and Human Capital on the Work and Work Lives of Truck Drivers," ILR Review, Cornell University, ILR School, vol. 54(2A), pages 502-524, March.
    5. Bender, Stefan & Lane, Julia & Shaw, Kathryn L. & Andersson, Fredrik & von Wachter, Till (ed.), 2008. "The Analysis of Firms and Employees," National Bureau of Economic Research Books, University of Chicago Press, number 9780226042879, December.
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