IDEAS home Printed from https://ideas.repec.org/a/eee/transe/v45y2009i4p538-550.html
   My bibliography  Save this article

Predicting truck driver turnover

Author

Listed:
  • Suzuki, Yoshinori
  • Crum, Michael R.
  • Pautsch, Gregory R.

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.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:transe:v:45:y:2009:i:4:p:538-550
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1366554509000210
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Phares, Jonathan & Miller, Jason W. & Burks, Stephen V., 2023. "State-Level Trucking Employment and the COVID-19 Pandemic in the U.S: Understanding Heterogenous Declines and Rebounds," IZA Discussion Papers 16265, Institute of Labor Economics (IZA).
    2. Zolfagharinia, Hossein & Haughton, Michael, 2016. "Effective truckload dispatch decision methods with incomplete advance load information," European Journal of Operational Research, Elsevier, vol. 252(1), pages 103-121.
    3. Lannoo, Steven & Verhofstadt, Elsy, 2016. "What drives the drivers? Predicting turnover intentions in the Belgian bus and coach industry," Transportation Research Part A: Policy and Practice, Elsevier, vol. 91(C), pages 251-259.
    4. Ashley Wygal & Douglas Voss & Michael B. Hargis & Scott Nadler, 2021. "Assessing Causes of Driver Job Dissatisfaction in the Flatbed Motor Carrier Industry," Logistics, MDPI, vol. 5(2), pages 1-15, June.
    5. Schuster, Amy M. & Agrawal, Shubham & Britt, Noah & Sperry, Danielle & Van Fossen, Jenna A. & Wang, Sicheng & Mack, Elizabeth A. & Liberman, Jessica & Cotten, Shelia R., 2023. "Will automated vehicles solve the truck driver shortages? Perspectives from the trucking industry," Technology in Society, Elsevier, vol. 74(C).
    6. Corsi, Thomas M. & Grimm, Curtis M. & Cantor, David E. & Sienicki, Dale, 2012. "Safety performance differences between unionized and non-union motor carriers," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(4), pages 807-816.
    7. 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).
    8. Wijngaards, Indy & Hendriks, Martijn & Burger, Martijn J., 2019. "Steering towards happiness: An experience sampling study on the determinants of happiness of truck drivers," Transportation Research Part A: Policy and Practice, Elsevier, vol. 128(C), pages 131-148.
    9. Chandiran, P. & Ramasubramaniam, M. & Venkatesh, V.G. & Mani, Venkatesh & Shi, Yangyan, 2023. "Can driver supply disruption alleviate driver shortages? A systems approach," Transport Policy, Elsevier, vol. 130(C), pages 116-129.
    10. 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.
    11. Ralf Elbert & Lowis Seikowsky, 2017. "The influences of behavioral biases, barriers and facilitators on the willingness of forwarders’ decision makers to modal shift from unimodal road freight transport to intermodal road–rail freight tra," Journal of Business Economics, Springer, vol. 87(8), pages 1083-1123, November.
    12. Richards, Timothy J. & Rutledge, Zachariah, 2023. "COVID-19, Truck Rates, and Trucking Shortages," 2023 Annual Meeting, July 23-25, Washington D.C. 335435, Agricultural and Applied Economics Association.
    13. Chenming Jiang & Linjun Lu & Jian John Lu, 2017. "Socioeconomic factors affecting the job satisfaction levels of self-employed container truck drivers: a case study from Shanghai Port," Maritime Policy & Management, Taylor & Francis Journals, vol. 44(5), pages 641-656, July.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:transe:v:45:y:2009:i:4:p:538-550. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/600244/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.