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A vehicle replacement policy for motor carriers in an unsteady economy

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  • Suzuki, Yoshinori
  • Pautsch, Gregory R.

Abstract

Recently, the motor carrier industry has experienced: (1) the sharp decline of vehicle (tractor) re-sale values, and (2) the substantial increase of vehicle insurance premiums. This study examines how motor carriers should adjust their vehicle replacement policies when dramatic changes of vehicle re-sale values and insurance premiums are observed. The study first develops a model of vehicle replacement optimization, and then solves the model by using the actual data obtained from a motor carrier. Intensive sensitivity analyses are performed to examine how the optimal solution is affected by the changes of vehicle re-sale values and insurance premiums, so that carriers can obtain normative policy implications. The results imply that: (1) carriers should use longer replacement cycles (extend the duration of vehicle use) when re-sale values decline, and (2) carriers' vehicle replacement policies should not be affected by the fluctuations of insurance premiums unless the fluctuations are substantial.

Suggested Citation

  • Suzuki, Yoshinori & Pautsch, Gregory R., 2005. "A vehicle replacement policy for motor carriers in an unsteady economy," Transportation Research Part A: Policy and Practice, Elsevier, vol. 39(5), pages 463-480, June.
    • Handle: RePEc:eee:transa:v:39:y:2005:i:5:p:463-480
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    References listed on IDEAS

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    1. Gerard J. Tellis & Fred S. Zufryden, 1995. "Tackling the Retailer Decision Maze: Which Brands to Discount, How Much, When and Why?," Marketing Science, INFORMS, vol. 14(3), pages 271-299.
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    Cited by:

    1. Stasko, Timon H. & Oliver Gao, H., 2012. "Developing green fleet management strategies: Repair/retrofit/replacement decisions under environmental regulation," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(8), pages 1216-1226.
    2. Durango-Cohen, Pablo L. & Madanat, Samer M., 2008. "Optimization of inspection and maintenance decisions for infrastructure facilities under performance model uncertainty: A quasi-Bayes approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 42(8), pages 1074-1085, October.
    3. Yoshinori Suzuki, 2008. "A generic model of motor‐carrier fuel optimization," Naval Research Logistics (NRL), John Wiley & Sons, vol. 55(8), pages 737-746, December.
    4. Parisa Ahani & Amílcar Arantes & Rohollah Garmanjani & Sandra Melo, 2023. "Optimizing Vehicle Replacement in Sustainable Urban Freight Transportation Subject to Presence of Regulatory Measures," Sustainability, MDPI, vol. 15(16), pages 1-18, August.
    5. Guerrero, Sebastian E. & Madanat, Samer M. & Leachman, Robert C., 2013. "The Trucking Sector Optimization Model: A tool for predicting carrier and shipper responses to policies aiming to reduce GHG emissions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 59(C), pages 85-107.
    6. Fan, Jin & He, Haonan & Wu, Yanrui, 2016. "Personal carbon trading and subsidies for hybrid electric vehicles," Economic Modelling, Elsevier, vol. 59(C), pages 164-173.

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