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Estimating the effects of carrier transit-time performance on logistics cost and service


  • Tyworth, John E.
  • Zeng, Amy Zhaohui


Joint determination of an appropriate transportation mode and an optimal inventory control policy is important in supply chain management. We present a method of estimating the effects of carrier transit-time performance on logistics cost and service. Unlike current approaches, this method enables users to develop accurate estimates when non-normal shapes characterize the probability distributions of both demand and lead time. Additionally, the methodology includes two important refinements to the standard transportation-inventory model. First, we relaxed the assumption that the shipping cost is a linear function of the order quantity. Second, we treated transit time as a segment of lead time. We used the gamma distribution to illustrate the flexibility of the method and developed an enhanced sensitivity-analysis tool for examining the effects of carrier transit time on both cost and service. The methodology is appropriate for the transportation of service-sensitive, independent-demand inventory items controlled by a continuous review inventory system.

Suggested Citation

  • Tyworth, John E. & Zeng, Amy Zhaohui, 1998. "Estimating the effects of carrier transit-time performance on logistics cost and service," Transportation Research Part A: Policy and Practice, Elsevier, vol. 32(2), pages 89-97, February.
  • Handle: RePEc:eee:transa:v:32:y:1998:i:2:p:89-97

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    References listed on IDEAS

    1. Allen, W. Bruce & Mahmoud, Mohamed M. & McNeil, Douglas, 1985. "The importance of time in transit and reliability of transit time for shippers, receivers, and carriers," Transportation Research Part B: Methodological, Elsevier, vol. 19(5), pages 447-456, October.
    2. Gary D. Eppen & R. Kipp Martin, 1988. "Determining Safety Stock in the Presence of Stochastic Lead Time and Demand," Management Science, INFORMS, vol. 34(11), pages 1380-1390, November.
    3. Blumenfeld, Dennis E. & Burns, Lawrence D. & Diltz, J. David & Daganzo, Carlos F., 1985. "Analyzing trade-offs between transportation, inventory and production costs on freight networks," Transportation Research Part B: Methodological, Elsevier, vol. 19(5), pages 361-380, October.
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    Cited by:

    1. Ruth Banomyong, 2010. "Supply Chain Dynamics in Asia," Working Papers id:3028, eSocialSciences.
    2. Engblom, Janne & Solakivi, Tomi & Töyli, Juuso & Ojala, Lauri, 2012. "Multiple-method analysis of logistics costs," International Journal of Production Economics, Elsevier, vol. 137(1), pages 29-35.
    3. repec:eee:transe:v:109:y:2018:i:c:p:139-150 is not listed on IDEAS
    4. Vernimmen, Bert & Dullaert, Wout & Willemé, Peter & Witlox, Frank, 2008. "Using the inventory-theoretic framework to determine cost-minimizing supply strategies in a stochastic setting," International Journal of Production Economics, Elsevier, vol. 115(1), pages 248-259, September.
    5. Tyworth, John E. & Saldanha, John, 2014. "The lead-time reliability paradox and inconsistent value-of-reliability estimates," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 70(C), pages 76-85.
    6. Shirley, Chad & Winston, Clifford, 2004. "Firm inventory behavior and the returns from highway infrastructure investments," Journal of Urban Economics, Elsevier, vol. 55(2), pages 398-415, March.
    7. Brand, Daniel & Parody, Thomas E & Orban, John E & Brown, Vincent J, 2004. "A Benefit/Cost Analysis Of The Commercial Vehicle Information Systems And Networks (Cvisn) Program," Research in Transportation Economics, Elsevier, vol. 8(1), pages 379-401, January.

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