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

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  • Tyworth, John E.
  • Zeng, Amy Zhaohui

Abstract

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

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    1. Randolph W. Hall, 1985. "Dependence between Shipment Size and Mode in Freight Transportation," Transportation Science, INFORMS, vol. 19(4), pages 436-444, November.
    2. 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.
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    Cited by:

    1. Schmidt, Carise E. & Silva, Arinei C.L. & Darvish, Maryam & Coelho, Leandro C., 2023. "Time-dependent fleet size and mix multi-depot vehicle routing problem," International Journal of Production Economics, Elsevier, vol. 255(C).
    2. Chuantao Cui & Leona Shao-Zhi Li, 2019. "High-speed rail and inventory reduction: firm-level evidence from China," Applied Economics, Taylor & Francis Journals, vol. 51(25), pages 2715-2730, May.
    3. Ochtman, G. & Dekker, R. & van Asperen, E. & Kusters, W., 2004. "Floating stocks in FMCG supply chains," Econometric Institute Research Papers EI 2004-17, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    4. 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.
    5. 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.
    6. Minken, Harald & Johansen, Bjørn Gjerde, 2019. "A logistics cost function with explicit transport costs," Economics of Transportation, Elsevier, vol. 19(C), pages 1-1.
    7. Yu Sun & Feng Lian & Zhong-Zhen Yang, 2022. "Optimizing the location of physical shopping centers under the clicks-and-mortar retail mode," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(2), pages 2288-2314, February.
    8. Ruth Banomyong, 2010. "Supply Chain Dynamics in Asia," Working Papers id:3028, eSocialSciences.
    9. 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.
    10. Engebrethsen, Erna & Dauzère-Pérès, Stéphane, 2019. "Transportation mode selection in inventory models: A literature review," European Journal of Operational Research, Elsevier, vol. 279(1), pages 1-25.
    11. Tyworth, John E., 2018. "A note on lead-time paradoxes and a tale of competing prescriptions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 109(C), pages 139-150.
    12. Bouchery, Yann & Woxenius, Johan & Fransoo, Jan C., 2020. "Identifying the market areas of port-centric logistics and hinterland intermodal transportation," European Journal of Operational Research, Elsevier, vol. 285(2), pages 599-611.
    13. 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.
    14. He, Xin & Xu, Xinwei & Shen, Yu, 2023. "How climate change affects enterprise inventory management —— From the perspective of regional traffic," Journal of Business Research, Elsevier, vol. 162(C).
    15. 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.
    16. Zhang, Liyunpeng & Zhuang, Yuhang & Ding, Yibing & Liu, Ziwei, 2023. "Infrastructure and poverty reduction: Assessing the dynamic impact of Chinese infrastructure investment in sub-Saharan Africa," Journal of Asian Economics, Elsevier, vol. 84(C).
    17. Ruth Banomyong, 2010. "Supply Chain Dynamics in Asia," Trade Working Papers 22879, East Asian Bureau of Economic Research.

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