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Determination of freight rates under stochastic demand and freight consolidation savings

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  • Christos Zikopoulos

Abstract

Following the trend for increased agility, flexibility, responsiveness and customer support of the modern supply chains, latest business practice indicates a preference to smaller transportation quantities as the percentage of truckload shipments is declining. Therefore, transportation rates determination that takes into account freight consolidation becomes more important for firms and logistics managers. We present a decision process for the configuration of a transportation pricing scheme, which ensures that total transportation charges to customers are equal in expectation to transportation expense of the shipper. It also succeeds in returning to the customers the savings in transportation cost because of freight consolidation in a fair manner, keeping its development and implementation quite simple. The proposed decision process consists of two steps, one dealing with the average, long-term transportation expenses estimation, and a second dedicated to the evaluation of the pricing scheme parameters. Our work provides a novel, accurate yet relatively simple method for addressing the issue of transportation cost accounting and pricing when demand for outbound transportation services is stochastic and there are opportunities to obtain savings because of freight consolidation. An interesting feature is that it combines some popular tools for transportation and distribution planning under a relatively new context.

Suggested Citation

  • Christos Zikopoulos, 2019. "Determination of freight rates under stochastic demand and freight consolidation savings," International Journal of Production Research, Taylor & Francis Journals, vol. 57(17), pages 5556-5573, September.
  • Handle: RePEc:taf:tprsxx:v:57:y:2019:i:17:p:5556-5573
    DOI: 10.1080/00207543.2018.1552033
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    Cited by:

    1. Yu Zhang & Nan Liu, 2021. "Optimal Internet of Things Technology Adoption Decisions and Pricing Strategies for High-Traceability Logistics Services," Sustainability, MDPI, vol. 13(19), pages 1-33, September.
    2. Breno Tostes de Gomes Garcia & Diana Mery Messias Lopes & Ilton Curty Leal Junior & José Carlos Cesar Amorim & Marcelino Aurélio Vieira da Silva & Vanessa de Almeida Guimarães, 2019. "Analysis of the Performance of Transporting Soybeans from Mato Grosso for Export: A Case Study of the Tapajós-Teles Pires Waterway," Sustainability, MDPI, vol. 11(21), pages 1-26, November.
    3. Zichong Lyu & Dirk Pons & Yilei Zhang & Zuzhen Ji, 2022. "Minimum Viable Model (MVM) Methodology for Integration of Agile Methods into Operational Simulation of Logistics," Logistics, MDPI, vol. 6(2), pages 1-28, June.

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