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Less-than-truckload Dynamic Pricing Model in Physical Internet

Author

Listed:
  • Bin Qiao

    (CGS i3 - Centre de Gestion Scientifique i3 - Mines Paris - PSL (École nationale supérieure des mines de Paris) - PSL - Université Paris Sciences et Lettres - I3 - Institut interdisciplinaire de l’innovation - CNRS - Centre National de la Recherche Scientifique)

  • Shenle Pan

    (CGS i3 - Centre de Gestion Scientifique i3 - Mines Paris - PSL (École nationale supérieure des mines de Paris) - PSL - Université Paris Sciences et Lettres - I3 - Institut interdisciplinaire de l’innovation - CNRS - Centre National de la Recherche Scientifique)

  • Eric Ballot

    (CGS i3 - Centre de Gestion Scientifique i3 - Mines Paris - PSL (École nationale supérieure des mines de Paris) - PSL - Université Paris Sciences et Lettres - I3 - Institut interdisciplinaire de l’innovation - CNRS - Centre National de la Recherche Scientifique)

Abstract

This paper investigates a decision-making problem consisting of less-than-truckload dynamic pricing (LTLDP) under Physical Internet (PI). PI can be seen as the interconnection of logistics networks via open PI-hubs, which can be considered as spot freight markets where LTL requests of different volume/destination continuously arrive over time for a short-stay. Carriers can bid for the requests by using short-term contract. This paper proposes a dynamic pricing model to optimise carrier's bid price to maximise his expected profits. Three influencing factors are investigated: requests quantity, carrier's capacity and cost. The results provide useful guidelines to carriers on pricing decisions in PI-hub.

Suggested Citation

  • Bin Qiao & Shenle Pan & Eric Ballot, 2016. "Less-than-truckload Dynamic Pricing Model in Physical Internet," Post-Print hal-01326416, HAL.
  • Handle: RePEc:hal:journl:hal-01326416
    Note: View the original document on HAL open archive server: https://minesparis-psl.hal.science/hal-01326416v1
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    References listed on IDEAS

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    Cited by:

    1. Lafkihi, Mariam & Pan, Shenle & Ballot, Eric, 2019. "Freight transportation service procurement: A literature review and future research opportunities in omnichannel E-commerce," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 125(C), pages 348-365.
    2. Feyza Gürbüz & İkbal Eski & Berrin Denizhan & Cihan Dağlı, 2019. "Prediction of damage parameters of a 3PL company via data mining and neural networks," Journal of Intelligent Manufacturing, Springer, vol. 30(3), pages 1437-1449, March.

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