Optimal lot-sizing and service level weighting in sequential multi-attribute global transportation service procurement

Xiang T.R. Kong, Zhan He, Kaize Yu and Pengyu Yan

European Journal of Operational Research, 2025, vol. 327, issue 3, 1052-1072

Abstract: The development of on-demand global transportation service procurement (oGTSP) through digital trading platforms has accelerated due to frequent fluctuations in transport capacity. In the oGTSP model, the exporter must consider logistics service quality and transport prices when sourcing global logistics services. To satisfy the continuous transport needs, procurement is conducted sequentially throughout multiple auction cycles. For a single auction, we constructed a service-level weight-scoring function and analysed the trading parties’ behavioural strategies to obtain an auction equilibrium strategy in a specific context. Then, we developed a multi-cycle sequential decision method based on a single-cycle equilibrium decision by forwarders that can dynamically adjust the auction lot size to help the exporter obtain optimal utility. Finally, based on the real case of a large electronic product exporter, the proposed approach was verified. The results demonstrated that exporters should pay more attention to the quality of service when choosing freight forwarders to improve the utility of transportation service procurement. The exporter can attract more forwarders to participate in auctions to obtain more capacity supply by increasing the weighting of service levels. Besides, the proposed auction system could effectively accommodate strategic forwarders with learning abilities. The exporter’s utility will significantly improve if the freight forwarders have learning ability. There is a marginal diminishing effect in that the benefits from additional participation of learning-oriented bidders are initially large but eventually stabilized. The strategic auction participation of learning-oriented freight forwarders smooths the capacity supply trend, reduces extreme fluctuations and makes multi-cycle predictions more accurate.

Keywords: Global transportation service procurement; Multi-attribute auction; Multi-cycle sequential decision model; Markov decision process; Reinforcement learning algorithm (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:327:y:2025:i:3:p:1052-1072

DOI: 10.1016/j.ejor.2025.05.037

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