Order allocation of logistics service supply chain with fairness concern and demand updating: model analysis and empirical examination

Weihua Liu (), Shuqing Wang (), DongLei Zhu (), Di Wang () and Xinran Shen ()
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Weihua Liu: Tianjin University
Shuqing Wang: Tianjin University
DongLei Zhu: Tianjin University
Di Wang: Tianjin University
Xinran Shen: Tianjin University

Annals of Operations Research, 2018, vol. 268, issue 1, No 10, 177-213

Abstract: Abstract Regarding a two-echelon supply chain consisting of a logistics service integrator (LSI) and several functional logistics service providers (FLSPs), this paper establishes a two-stage order allocation model considering demand updating and the FLSPs’ fairness preferences. This model is a multi-objective programming model, whose goal is to maximize profits of the LSI and the total utility of FLSPs. The ideal point method is used to obtain the optimal solution. In the numerical example, the impacts of FLSPs’ behavioral parameters and demand update parameters on the order allocation in the social services network are discussed. Besides, multi-methodological method is used to verify the theoretical perspectives through an empirical study of Tianjin SND Logistics Company. Our study obtains a few important conclusions. For example, when demand of the second stage is updated, there is an optimal updating time maximizing the supply chain performance. Increased demand of the second stage results in greater supply chain performance. When the demand during the second stage decreases, the bigger the difference of the fairness preference coefficients among FLSPs, the greater the LSI’s profits and the lower the FLSPs’ total utility will be. However, the difference of the fairness preference coefficients among FLSPs has little influence on the LSI’s profits and total utility of the FLSPs, when the demand during the second stage increases.

Keywords: Social network; Logistics service supply chain; Order allocation; Fairness preference; Demand updating; Multi-objective programming (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (13)

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DOI: 10.1007/s10479-017-2482-7

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