Selecting green third party logistics providers for a loss-averse fourth party logistics provider in a multiattribute reverse auction

Xiaohu QIAN, Shu-Cherng FANG, Mingqiang YIN, Min Huang, Xin Stephen LI

Research output: Contribution to journalArticlespeer-review

15 Citations (Scopus)

Abstract

Existing winner determination models tend to overlook the sustainable attributes of third party logistics (3PL) providers. This paper investigates a novel green winner determination problem that has several features, including (i) the sustainable attributes with conflicting and interactive properties of potential 3PLs, and (ii) the loss-averse behavior with an internal reference point of a fourth party logistics (4PL) provider. For the attributes with a combination of crisp data, interval numbers and intuitionistic 2-tuple linguistic terms, we integrate the prospect theory (PT) and Choquet integral with the “benefits, opportunities, costs and risks (BOCR)” framework to propose a novel PTC-BOCR solution method. Numerical experiments are conducted to illustrate the effectiveness and applicability of PTC-BOCR by comparing it with some known methods. Comparison analysis indicates that PTC-BOCR is robust with respect to the variance of 3PLs’ attribute values, while behavioral parameter analysis reveals that the loss-averse behavior of the 4PL is intensified as the difference of 3PLs varies. Managerial insights are also drawn for green 3PLs to win the auction. This study is a significant extension of traditional decision-making methods, which could benefit the realization of a sustainable logistics system in a cost-effective way for 4PLs. Copyright © 2020 Published by Elsevier Inc.

Original languageEnglish
Pages (from-to)357-377
JournalInformation Sciences
Volume548
Early online dateSep 2020
DOIs
Publication statusPublished - Feb 2021

Citation

Qian, X., Fang, S.-C., Yin, M., Huang, M., & Li, X. (2021). Selecting green third party logistics providers for a loss-averse fourth party logistics provider in a multiattribute reverse auction. Information Sciences, 548, 357-377. doi: 10.1016/j.ins.2020.09.011

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