TY - JOUR
T1 - An efficient multi-attribute multi-item auction mechanism with ex-ante and ex-post satisfaction for 4PL transportation service procurement
AU - Yuan, Na
AU - Qian, Xiaohu
AU - Huang, Min
AU - Liang, Haiming
AU - Ip, Andrew Wai Hung
AU - Yung, Kai Leung
N1 - Funding Information:
This work is supported by the National Key R&D Program of China Grant No. 2021YFB3300900; the NSFC Key Supported Project of the Major Research Plan Grant No. 92267206; the NSFC Grant No. 62032013; the Fundamental Research Funds for State Key Laboratory of Synthetical Automation for Process Industries Grant No. 2013ZCX11; the 111 Project 2.0 (No. B08015).
Publisher Copyright:
© 2023 by the authors; licensee Growing Science, Canada.
PY - 2023/6/1
Y1 - 2023/6/1
N2 - Reverse auction is an effective tool for a 4PL to purchase transportation services. This paper investigated a new transportation services procurement problem for 4PL, which involves three features: the 4PL’s loss-averse behavior, price and non-price attributes, and multiple transportation requests. An efficient multi-attribute multi-item reverse auction mechanism considering the 4PL ex-ante and ex-post satisfaction (EES-MMRA) is proposed to purchase transportation services for the 4PL. In the EES-MMRA, integrating the allocation rule with the 4PL ex-ante satisfaction, a 0-1 programming model is constructed to determine winning 3PLs and obtain efficient allocations. Then, a payment rule considering the 4PL ex-post satisfaction is established to ensure truthful bidding of 3PLs. And we discuss some desirable properties (e.g., incentive compatibility, individual rationality, efficiency, and budget balance properties) to justify the EES-MMRA mechanism, subsequently. Next, several numerical experiments are conducted to demonstrate the effectiveness and applicability of the EES-MMRA mechanism. Furthermore, sensitivity analysis presents the influences of the weights of the non-price attributes, risk attitude coefficients, and loss aversion coefficients. Finally, we conduct comparison analysis to show the advantages of the EES-MMRA mechanism over the known Vickrey–Clark–Groves (P-VCG) mechanism.
AB - Reverse auction is an effective tool for a 4PL to purchase transportation services. This paper investigated a new transportation services procurement problem for 4PL, which involves three features: the 4PL’s loss-averse behavior, price and non-price attributes, and multiple transportation requests. An efficient multi-attribute multi-item reverse auction mechanism considering the 4PL ex-ante and ex-post satisfaction (EES-MMRA) is proposed to purchase transportation services for the 4PL. In the EES-MMRA, integrating the allocation rule with the 4PL ex-ante satisfaction, a 0-1 programming model is constructed to determine winning 3PLs and obtain efficient allocations. Then, a payment rule considering the 4PL ex-post satisfaction is established to ensure truthful bidding of 3PLs. And we discuss some desirable properties (e.g., incentive compatibility, individual rationality, efficiency, and budget balance properties) to justify the EES-MMRA mechanism, subsequently. Next, several numerical experiments are conducted to demonstrate the effectiveness and applicability of the EES-MMRA mechanism. Furthermore, sensitivity analysis presents the influences of the weights of the non-price attributes, risk attitude coefficients, and loss aversion coefficients. Finally, we conduct comparison analysis to show the advantages of the EES-MMRA mechanism over the known Vickrey–Clark–Groves (P-VCG) mechanism.
KW - auction
KW - Efficient multi-attribute reverse
KW - Ex-ante and ex-post satisfaction
KW - Mechanism design
KW - procurement
KW - Transportation service
UR - http://www.scopus.com/inward/record.url?scp=85163813520&partnerID=8YFLogxK
U2 - 10.5267/j.ijiec.2023.3.001
DO - 10.5267/j.ijiec.2023.3.001
M3 - Journal article
AN - SCOPUS:85163813520
SN - 1923-2926
VL - 14
SP - 571
EP - 588
JO - International Journal of Industrial Engineering Computations
JF - International Journal of Industrial Engineering Computations
IS - 3
ER -