Truthful multi-attribute multi-unit double auctions for B2B e-commerce logistics service transactions

Hao Yu, Min Huang, Xiuli Chao and Xiaohang Yue

Transportation Research Part E: Logistics and Transportation Review, 2022, vol. 164, issue C

Abstract: This study investigates truthful multi-attribute multi-unit double auction mechanism design problem for B2B e-commerce logistics service transactions (LSTs). The optimization problem of the auctioneer is modeled as an integer program to maximize social welfare where the utility of shippers is related to their monetary profits and non-price attributes of corresponding carriers. To handle the information asymmetry of price and non-price attributes, a Multi-Attribute Multi-unit Trade Reduction (MA-MTR) mechanism is proposed to resolve the problem in a decentralized setting. A family of Enhanced Multi-Attribute Multi-unit Trade Reduction (E-MA-MTR) mechanisms is then designed to achieve fair allocation and capture the auctioneer’s tradeoff between various operational objectives. A family of Improved Multi-Attribute Multi-unit Trade Reduction (I-MA-MTR) auction mechanisms with elaborate efficiency-loss-alleviation strategies is further proposed to ameliorate efficiency performance. Theoretical analysis manifests that all above mechanisms satisfy incentive compatibility (IC), balanced budget (BB), individual rationality (IR) and asymptotical efficiency (AsE). Numerical results further demonstrate the superiority of the MA-MTR mechanism over its single-attribute counterpart, verify the effectiveness of relevant strategies in the E-MA-MTR and I-MA-MTR mechanisms and shed light on the choice of alternative mechanisms.

Keywords: Logistics service transactions; Multi-attribute auction; Mechanism design; Truthful double auction; Incentive compatibility (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (4)

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DOI: 10.1016/j.tre.2022.102814

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