Efficient Multi-Attribute Multi-Unit Auctions for B2B E-Commerce Logistics

• 成果类型: Article
• 署名作者: Xu, Su Xiu; Huang, George Q.
• 署名单位: Jinan University; Jinan University; University of Hong Kong
• 刊物名称: PRODUCTION AND OPERATIONS MANAGEMENT
• ISSN/ISSBN: 1059-1478
• DOI: 10.1111/poms.12638
• 发表日期: 2017
• 页码: 292-304
• 关键词: E-commerce logistics problem (ELP); mechanism design; multi-attribute auctions; primal-dual algorithm; Allocative efficiency

摘要

This study is the first proposing allocatively efficient multi-attribute auctions for the procurement of multiple items. In the B2B e-commerce logistics problem (ELP), the e-commerce platform is the shipper generating a large number of online orders between product sellers and buyers, and third-party logistics (3PL) providers are carriers that can deliver these online orders. This study focuses on the ELP with multiple attributes (ELP-MA), which is generally the problem of matching the shipper's online orders and 3PL providers given that price and other attributes are jointly evaluated. We develop a one-sided Vickrey-Clarke-Groves (O-VCG) auction for the ELP-MA. The O-VCG auction leads to incentive compatibility (on the sell side), allocative efficiency, budget balance, and individual rationality. We next introduce the concept of universally unsatisfied set to construct a primal-dual algorithm, also called the primal-dual Vickrey (PDV) auction. We prove that the O-VCG auction can be viewed as a single-attribute multi-unit forward Vickrey (SA-MFV) auction. Both PDV and SA-MFV auctions realize VCG payments and truthful bidding for general valuations. This result reveals the underlying link not only between single-attribute and multi-attribute auctions, but between static and dynamic auctions in a multi-attribute setting.