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Efficient and truthful multi-attribute auctions for crowdsourced delivery

delete2021-10-01
delete21
PRE
AI
肖
肖 菲 (Fei Xiao)
王海军 封面图
王海军 (Haijun Wang) *
S
Shuojia Guo
关旭 封面图
关旭 (Xu Guan)
B
Baoshan Liu
DOI:10.1016/j.ijpe.2021.108233delete
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摘要

摘要

En 中文
Crowdsourced delivery is an emerging parcel delivery paradigm that leverages occasional couriers' excess capacities to transport goods. In a crowdsourced delivery system, couriers offer their excess trip capacities to requesters with packages of different weights and distinct valuations for the service. This paper studies the truthful and efficient multi-attribute auction design for the crowdsourced delivery. We develop a second-preferred-score and a Vickrey-Clarke-Groves score (VCG-score) auctions for both single-unit and multi-unit multi-attribute cases, where price and weight are jointly evaluated when assigning package delivery tasks. The proposed auctions lead to truthful private valuation revelation and social welfare maximization. Computational analyses show that our proposed multi-attribute auctions outperform the single-attribute auction and the fixed rate mechanism in maximizing social welfare.
Keyword:
Crowdsourced delivery
Multi-attribute auction
Mechanism design
Sharing economy
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期刊

International Journal of Production Economics 封面图
International Journal of Production Economics
IF:
10
论文数:
8.1K
被引数:
3.6W

机构

C
college of staten island (cuny)
学者数:
400
论文数: 293
被引数: 0
C
city university of new york (cuny) system
学者数:
1.6W
论文数: 1.5W
被引数: 26
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