The value of adaptive menu sizes in peer-to-peer platforms

被引：4
|
作者：
Karabulut, Ezgi [1 ]
Gholizadeh, Fatemeh [1 ]
Akhavan-Tabatabaei, Raha [1 ]
机构：
[1] Sabanci Univ, Univ Cad 27 Orta Mah Tuzla, Istanbul, Turkey
来源：
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES | 2022年 / 145卷
关键词：
Preference learning; Peer-to-peer platforms; Recommendation sets; RECOMMENDATION; MODEL;
D O I：
10.1016/j.trc.2022.103948
中图分类号：
U [交通运输];
学科分类号：
08 ; 0823 ;
摘要：
We consider a peer-to-peer logistics system, where the agents and the platform communicate in both directions in a multi-period setting. The goal of the platform is to select a subset of the requests to offer to each agent that would result in a maximum valued matching for the platform. The platform utilizes the agent's choice to learn about her preferences and improve the estimated decision mechanism of the agent. Through systematic experimentation, we first establish that at the earlier iterations and while the decision mechanism of the agent is not yet accurately estimated, a larger menu size could benefit the platform's overall gain better. However, after the estimates become more accurate through the learning process, a smaller menu size can further increase the overall benefits.
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页数：11
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