Human-Robot Interaction: When Investors Adjust the Usage of Robo-Advisors in Peer-to-Peer Lending

被引:45
|
作者
Ge, Ruyi [1 ]
Zheng, Zhiqiang [2 ]
Tian, Xuan [3 ]
Liao, Li [3 ]
机构
[1] Shanghai Business Sch, Dept Elect Commerce, Shanghai 200235, Peoples R China
[2] Univ Texas Dallas, Jindal Sch Management, Richardson, TX 75080 USA
[3] Tsinghua Univ, PBC Sch Finance, Beijing 100083, Peoples R China
基金
中国国家自然科学基金;
关键词
robo-advisor; human-in-the-loop; peer-to-peer lending; augmented intelligence; DISTRIBUTION CHANNELS; INFORMATION; ALGORITHMS; JUDGMENT; ADOPTION; SYSTEMS; TRUST;
D O I
10.1287/isre.2021.1009
中图分类号
G25 [图书馆学、图书馆事业]; G35 [情报学、情报工作];
学科分类号
1205 ; 120501 ;
摘要
We study the human-robot interaction of financial-advising services in peer-to peer lending (P2P). Many crowdfunding platforms have started using robo-advisors to help lenders augment their intelligence in P2P loan investments. Collaborating with one of the leading P2P companies, we examine how investors use robo-advisors and how the human adjustment of robo-advisor usage affects investment performance. Our analyses show that, somewhat surprisingly, investors who need more help from robo-advisors-that is, those encountered more defaults in their manual investing-are less likely to adopt such services. Investors tend to adjust their usage of the service in reaction to recent robo-advisor performance. However, interestingly, these human-in-the-loop interferences often lead to inferior performance.
引用
收藏
页码:774 / 785
页数:13
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