Investor Platform Choice: Herding, Platform Attributes, and Regulations

Journal of Management Information Systems, 35(1) pp. 86-116, 2018

34 Pages Posted: 6 Oct 2016 Last revised: 12 Nov 2021

See all articles by Yang Jiang

Yang Jiang

Nanjing University - School of Business

Yi-Chun (Chad) Ho

George Washington University - School of Business

Xiangbin Yan

Harbin Institute of Technology - School of Management

Yong Tan

University of Washington - Michael G. Foster School of Business

Date Written: 2018

Abstract

Online peer-to-peer (P2P) lending, one of the most successful technology-enabled initiatives in the fintech revolution, has drastically changed the way individual investors and borrowers meet and transact. While prior research has found herding among investors at the listing level, such social behavior has been underexplored at a macro, platform level. In this study, we attempt to fill this gap by examining whether subsequent investors follow their predecessors’ actions when choosing which platform to invest, and if so, how various platform attributes and regulations moderate herding behavior. We collected a novel dataset from leading platforms in a large P2P lending market. Our baseline analysis reveals that herding exists at the platform level. Using a multilevel model, we further identify several interesting moderators: the investor’s herding behavior is accentuated by platforms’ market share and the cumulative amount funded, but attenuated, by their time in operation. Finally, we find that government regulatory events dampen the magnitude of the herding effect, suggesting that more information disclosure and stricter operation standards reduce the value of observational learning. The results from our analysis provide implications for P2P lending investors, platform designers, and policy makers.

Keywords: fintech, peer-to-peer lending, crowdfunding, herding, multilevel model, regulations

Suggested Citation

Jiang, Yang and Ho, Yi-Chun (Chad) and Yan, Xiangbin and Tan, Yong, Investor Platform Choice: Herding, Platform Attributes, and Regulations (2018). Journal of Management Information Systems, 35(1) pp. 86-116, 2018, Available at SSRN: https://ssrn.com/abstract=2847318 or http://dx.doi.org/10.2139/ssrn.2847318

Yang Jiang

Nanjing University - School of Business ( email )

Nanjing, Jiangsu 210093
China

Yi-Chun (Chad) Ho (Contact Author)

George Washington University - School of Business ( email )

Washington, DC 20052
United States

HOME PAGE: http://business.gwu.edu/chad-ho

Xiangbin Yan

Harbin Institute of Technology - School of Management ( email )

Heilongjiang
China

Yong Tan

University of Washington - Michael G. Foster School of Business ( email )

Box 353226
Seattle, WA 98195-3226
United States

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