Understanding Lenders’ Investment Behavior in Online Peer-to-Peer Lending: A Construal Level Theory Perspective

Online peer-to-peer lending (i.e., P2P lending) has grown rapidly in recent years and is a new source of fixed income for investors. However, there is limited understanding of factors affecting individual lenders’ decision making in this context, which is characterized as highly risky. Drawing on construal level theory, we theorize how bidding amounts lenders submit are affected by interest rates and psychological distance caused by the borrower’s demographic attributes (i.e., geographic location, age, educational degree, and marital status) relative to those of the lender. Specifically, we study how psychological distance directly influences and shapes the effects of the duality of interest rates (i.e., as rates of return and as signals of potential risk) on bidding amounts. Using a rich data set from a popular Chinese online P2P lending platform, we apply multiple identification strategies and estimation methods to conduct our analyses. We find that geographic distance decreases the lenders’ bidding amounts (i.e., home bias effect ), whereas social distance increases the bidding amounts (i.e., social distance effect ). In addition, the positive effects of interest rates on bidding amounts are strengthened by the geographic and social distance between the lender and the borrower. Furthermore, we conduct four controlled experiments to explore the causality and mechanisms behind these relationships. Theoretical contributions and practical implications are discussed.