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, we have a rather limited understanding of factors affecting lenders’ decision making in this context, which is characterized as high risk and prosocial in nature. In our research, drawing upon incentive theory of motivation and construal level theory (CLT), we theorize how interest rate and psychological distance caused by the borrower’s demographic attributes (i.e., geographic location and educational level) relative to those of the lender jointly affect the bidding value submitted by the lender. Using a rich data set from a popular online P2P lending platform in China, we apply multiple identification strategies and estimation methods to conduct the analysis. We find that interest rate is the driving factor for the lender’s bidding value on a loan listing and that such positive effects are strengthened by the geographic and educational distance between the lender and the borrower. In addition, geographic distance decreases the lender’s bidding value on a loan listing (i.e., home bias effect), whereas educational distance increases the bidding value (i.e., educational distance effect). Theoretical contributions and practical implications are discussed.