Judging online peer-to-peer lending behavior: A comparison of first-time and repeated borrowing requests

The past decade has witnessed a growing number of business models that facilitate economic exchanges between individuals with limited institutional mediation. One of the important innovative business models is online peer-to-peer lending, which has received wide attention from government, industry, and researchers. Using the signaling theory, we compare the effects of various signals on the likelihood of successful funding in three models (i.e., first-time borrowing, repeated borrowing without prior lending, and repeated borrowing with prior lending). Using data collected from PPDAI.com, we verify the three proposed models by employing logistic regression. Results and implications are analyzed and discussed. (C) 2016 Elsevier B.V. All rights reserved.