In the online microloan market, the ability to evaluate the credit risk of borrowers is key to business success. Based on the general strain theory, this study proposes a contextualized two-stage model with stress factors, negative affects and constraint factors to explain the psychological mechanism of borrowers' default behaviors.
An online survey is conducted to test the hypotheses. We collect and analyze 713 valid responses through a structural equation model.
(1) Economic and social strains experienced by borrowers can cause four types of negative affects: life dissatisfaction, perceived unfairness, inferiority feeling and loneliness; (2) Both strains and negative affects have a considerable effect on borrowers' default intention; (3) Moral norm plays a negative moderating role in the relationship between strains, negative affects and default behavior, whereas perceived deterrence shows a strong main effect.
(1) This study introduces the GST from sociology and criminology, and contextualizes it in the microloan context to explain default behavior; (2) This study provides a comprehensive and staged psychological mechanism to explain deviant behavior; (3) This study bears critical implications for the current practice in credit assessment and default prevention.
This work was supported by National Natural Science Foundation of China (grant numbers: 71802108, 91546104, 71872050, and 71531006); Research Funds for Young Scholars in School of Economics and Management, Nanjing University of Science and Technology (grant number: JGQN1802); Program for Professor of Special Appointment (Eastern Scholar) at Shanghai Institutions of Higher Learning. The author Xiaolun Wang is also supported by China Scholarship Council (No. 201906845029) as a visiting scholar in Humboldt University of Berlin. The authors make equal contribution to this paper. This paper is developed from our research-in-progress manuscript presented in PACIS 2016 as “Psychosocial Factors Lead to Delinquency Intention on Online Peer-To-Peer Lending Platform: A Survey Evidence”, proceedings of the 20th Pacific Asia Conference on Information Systems (https://aisel.aisnet.org/cgi/viewcontent.cgi?article=1386&context=pacis2016).
Wang, X., Xu, Y.C., Lu, T. and Zhang, C. (2020), "Why do borrowers default on online loans? An inquiry of their psychology mechanism", Internet Research, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/INTR-05-2019-0183Download as .RIS
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