Influencing Factors of Online P2P Lending Success Rate in China

Zhuopei Yang (), Yanmei Zhang () and Hengyue Jia
Additional contact information
Zhuopei Yang: Shanghai Nuclear Engineering Research and Design Institute
Yanmei Zhang: Central University of Finance and Economics
Hengyue Jia: Central University of Finance and Economics

Annals of Data Science, 2017, vol. 4, issue 2, No 7, 289-305

Abstract: Abstract The low success rate of lending is the main drawback of development of online P2P lending platforms in China. Based on the theory of social capital, this study analysed the influence factors of success rate of P2P lending platform in China, using social network method and multiple linear regression model. Soft information, such as bidding record, has been creatively employed to study the corresponding topics. Data used in this study comes from the largest online P2P lending platform in China. The results show that: compared with other influence factors, the bidding record has a more significant effect on the success rate, and the users depend more on the social capital; the bidding records reduce the asymmetry of information, and help increasing the success rate of lending and decreasing the cost of online P2P lending.

Keywords: Bidding record; Online P2P lending; Influencing factors; Success rate (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://link.springer.com/10.1007/s40745-017-0103-6 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:aodasc:v:4:y:2017:i:2:d:10.1007_s40745-017-0103-6

Ordering information: This journal article can be ordered from
https://www.springer ... gement/journal/40745

DOI: 10.1007/s40745-017-0103-6

Access Statistics for this article

Annals of Data Science is currently edited by Yong Shi

More articles in Annals of Data Science from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().