Huang, Jin (2020) Essays on Peer to Peer Lending. PhD thesis, University of Essex.
Huang, Jin (2020) Essays on Peer to Peer Lending. PhD thesis, University of Essex.
Huang, Jin (2020) Essays on Peer to Peer Lending. PhD thesis, University of Essex.
Abstract
The Peer-to-Peer (P2P) lending model has become increasingly popular in China in recent years. In 2012, there are only 298 P2P platforms operating in China and loan volume is 22.9 billion RMB while in the first half of 2018, there are 1881 P2P platforms and trading volume has reached 7.33 trillion RMB. Although both number of platforms and transaction volume have increased significantly, severe asymmetric information still discourages participants. This doctoral thesis uses three empirical chapters to investigate the P2P lending market in China. Drawing on Message framing and signaling theory, we first examines the extent to which message framing is associated with funding outcomes receive in the context of P2P lending and whether positive message framing reinforces the positive impact of credit ratings on funding outcomes. Using a Heckman two stage model, we find that the use of positively framed messages is positively associated with positive funding outcomes. Besides, positive message framing enhances the positive impact of the credit ratings (an example of costly signals) on funding outcomes. The results contribute to the literature on the effectiveness of cheap signals in the context of Internet-based interactions while highlighting complementarities between different types of signals in P2P lending. We then investigate the role of psychological distancing and language intensity in P2P funding performance. We bridge the P2P lending literature and psycholinguistics literature and set out to explain how psychological distancing manifested by linguistic styles can influence lenders’ decision on P2P funding campaign. We argue find that linguistic styles related to psychological distancing have a negative impact onare negatively related to P2P funding success. Moreover, the language intensity tends to strengthen the negative relationship between psychological distancing and funding success. Our empirical results provide general support for the argument. This finding is consistent with psycholinguistics literature which suggests that psychological distancing is associated with negative interpersonal outcome (Simmons et al, 2005; Revenstorf et al, 1984). Specifically, the number of “you” and the number of negations used in borrowers’ description are negatively related to the willingness of the lender to support the funding campaign. The intensive language negatively strengths the relationship between the funding performance and number of “you” but does not apply to number of negations. Lastly, we investigate the funding performance of the financial excluded borrower in a large P2P lending platform. The association of financial technology (fintech) and financial exclusion has attracted attention since rapid growth of fintech innovation. Using loan-level data from a lending Chinese P2P company, we find there is a negative indirect effect of financial exclusion on funding success through credit score. In a moderated mediation analysis, we also find new business model such as offline authentication and education qualification positively moderates the linkage between the financial excluded and credit score and therefore negative indirect effect of financial exclusion on funding success is overturned when the excluded borrower has conducted offline authentication and obtained higher education qualification. In the end, we examine the determinants of offline authentication decision. We find the borrowers in a city with better financial infrastructure are more willing to conduct authentication. However, the financial excluded borrowers are less likely to conduct offline authentication.
Item Type: | Thesis (PhD) |
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Subjects: | H Social Sciences > HF Commerce |
Divisions: | Faculty of Social Sciences > Essex Business School > Strategy, Operations and Entrepreneurship |
Depositing User: | Jin Huang |
Date Deposited: | 08 Mar 2021 12:05 |
Last Modified: | 08 Mar 2021 12:05 |
URI: | http://repository.essex.ac.uk/id/eprint/29960 |
Available files
Filename: PhD thesis submission.pdf