| Autor: |
Ting-Kai Hwang, Yung-Ming Li, Jun-Fei Wan |
| Předmět: |
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| Zdroj: |
Proceedings of the Americas Conference on Information Systems (AMCIS); 2018, p1-10, 10p |
| Abstrakt: |
Compared with traditional bank, Peer-to-Peer (P2P) lending is claimed to benefit both borrowers and lenders. However, because of the information asymmetry online, much fewer investors dare to use this new alternative finance comparing to the potential market. Moreover, for borrowers, they always spend much more time to wait for the bidders during the initial phase than the other phases. This research has proposed a social recommendation mechanism to help borrowers to find suitable lenders based on the theory of social capital and techniques of social computing and to attract more potential lenders to join in the P2P lending utilizing the theory of social influence. An experiment simulating the process of P2P lending has been executed in this paper. With comparisons in multiple dimensions, it shows our proposed mechanism can effectively improve the bidding rate for borrowers and the lenders are willing to lend out more money in each bid when they have social relationships with borrowers. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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