標題: P2P借貸之社群推薦機制
A Social Recommendation Mechanism for Peer-to-Peer Lending
作者: 萬駿飛
李永銘
Wan,Jun-Fei
Li,Yung-Ming
資訊管理研究所
關鍵字: P2P 借貸;資訊不對稱;社群推薦;社會資本;社群影響力;Peer-to-Peer lending;Information asymmetry;Social recommendation;Social Capital;Social influence
公開日期: 2017
摘要: P2P借貸(Peer-to-Peer lending)相較於傳統銀行,被認為更有利於借貸雙方,因而成為時下熱門的一種新型替代金融。但是,基於線上資訊不對稱原因,相比較潛在投資者,參與P2P投資的人並不多,另一邊,對於貸款人來說,通常大部分的募款時間都花費在最初階段。本文提出一種社群推薦機制,借助社會資本與社群計算,幫助貸款人在最初階段就能盡快尋找到合適的投資者,同時,借助社群影響力,吸引更多潛在投資者加入P2P借貸行為中。本文實驗利用模擬借貸過程,對推薦機制進行了多維度的評估,並最終顯示機制對貸款人的借款成功率有促進作用,而且,相比於現存平台,借助社群關係,投資人在單筆投資中願意借出更多的金額。
Compared with traditional bank, Peer-to-Peer(P2P) lending, as a hot topic recently, is claimed to benefit both borrowers and lenders. However, because of the problem of 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 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.
URI: http://etd.lib.nctu.edu.tw/cdrfb3/record/nctu/#GT070353437
http://hdl.handle.net/11536/140256
顯示於類別:畢業論文