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How friendship networks work in online P2P lending markets

Author

Listed:
  • Siming Li
  • Zhangxi Lin
  • Jiaxian Qiu
  • Roozmehr Safi
  • Zhongyi Xiao

Abstract

Purpose - – The purpose of this paper is to study the effects of multidimensional friendship networks on economic outcomes in the domain of online people-to-people (P2P) lending markets. Design/methodology/approach - – The empirical analysis is based on the data set of transactions and friendship networks fromPPDai.commarket, the most prominent P2P lending market in China. A friendship hierarchy is proposed in this paper to conceptualize friendship network types. Furthermore, methodologies oft-test, logistic regression and ordinary least squares regression are implemented to measure the impact of multidimensional friendship network variables on the probability of successful funding, as well as the interest rates on funded loans. Findings - – The study demonstrates significant effects of structural, relational and cognitive friendship networks usingPPDai.comdata. The results indicate that structural friendship network measured in terms of the number of friendship ties is a significant factor of funding performance. Additionally, borrowers, who are involved in higher-quality friendship networks, are more likely to be funded and pay lower interest rates on funded loans. Also, the deeper the level of the relationship is in the friendship hierarchy, the more significant will be the effect of friendship on the final economic results. Furthermore, quality is more important than quantity in determining funding performance. Originality/value - – This paper is the first to study the effects of multidimensional friendship networks on economic outcome variables in the domain of online P2P lending, thus broadening the theory of multidimensional social capital, which can deepen our understanding about how social networks work and have significant implications practically and theoretically.

Suggested Citation

  • Siming Li & Zhangxi Lin & Jiaxian Qiu & Roozmehr Safi & Zhongyi Xiao, 2015. "How friendship networks work in online P2P lending markets," Nankai Business Review International, Emerald Group Publishing Limited, vol. 6(1), pages 42-67, March.
    • Handle: RePEc:eme:nbripp:v:6:y:2015:i:1:p:42-67
    DOI: 10.1108/NBRI-01-2014-0010
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    Citations

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    Cited by:

    1. Wu, Bao & Liu, Zijia & Gu, Qiuyang & Tsai, Fu-Sheng, 2023. "Underdog mentality, identity discrimination and access to peer-to-peer lending market: Exploring effects of digital authentication," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 83(C).
    2. Qun Chen & Ji-Wen Li & Jian-Guo Liu & Jing-Ti Han & Yun Shi & Xun-Hua Guo, 2021. "Borrower Learning Effects: Do Prior Experiences Promote Continuous Successes in Peer-to-Peer Lending?," Information Systems Frontiers, Springer, vol. 23(4), pages 963-986, August.
    3. Qun Chen & Ji-Wen Li & Jian-Guo Liu & Jing-Ti Han & Yun Shi & Xun-Hua Guo, 0. "Borrower Learning Effects: Do Prior Experiences Promote Continuous Successes in Peer-to-Peer Lending?," Information Systems Frontiers, Springer, vol. 0, pages 1-24.
    4. Kun Liang & Chen Zhang & Cuiqing Jiang, 2022. "Analyzing default risk among P2P platforms based on the LAS-STACK method by considering multidimensional signals under specific economic contexts," Electronic Commerce Research, Springer, vol. 22(1), pages 77-111, March.
    5. Xiong Xiong & Zhang Jin & Feng Xu & Jin Xi, 2016. "Review on Financial Innovations in Big Data Era," Journal of Systems Science and Information, De Gruyter, vol. 4(6), pages 489-504, December.
    6. Sulin Pang & Huili Xian & Rongzhou Li, 2022. "A default penalty model based on C2VP2C mode for internet financial platforms in Chinese market," Electronic Commerce Research, Springer, vol. 22(2), pages 485-511, June.
    7. Zhangxi Lin & Andrew B. Whinston & Shaokun Fan, 2015. "Harnessing Internet finance with innovative cyber credit management," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 1(1), pages 1-24, December.
    8. Beibei Niu & Jinzheng Ren & Ansa Zhao & Xiaotao Li, 2020. "Lender Trust on the P2P Lending: Analysis Based on Sentiment Analysis of Comment Text," Sustainability, MDPI, vol. 12(8), pages 1-14, April.

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