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Exploring the critical factors influencing online lending intentions

Author

Listed:
  • Peng Wang

    (Southwestern University of Finance and Economics)

  • Haichao Zheng

    (Southwestern University of Finance and Economics)

  • Dongyu Chen

    (Soochow University)

  • Liangchao Ding

    (Soochow University)

Abstract

Background Online lending (P2P lending) is a type of internet finance mainly used to meet the financial needs of small and medium-sized enterprises and groups of individuals. It is a supplement to the traditional financial system. Method This paper uses PPDai.com—the most influential online lending platform in China—as a research object to study the leading factors that affect lenders’ loan trust and perception of information asymmetry. It also studies the impacts of these factors on lending intention. Results The results of this study show that the lending intention is mainly influenced by trust; perceived information asymmetry will affect trust, but it will not have a direct impact on lending intention. Trust is significantly affected by the borrowers’ reputation and information integrity. Information asymmetry has various causes, including structural assurance and legitimacy. This perception of information asymmetry significantly prevents the further development of online P2P lending. Conclusion The findings in this research imply that there are profound differences between online lending and online purchasing, thus the results obtained in the traditional e-commerce market cannot be applied in the field of online lending without verification.

Suggested Citation

  • Peng Wang & Haichao Zheng & Dongyu Chen & Liangchao Ding, 2015. "Exploring the critical factors influencing online lending intentions," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 1(1), pages 1-11, December.
    • Handle: RePEc:spr:fininn:v:1:y:2015:i:1:d:10.1186_s40854-015-0010-9
    DOI: 10.1186/s40854-015-0010-9
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    References listed on IDEAS

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    1. Herzenstein, Michal & Dholakia, Utpal M. & Andrews, Rick L., 2011. "Strategic Herding Behavior in Peer-to-Peer Loan Auctions," Journal of Interactive Marketing, Elsevier, vol. 25(1), pages 27-36.
    2. Paul A. Pavlou & David Gefen, 2004. "Building Effective Online Marketplaces with Institution-Based Trust," Information Systems Research, INFORMS, vol. 15(1), pages 37-59, March.
    3. Seth Freedman & Ginger Zhe Jin, 2008. "Do Social Networks Solve Information Problems for Peer-to-Peer Lending? Evidence from Prosper.com," Working Papers 08-43, NET Institute.
    4. Mingfeng Lin & Nagpurnanand R. Prabhala & Siva Viswanathan, 2013. "Judging Borrowers by the Company They Keep: Friendship Networks and Information Asymmetry in Online Peer-to-Peer Lending," Management Science, INFORMS, vol. 59(1), pages 17-35, August.
    5. Juanjuan Zhang & Peng Liu, 2012. "Rational Herding in Microloan Markets," Management Science, INFORMS, vol. 58(5), pages 892-912, May.
    6. Jefferson Duarte & Stephan Siegel & Lance Young, 2012. "Trust and Credit: The Role of Appearance in Peer-to-peer Lending," The Review of Financial Studies, Society for Financial Studies, vol. 25(8), pages 2455-2484.
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    Cited by:

    1. Mohammad Tariqul Islam Khan & Gan Han Yee & Gerald Goh Guan Gan, 2023. "Antecedents of Intention to Use Online Peer-to-Peer Platform in Malaysia," Vision, , vol. 27(5), pages 680-694, November.

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