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Building investor trust in the P2P lending platform with a focus on Chinese P2P lending platforms

Author

Listed:
  • Yuwei Yan

    (Huazhong University of Science and Technology
    Taishan University)

  • Zhihan Lv

    (Chinese Academy of Science)

  • Bin Hu

    (Huazhong University of Science and Technology)

Abstract

Despite the rapid development of peer-to-peer (P2P) lending in the world, massive Chinese P2P platforms have failed due to moral risk and liquidity risk, which decreased investors’ confidence in P2P lending. A major question facing the future growth and development of P2P platforms is how to best build investors’ trust. This study was based on the elaboration likelihood model and examines how to persuade investors to develop initial trust in P2P platform. The empirical analysis data were collected from 70 Chinese P2P platforms. The multiple linear regression results support central route variables: the financial and credit status of P2P platforms are key elements in building the trust of investors and impacting their decisions. The subordinate route variables including social capital, risk management, and operating duration provide the necessary support to increase the number of platform investors. The relationship between the average interest rate and number of investors is not linear but exhibits an inverted U-shaped curve. The disclosure of information by the borrowers does not significantly affect the number of platform investors. These findings are an important complement to existing research and will facilitate future development efforts for P2P lending and the rational investments of investors.

Suggested Citation

  • Yuwei Yan & Zhihan Lv & Bin Hu, 2018. "Building investor trust in the P2P lending platform with a focus on Chinese P2P lending platforms," Electronic Commerce Research, Springer, vol. 18(2), pages 203-224, June.
    • Handle: RePEc:spr:elcore:v:18:y:2018:i:2:d:10.1007_s10660-017-9255-x
    DOI: 10.1007/s10660-017-9255-x
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    Cited by:

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    3. Wang, Qi & Xiong, Xiong & Zheng, Zunxin, 2021. "Platform Characteristics and Online Peer-to-Peer Lending: Evidence from China," Finance Research Letters, Elsevier, vol. 38(C).
    4. Carlos Sanchis-Pedregosa & Emma Berenguer & Gema Albort-Morant & Jorge Anton Sanz, 2020. "Guaranteed Crowdlending Loans: A Tool for Entrepreneurial Finance Ecosystem Sustainability," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 22(55), pages 775-775, August.
    5. Arif Perdana & Pearpilai Jutasompakorn & Sunghun Chung, 2023. "Shaping crowdlending investors’ trust: Technological, social, and economic exchange perspectives," Electronic Markets, Springer;IIM University of St. Gallen, vol. 33(1), pages 1-17, December.
    6. Na Sun & Liangrong Song & Yan Sun, 2021. "Fuze Effect: A Landmine in the Way of Sustainable Development of FinTech—The Lessons from the Peer-To-Peer Risk Outbreak," Sustainability, MDPI, vol. 13(4), pages 1-21, February.
    7. Xueru Chen & Xiaoji Hu & Shenglin Ben, 2021. "How do reputation, structure design and FinTech ecosystem affect the net cash inflow of P2P lending platforms? Evidence from China," Electronic Commerce Research, Springer, vol. 21(4), pages 1055-1082, December.
    8. Galit Klein & Zeev Shtudiner & Moti Zwilling, 2023. "Why do peer-to-peer (P2P) lending platforms fail? The gap between P2P lenders' preferences and the platforms’ intentions," Electronic Commerce Research, Springer, vol. 23(2), pages 709-738, June.
    9. Satish Kumar & Weng Marc Lim & Nitesh Pandey & J. Christopher Westland, 2021. "20 years of Electronic Commerce Research," Electronic Commerce Research, Springer, vol. 21(1), pages 1-40, March.
    10. Ji-Wen Li & Qinghui Cui & Jia-Jia Zhang, 2021. "Examining failure learning in online lending: Complete failure vs. incomplete failure," PLOS ONE, Public Library of Science, vol. 16(11), pages 1-17, November.
    11. Ying Liu & Rui Wang & Jin Qin, 2021. "CEO influence on P2P platform survival: Education and experience do matter!," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 42(3), pages 622-634, April.
    12. Jen-Yin Yeh & Hsin-Yu Chiu & Jhih-Huei Huang, 2023. "Predicting Failure of P2P Lending Platforms through Machine Learning: The Case in China," Papers 2311.14577, arXiv.org.

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