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Incentive mechanism to prevent moral hazard in online supply chain finance

Author

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  • Qiang Lin

    (Tianjin University)

  • Ying Peng

    (Tianjin University)

Abstract

With e-commerce developing rapidly, banks have begun to cooperate with online platform operators to finance small and medium-sized enterprises (SMEs). However, this process engenders its own unique financial risks. This study highlights and investigates the risks in a four-party supply chain that include a third-party logistics provider, a bank, a B2B platform operator, and SMEs. In an asymmetric information setting, the collusion mechanisms in this four-party online supply chain are also explored. Subsequently, a two-part incentive contract is designed that can reduce the moral hazard faced by the banks while addressing the trade-off between the payments to the platform operator for better credit rating information and the payments to the third-party logistics provider for supervising collateral storage. For further confirmation, a numerical analysis is presented. The results indicate that based on a suitable capital coefficient, the two-part incentive contract may prevent moral hazard in online supply chains. Furthermore, when the line of credit is high, the bank must increase the incentives for the B2B platform operator to avoid default risk and decrease the incentives for 3PL.

Suggested Citation

  • Qiang Lin & Ying Peng, 2021. "Incentive mechanism to prevent moral hazard in online supply chain finance," Electronic Commerce Research, Springer, vol. 21(2), pages 571-598, June.
    • Handle: RePEc:spr:elcore:v:21:y:2021:i:2:d:10.1007_s10660-019-09385-0
    DOI: 10.1007/s10660-019-09385-0
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    References listed on IDEAS

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    1. Heng, Michael S.H., 2001. "Implications of e-commerce for banking and finance," Serie Research Memoranda 0006, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
    2. repec:bla:ecnote:v:32:y:2003:i:2:p:243-282 is not listed on IDEAS
    3. Ohlson, Ja, 1980. "Financial Ratios And The Probabilistic Prediction Of Bankruptcy," Journal of Accounting Research, John Wiley & Sons, Ltd., vol. 18(1), pages 109-131.
    4. Baliga, Sandeep & Sjostrom, Tomas, 1998. "Decentralization and Collusion," Journal of Economic Theory, Elsevier, vol. 83(2), pages 196-232, December.
    5. Romero, Isidoro & Tejada, Pilar, 2011. "A multi-level approach to the study of production chains in the tourism sector," Tourism Management, Elsevier, vol. 32(2), pages 297-306.
    6. Holmstrom, Bengt & Milgrom, Paul, 1994. "The Firm as an Incentive System," American Economic Review, American Economic Association, vol. 84(4), pages 972-991, September.
    7. Esa Jokivuolle & Samu Peura, 2003. "Incorporating Collateral Value Uncertainty in Loss Given Default Estimates and Loan‐to‐value Ratios," European Financial Management, European Financial Management Association, vol. 9(3), pages 299-314, September.
    8. Meyer, Paul A & Pifer, Howard W, 1970. "Prediction of Bank Failures," Journal of Finance, American Finance Association, vol. 25(4), pages 853-868, September.
    9. Tirole, Jean, 1986. "Hierarchies and Bureaucracies: On the Role of Collusion in Organizations," The Journal of Law, Economics, and Organization, Oxford University Press, vol. 2(2), pages 181-214, Fall.
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    1. Zhang, Lu & Cui, Li & Chen, Lujie & Dai, Jing & Jin, Ziyi & Wu, Hao, 2023. "A hybrid approach to explore the critical criteria of online supply chain finance to improve supply chain performance," International Journal of Production Economics, Elsevier, vol. 255(C).
    2. Saumyaranjan Sahoo & Satish Kumar & Uthayasankar Sivarajah & Weng Marc Lim & J. Christopher Westland & Ashwani Kumar, 2024. "Blockchain for sustainable supply chain management: trends and ways forward," Electronic Commerce Research, Springer, vol. 24(3), pages 1563-1618, September.
    3. Jingwei Li & Shouwei Li & Yonghong Zhang & Xiaoyu Tang, 2023. "Evolutionary game analysis of rent seeking in inventory financing based on blockchain technology," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 44(8), pages 4278-4294, December.
    4. Han, Hongjun & Song, Shu & Tian, Grace (Li), 2025. "Can supply chain finance enhance corporate solvency? — The impact mechanism of corporate litigation," International Review of Economics & Finance, Elsevier, vol. 103(C).
    5. Qiang Yan & Wenyan Zhuo & Chongcong Yu, 2025. "Online retailer’s optimal financing strategy in an online marketplace," Electronic Commerce Research, Springer, vol. 25(1), pages 125-154, February.
    6. M. Sivarama Anandha Krishnan & Rahul R. Marathe, 2025. "Contracting and competing on a food delivery platform," Electronic Commerce Research, Springer, vol. 25(5), pages 3663-3688, October.

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