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Coordinating Supply Chain Financing for E-commerce Companies Through a Loan Contract

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Listed:
  • Jinjin Zhang
  • Xin Li
  • Yong-Hong Kuo
  • Yan Chen

Abstract

This paper considers an online retailer and his or her manufacturer, both facing financial constraints and wishing to get loans from their e-commerce platform-backed finance company. Based on shared transaction data and monitored sales accounts, a tripartite loan contract is proposed to coordinate three parties’ actions in this supply chain financing problem. We prove that the proposed loan contract aligns the decentralized decision-makings of each party and duplicates the optimal channel performance under a fully integrated decision-making framework. A case study is then conducted to illustrate the performance of the proposed loan contract. The result shows that the proposed loan contract outperforms wholesale-price contracts, where coordination does not take place, and buyback contracts, where coordination happens between the retailer and the manufacturer only. Furthermore, a sensitivity analysis reveals that profit allocations among the lender, the retailer, and the manufacturer resulted from the proposed loan contract are more balanced when the cost-to-retail ratio or risk premium is high.

Suggested Citation

  • Jinjin Zhang & Xin Li & Yong-Hong Kuo & Yan Chen, 2021. "Coordinating Supply Chain Financing for E-commerce Companies Through a Loan Contract," SAGE Open, , vol. 11(4), pages 21582440211, December.
    • Handle: RePEc:sae:sagope:v:11:y:2021:i:4:p:21582440211065455
    DOI: 10.1177/21582440211065455
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    References listed on IDEAS

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    Cited by:

    1. Rui Wang & Xiao Yan & Chuanjin Zhu, 2023. "Solving a Distribution-Free Multi-Period Newsvendor Problem With Advance Purchase Discount via an Online Ordering Solution," SAGE Open, , vol. 13(2), pages 21582440231, June.
    2. Xiaotong Guo & Yong He, 2022. "Mathematical Modeling and Optimization of Platform Service Supply Chains: A Literature Review," Mathematics, MDPI, vol. 10(22), pages 1-19, November.

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