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Risk Transfer Mechanism for Agricultural Products Supply Chain Based on Weather Index Insurance

Author

Listed:
  • Hongyong Fu
  • Jiawen Li
  • Yujie Li
  • Shengzhong Huang
  • Xiangkai Sun

Abstract

The risk management for agricultural products supply chain is more complex than that for typical manufacturing supply chain. Agricultural production is vulnerable to severe weather such as heavy rain, cyclones, and cold wave, which challenges the matching of random output with random demand for agricultural products supply chains. The goal of this paper is to design an effective risk transfer mechanism for managing severe weather risks so as to ensure the stable operation of the agricultural products supply chain. We study the coordination of two-level agricultural products supply chain with a single company and a single farmer under the influence of severe weather. Taking rainstorm weather as an example, this paper designs a risk transfer mechanism based on weather index (rainfall) insurance: “rainfall index insurance + revenue sharing + risk transfer fee.” It is found that this risk transfer mechanism can overcome distortion of the farmer’s agricultural investment level under the influence of severe weather. When the contract parameters meet certain conditions, using the risk transfer mechanism can achieve the supply chain coordination and a win-win situation. More importantly, weather change does not affect the Pareto improvement of the company and the farmer under the risk transfer mechanism. In addition, we also find that the company can incentivize the farmer to purchase weather index insurance and use the insurance market to shift the severe weather risk encountered during the agricultural production to protect the company’s and farmer’s income and the stable operation of the supply chain.

Suggested Citation

  • Hongyong Fu & Jiawen Li & Yujie Li & Shengzhong Huang & Xiangkai Sun, 2018. "Risk Transfer Mechanism for Agricultural Products Supply Chain Based on Weather Index Insurance," Complexity, Hindawi, vol. 2018, pages 1-17, August.
    • Handle: RePEc:hin:complx:2369423
    DOI: 10.1155/2018/2369423
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    References listed on IDEAS

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    1. Bertrand, Jean-Louis & Brusset, Xavier & Fortin, Maxime, 2015. "Assessing and hedging the cost of unseasonal weather: Case of the apparel sector," European Journal of Operational Research, Elsevier, vol. 244(1), pages 261-276.
    2. Lukas Buchheim & Thomas Kolaska, 2017. "Weather and the Psychology of Purchasing Outdoor Movie Tickets," Management Science, INFORMS, vol. 63(11), pages 3718-3738, November.
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    Cited by:

    1. Yan Shi & Fulin Wang & Ying Wang & Lili Jia, 2023. "The Maize Supply Chain Coordination Mechanism under Yield Uncertainty Caused by Drought: A Study in the Heilongjiang Province of China," Sustainability, MDPI, vol. 15(14), pages 1-17, July.
    2. Lixia Liu & Xueli Zhan, 2019. "Analysis of Financing Efficiency of Chinese Agricultural Listed Companies Based on Machine Learning," Complexity, Hindawi, vol. 2019, pages 1-11, July.
    3. Yan Shi & Fulin Wang, 2022. "Agricultural Supply Chain Coordination under Weather-Related Uncertain Yield," Sustainability, MDPI, vol. 14(9), pages 1-12, April.
    4. Yong Sun & Hui Liu & Jiwei Liu & Mingyu Sun & Qun Li, 2023. "Analysis of Factors Influencing the Corporate Performance of Listed Companies in China’s Agriculture and Forestry Sector Based on a Panel Threshold Model," Sustainability, MDPI, vol. 15(2), pages 1-21, January.
    5. Md. Bokhtiar Hasan & Md. Delowar Hossain & Abu N.M. Wahid, 2018. "Application of Forward Contract and Crop Insurance as Risk Management Tools of Agriculture: A Case Study in Bangladesh," Asian Economic and Financial Review, Asian Economic and Social Society, vol. 8(12), pages 1394-1405, December.

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