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Research on Risk Avoidance and Coordination of Supply Chain Subject Based on Blockchain Technology

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  • Liang Liu

    (School of Economics and Management, Tianjin Polytechnic University, Tianjin 300387, China)

  • Futou Li

    (School of Economics and Management, Tianjin Polytechnic University, Tianjin 300387, China)

  • Ershi Qi

    (School of Management and Economics, Tianjin University, Tianjin 300072, China)

Abstract

Based on the influence of block chain technology on information sharing among supply chain participants, mean-CVaR (conditional value at risk) is used to characterize retailers’ risk aversion behavior, while a Stackelberg game is taken to study the optimal decision-making of manufacturers and retailers during decentralized and centralized decision-making processes. Finally, the mean-CVaR-based revenue-sharing contract is used to coordinate the supply chain and profit distribution. The research shows that, under the condition of decentralized decision-making, when the retailer’s optimal order quantity is low, it is an increasing function of the weighted proportion and the risk aversion degree, while, when the retailer’s optimal order quantity is high, it is an increasing function of the weighted proportion, and has nothing to do with the risk aversion degree. The manufacturer’s blockchain technology application degree is a reduction function of the weighted proportion. When the retailer’s order quantity is low, the manufacturer’s blockchain technology application degree is a decreasing function of risk aversion, while, when the retailer’s order quantity is high, the manufacturer’s blockchain technology application is independent of risk aversion. The profit of the supply chain system under centralized decision-making is higher than that of decentralized decision-making. The revenue sharing contract can achieve the coordination of the supply chain to the level of centralized decision-making. Through blockchain technology, transaction costs among members of the supply chain can be reduced, information sharing can be realized, and the benefits of the supply chain can be improved. Finally, the specific numerical simulation is adopted to analyze the weighted proportion, risk aversion and the impact of blockchain technology on the supply chain, and verify the relevant conclusions.

Suggested Citation

  • Liang Liu & Futou Li & Ershi Qi, 2019. "Research on Risk Avoidance and Coordination of Supply Chain Subject Based on Blockchain Technology," Sustainability, MDPI, vol. 11(7), pages 1-14, April.
  • Handle: RePEc:gam:jsusta:v:11:y:2019:i:7:p:2182-:d:222013
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    References listed on IDEAS

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    1. Joseph J. Spengler, 1950. "Vertical Integration and Antitrust Policy," Journal of Political Economy, University of Chicago Press, vol. 58(4), pages 347-347.
    2. Rockafellar, R. Tyrrell & Uryasev, Stanislav, 2002. "Conditional value-at-risk for general loss distributions," Journal of Banking & Finance, Elsevier, vol. 26(7), pages 1443-1471, July.
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    13. Vaibhav S. Narwane & Rakesh D. Raut & Sachin Kumar Mangla & Manoj Dora & Balkrishna E. Narkhede, 2023. "Risks to Big Data Analytics and Blockchain Technology Adoption in Supply Chains," Annals of Operations Research, Springer, vol. 327(1), pages 339-374, August.
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