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The Optimal Production Decision of Competing Supply Chains When Considering Green Degree: A Game-Theoretic Approach

Author

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  • Jiguang Wang

    (School of Economics & Management, Shanxi University, Taiyuan 030006, China)

  • Jianhong Chang

    (School of Economics & Management, Shanxi University, Taiyuan 030006, China)

  • Yucai Wu

    (Faculty of Business Administration, Shanxi University of Finance & Economics, Taiyuan 030006, China)

Abstract

Nowadays, the green supply chain has become an exciting concept in academic societies. This paper focuses on the optimal production decisions of two competing supply chains from the perspective of green degree. The manufacturers in each supply chain have two options—producing a green product or a non-green product. Game theory is applied to study four decision scenarios, which are derived from the difference in the products of the two supply chains. This study investigates the influence of inter-supply-chain competition on the wholesale price, green degree, and profits of the supply chain members. The results indicate that the inter-supply-chain competition has a negative correlation with the wholesale price. The inter-supply-chain competition has a significant impact on green degree in the four decision scenarios. In addition, green products are not always the dominant strategy of manufacturers. Both the competitors’ product decisions and the degree of inter-supply-chain competition should be considered. Finally, weak inter-supply-chain competition is beneficial to the leader supply chain, while strong competition is beneficial to the follower supply chain.

Suggested Citation

  • Jiguang Wang & Jianhong Chang & Yucai Wu, 2020. "The Optimal Production Decision of Competing Supply Chains When Considering Green Degree: A Game-Theoretic Approach," Sustainability, MDPI, vol. 12(18), pages 1-20, September.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:18:p:7413-:d:411174
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    References listed on IDEAS

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    4. Jindai Zhang & Jinlou Zhao, 2022. "Prediction-Driven Sequential Optimization for Refined Oil Production-Sales-Stock Decision-Making," Energies, MDPI, vol. 15(12), pages 1-19, June.

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