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Consumer-Centered Collaborative Governance of Regional Business Environment

Author

Listed:
  • Tingting Xiang

    (School of Economics and Management, Southeast University, Nanjing 211189, China)

  • Hongzhi Lin

    (School of Economics and Management, Southeast University, Nanjing 211189, China)

Abstract

Optimizing the regional business environment plays a crucial role in improving the market supply structure, enhancing market dynamism, and boosting consumer welfare. Investigating how the government can effectively improve the business environment and promote consumer welfare through scientific and strategic investment allocation is a topic that warrants comprehensive and in-depth research. This paper proposes a bi-level programming model based on consumer welfare, with the upper-level model focusing on optimizing the government’s investment allocation strategy to maximize consumer welfare, and the lower-level model addressing the spatial price equilibrium problem after improving the business environment. The experimental results confirm the effectiveness and practicality of the proposed algorithm. The findings reveal that the bi-level programming model, integrating simulated annealing and projection algorithms, provides support for governments in accurately determining investment allocation strategies, enabling the simultaneous maximization of consumer welfare and optimization of the business environment. Additionally, increased government investment significantly improves both the business environment and consumer welfare, while appropriately managing the intensity of investment further enhances consumer welfare. This study offers valuable theoretical insights and practical guidance for governments to refine investment decisions, foster business environment development, and improve societal well-being.

Suggested Citation

  • Tingting Xiang & Hongzhi Lin, 2025. "Consumer-Centered Collaborative Governance of Regional Business Environment," Mathematics, MDPI, vol. 13(15), pages 1-17, July.
  • Handle: RePEc:gam:jmathe:v:13:y:2025:i:15:p:2340-:d:1707568
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    References listed on IDEAS

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    1. Kreuter, Helena & Riccaboni, Massimo, 2023. "The impact of import tariffs on GDP and consumer welfare: A production network approach," Economic Modelling, Elsevier, vol. 126(C).
    2. Jiayi Joey Yu & Christopher S. Tang & Zuo-Jun Max Shen, 2018. "Improving Consumer Welfare and Manufacturer Profit via Government Subsidy Programs: Subsidizing Consumers or Manufacturers?," Manufacturing & Service Operations Management, INFORMS, vol. 20(4), pages 752-766, October.
    3. Anna Nagurney & Patrizia Daniele & Shivani Shukla, 2017. "A supply chain network game theory model of cybersecurity investments with nonlinear budget constraints," Annals of Operations Research, Springer, vol. 248(1), pages 405-427, January.
    4. Nagurney, Anna & Shukla, Shivani & Nagurney, Ladimer S. & Saberi, Sara, 2018. "A game theory model for freight service provision security investments for high-value cargo," Economics of Transportation, Elsevier, vol. 16(C), pages 21-28.
    5. Yong Zhang & Xiaomeng Lu & Jing Jian Xiao, 2023. "Can financial education improve consumer welfare in investment markets? Evidence from China," Journal of the Asia Pacific Economy, Taylor & Francis Journals, vol. 28(3), pages 1286-1312, July.
    6. Jerome Bracken & James T. McGill, 1973. "Mathematical Programs with Optimization Problems in the Constraints," Operations Research, INFORMS, vol. 21(1), pages 37-44, February.
    7. He, Congxian & Zhou, Can & Wen, Huwei, 2024. "Improving the consumer welfare of rural residents through public support policies: A study on old revolutionary areas in China," Socio-Economic Planning Sciences, Elsevier, vol. 91(C).
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