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Research on the collaborative governance of urban regeneration based on a Bayesian network: The case of Chongqing

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  • Liu, Guiwen
  • Fu, Xinyue
  • Han, Qingye
  • Huang, Ruopeng
  • Zhuang, Taozhi

Abstract

The rapid development of the economy and urbanization has led to numerous urban regeneration projects, and collaborative governance is increasingly advocated to address the management issues that occur during urban regeneration. However, strong collaboration is still a great challenge among multiple stakeholders during the process of urban regeneration. Based on Bayesian network theory and the case of Chongqing, this article aims to deconstruct the complex structure and explore the inherent mechanism of urban regeneration governance to achieve collaboration. First, a Bayesian network model of urban regeneration governance was developed to visualize the complex structure of multiple stakeholders’ interests. Second, the inherent mechanism was analyzed though Bayesian inference. The results indicate that the cooperation degree of related governments, conflict resolution efficiency, degree of public participation, and normality of public participation may be key factors that lead to collaborative behavior. Third, a further discussion was conducted, based on which policy implications were drawn to promote collaborative governance in urban regeneration.

Suggested Citation

  • Liu, Guiwen & Fu, Xinyue & Han, Qingye & Huang, Ruopeng & Zhuang, Taozhi, 2021. "Research on the collaborative governance of urban regeneration based on a Bayesian network: The case of Chongqing," Land Use Policy, Elsevier, vol. 109(C).
    • Handle: RePEc:eee:lauspo:v:109:y:2021:i:c:s026483772100363x
    DOI: 10.1016/j.landusepol.2021.105640
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    References listed on IDEAS

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    Cited by:

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    5. Guiwen Liu & Cheng Li & Taozhi Zhuang & Yuhan Zheng & Hongjuan Wu & Jian Tang, 2022. "Determining the Spatial Distribution Characteristics of Urban Regeneration Projects in China on the City Scale: The Case of Shenzhen," Land, MDPI, vol. 11(8), pages 1-27, July.
    6. Zhang, Mingming & Zhou, Simei & Wang, Qunwei & Liu, Liyun & Zhou, Dequn, 2023. "Will the carbon neutrality target impact China's energy security? A dynamic Bayesian network model," Energy Economics, Elsevier, vol. 125(C).

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