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Urban industrial transformation patterns under natural resource dependence: A rule mining technique

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  • Mao, Wenxin
  • Wang, Wenping
  • Sun, Huifang
  • Yao, Peiyi
  • Wang, Xiaolei
  • Luo, Dang

Abstract

Urban industrial transformation is crucial for resource-based cities to break through the lock-in effect of natural resources dependence and achieve economic, environmental and energy sustainability. This paper proposes a rough set-based rule mining technique of learning, validation and generalisation to identify what influential factors, under which synergetic combination methods and influencing levels lead to successful industrial structural transformation in resource-based cities. The extracted decision rules reveal the transformation patterns from the rationalisation and optimisation of industrial structure, as well as the potential path transmission mechanism that help prevent the negative effects of resource dependence. The results from China's 115 resource-based cities during 2004–2017 show resource curses that may hinder industrial structural transformation are not absolute existence but conditional appearance. Abundant resources in superior urban transformation cases promote the rationalisation and optimisation of industrial structure by driving material and human capital investment under a reasonable government policy intervention. However, resource dependence squeezes out the technological innovation and marketing competition for developing private enterprises, challenging transformations that improve resource allocation efficiency based on marketisation. The identified patterns inspire policy-makers to adjust urban industrial structure through developing urban resource advantages and bypassing insufficiencies in historical transformation.

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  • Mao, Wenxin & Wang, Wenping & Sun, Huifang & Yao, Peiyi & Wang, Xiaolei & Luo, Dang, 2021. "Urban industrial transformation patterns under natural resource dependence: A rule mining technique," Energy Policy, Elsevier, vol. 156(C).
    • Handle: RePEc:eee:enepol:v:156:y:2021:i:c:s0301421521002536
    DOI: 10.1016/j.enpol.2021.112383
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