Green transformation is an unavoidable choice for resource-based cities(RBCs)that face resource depletion and environmental pollution.Existing research has focused primarily on specific RBCs,making it challenging to a...Green transformation is an unavoidable choice for resource-based cities(RBCs)that face resource depletion and environmental pollution.Existing research has focused primarily on specific RBCs,making it challenging to apply green transformation strategies universally across cities.The fuzzy set qualitative comparative analysis(fsQCA)is a combination of qualitative and quantitative analyses that can handle multiple concurrent causality problems and determine how different conditions combine into configurations and generate an outcome.Thus,to address this gap,in this study,we established a research framework for green transformation and utilized the fsQCA to examine the configurations of 113 RBCs in China.By incorporating the element of time,this study explored the dynamic evolution of solutions in 2013,2016,and 2019.The main findings indicate that individual elements do not constitute the necessary conditions for improving the green transformation efficiency(GTE),and the systematic combination of multiple conditions is an effective path for realizing the improvement of the GTE in RBCs.Green transformation paths of RBCs exhibit the same destination through different paths.Additionally,the combination of system environment elements and system structure elements is both complementary and alternative.Differences in RBCs have led to various factor combinations and development paths,but there are some similarities in the key elements of the factor combinations at different stages.Economic environment,government support,and technological innovation are key factors that universally enhance the GTE in RBCs.These insights can assist city managers in formulating policies to drive green transformation and contribute to a better theoretical understanding of green transformation paths in RBCs.展开更多
基金the Key Scientific Research Projects of Institutions of Higher Learning in Henan Province (No. 16A413003)the Nature Science Foundation of China (No. 61403124)
基金supported by the Chongqing Social Science Planning Fund,China(2023BS034)the Science and Technology Project of Chongqing Jiaotong University,China(F1230069).
文摘Green transformation is an unavoidable choice for resource-based cities(RBCs)that face resource depletion and environmental pollution.Existing research has focused primarily on specific RBCs,making it challenging to apply green transformation strategies universally across cities.The fuzzy set qualitative comparative analysis(fsQCA)is a combination of qualitative and quantitative analyses that can handle multiple concurrent causality problems and determine how different conditions combine into configurations and generate an outcome.Thus,to address this gap,in this study,we established a research framework for green transformation and utilized the fsQCA to examine the configurations of 113 RBCs in China.By incorporating the element of time,this study explored the dynamic evolution of solutions in 2013,2016,and 2019.The main findings indicate that individual elements do not constitute the necessary conditions for improving the green transformation efficiency(GTE),and the systematic combination of multiple conditions is an effective path for realizing the improvement of the GTE in RBCs.Green transformation paths of RBCs exhibit the same destination through different paths.Additionally,the combination of system environment elements and system structure elements is both complementary and alternative.Differences in RBCs have led to various factor combinations and development paths,but there are some similarities in the key elements of the factor combinations at different stages.Economic environment,government support,and technological innovation are key factors that universally enhance the GTE in RBCs.These insights can assist city managers in formulating policies to drive green transformation and contribute to a better theoretical understanding of green transformation paths in RBCs.