Heterogeneity of correlation between the locational condition and industrial transformation of regenerative resource‐based cities in China
Fangdao Qiu and
Growth and Change, 2020, vol. 51, issue 2, 771-791
Based on the measurement of the locational condition from a spatiotemporal perspective, the entropy weight TOPSIS, a grey relational analysis model, and other methods are adopted to analyze the correlative heterogeneity characteristics of industrial restructuring, path locking, and path innovation of regenerative resource‐based cities in China from 2005 to 2016. In this paper, we conclude that locational conditions were closely related to industrial transformation. And specifically, the locational condition of study cities was the most closely related to path innovation, followed by the advanced index of industrial structuring, and the weakest correlation with the speed of industrial restructuring. For non‐remote cities, due to the proximity of provincial capitals and regional central cities, the path innovation was the fastest, and the correlation with the advanced index was the closest. For remote cities, the advanced index showed a downward trend. However, the correlation between the locational condition and the advanced index or path innovation were both high. For extremely remote cities, the speed and advanced index of industrial restructuring were most disadvantaged. Furthermore, the path locking was the strongest, and the path innovation was the weakest. It had the strongest correlation with path innovation. Overall, the heterogeneity of the correlation between geographic location and industrial transformation is significant.
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Persistent link: https://EconPapers.repec.org/RePEc:bla:growch:v:51:y:2020:i:2:p:771-791
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