Coupling coordination analysis and Spatiotemporal heterogeneity between data elements and green development in China

Abstract

By constructing a comprehensive evaluation index system for data elements and green development, this paper measures the level of data elements and green development in 273 prefecture-level cities in China from 2011 to 2019 using the random forest algorithm and calculates the coupling coordination degree (CCD) of the two systems using the coupling coordination degree model. Furthermore, this paper classifies the 273 cities into six types based on their “business charm” rankings and uses the Dagum Gini coefficient, kernel density estimation and a spatial Markov chain model to investigate the spatiotemporal characteristics and dynamic evolution of the CCD between data elements and green development. The results show that: (1) the average level of data elements is 0.087, which obviously lags behind the average level of green development, but the levels of both data elements and green development are on the rise; (2) the average CCD between data elements and green development is 0.44, which is in the moderate coordination stage and the CCD shows a year-on-year increase; (3) the higher the business charm ranking of a city, the higher the CCD between Data elements Green development (4) the CCD is affected by the city business charm ranking, showing significant differences, which mainly originate from the intergroup differences; (5) the CCD between data elements and green development in a city is also influenced by its neighboring cities, and the spatial pattern of the CCD evolution shows a “club convergence” phenomenon in the extreme coupling coordination stage. These findings provide important implications for promoting synergies between data elements and green development in both developing and developed countries.