The spatiotemporal evolution and formation mechanism of the digital economic gap: Based on the case of China

We analyzed the formation mechanism of digital economic gap (DEG), measured the DEGs at four levels (the gaps in information and communication technology accessibility, application skill, digital economic outcome, and efficiency), and explored its spatiotemporal evolution in China by using DEA–Malmquist index method, Gini Coefficent method, Kernel density, and Geodetector. Data from 263 cities in China between 2011 and 2019 were collected. The results demonstrated that (1) The four levels of DEGs showed different trends. The first-, second- and third- level DEGs showed ceiling effects, and the fourth-level DEG oscillated upward. (2) The distribution location of the four levels of DEGs varied. The first- and second-level DEGs shifted at a stable low degree. The third-level DEG increased steadily and polarized. The fourth-level DEG increased steadily and formed a multi-polarization trend, with one strong polar. (3) The long-term transfer trend of the DEGs at four levels changed little, and showed a phenomenon of “club convergence”. (4) As for the formation of DEGs, the first-level DEG was influenced by most factors and was education- and policy-driven; the second-level DEG was profit-driven; the third-level DEG was profit- and education-driven; the fourth-level DEG was human resource-driven.

Methods
A total of 263 cities in 30 provinces (cities or regions) in China were selected as the study subjects. Data were obtained from the China Statistical Yearbook, China Science and Technology Statistical Yearbook, Provincial and City Statistical Yearbooks, White Paper on China City DE Index, and the Mark Data website (https://www.macrodatas.cn/). The expedition period for this study was from 2011 to 2019.