China's prefectural digital divide: Spatial analysis and multivariate determinants of ICT diffusion. (June 2020) - Song, Zhouying
Highlights: We built a conceptual model of digital divide, covering the first, second, and third-order digital divide. Spatial differences and geographical cluster characteristics are identified and analyzed. The leading determinants of ICT diffusion are urban residential income, gross enrollment ratio, and rural residential income. Socio-economic problems, rather than institutions and innovation aspects, have to be solved for ICT diffusion. Abstract: Much research has made efforts to elaborate upon different dimensions to the digital divide, including informational and communications technology (ICT) access, ICT usage, and ICT outcomes. We assess the utility of such perspectives for studying digital inequality across prefectural cities in China. China is the world's largest ICT market in terms of the number of mobile devices in use, internet users, and broadband subscriptions, yet it has notable digital inequality within and between provinces, prefectural cities, and counties. In this study, we built a conceptual framework of digital divides for prefectural cities in China, examined spatial agglomeration using cluster analysis, and explored the leading correlates using a geographically-weighted regression (GWR) model. A large digital divide among the prefectural cities in China was revealed, with cities with a high administrative level having a relatively high digital development index(DDI) score. Prefectural cities with high DDI levels are mainly agglomerated in large metropolitan areas, such as Beijing–Tianjin–Hebei, the Yangtze River Delta, the Pearl River Delta, and the West Coast Economic Zone of the Taiwan Straits. Prefectural cities with low DDI levels are concentrated in the rural-mountainous regions in southwest China and poverty-stricken areas in central and western China. This study also found that the leading determinants of the digital divide are urban residential income, the secondary education gross enrollment ratio, rural residential income, and the working age population ratio, which indicates that socio-economic problems, rather than institution and innovation aspects, have to be solved for improving ICT use and outcomes.