Digital divides

Skaletsky, Maria; Pick, James B.; Sarkar, Avijit; Yates, David J.

doi:10.4324/9781315619361-31

Cited by 5 publications

(3 citation statements)

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“…The provincial variation across the infrastructure and use groups is relatively small, whereas provincial inequality for IT services and e-commerce is large, as reflected by their elevated coefficients of variation. This finding relates to prior studies identifying the succession of stages of ICT access, use, and purposeful use [6][7][8]. In China, access and use have mostly achieved evenness among the provinces.…”

Section: Discussionsupporting

confidence: 84%

“…Digital inequality is a complex phenomenon that has been formulated theoretically to include a range of types of access, cultural factors, socioeconomic and political aspects, and the importance of digital learning. A conceptual approach to access to digital technologies is to consider a sequence starting with motivation and extending to physical infrastructure, digital skills, and usage [5][6][7][8]. These laddered elements were encompassed in a complex model of digital media under the category of "access", along with personal characteristics, resources, positional categories, and participation outcomes [6].…”

Section: Literature Reviewmentioning

confidence: 99%

“…Approaches to modeling digital inequalities for China range from econometric models [15,16] to simple frameworks of ICT use [12,17] to spatial analytics [3,18]. Apart from China, more complex conceptual models of digital inequalities and divides include digital divide multi-level behavioral modeling [6,9], digital divide units of analysis and access-use progression [20], and spatial modeling [8,21].…”

Section: Conceptual Modelmentioning

confidence: 99%

See 2 more Smart Citations

Digital Inequalities in China in 2020: Spatial and Multivariate Analysis

Pick,

Ren,

Sarkar

2024

Applied Sciences

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China’s digital divide is explored through spatial and multivariate analysis. The dependent variables include general uses of information and communication technologies (ICTs) and mobile devices, measures of ICT infrastructure, purposeful uses for software services, and purposeful uses of e-commerce. Independent variables include a variety of demographic, economic, educational, ethnic, innovation, and knowledge production indicators. Data come from the China Yearbook. Theoretically, the study draws on the Spatially Aware Technology Utilization Model (SATUM). Digital disparities in Chinese provinces are analyzed using regression analysis, spatial autocorrelation, and k-means cluster analysis. The important correlates associated with digital inequality are expenditure for science and technology, income, R&D investment, full-time teachers, non-Han (minority) population, and proportion of urbanization. Longitudinal comparison reveals factors influencing ICT changes to be expenditure on science and technology, the unemployment rate, and college degree. Among the cluster findings are geographic concentrations of digital variables in Shanghai and Beijing and marked spatial pattern differences in central and central–east China between variable groups. Provincial and national policy implications, which are compared to China’s five-year plans, include an emphasis on science and technology, technology education in all provinces, support for higher provincial incomes, and ICT training for the non-Han population. These steps are especially important in ICT-deprived provinces.

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Section: Discussionsupporting

confidence: 84%