How does digitalization affect the urban-rural disparity at different disparity levels: A Bayesian Quantile Regression approach

Hongpeng Fu, Jianxing Guan, Runzi Wang, Liangji Kong and Qinqin Dai

Technology in Society, 2024, vol. 78, issue C

Abstract: The digital revolution is bringing profound changes to the production, lifestyle, and governance in urban and rural areas. However, the varying impacts of different digitalization dimensions on urban-rural disparity have been understudied, particularly in developing countries. Based on 1931 county-level administrative units, this study used cluster analysis and a novel Bayesian Quantile Regression approach to explore the digitalization characteristics, and how digitalization influences urban-rural disparity at different disparity levels and in different regions. We found three types of digitalization development, including Balanced Digital Progression (29.26 %), Digital Consumption Powerhouse (17.50 %), and Digital Development Potential (53.24 %). Digitalization played an essential role in alleviating urban-rural disparity, with a more pronounced effect in areas with higher levels of disparity. The access to information infrastructure related to the first-level digital divide may exacerbate the urban-rural disparity, while the digitalization dimensions related to the second-level digital divide could mitigate the urban-rural disparity. Regarding the regional effects, information infrastructure adoption has different impacts on urban-rural disparity across various regions, while digitalization usage is consistently mitigating urban-rural disparities. By comprehensively examining the role of digitalization, we provided a scientific basis for formulating more precise and effective policies for a more balanced and integrated urban-rural development.

Keywords: Bayesian quantile regression; Urban-rural disparity; Digitalization; Digital divide; Sustainable development goals (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:teinso:v:78:y:2024:i:c:s0160791x24001817

DOI: 10.1016/j.techsoc.2024.102633

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