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<p>As digital transformation accelerates globally, studies of its impact on citizens’ subjective well-being (SWB) and inequality remain limited. This study constructs a provincial-level measure of digital investment in basic public services by applying machine learning and text analysis to over 70,000 government procurement contracts from the China Government Procurement Network. By merging this measure with more than 80,000 individual observations from the China Family Panel Studies (CFPS, 2014–2022), this study examines how the digital transformation of public services affects citizens’ SWB and its distribution. The results show that this transformation enhances citizens’ SWB, particularly via healthcare and education. Mechanism tests reveal that digital transformation promotes SWB primarily by reducing household service expenditures and lowering social policy insecurity. However, Recentred Influence Function regression shows that this transformation has also generated SWB inequality, and dimension-specific estimates further reveal that education and social security widen disparities, whereas healthcare and culture help reduce them. Further mechanism analysis indicates that differences in digital literacy underlie this divergence. Groups with higher digital literacy benefit disproportionately from the digital transformation of education and social security, thereby exacerbating SWB gaps, whereas healthcare and culture show no significant differences in group benefits and are more inclusive of digitally disadvantaged populations, thus narrowing overall inequality. These findings underscore the limited gains for digitally disadvantaged groups and reveal the social differentiation risks of digital development, emphasizing that future digital governance must balance efficiency improvements with inclusive protections.</p>

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Research on China’s level and inequality of SWB based on digital transformation of public services

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年7月4日

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  • Mi Xu,
  • Dongmei Mu,
  • Daifu Yang

摘要

As digital transformation accelerates globally, studies of its impact on citizens’ subjective well-being (SWB) and inequality remain limited. This study constructs a provincial-level measure of digital investment in basic public services by applying machine learning and text analysis to over 70,000 government procurement contracts from the China Government Procurement Network. By merging this measure with more than 80,000 individual observations from the China Family Panel Studies (CFPS, 2014–2022), this study examines how the digital transformation of public services affects citizens’ SWB and its distribution. The results show that this transformation enhances citizens’ SWB, particularly via healthcare and education. Mechanism tests reveal that digital transformation promotes SWB primarily by reducing household service expenditures and lowering social policy insecurity. However, Recentred Influence Function regression shows that this transformation has also generated SWB inequality, and dimension-specific estimates further reveal that education and social security widen disparities, whereas healthcare and culture help reduce them. Further mechanism analysis indicates that differences in digital literacy underlie this divergence. Groups with higher digital literacy benefit disproportionately from the digital transformation of education and social security, thereby exacerbating SWB gaps, whereas healthcare and culture show no significant differences in group benefits and are more inclusive of digitally disadvantaged populations, thus narrowing overall inequality. These findings underscore the limited gains for digitally disadvantaged groups and reveal the social differentiation risks of digital development, emphasizing that future digital governance must balance efficiency improvements with inclusive protections.