Evidence map›Paper›PMID 41326473›Full record

ArticleScientific reports2025

The associational relationships between multidimensional digital literacy and wage income: evidence from urban-rural heterogeneity.

Jiangwei Hu, Chunyun Tan, Yamei Jiao, Xu Mou, Pengjun Wu

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In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Jiangwei Hu *School of Chinese Literature and Media, Hubei University of Arts and Science, Xiangyang, Hubei, China.
Chunyun Tan *School of Chinese Literature and Media, Hubei University of Arts and Science, Xiangyang, Hubei, China.
Yamei JiaoInstitute of Industry And Art Design, Guangxi Eco-Engineering Vocational & Technical College, LiuZhou, Guangxi, China.
Xu MouSchool of Arts, Liuzhou Polytechnic University, Liu Zhou, Guangxi, China.
Pengjun WuSchool of Plastic Arts, Daegu University, Gyeongsangbukdo, South Korea. wupengjun@daegu.ac.kr.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Amid the rapid development of the digital economy, digital literacy has become a crucial factor associated with labor market outcomes and wage levels, particularly in China, where urban–rural disparities and structural inequalities remain pronounced. Drawing on data from the 2022 China Family Panel Studies (CFPS 2022), this study constructs a multidimensional digital literacy index using the entropy–TOPSIS method, covering five behavioral dimensions: digital tool usage, online social interaction, online learning, entertainment consumption, and e-commerce activities. Stepwise OLS regressions are employed as the main analytical approach to examine how digital literacy is associated with wage income, while a supplementary SEM analysis is conducted to validate the robustness of the observed relationships and to explore potential mediating pathways. The results indicate that digital literacy is positively and significantly associated with wage income after controlling for key covariates, with a stronger association observed among urban workers, highlighting its structural role as a new form of human capital. However, the mediating association of non-farm employment is not statistically significant, suggesting that the linkage between digital skills and employment outcomes may be constrained by skill mismatches, institutional barriers, and unequal access to resources. Overall, this study contributes to a correlational understanding of the relationship between digital literacy and income distribution and provides empirical evidence and policy insights for enhancing digital skills, promoting labor mobility, and narrowing the urban–rural income gap.

Indexed as

Computer LiteracyIncomeRural PopulationSalaries and Fringe BenefitsUrban PopulationChinaEmploymentFemaleHumansSocioeconomic FactorsDigital literacyEntropy–TOPSISOLS regressionStructural equation modeling (SEM)Urban–rural disparitiesWage income

Identifiers

PMID41326473
PMCPMC12669597

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