How Digitalization and Its Context Affect the Urban–Rural Income Gap: A Configurational Analysis Based on 274 Prefecture-Level Administrative Regions in China

Yulong Jie, Shuigen Hu, Siling Zhu and Lieen Weng ()
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Yulong Jie: School of Public Affairs, Zhejiang University, Hangzhou 310058, China
Shuigen Hu: School of Public Affairs, Zhejiang University, Hangzhou 310058, China
Siling Zhu: School of Public Affairs, Zhejiang University, Hangzhou 310058, China
Lieen Weng: School of Public Administration, Zhejiang University of Technology, Hangzhou 310014, China

Land, 2024, vol. 13, issue 12, 1-41

Abstract: Digitalization offers an opportunity to narrow the economic gap between urban and rural areas; however, there are fragmented and competing explanations regarding its impact mechanisms. Responding to calls for research on the complex effects of digitalization, this paper, based on a contextual perspective and configurational theory, analyzes the impact of digitalization conditions embedded in contexts on the urban–rural income gap. The study, based on a sample of 274 prefecture-level administrative regions in China from 2014 to 2021, employs a Panel Fuzzy-Set Qualitative Comparative Analysis (Panel fsQCA) and Necessary Condition Analysis (NCA). The combined application of necessity analysis and sufficiency analysis reveals that certain digitalization conditions—such as digital infrastructure, digital industry, and digital finance—have a universal influence on the urban–rural income gap. Importantly, the sufficiency analysis demonstrates that the impact mechanisms of digitalization conditions exhibit configurational effects, varying with changes in contextual and conditional combinations. The models that significantly narrow the urban–rural income gap include (1) the “infrastructure–finance–governance” model, (2) the comprehensive digital transformation model, (3) the “technology–infrastructure–industry” model, and (4) the digital infrastructure transformation model. Among these, the comprehensive digital transformation model is the most universally effective. These configurations reflect the logic of completeness and substitutability and exhibit specific dynamic evolutionary trends and spatial distribution characteristics. These findings provide contextual and adaptable empirical insights for economies, including China, to implement targeted digital transformation strategies that effectively narrow the urban–rural income gap. For instance, economies can focus on developing comprehensive digital transformation in prosperous and open regions to reduce income gap.

Keywords: urban–rural income gap; digitalization; panel fsQCA; NCA (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2024
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