ORIGINAL RESEARCH article
Front. Sustain. Food Syst.
Sec. Agricultural and Food Economics
This article is part of the Research TopicAdvancing Sustainability and Resilience in Agri-Food Supply Chains Through Multi-Criteria Decision-Making MethodsView all 7 articles
The Impact of Data Factor-driven Industry on Rural Revitalisation: Evidence from China
Provisionally accepted
- 1School of Economics and Finance, GuiZhou University of Commerce, Guiyang, China
- 2College of Economics and Management, Aba Teachers University, Aba, China
- 3Faculty of Economics and Business Administration, Yibin University, Yibin, China
- 4International Business School, Chongqing Technology and Business University, Chongqing, China
- 5School of Management engineering, Henan University of Engineering, Zhengzhou, China
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Introduction: As a new production factor, data can interact synergistically with traditional factors such as labor and capital, generating amplification, superposition, and multiplication effects. In China, the vast rural market, abundant agricultural data resources, and diverse application scenarios provide fertile ground for the growth of data factor–driven industries. These industries have great potential to promote digital intelligence in agricultural production, improve market connectivity, and enhance farmers' income, thereby contributing to rural revitalization. Methods: This study constructs a panel data-set covering 261 Chinese cities from 2014 to 2022 to empirically examine the impact and mechanisms of data factor–driven industries on rural revitalization. A two-way fixed effects model is employed to identify the direct effects, while mediating effect tests are used to explore the underlying transmission channels. Results: The empirical results show that data factor–driven industries significantly promote rural revitalization. Mechanism analyses further reveal that rural innovation and entrepreneurship act as key mediating pathways through which data factor–driven industries enhance rural revitalization. Moreover, heterogeneity tests indicate that this positive effect is more pronounced in regions with highly advanced industrial structures and a greater degree of fiscal decentralization. Discussion: These findings provide new empirical evidence on the role of data factors in driving rural revitalization. The results suggest that promoting data factor–driven industries can stimulate innovation and entrepreneurship in rural areas, thereby fostering high-quality rural development. Policy efforts should focus on strengthening data infrastructure, improving institutional environments, and encouraging the integration of digital technologies into rural industrial transformation.
Keywords: data factor-driven industry, Rural revitalisation, Rural entrepreneurship, Rural innovation, agriculturalproduction
Received: 23 Jul 2025; Accepted: 24 Nov 2025.
Copyright: © 2025 Huang, Cui, Chen, Dai, Wang and Mei. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Yu qing Cui
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