Spatiotemporal Evolution and Driving Factors of Agricultural Digital Transformation in China

Jinli Wang, Jun Wen (), Jie Lin and Xingqun Li
Additional contact information
Jinli Wang: College of Agriculture, Guangxi University, Nanning 530004, China
Jun Wen: College of Agriculture, Guangxi University, Nanning 530004, China
Jie Lin: College of Plant Protection, Shenyang Agricultural University, Shenyang 110866, China
Xingqun Li: College of Agriculture, Guangxi University, Nanning 530004, China

Agriculture, 2025, vol. 15, issue 15, 1-19

Abstract: With the digital economy continuing to integrate deeply into the agricultural sector, agricultural digital transformation has emerged as a pivotal driver of rural revitalization and the development of a robust agricultural economy. Although existing studies have affirmed the positive role of agricultural digital transformation in promoting rural development and enhancing agricultural efficiency, its spatiotemporal evolution patterns, regional disparities, and underlying driving factors have not yet been systematically and thoroughly investigated. This study seeks to fill that gap. Based on provincial panel data from China spanning 2011 to 2023, this study employs the Theil index, kernel density estimation, Moran’s index, and quantile regression to systematically assess the spatiotemporal dynamics and driving factors of agricultural digital transformation at both national and regional levels. The results reveal a steady overall improvement in agricultural digital transformation, yet regional development imbalances remain prominent, with a shift from inter-regional disparities to intra-regional disparities over time. The four major regions exhibit a stratified evolutionary trajectory marked by internal differentiation: the eastern region retains its lead, while central and western regions show potential for catch-up, and the northeastern region faces a “balance trap.” Economic development foundation, human capital quality, and policy environment support are identified as the core driving forces of transformation, while other factors demonstrate pronounced regional and phase-specific variability. This study not only deepens theoretical understanding of the uneven development and driving logic of agricultural digital transformation but also provides empirical evidence to support policy optimization and promote more balanced and sustainable development in the agricultural sector.

Keywords: agricultural digital transformation; spatiotemporal evolution characteristics; driving factors; regional development (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2077-0472/15/15/1600/pdf (application/pdf)
https://www.mdpi.com/2077-0472/15/15/1600/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jagris:v:15:y:2025:i:15:p:1600-:d:1709809

Access Statistics for this article

Agriculture is currently edited by Ms. Leda Xuan

More articles in Agriculture from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().