Research on the Impact of Digital Rural Construction on Agricultural Economic Resilience

The resilience of the agricultural economy and the process of rural revitalization are substantially strengthened through digital rural development. Comprehensive indicator systems for digital rural development and agricultural economic resilience are constructed using inter-provincial panel data from China between 2011 and 2023. The cross-entropy unbiased weighting approach is adopted to quantify development levels, and a double machine learning framework is applied to examine the association between the two. First, agricultural economic resilience generally exhibits an upward trend across provinces, with comparatively higher levels concentrated in regions such as Northeast and North China. Second, digital rural development contributes substantially to agricultural economic resilience, primarily through improvements in agricultural labor productivity, innovation capacity, and industrial structural upgrading. Third, the effects vary across regions, with the western region experiencing a more pronounced effect than other areas; the effect is greater during 2017–2023 than during 2011–2016; and non-major agricultural provinces benefit more than major agricultural provinces. It is recommended to further promote digital rural development, expand the utilization of digital technologies across the agricultural sector, and adopt region-specific strategies to enhance agricultural economic resilience and provide solid support for rural revitalization as well as the modernization of agriculture and rural areas.

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Publication Details

Journal
Journal of Advanced Computational Intelligence and Intelligent Informatics
Published
2026-09-19
DOI
https://doi.org/10.20965/jaciii.2026.p1389
Primary Topic
Regional resilience and development
Type
article
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article

Research on the Impact of Digital Rural Construction on Agricultural Economic Resilience

Chengkun Liu, Xiqin Pan
Journal of Advanced Computational Intelligence and Intelligent Informatics
Regional resilience and development
article

Research on the Impact of Digital Rural Construction on Agricultural Economic Resilience

Chengkun Liu, Xiqin Pan
article en

Abstract

The resilience of the agricultural economy and the process of rural revitalization are substantially strengthened through digital rural development. Comprehensive indicator systems for digital rural development and agricultural economic resilience are constructed using inter-provincial panel data from China between 2011 and 2023. The cross-entropy unbiased weighting approach is adopted to quantify development levels, and a double machine learning framework is applied to examine the association between the two. First, agricultural economic resilience generally exhibits an upward trend across provinces, with comparatively higher levels concentrated in regions such as Northeast and North China. Second, digital rural development contributes substantially to agricultural economic resilience, primarily through improvements in agricultural labor productivity, innovation capacity, and industrial structural upgrading. Third, the effects vary across regions, with the western region experiencing a more pronounced effect than other areas; the effect is greater during 2017–2023 than during 2011–2016; and non-major agricultural provinces benefit more than major agricultural provinces. It is recommended to further promote digital rural development, expand the utilization of digital technologies across the agricultural sector, and adopt region-specific strategies to enhance agricultural economic resilience and provide solid support for rural revitalization as well as the modernization of agriculture and rural areas.

Journal of Advanced Computational Intelligence and Intelligent InformaticsVol. 30(5)
Jiangxi University of Finance and Economics (CN)
Zero hunger
Openalex Percentile: Top 5%
Regional resilience and development
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Research on the Impact of Digital Rural Construction on Agricultural Economic Resilience — Chengkun Liu, Xiqin Pan · Journal of Advanced Computational Intelligence and Intelligent Informatics (2026) | TGRS Research Map | TGRS