The multidimensional impact of digital agriculture development on agricultural industry upgrading and agricultural economic growth
Main Article Content
Abstract
Digital agriculture transforms agricultural production through the Internet of Things, big data, artificial intelligence, and blockchain technologies, improving precision production, resource allocation, and supply-chain transparency. This paper constructs a collaborative model of digital agriculture development and agricultural industrial upgrading. Using panel data from 31 Chinese provinces from 2015 to 2024, the entropy method is adopted to measure the development level of digital agriculture. Multiple regression and mediation-effect models are used to analyze the transmission mechanisms of technological innovation, resource allocation efficiency, and agricultural product added value. The research process includes establishing and standardizing a digital agriculture evaluation index system, calculating a comprehensive index and conducting regional comparisons, introducing an agricultural industrial upgrading index to test its effect on agricultural economic growth, and verifying results through robustness checks. Results show that for every 1% increase in the digital agriculture comprehensive index, the agricultural industrial upgrading index increases by 0.062, and agricultural added value increases by 0.54%. The promotion effect in central and western regions is stronger than that in eastern regions.
Downloads
Article Details

This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
References
H. Wang, R. Liu, and W. Bao, “A Study on Regional Differences and Driving Factors in the Development Level of Digital Agriculture in the Yellow River Basin,” Yellow River, vol. 47, no. 3, pp. 18-23, 2025, doi: 10.3969/j.issn.1000-1379.2025.03.003.
X. Wang, “Evaluation of the Development Level of Digital Agriculture in Gansu Province from 2013 to 2022 Based on Entropy Method and TOPSIS Method,” Central South Agricultural Science and Technology, vol. 46, no. 3, pp. 144-148, 2025, doi: 10.3969/j.issn.1007-273X.2025.03.032.
Z. Liu and X. Li, “Development level and regional differences of digital agriculture in Xinjiang,” Rural Economy and Science & Technology, vol. 36, no. 9, pp. 116-119, 2025, doi: 10.3969/j.issn.1007-7103.2025.09.030.
H. Liu and X. Xie, “Research on Economic and Legal Issues in the Development of Digital Agriculture,” Shaanxi Agricultural Sciences, vol. 71, no. 5, pp. 105-108, 2025, doi: 10.3969/j.issn.0488-5368.2025.05.023.
Y. Tang and J. Bi, “Current Status of Digital Agriculture Development in Myanmar and Prospects for China-Myanmar Cooperation,” Agricultural Outlook, vol. 21, no. 1, pp. 10-18, 2025, doi: 10.3969/j.issn.1673-3908.2025.01.003.
M. McCampbell, C. Schumann, and L. Klerkx, “Good intentions in complex realities: Challenges for designing responsibly in digital agriculture in low-income countries,” Sociologia Ruralis, vol. 62, no. 2, pp. 279-304, 2022, doi: 10.1111/soru.12359.
R. Chandra and S. Collis, “Digital agriculture for small-scale producers: challenges and opportunities,” Communications of the ACM, vol. 64, no. 12, pp. 75-84, 2021, doi: 10.1145/3454008.
R. Birner, T. Daum, and C. Pray, “Who drives the digital revolution in agriculture? A review of supply-side trends, players and challenges,” Applied economic perspectives and policy, vol. 43, no. 4, pp. 1260-1285, 2021, doi: 10.1002/aepp.13145.
S. Cook, L. Jackson E, J. Fisher M, et al., “Embedding digital agriculture into sustainable Australian food systems: pathways and pitfalls to value creation,” International Journal of Agricultural Sustainability, vol. 20, no. 3, pp. 346-367, 2022, doi: 10.1080/14735903.2021.1937881.
J. Liu and P. Sengers, “Legibility and the legacy of racialized dispossession in digital agriculture,” Proceedings of the ACM on Human-Computer Interaction, vol. 5, no. CSCW2, pp. 1-21, 2021, doi: 10.1145/3479867.