Influence of data elements on China’s agricultural green total factor productivity

Exploring the effect and mechanism of data elements on agricultural green total factor productivity in China, has great significance for fully releasing the significant potential of data elements and promoting green agricultural development. Based on the panel data of China's 30 provinces from 2010 to 2022, this paper explored the fixed effects model to analyze the functional response of data elements on the agricultural green total factor productivity (AGTFP). The research finding shows that the data elements have significant promoting effects on the AGTFP, after a series of robustness and endogeneity tests. The mechanism analysis shows that the data elements can influence AGTFP via promoting labors' non-agricultural transfer, enhancing the optimum scale management, and driving agricultural technological innovation. The heterogeneity analysis revealed that the impact of data elements on AGTFP is more pronounced in China's western regions. The data elements are only significant on the southeast side of the 'Hu-Huanyong Line'. Based on the research findings, this paper proposes to expedite the interconnectivity and interoperability of data infrastructure, foster the development of advanced agricultural productivity, and facilitate green and sustainable agricultural growth through location-specific policies in years to come.

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Publication Details

Journal
Scientific Reports
Published
2025-08-26
DOI
https://doi.org/10.1038/s41598-025-16490-8
Citations
4
Primary Topic
Energy, Environment, Economic Growth
Type
article
Field-Weighted Citation Impact
12.52

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article

Influence of data elements on China’s agricultural green total factor productivity

Y. Sim Tang, Ruimin Qin, Guoqun Ma, Lei Shi
4 citations
Scientific Reports
Energy, Environment, Economic Growth
12.52
article

Influence of data elements on China’s agricultural green total factor productivity

Y. Sim Tang, Ruimin Qin, Guoqun Ma, Lei Shi
article en
4 citations

Abstract

Exploring the effect and mechanism of data elements on agricultural green total factor productivity in China, has great significance for fully releasing the significant potential of data elements and promoting green agricultural development. Based on the panel data of China's 30 provinces from 2010 to 2022, this paper explored the fixed effects model to analyze the functional response of data elements on the agricultural green total factor productivity (AGTFP). The research finding shows that the data elements have significant promoting effects on the AGTFP, after a series of robustness and endogeneity tests. The mechanism analysis shows that the data elements can influence AGTFP via promoting labors' non-agricultural transfer, enhancing the optimum scale management, and driving agricultural technological innovation. The heterogeneity analysis revealed that the impact of data elements on AGTFP is more pronounced in China's western regions. The data elements are only significant on the southeast side of the 'Hu-Huanyong Line'. Based on the research findings, this paper proposes to expedite the interconnectivity and interoperability of data infrastructure, foster the development of advanced agricultural productivity, and facilitate green and sustainable agricultural growth through location-specific policies in years to come.

Scientific ReportsVol. 15(1)
Guangxi Normal University (CN), Guilin University of Aerospace Technology (CN), Guilin University of Electronic Technology (CN)
National Social Science Fund of China
Zero hunger
Openalex Percentile: Top 2%
Energy, Environment, Economic Growth
12.52
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Influence of data elements on China’s agricultural green total factor productivity — Y. Sim Tang, Ruimin Qin, et al. · Scientific Reports (2025) | TGRS Research Map | TGRS