Research on the Effects and Mechanisms of Digital Intelligence on Agricultural Carbon Emissions

Hesi Pan and Dingzhen Xing ()
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Hesi Pan: Harbin University of Commerce, School of Economics
Dingzhen Xing: Harbin University of Commerce, School of Economics

A chapter in Proceedings of the 2025 7th International Conference on Economic Management and Cultural Industry (ICEMCI 2025), 2025, pp 598-617 from Springer

Abstract: Abstract To synergistically promote the development of new quality agricultural productivity and accelerate the comprehensive green and low-carbon transformation of the economy and society. Based on the constructed Numerical Intelligence Indicator System, this paper quantitatively measures the development level of Numerical Intelligence in each province based on the panel data of 30 provinces (except Tibet, Hong Kong, Macao, and Taiwan) from 2011–2022, and constructs a two-way fixed model, mediation effect model, and threshold effect model to examine the effect and mechanism of Numerical Intelligence on agricultural carbon emission reduction. The study finds that digital intelligence has a significant effect on agricultural carbon emission reduction, and the conclusion still holds after a series of robustness tests. Numerical Intelligence promotes agricultural carbon emission reduction by promoting green technology innovation and improving rural human capital. The results of the threshold effect show that the inhibitory effect of digital intellectualization on agricultural carbon emissions is also affected by the degree of government intervention and the level of agricultural mechanization. Further, there is significant regional and environmental regulation heterogeneity in the impact of Numerical Intelligence on agricultural carbon emissions. In both the central and northeastern regions, Numerical Intelligence shows a significant inhibitory effect, and the effect is greater in the northeastern region; the emission reduction effect is significant in regions with high levels of environmental regulation.

Keywords: Digital Intelligence; Agricultural Carbon Emission; Green Low-Carbon (search for similar items in EconPapers)
Date: 2025
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DOI: 10.2991/978-94-6463-888-2_58

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