Does Digital Transformation Promote Agricultural Carbon Productivity in China?

Abstract

Against the background of global climate change and the rapid rise of the digital economy, the digital transformation of agriculture is profoundly changing the agricultural production and operation mode with the help of digital technology, becoming a new driving force for low-carbon and sustainable development of agriculture. However, previous studies rarely examined the impact of agricultural digital transformation on agricultural low-carbon transformation from the perspective of carbon productivity. To fill this gap, this study attempts to build a theoretical analysis framework for the impact of agricultural digital transformation on agricultural carbon productivity (ACP). By using a set of panel data from 30 provinces (cities) in China from 2011 to 2019, this study explores the impact of agricultural digital transformation on ACP, as well as its conduction mechanism and the non-linear mechanism. Empirical results show that the transformation of agricultural digitalization is conducive to the promotion of ACP. A series of robustness analyses support this conclusion. The main transmission mechanisms for digital transformation to affect ACP include agricultural industrial structure upgrading, and the agricultural scale operation. In addition, with the improvement of urbanization level and rural human capital, the impact of agricultural digital transformation on ACP presents a “U” type non-linear feature of inhibition first and promotion later. Furtherly, heterogeneity analysis shows that the impact of digital transformation on ACP will vary greatly depending on the levels of ACP, the geographical location of the studied area and whether it is a main grain-producing area. This study provides a theoretical and empirical basis for the improvement of China’s agricultural carbon productivity from the perspective of the digital economy.

The spatiotemporal characteristics and obstacle factors of the coupled and coordinated development of agricultural and rural digitalization and food system sustainability in China

“…It also takes Chinese PAAs as the research object and measures the comprehensive development index of each PAA from 2011 to 2020, respectively, using the entropy weight method. The results show that the development (Tang and Chen, 2022;Xu et al, 2022). For the measurement of FSS, existing studies mainly focus on economically developed countries, including the United States (Heller and Keoleian, 2003), the United Kingdom (Yakovleva, 2007), Japan (Tsuchiya et al, 2021), and Germany (Keuter et al, 2021), etc., while studies for developing countries are still scarce.…”

“…In addition, existing measurement studies on the ARD mainly focus on a local area (Zhao and Li, 2022;Zhu et al, 2023) and regions (states, provinces, or cities, etc.) within a country (Tang and Chen, 2022;Xu et al, 2022), and there is a lack of comparative studies on different regions within a country. In contrast, current measures of FSS tend to be based on characteristic facts and national policies from a holistic perspective but do not specifically address FSS in regions (states, provinces, cities, etc.)…”

Enabling In-Situ Urbanization through Digitalization

“…Evidence proves that the digital transformation is radically changing constellations and processes of production, marketing, and consumption in the agrifood system, helping farmers deliver safe, sustainable, and quality food [50]. However, it can also be more adaptive to climate change [51]. In addition to upgrading traditional agriculture, digitalization-enabled rural growth is more prominent and empowered by the so-called "rural industry", which refers to the dominant non-agricultural industry, either in manufacture or services, in one township and surrounding villages [13].…”

Research on the Carbon Reduction Effect of Digital Transformation of Agriculture in China

“…Referring to Fang et al ( 2021) [38] and Guo & Zhang (2023) [5], and Xu et al (2022) [39], this article considers the control variables affecting carbon emissions of agriculture by including the degree of urbanization (urb), the degree of agricultural mechanization (machine), natural disasters (disas), and resource consumption (elect) measured by the proportion of urban population to total population, total power of agricultural machinery, crop affected area, and rural electricity consumption, respectively.…”