Digital agricultural technology innovation and agricultural green total factor productivity: county-level evidence from China

Abstract

Digital agricultural technology innovation (DATI) has become an important driver of agricultural modernization and green transformation. By integrating county-level socioeconomic statistics with agricultural patent records, this study develops a county-level measure of DATI and provides more fine-grained evidence on how digital agricultural technology innovation affects agricultural green total factor productivity in China. Using a balanced panel of Chinese counties data from 2014 to 2021, we examine the effect of DATI on agricultural green total factor productivity (AGTFP). The results reveal three main findings. First, DATI significantly improves AGTFP, although its effects differ across regions, digital infrastructure endowments, and agricultural development conditions. Second, the effect of DATI on AGTFP displays pronounced threshold characteristics, with digital infrastructure and fiscal support for agriculture acting as key threshold variables; once the relevant thresholds are crossed, the estimated effect turns from negative to positive. Third, DATI exhibits significant spatial dependence, but its spatial spillover effects are limited, indicating that the green productivity gains generated by digital agricultural technology innovation remain largely localized. These findings provide fine-grained county-level evidence on the role of DATI in promoting green agricultural development and underscore the need to strengthen rural digital infrastructure, deepen the application of digital technologies in agricultural production, and tailor the coordinated digital and green transformation of agriculture to local conditions.

1 Introduction

Agricultural green total factor productivity is widely recognized as a key indicator of agricultural green development and sustainability. Enhancing AGTFP is essential not only for improving resource-use efficiency and environmental performance but also for advancing agricultural modernization and rural revitalization. In recent years, the rapid integration of digital technologies into agricultural production has created new opportunities for agricultural green transformation. Existing studies suggest that digital technologies can improve information acquisition, expand market access, and enhance resource allocation efficiency, thereby promoting agricultural performance and rural development (; ; ). Meanwhile, the proliferation of digital platforms, e-commerce networks, and information and communication technology (ICT) services has significantly expanded market opportunities and improved agricultural productivity, particularly in rural areas where traditional information channels remain limited (; ; ). Digital agricultural technology innovation, represented by big data, artificial intelligence (AI), smart agricultural machinery, and digital management platforms, has emerged as a critical force driving agricultural green development.

The relationship between digitalization and AGTFP has attracted increasing attention in the agricultural economics. Existing evidence indicates that digital technologies can promote AGTFP through technological innovation, industrial upgrading, and improvements in production efficiency (; ; ). From green development perspective, technological innovation is widely regarded as a fundamental driver of green productivity growth, as it enhances resource-use efficiency, reduces environmental costs, and facilitates environmentally directed technological change (; ). These findings suggest that digital agricultural technology innovation is not only an important manifestation of agricultural digital transformation but also a potential pathway for simultaneously achieving productivity growth and environmental sustainability.

However, the effectiveness of digital agricultural technology innovation depends on the successful adoption and diffusion of new technologies. Existing studies emphasize that learning processes, social interactions, and absorptive capacities are crucial in determining whether technological advances can be translated into productivity gains (; ; ). As digital technologies become increasingly embedded in agricultural production systems, digital agricultural technology innovation can accelerate the diffusion of green technologies, improve production efficiency, reduce production risks, and facilitate agricultural modernization (; ). Nevertheless, its impacts are unlikely to be uniform across regions, as they are conditioned by differences in digital infrastructure, institutional environments, and local absorptive capacities. Existing evidence further shows that high-quality innovation can significantly enhance green productivity and strengthen the environmental benefits of technological progress (; ). Moreover, innovation activities often generate knowledge diffusion and interregional learning effects, enabling technological benefits to extend beyond local jurisdictions (; ). Given that knowledge spillovers and factor mobility frequently transcend administrative boundaries, innovation activities tend to exhibit significant spatial dependence and spillover effects (; ). Therefore, digital agricultural technology innovation may not only improve local AGTFP but also promote agricultural green development in neighboring regions through technology diffusion and knowledge spillovers.

Overall, existing studies have highlighted the positive role of digitalization in agricultural green development. However, several important gaps remain. First, most existing studies rely on provincial- or prefecture-level data, while county-level evidence remains relatively scarce despite counties being the primary units for agricultural production and technology adoption in China. In China, counties constitute a key spatial unit for agricultural production, technology extension, infrastructure provision, and rural policy implementation, and a large share of agricultural activities is organized at the county level. Compared with analyses based on provincial or prefecture-level data, a county-level approach can more precisely capture local heterogeneity in agricultural resource endowments, digital infrastructure, technology diffusion capacity, and policy implementation. This finer spatial scale is therefore particularly suitable for examining the effect of digital agricultural technology innovation on agricultural green total factor productivity. By combining county-level panel data with an SBM-based measure of AGTFP that accounts for undesirable outputs, this study provides a more disaggregated empirical assessment of the green productivity effects of digital agricultural technology innovation. In doing so, it extends the literature on digital agriculture and agricultural green development by moving beyond broad measures of digitalization and by identifying the role of agricultural digital innovation at the spatial level where agricultural technologies are adopted and rural policies are implemented.

Digitalization is typically measured using broad indicators such as digital economy indices, internet penet ration rates, or digital finance indicators, whereas relatively few studies directly capture digital agricultural technology innovation from the perspective of agricultural digital innovation and agricultural technology patents. Third, although increasing attention has been paid to threshold effects and spatial dependence, a unified analytical framework integrating digital agricultural technology innovation, threshold effects, spatial spillovers, and AGTFP remains underdeveloped. To address these gaps, this study employs Chinese county-level panel data and incorporates digital agricultural technology innovation, threshold models, and spatial Durbin models into a unified analytical framework to systematically examine the impact of digital agricultural technology innovation on AGTFP and its underlying mechanisms. This study provides new county-level evidence on how digital agriculture contributes to agricultural green transformation and sustainable development.

This study contributes to the existing literature in three principal respects. First, it shifts the analytical focus from general digitalization to digital agricultural technology innovation. Using county-level agricultural patent information, we capture the creation and accumulation of digital technological knowledge in agriculture and examine how agricultural digital technologies affect county-level AGTFP. Second, the study provides county-level evidence and thereby addresses the relative scarcity of fine-grained empirical evidence in the existing literature. Counties are key spatial units for agricultural production, technology adoption, infrastructure provision, and rural policy implementation in China; thus, a county-level perspective allows for a more precise identification of local heterogeneity in the effect of digital agricultural technology innovation on AGTFP. Third, within an integrated framework linking digital agricultural technology innovation and green productivity, this study examines whether DATI improves AGTFP, thereby deepening our understanding of the mechanisms through which digital agriculture contributes to green agricultural transformation.

2 Theoretical analysis and research hypotheses

2.1 Digital economy and agricultural green total factor productivity

Digital economy has become an important driver of agricultural green transformation. find that digital inclusive finance significantly improves AGTFP by promoting agricultural technological innovation and industrial structure optimization. emphasize that digital finance promotes AGTFP partly through digital village development. explored the impact of digital transformation on supply chain resilience among Chinese listed agricultural firms. The results demonstrate that digital transformation significantly enhances supply chain resilience. Overall, this strand of literature suggests that the digital economy improves AGTFP through digital infrastructure, financial inclusion, agricultural innovation, industrial upgrading, and rural digital transformation. Recent studies have extended this line of research from the perspectives of digitalization, digital technology adoption, and digital village development. shows that the use of digital technologies can effectively improve agricultural productivity across EU countries. further indicate that ICT adoption contributes to higher land and labor productivity in agriculture. provide recent evidence that agricultural and rural digitalization significantly increases agricultural green total factor productivity (AGTFP), while show that digital village development affects AGTFP through both supply-side and demand-side mechanisms. Taken together, the existing literature suggests that the digital economy can improve AGTFP through digital infrastructure, financial inclusion, agricultural innovation, industrial upgrading, ICT diffusion, and rural digital transformation. Based on the above analysis, we propose research hypothesis 1 as follows:

H1: Digital technology applications significantly promote AGTFP.

2.2 Digital technology applications and agricultural green total factor productivity

Another strand of literature focuses on the application of digital technologies in agricultural production. show that big data in smart farming improves decision-making efficiency across agricultural production and the food supply chain. show that digital agriculture development significantly contributes to AGTFP improvement. demonstrate that deep learning can be applied to crop monitoring, disease detection, yield prediction, and agricultural automation. shows that meaningful participation in digital technologies varies across actors, and that differences in technological perceptions and interpretations influence the diffusion and adoption of digital agricultural technologies. emphasize that farmers’ technology adoption behavior determines whether precision agricultural technologies can effectively improve production efficiency. Therefore, digital technology applications promote AGTFP mainly by improving input-use efficiency, reducing agricultural pollution, strengthening monitoring capacity, and improving production decision-making.

Digital agricultural technologies are not merely general ICT applications, but are embedded in agricultural production systems, farm management, and technology adoption decisions. discuss the opportunities and potential dilemmas associated with agricultural digitalization, suggesting that digital transformation in agriculture should be evaluated in relation to production efficiency, inclusiveness, and sustainability. emphasizes that digital transformation of the agricultural sector can reshape production practices through data collection, monitoring, decision support, and precision input application. further show that the digital revolution in agriculture is driven not only by farmers’ demand but also by supply-side actors, including input firms, software providers, digital service platforms, and technology start-ups. argues that digital innovations can contribute to sustainable and resilient agricultural systems by improving productivity, reducing environmental pressure, and strengthening adaptive capacity. also show that farmers’ preferences and perceived technology attributes are important determinants of precision farming adoption. In addition, agricultural technology innovation and agricultural patents provide an important foundation for understanding DATI. examine China’s agricultural patents and show that agricultural patent value has changed amid the rapid expansion of patent applications, indicating that agricultural patents can reflect important dimensions of agricultural technological innovation. Related studies highlight the roles of environmental regulation, digital technologies, and technological progress in agricultural green development. shows that environmental regulation promotes agricultural green innovation and AGTFP, emphasize the potential of agricultural IoT for monitoring, precision management, and data-driven decision-making. further demonstrate that green innovation, human capital, and infrastructure are important drivers of agricultural green productivity growth.

In this study, the role of agricultural technological innovation is conceptualized as a transmission mechanism rather than a moderating effect. A moderating effect would imply that agricultural technological innovation changes the strength or direction of the relationship between digital technology applications and AGTFP. However, our theoretical framework emphasizes that digital agricultural technology applications affect AGTFP through specific transmission channels. More specifically, digital agricultural technologies improve agricultural production efficiency, enhance agricultural value creation, facilitate technology adoption and diffusion, and improve rural development conditions. These changes subsequently contribute to the improvement of AGTFP. Therefore, the mechanism is examined through channel variables that capture productivity enhancement and rural development improvement. Based on the above analysis, we propose research hypothesis 2 as follows:

H2: Digital agricultural technology applications promote AGTFP by enhancing agricultural value creation and improving rural development conditions.

2.3 Spatial effects of digital agricultural technology innovation on agricultural green total factor productivity

According to the theories of new economic geography and spatial spillovers, knowledge, technology, and production factors can flow across regional boundaries, thereby generating significant spatial interactions. Digital agricultural technology innovation is characterized by strong openness, connectivity, and diffusibility. Consequently, it may not only improve local AGTFPbut also influence on neighboring regions through knowledge spillovers, technology diffusion, and factor mobility. Existing studies have documented significant spatial spillover effects of digitalization. found that the digital economy promotes agricultural green development and generates positive effects on neighboring regions through spatial interaction mechanisms. further demonstrated that the digital economy exerts significant spatial spillover effects on green total factor productivity, primarily through green technological innovation and industrial upgrading. showed that carbon trading policies not only improve AGTFP in pilot regions but also generate spillover effects on surrounding areas through technology diffusion and policy transmission. found that the digital economy significantly enhances green total factor productivity and exhibits strong spatial dependence. further confirmed that the digital economy improves green productivity through technological innovation diffusion and cross-regional factor mobility, thereby generating significant spatial spillover effects. Therefore, the knowledge spillover, technology diffusion, and resource allocation effects generated by digital agricultural technology innovation may extend beyond administrative boundaries and influence AGTFP in neighboring regions. Digital agricultural technology innovation may not only promote local agricultural green transformation but also facilitate agricultural green development in surrounding regions through interregional learning and information sharing. Based on the above analysis, the following hypothesis is proposed:

H3: Digital agricultural technology innovation exhibits spatial correlation and generate positive spatial spillover effects on agricultural green total factor productivity.

To clarify the theoretical basis of Figure 1, this study constructs the analytical framework by integrating technological innovation theory, innovation diffusion theory, green total factor productivity theory, and agricultural sustainable development theory. Digital agricultural technology innovation (DATI) refers to the innovation, diffusion, and application of digital technologies in agricultural production, agricultural resource allocation, rural governance, and agricultural industrial chains. It includes not only the generation of digital agricultural technologies, such as digital patents and intelligent agricultural equipment, but also their practical application in agricultural production and rural development.

Figure 1

Based on this conceptual framework, DATI affect AGTFP through three main pathways. First, the application of digital technologies in agriculture promotes agricultural digitalization and intelligent transformation, improves the allocation and utilization efficiency of agricultural resources, and thereby facilitates the green transformation of agricultural production. Second, DATI accelerates agricultural technology diffusion and innovation, promotes the modernization of agricultural industrial chains, and enhances agricultural technological progress and industrial upgrading. Third, DATI supports rural digitalization and green transformation, improves the rural ecological environment and factor mobility, and thus creates favorable conditions for the growth of AGTFP. Figure 1 illustrates these theoretical mechanisms.

3 Data, variables and methodology

3.1 Empirical model

The empirical models are organized according to the research hypotheses. Equation 1 is used to estimate the baseline effect of DATI on AGTFP. Equation 2 is used