From weather reliance to digital empowerment: the role of the digital economy in enhancing agricultural industry resilience

Abstract

Introduction:

Traditional agriculture is highly dependent on climatic conditions, making its output particularly sensitive to climate variability. The uncertainties associated with climate change pose ongoing challenges to agricultural industry resilience (AIR). In this context, the development of the digital economy is facilitating a shift from climate-dependent production to digitally empowered agriculture.

Methods:

This study empirically examines the impact of the digital economy on AIR using panel data from 30 Chinese provinces over the period 2011–2022.

Results:

The results indicate that the digital economy significantly enhances AIR, with a pronounced nonlinear relationship: as the level of digital economy development increases, its marginal empowering effect gradually diminishes, consistent with the typical pattern of technology diffusion. Mechanism analysis reveals that the digital economy strengthens AIR through three main pathways: promoting agricultural technological innovation, accelerating digital transformation, and improving production efficiency. Heterogeneity analysis further shows that the empowering effect of the digital economy is more pronounced in non-major grain-producing regions, areas with lower levels of agricultural modernization, and regions with higher degrees of population aging. This highlights the role of digital development in addressing structural weaknesses in traditional agriculture and alleviating resource constraints.

Discussion:

This study provides empirical evidence on the complex nonlinear relationship between digital technologies and agricultural resilience, offering theoretical insights and practical guidance for policymakers to implement targeted digital strategies.

1 Introduction

In the context of intensifying climate change, ecological degradation, and rising global economic uncertainty, the sustainability of agricultural systems has become a critical issue for achieving the United Nations Sustainable Development Goals. Agriculture not only serves as a fundamental pillar of food security and economic development but also plays a crucial role in ecosystem conservation and regional coordinated development (; ). Under the combined influence of multiple external shocks—such as climate variability, geopolitical conflicts, and economic fluctuations—agricultural production systems are facing heightened uncertainty, posing severe challenges to their stability, adaptability, and resilience (; ). Against this backdrop, enhancing AIR and promoting the green, intelligent, and sustainable transformation of agriculture has emerged as a key research agenda.

Traditional agricultural production is highly dependent on favorable climatic conditions. Disasters such as droughts, floods, and extreme temperatures directly affect the stability of agricultural outputs. AIR is a critical metric that captures the capacity of agricultural systems to withstand shocks, maintain core functions, and adapt structurally under complex and uncertain environments (; ). Unlike metrics focusing solely on output or productivity, resilience emphasizes system-level, dynamic, and long-term perspectives, reflecting the ability of agricultural systems to absorb shocks, recover, and regenerate. AIR encompasses multiple dimensions, including stability and carrying capacity, adaptive recovery capability, and innovation support capability. In particular, in developing countries or major agricultural nations, enhancing AIR is fundamental for ensuring food security, narrowing urban–rural disparities, promoting rural revitalization, and building a modern agricultural system.

The rapid development of the digital economy presents new opportunities for the sustainable transformation of agricultural systems (). Digital technologies have increasingly permeated all stages of agricultural production, management, distribution, and consumption, driving agriculture toward greater intelligence, precision, and interconnectedness. In China, the “Digital Agriculture and Rural Development Plan (2019–2025)” explicitly emphasizes digitalization as a key driver of agricultural and rural modernization. In this context, the digital economy not only reshapes agricultural value chains but also significantly improves resource allocation efficiency and organizational practices (). This transformation reflects a profound shift in production paradigms, from weather-dependent and passive risk management to digitally empowered, proactive control. However, while the digital economy can enhance efficiency and resilience, it may also exacerbate structural disparities due to uneven regional development and unequal resource access, resulting in a “digital divide.” This underscores a critical challenge: moving beyond mere infrastructure expansion toward substantive empowerment, whereby digital technologies genuinely enhance agricultural industrial resilience. Therefore, a systematic assessment of the pathways and boundary conditions through which the digital economy impacts agricultural systems is necessary.

Based on this context, this study evaluates agricultural system sustainability from the perspective of AIR. Using panel data from 30 Chinese provinces between 2011 and 2022, it systematically analyses the effects of the digital economy on agricultural sustainability and its underlying mechanisms. Specifically, the study first identifies the overall effect of the digital economy, then uncovers the internal pathways through technological innovation, digital transformation, and productivity enhancement, thereby illustrating the transition from weather-dependent to digitally empowered agriculture. Moreover, threshold models are employed to examine nonlinear effects across different development stages, while regional and structural heterogeneity are considered to investigate contextual variations in the digital economy’s impact.

The main contributions of this study can be summarized in three aspects. First, from the perspective of agricultural system sustainability, we reconstruct the AIR indicator framework, clearly defining three key dimensions: stability and carrying capacity, adaptive recovery capability, and innovation support capacity. This extends the analytical scope and theoretical boundaries of existing research, providing a more systematic and comprehensive tool to measure the overall resilience of agricultural systems under complex and uncertain environments. Second, the study reveals the mechanisms through which the digital economy enhances AIR via three pathways: technological innovation, digital transformation, and improvements in production efficiency. Empirically, we systematically identify the effects of these mechanisms across regions and development stages. Theoretically, by integrating complex systems theory with innovation diffusion theory, we illustrate how technological innovation strengthens system adaptability and recovery by enhancing information acquisition and decision-making capabilities, how digital transformation improves agricultural resilience through optimized organizational structures and resource allocation, and how increased production efficiency reinforces the system’s stability and carrying capacity. This combined theoretical and empirical analysis not only clarifies the pathways through which the digital economy enhances AIR but also provides a logical basis for understanding its heterogeneous effects across different contexts. Third, with regard to nonlinearity and heterogeneity, the study conducts differentiated analyses based on agricultural production function, development stage, and factor endowment differences. Specifically, it examines the effects of the digital economy across major versus non-major grain-producing regions, levels of agricultural modernization, and degrees of population aging. This allows us to identify diversified pathways through which the digital economy influences AIR, offering both theoretical grounding and empirical evidence to support context-specific digital empowerment strategies.

The remainder of the paper is organized as follows: Section 2 presents the literature review; Section 3 develops the theoretical framework and hypothesis development; Section 4 outlines the research design; Section 5 reports the empirical results and discussion; and the final section provides the conclusions, policy recommendations and study limitations.

2 Literature review

Research on AIR has primarily focused on its conceptual definition, the construction of evaluation indicator systems, analysis of influencing factors, and pathways for enhancement.

In terms of conceptual studies of AIR, the definition has evolved from a single-dimensional perspective to a multidimensional one. Early studies mainly emphasized the resistance capacity of agricultural systems. For example, argued that agricultural resilience reflects the system’s ability to maintain stable operation when facing shocks. further conceptualized resilience as the ability to absorb external shocks and return to a normal state, highlighting that the system not only needs to withstand stress but also possesses rapid recovery characteristics. Building on this, scholars have further emphasized both the system’s capacity to endure shocks and the efficiency of post-shock recovery, suggesting that resilience encompasses not only the ability to resist pressure but also the speed and extent of recovery (). As research perspectives have expanded, some scholars have extended the analytical scope to cover the entire agricultural value chain, including production, processing, distribution, and consumption, arguing that agricultural value chain resilience represents the integrated capability of all segments to maintain core functions, achieve dynamic restoration, and pursue new development pathways under uncertain shocks (). Overall, despite differences in emphasis across studies, a growing consensus has emerged that agricultural value chain resilience is a multidimensional and composite concept encompassing shock resistance, recovery capacity, and dynamic adaptive capability.

Regarding the influencing factors of agricultural value chain resilience, existing studies have identified key drivers from multiple perspectives. From the perspective of factor inputs, the level of human capital accumulation, the intensity of investment in scientific research and innovation, and the adequacy of infrastructure such as farmland irrigation and storage and logistics facilities constitute the fundamental support conditions for enhancing resilience (; ). From the perspective of industrial organization, the degree of coordination within agricultural industrial alliances and the smoothness of benefit linkage mechanisms among different segments of the value chain significantly affect the overall risk resistance of the chain (). From the perspective of the external environment, the continuity and stability of institutional provision, the extent of market-oriented reforms, and the soundness of risk warning and emergency management systems collectively shape the external conditions for agricultural value chain resilience (). Moreover, some studies have examined the “stress-testing” effects of natural disasters and market fluctuations on agricultural value chain resilience, providing empirical insights into its performance under real-world shocks (). Building on this, with the accelerated penetration of digital technologies into the agricultural and rural sectors, the digital economy has gradually emerged as an important new factor influencing agricultural resilience. Existing studies have explored the mechanisms through which the digital economy affects agricultural systems from various angles. using a difference-in-differences model, found that the development of the digital economy significantly enhances food system resilience. () argued that the digital economy strengthens agricultural systems’ ability to withstand external shocks by optimizing resource and factor allocation. Furthermore, indicates that the digital economy exerts a significant positive effect on agricultural economic resilience, with industrial upgrading serving as an important transmission pathway. taking a regional heterogeneity perspective, found that the promoting effect of digital technologies on agricultural resilience varies across regions, being particularly pronounced in eastern China.

A systematic review of the existing literature indicates that significant progress has been made in defining the concept of agricultural value chain resilience, constructing measurement systems, analyzing influencing factors, and exploring enhancement pathways, thereby laying a solid foundation for further research. However, there are still several areas that require further development: First, in terms of the measurement system, although previous studies have attempted to conduct quantitative analyses of agricultural value chain resilience from a multidimensional perspective, there remain issues related to the scattered selection of indicators and insufficient theoretical integration. There is a lack of a unified and highly explanatory analytical framework across studies, which to some extent affects the comparability and stability of measurement results. Second, regarding the mechanisms, existing literature mainly focuses on empirical relationship testing and lacks systematic integration of the underlying transmission paths that influence agricultural resilience, especially in key processes such as technological innovation, information flow and feedback regulation mechanisms, and improvements in resource allocation efficiency. The theoretical explanations in these areas still require further refinement. Third, in terms of research methodology, most studies are based on linear analytical frameworks and give insufficient attention to the stage-specific characteristics, nonlinear relationships, and heterogeneity under different agricultural production conditions or regional development levels. As a result, this limits the depth of interpretation of conclusions and the policy implications derived from them.

Based on the existing research, this study aims to further integrate and expand the analytical framework of agricultural value chain resilience from the perspective of agricultural system sustainability. By combining nonlinear analysis and mechanism testing methods, it systematically explores the pathways and mechanisms through which the digital economy empowers agricultural resilience, with the aim of providing valuable insights to complement related research.

3 Theoretical analysis and hypothesis development

3.1 Digital economy and AIR

AIR reflects the overall capacity of agricultural systems to withstand disturbances, adapt, and sustain development in the face of external shocks. Its formation relies on the efficiency of internal resource allocation, the effectiveness of information transmission mechanisms, and the flexibility of organizational structures (). In traditional agricultural systems, production decisions heavily depend on natural conditions and experiential judgment, while information acquisition is costly and often significantly asymmetric, making the system prone to delayed responses and rigid adjustments when facing climate variability, market shocks, or policy changes ().

Digital economy, through the capitalization of data as a production factor and the pervasive penetration of digital technologies, is reshaping the operational paradigm of agricultural systems and offering new pathways to enhance agricultural sustainability (). In the dimension of resistance, platform economies improve market efficiency and information transparency in agricultural factor markets (; ), optimize spatiotemporal resource allocation, and bolster the system’s capacity for rapid response to unexpected events (). In the adaptation dimension, digital tools facilitate sharing and organizational learning among agricultural stakeholders, strengthening dynamic adjustment and feedback mechanisms within the system (; ). In the transformation dimension, digitally enabled ecosystems foster new organizational forms and industrial models that drive the intelligent and green transformation of agricultural value chains, expanding the system’s capacity for self-evolution amid complex environments (; ). This constructs a closed-loop perceive–feedback–transform capability within agricultural systems, making the digital economy a potential cornerstone of sustainability support. In China, agricultural digitization is transitioning from infrastructure to deep integration, while the risk of digital divide still exists, the digital economy as a whole is more likely to show the effect of elastic bridge. Through information symmetry, efficiency improvement and innovation mode, the coordination and change flexibility of the whole system are enhanced.

From the perspective of system evolution, the impact of the digital economy on agricultural sustainability may not follow a linear upward trajectory. In the early stages of development, enabling investments such as the construction of digital infrastructure and the introduction of platforms can rapidly enhance the system’s capacity for resource integration and risk resistance. However, at more advanced stages, as the technological dividends become saturated and marginal returns diminish, the system’s ability to absorb additional digital inputs becomes a key determinant of the effectiveness of sustainable transformation. This dynamic evolutionary pattern suggests that the digital economy’s impact on agricultural system sustainability exhibits clear stage-dependent and threshold characteristics.

Based on this, this article proposes the core hypothesis:

H1: The development of the digital economy positively enhances AIR, and this effect exhibits nonlinear threshold characteristics.

3.2 Mediating pathways of digital economy on AIR

This study uses the Complex Adaptive Systems (CAS) theory as a theoretical foundation to examine the transmission pathways through which the digital economy affects agricultural industry resilience. CAS theory posits that a system’s resilience in the face of external disturbances stems from three intrinsic mechanisms: ① Learning and innovation mechanism, whereby the system adapts to environmental changes through variation, selection, and retention. ② Information flow and feedback regulation mechanism, where the system achieves dynamic coordination through real-time information exchange. ③ Resource reallocation and efficiency mechanism, where the system buffers shocks through flexible resource deployment (). The agricultural industry, as a typical CAS unit, exhibits resilience in terms of the continuous production capacity of production units, the coordination and reconfiguration ability of the industrial chain, and the overall stability and recovery capacity of regional agricultural systems when facing environmental or market shocks (). The digital economy, with data as a core production factor, reduces information processing and coordination costs and can specifically enhance the above three resilience mechanisms, transmitting its impact on agricultural industry resilience through three mediating pathways: agricultural technological innovation, agricultural digital transformation, and improvement in agricultural production efficiency.

First, the mediating pathway of agricultural technological innovation. According to CAS theory, the system’s learning and innovation mechanism is the long-term adaptive basis for resilience: a system needs to continuously update its technologies and organizational forms to cope with unpredictable shocks (). In traditional agricultural systems, technological innovation is constrained by regional segmentation, slow accumulation of experience, and high knowledge diffusion