In the face of escalating challenges from extreme weather events to volatile global markets, traditional agricultural production models are being pushed to their limits. This has prompted policymakers and researchers to increasingly view digital and intelligent technologies not as optional enhancements, but as essential tools for building resilience in agricultural systems. A recent study from China, published in the journal Sustainability, sheds light on how the integration of these technologies with policy, infrastructure, and organizational capacity can determine the resilience of agricultural systems under stress.
The study, titled “Diverse Pathways for Digital and Intelligent Technologies to Enhance Resilience in the Agricultural Industry Chain—A Configuration Analysis Based on 99 Prefecture-Level Cities in China’s Yellow River Basin,” explores this critical issue. It reveals that digital intelligence is emerging as a core driver of agricultural resilience, which is now defined not just by yields or recovery speed after disruptions, but by a system’s ability to anticipate risks, maintain functional continuity, adapt to shocks, and regenerate through innovation.
The Yellow River Basin, a key region for grain and specialty crop production spanning eastern, central, and western China, faces particularly acute pressures. The researchers applied a configurational analytical approach to data from 99 prefecture-level cities in this region. This method captures the complexity of agricultural systems by examining how combinations of conditions jointly produce high resilience outcomes. The findings are clear: no single factor, whether digital technology adoption, fiscal investment, or economic development, is sufficient on its own to guarantee resilience. Instead, digital and intelligent technologies consistently appear as central enabling forces across all successful configurations.
Digital intelligence technologies, as defined in the study, include data-driven systems, artificial intelligence applications, networked platforms, and smart infrastructure that support various aspects of agricultural production, processing, logistics, and coordination. These technologies improve real-time monitoring, enhance decision-making accuracy, and strengthen information flows across fragmented agricultural chains. In regions where climate variability, market uncertainty, and logistical bottlenecks are common, such capabilities significantly reduce vulnerability. The study underscores that digital infrastructure, including internet penetration and telecommunications capacity, is just as critical as advanced applications themselves. Without reliable connectivity, even sophisticated technologies fail to translate into operational resilience. Thus, digital intelligence functions as a system-level capability that amplifies the effectiveness of organizational and policy inputs.
The study identifies four distinct pathways through which agricultural industrial chain resilience can be achieved. Each pathway reflects a different configuration of technology, organizational capacity, fiscal support, and policy environment, revealing that resilience is not a one-size-fits-all outcome. The first pathway, technology-enabled resilience, applies to regions with well-developed digital infrastructure and mature agricultural business entities. Here, digital and intelligent technologies directly drive efficiency, coordination, and risk mitigation, with agricultural operators acting as the primary agents translating technology into practice. Government fiscal investment and broader economic conditions play a less decisive role in these areas.
The second pathway, information-driven resilience, highlights regions with strong digital infrastructure but limited fiscal support or weaker digital policy environments. In such contexts, advanced information systems and intelligent technologies substitute for formal institutional backing. Data sharing, early warning systems, and intelligent coordination mechanisms allow agricultural chains to maintain stability despite funding gaps. The study shows that robust digital information environments can partially offset policy and financial limitations by enabling faster responses to disruptions and more efficient resource allocation.
The third pathway, multi-stakeholder collaborative resilience, emerges in regions with strong economic foundations, substantial government fiscal investment, and advanced digital infrastructure. Here, resilience is achieved through the combined force of public investment, private sector participation, and technological integration. Government funding supports large-scale digital transformation projects, while enterprises and cooperatives leverage these investments to enhance coordination across production, processing, and distribution. This configuration represents the most comprehensive and resource-intensive approach, producing high resilience through systemic alignment.
The fourth pathway, policy-guided resilience, applies to regions with weaker economic bases and limited fiscal investment but strong digital policy frameworks and active agricultural operators. In these areas, policy guidance acts as a critical lever. Forward-looking digital agriculture policies, incentives, and institutional frameworks mobilize market actors and encourage technology adoption even in the absence of strong financial backing. Agricultural entities respond to policy signals by aligning operational strategies with digital transformation goals, creating resilience through coordinated adaptation rather than capital intensity.
Together, these pathways demonstrate that digital and intelligent technologies can function as both complementary and substitutive forces. In some regions, technology amplifies existing economic and fiscal strength. In others, it compensates for structural weaknesses. The implication is clear: agricultural resilience depends less on any single input and more on how resources are combined to fit local conditions.
The evidence suggests that uniform digital agriculture strategies are unlikely to succeed across diverse regions. Instead, governments must align digital investments, policy tools, and organizational support with the dominant resilience pathway in each area. In technology-enabled and information-driven regions, the priority is lowering adoption barriers for farmers and agricultural enterprises. Targeted subsidies, training programs, and partnerships with technology providers can help