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Smart Agriculture ›› 2026, Vol. 8 ›› Issue (3): 203-214.doi: 10.12133/j.smartag.SA202602013

• 专刊--数字技术赋能与农业经济范式转型 • 上一篇    下一篇

数字技术驱动农业经济韧性提升:作用机理、实证检验及政策启示

朱孟帅, 黄明义, 沈辰, 迟亮, 张晶, 吴建寨()   

  1. 中国农业科学院农业信息研究所/农业农村部区块链农业应用重点实验室,北京 100081,中国
  • 收稿日期:2026-02-05 出版日期:2026-05-30
  • 基金项目:
    国家自然科学基金项目(42271313); 中央级公益性科研院所基本科研业务费专项(JBYW-AII-2025-25); 中国农业科学院科技创新工程项目(CAAS-ASTIP-2025-AII)
  • 作者简介:

    朱孟帅,博士,助理研究员,研究方向为农业经济政策。E-mail:

  • 通信作者:
    吴建寨,博士,研究员,研究方向为农业信息技术。E-mail:

Digital Technology Driving Agricultural Economic Resilience: Mechanism Analysis, Empirical Test, and Policy Implications

ZHU Mengshuai, HUANG Mingyi, SHEN Chen, CHI Liang, ZHANG Jing, WU Jianzhai()   

  1. Agricultural Information Institute, Chinese Academy of Agricultural Sciences/Key Laboratory of Agricultural Blockchain Application, Ministry of Agriculture and Rural Affair, Beijing 100081, China
  • Received:2026-02-05 Online:2026-05-30
  • Foundation items:National Natural Science Foundation of China(42271313); Central Public-interest Scientific Institution Basal Research Fund(JBYW-AII-2025-25); Chinese Academy of Agricultural Sciences Innovation Project(CAAS-ASTIP-2025-AII)
  • About author:

    ZHU Mengshuai, E-mail:

  • Corresponding author:
    WU Jianzhai, E-mail:

摘要:

【目的/意义】 提升农业经济韧性是保障国家粮食安全与促进乡村振兴的重要路径。本研究旨在探讨数字技术投入对农业经济韧性的驱动效应及内在机理,为制定差异化的数字农业政策提供理论参考。 【方法】 基于2012、2015、2017、2018、2020年中国省级面板数据,利用投入产出模型测算数字技术对农业的完全投入值,通过熵值法构建涵盖抵抗力、恢复力与发展力的评价体系,并运用工具变量法及中介效应模型进行实证检验。 【结果和讨论】 研究发现:(1)数字技术投入显著增强了农业经济韧性,且呈现出“强力驱动恢复力与发展力、弱影响抵抗力”的非对称特征;(2)机理分析表明,市场化进程、经济效率提升及交通密度优化是主要传导路径,其中市场化路径的贡献最为显著;(3)异质性分析显示,数字技术在西部地区及粮食主销区表现出明显的“数字补偿”优势,而农村合作社的组织效应在数字化进程中尚未得到充分释放。 【结论】 数字技术能显著提升农业经济韧性,且影响具有时空异质性和非对称性。应加强基础设施建设,优化数字技术要素配置,实施差异化扶持策略,加强人力资本投入,以全面提升农业经济韧性。

关键词: 数字技术投入, 农业经济韧性, 投入产出表, 信息和通信技术投入

Abstract:

[Objective] Enhancing agricultural economic resilience is a critical strategic path for ensuring national food security and promoting the comprehensive implementation of rural revitalization. Against the backdrop of accelerated digital penetration in rural areas, existing research often focuses on macro-level digitalization, making it difficult to isolate the authentic contribution of digital inputs to agricultural systems. The driving effects and internal mechanisms of information and communication technology (ICT) input on agricultural economic resilience are explored in this research. Through clarifying its asymmetric impacts on resistance, recovery, and development capacities, a robust theoretical reference and empirical basis are offered for formulating differentiated digital agriculture policies that transition from traditional production modes to intelligent, resilient systems. [Methods] Based on Chinese provincial non-continuous panel data for 2012, 2015, 2017, 2018, and 2020, an advanced input-output (I-O) model framework was utilized. Leveraging the multi-regional input-output tables, the Leontief inverse matrix was employed to calculate the total consumption coefficient of the "Information Transmission, Software, and Information Technology Services" industry by the agricultural sector, which defined the total digital technology input value. Simultaneously, the entropy weight method was used to construct a comprehensive evaluation system for agricultural economic resilience. In terms of the econometric strategy, potential endogeneity was addressed by selecting the product of rural radio stations in 1988 and the previous year's Internet users as an instrumental variable (IV). The analysis was further supported by a 5% bilateral winsorization and a mediation effect model for rigorous empirical testing. [Results and Discussions] The empirical results demonstrated that digital technology input significantly enhanced overarching agricultural economic resilience. Benchmark regressions showed that the coefficient of ICT input was significantly positive at the 1% level, and the driving effect remained robust after correcting for endogeneity bias, which confirmed the core role of digital transformation in systemic risk management. Dimensional decomposition revealed a significant asymmetric characteristic: Digital technology strongly drives recovery capacity after exogenous shocks and developmental capacity during long-term evolution. However, its impact on the resistance dimension was relatively limited and exhibited a marginal negative effect. This reflected a potential technological dependence risk, where the system's increased sensitivity to power grids and network stability might weaken its original stress-resistance capacity during the onset of extreme risks. Furthermore, control variable analysis showed that per capita gross domestic product (GDP) and optimized planting structures promoted resilience, while the number of rural cooperatives exerted a negative influence, suggesting that some grassroots organizations suffered from insufficient digital adaptability. Mechanism analysis indicated that marketization, economic efficiency, and transport density were the primary transmission paths. Specifically, the marketization path contributed most significantly by reducing institutional transaction costs. Additionally, digital technology improved output efficiency through precision management and optimized transport logistics in synergy with physical infrastructure. Heterogeneity analysis showed that digital technology exhibited a clear "digital compensation" advantage in Western China, effectively offsetting natural resource endowment disadvantages. [Conclusions] This study confirms that digital input constitutes a new quality productive force that fundamentally strengthens the risk-resistance capacity of agricultural systems. The conclusions are summarized as follows: First, the empowerment of agricultural resilience by digital technology is characterized by a profound asymmetry. While it significantly improves the efficiency of systemic recovery and evolutionary development, it may simultaneously weaken original resistance due to intensified technological coupling and infrastructure dependence. Second, the reduction of institutional transaction costs through marketization is identified as the core mechanism for digital factors to exert their resilience-enhancing effects. The depth of the digital dividend is largely determined by the maturity of the market environment and its capacity for factor mobility. Third, the release of digital dividends in agriculture is heavily constrained by organizational adaptability. The lagging digital transformation and inherent structural rigidity of certain grassroots organizations have become the primary institutional bottlenecks restricting the conversion of digital technology inputs into practical systemic resilience. Ultimately, achieving a resilient agricultural economy requires a synergistic alignment between advanced digital production forces and modernized rural production relations.

Key words: digital technology input, agricultural economic resilience, input-output tables, information and communications technology input

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