数字技术赋能粮食体系韧性的空间效应研究

The Spatial Effects of Digital Technology Empowering Food System Resilience

摘要

基于2011—2022年中国30个省份的面板数据，运用熵权TOPSIS法对数字技术和粮食体系韧性的指标体系进行测度，并采用空间杜宾模型考察数字技术对粮食体系韧性的空间溢出效应，以期为优化我国数字农业布局、筑牢粮食安全根基提供决策依据。研究表明：1）基于三维核密度图分析，从区域层面看，2011—2022年我国粮食主产区的粮食体系韧性呈现“提升—分化—集中”的演化特征；主销区表现为先提升后回落的波动态势；产销平衡区则呈现前期提升集聚、后期分散回落的阶段性特征。从全国整体来看，全国粮食体系韧性虽呈逐年增长态势，但在空间维度上存在显著的“俱乐部收敛”特征，区域发展不均衡问题较为突出。2）计量结果表明，数字技术对粮食体系韧性具有显著的促进作用，且表现出强劲的正向空间溢出效应，溢出效应占总效应的795%，远高于直接效应。在更换权重矩阵和剔除样本后，该结果依然稳健。3）区域异质性分析表明，三大粮食功能区直接效应均正向显著，主销区溢出效应占总效应的比重最高（80.6%），产销平衡区次之（58.9%），主产区溢出效应不显著。基于上述结论，提出以下政策建议：应充分释放数字技术的空间溢出红利，借助发达地区的数字技术优势，强化跨区域辐射带动作用；结合三大粮食功能区的资源禀赋与功能定位，因地制宜实施梯度化数字技术推广策略，构建“主销区引领、主产区攻坚、平衡区衔接”的全域数字赋能格局，通过数字技术协同驱动区域粮食体系韧性均衡提升，从而为筑牢国家粮食安全屏障提供理论支撑与实践路径。

Abstract

Based on provincial panel data from 30 provinces in China from 2011 to 2022, the entropy-weighted TOPSIS method is used to measure the indicator systems of digital technology and food system resilience, and the spatial Durbin model is employed to examine the spatial spillover effect of digital technology on food system resilience, aiming to provide a decision-making basis for optimizing China's digital agriculture layout and consolidating the foundation of food security. Based on the three-dimensional kernel density plot analysis, at the regional level, from 2011 to 2022, the food system resilience of China's main grain-producing areas exhibits an evolutionary characteristic of “improvement-differentiation-concentration”; the main grain-selling areas show a fluctuating trend of first increasing and then declining; and the production-marketing balance areas present a phased characteristic of improvement and agglomeration in the early period and dispersion and decline in the later period. At the national level, although China's food system resilience shows a year-by-year growth trend, it exhibits significant “club convergence” in the spatial dimension, and the problem of unbalanced regional development is relatively prominent. The econometric results show that digital technology has a significant promoting effect on food system resilience and demonstrates a strong positive spatial spillover effect, with the spillover effect accounting for 79.5% of the total effect, far higher than the direct effect. This result remains robust after replacing the weight matrix and excluding samples. Regional heterogeneity analysis shows that the direct effects in all three major grain functional areas are positive and significant. The main grain-selling areas have the highest proportion of spillover effect in the total effect (80.6%), followed by the production-marketing balance areas (58.9%), while the spillover effect in the main grain-producing areas is not significant. Based on the above conclusions, it is proposed that the spatial spillover dividend of digital technology should be fully released, and the digital technology advantages of developed regions should be leveraged to strengthen cross-regional radiation and driving effects. In combination with the resource endowments and functional positioning of the three major grain functional areas, differentiated digital technology promotion strategies should be implemented according to local conditions, and a comprehensive digital empowerment pattern of “main grain-selling areas leading, main grain-producing areas tackling key problems, and balance areas connecting” should be built. Through digital technology, the balanced improvement of regional food system resilience should be collaboratively driven, thereby providing theoretical support and practical pathways for building a solid national food security barrier.

关键词

数字技术 / 粮食体系韧性 / 空间溢出效应 / 空间杜宾模型

Key words

digital technology / food system resilience / spatial spillover effect / spatial Durbin model

参考文献

[1] 陈建军, 陈国亮, 黄洁, 2009. 新经济地理学视角下的生产性服务业集聚及其影响因素研究: 来自中国222个城市的经验证据[J]. 管理世界(4): 83-95.

[2] 方湖柳, 潘娴, 马九杰, 2022. 数字技术对长三角产业结构升级的影响研究[J]. 浙江社会科学(4): 25-35, 156-157.

[3] 〔Fang Huliu, Pan Xian, Ma Jiujie, 2022. The impact of digital technologies on the upgrading of industrial structure in Yangtze River Delta[J]. Zhejiang Social Sciences(4): 25-35, 156-157. 〕

[4] 郝爱民, 谭家银, 2022. 数字乡村建设对我国粮食体系韧性的影响[J]. 华南农业大学学报(社会科学版), 21(3): 10-24.

[5] 〔Hao Aimin, Tan Jiayin, 2022. Impact of digital rural construction on food system resilience[J]. Journal of South China Agricultural University (Social Science Edition), 21(3): 10-24.〕

[6] 侯怡爽, 马永欢, 祝培甜, 等, 2026. 中国经济-人口-粮食产量重心的演变特征及耦合关系[J]. 资源与产业, 28(1): 53-66.

[7] 〔Hou Yishuang, Ma Yonghuan, Zhu Peitian, et al., 2026. Evolution and coupling among China's economy-population-grain production gravity center[J]. Resources & Industries, 28(1): 53-66.〕

[8] 华坚, 杨梦依, 曹慧敏, 2024. 粮食主产区的新型城镇化与粮食安全: 基于土地规模化经营中介效应检验[J]. 资源与产业, 26(1): 50-60.

[9] 〔Hua Jian, Yang Mengyi, Cao Huimin, 2024. New urbanization and grain security in major grain producing areas based on mediating effects of land scaling operation[J]. Resources & Industries, 26(1): 50-60.〕

[10] 李盛竹, 薛枫, 姜金贵, 2024. 农业数字化对中国粮食新质生产力的影响效应研究[J]. 农林经济管理学报, 23(4): 435-445.

[11] 〔Li Shengzhu, Xue Feng, Jiang Jingui, 2024. Effect of agricultural digitization on new productive forces of food in China[J]. Journal of Agro-Forestry Economics and Management, 23(4): 435-445.〕

[12] 李豫新, 项升, 2025. 数字技术发展对粮食绿色全要素生产率的影响研究[J]. 中国农业资源与区划, 46(9): 55-63.

[13] 〔Li Yuxin, Xiang Sheng, 2025. Research on the impact of digital technology development on green total factor productivity of grain[J]. Chinese Journal of Agricultural Resources and Regional Planning, 46(9): 55-63.〕

[14] 刘卓颖, 2012. 多尺度人口增长的空间统计分析[J]. 测绘通报(2): 65-67.

[15] 〔Liu Zhuoying, 2012. The analysis of spatial statistics by use of multi-distance[J]. Bulletin of Surveying and Mapping(2): 65-67.〕

[16] 罗英, 2022. 数字技术风险程序规制的法理重述[J]. 法学评论, 40(5): 151-160.

[17] 〔Luo Ying, 2022. Jurisprudential restatement of digital technology risk procedural regulation[J]. Law Review, 40(5): 151-160.〕

[18] 马俊凯, 李光泗, 2025. 数字技术赋能国家粮食安全治理: 基于央地关系视角[J]. 农村经济(4): 42-50.

[19] 〔Ma Junkai, Li Guangsi, 2025. Digital technology enabling national food security governance: Based on the perspective of central-local relationship[J]. Rural Economy(4): 42-50.〕

[20] 彭建仿, 黄世成, 2024. 粮食安全视角下数字技术对粮食单产的影响机制[J]. 华南农业大学学报(社会科学版), 23(4): 77-92.

[21] 〔Peng Jianfang, Huang Shicheng, 2024. Mechanisms of digital technology's impact on grain yield from perspective of food security[J]. Journal of South China Agricultural University (Social Science Edition), 23(4): 77-92.〕

[22] 宋海荣, 2005. 新经济增长理论述评及其政策取向[J]. 统计与决策(9): 113-115.

[23] 王可山, 2023. 新时代我国粮食安全保障的成就与经验[J]. 改革(9): 99-109.

[24] 〔Wang Keshan, 2023. Achievements and experiences of China's food security in the new era[J]. Reform(9): 99-109.〕

[25] 王妍霏, 叶举, 曹杰, 2025. 农村流通数字化影响粮食体系韧性的机理及效应研究[J]. 长江流域资源与环境, 34(2): 423-436.

[26] 〔Wang Yanfei, Ye Jü, Cao Jie, 2025. Mechanism and effect of digitalization of rural circulation on the resilience of grain system[J]. Resources and Environment in the Yangtze Basin, 34(2): 423-436.〕

[27] 汪振, 刘滨, 朱家仪, 2024. 数字经济对中国粮食体系韧性的影响[J]. 中国农业大学学报, 29 (11): 261-275.

[28] 〔Wang Zhen, Liu Bin, Zhu Jiayi, 2024. Effects of the digital economy on China's food system resilience[J]. Journal of China Agricultural University, 29(11): 261-275.〕

[29] 魏后凯, 2020. “十四五”时期中国农村发展若干重大问题[J]. 经济研究参考(8): 110-113.

[30] 邢小强, 周平录, 张竹, 等, 2019. 数字技术、BOP商业模式创新与包容性市场构建[J]. 管理世界, 35(12): 116-136.

[31] 〔Xing Xiaoqiang, Zhou Pinglu, Zhang Zhu, et al., 2009. Digital technology, BOP business model innovation and inclusive market building[J]. Journal of Management World, 35(12): 116-136.〕

[32] 杨军鸽, 王琴梅, 2023. 数字技术与农业高质量发展: 基于数字生产力的视角[J]. 山西财经大学学报, 45(4): 47-63.

[33] 〔Yang Junge, Wang Qinmei, 2023. Digital technology and high-quality agricultural development: From the perspective of digital productivity[J]. Journal of Shanxi University of Finance and Economics, 45(4): 47-63.〕

[34] 赵巍, 徐筱雯, 2023. 数字经济对农业经济韧性的影响效应与作用机制[J]. 华南农业大学学报(社会科学版), 22(2): 87-96.

[35] 〔Zhao Wei, Xu Xiaowen, 2023. Effect and mechanism of digital economy on the resilience of agricultural economy[J]. Journal of South China Agricultural University(Social Sciences Edition), 22(2): 87-96.〕

[36] 郑骏川, 周世昕, 李璨, 2025. 中国粮食体系韧性测度、时空分异及推进路径: 基于三大粮食功能区及四大经济区域的比较视角[J]. 中国农业资源与区划, 46(1): 1-12.

[37] 〔Zheng Junchuan, Zhou Shixin, Li Can, 2025. Measurement, spatiotemporal differentiation, and promotion path of resilience in China's grain system: A comparative perspective based on the three major grain functional zones and the four major economic regions[J]. Chinese Journal of Agricultural Resources and Regional Planning, 46(1): 1-12.〕

[38] 左秀平, 叶林祥, 2024. 中国粮食体系韧性: 水平测度及动态演进[J]. 华南农业大学学报(社会科学版), 23(1): 88-101.

[39] 〔Zuo Xiuping, Ye Linxiang, 2024. China's grain system resilience: Level measurement and dynamic evolution[J]. Journal of South China Agricultural University (Social Sciences Edition), 23(1): 88-101.〕

[40] Hodbod J, Eakin H, 2015. Adapting a social-ecological resilience framework for food systems[J]. Journal of Environmental Studies and Sciences, 5(3): 474-484.

[41] Larisa H, 2020. Sustainability driven by agriculture through digital transformation[J]. Sustainability, 12(20): 8596.

[42] Talaviya T, Shah D, Patel N, et al., 2020. Implementation of artificial intelligence in agriculture for optimisation of irrigation and application of pesticides and herbicides[J]. Artificial Intelligence in Agriculture, 4: 58-73.

[43] Tendall D M, Joerin J, Kopainsky B, et al., 2015. Food system resilience: Defining the concept[J]. Global Food Security, 6: 17-23.

[44] Trivelli L, Apicella A, Chiarello F, et al., 2019. From precision agriculture to Industry 4.0: Unveiling technological connections in the agrifood sector[J]. British Food Journal, 121(8): 1730-1743.

基金资助

延安市科技计划项目(2023-SFGG-125)