[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-2627":3},{"id":4,"title":5,"url":6,"summary":7,"summary_zh":8,"content":9,"source_name":10,"source_url":6,"published_at":11,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":15,"score_detail":16,"sources":22,"tags":24,"view_count":30,"doi":31,"paper":32,"created_at":50},2627,"How does agricultural digitalization drive green total factor productivity? Evidence from rural industrial integration, data factor allocation, and spatial effects in China","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1852421","Introduction Digital empowerment accelerates cross-sectoral integration within the rural economy, driving profound structural shifts in agricultural development. Methods Using a provincial-level panel dataset from China spanning 2012 to 2022, this study constructs comprehensive indices to assess agricultural digitalization, rural industrial integration, and data factor allocation. By employing mediation, moderation, and spatial Durbin models, this research investigates the underlying mechanisms through which agricultural digitalization affects agricultural green total factor productivity. Results The empirical results demonstrate that agricultural digitalization significantly enhances AGTFP, a finding that is robust to a battery of specification checks. Mechanism analysis reveals that rural industrial integration serves as a crucial partial mediator in this relationship. Furthermore, optimizing data factor allocation positively moderates and thereby amplifies the impact of agricultural digitalization on AGTFP. Spatial analysis indicates that agricultural digitalization generates positive spatial spillover effects, boosting AGTFP in both local and neighboring regions. Finally, heterogeneity analyses reveal that this positive effect is particularly pronounced in the Eastern region and in areas with high levels of urban-rural integration, and it remains robust across both major and non-major grain-producing areas. Discussion Ultimately, this study deepens the understanding of the digitalization-sustainability nexus in agriculture, underscoring the vital role of advancing rural industrial integration and optimizing data factor allocation in driving green productivity.","引言 数字赋能加速了农村经济内部的跨部门融合，推动农业发展发生深刻的结构性变革。方法 本研究利用中国2012年至2022年的省级面板数据集，构建了农业数字化、农村产业融合和数据要素配置的综合指数。通过采用中介模型、调节模型和空间杜宾模型，本研究探讨了农业数字化影响农业绿色全要素生产率的潜在机制。结果 实证结果表明，农业数字化显著提升了农业绿色全要素生产率（AGTFP），这一发现在一系列设定检验中保持稳健。机制分析揭示，农村产业融合在这一关系中起到了关键的部分中介作用。此外，优化数据要素配置对这一关系产生了正向调节作用，从而放大了农业数字化对AGTFP的影响。空间分析表明，农业数字化产生了正向空间溢出效应，提升了本地及邻近地区的AGTFP。最后，异质性分析显示，这一正向效应在东部地区和城乡融合水平较高的地区尤为显著，且在粮食主产区和非主产区均保持稳健。讨论 最终，本研究深化了对农业数字化与可持续性关系的理解，凸显了推进农村产业融合和优化数据要素配置在推动绿色生产力方面的重要作用。",null,"Frontiers in Sustainable Food Systems","2026-09-16T00:00:00Z","论文",10,false,81,{"impact":17,"substance":18,"depth":17,"authority":19,"freshness":13,"relevant":20,"comment":21},18,22,13,1,"基于2012—2022年省级面板数据的实证研究，揭示农业数字化通过农村产业融合与数据要素配置提升农业绿色全要素生产率并具空间溢出效应，方法规范、结论有政策参考价值，值得进入每日精选。",[23],{"name":10,"url":6},[25,26,27,28,29],"数字乡村","数据要素","农业数字化","绿色全要素生产率","农村产业融合",0,"10.3389\u002Ffsufs.2026.1852421",{"doi":31,"openalex_id":33,"authors":34,"venue":10,"cited_by_count":30,"oa_url":6,"card":43,"direction":47,"ingested_from":49},"W7213309985",[35,37,40],{"name":36,"orcid":9},"Yijia Zhou",{"name":38,"orcid":39},"Jun He","https:\u002F\u002Forcid.org\u002F0000-0003-4839-3950",{"name":41,"orcid":42},"Jun Chen","https:\u002F\u002Forcid.org\u002F0000-0001-7397-2714",{"tldr":44,"method":45,"finding":46,"direction":47,"opportunity":48},"基于中国省级面板数据，揭示农业数字化通过产业融合与数据要素配置提升农业绿色全要素生产率。","2012-2022年省级面板数据，构建综合指数，用中介、调节与空间杜宾模型。","农业数字化显著提升AGTFP，农村产业融合起部分中介作用，数据要素配置正向调节，且具正向空间溢出。","农业绿色发展与碳","可深入微观地块或县域尺度，探究数据要素配置的阈值效应及跨区域溢出衰减机制。","openalex","2026-09-16T23:30:07.645013Z"]