[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-2759":3,"related-2759":97},{"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":23,"tags":25,"primary_topic":31,"secondary_topics":37,"classification":38,"search_phrases":69,"slug":72,"view_count":59,"doi":73,"paper":74,"created_at":96},2759,"Impact of digital infrastructure on agricultural green transformation: theory and China’s experience","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1869475","The digital infrastructure is the core support of promoting rural revitalization and agricultural green transformation. However, the impact and implementation pathways through which digital infrastructure affect the agricultural green transformation remain insufficiently explored and require in-depth empirical investigation. This paper utilizes panel data from Chinese counties spanning 2013 to 2023, treating the pilot policy of digital rural construction as a quasi-natural experiment, and employs a difference-in-differences (DID) model to examine the impact and underlying mechanisms of digital infrastructure on agricultural green transformation. The results indicate that digital infrastructure have a significant positive effect on agricultural green transformation, and this conclusion remains robust across multiple robustness checks. Mechanism analysis indicates that digital infrastructure influences the agricultural green transformation through three primary pathways: facilitating agricultural green technological innovation, improving the resource allocation efficiency, and enhancing the agricultural socialized services. Heterogeneity analysis reveals that the driving effect of digital infrastructure is significant in eastern regions, low-altitude counties, and major grain-producing areas, and the impact in other regions is relatively weak. This paper provides empirical evidence and policy implications for leveraging digital infrastructure to promote the agricultural green transformation.","数字基础设施是推动乡村振兴与农业绿色转型的核心支撑。然而，数字基础设施对农业绿色转型的影响及其实现路径尚缺乏充分探讨，有待深入的实证研究。本文利用2013至2023年中国县域面板数据，将数字乡村建设试点政策视为准自然实验，采用双重差分（DID）模型考察数字基础设施对农业绿色转型的影响及其内在机制。结果表明，数字基础设施对农业绿色转型具有显著正向效应，且该结论在多种稳健性检验下依然成立。机制分析表明，数字基础设施通过三条主要路径影响农业绿色转型：促进农业绿色技术创新、提高资源配置效率以及增强农业社会化服务。异质性分析显示，数字基础设施的驱动效应在东部地区、低海拔县域及粮食主产区显著，而在其他地区影响相对较弱。本文为利用数字基础设施推动农业绿色转型提供了经验证据与政策启示。",null,"Frontiers in Sustainable Food Systems","2026-09-16T00:00:00Z","论文",10,false,84,{"impact":17,"substance":17,"depth":18,"authority":19,"freshness":20,"relevant":21,"comment":22},22,18,13,9,1,"基于2013—2023年中国县域面板数据与数字乡村试点准自然实验，实证揭示数字基础设施通过绿色技术创新、资源配置效率和社会化服务三条路径推动农业绿色转型，方法规范、结论可靠，对数字乡村政策具有参考价值。",[24],{"name":10,"url":6},[26,27,28,29,30],"数字乡村","数字基础设施","农业绿色转型","农业社会化服务","县域面板数据",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},"I6","digital-village","数字乡村与数据要素","\u002Ftopic\u002Fdigital-agriculture\u002Fdigital-village","I",[],{"status":39,"locked":14,"version":40,"method":41,"evidence":42},"classified","2026-10-22.2","rules",{"candidates":43,"agricultural_evidence":46},[44,50,57,64],{"code":32,"score":45,"supported":46,"title":47,"abstract":48,"tags":49},5,true,[],[26],[26,27],{"code":51,"score":52,"supported":46,"title":53,"abstract":54,"tags":56},"G2",4,[],[55],"社会化服务",[29],{"code":58,"score":59,"supported":46,"title":60,"abstract":61,"tags":63},"G",3,[],[62],"乡村振兴",[],{"code":65,"score":21,"supported":14,"title":66,"abstract":67,"tags":68},"H4",[],[],[28],[70,71],"农业社会化服务 农业绿色转型 县域面板数据 数字基础设施","农业社会化服务 农业绿色转型","农业社会化服务农业绿色转型县域面板数据数字基础设施-2759","10.3389\u002Ffsufs.2026.1869475",{"doi":73,"openalex_id":75,"authors":76,"venue":10,"cited_by_count":87,"oa_url":88,"card":89,"direction":93,"ingested_from":95},"W7213421769",[77,80,82,85],{"name":78,"orcid":79},"Guoqun Ma","https:\u002F\u002Forcid.org\u002F0000-0002-9619-8423",{"name":81,"orcid":9},"Qin Su",{"name":83,"orcid":84},"Yan Luo","https:\u002F\u002Forcid.org\u002F0000-0002-9731-4983",{"name":86,"orcid":9},"Wenying Xiao",0,"https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fsustainable-food-systems\u002Farticles\u002F10.3389\u002Ffsufs.2026.1869475\u002Fpdf",{"tldr":90,"method":91,"finding":92,"direction":93,"opportunity":94},"基于中国县域面板数据，用DID模型检验数字基础设施对农业绿色转型的影响与机制。","2013-2023年县域面板数据，数字乡村试点作准自然实验，DID模型。","数字基础设施显著促进农业绿色转型，通过绿色技术创新、资源配置效率、社会化服务三条路径。","农业绿色发展与碳","可探究数字基础设施对农业碳排放与绿色全要素生产率的非线性影响及空间溢出效应。","openalex","2026-09-17T23:30:08.126393Z",{"total":98,"page":21,"page_size":98,"items":99},6,[100,152,218,282,340,409],{"id":101,"title":102,"url":103,"summary":104,"summary_zh":9,"content":9,"source_name":105,"source_url":9,"published_at":106,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":107,"score_detail":108,"sources":112,"tags":114,"primary_topic":117,"secondary_topics":118,"classification":119,"search_phrases":137,"slug":140,"view_count":87,"doi":141,"paper":142,"created_at":151},5459,"数字乡村建设对农业能源韧性的影响研究 (Research on the Impact of Digital Village Construction on Agricultural Energy Resilience)","https:\u002F\u002Fdoi.org\u002F10.13872\u002Fj.1000-0275.2026.0997","基于2011—2024年30个省份面板数据，三维构建农业能源韧性指标，双向固定效应、中介与门槛模型检验。数字乡村显著提升农业能源韧性，农业社会化服务部分中介，呈单一门槛。粮食主产区与主销区显著。属网络首发。","农业现代化研究（网络首发）2026-10-19","2026-10-19T00:00:00Z",80,{"impact":18,"substance":17,"depth":18,"authority":109,"freshness":110,"relevant":21,"comment":111},14,8,"基于30省14年面板数据的网络首发论文，方法规范、结论有新意，但属学术细分议题，公共影响有限，可作精选备选。",[113],{"name":105,"url":103},[26,115,29,116],"粮食主产区","农业能源韧性",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":14,"version":40,"method":41,"evidence":120},{"candidates":121,"agricultural_evidence":46},[122,128,132],{"code":32,"score":123,"supported":46,"title":124,"abstract":126,"tags":127},20,[26,125],"digital village",[26],[26],{"code":51,"score":52,"supported":46,"title":129,"abstract":130,"tags":131},[],[55],[29],{"code":133,"score":21,"supported":14,"title":134,"abstract":135,"tags":136},"A8",[],[],[115],[138,139],"数字乡村 农业能源韧性","农业社会化服务 中介效应","数字乡村农业能源韧性-5459","10.13872\u002Fj.1000-0275.2026.0997",{"doi":141,"openalex_id":9,"authors":143,"venue":9,"cited_by_count":87,"oa_url":9,"card":144,"direction":148,"ingested_from":150},[],{"tldr":145,"method":146,"finding":147,"direction":148,"opportunity":149},"基于30省面板数据，检验数字乡村建设对农业能源韧性的提升作用。","2011—2024年30省面板数据，三维构建韧性指标，双向固定效应、中介与门槛模","数字乡村显著提升农业能源韧性，农业社会化服务部分中介，存在单一门槛，主产区与主销区显著。","数字乡村与农业信息化","可延伸研究数字乡村影响农业能源韧性的区域异质机制及社会化服务之外的中介路径。","agent","2026-10-21T00:10:08.067176Z",{"id":153,"title":154,"url":155,"summary":156,"summary_zh":9,"content":9,"source_name":157,"source_url":9,"published_at":158,"category":12,"cover_url":9,"hotness":13,"is_selected":46,"score":159,"score_detail":160,"sources":164,"tags":166,"primary_topic":170,"secondary_topics":175,"classification":182,"search_phrases":206,"slug":209,"view_count":52,"doi":9,"paper":210,"created_at":217},4194,"数字乡村建设的代价？数字乡村战略对粮食安全和农业碳循环的非对称影响——来自中国的证据","https:\u002F\u002Fideas.repec.org\u002Fa\u002Fspr\u002Fagfoec\u002Fv14y2026i1d10.1186_s40100-026-00503-9.html","Weilong Gao、Qian Zhang、Ying Peng（吉林大学国家发展与安全研究院、大连理工大学商学院、长春工业大学经济管理学院）。发表于Agricultural and Food Economics 2026, 14(1): 1-22。基于989个县和1835户农户的多层次数据，将县级数字乡村发展指数与家庭层面数字采纳指数链接，运用固定效应和两阶段最小二乘法模型。结果显示：农村数字化与粮食产量显著正相关，与农业碳排放显著负相关，但对作物生物量碳吸收或净碳足迹无显著改善。机制分析表明生产收益与土地利用集约化（特别是双季种植扩张）相关，减排与减少劳动力和农药使用一致。异质性分析显示数字基础设施驱动生产率增长，数字治理和数字生活与减排关联更密切。","Agricultural and Food Economics 2026, 14(1)","2026-10-01T00:00:00Z",88,{"impact":17,"substance":161,"depth":162,"authority":109,"freshness":20,"relevant":21,"comment":163},24,19,"基于989县1835户的全国性实证研究，揭示数字乡村对粮食安全与农业碳循环的非对称影响，数据规模大、结论有政策参考价值，值得进入每日精选。",[165],{"name":157,"url":155},[26,27,167,168,169],"粮食安全","农业碳排放","农户数字化",{"code":133,"slug":171,"name":172,"path":173,"parent_code":174},"yield-food-security","单产提升与粮食安全","\u002Ftopic\u002Ffield-crops\u002Fyield-food-security","A",[176,181],{"code":65,"slug":177,"name":178,"path":179,"parent_code":180},"carbon","农业碳与绿色低碳","\u002Ftopic\u002Fenvironment\u002Fcarbon","H",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},{"status":39,"locked":14,"version":40,"method":41,"evidence":183},{"candidates":184,"agricultural_evidence":46},[185,192,196,200],{"code":65,"score":18,"supported":46,"title":186,"abstract":188,"tags":191},[187],"农业碳",[189,187,190],"碳排放","碳足迹",[168],{"code":32,"score":19,"supported":46,"title":193,"abstract":194,"tags":195},[26],[26],[26,27],{"code":133,"score":20,"supported":46,"title":197,"abstract":198,"tags":199},[167],[],[167],{"code":201,"score":59,"supported":46,"title":202,"abstract":203,"tags":205},"F4",[],[204],"农药",[],[207,208],"数字乡村 粮食安全 农业碳循环","吉林大学 数字乡村 农户","数字乡村粮食安全农业碳循环-4194",{"doi":9,"openalex_id":9,"authors":211,"venue":9,"cited_by_count":87,"oa_url":9,"card":212,"direction":148,"ingested_from":150},[],{"tldr":213,"method":214,"finding":215,"direction":148,"opportunity":216},"基于中国县级与农户数据，评估数字乡村战略对粮食安全和农业碳循环的非对称影响。","989县与1835户多层次数据，固定效应和两阶段最小二乘法。","数字化提升粮食产量并减少碳排放，但未改善作物碳吸收或净碳足迹。","可探究数字乡村对碳吸收无显著影响的原因，并优化数字治理以协同减排与固碳。","2026-10-05T00:04:55.880239Z",{"id":219,"title":220,"url":221,"summary":222,"summary_zh":223,"content":9,"source_name":10,"source_url":221,"published_at":158,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":224,"score_detail":225,"sources":227,"tags":229,"primary_topic":232,"secondary_topics":233,"classification":234,"search_phrases":257,"slug":260,"view_count":261,"doi":262,"paper":263,"created_at":281},4003,"Does rural digitalization improve food production security? Evidence from China’s digital village construction policy","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1914989","Introduction Food production security (FPS) remains a core challenge for developing economies. Although rural digitalization serves as a fundamental strategy to reshape agricultural systems in developing countries, its impact on food supply resilience remains underexplored. Methods This study investigates the impact of rural digitalization on regional FPS by exploiting China’s Digital Village Construction policy as a quasi-natural experiment. We employ the DID model on a panel dataset comprising 334 prefecture-level cities from 2015 to 2024. Results The empirical results demonstrate that rural digitalization significantly improves regional FPS. Specifically, the digital intervention increases the FPS of treated cities by an average of 8.2 percent. Regarding the mechanisms, we find that rural digitalization enhances FPS by facilitating smallholders’ food production viability and promoting food-oriented land reallocation. Furthermore, heterogeneity analyses reveal that the impact is more pronounced in regions equipped with superior agricultural socialized services, advanced agricultural industry structures, and major food producing area designations. Discussion These findings demonstrate that comprehensive rural digitalization strengthens the resilience of food production systems in developing economies and offer guidance for other Global South countries pursuing similar rural development paradigms.","引言 粮食生产安全（Food Production Security, FPS）仍是发展中经济体面临的核心挑战。尽管乡村数字化是发展中国家重塑农业体系的基础性战略，但其对粮食供给韧性的影响仍缺乏深入探讨。方法 本研究以中国数字乡村建设政策作为准自然实验，考察乡村数字化对区域粮食生产安全的影响。我们基于2015年至2024年334个地级市的面板数据集，采用双重差分（DID）模型进行实证分析。结果 实证结果表明，乡村数字化显著提升了区域粮食生产安全。具体而言，数字干预使处理组城市的粮食生产安全平均提高8.2%。在机制方面，我们发现乡村数字化通过促进小农户的粮食生产可行性和推动粮食导向的土地再配置来增强粮食生产安全。此外，异质性分析显示，在农业社会化服务较优、农业产业结构较先进以及被划定为粮食主产区的地区，该影响更为显著。讨论 这些发现表明，全面的乡村数字化增强了发展中经济体粮食生产体系的韧性，并为其他全球南方国家追求类似乡村发展范式提供了借鉴。",86,{"impact":161,"substance":17,"depth":18,"authority":19,"freshness":20,"relevant":21,"comment":226},"基于中国数字乡村政策准自然实验，用DID方法量化农村数字化对粮食生产安全的提升效应，数据规模大、结论可靠，对数字乡村与粮食安全主题有较高参考价值。",[228],{"name":10,"url":221},[26,167,230,29,231],"发展中国家","准自然实验",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":14,"version":40,"method":41,"evidence":235},{"candidates":236,"agricultural_evidence":46},[237,242,248,253],{"code":32,"score":238,"supported":46,"title":239,"abstract":240,"tags":241},15,[125],[26,125],[26],{"code":51,"score":243,"supported":46,"title":244,"abstract":245,"tags":247},7,[],[55,246],"小农户",[29],{"code":58,"score":59,"supported":46,"title":249,"abstract":250,"tags":252},[],[251],"rural development",[],{"code":133,"score":21,"supported":14,"title":254,"abstract":255,"tags":256},[],[],[167],[258,259],"数字乡村建设 粮食生产安全","农村数字化 粮食安全","数字乡村建设粮食生产安全-4003",2,"10.3389\u002Ffsufs.2026.1914989",{"doi":262,"openalex_id":264,"authors":265,"venue":10,"cited_by_count":87,"oa_url":221,"card":276,"direction":148,"ingested_from":95},"W7215123040",[266,269,271,274],{"name":267,"orcid":268},"Meng Zhao","https:\u002F\u002Forcid.org\u002F0000-0003-2049-9147",{"name":270,"orcid":9},"Jianhua Wang",{"name":272,"orcid":273},"Jiaqing Zhang","https:\u002F\u002Forcid.org\u002F0000-0003-4702-9495",{"name":275,"orcid":9},"Zixuan Ai",{"tldr":277,"method":278,"finding":279,"direction":148,"opportunity":280},"以中国数字乡村建设政策为准自然实验，评估农村数字化对区域粮食生产安全的影响。","基于334个地级市2015—2024年面板数据，采用双重差分（DID）模型。","农村数字化使处理组城市粮食生产安全平均提升8.2%，通过小农户生产可行性与耕地再配置实现。","可探究数字乡村政策对粮食安全的长期动态效应及社会化服务、产业结构的门槛机制。","2026-10-02T23:30:10.524948Z",{"id":283,"title":284,"url":285,"summary":286,"summary_zh":287,"content":9,"source_name":10,"source_url":285,"published_at":288,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":224,"score_detail":289,"sources":292,"tags":294,"primary_topic":298,"secondary_topics":299,"classification":300,"search_phrases":322,"slug":325,"view_count":59,"doi":326,"paper":327,"created_at":339},3457,"Social service accessibility and Green Agricultural Development Intensity as pathways to Rural Elderly Welfare: panel evidence from China’s underserved regions","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1863204","Background The elderly population in the rural areas of China, defined as 60 years or older, is over 121 million, representing 23.8% of the total rural population. The elderly population is growing rapidly and is characterized by the triple burden of poor access to healthcare, reduced agricultural income, and being digitally excluded. Although numerous national programs to expand social services and promote green agricultural transformation have been developed, the overall impact of these two policy streams on elderly wellbeing remains an untested area. This study aims to examine the independent and combined effects of social service accessibility (SSA) and Green Agricultural Development Intensity (GADI) on Rural Elderly Welfare (REW), while considering livelihood resilience (LR) as the mediating variable and the digital divide index (DDI) as the moderating condition. Both SSA and GADI are operationalized as province-level composite indices of service provision and agricultural development intensity, respectively, rather than as direct measures of individual elderly residents’ service use or farming behavior; this measurement level is made explicit throughout. Methods A panel data set was created, with the data collected at the provincial level and covering 30 provinces in China from 2013 to 2022 ( N = 268). Three province-year cells are missing because Tibet and Hainan entered the relevant statistical series after 2013, and a further 29 cells were dropped through listwise deletion of province-years with incomplete sub-indicators. The data was collected from the China Statistical Yearbooks, CNNIC internet reports, and the China Health and Retirement Longitudinal Study. The estimation results were based on two-way fixed-effects regression with interaction terms, and a bootstrap mediation analysis with 5,000 replications. The results were also checked for robustness through IV-2SLS estimation, winsorization, alternative specification for the dependent variable, excluding municipalities, and dynamic panel (system-GMM) estimation. Results SSA exerted a significant positive effect on REW ( β = 0.27, p \u003C 0.05), as did GADI ( β = 0.18, p \u003C 0.10). The SSA × GADI interaction was significant and positive ( β = 0.14, p \u003C 0.05), implying that the combined effect exceeds the additive effect of individual components. Livelihood resilience partially mediated both the SSA–REW pathway (indirect effect = 0.09, 95% CI [0.03, 0.16]) and the GADI–REW pathway (indirect effect = 0.06, 95% CI [0.01, 0.12]). Contrary to expectations, DDI failed to significantly moderate the relationship between GADI and REW ( β = −0.023, p = 0.412). Conclusion Coordinating social services with green agriculture was associated with wellbeing gains modestly but significantly greater than the sum of the two policy streams implemented in isolation. The synergy premium was estimated at 6% over the additive prediction (approximately 1–11% based on the 95% CI of the interaction coefficient), a pattern consistent with partial transmission through livelihood resilience. Interventions in the underserved rural areas should focus on integrated packages consisting of improved access to healthcare services and subsidies in green agriculture, rather than the two policy streams in isolation.","背景 中国农村60岁及以上老年人口超过1.21亿，占农村总人口的23.8%。老年人口增长迅速，且呈现出三重负担特征：医疗服务可及性差、农业收入减少以及被数字排斥。尽管国家已制定多项扩大社会服务和推动绿色农业转型的计划，但这两类政策对老年人福祉的总体影响仍是一个未经检验的领域。本研究旨在考察社会服务可及性（SSA）与绿色农业发展强度（GADI）对农村老年人福祉（REW）的独立效应和联合效应，同时将生计韧性（LR）作为中介变量、数字鸿沟指数（DDI）作为调节条件纳入考量。SSA和GADI分别被操作化为省级层面的服务供给和农业发展强度综合指数，而非个体老年居民服务使用或耕作行为的直接测量指标；这一测量层次在全文中有明确说明。方法 本研究构建了一个面板数据集，数据在省级层面收集，覆盖中国30个省份2013年至2022年（N = 268）。由于西藏和海南在2013年之后才进入相关统计序列，有3个省份-年份单元缺失；另有29个单元因省份-年份子指标不完整而通过列表删除法被剔除。数据来源于《中国统计年鉴》、CNNIC互联网报告和中国健康与养老追踪调查。估计结果基于带交互项的双向固定效应回归，以及重复5,000次的Bootstrap中介分析。研究还通过IV-2SLS估计、缩尾处理、因变量替代设定、剔除直辖市以及动态面板（系统GMM）估计对结果进行了稳健性检验。结果 SSA对REW具有显著正向效应（β = 0.27，p \u003C 0.05），GADI亦然（β = 0.18，p \u003C 0.10）。SSA × GADI交互项显著且为正（β = 0.14，p \u003C 0.05），表明联合效应超过各组成部分的加性效应。生计韧性部分中介了SSA–REW路径（间接效应 = 0.09，95% CI [0.03, 0.16]）和GADI–REW路径（间接效应 =","2026-09-24T00:00:00Z",{"impact":17,"substance":290,"depth":18,"authority":109,"freshness":20,"relevant":21,"comment":291},23,"基于30省十年面板数据，首次量化社会服务可及性与绿色农业发展强度对农村老年福祉的协同效应，方法扎实、结论有政策参考价值，值得进入每日精选。",[293],{"name":10,"url":285},[26,295,296,29,297],"绿色农业","数字鸿沟","农村养老",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":14,"version":40,"method":41,"evidence":301},{"candidates":302,"agricultural_evidence":46},[303,308,312,317],{"code":32,"score":110,"supported":46,"title":304,"abstract":305,"tags":307},[],[296,306],"digital divide",[26,296],{"code":51,"score":21,"supported":14,"title":309,"abstract":310,"tags":311},[],[],[29],{"code":313,"score":21,"supported":14,"title":314,"abstract":315,"tags":316},"G5",[],[],[297],{"code":318,"score":21,"supported":14,"title":319,"abstract":320,"tags":321},"H8",[],[],[295],[323,324],"农村老年福祉 绿色农业 社会服务","中国农村 数字鸿沟 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