[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-3754":3,"related-3754":46},{"id":4,"title":5,"url":6,"summary":7,"summary_zh":8,"content":8,"source_name":9,"source_url":8,"published_at":10,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":14,"score_detail":15,"sources":23,"tags":25,"search_phrases":31,"slug":34,"view_count":35,"doi":8,"paper":36,"created_at":45},3754,"数字基础设施何以赋能农业产业链韧性提升","http:\u002F\u002Fhnxbw.cnjournals.net\u002Fhznydxsk\u002Fch\u002Freader\u002Fview_abstract.aspx?file_no=202605005&flag=1","以宽带中国试点政策为外生冲击事件，基于2010-2024年中国295个地级市及直辖市辖区面板数据，构建农业产业链韧性评价指标体系，运用双重差分模型。数字基础设施能显著提升农业产业链韧性，主要通过促进农业技术创新、推动产业结构高级化和发展数字普惠金融提升。效应在东部和东北地区更明显。",null,"华中农业大学学报（社会科学版）","2026-05-15T00:00:00Z","论文",10,false,79,{"impact":16,"substance":17,"depth":18,"authority":19,"freshness":20,"relevant":21,"comment":22},22,23,18,14,2,1,"基于295个地级市面板数据的双重差分实证研究，方法规范、结论有新意，但发表于四个多月前，时效性偏弱，适合作为主题页深度文献而非当日精选。",[24],{"name":9,"url":6},[26,27,28,29,30],"数字基础设施","数字普惠金融","宽带中国","农业技术创新","农业产业链韧性",[32,33],"宽带中国 农业产业链韧性","数字基础设施 地级市 面板数据","宽带中国农业产业链韧性-3754",0,{"doi":8,"openalex_id":8,"authors":37,"venue":8,"cited_by_count":35,"oa_url":8,"card":38,"direction":42,"ingested_from":44},[],{"tldr":39,"method":40,"finding":41,"direction":42,"opportunity":43},"以宽带中国试点为准自然实验，检验数字基础设施对农业产业链韧性的因果影响。","2010-2024年295个地级市面板数据，双重差分模型。","数字基础设施显著提升农业产业链韧性，经由技术创新、结构高级化与数字普惠金融，东部东北更明显。","数字乡村与农业信息化","可深入探究中西部效应偏弱的原因，并考察数字基础设施与产业链韧性间的非线性门槛与空间溢出。","agent","2026-09-29T00:08:27.107183Z",{"total":47,"page":21,"page_size":47,"items":48},6,[49,78,103,149,178,220],{"id":50,"title":51,"url":52,"summary":53,"summary_zh":8,"content":8,"source_name":54,"source_url":8,"published_at":55,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":56,"score_detail":57,"sources":59,"tags":61,"search_phrases":66,"slug":69,"view_count":35,"doi":8,"paper":70,"created_at":77},3438,"《数字乡村建设与城乡收入差距：一个U型关系》——基于县域数字乡村发展指数","http:\u002F\u002Fwww.qikanzj.com\u002Fhek\u002Fhznydxxbshkxb\u002Fmulu\u002F559280.html","李晓慧、李谷成基于偏向型技术进步理论，利用县域数字乡村发展指数与县域经济统计数据实证检验数字乡村建设与城乡收入差距之间的关系。基准回归结果显示数字乡村建设对城乡收入差距的影响呈现出先缩小后扩大的U型效应；从各维度看，数字基础设施对城乡收入差距的影响处于扩大阶段，而乡村经济数字化、乡村治理数字化及乡村生活数字化对城乡收入差距的影响处于缩小阶段；机制研究显示技能溢价是阻碍数字乡村建设缩小城乡收入差距的重要因素。","《华中农业大学学报（社会科学版）》","2026-09-20T00:00:00Z",78,{"impact":18,"substance":16,"depth":18,"authority":19,"freshness":47,"relevant":21,"comment":58},"核心期刊实证研究，基于县域指数揭示数字乡村与城乡收入差距的U型关系及技能溢价机制，结论具政策参考价值。",[60],{"name":54,"url":52},[62,26,63,64,65],"数字乡村","县域经济","城乡收入差距","技能溢价",[67,68],"数字乡村 城乡收入差距","城乡收入差距 数字基础设施 县域经济 技能溢价","数字乡村城乡收入差距-3438",{"doi":8,"openalex_id":8,"authors":71,"venue":8,"cited_by_count":35,"oa_url":8,"card":72,"direction":42,"ingested_from":44},[],{"tldr":73,"method":74,"finding":75,"direction":42,"opportunity":76},"基于县域数字乡村发展指数，实证检验数字乡村建设与城乡收入差距呈先缩小后扩大的U型关系。","偏向型技术进步理论，县域数字乡村发展指数与县域经济统计数据实证回归。","数字乡村建设对城乡收入差距呈U型效应，技能溢价是阻碍其缩小差距的重要因素。","可探究技能溢价门槛下数字乡村各维度对收入差距的异质性影响及技能培训等调节机制。","2026-09-25T00:09:33.905388Z",{"id":79,"title":80,"url":81,"summary":82,"summary_zh":8,"content":8,"source_name":83,"source_url":8,"published_at":55,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":35,"score_detail":84,"sources":86,"tags":88,"search_phrases":91,"slug":94,"view_count":35,"doi":8,"paper":95,"created_at":102},3437,"《数字普惠金融对低收入群体收入流动性的影响研究》——基于中国家庭追踪调查","https:\u002F\u002Fpublish.cnki.net\u002Fjournal\u002Fportal\u002Fcyzp\u002Fclient\u002Fpaper\u002F403264d562fcc35bdc3a4633c46b87a6","眭强、冯亚芳、张立冬基于中国家庭追踪调查（CFPS）和数字普惠金融指数的数据分析数字普惠金融对低收入群体收入流动性的影响。研究发现：数字普惠金融能够显著提升低收入群体收入地位，主要归因于家庭财务韧性效应和收入提升效应；异质性研究显示对农村、中西部地区以及非正规就业的低收入群体促进作用更为显著；金融素养和数字素养是影响数字普惠金融提升低收入群体收入地位的重要因素。","《产业组织评论》2026-09-20",{"impact":35,"substance":35,"depth":35,"authority":35,"freshness":35,"relevant":35,"comment":85},"论文聚焦数字普惠金融与低收入群体收入流动性，属农村金融与数字乡村交叉议题，但非三农信息化核心范畴，相关性不足，不建议进入每日精选。",[87],{"name":83,"url":81},[62,27,89,90],"低收入群体","收入流动性",[92,93],"数字普惠金融 低收入群体 收入流动性","CFPS 数字普惠金融","数字普惠金融低收入群体收入流动性-3437",{"doi":8,"openalex_id":8,"authors":96,"venue":8,"cited_by_count":35,"oa_url":8,"card":97,"direction":42,"ingested_from":44},[],{"tldr":98,"method":99,"finding":100,"direction":42,"opportunity":101},"基于CFPS数据，研究数字普惠金融如何提升低收入群体收入流动性。","使用中国家庭追踪调查（CFPS）与数字普惠金融指数进行实证分析。","数字普惠金融显著提升低收入群体收入地位，通过财务韧性和收入提升效应，对农村和中西部群体更明显。","可探究数字普惠金融在农业低收入群体中的具体作用机制及与数字素养的交互效应。","2026-09-25T00:09:33.835025Z",{"id":104,"title":105,"url":106,"summary":107,"summary_zh":108,"content":8,"source_name":109,"source_url":106,"published_at":110,"category":11,"cover_url":8,"hotness":111,"is_selected":112,"score":113,"score_detail":114,"sources":119,"tags":123,"search_phrases":129,"slug":132,"view_count":35,"doi":133,"paper":134,"created_at":148},3359,"Agroforestry Policies in 16 European Countries: Current Limitations and a Blueprint for the Future. DigitAF Project - Deliverable 1.6.","https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.20312118","Deliverable 1.6 of the EU DigitAF Project (digitaf.eu) is the final deliverable of WorkPackage 1 \"Strengthening agroforestry and carbon farming policies: tools for policymakers\". It analyses agroforestry policies across 14 EU Member States, examining current regulatory limitations, land tenure constraints, and the integration of agricultural trees with broader EU environmental lelgislation. It closes with a blueprint for future agroforestry policy reform. The report highlights severe historical deficiencies in Common Agricultural Policy (CAP) implementation, noting that actual agroforestry adoption has consistently falled short of targets - due to administrative complexities and inadequate data tracking. Land tenancy acts as a major bottleneck; with roughly 46% of EU farmland rented, and short-term lease frameworks which fundamentally conflict with the long-term capital investment required for agroforestry. Beyond the CAP, the scaling of agroforestry is paralyzed by institutional silos and regulatory contradictions. Notably, remote sensing algorithms implemented under the EUDR may bring critical errors, misclassifying traditional anthropogenic silvopastoral systems (like the Spanish Dehesa) as forests, and risking false flags for forest degradation. To resolve these issues, the report presents the EURAF Agroforestry Blueprint (2028–2040). This blueprint includes unified digital infrastructures (LPIS and NFI integration), harmonized definitions recognizing trees as productive assets, and financial de-risking through blended finance like Nature Credits.","欧盟DigitAF项目（digitaf.eu）的可交付成果1.6是工作包1“加强农林业与碳农业政策：政策制定者工具”的最终交付成果。该报告分析了14个欧盟成员国的农林业政策，考察了当前的监管限制、土地权属约束，以及农业树木与更广泛的欧盟环境立法的整合情况。报告最后提出了未来农林业政策改革的蓝图。报告强调了共同农业政策（CAP）实施中严重的历史性缺陷，指出由于行政复杂性及数据追踪不足，农林业的实际采用率始终未能达到目标。土地租赁是主要瓶颈；欧盟约46%的农田为租赁经营，而短期租赁框架与农林业所需的长期资本投资存在根本性冲突。除CAP之外，农林业的规模化还因机构壁垒和监管矛盾而陷入瘫痪。值得注意的是，根据欧盟零毁林法规（EUDR）实施的遥感算法可能带来严重错误，将传统人为林牧系统（如西班牙德埃萨牧场）误分类为森林，并可能错误触发森林退化预警。为解决这些问题，报告提出了EURAF农林业蓝图（2028—2040）。该蓝图包括统一数字基础设施（LPIS与NFI整合）、承认树木为生产性资产的协调定义，以及通过自然信用等混合融资实现金融风险缓释。","Zenodo (CERN European Organization for Nuclear Research)","2026-09-23T00:00:00Z",25,true,87,{"impact":115,"substance":17,"depth":18,"authority":116,"freshness":117,"relevant":21,"comment":118},24,13,9,"欧盟DigitAF项目终期报告，系统剖析14国农林业政策瓶颈并提出2028-2040改革蓝图，数据与政策细节扎实，对农业政策与遥感信息化研究有参考价值。",[120,121],{"name":109,"url":106},{"name":109,"url":122},"https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.22909703",[26,124,125,126,127,128],"遥感监测","碳农业","农林业","欧盟CAP","土地权属",[130,131],"DigitAF 农林业政策","EUDR 遥感 Dehesa","DigitAF农林业政策-3359","10.5281\u002Fzenodo.20312118",{"doi":133,"openalex_id":135,"authors":136,"venue":109,"cited_by_count":35,"oa_url":106,"card":140,"direction":146,"ingested_from":147},"W7165358105",[137],{"name":138,"orcid":139},"Gerry LAWSON","https:\u002F\u002Forcid.org\u002F0000-0002-1395-3092",{"tldr":141,"method":142,"finding":143,"direction":144,"opportunity":145},"分析14个欧盟成员国农林业政策局限，提出2028-2040年改革蓝图。","政策文本分析、土地权属与遥感算法评估，结合CAP实施数据。","CAP实施不足、土地租赁短期化及EUDR遥感误判阻碍农林业推广。","农业绿色发展与碳","可研究遥感算法对传统农林系统的误判校正及数字基础设施整合方案。","农业遥感与作物表型","openalex","2026-09-24T23:30:20.637258Z",{"id":150,"title":151,"url":152,"summary":153,"summary_zh":8,"content":8,"source_name":154,"source_url":8,"published_at":155,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":156,"score_detail":157,"sources":159,"tags":161,"search_phrases":165,"slug":168,"view_count":21,"doi":169,"paper":170,"created_at":177},3003,"数字乡村建设对农业经济韧性的影响研究——基于2014—2023年30个省份面板数据","https:\u002F\u002Fxb.ynau.edu.cn\u002Fjwk_sk\u002Fcn\u002Farticle\u002Fpdf\u002Fpreview\u002F10.12371\u002Fj.ynau(s).202603058.pdf","安徽建筑大学潘和平等基于2014—2023年中国30个省份面板数据，运用双向固定效应模型和中介效应模型系统考察数字乡村建设对农业经济韧性的影响与传导机制。研究结果表明：数字乡村建设显著提升农业经济韧性，且这种正向效应在自然灾害频发区、粮食主产区及高数字乡村试点区表现更为突出；其传导机制主要通过促进农业技术创新实现。","云南农业大学学报(社会科学)2026,20(0):1-8","2026-09-15T00:00:00Z",80,{"impact":18,"substance":16,"depth":18,"authority":116,"freshness":117,"relevant":21,"comment":158},"基于30省十年面板数据的实证研究，方法规范、结论明确，对数字乡村政策评估有参考价值，但属学术论文，公共传播性有限。",[160],{"name":154,"url":152},[62,162,163,29,164],"农业经济韧性","粮食主产区","面板数据",[166,167],"数字乡村 农业经济韧性","潘和平 安徽建筑大学 数字乡村","数字乡村农业经济韧性-3003","10.12371\u002Fj.ynau(s).202603058.pdf",{"doi":169,"openalex_id":8,"authors":171,"venue":8,"cited_by_count":35,"oa_url":8,"card":172,"direction":42,"ingested_from":44},[],{"tldr":173,"method":174,"finding":175,"direction":42,"opportunity":176},"基于30省面板数据，实证检验数字乡村建设对农业经济韧性的提升效应及传导机制。","2014—2023年30省面板数据，双向固定效应与中介效应模型。","数字乡村建设显著提升农业经济韧性，且在灾害频发区、粮食主产区、高试点区更突出，农业技术创新为中介。","可进一步探究数字乡村不同维度（如电商、治理数字化）对韧性的异质性影响及空间溢出效应。","2026-09-20T00:03:08.396757Z",{"id":179,"title":180,"url":181,"summary":182,"summary_zh":183,"content":8,"source_name":184,"source_url":181,"published_at":185,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":186,"score_detail":187,"sources":189,"tags":191,"search_phrases":195,"slug":198,"view_count":21,"doi":199,"paper":200,"created_at":219},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。","Frontiers in Sustainable Food Systems","2026-09-16T00:00:00Z",84,{"impact":16,"substance":16,"depth":18,"authority":116,"freshness":117,"relevant":21,"comment":188},"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。",[190],{"name":184,"url":181},[62,26,192,193,194],"农业绿色转型","农业社会化服务","县域面板数据",[196,197],"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":199,"openalex_id":201,"authors":202,"venue":184,"cited_by_count":35,"oa_url":213,"card":214,"direction":144,"ingested_from":147},"W7213421769",[203,206,208,211],{"name":204,"orcid":205},"Guoqun Ma","https:\u002F\u002Forcid.org\u002F0000-0002-9619-8423",{"name":207,"orcid":8},"Qin Su",{"name":209,"orcid":210},"Yan Luo","https:\u002F\u002Forcid.org\u002F0000-0002-9731-4983",{"name":212,"orcid":8},"Wenying Xiao","https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fsustainable-food-systems\u002Farticles\u002F10.3389\u002Ffsufs.2026.1869475\u002Fpdf",{"tldr":215,"method":216,"finding":217,"direction":144,"opportunity":218},"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。","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。","2026-09-17T23:30:08.126393Z",{"id":221,"title":222,"url":223,"summary":224,"summary_zh":8,"content":8,"source_name":225,"source_url":8,"published_at":226,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":156,"score_detail":227,"sources":231,"tags":233,"search_phrases":237,"slug":240,"view_count":35,"doi":8,"paper":241,"created_at":248},2216,"《数字普惠金融与农业新质生产力:来自中国的证据》","https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F17\u002F9149","Songqi Liu等(辽宁大学、沈阳农业大学、普渡大学)基于2011-2022年中国30个省份面板数据,考察数字普惠金融(DFI)对农业新质生产力(ANQP)的影响及其传导渠道。结果显示DFI显著正向促进ANQP,DFI每增加一个标准差,ANQP相应增加约样本均值64.35%。绿色技术创新是统计显著的传导渠道,但间接效应仅占总效应的3.31%。DFI与ANQP关系在DFI水平上呈双门槛模式,在区域经济发展水平上呈单门槛模式。","Sustainability 2026年9月7日","2026-09-07T00:00:00Z",{"impact":18,"substance":16,"depth":228,"authority":116,"freshness":229,"relevant":21,"comment":230},19,8,"基于30省11年面板数据的实证研究，量化了数字普惠金融对农业新质生产力的促进效应与门槛特征，结论具体、方法规范，对数字乡村金融政策有参考价值。",[232],{"name":225,"url":223},[62,234,235,27,236],"农业经济","农业新质生产力","绿色技术创新",[238,239],"农业新质生产力 数字普惠金融 绿色技术创新 农业经济","农业新质生产力 数字普惠金融","农业新质生产力数字普惠金融绿色技术创新农业经济-2216",{"doi":8,"openalex_id":8,"authors":242,"venue":8,"cited_by_count":35,"oa_url":8,"card":243,"direction":42,"ingested_from":44},[],{"tldr":244,"method":245,"finding":246,"direction":42,"opportunity":247},"基于中国30省面板数据，实证检验数字普惠金融对农业新质生产力的促进效应及传导渠道。","2011-2022年30省面板数据，面板回归与门槛模型","数字普惠金融显著促进农业新质生产力，绿色技术创新为传导渠道但间接效应仅占3.31%。","绿色技术创新中介效应极弱，可挖掘其他传导机制及数字普惠金融赋能农业新质生产力的微观路径。","2026-09-12T00:06:40.610993Z"]