[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-2110":3,"related-2110":84},{"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,"primary_topic":31,"secondary_topics":37,"classification":38,"search_phrases":69,"slug":72,"view_count":45,"doi":8,"paper":73,"created_at":83},2110,"《绿色算力建设驱动农业数字化绿色化协同发展的机制研究》 249地级市3 237观测值渐进DID","https:\u002F\u002Fnyxdhyj.isa.ac.cn\u002F","在\"双碳\"目标与数字中国战略双重驱动下,以国家绿色数据中心试点为准自然实验,基于2011—2023年全国249个地级市3237个城市-年份观测值,采用渐进双重差分模型考察绿色算力建设对农业数字化绿色化协同发展的影响及机制。研究发现绿色算力建设显著提升农业数字化绿色化耦合协调度(系数0.076,1%显著水平),主要通过促进数据要素流通、扩大清洁能源应用、推动绿色算力与农业技术融合。西部地区政策效应显著强于东北地区。",null,"农业现代化研究","2026-09-07T00:00:00Z","论文",10,false,84,{"impact":16,"substance":17,"depth":18,"authority":19,"freshness":20,"relevant":21,"comment":22},22,23,19,14,6,1,"基于249个地级市3237个观测值的渐进DID实证，量化绿色算力对农业数字化绿色化协同的促进效应，方法规范、数据规模大，对数字乡村与农业绿色发展政策有参考价值。",[24],{"name":9,"url":6},[26,27,28,29,30],"数字乡村","数据要素","农业绿色发展","农业数字化","绿色算力",{"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":13,"version":40,"method":41,"evidence":42},"classified","2026-10-22.2","rules",{"candidates":43,"agricultural_evidence":46},[44,50,55,60,64],{"code":32,"score":45,"supported":46,"title":47,"abstract":48,"tags":49},5,true,[],[27],[26,27],{"code":51,"score":21,"supported":13,"title":52,"abstract":53,"tags":54},"H4",[],[],[28],{"code":56,"score":21,"supported":13,"title":57,"abstract":58,"tags":59},"H8",[],[],[28],{"code":36,"score":21,"supported":13,"title":61,"abstract":62,"tags":63},[],[],[29],{"code":65,"score":21,"supported":13,"title":66,"abstract":67,"tags":68},"I1",[],[],[29],[70,71],"农业绿色发展 农业数字化 数字乡村 数据要素","农业绿色发展 农业数字化","农业绿色发展农业数字化数字乡村数据要素-2110",{"doi":8,"openalex_id":8,"authors":74,"venue":8,"cited_by_count":75,"oa_url":8,"card":76,"direction":80,"ingested_from":82},[],0,{"tldr":77,"method":78,"finding":79,"direction":80,"opportunity":81},"以国家绿色数据中心试点为准自然实验，检验绿色算力建设对农业数字化绿色化协同发展的影响。","2011—2023年249个地级市3237个观测值，渐进双重差分模型。","绿色算力建设显著提升农业数字化绿色化耦合协调度，西部效应强于东北。","农业绿色发展与碳","可探究绿色算力对不同农业细分行业与经营主体的异质性影响，及数据要素流通的微观路径。","agent","2026-09-11T00:04:22.926298Z",{"total":20,"page":21,"page_size":20,"items":85},[86,150,189,249,315,397],{"id":87,"title":88,"url":89,"summary":90,"summary_zh":8,"content":8,"source_name":91,"source_url":8,"published_at":8,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":92,"score_detail":93,"sources":100,"tags":102,"primary_topic":106,"secondary_topics":107,"classification":108,"search_phrases":138,"slug":141,"view_count":75,"doi":8,"paper":142,"created_at":149},5226,"How does agricultural digitalization drive green total factor productivity? Evidence from rural industrial integration, data factor allocation, and spatial effects in China","https:\u002F\u002Fwww.lnu.edu.cn\u002Finfo\u002F15114\u002F84907.htm","辽宁大学经济学院和军教授等在《Frontiers in Sustainable Food Systems》2026年第10卷发表的论文,基于中国省级面板数据,采用Super-SBM模型与GML指数,发现农业数字化通过农村产业融合中介与数据要素配置调节显著提升农业绿色全要素生产率,并对邻近地区产生正向溢出,为农业绿色转型提供理论依据。","Frontiers in Sustainable Food Systems 10(2026)",71,{"impact":94,"substance":95,"depth":96,"authority":97,"freshness":98,"relevant":21,"comment":99},18,21,17,13,2,"基于省级面板数据的实证研究，方法规范、结论有新意，但属学术论文且发布日期不明，时效性弱，适合作为研究参考而非每日精选头条。",[101],{"name":91,"url":89},[27,103,29,104,105],"空间溢出","绿色全要素生产率","农村产业融合",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":13,"version":40,"method":41,"evidence":109},{"candidates":110,"agricultural_evidence":46},[111,116,121,125,129,133],{"code":32,"score":112,"supported":46,"title":113,"abstract":114,"tags":115},4,[],[27],[27],{"code":117,"score":21,"supported":13,"title":118,"abstract":119,"tags":120},"G4",[],[],[105],{"code":51,"score":21,"supported":13,"title":122,"abstract":123,"tags":124},[],[],[104],{"code":36,"score":21,"supported":13,"title":126,"abstract":127,"tags":128},[],[],[29],{"code":65,"score":21,"supported":13,"title":130,"abstract":131,"tags":132},[],[],[29],{"code":134,"score":21,"supported":13,"title":135,"abstract":136,"tags":137},"I4",[],[],[103],[139,140],"辽宁大学 农业数字化 绿色全要素生产率","农村产业融合 数据要素 空间杜宾","辽宁大学农业数字化绿色全要素生产率-5226",{"doi":8,"openalex_id":8,"authors":143,"venue":8,"cited_by_count":75,"oa_url":8,"card":144,"direction":80,"ingested_from":82},[],{"tldr":145,"method":146,"finding":147,"direction":80,"opportunity":148},"基于中国省级面板数据，检验农业数字化对农业绿色全要素生产率的影响及机制。","Super-SBM模型与GML指数测算GTFP，省级面板数据中介与调节效应分析。","农业数字化显著提升农业绿色全要素生产率，农村产业融合起中介作用，数据要素配置起调节作用，并存在正向空","可深入微观主体或县域尺度，检验数据要素配置的门槛效应与空间溢出的衰减边界。","2026-10-18T00:05:30.603519Z",{"id":151,"title":152,"url":153,"summary":154,"summary_zh":8,"content":8,"source_name":155,"source_url":8,"published_at":156,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":14,"score_detail":157,"sources":160,"tags":162,"primary_topic":166,"secondary_topics":167,"classification":168,"search_phrases":176,"slug":179,"view_count":21,"doi":8,"paper":180,"created_at":188},5061,"国家数字乡村试点政策能否促进农业产业链和创新链融合发展","http:\u002F\u002Fjsjj.ijournals.cn\u002Ftechnology_economics\u002Fhome","鄢城名在《科学技术与工程》2026-10-14优先出版的研究,将国家数字乡村试点政策作为准自然实验,依托2016-2024年766个县(县级市、区)的面板数据,借助多期双重差分模型与中介效应模型,实证检验国家数字乡村试点政策对农业产业链和创新链融合发展的影响效应及中介效应。研究发现:国家数字乡村试点政策可正向促进农业产业链和创新链融合发展,且该结果经由系列稳健性检验后证实具有稳健性;中介效应检验发现,数据要素配置、耐心资本投入是核心中介变量;异质性检验发现,试点政策对低海拔、劳动力规模较大地区的促进效应更强。研究结论可为稳步推动农业产业链和创新链融合发展提供实践参考。","《科学技术与工程》优先出版 2026-10-14","2026-10-14T00:00:00Z",{"impact":16,"substance":16,"depth":94,"authority":19,"freshness":158,"relevant":21,"comment":159},8,"基于766个县面板数据的准自然实验研究，方法规范、结论稳健，对数字乡村与产业链创新链融合政策有实证参考价值。",[161],{"name":155,"url":153},[26,27,163,164,165],"农业产业链","创新链融合","耐心资本",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":13,"version":40,"method":41,"evidence":169},{"candidates":170,"agricultural_evidence":46},[171],{"code":32,"score":172,"supported":46,"title":173,"abstract":174,"tags":175},16,[26],[26,27],[26,27],[177,178],"国家数字乡村试点 农业产业链 创新链","数字乡村试点 县域面板数据","国家数字乡村试点农业产业链创新链-5061",{"doi":8,"openalex_id":8,"authors":181,"venue":8,"cited_by_count":75,"oa_url":8,"card":182,"direction":186,"ingested_from":82},[],{"tldr":183,"method":184,"finding":185,"direction":186,"opportunity":187},"以国家数字乡村试点为准自然实验，检验政策对农业产业链与创新链融合的促进效应。","2016-2024年766县面板数据，多期双重差分与中介效应模型。","试点政策显著促进两链融合，数据要素配置与耐心资本投入是核心中介。","数字乡村与农业信息化","可探究数据要素与耐心资本如何协同驱动两链融合，并关注高海拔与劳动力不足地区的差异化政策设计。","2026-10-16T00:14:00.876540Z",{"id":190,"title":191,"url":192,"summary":193,"summary_zh":8,"content":8,"source_name":194,"source_url":8,"published_at":195,"category":196,"cover_url":8,"hotness":12,"is_selected":13,"score":197,"score_detail":198,"sources":201,"tags":203,"primary_topic":207,"secondary_topics":208,"classification":209,"search_phrases":244,"slug":247,"view_count":98,"doi":8,"paper":8,"created_at":248},4941,"农业(种植)行业可信数据空间首批成果发布 杭州拱墅打造'DeepSeek+农业'新高地","https:\u002F\u002Fszb.farmer.com.cn\u002Fnmrb\u002Fhtml\u002F2026\u002F20261013\u002F20261013_6\u002Fnmrb_20261013_13424_6_2109757807733608524.html","第五届全球数字贸易博览会'数据要素治理与市场化交流'专场活动上,发布农业(种植)行业可信数据空间首批5个高价值场景和首批50个生态伙伴。中国水稻研究所、中国农业科学院茶叶研究所、杭州市数据局、浙江省数据集团等共同发布。空间已统筹接入公共、科研、产业、企业四类资源,汇聚涵盖水稻、茶、番茄、脐橙等近40个典型场景,贯通病虫害防治、金融服务等近20个领域。","农民日报 2026 年 10 月 13 日","2026-10-13T00:00:00Z","报道",87,{"impact":199,"substance":16,"depth":96,"authority":19,"freshness":158,"relevant":21,"comment":200},26,"全国首个农业种植行业可信数据空间首批成果落地，场景与生态伙伴数据具体，产业级意义突出，值得进入每日精选。",[202],{"name":194,"url":192},[26,204,205,27,206],"智慧农业","农业人工智能","农业数据空间",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":13,"version":40,"method":41,"evidence":210},{"candidates":211,"agricultural_evidence":46},[212,216,223,229,235,239],{"code":32,"score":45,"supported":46,"title":213,"abstract":214,"tags":215},[],[27],[26,27],{"code":217,"score":218,"supported":46,"title":219,"abstract":220,"tags":222},"A1",3,[],[221],"水稻",[],{"code":224,"score":218,"supported":46,"title":225,"abstract":226,"tags":228},"B1",[],[227],"番茄",[],{"code":230,"score":218,"supported":46,"title":231,"abstract":232,"tags":234},"B3",[],[233],"茶叶",[],{"code":65,"score":21,"supported":13,"title":236,"abstract":237,"tags":238},[],[],[204],{"code":240,"score":21,"supported":13,"title":241,"abstract":242,"tags":243},"I2",[],[],[205],[245,246],"DeepSeek 拱墅","农业人工智能 农业数据空间 数字乡村 数据要素","DeepSeek拱墅-4941","2026-10-15T00:06:02.166271Z",{"id":250,"title":251,"url":252,"summary":253,"summary_zh":254,"content":8,"source_name":255,"source_url":252,"published_at":256,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":14,"score_detail":257,"sources":260,"tags":262,"primary_topic":266,"secondary_topics":267,"classification":268,"search_phrases":295,"slug":298,"view_count":218,"doi":299,"paper":300,"created_at":314},4033,"The Upgrading and Transformation of Farmer Professional Cooperative in the Digital Age: Insights from China Digital Village Policy","https:\u002F\u002Fdoi.org\u002F10.3390\u002Feconomies14100435","Farmer professional cooperatives are important vehicles for agricultural modernisation. In the digital age, the development of cooperatives has followed two typical pathways: upgrading in scale and transformation in business operations. Existing research has focused on the impact of digitalisation on the former, while paying less attention to the issue of structural transformation within cooperatives. To investigate this issue, this study constructs a difference-in-differences model based on a sample of data from Chinese farmer professional cooperatives. By leveraging the quasi-natural experiment of the digital village policy to construct variables, this study examines the impact of rural digitalisation on cooperative upgrading and transformation and analyses the mechanisms driving the divergence of cooperative development pathways. The study indicates that: (1) The China Digital Village Policy has had a significant positive impact on both the transformation and upgrading of farmer professional cooperatives. (2) Conditional on observable variables, the China Digital Village Policy is positively associated with cooperative upgrading and transformation, with patterns consistent with potential pathways through information channel capability and technological innovation capability. (3) Under the same observable-variable constraints, market expansion capability and capital acquisition capability show conditional association patterns that are significantly positively associated with cooperative upgrading. For cooperative transformation, however, they show conditional suppression patterns. This indicates that agricultural digitalisation is closely linked to cooperative upgrading and transformation. The differentiated empirical patterns of digitalisation along the dimensions of information channels, technological innovation, market expansion and capital acquisition provide empirical evidence for understanding the pathways of cooperative differentiation.","农民专业合作社是农业现代化的重要载体。在数字时代，合作社发展遵循了两条典型路径：规模升级与经营转型。已有研究主要关注数字化对前者的影响，而对合作社结构转型问题关注不足。为探究这一问题，本研究基于中国农民专业合作社数据样本构建了双重差分模型。通过利用数字乡村政策的准自然实验构建变量，本研究考察了乡村数字化对合作社升级与转型的影响，并分析了驱动合作社发展路径分化的机制。研究表明：(1) 中国数字乡村政策对农民专业合作社的转型与升级均产生了显著正向影响。(2) 在可观测变量条件下，中国数字乡村政策与合作社升级和转型呈正相关，其模式与通过信息渠道能力和技术创新能力的潜在路径相一致。(3) 在相同的可观测变量约束下，市场拓展能力和资本获取能力与合作社升级呈现显著正相关的条件关联模式；然而对于合作社转型，它们则呈现条件抑制模式。这表明农业数字化与合作社升级和转型密切相关。数字化在信息渠道、技术创新、市场拓展和资本获取等维度上的差异化实证模式，为理解合作社分化路径提供了经验证据。","Economies","2026-10-01T00:00:00Z",{"impact":16,"substance":16,"depth":94,"authority":97,"freshness":258,"relevant":21,"comment":259},9,"基于中国数字乡村政策准自然实验的双重差分研究，方法规范、结论有新意，对数字乡村与合作社发展路径具参考价值。",[261],{"name":255,"url":252},[26,29,263,264,265],"农业现代化","农民合作社","合作社转型",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":13,"version":40,"method":41,"evidence":269},{"candidates":270,"agricultural_evidence":46},[271,277,282,287,291],{"code":32,"score":272,"supported":46,"title":273,"abstract":275,"tags":276},15,[274],"digital village",[26,274],[26],{"code":278,"score":112,"supported":46,"title":279,"abstract":280,"tags":281},"J2",[],[263],[263],{"code":283,"score":21,"supported":13,"title":284,"abstract":285,"tags":286},"G2",[],[],[264],{"code":36,"score":21,"supported":13,"title":288,"abstract":289,"tags":290},[],[],[29],{"code":65,"score":21,"supported":13,"title":292,"abstract":293,"tags":294},[],[],[29],[296,297],"中国数字乡村政策 农民专业合作社","数字乡村 合作社 转型升级","中国数字乡村政策农民专业合作社-4033","10.3390\u002Feconomies14100435",{"doi":299,"openalex_id":301,"authors":302,"venue":255,"cited_by_count":75,"oa_url":252,"card":308,"direction":186,"ingested_from":313},"W7215037926",[303,305],{"name":304,"orcid":8},"Yingying Zhang",{"name":306,"orcid":307},"Yaodong Zhou","https:\u002F\u002Forcid.org\u002F0000-0002-7573-2850",{"tldr":309,"method":310,"finding":311,"direction":186,"opportunity":312},"基于中国数字乡村政策准自然实验，用双重差分法检验数字化对农民合作社升级与转型的影响。","双重差分模型，中国农民专业合作社样本，数字乡村政策准自然实验。","数字乡村政策显著促进合作社升级与转型，信息渠道与技术创新为潜在路径，市场与资本能力对升级促进、对转型","可深入探究市场扩张与资本获取能力为何抑制合作社业务转型，及其组织与制度边界条件。","openalex","2026-10-02T23:30:30.775133Z",{"id":316,"title":317,"url":318,"summary":319,"summary_zh":320,"content":8,"source_name":321,"source_url":318,"published_at":322,"category":11,"cover_url":8,"hotness":323,"is_selected":13,"score":324,"score_detail":325,"sources":327,"tags":332,"primary_topic":336,"secondary_topics":337,"classification":344,"search_phrases":369,"slug":372,"view_count":20,"doi":373,"paper":374,"created_at":396},3562,"Toward Common Prosperity: Spatially Heterogeneous Effects and Mechanisms of Digital Village Construction on the Urban–Rural Income Gap in Mountainous China","https:\u002F\u002Fdoi.org\u002F10.3390\u002Fland15101801","Mountainous regions are critical to promoting inclusive growth and reducing spatial inequality worldwide. Digital village construction offers a new pathway to overcome geographical constraints and reshape urban–rural income distribution in these areas. Using county-level data for 2020 and focusing on mountainous China, this study integrates the Theil index, IV-2SLS, MGWR, and mediation models to characterize the spatial pattern of the urban–rural income gap (URIG) and identify the spatially heterogeneous effects and potential mechanisms of digital village construction across different geomorphological settings. The results indicate that: (1) Large and highly dispersed URIG are concentrated in mountainous regions. On average, the gap is approximately twice as large as that in non-mountainous regions and varies markedly across geomorphological types. URIG is highest in mountain counties, shows the greatest variation in plateau counties, and tends to be lower in hill counties. (2) Digital village construction exerts a significant negative effect on URIG in mountainous China, with the effect being stronger than in non-mountainous regions and generally increasing in magnitude from east to west. (3) The effects of different DVI dimensions on URIG exhibit substantial spatial heterogeneity and vary in their spatial scales of influence. Rural economy digitalization shows widespread and consistently negative effects and emerges as the dominant dimension across most mountainous regions, while the effect of other dimensions is more localized, particularly rural life digitalization, which shows stronger negative effects in mountain counties, plateau counties, and underdeveloped mountainous counties. (4) Agricultural operation modernization and labor allocation optimization constitute potential channels underlying the association between digital village construction and a narrower URIG, with the estimated indirect effect being more pronounced through labor allocation optimization. These findings provide empirical evidence for advancing inclusive development in mountainous regions amid China’s common prosperity agenda, with broader implications for place-based digital village construction.","山区对于促进包容性增长和缩小全球空间不平等至关重要。数字乡村建设为这些地区突破地理约束、重塑城乡收入分配格局提供了新路径。本研究以2020年县级数据为基础，聚焦中国山区，综合运用泰尔指数、IV-2SLS、MGWR和中介模型，刻画城乡收入差距（URIG）的空间格局，并识别数字乡村建设在不同地貌条件下的空间异质性效应及其潜在机制。结果表明：（1）规模较大且高度分散的URIG集中于山区。其平均值约为非山区的两倍，且在不同地貌类型间差异显著。URIG在山区县最高，在高原县变异最大，在丘陵县则趋于较低水平。（2）数字乡村建设对中国山区URIG具有显著负向影响，其效应强于非山区，且总体上呈自东向西递增态势。（3）数字乡村建设不同维度对URIG的影响表现出显著的空间异质性，且其影响的空间尺度各异。农村经济数字化呈现出广泛且稳定的负向效应，并在大多数山区成为主导维度，而其他维度的效应则更具局部性，尤其是农村生活数字化，在山区县、高原县及欠发达山区县表现出更强的负向效应。（4）农业经营现代化和劳动力配置优化构成数字乡村建设与URIG缩小之间关联的潜在渠道，其中通过劳动力配置优化的间接效应更为明显。上述发现为中国共同富裕议程下推进山区包容性发展提供了经验证据，并对因地制宜推进数字乡村建设具有更广泛的启示。","Land","2026-09-25T00:00:00Z",25,80,{"impact":94,"substance":16,"depth":94,"authority":97,"freshness":258,"relevant":21,"comment":326},"基于县域数据的实证研究，方法扎实、结论对山区数字乡村政策有参考价值，但属学术论文，公共传播热度有限。",[328,329],{"name":321,"url":318},{"name":330,"url":331},"MDPI Land 15(10), 1801 2026-09-25","https:\u002F\u002Fwww.mdpi.com\u002F2073-445X\u002F15\u002F10\u002F1801",[26,333,29,334,335],"县域经济","山区农业","城乡收入差距",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[338],{"code":339,"slug":340,"name":341,"path":342,"parent_code":343},"G6","rural-integration","帮扶与城乡融合","\u002Ftopic\u002Frural-services\u002Frural-integration","G",{"status":39,"locked":13,"version":40,"method":41,"evidence":345},{"candidates":346,"agricultural_evidence":46},[347,351,357,361,365],{"code":32,"score":272,"supported":46,"title":348,"abstract":349,"tags":350},[274],[26,274],[26],{"code":339,"score":352,"supported":46,"title":353,"abstract":355,"tags":356},12,[354],"rural income",[354],[335],{"code":117,"score":21,"supported":13,"title":358,"abstract":359,"tags":360},[],[],[333],{"code":36,"score":21,"supported":13,"title":362,"abstract":363,"tags":364},[],[],[29],{"code":65,"score":21,"supported":13,"title":366,"abstract":367,"tags":368},[],[],[29],[370,371],"数字乡村 城乡收入差距 山区","县域 数字乡村 泰尔指数","数字乡村城乡收入差距山区-3562","10.3390\u002Fland15101801",{"doi":373,"openalex_id":375,"authors":376,"venue":321,"cited_by_count":75,"oa_url":318,"card":391,"direction":186,"ingested_from":313},"W7214349448",[377,380,383,386,388],{"name":378,"orcid":379},"Xueting Yang","https:\u002F\u002Forcid.org\u002F0000-0003-4633-2185",{"name":381,"orcid":382},"Xiaoping Qiu","https:\u002F\u002Forcid.org\u002F0000-0001-6310-5959",{"name":384,"orcid":385},"Fubiao Zhu","https:\u002F\u002Forcid.org\u002F0000-0002-4606-3336",{"name":387,"orcid":8},"Mingkai Xu",{"name":389,"orcid":390},"Yun Xu","https:\u002F\u002Forcid.org\u002F0000-0002-2442-7792",{"tldr":392,"method":393,"finding":394,"direction":186,"opportunity":395},"研究数字乡村建设对中国山区城乡收入差距的空间异质性影响及机制。","用2020年县级数据，结合泰尔指数、IV-2SLS、MGWR与中介模型。","数字乡村建设显著缩小山区城乡收入差距，效应自东向西增强，且存在地貌与维度异质性。","可深入探究不同地貌下数字乡村各维度的空间尺度差异及劳动力配置中介的微观路径。","2026-09-26T23:30:38.665617Z",{"id":398,"title":399,"url":400,"summary":401,"summary_zh":8,"content":8,"source_name":402,"source_url":8,"published_at":403,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":404,"score_detail":405,"sources":407,"tags":409,"primary_topic":412,"secondary_topics":413,"classification":414,"search_phrases":433,"slug":436,"view_count":437,"doi":438,"paper":439,"created_at":446},2109,"《Digital villages and agricultural green total factor productivity》 数字乡村试点DID评估AGTFP","https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fsustainable-food-systems\u002Farticles\u002F10.3389\u002Ffsufs.2026.1831978\u002Ffull","Guo Hui、Wang Xinyi、Xia He、Jiang Wenjie基于2014—2023年中国县级面板数据,采用超效率SBM-DDF-GML模型测算AGTFP,以国家数字乡村试点为准自然实验,运用双重差分法评估数字乡村建设对AGTFP的影响、机制与空间溢出效应。结果显示数字乡村显著提升AGTFP,主要通过绿色技术进步而非绿色技术效率改善;机制上通过优化劳动力配置、激发农业经营创业、扩大消费实现;政策效应在靠近省会城市、地形起伏大、路网密度低的地区更显著。","Frontiers in Sustainable Food Systems 10:1831978","2026-09-05T00:00:00Z",82,{"impact":16,"substance":17,"depth":94,"authority":97,"freshness":20,"relevant":21,"comment":406},"基于县级面板与试点准自然实验，方法规范、结论明确，对数字乡村政策评估有参考价值。",[408],{"name":402,"url":400},[26,333,28,410,411],"政策评估","全要素生产率",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":13,"version":40,"method":41,"evidence":415},{"candidates":416,"agricultural_evidence":46},[417,421,425,429],{"code":32,"score":352,"supported":46,"title":418,"abstract":419,"tags":420},[26],[26],[26],{"code":117,"score":21,"supported":13,"title":422,"abstract":423,"tags":424},[],[],[333],{"code":51,"score":21,"supported":13,"title":426,"abstract":427,"tags":428},[],[],[28],{"code":56,"score":21,"supported":13,"title":430,"abstract":431,"tags":432},[],[],[28],[434,435],"全要素生产率 农业绿色发展 县域经济 政策评估","全要素生产率 农业绿色发展","全要素生产率农业绿色发展县域经济政策评估-2109",7,"10.3389\u002Ffsufs.2026.1831978\u002Ffull",{"doi":438,"openalex_id":8,"authors":440,"venue":8,"cited_by_count":75,"oa_url":8,"card":441,"direction":186,"ingested_from":82},[],{"tldr":442,"method":443,"finding":444,"direction":186,"opportunity":445},"基于县级面板数据，用DID评估数字乡村试点对农业绿色全要素生产率的影响。","超效率SBM-DDF-GML测算AGTFP，双重差分法，2014—2023年县级","数字乡村显著提升AGTFP，主要靠绿色技术进步，通过劳动力配置、创业和消费实现。","可探究数字乡村对AGTFP的空间溢出边界及绿色技术效率滞后原因。","2026-09-11T00:04:22.864968Z"]