[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-2404":3,"related-2404":65},{"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":22,"tags":24,"primary_topic":8,"secondary_topics":30,"classification":31,"search_phrases":49,"slug":52,"view_count":53,"doi":8,"paper":54,"created_at":64},2404,"数林协同发展的农村居民增收机制——基于浙江省山区26县的实证检验","http:\u002F\u002Fwww.qikanvip.com\u002Fqkml\u002F169001.html","林业经济问题2026年第01期。徐彩瑶、严露、吴芸茜等基于浙江省山区26县2001-2023年面板数据，综合运用双向固定效应、中介效应、面板门槛、调节效应与空间杜宾模型实证检验。结果表明：数林协同发展能显著提升山区农村居民收入；人力资本升级与就业机会增加是关键路径；存在双门槛效应；具有正向空间溢出效应，能带动邻近地区农村居民收入增长。",null,"林业经济问题 | 2026-09-08","2026-09-08T00:00:00Z","论文",10,false,78,{"impact":16,"substance":17,"depth":16,"authority":18,"freshness":19,"relevant":20,"comment":21},18,22,14,6,1,"基于浙江山区26县长面板数据的实证研究，方法扎实、结论明确，对数字技术与林业协同促进山区增收有参考价值，但属学术论文且时效性一般。",[23],{"name":9,"url":6},[25,26,27,28,29],"数字乡村","空间溢出","林业经济","农村居民增收","浙江山区",[],{"status":32,"locked":13,"version":33,"method":34,"evidence":35},"unclassified","2026-10-22.2","rules",{"candidates":36,"agricultural_evidence":47,"reason":48},[37,42],{"code":38,"score":20,"supported":13,"title":39,"abstract":40,"tags":41},"I4",[],[],[26],{"code":43,"score":20,"supported":13,"title":44,"abstract":45,"tags":46},"I6",[],[],[25],true,"缺少足够的主题证据",[50,51],"农村居民增收 数字乡村 林业经济 浙江山区","农村居民增收 数字乡村","农村居民增收数字乡村林业经济浙江山区-2404",3,{"doi":8,"openalex_id":8,"authors":55,"venue":8,"cited_by_count":56,"oa_url":8,"card":57,"direction":61,"ingested_from":63},[],0,{"tldr":58,"method":59,"finding":60,"direction":61,"opportunity":62},"基于浙江山区26县面板数据，实证检验数林协同发展对农村居民增收的机制与空间效应。","2001-2023年面板数据，双向固定效应、中介、门槛、调节与空间杜宾模型。","数林协同显著提升山区农村居民收入，人力资本与就业是关键路径，存在双门槛与正向空间溢出。","数字乡村与农业信息化","可探究数林协同的数字化测度与跨区域溢出边界，及不同山区类型的门槛异质性。","agent","2026-09-14T00:06:33.614332Z",{"total":19,"page":20,"page_size":19,"items":66},[67,108,181,236,287,352],{"id":68,"title":69,"url":70,"summary":71,"summary_zh":8,"content":8,"source_name":72,"source_url":8,"published_at":73,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":74,"score_detail":75,"sources":77,"tags":79,"primary_topic":8,"secondary_topics":83,"classification":84,"search_phrases":95,"slug":98,"view_count":56,"doi":99,"paper":100,"created_at":107},5461,"Research on the multidimensional impact effects of the rural digital economy on the resilience of agricultural development: evidence from 30 provinces in China（农村数字经济对农业发展韧性的多维影响效应：来自中国30个省份的证据）","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1057\u002Fs41599-026-09360-9","基于2011—2022年30个省份数据，熵值法测度农村数字经济与农业韧性，用空间杜宾模型检验直接效应、空间溢出与技术进步中介。直接效应在西部与非粮食主产区更显著，溢出在东部与主产区更显著，技术进步仅有本地中介。","Humanities and Social Sciences Communications 2026-10-17","2026-10-17T00:00:00Z",82,{"impact":17,"substance":17,"depth":16,"authority":18,"freshness":19,"relevant":20,"comment":76},"基于30省11年面板数据的实证研究，方法规范、结论有区域异质性价值，属数字乡村与农业经济交叉领域的高质量论文，值得进入每日精选。",[78],{"name":72,"url":70},[25,80,26,81,82],"农业韧性","省级面板","农村数字经济",[],{"status":32,"locked":13,"version":33,"method":34,"evidence":85},{"candidates":86,"agricultural_evidence":47,"reason":48},[87,91],{"code":38,"score":20,"supported":13,"title":88,"abstract":89,"tags":90},[],[],[26],{"code":43,"score":20,"supported":13,"title":92,"abstract":93,"tags":94},[],[],[25],[96,97],"农村数字经济 农业韧性","空间杜宾模型 省级面板","农村数字经济农业韧性-5461","10.1057\u002Fs41599-026-09360-9",{"doi":99,"openalex_id":8,"authors":101,"venue":8,"cited_by_count":56,"oa_url":8,"card":102,"direction":61,"ingested_from":63},[],{"tldr":103,"method":104,"finding":105,"direction":61,"opportunity":106},"基于2011—2022年30省数据，检验农村数字经济对农业发展韧性的多维影响效应。","熵值法测度农村数字经济与农业韧性，空间杜宾模型检验直接、溢出与中介效应。","直接效应在西部与非粮食主产区更显著，溢出效应在东部与主产区更显著，技术进步仅具本地中介。","可深入探究技术进步跨区溢出缺失的机制，并识别主产区与非主产区差异化数字乡村政策路径。","2026-10-21T00:10:08.312922Z",{"id":109,"title":110,"url":111,"summary":112,"summary_zh":113,"content":8,"source_name":114,"source_url":111,"published_at":115,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":116,"score_detail":117,"sources":122,"tags":124,"primary_topic":8,"secondary_topics":128,"classification":129,"search_phrases":159,"slug":162,"view_count":56,"doi":163,"paper":164,"created_at":180},5373,"Can rural digitalization promote the green transformation of cultivated land? Evidence from rural China","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1831062","Exploring how rural digitalization influences the green transformation of cultivated land and its spatial spillover effects holds significant implications for resolving the contradiction between cultivated land conservation and sustainable agricultural development, as well as advancing agricultural and rural modernization. With an emphasis on its underlying mechanisms, regional heterogeneity, and spatial spillover effects, this paper systematically examines how rural digitalization affects the greening transformation of cultivated land using panel data from 31 Chinese provinces over the 2011–2023 period and econometric techniques. The results show: (1) The level of green transformation of cultivated land in China has steadily risen, with a spatial gradient characterized by “leading in the eastern coastal areas, steady in central China, and lagging in the western and northeastern regions”; (2) Rural digitalization significantly promotes the green transformation of cultivated land by facilitating industrial structure upgrading, improving human capital, and optimizing land resource allocation; (3) Rural digitalization has a significantly positive spatial spillover effect on green transformation, raising the greening level of surrounding cultivated lands; (4) The impact of rural digitalization exhibits pronounced regional and digitalization-level heterogeneity. In addition to offering empirical data and useful insights for developing unique policies and promoting regional cooperative governance, this study enhances theoretical viewpoints on digital villages and green agricultural growth.","探究乡村数字化对耕地绿色转型的影响及其空间溢出效应，对于破解耕地保护与农业可持续发展之间的矛盾、推进农业农村现代化具有重要意义。本文以作用机制、区域异质性和空间溢出效应为重点，基于2011—2023年中国31个省份的面板数据，运用计量经济学方法，系统考察了乡村数字化如何影响耕地绿色转型。结果表明：(1)中国耕地绿色转型水平稳步上升，呈现“东部沿海领先、中部平稳、西部和东北地区滞后”的空间梯度特征；(2)乡村数字化通过促进产业结构升级、提升人力资本和优化土地资源配置，显著推动耕地绿色转型；(3)乡村数字化对耕地绿色转型具有显著的正向空间溢出效应，能够提升周边地区耕地的绿色化水平；(4)乡村数字化的影响表现出明显的区域异质性和数字化水平异质性。本研究不仅为制定差异化政策和推进区域协同治理提供了经验数据和有益启示，也丰富了对数字乡村与农业绿色发展的理论认识。","Frontiers in Sustainable Food Systems","2026-10-19T00:00:00Z",81,{"impact":16,"substance":17,"depth":118,"authority":119,"freshness":120,"relevant":20,"comment":121},19,13,9,"基于31省面板数据的实证研究，方法规范、结论有新意，对数字乡村与耕地绿色转型政策有参考价值，值得进入每日精选。",[123],{"name":114,"url":111},[25,26,125,126,127],"农业现代化","绿色转型","耕地保护",[],{"status":130,"locked":13,"version":33,"method":34,"evidence":131},"needs_review",{"candidates":132,"agricultural_evidence":47,"reason":158},[133,139,143,149,154],{"code":134,"score":135,"supported":47,"title":136,"abstract":137,"tags":138},"H1",4,[],[127],[127],{"code":43,"score":135,"supported":47,"title":140,"abstract":141,"tags":142},[],[25],[25],{"code":144,"score":135,"supported":47,"title":145,"abstract":146,"tags":148},"J2",[],[147],"农业农村现代化",[125],{"code":150,"score":20,"supported":13,"title":151,"abstract":152,"tags":153},"H4",[],[],[126],{"code":38,"score":20,"supported":13,"title":155,"abstract":156,"tags":157},[],[],[26],"多个产业证据相当，需要确认主归属",[160,161],"农村数字化 耕地绿色转型","数字乡村 空间溢出效应","农村数字化耕地绿色转型-5373","10.3389\u002Ffsufs.2026.1831062",{"doi":163,"openalex_id":165,"authors":166,"venue":114,"cited_by_count":56,"oa_url":111,"card":173,"direction":61,"ingested_from":179},"W7222979824",[167,169,171],{"name":168,"orcid":8},"Yifeng Lv",{"name":170,"orcid":8},"Daichen Guo",{"name":172,"orcid":8},"Sanglin Zhao",{"tldr":174,"method":175,"finding":176,"direction":177,"opportunity":178},"用中国31省面板数据检验农村数字化对耕地绿色转型的影响及空间溢出。","2011–2023年31省面板数据与计量模型，含机制、异质性和空间溢出分析。","农村数字化通过产业升级、人力资本和土地配置显著促进耕地绿色转型，并具正向空间溢出。","农业绿色发展与碳","可深入县域或地块尺度，结合数字基础设施数据识别因果机制与跨区协同治理路径。","openalex","2026-10-20T23:30:07.007802Z",{"id":182,"title":183,"url":184,"summary":185,"summary_zh":8,"content":8,"source_name":186,"source_url":8,"published_at":8,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":187,"score_detail":188,"sources":191,"tags":193,"primary_topic":196,"secondary_topics":201,"classification":202,"search_phrases":224,"slug":227,"view_count":53,"doi":8,"paper":228,"created_at":235},4405,"数字化赋能农业农村现代化的逻辑机理与实证研究","http:\u002F\u002Fwww.qikanvip.com\u002Fqkml\u002F172930.html","徐卓顺、任鹏基于 2014-2024 年中国省际面板数据,构建数字化与农业农村现代化评价指标体系,结合主成分分析法提取数字化发展基础、创新能力、人力资本三大核心因子,运用 SDM 模型实证检验发现数字化对农业农村现代化的直接效应、间接效应及总效应均显著为正,存在明显的省际空间反馈效应;创新能力助推作用最强、基础设施建设水平次之;东部赋能优势突出、西部存在负向空间外溢。","吉林省社会科学院软科学所 吉林省科学技术信息研究所《吉林大学社会科学学报》2026 年第 04 期",74,{"impact":16,"substance":17,"depth":16,"authority":18,"freshness":189,"relevant":20,"comment":190},2,"基于2014-2024省际面板数据的实证研究，方法规范、结论有政策参考价值，但属学术论文且时效性偏弱，适合主题聚合而非每日精选。",[192],{"name":186,"url":184},[25,147,26,194,195],"数字化转型","省级面板数据",{"code":144,"slug":197,"name":198,"path":199,"parent_code":200},"modernization","农业强国与现代化","\u002Ftopic\u002Fpolicy\u002Fmodernization","J",[],{"status":203,"locked":13,"version":33,"method":34,"evidence":204},"classified",{"candidates":205,"agricultural_evidence":47},[206,211,216,220],{"code":144,"score":207,"supported":47,"title":208,"abstract":209,"tags":210},12,[147],[147],[147],{"code":212,"score":20,"supported":13,"title":213,"abstract":214,"tags":215},"I1",[],[],[194],{"code":38,"score":20,"supported":13,"title":217,"abstract":218,"tags":219},[],[],[26],{"code":43,"score":20,"supported":13,"title":221,"abstract":222,"tags":223},[],[],[25],[225,226],"徐卓顺 任鹏 数字化 农业农村现代化","吉林大学社会科学学报 数字化 空间溢出","徐卓顺任鹏数字化农业农村现代化-4405",{"doi":8,"openalex_id":8,"authors":229,"venue":8,"cited_by_count":56,"oa_url":8,"card":230,"direction":61,"ingested_from":63},[],{"tldr":231,"method":232,"finding":233,"direction":61,"opportunity":234},"基于省际面板数据实证检验数字化对农业农村现代化的空间效应与赋能机制。","2014-2024年省际面板数据，主成分分析提取因子，SDM空间杜宾模型。","数字化直接、间接与总效应均显著为正，创新能力助推最强，东部优势突出、西部负向外溢。","可深入探究西部负向空间外溢的成因，并检验数字鸿沟与人力资本门槛的非线性调节机制。","2026-10-08T00:07:47.101032Z",{"id":237,"title":238,"url":239,"summary":240,"summary_zh":8,"content":8,"source_name":241,"source_url":8,"published_at":242,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":187,"score_detail":243,"sources":246,"tags":248,"primary_topic":252,"secondary_topics":257,"classification":258,"search_phrases":274,"slug":277,"view_count":278,"doi":8,"paper":279,"created_at":286},3654,"数字乡村建设、农旅融合与农民农村共同富裕","http:\u002F\u002Fxn--vhqr8o5pj9uhezh2nrx2biude8o.com\u002Fqikan_detail.asp?id=13109","巴责达发表于《商业经济研究》2026年第9期。本文基于2012—2023年我国30个省份面板数据，探析数字乡村建设、农旅融合与农民农村共同富裕之间的关系。研究发现：数字乡村建设可显著影响农民农村共同富裕，这一结论在相关稳健性检验中得到验证。中介效应检验显示，数字乡村建设可通过促进农旅融合，间接赋能农民农村共同富裕。异质性分析表明，数字乡村建设对东部地区农民农村共同富裕的驱动作用更强。空间效应检验显示，数字乡村建设对本地区、邻近地区农民农村共同富裕呈现正向空间溢出效应。","商业经济研究 2026年第9期 (巴责达)","2026-09-15T00:00:00Z",{"impact":16,"substance":244,"depth":16,"authority":119,"freshness":135,"relevant":20,"comment":245},21,"基于30省面板数据的实证研究，方法规范、结论有政策参考价值，但属学术论文且已发表近两周，时效性一般。",[247],{"name":241,"url":239},[25,26,249,250,251],"共同富裕","农旅融合","省域面板数据",{"code":43,"slug":253,"name":254,"path":255,"parent_code":256},"digital-village","数字乡村与数据要素","\u002Ftopic\u002Fdigital-agriculture\u002Fdigital-village","I",[],{"status":203,"locked":13,"version":33,"method":34,"evidence":259},{"candidates":260,"agricultural_evidence":47},[261,265,270],{"code":43,"score":207,"supported":47,"title":262,"abstract":263,"tags":264},[25],[25],[25],{"code":266,"score":20,"supported":13,"title":267,"abstract":268,"tags":269},"G4",[],[],[249],{"code":38,"score":20,"supported":13,"title":271,"abstract":272,"tags":273},[],[],[26],[275,276],"数字乡村 农旅融合 共同富裕","巴责达 商业经济研究","数字乡村农旅融合共同富裕-3654",7,{"doi":8,"openalex_id":8,"authors":280,"venue":8,"cited_by_count":56,"oa_url":8,"card":281,"direction":61,"ingested_from":63},[],{"tldr":282,"method":283,"finding":284,"direction":61,"opportunity":285},"基于2012—2023年30省面板数据，检验数字乡村建设通过农旅融合促进农民农村共同富裕的效应。","30省面板数据，中介效应、异质性分析与空间溢出检验。","数字乡村建设显著促进共同富裕，农旅融合起中介作用，东部更强且有正向空间溢出。","可深入探究农旅融合的中介机制与空间溢出的衰减边界，并关注中西部数字乡村的差异化路径。","2026-09-28T00:03:02.637755Z",{"id":288,"title":289,"url":290,"summary":291,"summary_zh":292,"content":8,"source_name":114,"source_url":290,"published_at":293,"category":11,"cover_url":8,"hotness":12,"is_selected":47,"score":294,"score_detail":295,"sources":299,"tags":301,"primary_topic":305,"secondary_topics":306,"classification":307,"search_phrases":331,"slug":334,"view_count":53,"doi":335,"paper":336,"created_at":351},3336,"Prosper or beggar thy neighbor? non-farm employment effects and spatial spillovers of China's National Digital Village Pilot Program","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1950504","Introduction Counties are a key spatial unit linking cities and villages in China's rural transformation, yet many still lack the industrial base, market scale, and non-farm job opportunities needed to absorb rural labor. This study examines whether China's National Digital Village Pilot Program expands rural non-farm employment and whether its effects extend beyond pilot counties. Methods Using a panel of 1,450 Chinese counties and 24,111 county-year observations from 2007 to 2024, this study exploits the staggered implementation of the 2020 and 2024 pilot cohorts as a quasi-natural experiment. The policy effect is estimated using a multi-period difference-in-differences model and cross-validated with stacked DID and the Callaway-Sant'Anna estimator. Robustness is further assessed through propensity score matching, inverse probability weighting, entropy balancing, placebo tests, and alternative samples and specifications. Transmission channels, heterogeneity, and spatial effects are also examined. Results The National Digital Village Pilot Program increased rural non-farm employment in pilot counties by approximately 25% relative to non-pilot counties, and the result remains robust across alternative identification and estimation strategies. The two-step transmission-channel analysis provides evidence consistent with two potential channels: enhanced county-level innovation and improved mobile network access capability. The policy effect is significantly stronger in central-region counties than in western counties and stronger in smaller counties than in larger ones, with weaker evidence of a larger effect in counties with lower human capital. Spatial analysis shows a positive direct effect on pilot counties but a negative spillover effect on neighboring counties. Discussion The findings indicate that digital village development can strengthen local non-farm employment absorption, but part of the local gain may reflect a spatial reallocation of economic activity rather than net regional job creation. Effective implementation therefore requires not only county-level digital development but also cross-county resource coordination and regional policy integration.","引言 县域是中国城乡转型中连接城市与乡村的关键空间单元，但许多县域仍缺乏吸纳农村劳动力所需的产业基础、市场规模和非农就业机会。本研究考察中国国家数字乡村试点项目是否扩大了农村非农就业，以及其效应是否超出试点县范围。方法 本研究使用2007年至2024年间1，450个中国县域、24，111个县—年观测值的面板数据，将2020年和2024年试点批次的分批实施作为准自然实验。政策效应采用多期双重差分模型估计，并通过堆叠双重差分和Callaway-Sant'Anna估计量进行交叉验证。稳健性进一步通过倾向得分匹配、逆概率加权、熵平衡、安慰剂检验以及替代样本和设定加以评估。研究还考察了传导渠道、异质性和空间效应。结果 国家数字乡村试点项目使试点县的农村非农就业相对于非试点县增加了约25%，且该结果在替代性识别和估计策略下保持稳健。两步传导渠道分析提供的证据与两个潜在渠道相一致：县域创新能力增强和移动网络接入能力改善。政策效应在中部地区县域显著强于西部地区县域，在较小县域强于较大县域，而在人力资本较低县域效应更大的证据较弱。空间分析显示，政策对试点县具有正向直接效应，但对邻近县域产生负向溢出效应。讨论 研究结果表明，数字乡村发展能够增强本地非农就业吸纳能力，但部分本地收益可能反映的是经济活动的空间再配置，而非区域净就业创造。因此，有效实施不仅需要县域层面的数字发展，还需要跨县域资源协调和区域政策整合。","2026-09-23T00:00:00Z",89,{"impact":296,"substance":297,"depth":118,"authority":18,"freshness":120,"relevant":20,"comment":298},24,23,"基于1450个县2007-2024年面板数据的准自然实验研究，证实数字乡村试点使县域非农就业提升约25%，但存在对邻县的负向溢出，对政策协调具有实质参考价值。",[300],{"name":114,"url":290},[25,26,302,303,304],"县域经济","数字乡村试点","非农就业",{"code":43,"slug":253,"name":254,"path":255,"parent_code":256},[],{"status":203,"locked":13,"version":33,"method":34,"evidence":308},{"candidates":309,"agricultural_evidence":47},[310,316,322,326],{"code":43,"score":311,"supported":47,"title":312,"abstract":314,"tags":315},16,[313],"digital village",[25,313],[25,303],{"code":38,"score":278,"supported":47,"title":317,"abstract":318,"tags":321},[],[319,320],"空间分析","spatial analysis",[26],{"code":266,"score":20,"supported":13,"title":323,"abstract":324,"tags":325},[],[],[302],{"code":327,"score":20,"supported":13,"title":328,"abstract":329,"tags":330},"G6",[],[],[304],[332,333],"国家数字乡村试点 非农就业","县域 数字乡村 空间溢出","国家数字乡村试点非农就业-3336","10.3389\u002Ffsufs.2026.1950504",{"doi":335,"openalex_id":337,"authors":338,"venue":114,"cited_by_count":56,"oa_url":290,"card":346,"direction":61,"ingested_from":179},"W7214093544",[339,342,344],{"name":340,"orcid":341},"Wei Yang","https:\u002F\u002Forcid.org\u002F0000-0002-0540-5934",{"name":343,"orcid":8},"Lijun Wang",{"name":345,"orcid":8},"Yizhuo Ma",{"tldr":347,"method":348,"finding":349,"direction":61,"opportunity":350},"评估国家数字乡村试点对县域非农就业的影响及空间溢出效应。","2007-2024年1450个县面板数据，多期DID与Callaway-Sant","试点县非农就业增约25%，但邻县出现负向溢出，部分为就业空间再分配。","可探究数字乡村试点的跨县协同机制与负溢出治理，及不同区域差异化政策设计。","2026-09-24T23:30:07.434384Z",{"id":353,"title":354,"url":355,"summary":356,"summary_zh":8,"content":8,"source_name":357,"source_url":8,"published_at":358,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":14,"score_detail":359,"sources":361,"tags":363,"primary_topic":8,"secondary_topics":367,"classification":368,"search_phrases":388,"slug":391,"view_count":278,"doi":8,"paper":392,"created_at":399},3321,"数智化如何提升粮食供应链韧性——基于空间溢出与农业集聚的实证分析（2011—2023省级面板）","http:\u002F\u002Fwww.qikanvip.com\u002Fqkml\u002F165475.html","《农业经济与管理》2026年第03期。李盛竹、王延浩、姜金贵（重庆邮电大学\u002F哈尔滨工程大学）基于2011—2023年中国省级面板数据，构建数智化与粮食供应链韧性综合评价指标体系。结果显示：数智化显著增强了粮食供应链韧性；该结论经过一系列稳健性检验与内生性处理后依然成立，且在粮食主产区和西部地区的促进作用更为突出。机制分析表明，农业生产水平在数智化影响粮食供应链韧性过程中，发挥着正向调节作用；农业产业集聚具有显著的门槛效应，只有跨越特定集聚水平后，数智化的促进作用才更为明显。此外，数智化对粮食供应链韧性的影响存在显著的空间溢出效应。","《农业经济与管理》2026年第03期","2026-09-17T00:00:00Z",{"impact":16,"substance":17,"depth":16,"authority":18,"freshness":19,"relevant":20,"comment":360},"基于2011—2023省级面板的实证研究，方法规范、结论有新意，对数字乡村与粮食安全议题有参考价值，但属学术论文，公共传播性有限。",[362],{"name":357,"url":355},[25,364,365,26,366],"智慧农业","粮食安全","农业产业集聚",[],{"status":32,"locked":13,"version":33,"method":34,"evidence":369},{"candidates":370,"agricultural_evidence":47,"reason":48},[371,376,380,384],{"code":372,"score":20,"supported":13,"title":373,"abstract":374,"tags":375},"A8",[],[],[365],{"code":212,"score":20,"supported":13,"title":377,"abstract":378,"tags":379},[],[],[364],{"code":38,"score":20,"supported":13,"title":381,"abstract":382,"tags":383},[],[],[26],{"code":43,"score":20,"supported":13,"title":385,"abstract":386,"tags":387},[],[],[25],[389,390],"数智化 粮食供应链韧性","农业集聚 门槛效应","数智化粮食供应链韧性-3321",{"doi":8,"openalex_id":8,"authors":393,"venue":8,"cited_by_count":56,"oa_url":8,"card":394,"direction":61,"ingested_from":63},[],{"tldr":395,"method":396,"finding":397,"direction":61,"opportunity":398},"基于2011—2023省级面板，实证检验数智化对粮食供应链韧性的提升作用及机制。","省级面板数据，构建综合评价指标体系，调节效应、门槛模型与空间溢出分析。","数智化显著增强粮食供应链韧性，主产区和西部更突出，农业集聚存在门槛效应。","可探究数智化空间溢出的衰减边界与跨区域协同机制，及集聚门槛的差异化政策设计。","2026-09-24T00:04:02.337256Z"]