[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-4641":3,"related-4641":73},{"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":27,"primary_topic":8,"secondary_topics":33,"classification":34,"search_phrases":52,"slug":55,"view_count":20,"doi":56,"paper":57,"created_at":72},4641,"中国数字经济与农业产业融合的时空格局、区域差异及影响因素(Spatiotemporal patterns, regional differences, and influencing factors of the integration of digital economy and agricultural industry in China)","https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fsustainable-food-systems\u002Farticles\u002F10.3389\u002Ffsufs.2026.1985406\u002Ffull","基于2013—2022年省级数据,采用CRITIC赋权、Dagum Gini系数与GTWR模型,分析中国数字经济与农业产业融合(IDEAI)水平及其影响因素。结果显示:融合水平持续上升但总体仍较低,呈东高西低格局;整体差距趋缓,区域间差异是主要来源;技术创新、市场需求、政府支持对融合有正向作用,金融服务2018年前为正后转弱,规模经营与融合呈负相关。局限:数据仅至2022年,部分指标采用代理变量。",null,"Frontiers in Sustainable Food Systems 2026-10-06","2026-10-06T00:00:00Z","论文",25,false,77,{"impact":16,"substance":17,"depth":16,"authority":18,"freshness":19,"relevant":20,"comment":21},18,22,13,6,1,"基于2013—2022年省级数据的实证研究，方法规范、结论有参考价值，但数据滞后且属学术论文，时效性与公共传播性一般。",[23,24],{"name":9,"url":6},{"name":25,"url":26},"Frontiers in Sustainable Food Systems","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1985406",[28,29,30,31,32],"数字乡村","产业融合","区域差异","农业数字经济","GTWR模型",[],{"status":35,"locked":13,"version":36,"method":37,"evidence":38},"unclassified","2026-10-22.2","rules",{"candidates":39,"agricultural_evidence":50,"reason":51},[40,45],{"code":41,"score":20,"supported":13,"title":42,"abstract":43,"tags":44},"G4",[],[],[29],{"code":46,"score":20,"supported":13,"title":47,"abstract":48,"tags":49},"I6",[],[],[28],true,"缺少足够的主题证据",[53,54],"数字经济 农业产业融合","农业产业融合 区域差异","数字经济农业产业融合-4641","10.3389\u002Ffsufs.2026.1985406\u002Ffull",{"doi":56,"openalex_id":58,"authors":59,"venue":25,"cited_by_count":64,"oa_url":26,"card":65,"direction":69,"ingested_from":71},"W7223154949",[60,62],{"name":61,"orcid":8},"Di Wu",{"name":63,"orcid":8},"艾维 陶",0,{"tldr":66,"method":67,"finding":68,"direction":69,"opportunity":70},"基于2013—2022年省级数据，测度中国数字经济与农业产业融合水平并分析其时空格局与影响因素。","CRITIC赋权、Dagum Gini系数与GTWR模型，使用省级面板数据。","融合水平持续上升但总体偏低、东高西低；区域间差异是主要来源；技术创新、市场需求、政府支持正向促进。","数字乡村与农业信息化","可延伸至县域或企业微观尺度，探究金融服务作用由正转弱的机制及规模经营负相关的成因。","openalex","2026-10-11T00:09:47.185401Z",{"total":19,"page":20,"page_size":19,"items":74},[75,128,180,227,272,341],{"id":76,"title":77,"url":78,"summary":79,"summary_zh":8,"content":8,"source_name":80,"source_url":8,"published_at":81,"category":11,"cover_url":8,"hotness":82,"is_selected":13,"score":14,"score_detail":83,"sources":85,"tags":87,"primary_topic":91,"secondary_topics":96,"classification":97,"search_phrases":115,"slug":118,"view_count":64,"doi":8,"paper":119,"created_at":127},4781,"中国数字乡村建设与县域老年照护产业的耦合协调关系及区域差异研究","https:\u002F\u002Fwww.ebiotrade.com\u002Fnewsf\u002F2026-10\u002F20261009225937972.htm","本研究利用中国县域数字乡村指数2018年和2020年及匹配的老年照护产业统计数据,采用综合耦合协调度评价模型考察两大系统之间的耦合协调度及其区域差异。研究发现,全国整体耦合协调水平仍偏低,农村经济、日常生活和治理的数字化与老年照护产业耦合度呈中度失衡。结论建议政府应优先关注数字乡村建设的社会效益,加强农村老年照护的技术和服务支持。","生物通 报道 BMC Geriatrics 2026-10-10","2026-10-10T00:00:00Z",10,{"impact":16,"substance":17,"depth":16,"authority":18,"freshness":19,"relevant":20,"comment":84},"基于县域面板数据的实证研究，揭示数字乡村与老年照护产业耦合失衡，对农村数字化社会效益有政策参考价值。",[86],{"name":80,"url":78},[28,88,89,30,90],"县域经济","耦合协调","老年照护",{"code":46,"slug":92,"name":93,"path":94,"parent_code":95},"digital-village","数字乡村与数据要素","\u002Ftopic\u002Fdigital-agriculture\u002Fdigital-village","I",[],{"status":98,"locked":13,"version":36,"method":37,"evidence":99},"classified",{"candidates":100,"agricultural_evidence":50},[101,106,110],{"code":46,"score":102,"supported":50,"title":103,"abstract":104,"tags":105},12,[28],[28],[28],{"code":41,"score":20,"supported":13,"title":107,"abstract":108,"tags":109},[],[],[88],{"code":111,"score":20,"supported":13,"title":112,"abstract":113,"tags":114},"I4",[],[],[89],[116,117],"中国县域数字乡村指数 老年照护产业","区域差异 县域经济 数字乡村 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模型测度数字技术发展与农业绿色全要素生产率,运用双向固定效应模型检验发现数字技术发展具有显著促进作用且存在双重异质性;空间上回报率呈地理位置为主导的分化,效率上呈边际效应递减;机制上要素数字化呈现「转化—产出」结构性失衡,东部强于转化弱于产出,中西部相反。","西藏大学经济与管理学院《华东经济管理》2026 年第 06 期",73,{"impact":16,"substance":17,"depth":16,"authority":18,"freshness":136,"relevant":20,"comment":137},2,"基于31省面板数据的实证研究，方法规范、结论有区域适配价值，但属学术论文且时效性弱，适合主题聚合而非每日精选。",[139],{"name":133,"url":131},[28,141,142,30,143],"数字技术","农业绿色发展","农业全要素生产率",[],{"status":35,"locked":13,"version":36,"method":37,"evidence":146},{"candidates":147,"agricultural_evidence":50,"reason":51},[148,153,158,163],{"code":149,"score":20,"supported":13,"title":150,"abstract":151,"tags":152},"H4",[],[],[142],{"code":154,"score":20,"supported":13,"title":155,"abstract":156,"tags":157},"H8",[],[],[142],{"code":159,"score":20,"supported":13,"title":160,"abstract":161,"tags":162},"I1",[],[],[141],{"code":46,"score":20,"supported":13,"title":164,"abstract":165,"tags":166},[],[],[28],[168,169],"数字技术 农业绿色全要素生产率","SBM-GML 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20(0):1-7。张庆红、贺纯、刘振峰基于2015-2023年省级面板数据，构建评价指标体系测度和分析各省份数字乡村建设水平，借助固定效应、中介效应与门槛效应等模型实证检验。结果表明：数字乡村建设不仅直接促进农民增收，还通过劳动力转移产生积极作用；在东部、中部、东北部地区表现突出，在高经济水平与人力资本高潜力地区更为明显。","云南农业大学学报 | 2026-09-08","2026-09-08T00:00:00Z",75,{"impact":16,"substance":189,"depth":190,"authority":191,"freshness":192,"relevant":20,"comment":193},21,17,14,5,"基于2015—2023年省级面板数据的实证研究，方法规范、结论明确，对数字乡村建设与农民增收的政策制定有参考价值，但属学术论文且时效性一般，适合进入主题聚合而非每日精选头条。",[195],{"name":185,"url":183},[28,197,30,198,199],"农民增收","省级面板数据","农村劳动力转移",{"code":46,"slug":92,"name":93,"path":94,"parent_code":95},[],{"status":98,"locked":13,"version":36,"method":37,"evidence":203},{"candidates":204,"agricultural_evidence":50},[205,209],{"code":46,"score":102,"supported":50,"title":206,"abstract":207,"tags":208},[28],[28],[28],{"code":210,"score":211,"supported":50,"title":212,"abstract":213,"tags":214},"G6",4,[],[197],[197],[216,217],"农村劳动力转移 省级面板数据 农民增收 区域差异","农村劳动力转移 省级面板数据","农村劳动力转移省级面板数据农民增收区域差异-2402",{"doi":8,"openalex_id":8,"authors":220,"venue":8,"cited_by_count":64,"oa_url":8,"card":221,"direction":69,"ingested_from":126},[],{"tldr":222,"method":223,"finding":224,"direction":69,"opportunity":225},"基于2015—2023年省级面板数据，实证检验数字乡村建设对农民收入的影响及机制。","构建数字乡村评价指标体系，用固定效应、中介效应与门槛效应模型分析省级面板数据。","数字乡村建设直接促进农民增收，并通过劳动力转移间接起作用，区域与禀赋异质性明显。","可深入微观农户数据，探究数字乡村增收效应的空间溢出与数字鸿沟调节机制。","2026-09-14T00:06:33.480192Z",{"id":228,"title":229,"url":230,"summary":231,"summary_zh":8,"content":232,"source_name":233,"source_url":8,"published_at":234,"category":11,"cover_url":8,"hotness":82,"is_selected":13,"score":235,"score_detail":236,"sources":239,"tags":241,"primary_topic":247,"secondary_topics":248,"classification":249,"search_phrases":265,"slug":268,"view_count":211,"doi":8,"paper":269,"created_at":271},1033,"数字乡村建设对农业新质生产力的影响效应与作用机制——基于2012—2023年30省份面板数据","http:\u002F\u002Fwww.qikanvip.com\u002Fqkml\u002F127584.html","原文标题:数字乡村建设对农业新质生产力的影响效应与作用机制。作者:杜一鸣、贾慧静、王强(西安交通大学马克思主义学院等)。基于2012—2023年中国30个省份的面板数据,采用双向固定效应模型,实证检验数字乡村建设对农业新质生产力的影响,并引入中介效应模型和调节效应模型考察农村创新创业活跃度的中介作用以及农村产业融合的调节效应。研究结果表明:数字乡村建设可以显著促进农业新质生产力提升,且这种促进作用在'胡焕庸线'以东地区、非粮食主产区及农业新质生产力水平较高的地区更为显著;农村创新创业活跃度发挥了部分中介作用;农村产业融合对数字乡村建设与农业新质生产力之间的关系具有显著的正向调节作用。","0\n\n发表咨询在线!\n\n###### 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[数字乡村建设对农业新质生产力的影响效应与作用机制](http:\u002F\u002Fwww.qikanvip.com\u002Fqkml\u002F127584.html)\n\n# 统计与决策2026年第01期：数字乡村建设对农业新质生产力的影响效应与作用机制\n\n来源：[期刊VIP网](http:\u002F\u002Fwww.qikanvip.com\u002F)时间： 2026年8月28日 星期五\n\n* * *\n\n作者：杜一鸣;贾慧静;王强;\n\n单位：西安交通大学马克思主义学院;延安大学政法与公共管理学院;温州理工学院经济与管理学院;\n\n**摘要：**在加快培育新质生产力的背景下，数字乡村建设已成为推动农业现代化和农业生产力提升的重要路径，但其对农业新质生产力的作用路径与内在机制仍有待系统考察。文章基于2012—2023年中国30个省份的面板数据，采用双向固定效应模型，实证检验数字乡村建设对农业新质生产力的影响，并进一步引入中介效应模型和调节效应模型，考察农村创新创业活跃度的中介作用以及农村产业融合的调节效应。研究结果表明：数字乡村建设可以显著促进农业新质生产力提升，且这种促进作用在“胡焕庸线”以东地区、非粮食主产区及农业新质生产力水平较高的地区更为显著。从作用机制看，农村创新创业活跃度在数字乡村建设与农业新质生产力之间发挥了部分中介作用，数字要素投入通过激发农村创新创业活动加速了新质劳动者、新质劳动资料与新质劳动对象的形成与升级。此外，农村产业融合对数字乡村建设与农业新质生产力之间的关系具有显著的正向调节作用，农村产业融合水平越高，数字乡村建设对农业新质生产力的赋能作用越强。\n\n**关键词：**数字乡村建设;;农业新质生产力;;农村创新创业活跃度;;产业融合\n\n**基金资助：**浙江省哲学社会科学规划“省市合作”课题（25SSHZ079YB）\n\n##### 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统计与决策](http:\u002F\u002Fwww.qikanvip.com\u002Fstatic\u002Fhexin\u002Ftjjc.jpg)统计与决策 北大核心 CSSCI AMI扩展 ISSN：1002-6487 CN：42-1009\u002FC 出版地：北京市 主办单位：湖北长江报刊传媒(集团)有限公司 主管单位：长江出版传媒股份有限公司 复合影响因子：9.86 综合影响因子：6.682 创刊时间：1984 期刊官网：http:\u002F\u002Fwww.tjyjc.com\u002F出版周期：半月](http:\u002F\u002Ftjjc.qikanvip.com\u002F \"统计与决策\")\n\n期刊VIP网专注学术论文咨询指导、国外出版指导、国内出版指导，提供全方位专业服务，论文指导服务涵盖SCI、SSCI、EI、SCOPUS，论文指导服务内容包括翻译、润色、预审，期刊指导服务内容包括期刊推荐、发表支持。您可以与学术顾问沟通，介绍自己的学术需求，制定专属学术服务方案。\n\n* * *\n\nwww.qikanvip.com版权所有 仿冒必究 投诉邮箱：qianyanns@163.com [京ICP备17075097号-4](http:\u002F\u002Fbeian.miit.gov.cn\u002F \"工信部备案系统\")\n\n**科核2个月出刊 收稿方向**\n\n#### [方向：就业、人力资源 ##### 了解适投期刊 #### 方向：法律、财务、经济 ##### 了解适投期刊 #### 方向：人才培养、企业管理 ##### 了解适投期刊 #### 方向：计算机、机械、电力 ##### 了解适投期刊 #### 方向：化工、医药化工 ##### 了解适投期刊 #### 方向：物流、环保、汽车 ##### 了解适投期刊 #### 方向：知识产权、营销 ##### 了解适投期刊 #### 方向：舞蹈、绘画、雕塑、美术 ##### 了解适投期刊 #### 方向：艺术设计、视觉设计、创意设计 ##### 了解适投期刊 #### 方向：广告、创意设计 ##### 了解适投期刊 #### 方向：室内设计、装饰设计 ##### 了解适投期刊 #### 方向：文创设计、平面设计 ##### 了解适投期刊 #### 方向：包装设计、装帧设计 ##### 了解适投期刊 #### 方向：新媒体、家具、陶瓷、旅游 ##### 了解适投期刊 #### 方向：非遗、戏剧、服装、书法 ##### 了解适投期刊 #### 方向：体育、教育 ##### 了解适投期刊](javascript:void(0))\n\n[站长统计](https:\u002F\u002Fwww.cnzz.com\u002Fstat\u002Fwebsite.php?web_id=1255393057 \"站长统计\")\n\n[理工科核心资源库](http:\u002F\u002Fwww.qikanvip.com\u002Fhot.html)","统计与决策 2026(1)","2026-08-20T16:00:00Z",76,{"impact":237,"substance":17,"depth":16,"authority":191,"freshness":136,"relevant":20,"comment":238},20,"基于省级面板数据的实证研究，探讨数字乡村建设对农业新质生产力的影响机制，数据详实、方法规范，但发表于2026年第1期，时效性较低。",[240],{"name":233,"url":230},[28,242,243,244,245,29,246],"农业新质生产力","中介效应","双向固定效应","30省份面板","胡焕庸线",{"code":46,"slug":92,"name":93,"path":94,"parent_code":95},[],{"status":98,"locked":13,"version":36,"method":37,"evidence":250},{"candidates":251,"agricultural_evidence":50},[252,256,260],{"code":46,"score":102,"supported":50,"title":253,"abstract":254,"tags":255},[28],[28],[28],{"code":41,"score":20,"supported":13,"title":257,"abstract":258,"tags":259},[],[],[29],{"code":261,"score":20,"supported":13,"title":262,"abstract":263,"tags":264},"J2",[],[],[242],[266,267],"农业新质生产力 双向固定效应 30省份面板 中介效应","农业新质生产力 双向固定效应","农业新质生产力双向固定效应30省份面板中介效应-1033",{"doi":8,"openalex_id":8,"authors":270,"venue":8,"cited_by_count":64,"oa_url":8,"card":8,"direction":8,"ingested_from":126},[],"2026-08-28T00:07:02.181336Z",{"id":273,"title":274,"url":275,"summary":276,"summary_zh":277,"content":8,"source_name":278,"source_url":275,"published_at":279,"category":11,"cover_url":8,"hotness":82,"is_selected":13,"score":280,"score_detail":281,"sources":284,"tags":286,"primary_topic":291,"secondary_topics":292,"classification":293,"search_phrases":319,"slug":322,"view_count":64,"doi":323,"paper":324,"created_at":340},5581,"How Does Digital Literacy Promote Inclusive Rural Growth? Micro-Level Evidence from Income Inequality Among Farm Households","https:\u002F\u002Fdoi.org\u002F10.3390\u002Fsu182010689","Against the backdrop of the coordinated advancement of digital village construction and the common prosperity strategy, the widespread improvement in rural households’ digital literacy is emerging as a key force in reshaping rural income distribution and enabling sustainable rural development. Whether digital dividends can equitably benefit farm households with heterogeneous endowments has a direct bearing on the inclusive growth outcomes of digital village construction and the sustainable advancement of the common prosperity goal. Using three waves of panel data from the China Family Panel Studies (CFPS) covering 2018 to 2022, this paper empirically examines the impact of digital literacy on income inequality among rural households. The findings indicate that improvements in digital literacy significantly reduce rural household income inequality, and this conclusion remains robust across a series of robustness checks. Mechanism analysis reveals that digital literacy mainly curbs the widening of rural household income gaps through two core channels: expanding social capital and alleviating credit constraints. Heterogeneity analysis shows that the inequality-reducing effect of digital literacy is more pronounced among households that depend on non-agricultural income, have lower levels of human capital, or fall into relatively lower income brackets. Further analysis demonstrates that digital literacy significantly reduces inequalities in wage income, business income, and property income across rural households, whereas its mitigating effect on transfer income inequality is not statistically significant. Meanwhile, digital literacy significantly raises the probability of upward income mobility among rural households, thereby alleviating income inequality from a dynamic perspective. On the basis of these findings, this paper proposes policy implications in several areas: building a hierarchical and categorized rural digital literacy cultivation system, fostering a virtuous cycle of digital empowerment, equal opportunity, and income convergence, and optimizing income distribution structures and dynamic mobility mechanisms, with the aim of accelerating progress toward common prosperity.","在数字乡村建设与共同富裕战略协同推进的背景下，农户数字素养的普遍提升正成为重塑乡村收入分配格局、实现乡村可持续发展的重要力量。数字红利能否公平惠及禀赋异质性农户，直接关系到数字乡村建设的包容性增长成效与共同富裕目标的可持续推进。本文利用中国家庭追踪调查（CFPS）2018—2022年三期面板数据，实证检验数字素养对农户收入不平等的影响。研究发现，数字素养的提升显著降低了农户收入不平等，这一结论在一系列稳健性检验后依然成立。机制分析表明，数字素养主要通过拓展社会资本与缓解信贷约束两条核心渠道抑制农户收入差距的扩大。异质性分析显示，数字素养的减不平等效应在依赖非农收入、人力资本水平较低或处于相对较低收入区间的农户中更为明显。进一步分析发现，数字素养显著缩小了农户工资性收入、经营性收入和财产性收入的不平等，而对转移性收入不平等的缓解作用在统计上不显著。同时，数字素养显著提高了农户收入向上流动的概率，从而从动态视角缓解了收入不平等。基于上述发现，本文从构建分层分类的农户数字素养培育体系、形成数字赋能—机会均等—收入收敛的良性循环、优化收入分配结构与动态流动机制等方面提出政策启示，以期为加快共同富裕进程提供参考。","Sustainability","2026-10-21T00:00:00Z",80,{"impact":16,"substance":17,"depth":16,"authority":18,"freshness":282,"relevant":20,"comment":283},9,"基于CFPS三期面板数据的微观实证，方法规范、结论有新意，对数字乡村与共同富裕政策有参考价值，值得进入每日精选。",[285],{"name":278,"url":275},[28,287,288,289,290],"数字素养","共同富裕","农民收入","收入不平等",{"code":46,"slug":92,"name":93,"path":94,"parent_code":95},[],{"status":98,"locked":13,"version":36,"method":37,"evidence":294},{"candidates":295,"agricultural_evidence":50},[296,302,308,315],{"code":46,"score":297,"supported":50,"title":298,"abstract":299,"tags":301},8,[],[28,300],"digital village",[28,287],{"code":210,"score":19,"supported":50,"title":303,"abstract":304,"tags":307},[],[305,306],"农户收入","rural income",[],{"code":309,"score":310,"supported":50,"title":311,"abstract":312,"tags":314},"G",3,[],[313],"rural development",[],{"code":41,"score":20,"supported":13,"title":316,"abstract":317,"tags":318},[],[],[288],[320,321],"CFPS 数字素养 农户收入","数字素养 农村收入差距","CFPS数字素养农户收入-5581","10.3390\u002Fsu182010689",{"doi":323,"openalex_id":325,"authors":326,"venue":278,"cited_by_count":64,"oa_url":275,"card":335,"direction":69,"ingested_from":71},"W7223105459",[327,330,333],{"name":328,"orcid":329},"Yong Feng","https:\u002F\u002Forcid.org\u002F0000-0002-8151-8594",{"name":331,"orcid":332},"Shuokai  kai Wang","https:\u002F\u002Forcid.org\u002F0009-0002-7439-1764",{"name":334,"orcid":8},"Fangping Cao",{"tldr":336,"method":337,"finding":338,"direction":69,"opportunity":339},"基于CFPS三期面板数据，实证检验数字素养对农户收入不平等的影响。","使用CFPS 2018-2022三期面板数据，进行机制与异质性分析。","数字素养通过扩展社会资本和缓解信贷约束显著缩小农户收入差距。","可延伸研究数字素养对不同收入来源不平等的差异化机制及动态收入流动路径。","2026-10-22T11:20:47.675827Z",{"id":342,"title":343,"url":344,"summary":345,"summary_zh":346,"content":8,"source_name":25,"source_url":344,"published_at":279,"category":11,"cover_url":8,"hotness":82,"is_selected":13,"score":347,"score_detail":348,"sources":350,"tags":352,"primary_topic":8,"secondary_topics":357,"classification":358,"search_phrases":389,"slug":392,"view_count":64,"doi":393,"paper":394,"created_at":404},5545,"Regional digital finance and food supply-chain management resilience: evidence on the regional-to-firm conversion gap in China’s emerging listed food enterprises","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1948192","Food supply chains face climate shocks, logistics disruption, food-safety incidents and volatile demand, yet the relevance of regional digital finance for firm-level resilience remains uncertain. This study examines the association between a province-level digital-finance environment and an accounting-based food supply-chain resilience proxy among emerging listed food enterprises in China. Using public data for 122 eligible firms, we construct annual resistance, recovery and stability measures from revenue, operating cash flow and net margin; the common two-way fixed-effects sample contains 732 firm-year observations from 119 firms during 2017–2023. Regional digital finance is measured as a province-level external financial environment rather than firm-level digital transformation or adoption. Operational capability and regional consumption capacity are accounting- and province-level proxies and do not directly observe supplier coordination, traceability, cold-chain performance, or product-level demand. The preferred estimate is close to zero [beta = −0.005, SE = 0.063, 95% CI (−0.128, 0.117)]. Alternative covariance estimators, outcome definitions and timing specifications do not establish a stable positive within-firm association. The proxy-based operational-capability pathway and the conditional consumption-capacity association are likewise not established. Equivalence tests at 0.05 and 0.10 SCR-standard-deviation bounds are not significant, and the approximate 80% minimum detectable effect is 1.575 SCR standard deviations. The evidence therefore cannot distinguish a small contextual association from limited within-firm statistical precision. The findings support a bounded regional-to-firm conversion interpretation: regional finance may widen resource availability, but whether it is associated with resilience depends on unobserved operational conversion routines and food-sector coordination conditions.","食品供应链面临气候冲击、物流中断、食品安全事件和需求波动，但区域数字金融与企业层面韧性之间的关联仍不确定。本研究考察省级数字金融环境与中国新兴上市食品企业基于会计的食品供应链韧性代理指标之间的关联。利用122家合格企业的公开数据，我们从营业收入、经营现金流和净利润率构建年度抵抗能力、恢复能力和稳定性指标；共同双向固定效应样本包含2017—2023年间119家企业的732个企业—年度观测值。区域数字金融被衡量为省级外部金融环境，而非企业层面的数字化转型或采用。运营能力和区域消费能力为会计层面和省级层面的代理变量，并不直接观测供应商协调、可追溯性、冷链绩效或产品层面需求。首选估计值接近于零[beta = −0.005，SE = 0.063，95% CI（−0.128，0.117）]。替代协方差估计量、结果定义和时序设定均未能确立稳定的企业内正向关联。基于代理变量的运营能力路径和条件性消费能力关联同样未能确立。在0.05和0.10个SCR标准差边界上的等价性检验不显著，约80%的最小可检测效应为1.575个SCR标准差。因此，证据无法区分微小的情境性关联与有限的企业内统计精度。研究结果支持有界的情境到企业转化解释：区域金融可能拓宽资源可得性，但其是否与韧性相关联取决于未观测到的运营转化惯例和食品行业协调条件。",69,{"impact":297,"substance":189,"depth":190,"authority":18,"freshness":82,"relevant":20,"comment":349},"基于122家上市食品企业的严谨实证研究，发现区域数字金融与企业韧性关联接近于零，对数字乡村金融政策有边界性提示价值，但属细分学术结论，公共影响有限。",[351],{"name":25,"url":344},[28,353,354,355,356],"数字金融","供应链韧性","农业企业","食品供应链",[],{"status":359,"locked":13,"version":36,"method":37,"evidence":360},"needs_review",{"candidates":361,"agricultural_evidence":13,"reason":388},[362,368,374,379,384],{"code":363,"score":310,"supported":50,"title":364,"abstract":365,"tags":367},"E3",[],[366],"冷链",[],{"code":369,"score":310,"supported":50,"title":370,"abstract":371,"tags":373},"E4",[],[372],"食品安全",[],{"code":375,"score":20,"supported":13,"title":376,"abstract":377,"tags":378},"G2",[],[],[355],{"code":380,"score":20,"supported":13,"title":381,"abstract":382,"tags":383},"G3",[],[],[353],{"code":46,"score":20,"supported":13,"title":385,"abstract":386,"tags":387},[],[],[28],"农业相关性需要复核",[390,391],"区域数字金融 食品供应链韧性","中国上市食品企业 供应链韧性","区域数字金融食品供应链韧性-5545","10.3389\u002Ffsufs.2026.1948192",{"doi":393,"openalex_id":395,"authors":396,"venue":25,"cited_by_count":64,"oa_url":344,"card":399,"direction":69,"ingested_from":71},"W7223086503",[397],{"name":398,"orcid":8},"Jieyu Zhao",{"tldr":400,"method":401,"finding":402,"direction":69,"opportunity":403},"检验省级数字金融环境与中国新兴上市食品企业供应链韧性之间的关系。","基于122家上市食品企业2017–2023年公开数据，构建双向固定效应模型与等价","区域数字金融与企业供应链韧性无稳定正相关，估计值接近零且不显著。","可研究区域金融资源如何经企业运营惯例转化为供应链韧性，并补充冷链、溯源等微观数据。","2026-10-22T11:20:15.297878Z"]