[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-2921":3,"related-2921":82},{"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":9,"secondary_topics":31,"classification":32,"search_phrases":59,"slug":62,"view_count":63,"doi":64,"paper":65,"created_at":81},2921,"Can digital technology adoption enhance supply chain resilience? Evidence from listed food firms in China","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1930717","As a sector vital to national welfare and people’s livelihoods, the food industry has supply chains characterized by perishable raw materials, pronounced seasonality, stringent safety standards, extended chain structures, and highly fragmented participants. These features make food supply chains particularly vulnerable to external shocks, making the enhancement of supply chain resilience essential for safeguarding food safety and industrial and supply chain security. Using a sample of food firms listed on the Shanghai and Shenzhen A-share markets from 2009 to 2024, we systematically examine the effect of digital technology adoption on supply chain resilience, its potential channels, and heterogeneous effects. First, digital technology adoption significantly enhances the supply chain resilience of food firms. Second, digital technology adoption is significantly associated with greater information transparency, weaker financing constraints, and lower supply chain concentration. Third, this resilience-enhancing effect is more pronounced among firms facing lower environmental uncertainty, firms with stronger corporate innovation capability, and firms located in regions with a higher level of regional marketization. Focusing on the unique context of the food industry, we examine the potential channels and heterogeneous effects of digital technology adoption and provide micro-level empirical evidence for advancing the digital transformation of food firms, safeguarding food safety, and maintaining stable supply.","作为关乎国计民生的重要产业，食品产业的供应链具有原料易腐、季节性显著、安全标准严格、链条长、参与主体高度分散等特征。这些特征使食品供应链更易受到外部冲击，因此提升供应链韧性对于保障食品安全和产业链供应链安全至关重要。本文以2009—2024年沪深A股上市食品企业为样本，系统考察数字技术应用对供应链韧性的影响、潜在渠道及异质性效应。第一，数字技术应用显著提升了食品企业的供应链韧性。第二，数字技术应用与更高的信息透明度、更弱的融资约束和更低的供应链集中度显著相关。第三，这种韧性提升效应在环境不确定性较低的企业、创新能力较强的企业以及所在地区市场化水平较高的企业中更为明显。本文聚焦食品产业的独特情境，考察数字技术应用的潜在渠道和异质性效应，为推进食品企业数字化转型、保障食品安全和维持供应稳定提供微观层面的经验证据。",null,"Frontiers in Sustainable Food Systems","2026-09-18T00:00:00Z","论文",10,false,80,{"impact":17,"substance":18,"depth":17,"authority":19,"freshness":20,"relevant":21,"comment":22},18,22,13,9,1,"基于2009-2024年A股食品企业样本的实证研究，为农业食品行业数字化转型与供应链安全提供微观证据，方法规范、结论有政策参考价值。",[24],{"name":10,"url":6},[26,27,28,29,30],"数字农业","供应链韧性","数字化转型","农业企业","食品供应链",[],{"status":33,"locked":14,"version":34,"method":35,"evidence":36},"needs_review","2026-10-22.2","rules",{"candidates":37,"agricultural_evidence":14,"reason":58},[38,47,53],{"code":39,"score":40,"supported":41,"title":42,"abstract":43,"tags":46},"E4",6,true,[],[44,45],"食品安全","food safety",[],{"code":48,"score":49,"supported":14,"title":50,"abstract":51,"tags":52},"I1",2,[],[],[26,28],{"code":54,"score":21,"supported":14,"title":55,"abstract":56,"tags":57},"G2",[],[],[29],"农业相关性需要复核",[60,61],"食品企业 数字化转型 供应链韧性","A股食品企业 数字技术 供应链","食品企业数字化转型供应链韧性-2921",7,"10.3389\u002Ffsufs.2026.1930717",{"doi":64,"openalex_id":66,"authors":67,"venue":10,"cited_by_count":73,"oa_url":6,"card":74,"direction":78,"ingested_from":80},"W7213555796",[68,71],{"name":69,"orcid":70},"Meihui Li","https:\u002F\u002Forcid.org\u002F0009-0004-2665-2629",{"name":72,"orcid":9},"Yuechao Zhu",0,{"tldr":75,"method":76,"finding":77,"direction":78,"opportunity":79},"基于2009-2024年中国A股食品上市公司，实证检验数字技术采用对供应链韧性的影响及机制。","使用沪深A股食品企业面板数据，实证分析数字技术采用与供应链韧性的关系。","数字技术采用显著提升食品企业供应链韧性，通过提高信息透明度、缓解融资约束和降低供应链集中度实现。","数字乡村与农业信息化","可探究数字技术不同维度对食品供应链韧性的差异化影响，以及环境不确定性的调节机制。","openalex","2026-09-19T23:30:08.651264Z",{"total":40,"page":21,"page_size":40,"items":83},[84,147,215,275,363,415],{"id":85,"title":86,"url":87,"summary":88,"summary_zh":89,"content":9,"source_name":10,"source_url":87,"published_at":90,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":91,"score_detail":92,"sources":97,"tags":99,"primary_topic":9,"secondary_topics":102,"classification":103,"search_phrases":131,"slug":134,"view_count":73,"doi":135,"paper":136,"created_at":146},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。","2026-10-21T00:00:00Z",69,{"impact":93,"substance":94,"depth":95,"authority":19,"freshness":13,"relevant":21,"comment":96},8,21,17,"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。",[98],{"name":10,"url":87},[100,101,27,29,30],"数字乡村","数字金融",[],{"status":33,"locked":14,"version":34,"method":35,"evidence":104},{"candidates":105,"agricultural_evidence":14,"reason":58},[106,113,117,121,126],{"code":107,"score":108,"supported":41,"title":109,"abstract":110,"tags":112},"E3",3,[],[111],"冷链",[],{"code":39,"score":108,"supported":41,"title":114,"abstract":115,"tags":116},[],[44],[],{"code":54,"score":21,"supported":14,"title":118,"abstract":119,"tags":120},[],[],[29],{"code":122,"score":21,"supported":14,"title":123,"abstract":124,"tags":125},"G3",[],[],[101],{"code":127,"score":21,"supported":14,"title":128,"abstract":129,"tags":130},"I6",[],[],[100],[132,133],"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":135,"openalex_id":137,"authors":138,"venue":10,"cited_by_count":73,"oa_url":87,"card":141,"direction":78,"ingested_from":80},"W7223086503",[139],{"name":140,"orcid":9},"Jieyu Zhao",{"tldr":142,"method":143,"finding":144,"direction":78,"opportunity":145},"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",{"id":148,"title":149,"url":150,"summary":151,"summary_zh":152,"content":9,"source_name":10,"source_url":150,"published_at":153,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":15,"score_detail":154,"sources":156,"tags":158,"primary_topic":9,"secondary_topics":162,"classification":163,"search_phrases":189,"slug":192,"view_count":108,"doi":193,"paper":194,"created_at":214},3343,"Supply chain digitalization and proactive green innovation in agri-food enterprises: evidence from source-reduction patent bias","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1957657","Supply chain digitalization has emerged as a critical mechanism for advancing sustainable agriculture amidst intensifying climate and resource constraints. Utilizing panel data from A-share listed agri-food enterprises in China spanning 2013 to 2024, this study examines the impact of supply chain digitalization on corporate green innovation and its underlying transmission pathways. Our findings indicate that digital empowerment significantly enhances overall green innovation, with a pronounced structural preference for proactive source-reduction patents over reactive, end-of-pipe compliance technologies. This positive effect remains robust after addressing endogeneity concerns through instrumental variable (IV) analysis, Difference-in-Differences (DID) models, and double machine learning (DML) approaches. Mechanism tests reveal that digitalization fosters green innovation through three primary channels: enhancing supply chain synergies, strengthening R&D absorptive capacity, and elevating corporate risk-taking thresholds. Notably, this effect is amplified in environments characterized by high customer concentration and concentrated market structures. Furthermore, causal forest analysis underscores heterogeneous treatment effects, demonstrating that digital empowerment yields greater benefits for non-state-owned enterprises, firms with dominant market positions, and those deeply embedded in supply networks. These insights clarify the distributional implications of digital transformation and provide targeted policy guidance for accelerating the adoption of source-reduction technologies across the agri-food supply chain.","供应链数字化已成为在气候与资源约束日益加剧背景下推进可持续农业的关键机制。本研究利用2013年至2024年中国A股上市农业食品企业的面板数据，考察供应链数字化对企业绿色创新的影响及其内在传导路径。研究发现，数字赋能显著提升了整体绿色创新水平，且在结构上明显偏好主动型源头减量专利，而非末端治理型被动合规技术。在通过工具变量（IV）分析、双重差分（DID）模型和双重机器学习（DML）方法处理内生性问题后，这一正向效应依然稳健。机制检验表明，数字化通过三条主要渠道促进绿色创新：增强供应链协同效应、强化研发吸收能力以及提升企业风险承担阈值。值得注意的是，该效应在客户集中度高和市场结构集中的环境中更为显著。此外，因果森林分析揭示了异质性处理效应，表明数字赋能对非国有企业、具有市场主导地位的企业以及深度嵌入供应网络的企业带来更大收益。这些发现阐明了数字化转型的分配效应，并为加快农业食品供应链中源头减量技术的采用提供了有针对性的政策指引。","2026-09-23T00:00:00Z",{"impact":17,"substance":18,"depth":17,"authority":19,"freshness":20,"relevant":21,"comment":155},"基于A股农食企业面板数据的实证研究，方法扎实、结论新颖，对农业供应链数字化转型与源头减量技术政策有参考价值。",[157],{"name":10,"url":150},[26,159,29,160,161],"农业供应链","绿色创新","专利结构",[],{"status":33,"locked":14,"version":34,"method":35,"evidence":164},{"candidates":165,"agricultural_evidence":41,"reason":188},[166,173,180,184],{"code":167,"score":40,"supported":41,"title":168,"abstract":169,"tags":172},"H8",[],[170,171],"可持续农业","sustainable agriculture",[],{"code":174,"score":40,"supported":41,"title":175,"abstract":176,"tags":179},"I2",[],[177,178],"机器学习","machine learning",[],{"code":54,"score":21,"supported":14,"title":181,"abstract":182,"tags":183},[],[],[29],{"code":48,"score":21,"supported":14,"title":185,"abstract":186,"tags":187},[],[],[26],"多个产业证据相当，需要确认主归属",[190,191],"农业供应链 数字化 绿色创新","A股 农食企业 专利","农业供应链数字化绿色创新-3343","10.3389\u002Ffsufs.2026.1957657",{"doi":193,"openalex_id":195,"authors":196,"venue":10,"cited_by_count":73,"oa_url":150,"card":208,"direction":212,"ingested_from":80},"W7214118553",[197,200,202,205],{"name":198,"orcid":199},"Siliang Guo","https:\u002F\u002Forcid.org\u002F0000-0001-9093-9588",{"name":201,"orcid":9},"Yan Qu",{"name":203,"orcid":204},"Yang Zhang","https:\u002F\u002Forcid.org\u002F0000-0002-0789-4938",{"name":206,"orcid":207},"Bingqian Zhang","https:\u002F\u002Forcid.org\u002F0000-0002-8212-452X",{"tldr":209,"method":210,"finding":211,"direction":212,"opportunity":213},"基于2013-2024年中国农食上市企业面板数据，研究供应链数字化如何促进企业主动型绿色创新。","A股农食企业面板数据，IV、DID、双重机器学习及因果森林分析。","数字化显著提升绿色创新，且更偏向源头减量专利而非末端治理技术。","农业绿色发展与碳","可探究数字化驱动源头减量专利在中小农食企业及不同供应链结构中的扩散机制与政策激励。","2026-09-24T23:30:07.915956Z",{"id":216,"title":217,"url":218,"summary":219,"summary_zh":220,"content":9,"source_name":10,"source_url":218,"published_at":153,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":15,"score_detail":221,"sources":223,"tags":225,"primary_topic":229,"secondary_topics":235,"classification":236,"search_phrases":258,"slug":261,"view_count":262,"doi":263,"paper":264,"created_at":274},3341,"How the twin transition shapes green technological innovation in agricultural enterprises: evidence from China","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1893349","Introduction The twin transition is reshaping innovation patterns across industries, yet evidence on its effects in agriculture remains scarce despite the sector’s critical role in global food security and climate mitigation. Methods This study investigates how the twin transition influences green technological innovation in Chinese A-share agricultural listed enterprises from 2015 to 2024, drawing on a panel dataset of 860 firms. We measure the coupling coordination degree of digital and green transformation and estimate fixed effects models to examine both the direct effect and the underlying mechanisms. Results The results show that the twin transition significantly promotes green technological innovation, a finding that is robust to alternative measures and estimation methods. This aggregate effect, however, masks substantial heterogeneity: the innovation-enhancing effect is significant only for midstream processing firms and large enterprises, while it is negligible for upstream and downstream firms and weaker for small enterprises. Mechanism tests identify two mediating pathways. First, the twin transition enhances organizational response agility, enabling firms to sense and react to environmental and market changes more rapidly. Second, it alleviates financing constraints, thereby securing stable resources for long-term green innovation. Discussion These findings contribute to the twin transition literature by extending the empirical domain into agriculture and by specifying the organizational and financial channels through which digital-green coupling promotes innovation. They also provide evidence to inform differentiated policy design for sustainable agricultural development.","引言 双重转型正在重塑各行业的创新模式，但尽管农业在全球粮食安全和气候减缓中发挥着关键作用，关于其影响的证据仍然匮乏。方法 本研究基于860家企业的面板数据集，考察2015至2024年间双重转型如何影响中国A股农业上市企业的绿色技术创新。我们测度了数字化与绿色转型的耦合协调度，并估计固定效应模型以检验直接效应及其内在机制。结果 结果表明，双重转型显著促进了绿色技术创新，这一发现在替代测度和估计方法下依然稳健。然而，这一总体效应掩盖了显著的异质性：创新促进效应仅在中游加工企业和大企业中显著，而对上游和下游企业则可忽略不计，对小型企业也较弱。机制检验识别出两条中介路径。第一，双重转型增强了组织响应敏捷性，使企业能够更迅速地感知和应对环境与市场变化。第二，它缓解了融资约束，从而为长期绿色创新获取稳定资源。讨论 这些发现通过将实证领域拓展至农业，并明确数字化—绿色耦合促进创新的组织与金融渠道，为双重转型文献作出了贡献。它们也为面向可持续农业发展的差异化政策设计提供了依据。",{"impact":17,"substance":18,"depth":17,"authority":19,"freshness":20,"relevant":21,"comment":222},"基于860家中国农业上市公司面板数据，实证揭示数字化与绿色化协同对绿色技术创新的促进效应及组织敏捷性与融资约束两条中介路径，结论具政策参考价值。",[224],{"name":10,"url":218},[28,29,226,227,228],"双化协同","绿色技术创新","农业上市公司",{"code":230,"slug":231,"name":232,"path":233,"parent_code":234},"A8","yield-food-security","单产提升与粮食安全","\u002Ftopic\u002Ffield-crops\u002Fyield-food-security","A",[],{"status":237,"locked":14,"version":34,"method":35,"evidence":238},"classified",{"candidates":239,"agricultural_evidence":41},[240,246,250,254],{"code":230,"score":40,"supported":41,"title":241,"abstract":242,"tags":245},[],[243,244],"粮食安全","food security",[],{"code":167,"score":108,"supported":41,"title":247,"abstract":248,"tags":249},[],[170],[],{"code":54,"score":21,"supported":14,"title":251,"abstract":252,"tags":253},[],[],[29],{"code":48,"score":21,"supported":14,"title":255,"abstract":256,"tags":257},[],[],[28],[259,260],"农业上市公司 绿色技术创新","数字化转型 绿色转型 耦合协调","农业上市公司绿色技术创新-3341",5,"10.3389\u002Ffsufs.2026.1893349",{"doi":263,"openalex_id":265,"authors":266,"venue":10,"cited_by_count":73,"oa_url":218,"card":269,"direction":212,"ingested_from":80},"W7214110123",[267],{"name":268,"orcid":9},"Rongwang Guo",{"tldr":270,"method":271,"finding":272,"direction":212,"opportunity":273},"基于860家中国农业上市公司数据，研究数字与绿色双转型如何促进绿色技术创新。","2015-2024年面板数据，测度双转型耦合协调度，用固定效应模型检验机制。","双转型显著促进绿色创新，但仅在中游加工与大型企业显著，通过组织响应敏捷性与缓解融资约束起作用。","可延伸至上游种植与下游流通企业，探索数字绿色耦合的差异化路径及小企业赋能机制。","2026-09-24T23:30:07.783118Z",{"id":276,"title":277,"url":278,"summary":279,"summary_zh":280,"content":9,"source_name":281,"source_url":278,"published_at":282,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":283,"score_detail":284,"sources":289,"tags":291,"primary_topic":294,"secondary_topics":300,"classification":301,"search_phrases":339,"slug":342,"view_count":343,"doi":344,"paper":345,"created_at":362},1416,"THE IMPACT OF DIGITAL TECHNOLOGIES ON THE INNOVATIVE DEVELOPMENT OF AGRICULTURAL ENTERPRISES","https:\u002F\u002Fdoi.org\u002F10.32782\u002Finfrastruct90-32","The article examines the impact of digital technologies on the innovative development of agricultural enterprises in the context of economic digitalization and Industry 4.0. Digitalization is identified as a key driver of production efficiency, resource optimization, labor productivity, and competitiveness. The study considers the application of precision agriculture, the Internet of Things (IoT), artificial intelligence, Big Data, GIS, remote sensing, cloud technologies, and automated management systems. The main benefits include improved decision-making, lower production costs, higher productivity, reduced operational risks, and support for sustainable agricultural development. The paper also identifies barriers to digital transformation, such as limited investment, insufficient digital infrastructure, shortages of qualified personnel, and cybersecurity risks. Practical approaches are proposed to improve digital transformation and strengthen the innovative capacity and long-term competitiveness of agricultural enterprises.","本文探讨了在经济数字化与工业4.0背景下，数字技术对农业企业创新发展的影响。数字化被视为提升生产效率、优化资源配置、提高劳动生产率及增强竞争力的关键驱动力。研究涉及精准农业、物联网（IoT）、人工智能、大数据、地理信息系统（GIS）、遥感、云计算及自动化管理系统的应用。主要益处包括改善决策质量、降低生产成本、提高生产力、减少运营风险以及支持农业可持续发展。本文还指出了数字化转型面临的障碍，如投资有限、数字基础设施不足、专业人才短缺及网络安全风险。文章提出了改进数字化转型、增强农业企业创新能力与长期竞争力的实践路径。","Market Infrastructure","2026-09-01T00:00:00Z",51,{"impact":285,"substance":286,"depth":287,"authority":93,"freshness":49,"relevant":21,"comment":288},12,15,14,"论文系统梳理数字技术对农业企业创新的影响，但缺乏新数据，时效性低，适合行业参考。",[290],{"name":281,"url":278},[292,293,28,29],"智慧农业","精准农业",{"code":295,"slug":296,"name":297,"path":298,"parent_code":299},"I5","agricultural-iot","物联网传感与边缘计算","\u002Ftopic\u002Fdigital-agriculture\u002Fagricultural-iot","I",[],{"status":237,"locked":14,"version":34,"method":35,"evidence":302},{"candidates":303,"agricultural_evidence":41},[304,309,316,323,330,335],{"code":48,"score":20,"supported":41,"title":305,"abstract":306,"tags":308},[],[293,307],"precision agriculture",[28,292,293],{"code":295,"score":20,"supported":41,"title":310,"abstract":311,"tags":315},[],[312,313,314],"物联网","internet of things","IoT",[],{"code":317,"score":40,"supported":41,"title":318,"abstract":319,"tags":322},"I3",[],[320,321],"遥感","remote sensing",[],{"code":324,"score":40,"supported":41,"title":325,"abstract":326,"tags":329},"I4",[],[327,328],"地理信息","GIS",[],{"code":174,"score":108,"supported":41,"title":331,"abstract":332,"tags":334},[],[333],"artificial intelligence",[],{"code":54,"score":21,"supported":14,"title":336,"abstract":337,"tags":338},[],[],[29],[340,341],"数字化转型 农业企业 智慧农业 精准农业","数字化转型 农业企业","数字化转型农业企业智慧农业精准农业-1416",4,"10.32782\u002Finfrastruct90-32",{"doi":344,"openalex_id":346,"authors":347,"venue":281,"cited_by_count":73,"oa_url":278,"card":355,"direction":361,"ingested_from":80},"W7204884481",[348,350,353],{"name":349,"orcid":9},"Lidiіa Fedoryshynа",{"name":351,"orcid":352},"Yuliia Aleskerova","https:\u002F\u002Forcid.org\u002F0000-0003-3072-4854",{"name":354,"orcid":9},"Lydmyla Drymanova",{"tldr":356,"method":357,"finding":358,"direction":359,"opportunity":360},"探讨数字技术对农业企业创新发展的影响，分析效益与障碍并提出改进路径。","综述数字技术应用，分析效益与障碍，提出实践方案。","数字技术提升效率与竞争力，但受投资、设施、人才和网络安全制约。","农业人工智能与决策模型","可深入研究数字技术采纳的障碍机制，构建农业企业数字化转型的评估与促进模型。","智慧农业 \u002F 农业物联网","2026-09-02T23:30:15.371042Z",{"id":364,"title":365,"url":366,"summary":367,"summary_zh":9,"content":9,"source_name":368,"source_url":366,"published_at":90,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":369,"score_detail":370,"sources":372,"tags":374,"primary_topic":377,"secondary_topics":381,"classification":382,"search_phrases":394,"slug":397,"view_count":73,"doi":398,"paper":399,"created_at":414},5579,"A Composite Field-Evaluation Framework for Digital Agriculture Maps","https:\u002F\u002Fdoi.org\u002F10.21203\u002Frs.3.rs-11283264\u002Fv1","A Composite Field-Evaluation Framework for Digital Agriculture Maps。Research Square","Research Square",38,{"impact":93,"substance":40,"depth":93,"authority":40,"freshness":13,"relevant":21,"comment":371},"预印本提出数字农业地图的田间复合评估框架，方法有一定新意，但摘要信息极少、未经同行评审，公共影响有限，暂不宜进入每日精选。",[373],{"name":368,"url":366},[26,375,320,376],"农业信息化","地图评估",{"code":48,"slug":378,"name":379,"path":380,"parent_code":299},"smart-agriculture","智慧农业总论","\u002Ftopic\u002Fdigital-agriculture\u002Fsmart-agriculture",[],{"status":237,"locked":14,"version":34,"method":35,"evidence":383},{"candidates":384,"agricultural_evidence":41},[385,390],{"code":48,"score":19,"supported":41,"title":386,"abstract":388,"tags":389},[387],"digital agriculture",[387],[375,26],{"code":317,"score":21,"supported":14,"title":391,"abstract":392,"tags":393},[],[],[320],[395,396],"Research Square 数字农业","农业信息化 地图评估 数字农业 遥感","ResearchSquare数字农业-5579","10.21203\u002Frs.3.rs-11283264\u002Fv1",{"doi":398,"openalex_id":400,"authors":401,"venue":368,"cited_by_count":73,"oa_url":366,"card":9,"direction":78,"ingested_from":80},"W7223099987",[402,405,408,411],{"name":403,"orcid":404},"Phillip Lanza","https:\u002F\u002Forcid.org\u002F0000-0002-5545-1744",{"name":406,"orcid":407},"David G. Rossiter","https:\u002F\u002Forcid.org\u002F0000-0003-4558-1286",{"name":409,"orcid":410},"Diana Stuart Sinton","https:\u002F\u002Forcid.org\u002F0000-0001-5828-9001",{"name":412,"orcid":413},"Louis Longchamps","https:\u002F\u002Forcid.org\u002F0000-0002-4761-6094","2026-10-22T11:20:47.463814Z",{"id":416,"title":417,"url":418,"summary":419,"summary_zh":420,"content":9,"source_name":421,"source_url":418,"published_at":90,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":422,"score_detail":423,"sources":425,"tags":427,"primary_topic":432,"secondary_topics":433,"classification":434,"search_phrases":450,"slug":453,"view_count":73,"doi":454,"paper":455,"created_at":467},5578,"Unlocking digital agriculture through new quality productive forces: nonlinear thresholds and spatial spillovers in China","https:\u002F\u002Fdoi.org\u002F10.1057\u002Fs41599-026-09510-z","New quality productive forces (NQPF) critically enable agricultural digitisation. Using China as a case study, this paper employs panel data from 284 prefecture-level cities in China from 2011 to 2022. The results show that NQPF has a significant promoting effect on agricultural digital transformation and exhibits positive spatial spillover effects, driving not only local transformation but also the development of surrounding regions. Labour skills and innovation capacity play mediating roles in this process. Notably, the enabling effect of NQPF on agricultural digitisation displays significant regional heterogeneity. Threshold analysis indicates that its promoting effect follows a non-linear pattern, characterised by a double threshold effect. Therefore, the development of NQPF should be accelerated, with emphasis placed on regional coordination and talent cultivation, to promote the sustained and in-depth advancement of agricultural digital transformation in accordance with local conditions.","新质生产力（New Quality Productive Forces, NQPF）对农业数字化具有关键赋能作用。本文以中国为案例，采用2011—2022年中国284个地级市的面板数据。结果表明，新质生产力对农业数字化转型具有显著促进作用，并呈现正向空间溢出效应，不仅推动本地转型，也带动周边地区发展。劳动技能与创新能力在这一过程中发挥中介作用。值得注意的是，新质生产力对农业数字化的赋能效应表现出显著的区域异质性。门槛分析表明，其促进作用呈非线性特征，表现为双重门槛效应。因此，应加快新质生产力发展，注重区域协调与人才培养，因地制宜推动农业数字化转型持续深入推进。","Humanities and Social Sciences Communications",81,{"impact":17,"substance":18,"depth":17,"authority":287,"freshness":20,"relevant":21,"comment":424},"基于284个地级市面板数据的实证研究，揭示新质生产力对农业数字化的非线性门槛与空间溢出效应，方法规范、结论有政策参考价值，值得进入每日精选。",[426],{"name":421,"url":418},[26,428,429,430,431],"新质生产力","空间溢出","区域协调","农业数字化转型",{"code":48,"slug":378,"name":379,"path":380,"parent_code":299},[],{"status":237,"locked":14,"version":34,"method":35,"evidence":435},{"candidates":436,"agricultural_evidence":41},[437,441,445],{"code":48,"score":13,"supported":41,"title":438,"abstract":439,"tags":440},[387],[],[431,26],{"code":324,"score":21,"supported":14,"title":442,"abstract":443,"tags":444},[],[],[429],{"code":446,"score":21,"supported":14,"title":447,"abstract":448,"tags":449},"J2",[],[],[428],[451,452],"新质生产力 农业数字化","地级市 面板数据","新质生产力农业数字化-5578","10.1057\u002Fs41599-026-09510-z",{"doi":454,"openalex_id":456,"authors":457,"venue":421,"cited_by_count":73,"oa_url":418,"card":462,"direction":78,"ingested_from":80},"W7221723385",[458,460],{"name":459,"orcid":9},"Qingqing Huang",{"name":461,"orcid":9},"Wenjing Guo",{"tldr":463,"method":464,"finding":465,"direction":78,"opportunity":466},"基于中国284个地级市面板数据，检验新质生产力对农业数字化的促进、空间溢出与门槛效应。","2011—2022年284个地级市面板数据，空间计量与门槛回归，中介效应检验。","新质生产力显著促进农业数字化并具正向空间溢出，存在双门槛非线性效应与区域异质性。","可深入探究新质生产力影响农业数字化的微观机制，以及不同区域门槛条件下的差异化政策路径。","2026-10-22T11:20:47.354744Z"]