[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-3754":3,"related-3754":66},{"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":8,"secondary_topics":31,"classification":32,"search_phrases":50,"slug":53,"view_count":54,"doi":8,"paper":55,"created_at":65},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",[],{"status":33,"locked":13,"version":34,"method":35,"evidence":36},"unclassified","2026-10-22.2","rules",{"candidates":37,"agricultural_evidence":48,"reason":49},[38,43],{"code":39,"score":21,"supported":13,"title":40,"abstract":41,"tags":42},"G3",[],[],[27],{"code":44,"score":21,"supported":13,"title":45,"abstract":46,"tags":47},"I6",[],[],[26],true,"缺少足够的主题证据",[51,52],"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",3,{"doi":8,"openalex_id":8,"authors":56,"venue":8,"cited_by_count":57,"oa_url":8,"card":58,"direction":62,"ingested_from":64},[],0,{"tldr":59,"method":60,"finding":61,"direction":62,"opportunity":63},"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":67,"page":21,"page_size":67,"items":68},6,[69,156,202,251,306,384],{"id":70,"title":71,"url":72,"summary":73,"summary_zh":74,"content":8,"source_name":75,"source_url":72,"published_at":76,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":77,"score_detail":78,"sources":85,"tags":87,"primary_topic":92,"secondary_topics":98,"classification":99,"search_phrases":132,"slug":135,"view_count":57,"doi":136,"paper":137,"created_at":155},5491,"Analysis of the Impact of Digital Technology on the Resilience of Anhui’s Agricultural Industry Chain: Threshold Effect of Relative Grain Yield","https:\u002F\u002Fdoi.org\u002F10.3390\u002Fsu182010656","Improving the resilience of the agricultural industry chain to frequent external shocks and the intertwined agricultural production risks is critical for ensuring national food security and sustainable agricultural development. Taking the 16 prefecture-level cities in Anhui Province—a major grain-producing region in China—as the research sample, two composite proxy indices were constructed in this study; namely, an agricultural industry chain resilience index built upon aggregate official statistics (rather than direct observed shock-response outcomes) and an index capturing broad rural digital development instead of purely agriculture-specific digital adoption. Based on balanced panel data from 2015 to 2024, two-way fixed-effect, mediation-effect, and panel-threshold models were adopted in this study to examine the association, mediating mechanism, regional heterogeneity, and threshold characteristics conditioned on the relative grain yield. The empirical results show that the rural-oriented digital development index is significantly and robustly positively associated with our composite agricultural industry chain resilience proxy. Although agricultural TFP exhibits a statistically detectable partial mediating pattern in this correlational relationship, the economic magnitude of this indirect channel is extremely modest. As such, this finding indicates a potential theoretical transmission pathway rather than providing definitive empirical evidence for a causal mechanism. The promotion effect exhibits clear regional heterogeneity, with the strongest effect in Northern Anhui, followed by Central Anhui, while the coefficient is positive but insignificant in Southern Anhui. Furthermore, a single-threshold effect of the relative grain yield is identified; that is, the positive association between rural-oriented digital development and resilience proxy cannot be statistically detected when the grain yield remains below the threshold. Only after the agricultural grain yield increases can digital-related rural development release its resilience-related empowering dividends. We note that both composite indices are subject to measurement constraints linked to the local agricultural economic scale and broad rural digital conditions; these limitations are further discussed in the paper. This study provides empirical correlational evidence for the implementation of differentiated digital agriculture policies in major grain-producing provinces.","提升农业产业链对频繁外部冲击与交织叠加的农业生产风险的韧性，对保障国家粮食安全和农业可持续发展至关重要。本研究以中国粮食主产省安徽省的16个地级市为研究样本，构建了两个复合代理指标：一是基于官方统计数据总量（而非直接观测的冲击—响应结果）构建的农业产业链韧性指数，二是刻画农村数字化广泛发展（而非单纯农业领域数字化应用）的指数。基于2015—2024年平衡面板数据，本研究采用双向固定效应模型、中介效应模型和面板门槛模型，考察二者之间的关联、中介机制、区域异质性以及以相对粮食产量为条件变量的门槛特征。实证结果表明，农村导向的数字化发展指数与本研究的农业产业链韧性复合代理指标之间存在显著且稳健的正向关联。尽管农业全要素生产率在这一相关关系中呈现出统计上可检测的部分中介模式，但该间接渠道的经济量级极为有限。因此，这一发现指示的是一种潜在的理论传导路径，而非为因果机制提供确凿的实证证据。其促进效应表现出明显的区域异质性，皖北效应最强，皖中次之，皖南系数为正但不显著。此外，还识别出相对粮食产量的单一门槛效应，即当粮食产量低于门槛值时，农村导向的数字化发展与韧性代理指标之间的正向关联在统计上无法被检测到；只有在农业粮食产量提高之后，数字相关农村发展才能释放其韧性赋能红利。我们注意到，两个复合指数均受到与地方农业经济规模和农村数字化总体状况相关的测度约束；这些局限性在文中进一步讨论。本研究为粮食主产省实施差异化数字农业政策提供了实证相关性证据。","Sustainability","2026-10-20T00:00:00Z",74,{"impact":79,"substance":80,"depth":81,"authority":82,"freshness":83,"relevant":21,"comment":84},16,20,17,13,8,"基于安徽16市面板数据的实证研究，方法规范、结论有区域异质性价值，但属省级学术论文，公共影响有限，适合作为主题页聚合素材而非头条精选。",[86],{"name":75,"url":72},[88,89,90,30,91],"数字农业","数字乡村","粮食安全","安徽农业",{"code":93,"slug":94,"name":95,"path":96,"parent_code":97},"A8","yield-food-security","单产提升与粮食安全","\u002Ftopic\u002Ffield-crops\u002Fyield-food-security","A",[],{"status":100,"locked":13,"version":34,"method":35,"evidence":101},"classified",{"candidates":102,"agricultural_evidence":48},[103,109,115,122,128],{"code":93,"score":104,"supported":48,"title":105,"abstract":106,"tags":108},7,[],[90,107],"food security",[90],{"code":110,"score":104,"supported":48,"title":111,"abstract":112,"tags":114},"I1",[],[88,113],"digital agriculture",[88],{"code":116,"score":67,"supported":48,"title":117,"abstract":118,"tags":121},"G",[],[119,120],"农村发展","rural development",[],{"code":123,"score":54,"supported":48,"title":124,"abstract":125,"tags":127},"J1",[],[126],"农业政策",[],{"code":44,"score":21,"supported":13,"title":129,"abstract":130,"tags":131},[],[],[89],[133,134],"安徽 农业产业链韧性 数字技术","安徽 粮食产量 数字乡村","安徽农业产业链韧性数字技术-5491","10.3390\u002Fsu182010656",{"doi":136,"openalex_id":138,"authors":139,"venue":75,"cited_by_count":57,"oa_url":72,"card":149,"direction":62,"ingested_from":154},"W7223005655",[140,143,145,147],{"name":141,"orcid":142},"Lan Ma","https:\u002F\u002Forcid.org\u002F0000-0003-2468-9917",{"name":144,"orcid":8},"Yuyan Li",{"name":146,"orcid":8},"张国亮",{"name":148,"orcid":8},"Yaoyao Li",{"tldr":150,"method":151,"finding":152,"direction":62,"opportunity":153},"以安徽16市面板数据检验农村数字发展对农业产业链韧性的影响及粮食产量门槛效应。","2015—2024年安徽16市平衡面板，双向固定效应、中介效应与面板门槛模型。","数字发展显著提升产业链韧性，存在粮食相对产量单门槛，且皖北效应最强、皖南不显著。","可细化数字技术指标、引入真实冲击响应韧性测度，并探究门槛形成机制与皖南失效原因。","openalex","2026-10-21T23:30:29.219265Z",{"id":157,"title":158,"url":159,"summary":160,"summary_zh":8,"content":8,"source_name":161,"source_url":8,"published_at":76,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":14,"score_detail":162,"sources":166,"tags":168,"primary_topic":172,"secondary_topics":176,"classification":177,"search_phrases":189,"slug":192,"view_count":57,"doi":193,"paper":194,"created_at":201},5463,"中国粮食生产现代化时空演变特征及影响因素分析 (Spatiotemporal Evolution and Influencing Factors of Grain Production Modernization in China)","http:\u002F\u002Fzgnjhxb.niam.com.cn\u002FCN\u002F10.13733\u002Fj.jcam.issn.2095-5553.2026.10.042","基于2011—2023年省级面板数据，六维构建粮食生产现代化指标，用核密度、空间自相关与GTWR分析。水平稳步提升，呈主产区＞主销区＞产销平衡区梯度；山东、江苏、安徽形成稳定高—高集聚区。数字普惠金融与财政支农正向。","中国农机化学报 2026-10-20",{"impact":18,"substance":163,"depth":18,"authority":82,"freshness":164,"relevant":21,"comment":165},21,9,"基于省级面板数据构建六维指标并采用GTWR方法，结论对粮食生产现代化区域差异与数字普惠金融作用有参考价值，但属学术论文，公共影响有限。",[167],{"name":161,"url":159},[90,169,27,170,171],"财政支农","粮食生产现代化","空间集聚",{"code":39,"slug":173,"name":174,"path":175,"parent_code":116},"rural-finance","农村金融与保险","\u002Ftopic\u002Frural-services\u002Frural-finance",[],{"status":100,"locked":13,"version":34,"method":35,"evidence":178},{"candidates":179,"agricultural_evidence":48},[180,185],{"code":39,"score":181,"supported":48,"title":182,"abstract":183,"tags":184},5,[],[169],[27,169],{"code":93,"score":21,"supported":13,"title":186,"abstract":187,"tags":188},[],[],[90],[190,191],"粮食生产现代化 时空演变","数字普惠金融 粮食生产","粮食生产现代化时空演变-5463","10.13733\u002Fj.jcam.issn.2095-5553.2026.10.042",{"doi":193,"openalex_id":8,"authors":195,"venue":8,"cited_by_count":57,"oa_url":8,"card":196,"direction":62,"ingested_from":64},[],{"tldr":197,"method":198,"finding":199,"direction":62,"opportunity":200},"构建六维指标测度2011—2023年中国粮食生产现代化水平并分析其时空演变与影响因素。","省级面板数据，六维指标体系，核密度、空间自相关与GTWR模型。","现代化水平稳步提升，呈主产区>主销区>产销平衡区梯度，山东、江苏、安徽为稳定高—高集聚区。","可探究数字普惠金融与财政支农的协同机制，并细化到县域尺度检验空间溢出效应。","2026-10-21T00:10:08.522187Z",{"id":203,"title":204,"url":205,"summary":206,"summary_zh":207,"content":8,"source_name":208,"source_url":205,"published_at":209,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":210,"score_detail":211,"sources":213,"tags":215,"primary_topic":8,"secondary_topics":220,"classification":221,"search_phrases":233,"slug":236,"view_count":57,"doi":237,"paper":238,"created_at":250},5369,"Return-home entrepreneurship and rural economic resilience: evidence from China's National pilot program","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1961226","We study whether policies that encourage migrants to return home and start businesses strengthen rural economies. We treat China's national return-home entrepreneurship pilot, introduced in cohorts in 2016 and 2017, as a quasi-natural experiment and assemble an unbalanced panel of 2,097 counties, county-level cities, and urban districts from 1999 to 2023. A staggered difference-in-differences design indicates that pilot designation is positively associated with a principal-component index of rural economic resilience capacity and that the estimated effect emerges with a lag. The joint test of all pretreatment coefficients does not reject equality to zero at the 5% level, although it is marginal at the 10% level; a negative pooled long-lead estimate therefore continues to warrant caution. Alternative staggered-adoption estimators, resilience indices that exclude development-oriented components, a sample restricted through 2021, and a complete-case regression using only original non-interpolated observations all remain positive. Channel regressions show that the pilot raises the secondary- and tertiary-sector share and the China Rural Agriculture-Related Innovation Index, although these patterns do not establish causal mediation. Digital financial inclusion is not robust to county and year fixed effects. Formal between-group tests indicate significant regional and poverty-status differences, but not significant grain-production or labor-export differences; Hypothesis IV is therefore only partially supported. The national pilot ended in 2021, but return-home entrepreneurship policy continued through institutionalized support and nationwide promotion of the pilot experience. Accordingly, estimates after 2021 capture the persistent differential associated with earlier pilot designation in an environment of policy continuation and diffusion. Overall, the evidence is consistent with human-capital return and factor reallocation strengthening observed dimensions associated with rural economic resilience capacity, while the pooled long lead and the reduced coverage of the raw complete-case sample remain important qualifications.","我们研究鼓励流动人口返乡创业的政策是否增强了农村经济。我们将中国于2016年和2017年分批推出的全国返乡创业试点视为一项准自然实验，并构建了1999年至2023年涵盖2，097个县、县级市和市辖区的不平衡面板数据。交错双重差分设计表明，试点认定与农村经济韧性能力的主成分指数呈正相关，且估计效应存在滞后。对所有处理前系数的联合检验在5%水平上不能拒绝其等于零，尽管在10%水平上处于边缘显著；因此，合并的长期领先估计为负仍需谨慎对待。替代性交错采纳估计量、剔除发展导向成分的韧性指数、截至2021年的限制样本，以及仅使用原始非插值观测的完整案例回归，结果均保持为正。渠道回归显示，试点提高了第二产业和第三产业占比以及中国农村农业相关创新指数，尽管这些模式并不能确立因果中介效应。数字普惠金融在控制县和年份固定效应后不稳健。正式的组间检验表明，区域和贫困状况差异显著，但粮食生产或劳动力输出差异不显著；因此假设IV仅得到部分支持。全国试点于2021年结束，但返乡创业政策通过制度化支持和试点经验的全国推广得以延续。据此，2021年之后的估计捕捉的是在政策延续和扩散环境下与早期试点认定相关的持续性差异。总体而言，证据与人力资本回流和要素再配置强化农村经济韧性能力相关观测维度相一致，但合并的长期领先估计和原始完整案例样本覆盖范围缩小仍是重要的限定条件。","Frontiers in Sustainable Food Systems","2026-10-19T00:00:00Z",82,{"impact":16,"substance":163,"depth":18,"authority":82,"freshness":83,"relevant":21,"comment":212},"基于2097个县域面板数据的准自然实验，评估返乡创业试点对乡村经济韧性的滞后正向效应，方法规范、结论审慎，属三农政策研究前沿，值得精选。",[214],{"name":208,"url":205},[216,27,217,218,219],"县域经济","政策评估","返乡创业","乡村经济韧性",[],{"status":33,"locked":13,"version":34,"method":35,"evidence":222},{"candidates":223,"agricultural_evidence":48,"reason":49},[224,228],{"code":39,"score":21,"supported":13,"title":225,"abstract":226,"tags":227},[],[],[27],{"code":229,"score":21,"supported":13,"title":230,"abstract":231,"tags":232},"G4",[],[],[216],[234,235],"返乡创业试点 县域经济韧性","返乡创业 准自然实验","返乡创业试点县域经济韧性-5369","10.3389\u002Ffsufs.2026.1961226",{"doi":237,"openalex_id":239,"authors":240,"venue":208,"cited_by_count":57,"oa_url":244,"card":245,"direction":62,"ingested_from":154},"W7222929203",[241],{"name":242,"orcid":243},"Wenyi Zhou","https:\u002F\u002Forcid.org\u002F0009-0002-3482-0755","https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fsustainable-food-systems\u002Farticles\u002F10.3389\u002Ffsufs.2026.1961226\u002Fpdf",{"tldr":246,"method":247,"finding":248,"direction":62,"opportunity":249},"评估返乡创业试点政策是否增强中国县域农村经济韧性。","以2016-2017分批试点为准自然实验，用交错DID分析2097个县1999-","试点与农村经济韧性指数正相关且存在滞后效应，但长期前置估计需谨慎解读。","可结合县域数字化与数字普惠金融数据，检验返乡创业政策与信息化协同对韧性的因果机制。","2026-10-20T23:30:06.585096Z",{"id":252,"title":253,"url":254,"summary":255,"summary_zh":8,"content":8,"source_name":256,"source_url":8,"published_at":8,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":257,"score_detail":258,"sources":260,"tags":262,"primary_topic":267,"secondary_topics":273,"classification":274,"search_phrases":293,"slug":296,"view_count":57,"doi":8,"paper":297,"created_at":305},5360,"国家农业绿色发展试点区对农业碳排放的影响:基于 284 城市 2013-2023 年面板数据","https:\u002F\u002Fm2.mtmt.hu\u002Fapi\u002Fpublication\u002F37540958","研究基于 284 个城市 2013—2023 年面板数据,以国家农业绿色发展试点区(NAGDPZ)为准自然实验,采用双重差分法(DID)系统评估政策对农业碳排放的影响。研究发现:(1)NAGDPZ 政策显著降低农业碳排放,系数为 -0.008(10% 显著);(2)机制分析表明减排效应主要通过农业生产效率提升、数字普惠金融发展和农村创新创业推动;(3)异质性分析显示南方、非粮食主产区、农业金融支持水平较高地区的碳减排效应更显著,系数分别为 -0.008、-.016、-0.015。","《中国环境科学》46(1):555-567 2026",78,{"impact":16,"substance":16,"depth":18,"authority":19,"freshness":20,"relevant":21,"comment":259},"基于284城市十年面板数据的政策评估，方法规范、结论有新意，但发表时间较早、时效性弱，适合作为研究型精选而非快讯。",[261],{"name":256,"url":254},[263,27,264,265,266],"农业绿色发展","双重差分","农业碳排放","绿色试点区",{"code":268,"slug":269,"name":270,"path":271,"parent_code":272},"H4","carbon","农业碳与绿色低碳","\u002Ftopic\u002Fenvironment\u002Fcarbon","H",[],{"status":100,"locked":13,"version":34,"method":35,"evidence":275},{"candidates":276,"agricultural_evidence":48},[277,284,288],{"code":268,"score":278,"supported":48,"title":279,"abstract":282,"tags":283},24,[280,281],"碳排放","农业碳",[280,281],[265,263],{"code":39,"score":21,"supported":13,"title":285,"abstract":286,"tags":287},[],[],[27],{"code":289,"score":21,"supported":13,"title":290,"abstract":291,"tags":292},"H8",[],[],[263],[294,295],"国家农业绿色发展试点区 农业碳排放","284城市 面板数据 碳减排","国家农业绿色发展试点区农业碳排放-5360",{"doi":8,"openalex_id":8,"authors":298,"venue":8,"cited_by_count":57,"oa_url":8,"card":299,"direction":303,"ingested_from":64},[],{"tldr":300,"method":301,"finding":302,"direction":303,"opportunity":304},"基于284城市面板数据，用DID评估国家农业绿色发展试点区对农业碳排放的影响。","284城市2013-2023年面板数据，双重差分法（DID）准自然实验。","试点区政策显著降低农业碳排放，主要通过生产效率、数字普惠金融和农村创新创业实现。","农业绿色发展与碳","可探究数字普惠金融与绿色试点政策的协同减排机制，及非粮食主产区的差异化政策设计。","2026-10-20T02:47:54.150914Z",{"id":307,"title":308,"url":309,"summary":310,"summary_zh":311,"content":8,"source_name":312,"source_url":309,"published_at":313,"category":11,"cover_url":8,"hotness":314,"is_selected":13,"score":315,"score_detail":316,"sources":319,"tags":324,"primary_topic":329,"secondary_topics":334,"classification":335,"search_phrases":365,"slug":368,"view_count":57,"doi":369,"paper":370,"created_at":383},5247,"From transfers to transformation: mobile money and the modernization of rice farming in Côte d’Ivoire","https:\u002F\u002Fdoi.org\u002F10.6084\u002Fm9.figshare.34660410","In this study, we explore how Mobile Money (MM) adoption influences farm management choices of smallholder rice production in Côte d’Ivoire, a West African context characterised by rich agricultural potential and moderately low digital financial inclusion. Using an endogenous switching regression (ESR) framework to a sample of 1,370 smallholder producers from three rice-producing departments and complemented by an inverse probability weighted regression adjustment (IPWRA) estimator for robustness to estimate the impact of MM on both agricultural intensification (higher fertilizer use), extensification (greater expansion of cultivated areas for food and cash crops outside rice farming system), total rice productivity and better market participation. There is evidence to suggest that remittances may be a plausible channel through which these effects work, by alleviating liquidity constraints, thus allowing clients to invest seasonally in inputs and labor. Our findings extend the mobile money literature, which remains concentrated in East Africa, by providing new evidence from an under-explored West African context, and offers important implications for policies promoting digital financial inclusion as a means of rural transformation. This study looks at the role of mobile money in the modernization of smallholder rice farming in Côte d’Ivoire. Using survey data from rice farmers, we examine whether mobile money use is linked to changes in farm management, input use, productivity, and access to markets. The results provide evidence that mobile financial services can help farmers manage some of the financial and transaction constraints associated with agricultural production. The study adds to the limited empirical evidence on the productive use of mobile money in African agriculture and provides useful insights for policies aimed at expanding digital financial services among smallholder farmers.","本研究探讨移动货币（Mobile Money，MM）的采用如何影响科特迪瓦小农户水稻生产的农场管理选择，该西非背景以丰富的农业潜力和中等偏低的数字金融普惠水平为特征。研究采用内生转换回归（Endogenous Switching Regression，ESR）框架，对来自三个水稻生产部门的1，370名小农户生产者样本进行分析，并辅以逆概率加权回归调整（Inverse Probability Weighted Regression Adjustment，IPWRA）估计量进行稳健性检验，以估计移动货币对农业集约化（提高化肥使用量）、外延化（在稻田系统之外扩大粮食作物和经济作物的种植面积）、水稻总生产率以及更好的市场参与的影响。有证据表明，汇款可能是一个可行的渠道，通过这些效应发挥作用，即缓解流动性约束，从而使客户能够按季节投资于投入品和劳动力。我们的研究拓展了移动货币文献——该文献仍集中于东非——通过提供来自一个尚未充分探索的西非背景的新证据，并为促进数字金融普惠作为农村转型手段的政策提供了重要启示。本研究考察移动货币在科特迪瓦小农户水稻种植现代化中的作用。利用水稻种植者的调查数据，我们检验移动货币的使用是否与农场管理、投入品使用、生产率和市场准入的变化相关联。结果提供证据表明，移动金融服务可以帮助农民应对与农业生产相关的一些财务和交易约束。本研究补充了关于移动货币在非洲农业中生产性用途的有限实证证据，并为旨在扩大数字金融服务在小农户中覆盖面的政策提供了有益见解。","Figshare","2026-10-17T00:00:00Z",25,64,{"impact":317,"substance":163,"depth":81,"authority":67,"freshness":83,"relevant":21,"comment":318},12,"该研究基于1370户样本，采用ESR与IPWRA方法，为西非移动支付促进水稻生产现代化提供了新证据，但属区域性学术成果，公共影响有限，未达每日精选门槛。",[320,321],{"name":312,"url":309},{"name":322,"url":323},"Cogent Economics & 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水稻","科特迪瓦水稻移动支付-5247","10.6084\u002Fm9.figshare.34660410",{"doi":369,"openalex_id":371,"authors":372,"venue":312,"cited_by_count":57,"oa_url":309,"card":378,"direction":62,"ingested_from":154},"W7222786991",[373,376],{"name":374,"orcid":375},"Innocent Daniel Gniza","https:\u002F\u002Forcid.org\u002F0000-0002-9617-1562",{"name":377,"orcid":8},"Grakolet Arnold 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江 中国网络空间研究院院长","闪电新闻\u002F中国网信网 2026-10-09","2026-10-09T00:00:00Z","报道",92,{"impact":395,"substance":17,"depth":18,"authority":396,"freshness":83,"relevant":21,"comment":397},28,15,"中央三部门联合印发数字乡村五年行动计划，含5G通达率95%等关键数据与六大重点方向，权威性与信息增量俱佳，值得进入每日精选。",[399],{"name":390,"url":387},[89,401,27,402,403],"农业人工智能","乡村建设信息化","智慧美丽乡村",{"code":44,"slug":405,"name":406,"path":407,"parent_code":408},"digital-village","数字乡村与数据要素","\u002Ftopic\u002Fdigital-agriculture\u002Fdigital-village","I",[],{"status":100,"locked":13,"version":34,"method":35,"evidence":411},{"candidates":412,"agricultural_evidence":48},[413,417,421],{"code":44,"score":317,"supported":48,"title":414,"abstract":415,"tags":416},[89],[89],[89],{"code":39,"score":21,"supported":13,"title":418,"abstract":419,"tags":420},[],[],[27],{"code":422,"score":21,"supported":13,"title":423,"abstract":424,"tags":425},"I2",[],[],[401],[427,428],"乡村建设信息化 5G通达率","乡村建设信息化 农业人工智能 数字普惠金融 智慧美丽乡村","乡村建设信息化5G通达率-4623","2026-10-11T00:09:36.413889Z"]