[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-1118":3,"related-1118":71},{"id":4,"title":5,"url":6,"summary":7,"summary_zh":8,"content":9,"source_name":10,"source_url":8,"published_at":11,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":15,"score_detail":16,"sources":24,"tags":26,"primary_topic":32,"secondary_topics":38,"classification":39,"search_phrases":64,"slug":67,"view_count":68,"doi":69,"paper":8,"created_at":70},1118,"Rural household livelihood resilience under digital transformation: evidence from participation pathways and U-shaped effects","https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fsustainable-food-systems\u002Farticles\u002F10.3389\u002Ffsufs.2026.1826981\u002Ffull","Ying Yang、Zenghui Huo(中国计量大学经济管理学院)、Fuqiao Chen(中国农业科学院茶叶研究所)、Zhongming Zhang 发表论文。基于江苏省农村地区微观调查数据和县级数字基础设施指数,构建\"缓冲能力-自组织能力-学习能力-心理适应能力\"生计韧性衡量框架,采用OLS回归、U型回归模型、HLM分层线性模型和中介效应模型,实证分析数字基础设施对农户生计韧性的影响及机制。数字基础设施总体显著增强农户生计韧性,但呈现U型非线性影响;数字信息和数字金融参与是主要传导机制;高收入家庭、全职与兼业农户、非经济困难村的U型赋能效应更显著。本研究为乡村振兴与数字乡村建设融合推进提供实证证据与政策建议。",null,"## Abstract\n\n**Introduction:**\n\nDriven by the digital rural strategy, the construction of digital infrastructure has become a critical technological foundation for advancing agricultural and rural modernization, as well as enhancing the rural household livelihood resilience.\n\n**Methods:**\n\nDrawing on micro-level survey data from rural areas in Jiangsu Province and a county-level digital infrastructure index, this study constructs a “buffering capacity–self-organisation capacity–learning capacity–psychological adaptation capacity” framework for measuring livelihood resilience. Using Ordinary Least Squares models, U-shaped regression models, Hierarchical Linear Model (HLM) and mediation effect models, it empirically analyses the impact of digital infrastructure on rural household livelihood resilience and its underlying mechanisms. The study further employs instrumental variables (IV) and double\u002Fdebiased machine learning (DDML) models to address endogeneity issues.\n\n**Results:**\n\nThe findings suggest that digital infrastructure in rural areas remarkably enhances rural household livelihood resilience overall, though the impact follows a U-shaped nonlinear pattern. Mediation analysis indicates that digital infrastructure significantly enhances farmers’ participation in digital information and digital finance, which indirectly strengthens their livelihood resilience. Heterogeneity analysis reveals that higher-income households, full-time and part-time farming households, and non-economically disadvantaged villages exhibit a significant U-shaped empowerment effect from digital infrastructure. Among them, full-time farming households are more sensitive to digital infrastructure transformation, showing a steeper U-shaped curve.\n\n**Discussion:**\n\nThis research increases the comprehension of the connection between digital rural development and livelihood resilience at a micro level, offering empirical evidence and policy recommendations for the integrated advancement of rural revitalization and digital rural construction.\n\n## 1 Introduction\n\nIn the midst of rapid global digital transformation, digital technologies have become a key driver of national development and socio-economic change. However, this process has also intensified the urban–rural divide. Due to limited access to relevant technologies, rural areas lag behind in digitalization, restricting their economic growth and integration into broader economic systems ([Xia and Kong, 2024](https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fsustainable-food-systems\u002Farticles\u002F10.3389\u002Ffsufs.2026.1826981\u002Ffull#ref51)). Promoting digital transformation in rural areas is therefore crucial, not only to narrow this gap, but also to achieve long-term rural revitalization goals. Globally, developed countries recognize the role of digital technologies in rural revitalization and have implemented related policies. For example, both the [European Commission (2026)](https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fsustainable-food-systems\u002Farticles\u002F10.3389\u002Ffsufs.2026.1826981\u002Ffull#ref16) call to further advance “Smart Villages” under the frameworks of “the Long-Term Vision for Rural Areas” and “the Strategy on Generational Renewal in Agriculture” and the fifth round of “the USDA’s ReConnect Program” ([Rupasingha et al., 2026](https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fsustainable-food-systems\u002Farticles\u002F10.3389\u002Ffsufs.2026.1826981\u002Ffull#ref15)), highlight the empowering effects of digital rural development by seeking to expand internet access to stimulate economic vitality in rural areas. Similarly, developing countries like China are actively advancing rural digital infrastructure. For instance, the “China-FAO Phase III South-South Cooperation Trust Fund” project supports the digital transformation of food systems in the Community of Latin American and Caribbean States (CELAC), aiming to enhance the resilience of rural household livelihoods through information technology ([Dong, 2023](https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fsustainable-food-systems\u002Farticles\u002F10.3389\u002Ffsufs.2026.1826981\u002Ffull#ref12)). In addition, “the Key Tasks for Digital Rural Development in 2025”, jointly issued by four departments of the Chinese government, explicitly calls for consolidating the foundations of digital rural development and implementing targeted initiatives to strengthen agriculture, benefit farmers, and increase rural incomes through digitalization ([Dong, 2023](https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fsustainable-food-systems\u002Farticles\u002F10.3389\u002Ffsufs.2026.1826981\u002Ffull#ref12)). A recent FAO report (2025) further emphasizes that digital tools can help bridge gaps, improve transparency, and enhance resilience. It positions digital agriculture as a key pathway for strengthening smallholders’ livelihood resilience, safeguarding food security, and responding to risk.\n\nDigital infrastructure helps bridge capital endowment gaps among income groups and overcomes resource and geographic constraints that limit opportunities for the poor ([Chen et al., 2022](https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fsustainable-food-systems\u002Farticles\u002F10.3389\u002Ffsufs.2026.1826981\u002Ffull#ref7)). In this context, digital infrastructure is increasingly vital for rural households to withstand risk shocks and enhance livelihood security. At the same time, however, as a new technological factor, the spread of digital infrastructure in rural areas does not occur overnight. According to the technology adoption life cycle, the diffusion of new technologies in rural areas is typically characterized by staged frictions and time lags. The development of digital technologies creates phased thresholds for rural households. Yet, constraints in human capital may hinder the effective realization of digital dividends.\n\nIn the post-pandemic era, poverty in rural China has been addressed systematically, and the nation’s development focus is gradually shifting toward managing diverse risk shocks and achieving sustainable rural development. Sustainable development implies the capacity for long-term growth, which depends not only on the resource base supporting development but also on resilience in the face of risks ([Li et al., 2022](https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fsustainable-food-systems\u002Farticles\u002F10.3389\u002Ffsufs.2026.1826981\u002Ffull#ref23)). Within the framework of sustainable development goals, livelihood resilience is defined as the ability to maintain and expand livelihood opportunities and well-being amid economic, social, environmental, and political instability ([Tang et al., 2023](https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fsustainable-food-systems\u002Farticles\u002F10.3389\u002Ffsufs.2026.1826981\u002Ffull#ref44)). Historically, rural China has been widely regarded as a “society of personal relations” and “relationship-based society,” with a long history of smallholder farming, where farmers generally exhibit characteristics of “resilient households” ([Chen, 2019](https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fsustainable-food-systems\u002Farticles\u002F10.3389\u002Ffsufs.2026.1826981\u002Ffull#ref6)). However, with the interplay of climate change, economic fluctuations, and social structural adjustments, systemic risks facing rural livelihood systems have intensified, posing severe challenges to overall rural livelihood resilience ([Quandt, 2018](https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fsustainable-food-systems\u002Farticles\u002F10.3389\u002Ffsufs.2026.1826981\u002Ffull#ref33); [Roberts et al., 2019](https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fsustainable-food-systems\u002Farticles\u002F10.3389\u002Ffsufs.2026.1826981\u002Ffull#ref35)). Arguably, enhancing livelihood resilience is crucial for increasing rural household incomes and stabilizing poverty alleviation outcomes, and it also directly affects the inclusiveness and resilience of the rural revitalization strategy ([Li et al., 2021](https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fsustainable-food-systems\u002Farticles\u002F10.3389\u002Ffsufs.2026.1826981\u002Ffull#ref24)).\n\nTo date, research on livelihood resilience has primarily focused on three areas: conceptual definition, measurement framework development, and analysis of influencing factors. The concept of resilience was introduced by the ecologist [Holling (1973)](https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fsustainable-food-systems\u002Farticles\u002F10.3389\u002Ffsufs.2026.1826981\u002Ffull#ref20). Later, [Adger (2000)](https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fsustainable-food-systems\u002Farticles\u002F10.3389\u002Ffsufs.2026.1826981\u002Ffull#ref1) extended it to social systems, examining the link between ecological and social resilience in rural communities. More recently, [Lade et al. (2017)](https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fsustainable-food-systems\u002Farticles\u002F10.3389\u002Ffsufs.2026.1826981\u002Ffull#ref22) introduced resilience thinking into poverty governance. Regarding measurement frameworks, no consensus has been reached. The most widely applied framework is that of [Speranza et al. (2014)](https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fsustainable-food-systems\u002Farticles\u002F10.3389\u002Ffsufs.2026.1826981\u002Ffull#ref40), which assesses livelihood resilience through three dimensions: buffering capacity, self-organization, and learning capacity. The [RIMA-II (2016)](https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fsustainable-food-systems\u002Farticles\u002F10.3389\u002Ffsufs.2026.1826981\u002Ffull#ref34) developed a multi-level evaluation system based on policy needs, encompassing livelihood assets, agricultural exchange and learning, adaptive capacity, social safety nets, and access to basic services. Additionally, [Quandt (2018)](https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fsustainable-food-systems\u002Farticles\u002F10.3389\u002Ffsufs.2026.1826981\u002Ffull#ref33) developed a household livelihood resilience framework by incorporating cultural capital into the Sustainable Livelihoods Approach (SLA) proposed by the UK’s Department for International Development (DFID). However, traditional research frameworks have not placed psychological resilience at the center of analysis. Only a few scholars have incorporated it into evaluation systems, emphasizing the role of psychological capital in enhancing resilience and promoting sustainable development ([Cheng and Sun, 2025](https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fsustainable-food-systems\u002Farticles\u002F10.3389\u002Ffsufs.2026.1826981\u002Ffull#ref8)). Empirically, researchers often use weighted composite methods. For example, entropy weighting ([Xu et al., 2025](https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fsustainable-food-systems\u002Farticles\u002F10.3389\u002Ffsufs.2026.1826981\u002Ffull#ref55)) and principal component analysis ([Su et al., 2022](https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fsustainable-food-systems\u002Farticles\u002F10.3389\u002Ffsufs.2026.1826981\u002Ffull#ref42)) are used to determine the indicator weights, while composite index methods ([Dong and Qiu, 2024](https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fsustainable-food-systems\u002Farticles\u002F10.3389\u002Ffsufs.2026.1826981\u002Ffull#ref13)) and the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) model ([Ma et al., 2024a](https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fsustainable-food-systems\u002Farticles\u002F10.3389\u002Ffsufs.2026.1826981\u002Ffull#ref31)) calculate resilience indices. In the same vein, [Cissé and Barrett (2018)](https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fsustainable-food-systems\u002Farticles\u002F10.3389\u002Ffsufs.2026.1826981\u002Ffull#ref10) proposed a novel econometric approach measuring livelihood resilience by the conditional probability of households achieving a specific welfare threshold. In terms of influencing factors, existing studies have mainly analyzed the effects of livelihood capital ([Ma et al., 2024b](https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fsustainable-food-systems\u002Farticles\u002F10.3389\u002Ffsufs.2026.1826981\u002Ffull#ref30)), livelihood strategies ([Luo et al., 2022](https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fsustainable-food-systems\u002Farticles\u002F10.3389\u002Ffsufs.2026.1826981\u002Ffull#ref28)), risk shocks ([Gao et al., 2024](https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fsustainable-food-systems\u002Farticles\u002F10.3389\u002Ffsufs.2026.1826981\u002Ffull#ref18)), agricultural management models ([Lin and Du, 2023](https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fsustainable-food-systems\u002Farticles\u002F10.3389\u002Ffsufs.2026.1826981\u002Ffull#ref25)), and the digital economy ([Xu et al., 2024b](https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fsustainable-food-systems\u002Farticles\u002F10.3389\u002Ffsufs.2026.1826981\u002Ffull#ref56)) on livelihood resilience improvement from perspectives such as sustainable policy effects, regional characteristic resilience development, and external risk shocks.\n\nAgainst this backdrop of advancing digital transformation strategies, research on how digital development drives farmers’ livelihood resilience remains limited. Existing empirical studies primarily center on the empowering effects of digital technology adoption and economic digitization. For example, [Lyu et al. (2025)](https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fsustainable-food-systems\u002Farticles\u002F10.3389\u002Ffsufs.2026.1826981\u002Ffull#ref29) analyzed the impact of digital adoption on livelihood resilience within a sustainable livelihoods framework across the dimensions of production, sales, and financial services, capturing the synergistic effects of comprehensive digital participation. [Shahzad et al. (2025)](https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fsustainable-food-systems\u002Farticles\u002F10.3389\u002Ffsufs.2026.1826981\u002Ffull#ref38) investigated the digitalization of flood resilience strategies in marginalized rural communities in Pakistan. Their study notes that one-third of surveyed households were unable to establish adequate early warning mechanisms due to limited digital communication, thereby hindering the development of livelihood resilience in the area. [Zhu et al. (2025)](https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fsustainable-food-systems\u002Farticles\u002F10.3389\u002Ffsufs.2026.1826981\u002Ffull#ref63) examined the mechanisms through which farmers’ participation in the digital economy improves their livelihood resilience, focusing on three channels: strengthened production capacity, stimulated entrepreneurial vitality, and enhanced effectiveness of financial asset portfolios.\n\nHowever, as one of the two foundational pillars of the “Digital China” strategy, the potential role of digital infrastructure in enhancing rural livelihood resilience has yet to be systematically researched. Most existing literature remains at the level of theoretical deduction regarding digital empowerment and risk response. Only a few scholars have used township 4G base stations as proxies for digital infrastructure to explore its U-shaped impact on household development resilience ([Zhang et al., 2025](https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fsustainable-food-systems\u002Farticles\u002F10.3389\u002Ffsufs.2026.1826981\u002Ffull#ref60)). There is still a lack of in-depth empirical investigation into both the linear and nonlinear relationships between comprehensive regional digital infrastructure and livelihood resilience. In particular, whether these relationships vary across different population groups requires in-depth scrutiny. Furthermore, existing research has predominantly focused on the mechanisms through which digital participation influences livelihood resilience. As a foundational prerequisite for digital transformation, digital infrastructure lacks rigorous empirical exploration regarding its specific impact on farmers’ livelihood resilience. The interrelations among digital infrastructure, digital participation behaviors, and livelihood resilience also remain insufficiently addressed. There is an urgent need to refine the relevant empirical research.\n\nConsequently, this study approaches the issue from the perspective of digital rural construction, analyzing the impact and mechanisms of digital infrastructure development on household livelihood resilience in rural China. Building on current literature, this article may offer the following marginal contributions. First, it establishes a theoretical framework defining “Digital Infrastructure – Digital Participation – Resilience Enhancement.” This study incorporates county-level digital infrastructure as a core driving factor into the analysis of livelihood resilience. It also examines the mechanisms through which digital infrastructure enhances the livelihood resilience of rural households, from the perspectives of information and financial digital participation. It enriches micro-level empirical research on how digital rural construction influences resilience. Second, it comprehensively tests both the linear and nonlinear effects of digital infrastructure. Beyond examining linear impacts, this research introduces a squared term for digital infrastructure to identify potential nonlinearities. This provides empirical support for a comprehensive understanding of the dynamic process of digital infrastructure development and for identifying its stage threshold effects. Third, it reveals the heterogeneity of the U-shaped relationship at the micro level of households and the meso level of villages. It conducts U-shaped heterogeneity tests across household income, livelihood strategy, and village economic conditions. This provides empirical evidence to reveal structural differences in the empowering effects of digital infrastructure and informs targeted policy measures. In summary, this research aims to provide empirical evidence on how digital infrastructure can effectively enhance rural household livelihood resilience, and to offer policy insights for the in-depth integration of digital rural development with rural revitalization strategies.\n\n## 2 Theoretical analysis and research hypotheses\n\n### 2.1 Digital infrastructure and rural household livelihood resilience\n\nIn recent years, technologies such as the internet, big data, and cloud computing have advanced rapidly, making digital technology and the digital economy key areas of international competition ([Fu, 2024](https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fsustainable-food-systems\u002Farticles\u002F10.3389\u002Ffsufs.2026.1826981\u002Ffull#ref17); [Wang et al., 2024](https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fsustainable-food-systems\u002Farticles\u002F10.3389\u002Ffsufs.2026.1826981\u002Ffull#ref49)). It is against this backdrop that the development of digital infrastructure has become a cornerstone for rural digital transformation. By popularizing information technology, the socio-economic structure of rural areas is undergoing profound digital restructuring. Rural digital infrastructure comprises not only network facilities, such as mobile and broadband networks, but also information service platforms, including big data centers, e-commerce, along with the digital modernization of traditional agriculture and transportation infrastructure, among others. According to the China Internet Network Information Center ([CNNIC, 2025](https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fsustainable-food-systems\u002Farticles\u002F10.3389\u002Ffsufs.2026.1826981\u002Ffull#ref11)), the number of rural internet users in China reached 313 million by December 2024, with continuous improvements in rural digital service systems and digital production models. This process not only provides technical support to rural areas, but also serves as a crucial driver of rural economic growth and the improvement of farmers’ well-being.\n\nLivelihood resilience extends the concept of “resilience” into the socio-economic domain. It emphasizes how farmers respond to risks and pressures through resource transformation and strategic adjustments ([Tanner et al., 2015](https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fsustainable-food-systems\u002Farticles\u002F10.3389\u002Ffsufs.2026.1826981\u002Ffull#ref46)). This ability helps them maintain normal livelihoods and avoid falling back into poverty ([Zheng et al., 2023](https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fsustainable-food-systems\u002Farticles\u002F10.3389\u002Ffsufs.2026.1826981\u002Ffull#ref62)). The capability connotation is the intrinsic foundation of livelihood resilience. It highlights the comprehensive measurement of resilience through buffering capacity, self-organization capacity, learning capacity and psychological adaptation ([Gao et al., 2024](https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fsustainable-food-systems\u002Farticles\u002F10.3389\u002Ffsufs.2026.1826981\u002Ffull#ref18)). Buffering capacity refers to farmers’ ability to use their livelihood capital and resour","Frontiers in Sustainable Food Systems","2026-06-09T01:00:00Z","论文",10,false,76,{"impact":17,"substance":18,"depth":19,"authority":20,"freshness":21,"relevant":22,"comment":23},18,22,20,14,2,1,"论文基于江苏微观数据，实证分析数字基础设施对农户生计韧性的U型影响，方法严谨，结论新颖，对数字乡村建设有参考价值，但时效性较低。",[25],{"name":10,"url":6},[27,28,29,30,31],"数字乡村","数字基础设施","生计韧性","U型效应","江苏省",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},"I6","digital-village","数字乡村与数据要素","\u002Ftopic\u002Fdigital-agriculture\u002Fdigital-village","I",[],{"status":40,"locked":14,"version":41,"method":42,"evidence":43},"classified","2026-10-22.2","rules",{"candidates":44,"agricultural_evidence":47},[45,51,58],{"code":33,"score":46,"supported":47,"title":48,"abstract":49,"tags":50},5,true,[],[27],[27,28],{"code":52,"score":53,"supported":47,"title":54,"abstract":55,"tags":57},"B3",3,[],[56],"茶叶",[],{"code":59,"score":53,"supported":47,"title":60,"abstract":61,"tags":63},"G",[],[62],"乡村振兴",[],[65,66],"数字基础设施 数字乡村 生计韧性 U型效应","数字基础设施 数字乡村","数字基础设施数字乡村生计韧性U型效应-1118",4,"10.3389\u002Ffsufs.2026.1826981\u002Ffull","2026-08-30T00:11:11.453594Z",{"total":72,"page":22,"page_size":72,"items":73},6,[74,147,213,281,326,384],{"id":75,"title":76,"url":77,"summary":78,"summary_zh":8,"content":8,"source_name":79,"source_url":8,"published_at":80,"category":12,"cover_url":8,"hotness":13,"is_selected":47,"score":81,"score_detail":82,"sources":87,"tags":89,"primary_topic":93,"secondary_topics":99,"classification":107,"search_phrases":132,"slug":135,"view_count":68,"doi":8,"paper":136,"created_at":146},4194,"数字乡村建设的代价？数字乡村战略对粮食安全和农业碳循环的非对称影响——来自中国的证据","https:\u002F\u002Fideas.repec.org\u002Fa\u002Fspr\u002Fagfoec\u002Fv14y2026i1d10.1186_s40100-026-00503-9.html","Weilong Gao、Qian Zhang、Ying Peng（吉林大学国家发展与安全研究院、大连理工大学商学院、长春工业大学经济管理学院）。发表于Agricultural and Food Economics 2026, 14(1): 1-22。基于989个县和1835户农户的多层次数据，将县级数字乡村发展指数与家庭层面数字采纳指数链接，运用固定效应和两阶段最小二乘法模型。结果显示：农村数字化与粮食产量显著正相关，与农业碳排放显著负相关，但对作物生物量碳吸收或净碳足迹无显著改善。机制分析表明生产收益与土地利用集约化（特别是双季种植扩张）相关，减排与减少劳动力和农药使用一致。异质性分析显示数字基础设施驱动生产率增长，数字治理和数字生活与减排关联更密切。","Agricultural and Food Economics 2026, 14(1)","2026-10-01T00:00:00Z",88,{"impact":18,"substance":83,"depth":84,"authority":20,"freshness":85,"relevant":22,"comment":86},24,19,9,"基于989县1835户的全国性实证研究，揭示数字乡村对粮食安全与农业碳循环的非对称影响，数据规模大、结论有政策参考价值，值得进入每日精选。",[88],{"name":79,"url":77},[27,28,90,91,92],"粮食安全","农业碳排放","农户数字化",{"code":94,"slug":95,"name":96,"path":97,"parent_code":98},"A8","yield-food-security","单产提升与粮食安全","\u002Ftopic\u002Ffield-crops\u002Fyield-food-security","A",[100,106],{"code":101,"slug":102,"name":103,"path":104,"parent_code":105},"H4","carbon","农业碳与绿色低碳","\u002Ftopic\u002Fenvironment\u002Fcarbon","H",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},{"status":40,"locked":14,"version":41,"method":42,"evidence":108},{"candidates":109,"agricultural_evidence":47},[110,117,122,126],{"code":101,"score":17,"supported":47,"title":111,"abstract":113,"tags":116},[112],"农业碳",[114,112,115],"碳排放","碳足迹",[91],{"code":33,"score":118,"supported":47,"title":119,"abstract":120,"tags":121},13,[27],[27],[27,28],{"code":94,"score":85,"supported":47,"title":123,"abstract":124,"tags":125},[90],[],[90],{"code":127,"score":53,"supported":47,"title":128,"abstract":129,"tags":131},"F4",[],[130],"农药",[],[133,134],"数字乡村 粮食安全 农业碳循环","吉林大学 数字乡村 农户","数字乡村粮食安全农业碳循环-4194",{"doi":8,"openalex_id":8,"authors":137,"venue":8,"cited_by_count":138,"oa_url":8,"card":139,"direction":143,"ingested_from":145},[],0,{"tldr":140,"method":141,"finding":142,"direction":143,"opportunity":144},"基于中国县级与农户数据，评估数字乡村战略对粮食安全和农业碳循环的非对称影响。","989县与1835户多层次数据，固定效应和两阶段最小二乘法。","数字化提升粮食产量并减少碳排放，但未改善作物碳吸收或净碳足迹。","数字乡村与农业信息化","可探究数字乡村对碳吸收无显著影响的原因，并优化数字治理以协同减排与固碳。","agent","2026-10-05T00:04:55.880239Z",{"id":148,"title":149,"url":150,"summary":151,"summary_zh":152,"content":8,"source_name":10,"source_url":150,"published_at":153,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":154,"score_detail":155,"sources":157,"tags":159,"primary_topic":163,"secondary_topics":164,"classification":165,"search_phrases":186,"slug":189,"view_count":53,"doi":190,"paper":191,"created_at":212},2759,"Impact of digital infrastructure on agricultural green transformation: theory and China’s experience","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1869475","The digital infrastructure is the core support of promoting rural revitalization and agricultural green transformation. However, the impact and implementation pathways through which digital infrastructure affect the agricultural green transformation remain insufficiently explored and require in-depth empirical investigation. This paper utilizes panel data from Chinese counties spanning 2013 to 2023, treating the pilot policy of digital rural construction as a quasi-natural experiment, and employs a difference-in-differences (DID) model to examine the impact and underlying mechanisms of digital infrastructure on agricultural green transformation. The results indicate that digital infrastructure have a significant positive effect on agricultural green transformation, and this conclusion remains robust across multiple robustness checks. Mechanism analysis indicates that digital infrastructure influences the agricultural green transformation through three primary pathways: facilitating agricultural green technological innovation, improving the resource allocation efficiency, and enhancing the agricultural socialized services. Heterogeneity analysis reveals that the driving effect of digital infrastructure is significant in eastern regions, low-altitude counties, and major grain-producing areas, and the impact in other regions is relatively weak. This paper provides empirical evidence and policy implications for leveraging digital infrastructure to promote the agricultural green transformation.","数字基础设施是推动乡村振兴与农业绿色转型的核心支撑。然而，数字基础设施对农业绿色转型的影响及其实现路径尚缺乏充分探讨，有待深入的实证研究。本文利用2013至2023年中国县域面板数据，将数字乡村建设试点政策视为准自然实验，采用双重差分（DID）模型考察数字基础设施对农业绿色转型的影响及其内在机制。结果表明，数字基础设施对农业绿色转型具有显著正向效应，且该结论在多种稳健性检验下依然成立。机制分析表明，数字基础设施通过三条主要路径影响农业绿色转型：促进农业绿色技术创新、提高资源配置效率以及增强农业社会化服务。异质性分析显示，数字基础设施的驱动效应在东部地区、低海拔县域及粮食主产区显著，而在其他地区影响相对较弱。本文为利用数字基础设施推动农业绿色转型提供了经验证据与政策启示。","2026-09-16T00:00:00Z",84,{"impact":18,"substance":18,"depth":17,"authority":118,"freshness":85,"relevant":22,"comment":156},"基于2013—2023年中国县域面板数据与数字乡村试点准自然实验，实证揭示数字基础设施通过绿色技术创新、资源配置效率和社会化服务三条路径推动农业绿色转型，方法规范、结论可靠，对数字乡村政策具有参考价值。",[158],{"name":10,"url":150},[27,28,160,161,162],"农业绿色转型","农业社会化服务","县域面板数据",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[],{"status":40,"locked":14,"version":41,"method":42,"evidence":166},{"candidates":167,"agricultural_evidence":47},[168,172,178,182],{"code":33,"score":46,"supported":47,"title":169,"abstract":170,"tags":171},[],[27],[27,28],{"code":173,"score":68,"supported":47,"title":174,"abstract":175,"tags":177},"G2",[],[176],"社会化服务",[161],{"code":59,"score":53,"supported":47,"title":179,"abstract":180,"tags":181},[],[62],[],{"code":101,"score":22,"supported":14,"title":183,"abstract":184,"tags":185},[],[],[160],[187,188],"农业社会化服务 农业绿色转型 县域面板数据 数字基础设施","农业社会化服务 农业绿色转型","农业社会化服务农业绿色转型县域面板数据数字基础设施-2759","10.3389\u002Ffsufs.2026.1869475",{"doi":190,"openalex_id":192,"authors":193,"venue":10,"cited_by_count":138,"oa_url":204,"card":205,"direction":209,"ingested_from":211},"W7213421769",[194,197,199,202],{"name":195,"orcid":196},"Guoqun Ma","https:\u002F\u002Forcid.org\u002F0000-0002-9619-8423",{"name":198,"orcid":8},"Qin Su",{"name":200,"orcid":201},"Yan Luo","https:\u002F\u002Forcid.org\u002F0000-0002-9731-4983",{"name":203,"orcid":8},"Wenying Xiao","https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fsustainable-food-systems\u002Farticles\u002F10.3389\u002Ffsufs.2026.1869475\u002Fpdf",{"tldr":206,"method":207,"finding":208,"direction":209,"opportunity":210},"基于中国县域面板数据，用DID模型检验数字基础设施对农业绿色转型的影响与机制。","2013-2023年县域面板数据，数字乡村试点作准自然实验，DID模型。","数字基础设施显著促进农业绿色转型，通过绿色技术创新、资源配置效率、社会化服务三条路径。","农业绿色发展与碳","可探究数字基础设施对农业碳排放与绿色全要素生产率的非线性影响及空间溢出效应。","openalex","2026-09-17T23:30:08.126393Z",{"id":214,"title":215,"url":216,"summary":217,"summary_zh":218,"content":8,"source_name":219,"source_url":216,"published_at":220,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":221,"score_detail":222,"sources":224,"tags":226,"primary_topic":231,"secondary_topics":232,"classification":233,"search_phrases":259,"slug":262,"view_count":138,"doi":263,"paper":264,"created_at":280},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":17,"substance":18,"depth":17,"authority":118,"freshness":85,"relevant":22,"comment":223},"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。",[225],{"name":219,"url":216},[27,227,228,229,230],"数字素养","共同富裕","农民收入","收入不平等",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[],{"status":40,"locked":14,"version":41,"method":42,"evidence":234},{"candidates":235,"agricultural_evidence":47},[236,242,249,254],{"code":33,"score":237,"supported":47,"title":238,"abstract":239,"tags":241},8,[],[27,240],"digital village",[27,227],{"code":243,"score":72,"supported":47,"title":244,"abstract":245,"tags":248},"G6",[],[246,247],"农户收入","rural income",[],{"code":59,"score":53,"supported":47,"title":250,"abstract":251,"tags":253},[],[252],"rural development",[],{"code":255,"score":22,"supported":14,"title":256,"abstract":257,"tags":258},"G4",[],[],[228],[260,261],"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":263,"openalex_id":265,"authors":266,"venue":219,"cited_by_count":138,"oa_url":216,"card":275,"direction":143,"ingested_from":211},"W7223105459",[267,270,273],{"name":268,"orcid":269},"Yong Feng","https:\u002F\u002Forcid.org\u002F0000-0002-8151-8594",{"name":271,"orcid":272},"Shuokai  kai Wang","https:\u002F\u002Forcid.org\u002F0009-0002-7439-1764",{"name":274,"orcid":8},"Fangping Cao",{"tldr":276,"method":277,"finding":278,"direction":143,"opportunity":279},"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":282,"title":283,"url":284,"summary":285,"summary_zh":8,"content":286,"source_name":287,"source_url":8,"published_at":288,"category":289,"cover_url":8,"hotness":13,"is_selected":14,"score":290,"score_detail":291,"sources":295,"tags":297,"primary_topic":302,"secondary_topics":303,"classification":304,"search_phrases":321,"slug":324,"view_count":138,"doi":8,"paper":8,"created_at":325},5505,"广西以赛聚智赋能「AI+农业」 桂字号品牌与东盟水果IP赛道决出","https:\u002F\u002Fwww.agri.cn\u002Fzt\u002Fzhzz\u002Ftp\u002F202610\u002Ft20261019_8877223.htm","10月16日2026年广西智慧农业（数字乡村）创新大赛「桂字号」农业品牌推广赛道、中国（广西）—东盟水果贸易第一IP打造赛道决赛举行，55个项目同台竞技。自治区农业农村厅提出广西正按「北上广研发+广西集成+东盟应用」路径打造中国（广西）—东盟智慧农业先行区，去年一批项目已入选广西人工智能赋能千行百业拟补贴名单。","自治区农业农村厅党组成员、副厅长欧毅霞表示，本次大赛是落实中央一号文件关于因地制宜发展农业新质生产力、大力发展智慧农业部署的具体行动，也是推动人工智能与农业深度融合的重要举措。今年大赛聚焦“桂字号”农业品牌推广和中国（广西）—东盟水果贸易第一IP打造这两个赛道，主要基于三点考虑：一是广西农业资源丰富，“桂字号”品牌基础扎实，但数字化运营和品牌传播仍是短板，需要以赛聚智、以赛促创，借助数字化手段让好产品卖出好价钱；二是广西面向东盟的区位优势得天独厚，水果贸易体量大、潜力足，亟需打造具有国际影响力的第一IP，以数字技术赋能贸易全链条，提升通关、溯源、营销等环节效率；三是这两个赛道切口小、场景实、应用性强，能够有效打通“技术—产业—市场”闭环，推动创新链与产业链精准对接，让更多“金种子”项目在八桂大地上落地生根、开花结果。\n\n欧毅霞提出三点希望：专业组勇当产业升级“领跑者”，形成可复制、可推广的解决方案；学生组争做乡村振兴“生力军”，把创新火花带回课堂、实验室和田间地头；各方共筑智慧农业“生态圈”，推动技术、资本、人才、政策等要素集聚。\n\n广西农业职业技术大学党委书记韦波在致辞中表示，作为承办方，学校将联合广西数字乡村研究院，在赛道组委会统一领导下做好组织、服务与保障，推动赛事成果与教育教学、产业需求有效对接，发挥面向东盟农业职业教育合作优势，为“桂字号”出海、中国—东盟水果贸易双向流通搭建桥梁。\n\n据介绍，广西正按照“北上广研发+广西集成+东盟应用”路径，打造中国（广西）—东盟智慧农业先行区。智慧农业创新大赛不仅是竞技舞台，更是创新成果转化、产业赋能的重要平台。去年，广西首次举办智慧农业创新大赛并取得丰硕成果，一批新技术、新理念、新模式脱颖而出，逐步被大家看见、被市场认可；如捷佳润科技跨境农业智能决策系统、北部湾产权交易所集团AI赋能广西桑蚕茧丝绸全产业链项目入选广西人工智能赋能千行百业拟补贴项目名单；荣获“最佳潜力奖”的“桂鸟先飞—滴滴打药平台”获得地方政府投资扩容实现了升级蝶变。\n\n以赛为媒，向新而行。随着多个项目在决赛中展开比拼，一批聚焦品牌数字化运营、跨境贸易、品控溯源和IP打造的创新项目将在八桂大地加速落地。未来，广西将持续以大赛为纽带，推动技术、资本、人才、政策等要素向智慧农业集聚，促进创新链、产业链、资金链、人才链深度融合，让更多“金种子”项目生根发芽、茁壮成长，为“桂字号”香飘东盟、中国—东盟水果贸易双向流通注入新动能，助力中国（广西）—东盟智慧农业先行区建设迈上新台阶。","中国农业农村信息网 2026-10-19","2026-10-19T00:00:00Z","报道",66,{"impact":17,"substance":292,"depth":20,"authority":293,"freshness":72,"relevant":22,"comment":294},16,12,"省级智慧农业赛事报道，聚焦AI赋能品牌与东盟水果贸易，有具体路径与落地案例，但属活动通稿，时效稍滞后。",[296],{"name":287,"url":284},[27,298,299,300,301],"智慧农业","农业人工智能","桂字号","东盟水果贸易",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[],{"status":40,"locked":14,"version":41,"method":42,"evidence":305},{"candidates":306,"agricultural_evidence":47},[307,312,316],{"code":308,"score":68,"supported":47,"title":309,"abstract":310,"tags":311},"I1",[],[298],[298],{"code":33,"score":68,"supported":47,"title":313,"abstract":314,"tags":315},[],[27],[27],{"code":317,"score":22,"supported":14,"title":318,"abstract":319,"tags":320},"I2",[],[],[299],[322,323],"广西 智慧农业创新大赛","桂字号 东盟水果 IP","广西智慧农业创新大赛-5505","2026-10-22T00:06:58.572242Z",{"id":327,"title":328,"url":329,"summary":330,"summary_zh":331,"content":8,"source_name":332,"source_url":329,"published_at":333,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":334,"score_detail":335,"sources":338,"tags":340,"primary_topic":345,"secondary_topics":346,"classification":347,"search_phrases":362,"slug":365,"view_count":138,"doi":366,"paper":367,"created_at":383},5493,"Mapping Research on the Implementation of Smart Village Policies in Indonesia: A Bibliometric Study for the Years 2017-2025","https:\u002F\u002Fdoi.org\u002F10.66254\u002Fjgssvol5issue2page333-347","This research aims to analyze the role of public sector policies in the development of Smart Villages in Indonesia, focusing on the utilization of information and communication technology (ICT) to improve the quality of life in rural communities. Although the Indonesian government has launched various programs such as the Digital Village Program and Smart City, the implementation of these policies still faces various challenges, including limited infrastructure, low digital literacy, and lack of inter-agency coordination. This research uses a bibliometric approach to map relevant research and policy trends, as well as to identify challenges and opportunities in the development of Smart Villages. The research findings indicate that despite progress, existing public sector policies have not yet been fully effective in addressing the digital divide between villages and cities. This research recommends the need for more inclusive and integrated policy improvements, as well as strengthening human resource capacities in villages to support the creation of sustainable and competitive Smart Villages.","本研究旨在分析公共部门政策在印度尼西亚智慧村（Smart Villages）发展中的作用，重点关注利用信息通信技术（ICT）提升农村社区生活质量。尽管印度尼西亚政府已推出数字村计划（Digital Village Program）和智慧城市（Smart City）等多项举措，但这些政策的实施仍面临诸多挑战，包括基础设施有限、数字素养偏低以及跨机构协调不足。本研究采用文献计量学方法，梳理相关研究与政策趋势，并识别智慧村发展中的挑战与机遇。研究结果表明，尽管取得了一定进展，现有公共部门政策在弥合城乡数字鸿沟方面尚未充分发挥效用。本研究建议有必要进行更具包容性和整合性的政策改进，同时加强农村人力资源能力建设，以支持创建可持续且具有竞争力的智慧村。","Journal of Government Science Studies\u002FJournal Of Government Science Studies","2026-10-20T00:00:00Z",71,{"impact":292,"substance":17,"depth":336,"authority":118,"freshness":85,"relevant":22,"comment":337},15,"该文献计量研究系统梳理了印尼智慧乡村政策实施进展与数字鸿沟挑战，对数字乡村国际比较有参考价值，但属区域性研究，影响层级有限。",[339],{"name":332,"url":329},[27,341,342,343,344],"印尼","数字鸿沟","文献计量","智慧乡村",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[],{"status":40,"locked":14,"version":41,"method":42,"evidence":348},{"candidates":349,"agricultural_evidence":47},[350,356],{"code":351,"score":336,"supported":47,"title":352,"abstract":354,"tags":355},"I7",[353],"bibliometric",[343,353],[343],{"code":33,"score":357,"supported":47,"title":358,"abstract":359,"tags":361},11,[],[342,240,360],"digital divide",[27,342],[363,364],"印尼 智慧乡村","印尼 数字村 数字鸿沟","印尼智慧乡村-5493","10.66254\u002Fjgssvol5issue2page333-347",{"doi":366,"openalex_id":368,"authors":369,"venue":332,"cited_by_count":138,"oa_url":329,"card":378,"direction":143,"ingested_from":211},"W7223067869",[370,372,375],{"name":371,"orcid":8},"Syaifulrijal Mahulauw",{"name":373,"orcid":374},"Wahab Tuanaya","https:\u002F\u002Forcid.org\u002F0009-0001-9236-8149",{"name":376,"orcid":377},"Marno Wance","https:\u002F\u002Forcid.org\u002F0000-0001-6663-7598",{"tldr":379,"method":380,"finding":381,"direction":143,"opportunity":382},"用文献计量法梳理2017-2025年印尼智慧村政策实施研究，识别挑战与机会。","文献计量分析，覆盖2017-2025年相关文献与政策趋势。","政策尚未有效弥合城乡数字鸿沟，需更包容整合的政策与人力建设。","可延伸至跨国比较或政策效果量化评估，聚焦数字鸿沟与跨部门协同机制。","2026-10-21T23:30:33.962760Z",{"id":385,"title":386,"url":387,"summary":388,"summary_zh":389,"content":8,"source_name":10,"source_url":387,"published_at":333,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":390,"score_detail":391,"sources":394,"tags":396,"primary_topic":401,"secondary_topics":402,"classification":403,"search_phrases":428,"slug":431,"view_count":138,"doi":432,"paper":433,"created_at":446},5469,"How institutional digitalization reshapes entrepreneurial activity in new agricultural business forms: quasi-natural experimental evidence from China's Digital Village Pilot Policy","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1946061","New agricultural business forms are a key driving force for developing countries to overcome the constraints of traditional agriculture and achieve sustainability in food systems. However, it remains unclear whether institutional digitalization can effectively stimulate entrepreneurial vitality in new agricultural business forms. This study develops a theoretical framework of “opportunity creation–opportunity identification–opportunity transformation” and treats China's Digital Village Pilot Policy (DVPP), implemented in 2020, as a quasi-natural experiment. Based on panel data from 1,743 counties in China from 2014 to 2023, this study employs Double Machine Learning (DML) and Spatial Durbin Difference-in-Differences (SDM-DID) models, among other methods, to systematically identify the impact, transmission mechanisms, heterogeneous effects, and spatial spillover effects of institutional digitalization on Entrepreneurial Activity in New Agricultural Business Forms (EANA). The results reveal that: (1) DVPP significantly enhances EANA, and this finding remains robust after a series of tests, including placebo tests, Propensity Score Matching–Difference-in-Differences (PSM-DID), Synthetic Control Method–Difference-in-Differences (SCM-DID), and instrumental variable (IV) estimation; (2) agricultural technological innovation, digital infrastructure development, and digital financial development serve as mediating mechanisms; (3) the policy effects are more pronounced in counties with higher levels of digital access, better-developed transportation infrastructure, and higher levels of digital financial development, exhibiting a pattern of Central > Western > Eastern regions, and are significantly stronger in areas with advantages in characteristic agricultural products; (4) DVPP generates a significant negative spatial spillover effect on EANA in neighboring counties. This study expands theoretical understanding of the relationship between institutional digitalization and entrepreneurship in new agricultural business forms and provides empirical evidence for China and other developing countries to optimize digital rural development and foster new agricultural business forms.","农业新业态是发展中国家突破传统农业约束、实现食物系统可持续发展的关键驱动力。然而，制度数字化能否有效激发农业新业态的创业活力仍不明确。本研究构建了“机会创造—机会识别—机会转化”的理论框架，并将中国2020年实施的数字乡村试点政策（Digital Village Pilot Policy，DVPP）视为准自然实验。基于中国1743个县2014—2023年的面板数据，本研究采用双重机器学习（Double Machine Learning，DML）和空间杜宾双重差分（Spatial Durbin Difference-in-Differences，SDM-DID）等模型，系统识别制度数字化对农业新业态创业活动（Entrepreneurial Activity in New Agricultural Business Forms，EANA）的影响、传导机制、异质性效应和空间溢出效应。结果表明：（1）DVPP显著提升了EANA，且该结论在经过安慰剂检验、倾向得分匹配—双重差分（PSM-DID）、合成控制法—双重差分（SCM-DID）和工具变量（IV）估计等一系列检验后依然稳健；（2）农业技术创新、数字基础设施建设和数字金融发展发挥中介机制作用；（3）政策效应在数字接入水平较高、交通基础设施较完善和数字金融发展水平较高的县更为显著，呈现出中部>西部>东部的格局，且在特色农产品优势区显著更强；（4）DVPP对邻近县的EANA产生显著的负向空间溢出效应。本研究拓展了关于制度数字化与农业新业态创业之间关系的理论认识，为中国及其他发展中国家优化数字乡村发展、培育农业新业态提供了经验证据。",85,{"impact":18,"substance":392,"depth":17,"authority":118,"freshness":85,"relevant":22,"comment":393},23,"基于1743个县面板数据的准自然实验，方法扎实、结论有政策参考价值，值得进入每日精选。",[395],{"name":10,"url":387},[397,27,398,399,400],"数字农业","县域经济","农业政策","农村创业",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[],{"status":40,"locked":14,"version":41,"method":42,"evidence":404},{"candidates":405,"agricultural_evidence":47},[406,410,416,420,424],{"code":33,"score":336,"supported":47,"title":407,"abstract":408,"tags":409},[240],[27,240],[27],{"code":317,"score":72,"supported":47,"title":411,"abstract":412,"tags":415},[],[413,414],"机器学习","machine learning",[],{"code":59,"score":53,"supported":47,"title":417,"abstract":418,"tags":419},[],[252],[],{"code":255,"score":21,"supported":14,"title":421,"abstract":422,"tags":423},[],[],[400,398],{"code":308,"score":22,"supported":14,"title":425,"abstract":426,"tags":427},[],[],[397],[429,430],"数字乡村试点 新农业业态","DVPP 农村创业","数字乡村试点新农业业态-5469","10.3389\u002Ffsufs.2026.1946061",{"doi":432,"openalex_id":434,"authors":435,"venue":10,"cited_by_count":138,"oa_url":387,"card":441,"direction":143,"ingested_from":211},"W7223041086",[436,438],{"name":437,"orcid":8},"Su Li",{"name":439,"orcid":440},"Changjun Yang","https:\u002F\u002Forcid.org\u002F0009-0000-6236-3489",{"tldr":442,"method":443,"finding":444,"direction":143,"opportunity":445},"用双重机器学习与空间DID评估数字乡村试点政策对新农业业态创业活力的影响。","基于1743县2014-2023面板数据，用DML与SDM-DID做准自然实验。","试点政策显著提升新农业业态创业，经技术创新、数字基建与数字金融中介，并对邻县有负向溢出。","可探究政策负向空间溢出的形成机制及跨县协同激励设计，避免创业资源虹吸。","2026-10-21T23:30:07.205317Z"]