[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-791":3,"related-791":92},{"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":86,"slug":89,"view_count":90,"doi":8,"paper":8,"created_at":91},791,"数字乡村发展与牧户非农就业:来自甘青川藏26县2790户牧户调查的证据(原标题:From Grasslands to Markets: Digital Rural Development and Herders' Non-Farm Employment)","https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8503","兰州大学草地农业生态系统国家重点实验室吴忠安等团队基于2023-2025年甘青川藏26县2790户牧户调查数据,考察县级数字乡村发展与牧户非农就业关系。研究发现数字乡村发展与户主主要从事非农就业的可能性正相关,在系列稳健性和内生性检验后结果稳定;在第一产业基础较大的地区以及从事饲草种植的牧户中,正向关联较弱,表明当地生产结构和家庭劳动配置制约了数字机会向就业多元化转化。进一步分析表明数字金融和数字消费是数字乡村发展支持非农就业的两种潜在渠道。研究强调牧区就业收益既取决于数字接入,又取决于家庭劳动配置灵活性及非农机会可得性。",null,"Logical Operator Operator\n\nSearch Text\n\nSearch Type\n\n_add\\_circle\\_outline_\n\n_remove\\_circle\\_outline_\n\n[![Image 1: sustainability-logo](https:\u002F\u002Fpub.mdpi-res.com\u002Fimg\u002Fjournals\u002Fsustainability-logo.png?3798e4e58c765aed)](https:\u002F\u002Fwww.mdpi.com\u002Fjournal\u002Fsustainability)\n\n## Article Menu\n\nFont Type:\n\n_Arial_ _Georgia_ _Verdana_\n\nFont Size:\n\nAa Aa Aa\n\nLine Spacing:\n\n__ __ __\n\nColumn Width:\n\n__ __ __\n\nBackground:\n\nOpen Access Article\n\nby \nZhongan Wu\n\n *[](mailto:wuzha2023@lzu.edu.cn), \nToba Stephen Olasehinde\n\n and \nYubing Fan\n\nState Key Laboratory of Herbage Improvement and Grassland Agro-Ecosystems, Chinese Grass Industry Development Strategy Research Center, College of Pastoral Agriculture Science and Technology, Lanzhou University, Lanzhou 730020, China\n\n*\n\nAuthor to whom correspondence should be addressed.\n\nSubmission received: 3 July 2026 \u002F Revised: 11 August 2026 \u002F Accepted: 12 August 2026 \u002F Published: 19 August 2026\n\n## Abstract\n\nAlthough natural resources and geographical factors limit herders’ employment options, the development of digital rural helps herding households compete on an equal footing by expanding employment opportunities. Using survey data collected from 2790 herder households in 26 counties across Gansu, Qinghai, Sichuan and Tibet from 2023 to 2025, this study examines the relationship between county-level digital rural development and non-farm employment. We find that digital rural development is positively associated with the likelihood that household heads engage primarily in non-farm employment. This finding remains stable across a series of robustness and endogeneity checks. Moreover, the positive association is weaker in areas with a larger primary-industry base and among households engaged in forage cultivation, suggesting that local production structures and household labor commitments constrain the conversion of digital opportunities into employment diversification. Further analysis indicates that digital finance and digital consumption are two potential channels through which digital rural development supports non-farm employment. These findings highlight that the employment benefits of digital development depend not only on digital access but also on the flexibility of household labor allocation and the availability of non-farm opportunities in pastoral areas.\n\n## 1. Introduction\n\nArtificial intelligence, Big Data, and mobile internet are examples of digital technology that are spreading to all parts of the economy and society, changing how production is organized and people work [[1](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8503#B1-sustainability-18-08503)]. Given the above, China released the Digital Rural Development Plan in 2018 to promote the construction of a digital rural society and rural revitalization. As 5G networks expand into rural and pastoral areas, the all-weather demonstration project for e-commerce in rural areas continues to advance, and the coverage of digital inclusive finance is gradually expanding. At the same time, digital infrastructure and services are being rolled out in the grassland region at an ever-increasing rate [[2](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8503#B2-sustainability-18-08503)]. However, because of their remote areas, fragile ecosystems and unique cultures, these large pastoral areas have been lacking in development resources for a long time. Traditional livestock farming is limited by the productivity of natural grasslands, ecological red lines and fluctuations in market prices, and a single grazing-based livelihood model cannot provide stable income growth for herder households [[3](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8503#B3-sustainability-18-08503)]. Therefore, expanding non-farm employment opportunities and promoting the transfer of the pastoral workforce to the secondary and tertiary sectors are urgently needed to consolidate the results of poverty alleviation and prevent a relapse into poverty, as well as to achieve all-round rejuvenation of pastoral areas.\n\nNon-farm employment provides herder households with an alternative to relying entirely on traditional livestock production. This resulting income mix can reduce exposure to livestock losses and strengthen resilience to market, climatic and health shocks [[4](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8503#B4-sustainability-18-08503)]. Especially against the backdrop of increasing resource and environmental constraints in pastoral areas and shrinking growth prospects for traditional livestock farming, promoting the rational flow of labor into non-farm sectors is not only a practical necessity for herding households to enhance the resilience of their livelihoods, but also a key direction for industrial restructuring and socioeconomic transformation in pastoral areas. However, the formation of non-farm employment is not simply a matter of individual choice, as herders’ decision-making is influenced by a range of factors, including their ability to access information, job search costs, financial constraints, and the extent of market access [[5](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8503#B5-sustainability-18-08503),[6](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8503#B6-sustainability-18-08503)]. The reason why the development of digital rural may have an impact on herders’ non-farm employment is that it can, to some extent, alleviate these constraints.\n\nExisting research has provided a wealth of discussion on the relationship between the digital economy, information and communication technologies, and rural labor migration, as well as the growth of farm household income [[7](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8503#B7-sustainability-18-08503),[8](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8503#B8-sustainability-18-08503),[9](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8503#B9-sustainability-18-08503),[10](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8503#B10-sustainability-18-08503)]. A large body of the literature indicates that digital development can improve the information environment, expand market access, alleviate financial exclusion, and, to some extent, facilitate the shift in rural labor toward the non-farm sector [[11](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8503#B11-sustainability-18-08503),[12](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8503#B12-sustainability-18-08503),[13](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8503#B13-sustainability-18-08503)]. Some studies have also indicated that the development of internet usage, digital finance, and e-commerce has a positive impact on farmers’ non-farm employment, entrepreneurial activities, and income growth [[14](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8503#B14-sustainability-18-08503),[15](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8503#B15-sustainability-18-08503),[16](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8503#B16-sustainability-18-08503),[17](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8503#B17-sustainability-18-08503)]. More broadly, infrastructure development and technological progress can promote economic diversification and strengthen livelihood resilience in peripheral and resource-dependent regions [[18](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8503#B18-sustainability-18-08503)]. In terms of research subjects, most of the existing studies have focused on farmers and have paid relatively little attention to herders, another group in pastoral areas. Herders’ employment decisions are influenced by the general labor market, but they are also restricted by other factors, such as grassland management systems, livestock production cycles, household livestock assets and grazing practices; therefore, their non-farm employment behavior is relatively context-specific and constrained [[19](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8503#B19-sustainability-18-08503),[20](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8503#B20-sustainability-18-08503)]. Most studies have focused on the general inclusive benefits of digital technology for research, but there is a lack of specific research on how digital rural initiatives operate in the particular spatial conditions of pastoral areas and whether their effects differ among different groups and regions.\n\nThis paper takes as its focus the non-farm employment of herders and studies the effect of digital rural development on the transformation of herders’ employment, as well as the mechanisms through which this change occurs. Based on this, this paper seeks to answer the following questions: can digital rural development promote non-farm employment among herders?; through what mechanisms does it primarily achieve this?; and does this impact vary depending on individual characteristics, spatial conditions, and the level of development in each county? This study makes three contributions. First, it conceptualizes digital rural development in pastoral areas as a mechanism for translating digital access into non-farm employment opportunities, emphasizing the role of household labor constraints in livestock-based livelihoods. In doing so, it extends the literature on digital rural development and labor transition by showing that improved digital access does not automatically lead to labor reallocation, because pastoral production commitments may constrain herders’ ability to respond to new employment opportunities. Second, it integrates survey data from 2790 herding households across Gansu, Qinghai, Sichuan, and Tibet, with a county-level Digital Rural Development Index, providing evidence from underrepresented pastoral production systems. Third, it examines how structural and household-level conditions shape the relationship between digital rural development and non-farm employment, highlighting the importance of contextual heterogeneity in pastoral regions. By linking digital development with livelihood diversification, the study also contributes to the rural sustainability literature by showing that the employment benefits of digitalization depend on household labor flexibility and local economic conditions.\n\n## 2. Theoretical Framework\n\n### 2.1. Direct Effects of Digital Rural Development on Herders’ Non-Farm Employment\n\nCompared to typical rural areas, pastoral regions face long-standing constraints such as geographical dispersion, poor transportation, limited access to information and insufficient market access. As a result, employment options for herding households are often confined to traditional livestock farming. Access to non-farm employment depends largely on personal network or occasional face-to-face contact [[21](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8503#B21-sustainability-18-08503)]. In light of the above, the construction of an information infrastructure, the extension of platform coverage and the broad application of digital tools in the development of digital rural have created new employment opportunities for herders outside of traditional sectors.\n\nAccording to the theory of information asymmetry, if market participants cannot obtain the required information in time and to their full satisfaction, they will bear a higher search cost, be less efficient in matching, and thus lose opportunities in their decision-making [[22](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8503#B22-sustainability-18-08503),[23](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8503#B23-sustainability-18-08503)]. The development of digital rural is changing how herders get jobs and market information. New technologies are now available to help herders stay informed about new employment prospects outside farming, wage levels, working locations and required skills [[24](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8503#B24-sustainability-18-08503)]. In this way, information barriers between herders and the outside labor market have been reduced. Thus, employment information is no longer scarce and fragmented, but rather open and accessible. As a result, herders’ awareness of non-farm employment and their opportunities for employment have significantly increased [[25](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8503#B25-sustainability-18-08503)].\n\nAs is well-known, non-farm employment not only involves the movement of labor across sectors, but also entails costs associated with information search, transportation, payment settlements and job matching. Transaction cost theory suggests that improvements in market efficiency depend largely on reductions in transaction costs [[26](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8503#B26-sustainability-18-08503),[27](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8503#B27-sustainability-18-08503)]. The development of digital rural has reduced the time costs, communication costs, and institutional friction faced by herders when seeking non-farm employment through information dissemination, digital payments and platform integration. Looking further, improvements in the information environment and reductions in transaction costs do not stop at the level of access to employment opportunities. Rather, they continue to influence labor allocation within herding households. In this context, non-farm employment reflects the reallocation of household labor from livestock production to non-farm sector [[28](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8503#B28-sustainability-18-08503),[29](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8503#B29-sustainability-18-08503)]. Consequently, household labor may gradually shift away from traditional livestock production toward a wider range of market-based non-farm activities. In light of the above, this paper proposes the following hypothesis:\n\n**H1.**\n\nDigital rural development is positively associated with household non-farm employment.\n\n### 2.2. Boundary Conditions of the Employment Effects of Digital Rural Development\n\nDigital rural development can improve information access, reduce job-search costs, and strengthen links to external markets. Nevertheless, these improvements do not automatically generate non-farm employment. Whether herders convert digital opportunities into employment also depends on local industrial structure and household production systems. We therefore examine the moderating roles of primary-industry development and forage cultivation.\n\nStructural transformation involves the reallocation of labor from primary production toward secondary and tertiary activities [[30](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8503#B30-sustainability-18-08503)]. Primary-industry value added at the county level measures the absolute scale of agricultural and livestock output, rather than the sector’s share of the local economy or its relative return. A higher value may nevertheless indicate a larger agricultural and livestock production base. In such counties, digital tools may be used more extensively for production management, input procurement and product marketing within the primary sector [[31](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8503#B31-sustainability-18-08503)]. Digitalization may lower search, matching, and market-access costs while also improving production within the primary sector. Where digital services are used mainly for production management and product marketing, these benefits may be absorbed within agricultural and pastoral activities rather than translated into labor reallocation [[32](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8503#B32-sustainability-18-08503)]. The positive association between digital rural development and herders’ participation in non-farm employment may therefore be weaker in counties with a larger primary industry base. We propose:\n\n**H2a.**\n\nHigher primary industry value added in a county weakens the positive association between digital rural development and household non-farm employment.\n\nForage cultivation is closely integrated with livestock production and requires labor for planting, management, harvesting, transport and storage [[33](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8503#B33-sustainability-18-08503)]. These tasks increase household labor demands, particularly during busy seasons. With limited household labor, forage cultivation may reduce the time available for non-farm employment [[34](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8503#B34-sustainability-18-08503)]. It also binds cropland, forage, livestock and family labor into a more integrated production system. Households may therefore have less flexibility to act on digital employment information and market opportunities.\n\n**H2b.**\n\nForage cultivation weakens the positive association between digital rural development and household non-farm employment.\n\n### 2.3. Transmission Mechanisms of Digital Rural Development\n\nIn most cases, funding is a key factor limiting herders’ ability to engage in any activities. Continuing livestock production, starting a business, and seeking employment elsewhere may all require financial resources, while reliable payment services can facilitate related transactions [[35](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8503#B35-sustainability-18-08503),[36](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8503#B36-sustainability-18-08503)]. However, due to factors such as remote locations, a lack of financial service outlets and exclusion from the traditional financial system, herders have long faced challenges in accessing financial services [[37](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8503#B37-sustainability-18-08503)]. The development of digital rural has driven the shift in financial services toward online, convenient and grassroots-level delivery, providing herders with more accessible channels for payments, credit and financial services. The expansion of financial services to grassroots levels represents not only an increase in the scale of financial operations but also an extension of service coverage and an improvement in the efficiency of resource allocation. Digital rural development can facilitate the expansion of digital finance. Greater access to digital financial services may ease the credit and liquidity constraints faced by herding households. This, in turn, can lower the financial barriers to participation in non-farm employment and entrepreneurial activities [[38](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8503#B38-sustainability-18-08503)]. At the same time, development of digital finance has reduced the transaction costs for labor transfer and provided a relatively easy way for herders to access external labor markets [[39](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8503#B39-sustainability-18-08503)]. Therefore, the development of digital rural areas should not only increase the supply of financial products but also improve the financial situation for herders’ non-market activities at a deeper level and enhance their ability to engage in non-farm employment. Based on the above analysis, this study puts forward the following hypothesis:\n\n**H3.**\n\nDigital rural development promotes herders’ non-farm employment by expanding digital finance.\n\nWith the spread of online shopping, digital payments, and platform services, herding households have become more closely connected to digital markets. These developments have changed how households purchase goods, make payments, and access consumer services [[40](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8503#B40-sustainability-18-08503)].\n\nThe shift in consumption patterns is not merely a change in lifestyle. It also influences household employment choices through adjustments in income needs and labor allocation. Traditional herding households often rely on self-produced goods and local supplies. Digital rural development has expanded their access to external markets. Their consumption may therefore become more dependent on purchased goods and services. While households now have a wider range of choices regarding goods and services, they also have a greater need for a stable cash flow to support these choices [[41](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8503#B41-sustainability-18-08503)]. The increase in digital consumption suggests that more money will be needed by households. As a result, there has been a change in demand for labor, and many people have begun to leave traditional pastoralism for non-agricultural work in search of a more stable in","MDPI Sustainability 18(16):8503 2026-08-19","2026-08-19T00:00:00Z","论文",10,false,81,{"impact":17,"substance":18,"depth":19,"authority":20,"freshness":21,"relevant":22,"comment":23},18,22,20,13,8,1,"基于2790户牧户调查的实证研究，揭示数字乡村对非农就业的促进作用及条件，数据详实，结论可靠，对牧区数字乡村政策有参考价值。",[25],{"name":10,"url":6},[27,28,29,30,31],"数字乡村","Sustainability","数字金融","非农就业","牧户",{"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},[45,51,57,64,70,76,81],{"code":33,"score":46,"supported":47,"title":48,"abstract":49,"tags":50},12,true,[27],[27],[27],{"code":52,"score":21,"supported":47,"title":53,"abstract":55,"tags":56},"G",[54],"rural development",[],[],{"code":58,"score":59,"supported":47,"title":60,"abstract":61,"tags":63},"C4",3,[],[62],"饲草",[],{"code":65,"score":59,"supported":47,"title":66,"abstract":67,"tags":69},"F5",[],[68],"农机",[],{"code":71,"score":59,"supported":47,"title":72,"abstract":73,"tags":75},"H6",[],[74],"农业生态",[],{"code":77,"score":22,"supported":14,"title":78,"abstract":79,"tags":80},"G3",[],[],[29],{"code":82,"score":22,"supported":14,"title":83,"abstract":84,"tags":85},"G6",[],[],[30],[87,88],"数字乡村 数字金融 非农就业 牧户","数字乡村 数字金融","数字乡村数字金融非农就业牧户-791",5,"2026-08-21T00:05:57.571383Z",{"total":93,"page":22,"page_size":93,"items":94},6,[95,169,231,275,333,395],{"id":96,"title":97,"url":98,"summary":99,"summary_zh":100,"content":8,"source_name":101,"source_url":98,"published_at":102,"category":12,"cover_url":8,"hotness":13,"is_selected":47,"score":103,"score_detail":104,"sources":111,"tags":113,"primary_topic":117,"secondary_topics":118,"classification":119,"search_phrases":145,"slug":148,"view_count":59,"doi":149,"paper":150,"created_at":168},3336,"Prosper or beggar thy neighbor? non-farm employment effects and spatial spillovers of China's National Digital Village Pilot Program","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1950504","Introduction Counties are a key spatial unit linking cities and villages in China's rural transformation, yet many still lack the industrial base, market scale, and non-farm job opportunities needed to absorb rural labor. This study examines whether China's National Digital Village Pilot Program expands rural non-farm employment and whether its effects extend beyond pilot counties. Methods Using a panel of 1,450 Chinese counties and 24,111 county-year observations from 2007 to 2024, this study exploits the staggered implementation of the 2020 and 2024 pilot cohorts as a quasi-natural experiment. The policy effect is estimated using a multi-period difference-in-differences model and cross-validated with stacked DID and the Callaway-Sant'Anna estimator. Robustness is further assessed through propensity score matching, inverse probability weighting, entropy balancing, placebo tests, and alternative samples and specifications. Transmission channels, heterogeneity, and spatial effects are also examined. Results The National Digital Village Pilot Program increased rural non-farm employment in pilot counties by approximately 25% relative to non-pilot counties, and the result remains robust across alternative identification and estimation strategies. The two-step transmission-channel analysis provides evidence consistent with two potential channels: enhanced county-level innovation and improved mobile network access capability. The policy effect is significantly stronger in central-region counties than in western counties and stronger in smaller counties than in larger ones, with weaker evidence of a larger effect in counties with lower human capital. Spatial analysis shows a positive direct effect on pilot counties but a negative spillover effect on neighboring counties. Discussion The findings indicate that digital village development can strengthen local non-farm employment absorption, but part of the local gain may reflect a spatial reallocation of economic activity rather than net regional job creation. Effective implementation therefore requires not only county-level digital development but also cross-county resource coordination and regional policy integration.","引言 县域是中国城乡转型中连接城市与乡村的关键空间单元，但许多县域仍缺乏吸纳农村劳动力所需的产业基础、市场规模和非农就业机会。本研究考察中国国家数字乡村试点项目是否扩大了农村非农就业，以及其效应是否超出试点县范围。方法 本研究使用2007年至2024年间1，450个中国县域、24，111个县—年观测值的面板数据，将2020年和2024年试点批次的分批实施作为准自然实验。政策效应采用多期双重差分模型估计，并通过堆叠双重差分和Callaway-Sant'Anna估计量进行交叉验证。稳健性进一步通过倾向得分匹配、逆概率加权、熵平衡、安慰剂检验以及替代样本和设定加以评估。研究还考察了传导渠道、异质性和空间效应。结果 国家数字乡村试点项目使试点县的农村非农就业相对于非试点县增加了约25%，且该结果在替代性识别和估计策略下保持稳健。两步传导渠道分析提供的证据与两个潜在渠道相一致：县域创新能力增强和移动网络接入能力改善。政策效应在中部地区县域显著强于西部地区县域，在较小县域强于较大县域，而在人力资本较低县域效应更大的证据较弱。空间分析显示，政策对试点县具有正向直接效应，但对邻近县域产生负向溢出效应。讨论 研究结果表明，数字乡村发展能够增强本地非农就业吸纳能力，但部分本地收益可能反映的是经济活动的空间再配置，而非区域净就业创造。因此，有效实施不仅需要县域层面的数字发展，还需要跨县域资源协调和区域政策整合。","Frontiers in Sustainable Food Systems","2026-09-23T00:00:00Z",89,{"impact":105,"substance":106,"depth":107,"authority":108,"freshness":109,"relevant":22,"comment":110},24,23,19,14,9,"基于1450个县2007-2024年面板数据的准自然实验研究，证实数字乡村试点使县域非农就业提升约25%，但存在对邻县的负向溢出，对政策协调具有实质参考价值。",[112],{"name":101,"url":98},[27,114,115,116,30],"空间溢出","县域经济","数字乡村试点",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[],{"status":40,"locked":14,"version":41,"method":42,"evidence":120},{"candidates":121,"agricultural_evidence":47},[122,128,136,141],{"code":33,"score":123,"supported":47,"title":124,"abstract":126,"tags":127},16,[125],"digital village",[27,125],[27,116],{"code":129,"score":130,"supported":47,"title":131,"abstract":132,"tags":135},"I4",7,[],[133,134],"空间分析","spatial analysis",[114],{"code":137,"score":22,"supported":14,"title":138,"abstract":139,"tags":140},"G4",[],[],[115],{"code":82,"score":22,"supported":14,"title":142,"abstract":143,"tags":144},[],[],[30],[146,147],"国家数字乡村试点 非农就业","县域 数字乡村 空间溢出","国家数字乡村试点非农就业-3336","10.3389\u002Ffsufs.2026.1950504",{"doi":149,"openalex_id":151,"authors":152,"venue":101,"cited_by_count":160,"oa_url":98,"card":161,"direction":165,"ingested_from":167},"W7214093544",[153,156,158],{"name":154,"orcid":155},"Wei Yang","https:\u002F\u002Forcid.org\u002F0000-0002-0540-5934",{"name":157,"orcid":8},"Lijun Wang",{"name":159,"orcid":8},"Yizhuo Ma",0,{"tldr":162,"method":163,"finding":164,"direction":165,"opportunity":166},"评估国家数字乡村试点对县域非农就业的影响及空间溢出效应。","2007-2024年1450个县面板数据，多期DID与Callaway-Sant","试点县非农就业增约25%，但邻县出现负向溢出，部分为就业空间再分配。","数字乡村与农业信息化","可探究数字乡村试点的跨县协同机制与负溢出治理，及不同区域差异化政策设计。","openalex","2026-09-24T23:30:07.434384Z",{"id":170,"title":171,"url":172,"summary":173,"summary_zh":174,"content":8,"source_name":28,"source_url":172,"published_at":175,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":176,"score_detail":177,"sources":179,"tags":181,"primary_topic":186,"secondary_topics":187,"classification":188,"search_phrases":209,"slug":212,"view_count":160,"doi":213,"paper":214,"created_at":230},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。","2026-10-21T00:00:00Z",80,{"impact":17,"substance":18,"depth":17,"authority":20,"freshness":109,"relevant":22,"comment":178},"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。",[180],{"name":28,"url":172},[27,182,183,184,185],"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":189},{"candidates":190,"agricultural_evidence":47},[191,195,201,205],{"code":33,"score":21,"supported":47,"title":192,"abstract":193,"tags":194},[],[27,125],[27,182],{"code":82,"score":93,"supported":47,"title":196,"abstract":197,"tags":200},[],[198,199],"农户收入","rural income",[],{"code":52,"score":59,"supported":47,"title":202,"abstract":203,"tags":204},[],[54],[],{"code":137,"score":22,"supported":14,"title":206,"abstract":207,"tags":208},[],[],[183],[210,211],"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":213,"openalex_id":215,"authors":216,"venue":28,"cited_by_count":160,"oa_url":172,"card":225,"direction":165,"ingested_from":167},"W7223105459",[217,220,223],{"name":218,"orcid":219},"Yong Feng","https:\u002F\u002Forcid.org\u002F0000-0002-8151-8594",{"name":221,"orcid":222},"Shuokai  kai Wang","https:\u002F\u002Forcid.org\u002F0009-0002-7439-1764",{"name":224,"orcid":8},"Fangping Cao",{"tldr":226,"method":227,"finding":228,"direction":165,"opportunity":229},"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":232,"title":233,"url":234,"summary":235,"summary_zh":8,"content":236,"source_name":237,"source_url":8,"published_at":238,"category":239,"cover_url":8,"hotness":13,"is_selected":14,"score":240,"score_detail":241,"sources":243,"tags":245,"primary_topic":250,"secondary_topics":251,"classification":252,"search_phrases":270,"slug":273,"view_count":160,"doi":8,"paper":8,"created_at":274},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":123,"depth":108,"authority":46,"freshness":93,"relevant":22,"comment":242},"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。",[244],{"name":237,"url":234},[27,246,247,248,249],"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":253},{"candidates":254,"agricultural_evidence":47},[255,261,265],{"code":256,"score":257,"supported":47,"title":258,"abstract":259,"tags":260},"I1",4,[],[246],[246],{"code":33,"score":257,"supported":47,"title":262,"abstract":263,"tags":264},[],[27],[27],{"code":266,"score":22,"supported":14,"title":267,"abstract":268,"tags":269},"I2",[],[],[247],[271,272],"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":276,"title":277,"url":278,"summary":279,"summary_zh":280,"content":8,"source_name":281,"source_url":278,"published_at":282,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":283,"score_detail":284,"sources":287,"tags":289,"primary_topic":294,"secondary_topics":295,"classification":296,"search_phrases":311,"slug":314,"view_count":160,"doi":315,"paper":316,"created_at":332},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":123,"substance":17,"depth":285,"authority":20,"freshness":109,"relevant":22,"comment":286},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。",[288],{"name":281,"url":278},[27,290,291,292,293],"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":297},{"candidates":298,"agricultural_evidence":47},[299,305],{"code":300,"score":285,"supported":47,"title":301,"abstract":303,"tags":304},"I7",[302],"bibliometric",[292,302],[292],{"code":33,"score":306,"supported":47,"title":307,"abstract":308,"tags":310},11,[],[291,125,309],"digital divide",[27,291],[312,313],"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":315,"openalex_id":317,"authors":318,"venue":281,"cited_by_count":160,"oa_url":278,"card":327,"direction":165,"ingested_from":167},"W7223067869",[319,321,324],{"name":320,"orcid":8},"Syaifulrijal Mahulauw",{"name":322,"orcid":323},"Wahab Tuanaya","https:\u002F\u002Forcid.org\u002F0009-0001-9236-8149",{"name":325,"orcid":326},"Marno Wance","https:\u002F\u002Forcid.org\u002F0000-0001-6663-7598",{"tldr":328,"method":329,"finding":330,"direction":165,"opportunity":331},"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":334,"title":335,"url":336,"summary":337,"summary_zh":338,"content":8,"source_name":101,"source_url":336,"published_at":282,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":339,"score_detail":340,"sources":342,"tags":344,"primary_topic":348,"secondary_topics":349,"classification":350,"search_phrases":376,"slug":379,"view_count":160,"doi":380,"paper":381,"created_at":394},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":106,"depth":17,"authority":20,"freshness":109,"relevant":22,"comment":341},"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。",[343],{"name":101,"url":336},[345,27,115,346,347],"数字农业","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":351},{"candidates":352,"agricultural_evidence":47},[353,357,363,367,372],{"code":33,"score":285,"supported":47,"title":354,"abstract":355,"tags":356},[125],[27,125],[27],{"code":266,"score":93,"supported":47,"title":358,"abstract":359,"tags":362},[],[360,361],"机器学习","machine learning",[],{"code":52,"score":59,"supported":47,"title":364,"abstract":365,"tags":366},[],[54],[],{"code":137,"score":368,"supported":14,"title":369,"abstract":370,"tags":371},2,[],[],[347,115],{"code":256,"score":22,"supported":14,"title":373,"abstract":374,"tags":375},[],[],[345],[377,378],"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":380,"openalex_id":382,"authors":383,"venue":101,"cited_by_count":160,"oa_url":336,"card":389,"direction":165,"ingested_from":167},"W7223041086",[384,386],{"name":385,"orcid":8},"Su Li",{"name":387,"orcid":388},"Changjun Yang","https:\u002F\u002Forcid.org\u002F0009-0000-6236-3489",{"tldr":390,"method":391,"finding":392,"direction":165,"opportunity":393},"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",{"id":396,"title":397,"url":398,"summary":399,"summary_zh":8,"content":8,"source_name":400,"source_url":8,"published_at":238,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":176,"score_detail":401,"sources":403,"tags":405,"primary_topic":409,"secondary_topics":410,"classification":411,"search_phrases":429,"slug":432,"view_count":160,"doi":433,"paper":434,"created_at":442},5459,"数字乡村建设对农业能源韧性的影响研究 (Research on the Impact of Digital Village Construction on Agricultural Energy Resilience)","https:\u002F\u002Fdoi.org\u002F10.13872\u002Fj.1000-0275.2026.0997","基于2011—2024年30个省份面板数据，三维构建农业能源韧性指标，双向固定效应、中介与门槛模型检验。数字乡村显著提升农业能源韧性，农业社会化服务部分中介，呈单一门槛。粮食主产区与主销区显著。属网络首发。","农业现代化研究（网络首发）2026-10-19",{"impact":17,"substance":18,"depth":17,"authority":108,"freshness":21,"relevant":22,"comment":402},"基于30省14年面板数据的网络首发论文，方法规范、结论有新意，但属学术细分议题，公共影响有限，可作精选备选。",[404],{"name":400,"url":398},[27,406,407,408],"粮食主产区","农业社会化服务","农业能源韧性",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[],{"status":40,"locked":14,"version":41,"method":42,"evidence":412},{"candidates":413,"agricultural_evidence":47},[414,418,424],{"code":33,"score":19,"supported":47,"title":415,"abstract":416,"tags":417},[27,125],[27],[27],{"code":419,"score":257,"supported":47,"title":420,"abstract":421,"tags":423},"G2",[],[422],"社会化服务",[407],{"code":425,"score":22,"supported":14,"title":426,"abstract":427,"tags":428},"A8",[],[],[406],[430,431],"数字乡村 农业能源韧性","农业社会化服务 中介效应","数字乡村农业能源韧性-5459","10.13872\u002Fj.1000-0275.2026.0997",{"doi":433,"openalex_id":8,"authors":435,"venue":8,"cited_by_count":160,"oa_url":8,"card":436,"direction":165,"ingested_from":441},[],{"tldr":437,"method":438,"finding":439,"direction":165,"opportunity":440},"基于30省面板数据，检验数字乡村建设对农业能源韧性的提升作用。","2011—2024年30省面板数据，三维构建韧性指标，双向固定效应、中介与门槛模","数字乡村显著提升农业能源韧性，农业社会化服务部分中介，存在单一门槛，主产区与主销区显著。","可延伸研究数字乡村影响农业能源韧性的区域异质机制及社会化服务之外的中介路径。","agent","2026-10-21T00:10:08.067176Z"]