[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-941":3,"related-941":50},{"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":22,"tags":24,"primary_topic":8,"secondary_topics":30,"classification":31,"search_phrases":44,"slug":47,"view_count":48,"doi":8,"paper":8,"created_at":49},941,"数字经济对自然灾害下农村家庭生计韧性的缓解作用 基于中国家庭追踪调查CFPS的实证","https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F15\u002F1665","原文标题：Can the Digital Economy Mitigate the Adverse Impact of Natural Disasters on the Livelihood Resilience of Rural Households? Empirical Evidence from Rural China。选取2014-2020年中国家庭追踪调查CFPS大样本数据，实证检验数字经济在缓解自然灾害对农村家庭生计韧性负面影响中的作用。实证结果表明虽然自然灾害显著负面影响农村家庭生计韧性，数字技术嵌入可通过扩大农村家庭非农就业机会、增强家庭获取信贷的可得性、改善农业生产策略在一定程度上缓解该负面影响。中西部与高收入家庭中数字经济的缓解效应更为明显。本研究为强化农民灾害适应能力的数字技术政策干预与数字技能培训提供来自中国农村的经验证据。",null,"## 1. Introduction\n\nIn recent years, frequent natural disasters related to climate change have posed numerous challenges to agricultural production and rural livelihoods [[1](https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F15\u002F1665#B1-agriculture-16-01665)]. Extreme weather events (e.g., droughts, floods, frosts, etc.) have increased the vulnerability of agricultural systems, resulting in food yield declining, household income decrease, and population outflows [[2](https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F15\u002F1665#B2-agriculture-16-01665),[3](https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F15\u002F1665#B3-agriculture-16-01665),[4](https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F15\u002F1665#B4-agriculture-16-01665)]. The adverse effects of natural disasters are particularly severe for smallholder farmers who are dependent on the use of farmland resources and have a single livelihood. Moreover, farmers have limited livelihood capital and weak capacity and may tend to return to poverty when exposed to risk shocks [[5](https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F15\u002F1665#B5-agriculture-16-01665)]. Existing research suggests that disaster relief instruments based on financial compensation can help to mitigate the negative impacts of disaster shocks by increasing the livelihood capital of farmer households in the short term [[6](https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F15\u002F1665#B6-agriculture-16-01665)]. However, this ‘blood transfusion’ approach cannot substantially address the long-term impacts of natural disasters on farm households. Based on the resilience perspective, the resilience of farmer household livelihoods highlights the ability of a household to resist risk and sustain development when faced with complex natural risk shocks [[7](https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F15\u002F1665#B7-agriculture-16-01665),[8](https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F15\u002F1665#B8-agriculture-16-01665)]. Therefore, in the context of natural disaster shocks, enhancing the resilience of farm household livelihoods is an important strategy for farmers to withstand risks and achieve sustainable development.\n\nOn the one hand, livelihood resilience enhancement is predicated on the availability of livelihood capacity of farm households [[9](https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F15\u002F1665#B9-agriculture-16-01665)]. Because of their relatively disadvantaged position in the socio-economic system, farmers often find it difficult to compete with other actors in terms of resource allocation and market access. Farmers need to be provided with equal rights and opportunities through various policies or institutional means [[10](https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F15\u002F1665#B10-agriculture-16-01665)]. On the other hand, farmers have complex household assets, and the key to improving the resilience of their livelihoods lies not only in increasing the total amount of their assets, but also in achieving an efficient allocation of their asset portfolios and diversity of livelihood strategies [[11](https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F15\u002F1665#B11-agriculture-16-01665)].\n\nChina’s rapid development of the digital economy provides important momentum for the growth of the national economy [[12](https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F15\u002F1665#B12-agriculture-16-01665)]. In order to promote the process of agricultural and rural informatization, the state has introduced and implemented a series of policies, such as the “Information into Villages and Households Project”, the “Rural E-commerce Development Policy”, and the “Broadband Countryside Plan”. The implementation of these policies has protected the institutional equality of rural households in terms of their livelihood ability and facilitated the inclusive development of rural economy [[13](https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F15\u002F1665#B13-agriculture-16-01665)]. At the same time, a large number of scholars have proved that the development of the digital economy has achieved significant results in expanding the sale of agricultural products, promoting farmers’ income and accelerating the integration of rural industries, which effectively promotes the diversification of the livelihood capital of rural households [[14](https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F15\u002F1665#B14-agriculture-16-01665),[15](https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F15\u002F1665#B15-agriculture-16-01665)]. The development of digital economy provides opportunities to alleviate the risk vulnerability faced by farming households [[16](https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F15\u002F1665#B16-agriculture-16-01665)]. However, current research has focused on the relationship between the digital economy and farm household income, but whether the digital economy has a significant role in mitigating risk vulnerability and empowering farm households to enhance their livelihood resilience, as well as the transmission mechanism between them, still needs to be further tested. Moreover, some past studies have shown that the information welfare brought by the digital economy cannot fully benefit all farmers [[17](https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F15\u002F1665#B17-agriculture-16-01665),[18](https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F15\u002F1665#B18-agriculture-16-01665)]. In fact, the application of the digital economy has a threshold in different regions and individuals, and it is unclear whether the digital economy has a heterogeneous role in alleviating natural risk shocks.\n\nBased on the above research background, the impact and transfer mechanism of digital economy between the natural risk and livelihood resilience of farmer households were empirically examined. The research contribution of this study includes the following three aspects. First, this study developed a comprehensive framework for measuring rural household livelihood resilience by integrating the three resilience capacities of buffering capacity, self-organization capacity, and learning capacity. It further extended existing frameworks by incorporating psychological capital into buffering capacity to capture households’ internal resources for coping with external shocks. Second, based on the constructed indicator of livelihood resilience, the moderating role of the digital economy in the relationship between natural risks and livelihood resilience was examined. Third, three mechanistic paths of the digital economy, including non-farm employment, credit access, and agricultural production strategies, were further explored. Then, some theoretical and policy implications are provided for rural households to cope with disaster impacts and improve their livelihood resilience through the development of the digital economy.\n\n## 2. Literature Review and Research Hypothesis\n\n### 2.1. The Concept of Livelihood Resilience\n\nEcologist Holling [[19](https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F15\u002F1665#B19-agriculture-16-01665)] first introduced the term ‘resilience’ into ecosystem studies to analyze the dynamics of ecosystems and their ability to maintain stability in the face of external disturbances. Over time, the concept of livelihood resilience has been gradually applied to a variety of disciplines, such as ecology, engineering, and economics. The concept of livelihood resilience in this paper refers to the ability of rural households to avoid falling into poverty and maintain their livelihoods when faced with natural risk.\n\nBy sorting out the existing studies, three main approaches to livelihood resilience measurement are summarized: i. According to the sustainable livelihood framework, the livelihood resilience of farmer households can be divided into five types of capital: financial, physical, natural, human, and social capital [[20](https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F15\u002F1665#B20-agriculture-16-01665)]. ii. An analysis framework, namely “Capacity Framework”, based on buffering capacity, self-organizing capacity, and learning capacity, is constructed to measure livelihood resilience [[21](https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F15\u002F1665#B21-agriculture-16-01665)]. iii. The livelihood resilience of farmer households has been estimated through dynamic and non-linear modelling, which is measured based on conditional probabilities of specific welfare levels [[22](https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F15\u002F1665#B22-agriculture-16-01665)]. This paper followed the study of Speranza et al. [[21](https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F15\u002F1665#B21-agriculture-16-01665)] and measured the livelihood resilience of farmer households in terms of buffering capacity, self-organization capacity, and learning capacity. The buffering capacity referred to the ability of farmer households to cope with risky shocks and maintain their livelihoods at the same level; the self-organizing capacity was the ability to communicate with and receive assistance from external organizations when coping with risky shocks; and the learning capacity represented the ability of farmers to acquire knowledge and skills, as well as the ability of farmers to translate knowledge into action.\n\n### 2.2. Livelihood Resilience Needs in the Context of Disaster Vulnerability\n\nRural households remain disproportionately exposed to natural hazards such as floods, droughts, and extreme storms, and these shocks affect rural livelihoods through multiple interdependent channels [[23](https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F15\u002F1665#B23-agriculture-16-01665),[24](https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F15\u002F1665#B24-agriculture-16-01665)]. First, by causing physical damage to farmland and crops, natural disasters erode rural households’ natural and economic capital, thereby directly weakening their buffering capacity [[25](https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F15\u002F1665#B25-agriculture-16-01665)]. Second, natural disasters can severely undermine local social networks among villagers and organizations by triggering labor migration, destroying livelihood assets and infrastructure, disrupting information and communication channels, and intensifying resource competition, thus reducing households’ self-organizing capacity [[26](https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F15\u002F1665#B26-agriculture-16-01665)]. Third, the economic burden and psychological stress induced by disasters impair households’ learning capacity, diminishing both their motivation and their ability to acquire new knowledge for adaptive action [[27](https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F15\u002F1665#B27-agriculture-16-01665)]. In light of these multiple and interlinked pathways of influence, the vulnerability of rural households lies not only in their exposure to natural hazards, but also in the post-shock decline of the three core capacities (buffering capacity, self-organizing capacity, and learning capacity) that underpin livelihood resilience.\n\nThis recognition underscores an urgent need to shift the analytical focus from assessing disaster impacts to identifying the conditions that can sustain or restore livelihood resilience when shocks occur. While existing research has examined post-disaster coping strategies, such as income diversification and asset adjustment, a critical question remains underexplored: which external interventions can durably mitigate the intensity of natural hazard impacts on rural household livelihoods, rather than merely compensating for losses ex post?\n\n### 2.3. The Moderating Role of the Digital Economy\n\nWith the ongoing development of the digital economy in rural areas, digital technologies are increasingly supporting agricultural activities, offering practical channels for reducing farmers’ disaster vulnerability [[28](https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F15\u002F1665#B28-agriculture-16-01665)]. First, digital platforms lower the barriers to non-farm employment and e-commerce entrepreneurship, enabling rural households to offset disaster-induced agricultural losses with off-farm income [[29](https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F15\u002F1665#B29-agriculture-16-01665),[30](https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F15\u002F1665#B30-agriculture-16-01665)]. Mobile payment and digital credit services further allow households to rapidly mobilize financial resources for post-disaster recovery, thus alleviating the depletion of economic capital [[31](https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F15\u002F1665#B31-agriculture-16-01665),[32](https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F15\u002F1665#B32-agriculture-16-01665)]. Digital technologies can broaden income sources and thereby strengthen households’ buffering capacity.\n\nSecond, when physical social interactions are disrupted by disasters, the digital economy can restore and enhance self-organizing capacity. Online communication tools enable households to remotely maintain social networks, exchange recovery information, and access institutional support [[33](https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F15\u002F1665#B33-agriculture-16-01665)]. Such social connectivity becomes particularly valuable when geographical mobility is constrained in the aftermath of a disaster. Third, the digital economy can safeguard learning capacity by providing continuous access to knowledge and skill training, even during periods of livelihood stress. Through online platforms, household members can acquire agricultural techniques, disaster preparedness knowledge, and market information that are essential for adaptive action [[34](https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F15\u002F1665#B34-agriculture-16-01665),[35](https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F15\u002F1665#B35-agriculture-16-01665)].\n\nNotably, the existing literature on the rural digital economy has largely focused on its income-enhancing effects. Research on whether and how the digital economy alters the relationship between natural shocks and livelihood resilience remains limited. Moreover, the transmission mechanisms underlying such a moderating effect have yet to be empirically tested within a unified framework. This study aims to fill these gaps.\n\n### 2.4. Transmission Mechanisms of the Digital Economy\n\nBuilding on the preceding framework, three potential pathways through which the digital economy mitigates the impact of natural disaster shocks on rural household livelihood resilience are further explored: non-farm employment, credit access, and production strategy diversification.\n\n#### 2.4.1. The Non-Farm Employment Pathway\n\nNatural disasters often compel rural households to seek non-farm income to compensate for agricultural losses; however, information asymmetries in the labor market tend to render this channel precarious. The digital economy reduces these frictions by providing timely labor market information, creating remote work opportunities, and facilitating e-commerce participation [[36](https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F15\u002F1665#B36-agriculture-16-01665)]. Through this pathway, the digital economy helps rural households enrich their income sources. As an alternative source of agricultural income, non-agricultural income reduces farmers’ dependence on agricultural activities, allowing households to maintain basic consumption and production inputs when agricultural income decreases. Especially for households with limited land resources and a high proportion of agricultural income, this channel is particularly crucial. In the context of natural risk, the buffering capacity of rural households is consolidated through their participation in non-agricultural employment, and their livelihood resilience is further enhanced.\n\n#### 2.4.2. The Credit Access Pathway\n\nNatural disasters often cause serious mobility restrictions on rural households, leaving them with insufficient funds for post-disaster recovery and consumption smoothing. However, for a long time, the problem of information asymmetry in traditional rural financial markets has led to farmers with good credit being excluded from formal loans. The development of the digital economy provides new technological possibilities to solve this dilemma. Digital finance utilizes big data and mobile technology to reduce information friction, enabling institutions to more accurately assess creditworthiness and provide credit to previously underserved households [[35](https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F15\u002F1665#B35-agriculture-16-01665)]. The core value of credit access lies in providing a liquidity support for farmers. When disasters occur, timely credit funds can alleviate the funding gap in household consumption and production recovery, prevent farmers from selling their productive assets due to short-term liquidity depletion, and thus avoid falling into a vicious cycle of poverty, asset shrinkage, and weak recovery. Therefore, the credit pathway not only enhances farmers’ ability to allocate funds in response to current shocks, but also builds a financial defense line against future risks in their livelihood system, becoming a key support for enhancing farmers’ livelihood resilience.\n\n#### 2.4.3. The Production Strategy Diversification Pathway\n\nA key principle of risk management is that diversified production portfolios are better able to withstand idiosyncratic shocks [[37](https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F15\u002F1665#B37-agriculture-16-01665)]. Digital technologies, particularly including precision agriculture tools and big data analytics, can assist households in adjusting crop mixes, adopting integrated farming systems, and optimizing resource allocation based on real-time weather and market information [[38](https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F15\u002F1665#B38-agriculture-16-01665)]. The diversification of this production strategy not only enhances the flexibility of the agricultural system, but also establishes a dual resilience support for farmers. Firstly, diversification itself is an effective risk diversification mechanism. When a crop is reduced in yield due to disasters, the output of other crops or management projects can compensate for the loss of household income, avoiding livelihood difficulties caused by the collapse of a single link, and thus consolidating the buffering capacity of farmers. Secondly, diversified operations enable farmers to constantly come into contact with new crop varieties and production methods. Farmers accumulate knowledge through attempt and adaptation, thereby enhancing their learning capacity. The strengthening of buffering capacity and the improvement of learning ability complement each other, jointly building a more solid foundation for farmers’ livelihood resilience.\n\nBased on this, this article proposes hypotheses H1 to H3.\n\n**H1.**\n\nNatural risk shocks have a negative impact on the livelihood resilience of rural household.\n\n**H2.**\n\nThe digital economy alleviates the negative impact of natural disasters on the livelihood resilience of farmers.\n\n**H3.**\n\nThe digital economy alleviates the negative impact of natural disasters on farmers’ livelihood resilience by promoting non-agricultural employment transfer, improving rural households’ access to credit, and diversifying agricultural production strategies.\n\nAfter clarifying the dependent and independent variables and their relationships, we constructed the conceptual framework of this study ([Figure 1](https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F15\u002F1665#fig_body_display_agriculture-16-01665-f001)), which linked the livelihood resilience of rural households, natural risk shocks, and the level of digital economic development. Livelihood resilience was the focus of this study and consisted of buffering capacity, self-organization capacity, and learning capacity. Natural shock exposure and digital economy were considered as important influencing factors for livelihood resilience. As indicated by the arrows in [Figure 1](https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F15\u002F1665#fig_body_display_agriculture-16-01665-f001), the natural risk shocks had a negative impact of on livelihood resilience, while the direct impact of the digital economy on livelihood resilience was positive, and the digital economy played a moderating effect in the negative impact of natural risk shocks.\n\n**Figure 1.** Conceptual framework linking natural risk shocks, resilience capacities, and digital economy. Solid boxes represent the relationships among the three core research variables; dashed boxes highlight the heterogeneous scenarios, realistic contradictions, and policy implications examined in this study.\n\n## ","MDPI Agriculture 2026-08-02","2026-08-02T00:00:00Z","论文",10,false,69,{"impact":17,"substance":18,"depth":17,"authority":19,"freshness":20,"relevant":20,"comment":21},18,20,12,1,"论文实证数字经济对农村家庭生计韧性的缓解作用，数据详实，但时效性差。",[23],{"name":10,"url":6},[25,26,27,28,29],"数字经济","生计韧性","农村家庭","自然灾害","CFPS MDPI Agriculture",[],{"status":32,"locked":14,"version":33,"method":34,"evidence":35},"unclassified","2026-10-22.2","rules",{"candidates":36,"agricultural_evidence":42,"reason":43},[37],{"code":38,"score":20,"supported":14,"title":39,"abstract":40,"tags":41},"I6",[],[],[25],true,"缺少足够的主题证据",[45,46],"农村家庭 数字经济 生计韧性 自然灾害","农村家庭 数字经济","农村家庭数字经济生计韧性自然灾害-941",2,"2026-08-25T00:03:29.525742Z",{"total":51,"page":20,"page_size":51,"items":52},6,[53,103,186,232,284,323],{"id":54,"title":55,"url":56,"summary":57,"summary_zh":8,"content":8,"source_name":58,"source_url":8,"published_at":59,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":60,"score_detail":61,"sources":67,"tags":69,"primary_topic":8,"secondary_topics":74,"classification":75,"search_phrases":87,"slug":90,"view_count":91,"doi":92,"paper":93,"created_at":102},5458,"数字经济对农业高质量发展的影响——以新疆14地州市为例 (Impact of Digital Economy on the High-Quality Development of Agriculture: Evidence from the 14 Prefectures and Cities of Xinjiang)","http:\u002F\u002Fzgnjhxb.niam.com.cn\u002FCN\u002F10.13733\u002Fj.jcam.issn.2095-5553.2026.10.041","基于2010—2022年新疆14地州市面板数据，熵值法测度双指数，中介与固定效应模型分析。数字经济对农业高质量发展影响系数0.132且显著，农业产业结构升级中介效应0.0649。区域异质性为东疆最强、南疆次之、北疆最弱。","中国农机化学报 2026-10-20","2026-10-20T00:00:00Z",78,{"impact":62,"substance":63,"depth":17,"authority":64,"freshness":65,"relevant":20,"comment":66},16,21,14,9,"基于新疆14地州市面板数据的实证研究，方法规范、结论具体，对区域数字农业政策有参考价值，但属区域性学术成果，影响层级有限。",[68],{"name":58,"url":56},[25,70,71,72,73],"农业高质量发展","区域异质性","农业产业结构","新疆农业",[],{"status":32,"locked":14,"version":33,"method":34,"evidence":76},{"candidates":77,"agricultural_evidence":42,"reason":43},[78,82],{"code":38,"score":20,"supported":14,"title":79,"abstract":80,"tags":81},[],[],[25],{"code":83,"score":20,"supported":14,"title":84,"abstract":85,"tags":86},"J2",[],[],[70],[88,89],"新疆 数字经济 农业高质量发展","新疆 14地州市 面板数据","新疆数字经济农业高质量发展-5458",0,"10.13733\u002Fj.jcam.issn.2095-5553.2026.10.041",{"doi":92,"openalex_id":8,"authors":94,"venue":8,"cited_by_count":91,"oa_url":8,"card":95,"direction":99,"ingested_from":101},[],{"tldr":96,"method":97,"finding":98,"direction":99,"opportunity":100},"基于新疆14地州市面板数据，实证检验数字经济对农业高质量发展的影响及中介机制。","2010—2022年新疆14地州市面板数据，熵值法测度指数，中介与固定效应模型。","数字经济显著促进农业高质量发展（系数0.132），农业产业结构升级起中介作用，效应东疆最强、南疆次之","数字乡村与农业信息化","可延伸至县域尺度、微观农户数据及数字基础设施异质性下的机制识别与政策分区研究。","agent","2026-10-21T00:10:08.003418Z",{"id":104,"title":105,"url":106,"summary":107,"summary_zh":108,"content":8,"source_name":109,"source_url":106,"published_at":110,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":111,"score_detail":112,"sources":117,"tags":119,"primary_topic":124,"secondary_topics":130,"classification":131,"search_phrases":156,"slug":159,"view_count":91,"doi":160,"paper":161,"created_at":185},5372,"Livelihood risks and resilience of rural households: evidence from Sichuan Province, China","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1934397","Rural households in flood-prone areas face overlapping livelihood risks, yet evidence remains limited on how specific risk dimensions are associated with different components of livelihood resilience. This study examined these associations among rural households in three counties of Sichuan Province, China. Cross-sectional questionnaire data were collected from 540 rural households in Gaoxian, Jiajiang, and Yuechi counties. Composite indices were constructed for health, environmental, financial, and social risks and for buffering, self-organization, and learning capacities. Fractional logit models with county fixed effects were used to estimate adjusted associations, with inference based on village-clustered wild-bootstrap procedures. Social risk was negatively associated with buffering capacity, self-organization capacity, learning capacity, and overall livelihood resilience. Health risk was negatively associated with self-organization capacity at the 10% level and with overall livelihood resilience at the 5% level, but not with buffering or learning capacity. Financial risk was positively associated with overall livelihood resilience in the baseline model, but this association was not robust to excluding loan-amount indicators. Environmental risk was not statistically associated with any resilience outcome. The associations between livelihood risk and resilience were dimension-specific and should not be interpreted as causal. The findings identify social support and access to health services as priorities for further local assessment, while financial vulnerability should be distinguished from credit access and environmental interventions should be guided by additional evidence on local hazards and program performance.","洪涝易发地区的农村家庭面临多重生计风险，但关于具体风险维度与生计韧性不同组成部分之间关联的证据仍然有限。本研究考察了中国四川省三个县农村家庭中这些关联。研究收集了高县、夹江县和岳池县540户农村家庭的横截面问卷数据，构建了健康风险、环境风险、金融风险和社会风险以及缓冲能力、自组织能力和学习能力的综合指数。采用带县级固定效应的分数对数模型估计调整后的关联，推断基于村级聚类野生自助法程序。社会风险与缓冲能力、自组织能力、学习能力及总体生计韧性呈负相关。健康风险在10%水平上与自组织能力呈负相关，在5%水平上与总体生计韧性呈负相关，但与缓冲能力或学习能力无关。金融风险在基准模型中与总体生计韧性呈正相关，但该关联在剔除贷款金额指标后不稳健。环境风险与任何韧性结果均无统计学关联。生计风险与韧性之间的关联具有维度特异性，不应被解释为因果关系。研究结果将社会支持和卫生服务可及性确定为地方进一步评估的优先事项，同时应将金融脆弱性与信贷可及性加以区分，环境干预措施应以关于地方灾害和项目绩效的更多证据为指导。","Frontiers in Sustainable Food Systems","2026-10-19T00:00:00Z",63,{"impact":113,"substance":17,"depth":114,"authority":115,"freshness":65,"relevant":20,"comment":116},8,15,13,"基于四川三县540户问卷的实证研究，揭示社会风险对生计韧性的负向关联，方法规范但属区域案例，公共影响有限，可作参考而非精选。",[118],{"name":109,"url":106},[120,121,26,122,123],"乡村治理","农村金融","健康服务","农户生计",{"code":125,"slug":126,"name":127,"path":128,"parent_code":129},"H7","climate","气候适应与防灾减灾","\u002Ftopic\u002Fenvironment\u002Fclimate","H",[],{"status":132,"locked":14,"version":33,"method":34,"evidence":133},"classified",{"candidates":134,"agricultural_evidence":42},[135,141,146,151],{"code":125,"score":136,"supported":42,"title":137,"abstract":138,"tags":140},3,[],[139],"洪涝",[],{"code":142,"score":20,"supported":14,"title":143,"abstract":144,"tags":145},"G3",[],[],[121],{"code":147,"score":20,"supported":14,"title":148,"abstract":149,"tags":150},"G5",[],[],[120],{"code":152,"score":20,"supported":14,"title":153,"abstract":154,"tags":155},"G6",[],[],[123],[157,158],"四川 农户 生计韧性","高县 夹江 岳池 农户","四川农户生计韧性-5372","10.3389\u002Ffsufs.2026.1934397",{"doi":160,"openalex_id":162,"authors":163,"venue":109,"cited_by_count":91,"oa_url":106,"card":179,"direction":99,"ingested_from":184},"W7222969600",[164,167,169,171,173,175,177],{"name":165,"orcid":166},"Tao Liu","https:\u002F\u002Forcid.org\u002F0000-0002-0506-3356",{"name":168,"orcid":8},"Ting Zhao",{"name":170,"orcid":8},"Jiahui Tian",{"name":172,"orcid":8},"Shanshan Zhao",{"name":174,"orcid":8},"Tao Zeng",{"name":176,"orcid":8},"Lijie Xu",{"name":178,"orcid":8},"Wei Liu",{"tldr":180,"method":181,"finding":182,"direction":99,"opportunity":183},"分析四川三县540户农户生计风险各维度与生计韧性各成分的关联。","入户问卷构建风险与韧性指数，用分数logit模型加县固定效应和村级聚类野生自助法","社会风险与各韧性成分及总体韧性负相关，健康风险与总体韧性负相关，环境风险无显著关联。","可结合数字乡村建设，研究社会支持网络与医疗可及性等信息化服务如何提升农户生计韧性。","openalex","2026-10-20T23:30:06.775370Z",{"id":187,"title":188,"url":189,"summary":190,"summary_zh":8,"content":8,"source_name":191,"source_url":8,"published_at":192,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":193,"score_detail":194,"sources":197,"tags":199,"primary_topic":8,"secondary_topics":202,"classification":203,"search_phrases":219,"slug":222,"view_count":91,"doi":223,"paper":224,"created_at":231},5300,"张捷\u002F李林飞《中国林业经济》:数字经济政策对农业高质量发展的影响研究——基于国家大数据综合试验区的准自然实验","https:\u002F\u002Fzglyjj.nefu.edu.cn\u002Farticle\u002Fdoi\u002F10.13691\u002Fj.cnki.cn23-1539\u002Ff.2026.04.001","东北林业大学经济管理学院张捷、李林飞基于2011-2023年中国31个省级行政区面板数据,以国家大数据综合试验区建设为准自然实验,运用多期双重差分模型评估数字经济政策对农业高质量发展的影响;研究发现数字经济政策显著促进农业高质量发展且具滞后性和累积性;对本地区农业高质量发展具显著正向直接效应,但对其他地区产生负向空间溢出,呈现\"本地促进、外部抑制\"特征;非粮食主产区估计效应相对更强。","中国林业经济(2026,4)","2026-10-15T00:00:00Z",80,{"impact":17,"substance":195,"depth":17,"authority":64,"freshness":113,"relevant":20,"comment":196},22,"基于31省面板数据与国家大数据综合试验区的准自然实验，方法规范、结论有政策参考价值，但属学术论文且非时效热点，可入精选备选。",[198],{"name":191,"url":189},[25,70,200,201],"空间溢出","大数据试验区",[],{"status":32,"locked":14,"version":33,"method":34,"evidence":204},{"candidates":205,"agricultural_evidence":42,"reason":43},[206,211,215],{"code":207,"score":20,"supported":14,"title":208,"abstract":209,"tags":210},"I4",[],[],[200],{"code":38,"score":20,"supported":14,"title":212,"abstract":213,"tags":214},[],[],[25],{"code":83,"score":20,"supported":14,"title":216,"abstract":217,"tags":218},[],[],[70],[220,221],"国家大数据综合试验区 农业高质量发展","数字经济政策 双重差分","国家大数据综合试验区农业高质量发展-5300","10.13691\u002Fj.cnki.cn23-1539\u002Ff.2026.04.001",{"doi":223,"openalex_id":8,"authors":225,"venue":8,"cited_by_count":91,"oa_url":8,"card":226,"direction":99,"ingested_from":101},[],{"tldr":227,"method":228,"finding":229,"direction":99,"opportunity":230},"用多期DID评估国家大数据综合试验区对农业高质量发展的影响。","2011-2023年31省面板数据，多期双重差分模型。","政策显著促进本地农业高质量发展，但对其他地区有负向空间溢出。","可探究政策负向溢出的机制与跨区协同路径，及非粮食主产区的差异化政策设计。","2026-10-19T00:07:48.514777Z",{"id":233,"title":234,"url":235,"summary":236,"summary_zh":8,"content":8,"source_name":237,"source_url":8,"published_at":238,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":193,"score_detail":239,"sources":241,"tags":243,"primary_topic":248,"secondary_topics":253,"classification":254,"search_phrases":272,"slug":275,"view_count":136,"doi":8,"paper":276,"created_at":283},4155,"数字经济对粮食生产韧性的影响及作用机制检验","http:\u002F\u002Fwww.qikanvip.com\u002Fqkml\u002F127630.html","刘威、吴芮、郑雪丽、朱书葳（统计与决策2026年第02期；河南工业大学管理学院、西北农林科技大学乡村振兴学院）。基于2012—2023年中国31个省份面板数据，从理论与实证两方面探究数字经济对粮食生产韧性的影响及作用机制。结果表明：数字经济能显著促进粮食生产韧性提升；异质性检验表明东部地区促进效应显著大于中西部地区，粮食主销区大于粮食产销平衡区，粮食主产区不显著；机制检验表明增强农产品销售能力与技术创新能力是数字经济赋能粮食生产韧性提升的重要渠道；门槛效应检验表明数字经济与粮食生产韧性间存在明显门槛效应。","统计与决策2026年第02期","2026-10-01T00:00:00Z",{"impact":17,"substance":195,"depth":17,"authority":64,"freshness":113,"relevant":20,"comment":240},"基于31省面板数据的实证研究，结论与机制清晰，对数字乡村与粮食安全议题有参考价值，但属学术论文，公共传播性一般。",[242],{"name":237,"url":235},[244,25,245,246,247],"数字乡村","粮食主产区","粮食生产韧性","农业技术创新",{"code":249,"slug":250,"name":251,"path":252,"parent_code":8},"G","rural-services","农业服务与乡村发展","\u002Ftopic\u002Frural-services",[],{"status":255,"locked":14,"version":33,"method":34,"evidence":256},"partial",{"candidates":257,"agricultural_evidence":42},[258,263,268],{"code":249,"score":136,"supported":42,"title":259,"abstract":260,"tags":262},[],[261],"乡村振兴",[],{"code":264,"score":48,"supported":14,"title":265,"abstract":266,"tags":267},"A8",[],[],[245,246],{"code":38,"score":48,"supported":14,"title":269,"abstract":270,"tags":271},[],[],[244,25],[273,274],"数字经济 粮食生产韧性","河南工业大学 粮食生产韧性","数字经济粮食生产韧性-4155",{"doi":8,"openalex_id":8,"authors":277,"venue":8,"cited_by_count":91,"oa_url":8,"card":278,"direction":99,"ingested_from":101},[],{"tldr":279,"method":280,"finding":281,"direction":99,"opportunity":282},"基于2012—2023年31省面板数据，实证检验数字经济对粮食生产韧性的促进效应与作用机制。","31省面板数据，固定效应与门槛回归、异质性及中介机制检验。","数字经济显著提升粮食生产韧性，东部与主销区效应更强，主产区不显著。","可深入探究主产区数字经济效应不显著的成因，并细化销售与技术创新渠道的微观机制。","2026-10-04T00:09:09.867912Z",{"id":285,"title":286,"url":287,"summary":288,"summary_zh":8,"content":8,"source_name":289,"source_url":8,"published_at":290,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":291,"score_detail":292,"sources":294,"tags":296,"primary_topic":8,"secondary_topics":299,"classification":300,"search_phrases":311,"slug":314,"view_count":136,"doi":8,"paper":315,"created_at":322},3436,"《数字经济赋能农业高质量发展的实证分析》——基于2012—2022年省级面板数据","http:\u002F\u002Fwww.qikanvip.com\u002Fqkml\u002F174646.html","耿俊婷、徐梓钦、张朝辉基于2012—2022年省级面板数据，运用熵值法测算数字经济、农业新质生产力并用SBM-GML模型测算农业高质量发展，使用双向固定效应模型、中介效应模型等方法探究数字经济对农业高质量发展的影响及农业新质生产力的作用机制。研究发现：数字经济在推动农业实现高质量发展方面具有显著的正向效应且存在显著的时间异质性；农业新质生产力是数字经济赋能农业迈向高质量发展阶段的重要机制；在粮食主销区和产销平衡区存在显著正向影响。","《河南农业大学学报》2026年第2期","2026-09-20T00:00:00Z",81,{"impact":17,"substance":195,"depth":17,"authority":64,"freshness":65,"relevant":20,"comment":293},"基于2012—2022年省级面板数据的实证研究，方法规范、结论有新意，对数字乡村与农业高质量发展政策制定有参考价值。",[295],{"name":289,"url":287},[244,297,25,70,298],"农业新质生产力","省级面板数据",[],{"status":32,"locked":14,"version":33,"method":34,"evidence":301},{"candidates":302,"agricultural_evidence":42,"reason":43},[303,307],{"code":38,"score":48,"supported":14,"title":304,"abstract":305,"tags":306},[],[],[244,25],{"code":83,"score":48,"supported":14,"title":308,"abstract":309,"tags":310},[],[],[297,70],[312,313],"数字经济 农业高质量发展","农业新质生产力 中介效应","数字经济农业高质量发展-3436",{"doi":8,"openalex_id":8,"authors":316,"venue":8,"cited_by_count":91,"oa_url":8,"card":317,"direction":99,"ingested_from":101},[],{"tldr":318,"method":319,"finding":320,"direction":99,"opportunity":321},"基于2012—2022年省级面板数据，实证检验数字经济对农业高质量发展的影响及作用机制。","熵值法测度数字经济与农业新质生产力，SBM-GML测度农业高质量发展，双向固定效","数字经济显著正向促进农业高质量发展且具时间异质性，农业新质生产力为重要中介机制，效应在粮食主销区和产","可细化数字经济子维度（如数字基础设施、电商）对农业高质量发展的差异化路径，并补充微观农户或县域层面证据。","2026-09-25T00:09:33.774119Z",{"id":324,"title":325,"url":326,"summary":327,"summary_zh":328,"content":8,"source_name":109,"source_url":326,"published_at":329,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":330,"score_detail":331,"sources":334,"tags":336,"primary_topic":8,"secondary_topics":340,"classification":341,"search_phrases":348,"slug":351,"view_count":48,"doi":352,"paper":353,"created_at":368},3145,"Exploring household livelihood resilience and natural resource dependence in urban-oriented resettlement in rural China","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1948406","Urban-oriented resettlement is a key policy instrument for alleviating resource-driven livelihood constraints and fostering rural transformation and sustainable development in ecologically fragile regions. However, relocation not only changes residential locations but also alters households’ access to natural resources, livelihood capital structure, social networks, and livelihood strategy choices, leading to heterogeneous post-resettlement livelihood outcomes. Using household survey data from Ankang, Shaanxi Province, China, we develop an integrated framework coupling natural resource dependence (NRD) with household livelihood resilience (HLR) to examine how urban-oriented resettlement reconfigures this relationship. Group comparisons and multinomial logistic regression were used to examine the associations of relocation participation, voluntariness, subsidy level, and distance with HLR–NRD configuration membership. The results show that urban-oriented resettlement is associated with a significant reduction in households’ NRD, especially income and energy dependence; yet lower NRD does not consistently correspond to greater HLR. Relocation characteristics were also associated with households’ membership in different livelihood-transition configurations. These findings suggest that urban-oriented resettlement should be understood as a long-term process of livelihood-system reconstruction rather than as a one-time spatial intervention. Policy support should shift from uniform assistance toward differentiated livelihood recovery strategies based on HLR–NRD modes. This study extends household-level research on livelihood risk management and resettlement evaluation and offers empirical evidence for resettlement planning and sustainable livelihood governance in ecologically fragile regions and other developing contexts.","以城镇为导向的搬迁安置是缓解资源驱动型生计约束、促进生态脆弱地区农村转型与可持续发展的关键政策工具。然而，搬迁不仅改变了居民的居住地点，也改变了家庭对自然资源的获取、生计资本结构、社会网络以及生计策略选择，从而导致搬迁后生计结果呈现异质性。本文利用中国陕西省安康市的农户调查数据，构建了一个将自然资源依赖（NRD）与家庭生计韧性（HLR）相耦合的整合框架，以考察以城镇为导向的搬迁安置如何重构这一关系。研究采用组间比较和多项逻辑回归，分析搬迁参与、自愿性、补贴水平和距离与HLR–NRD配置归属之间的关联。结果表明，以城镇为导向的搬迁安置与家庭NRD的显著降低相关，尤其是收入和能源依赖；然而，较低的NRD并不总是对应更高的HLR。搬迁特征也与家庭在不同生计转型配置中的归属相关。这些发现表明，以城镇为导向的搬迁安置应被理解为生计系统重构的长期过程，而非一次性的空间干预。政策支持应从统一援助转向基于HLR–NRD模式的差异化生计恢复策略。本研究拓展了家庭层面的生计风险管理与搬迁评估研究，并为生态脆弱地区及其他发展中情境下的搬迁规划和可持续生计治理提供了经验证据。","2026-09-21T00:00:00Z",72,{"impact":19,"substance":63,"depth":332,"authority":115,"freshness":65,"relevant":20,"comment":333},17,"基于陕西安康农户调查，将自然资源依赖与生计韧性耦合，揭示搬迁后生计系统重构的异质性，对生态脆弱区搬迁后续扶持政策有实证参考价值。",[335],{"name":109,"url":326},[26,337,123,338,339],"易地搬迁","自然资源依赖","陕西安康",[],{"status":32,"locked":14,"version":33,"method":34,"evidence":342},{"candidates":343,"agricultural_evidence":42,"reason":43},[344],{"code":152,"score":48,"supported":14,"title":345,"abstract":346,"tags":347},[],[],[123,337],[349,350],"陕西安康 易地搬迁 农户生计","自然资源依赖 生计韧性","陕西安康易地搬迁农户生计-3145","10.3389\u002Ffsufs.2026.1948406",{"doi":352,"openalex_id":354,"authors":355,"venue":109,"cited_by_count":91,"oa_url":326,"card":363,"direction":99,"ingested_from":184},"W7213902576",[356,358,360],{"name":357,"orcid":8},"Ziqi Fang",{"name":359,"orcid":8},"Shaojun Chen",{"name":361,"orcid":362},"Xinyu Wu","https:\u002F\u002Forcid.org\u002F0000-0001-6130-7821",{"tldr":364,"method":365,"finding":366,"direction":99,"opportunity":367},"基于陕西安康农户调查，分析易地搬迁后自然资源依赖与生计韧性的关系。","农户调查数据，构建NRD-HLR耦合框架，用多项逻辑回归分析。","搬迁显著降低资源依赖，但低依赖未必带来高生计韧性，需差异化恢复策略。","可引入数字技术监测搬迁户生计资本与资源依赖动态，支撑差异化精准帮扶。","2026-09-22T23:30:08.101965Z"]