[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-3327":3,"related-3327":47},{"id":4,"title":5,"url":6,"summary":7,"summary_zh":8,"content":8,"source_name":9,"source_url":8,"published_at":10,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":14,"score_detail":15,"sources":23,"tags":25,"search_phrases":31,"slug":34,"view_count":35,"doi":36,"paper":37,"created_at":46},3327,"Digitalization of smallholder agriculture: Adoption and impacts——特刊导论（Sun et al. 2026）","https:\u002F\u002Fwww.sciopen.com\u002Flocal\u002Farticle_pdf\u002F10.1016\u002Fj.jia.2026.04.021.pdf","《Journal of Integrative Agriculture》2026年专刊导论，IAMO孙占力博士、华中农大熊航教授、北大易红梅教授等担任客座编辑。本专刊收录Liu et al. (2026)研究——使用面板数据和多种估计方法调查数字技术使用如何影响中国易地搬迁农户收入稳定性，发现数字技术显著改善收入水平和稳定性；Hu et al. (2026)使用来自5省1,833个农场的倾向得分匹配数据，发现网络信息使用实际上增加了小农户的化肥支出，反思了农业数字化的复杂性；Bai et al. (2026)研究数字素养通过改善农民对气候灾害风险的感知促进气候适应性生产行为；Amolegbe et al. (2026)研究尼日利亚数字知识与电商估值。",null,"《Journal of Integrative Agriculture》2026专刊","2026-09-17T00:00:00Z","论文",10,false,79,{"impact":16,"substance":17,"depth":18,"authority":19,"freshness":20,"relevant":21,"comment":22},18,22,19,14,6,1,"国际期刊专刊导论，汇集多国小农户数字化实证研究，方法扎实、结论具反思性，对农业信息化研究与实践有参考价值。",[24],{"name":9,"url":6},[26,27,28,29,30],"数字农业","农村电商","数字素养","小农户","数字鸿沟",[32,33],"Journal of Integrative Agriculture 数字农业 专刊","易地搬迁农户 数字技术 收入稳定性","JournalofIntegrativeAgriculture数字农业专刊-3327",0,"10.1016\u002Fj.jia.2026.04.021.pdf",{"doi":36,"openalex_id":8,"authors":38,"venue":8,"cited_by_count":35,"oa_url":8,"card":39,"direction":43,"ingested_from":45},[],{"tldr":40,"method":41,"finding":42,"direction":43,"opportunity":44},"该专刊导论综述小农户农业数字化的采纳与影响，涵盖中国及尼日利亚的多项实证研究。","基于面板数据、倾向得分匹配等方法的专刊导论，整合多国小农户实证研究。","数字技术可提升收入稳定性，但也可能增加化肥支出，数字化影响具有复杂性。","数字乡村与农业信息化","可深入探究数字技术对不同农户群体的异质性影响及化肥增投的机制与调控路径。","agent","2026-09-24T00:04:03.016677Z",{"total":20,"page":21,"page_size":20,"items":48},[49,76,113,139,163,182],{"id":50,"title":51,"url":52,"summary":53,"summary_zh":8,"content":54,"source_name":55,"source_url":8,"published_at":56,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":57,"score_detail":58,"sources":63,"tags":65,"search_phrases":71,"slug":74,"view_count":21,"doi":8,"paper":8,"created_at":75},539,"ICT-Based Versus Human-Based Climate Information: Implications for Agronomic Decisions Among Smallholder Farmers in the Eastern Cape, South Africa","https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8114","基于南非东开普省 217 户小农户的横断面调查与多阶段抽样,采用 logistic 回归识别 ICT 气候信息采纳决定因素,并用倾向得分匹配(PSM)评估其对农事决策的影响。结果显示 65% 农户通过 ICT 平台获取气候信息,35% 依赖人力渠道;ICT 采纳驱动因素包括教育、数字素养、移动网络可靠性、实时更新感知价值与智能手机持有;PSM 估计显示基于 ICT 的气候信息在影响种植决策、投入品使用与农事时机方面比人力渠道效果低 10%—15%,提示数字接入并不自动转化为有效使用。","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 \nJabulile Zamokuhle Manyike\n\n *[](mailto:jmanyike@ufh.ac.za)[![Image 2: ORCID](https:\u002F\u002Fpub.mdpi-res.com\u002Fimg\u002Fdesign\u002Forcid.png?0465bc3812adeb52?1786617101)](https:\u002F\u002Forcid.org\u002F0000-0001-6529-9574) and \nYanga-Inkosi Nocezo\n\n[](mailto:yanganocezo12@gmail.com)[![Image 3: ORCID](https:\u002F\u002Fpub.mdpi-res.com\u002Fimg\u002Fdesign\u002Forcid.png?0465bc3812adeb52?1786617101)](https:\u002F\u002Forcid.org\u002F0000-0002-7607-495X)\n\nDepartment of Agricultural Economics, Extension, and Agri-Business, Faculty of Science and Agriculture, University of Fort Hare, 1 King William’s Town Road, Alice 5700, South Africa\n\n*\n\nAuthor to whom correspondence should be addressed.\n\nSubmission received: 3 February 2026 \u002F Revised: 7 March 2026 \u002F Accepted: 8 March 2026 \u002F Published: 9 August 2026\n\n## Abstract\n\nSmallholder farmers in South Africa face increasing climate variability, yet their agronomic decision-making depends on timely and reliable climate information. Although digital ICT platforms are expanding, limited evidence exists on how their effectiveness compares to human-based advisory systems. The study addresses this gap by examining the determinants of ICT-based climate information adoption using logistic regression and assessing its influence on agronomic decisions through propensity score matching (PSM). A cross-sectional survey and multistage sampling were used to collect data from 217 smallholder crop farmers in the Eastern Cape. The results indicate that 65% of farmers accessed climate information through ICT platforms, while 35% relied on human-based sources. The adoption of ICT-based information is driven by education, digital literacy, mobile network reliability, the perceived value of real-time updates, and smartphone ownership, whereas habitual dependence on traditional channels hinders digital uptake. PSM estimates show that ICT-based climate information is 10–15% less effective than human-based sources in shaping planting decisions, input use, and the timing of farm operations, likely due to digital literacy and infrastructure constraints. The study demonstrates that access to digital tools does not automatically translate into effective use and recommends a hybrid information model integrating digital platforms with trusted human intermediaries to strengthen climate resilience and agronomic decision-making.\n\n## 1. Introduction\n\nAgriculture remains central to rural livelihoods in South Africa, particularly in provinces such as the Eastern Cape, where smallholder farmers form the majority of agricultural producers [[1](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8114#B1-sustainability-18-08114),[2](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8114#B2-sustainability-18-08114),[3](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8114#B3-sustainability-18-08114)]. Despite its importance, this sector is highly vulnerable to climate-related risks, as smallholder farmers often operate with limited resources, weak extension support, and poor access to climate adaptation tools [[4](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8114#B4-sustainability-18-08114),[5](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8114#B5-sustainability-18-08114),[6](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8114#B6-sustainability-18-08114),[7](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8114#B7-sustainability-18-08114)]. Increasingly frequent droughts, delayed rainfall, rising temperatures, and shifting pest and disease pressures threaten food security and economic stability in the region [[8](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8114#B8-sustainability-18-08114),[9](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8114#B9-sustainability-18-08114),[10](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8114#B10-sustainability-18-08114)]. Timely, reliable climate information is therefore critical for guiding agronomic decisions such as planting dates, crop choices, water management, and input application [[11](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8114#B11-sustainability-18-08114),[12](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8114#B12-sustainability-18-08114),[13](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8114#B13-sustainability-18-08114),[14](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8114#B14-sustainability-18-08114),[15](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8114#B15-sustainability-18-08114)]. Access to such information enhances farmers’ preparedness for climate extremes and strengthens their adaptive capacity [[15](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8114#B15-sustainability-18-08114),[16](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8114#B16-sustainability-18-08114),[17](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8114#B17-sustainability-18-08114),[18](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8114#B18-sustainability-18-08114)]. Climate information services typically include rainfall onset and cessation, seasonal duration, temperature trends, soil moisture, wind patterns, and early warnings for droughts or floods [[18](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8114#B18-sustainability-18-08114),[19](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8114#B19-sustainability-18-08114),[20](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8114#B20-sustainability-18-08114),[21](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8114#B21-sustainability-18-08114),[22](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8114#B22-sustainability-18-08114)]. Traditionally, this information has been disseminated through human-based channels—extension officers, farmer groups, NGOs, and community networks [[14](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8114#B14-sustainability-18-08114),[22](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8114#B22-sustainability-18-08114),[23](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8114#B23-sustainability-18-08114),[24](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8114#B24-sustainability-18-08114)]. These sources are valued for their contextual relevance and interpersonal trust [[21](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8114#B21-sustainability-18-08114)]. However, in South Africa, high extension-to-farmer ratios, inconsistent service delivery, communication gaps, and sociocultural barriers, including gendered access to advisory support, limit the effectiveness of these channels [[25](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8114#B25-sustainability-18-08114),[26](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8114#B26-sustainability-18-08114),[27](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8114#B27-sustainability-18-08114),[28](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8114#B28-sustainability-18-08114),[29](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8114#B29-sustainability-18-08114)].\n\nAt the same time, the expansion of digital infrastructure and mobile technologies has enabled Information and Communication Technologies (ICTs) such as mobile weather alerts, agricultural apps, WhatsApp groups, and voice-based advisory platforms to play an increasingly prominent role in climate information delivery [[23](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8114#B23-sustainability-18-08114),[30](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8114#B30-sustainability-18-08114),[31](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8114#B31-sustainability-18-08114),[32](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8114#B32-sustainability-18-08114),[33](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8114#B33-sustainability-18-08114),[34](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8114#B34-sustainability-18-08114),[35](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8114#B35-sustainability-18-08114),[36](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8114#B36-sustainability-18-08114)]. ICT-based tools have the potential to provide rapid, localized, and scalable climate information [[37](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8114#B37-sustainability-18-08114)]. However, their adoption remains uneven due to persistent digital barriers, including poor network coverage, low digital literacy, high data costs, and language mismatches [[33](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8114#B33-sustainability-18-08114),[38](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8114#B38-sustainability-18-08114),[39](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8114#B39-sustainability-18-08114),[40](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8114#B40-sustainability-18-08114)]. Moreover, farmers often continue to trust interpersonal sources more than digital platforms, creating a dual system where ICT-based and human-based information coexist but are not equally utilized or valued [[30](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8114#B30-sustainability-18-08114),[39](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8114#B39-sustainability-18-08114)]. These dynamics raise important questions regarding why some farmers adopt ICT-based climate information while others rely on traditional channels, and whether ICT-based information is as effective as human-based sources in influencing agronomic decisions. Addressing these questions is essential for designing climate information systems that are both accessible and impactful.\n\nThis study, therefore, seeks to bridge this gap by (i) identifying the factors that influence smallholder farmers’ adoption of ICT-based climate information over human-based sources, and (ii) evaluating the impact of ICT-based climate information on agronomic decision-making compared to human-based sources. Focusing on the Eastern Cape Province, where both ICT infrastructure and extension systems are active but unevenly distributed, the study provides timely insights into how information flows influence climate adaptation at the farm level. By shedding light on these dynamics, the study contributes to policy discussions on how to design integrated climate information services that are inclusive, accessible, and actionable. It also offers practical recommendations for strengthening both digital and interpersonal communication channels, ensuring that no farmer is left behind in the shift toward climate-resilient agriculture.\n\n## 2. Materials and Methods\n\n### 2.1. Description of the Study Area\n\nThe study was conducted in Elundini Local Municipality, located within the Joe Gqabi District of the Eastern Cape. The Municipality is made up of three towns, Mount Fletcher in the north, Maclear in the centre, and Ugie in the South. [Figure 1](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8114#fig_body_display_sustainability-18-08114-f001) illustrates their locations along with the distribution of sampled households across the study area. The municipality is located near Mthatha [[41](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8114#B41-sustainability-18-08114)], the third largest city within the province [[42](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8114#B42-sustainability-18-08114)]. Elundini’s economy is driven by agriculture, social services, and retail trade, with the agricultural sector comprising commercial, emerging, and subsistence farming [[43](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8114#B43-sustainability-18-08114)]. Farmers commonly grow maize, potatoes, and cabbages, and keep both large and small ruminants [[41](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8114#B41-sustainability-18-08114)]. The area receives an annual average rainfall of approximately 1200 mm, mostly received in the summer planting season [[44](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8114#B44-sustainability-18-08114)], but experiences significant climate variability, including erratic rainfall and periodic droughts that heighten production risks [[43](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8114#B43-sustainability-18-08114)]. Furthermore, Elundini has many natural resources and a good climate that makes it possible for households to engage in agriculture [[45](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8114#B45-sustainability-18-08114)]. However, its agricultural performance remains below its potential, constrained by limited market access, infrastructure, and technology uptake—conditions that contrast sharply with highly mechanized and well-serviced agricultural zones [[46](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8114#B46-sustainability-18-08114)]. In the area, government support is available through extension services and farmer assistance programmes such as the provision of seedlings, livestock facilities, and fencing materials [[41](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8114#B41-sustainability-18-08114),[46](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8114#B46-sustainability-18-08114)]. Nonetheless, the extent of their reach is limited due to high farmer-to-officer ratios and communication constraints [[25](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8114#B25-sustainability-18-08114),[26](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8114#B26-sustainability-18-08114),[27](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8114#B27-sustainability-18-08114),[28](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8114#B28-sustainability-18-08114),[29](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8114#B29-sustainability-18-08114)].\n\n**Figure 1.** Map of study area. Source: Department of GIS, University of Fort Hare. Note: Numbers 1–17 show the municipal wards; red dots mark the locations of the sampled households.\n\nICT infrastructure is provided through public libraries equipped with computers and internet access [[46](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8114#B46-sustainability-18-08114)], though network reliability and digital literacy remain barriers for many community members. Given the combination of high agricultural potential, exposure to climate-related risks, uneven technological advancement, and mixed advisory and ICT service environments, Elundini provides an ideal setting for analyzing differences in the adoption and effectiveness of ICT-based versus human-based climate information sources.\n\n### 2.2. Research Design\n\nThis study adopted a quantitative cross-sectional research design to investigate the adoption and impact of ICT-based climate information among smallholder crop farmers in the Eastern Cape Province of South Africa. A cross-sectional approach was deemed appropriate for capturing data at a single point in time, enabling an assessment of current patterns of ICT use, climate information access, and related agronomic decisions.\n\n### 2.3. Sampling Procedure and Sample Size\n\nA multistage sampling technique was employed to ensure representativeness and practicality in data collection. In the first stage, Elundini municipality was purposively selected. Within the municipality, eight wards were randomly selected based on their agricultural relevance and reported farming activity levels. Within each ward, one or two villages were randomly selected, leading to a total of twelve participating villages. Finally, within each village, a random sampling technique was used to select 217 smallholder farmers. [Table 1](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8114#table_body_display_sustainability-18-08114-t001) presents the distribution of sampled farmers across the three towns. From the total sample, 167 farmers indicated that they had access to some form of climate information, either through ICT-based platforms or human-based sources, while 50 had no access, and were excluded from the impact assessment component of the analysis. Additionally, among the 167 farmers included, 69 were from Maclear, and 65 from Mount Fletcher, with Ugie represented by 33 farmers.\n\n**Table 1.** Sampling size per location.\n\n### 2.4. Data Collection\n\nData was collected in May 2022 using a structured questionnaire, administered through face-to-face interviews to ensure comprehension and minimize non-response. The questionnaire consisted of questions on farmer’s socio-demographic characteristics (age, education, income, household size, and gender), sources of climate information (e.g., extension agents, radio, mobile apps, WhatsApp groups, local farmer associations), ICT access and use (mobile phone ownership, digital literacy, access to internet or network), and agronomic decision-making (e.g., planting time, crop choices, irrigation practices, input application). The instrument was pre-tested with a small group of farmers outside the sample area to ensure clarity and relevance, and necessary adjustments were made before final data collection. During the data collection phase, authors ensured that verbal consent was obtained from farmers, they were treated with respect and allowed to refuse to be part of the research or withdraw from it at any given time, and that their information was kept confidential and used for academic purposes only. All of these requirements were guided by the ethical approval letter [MAN011SNOC01], which was obtained from the department of agricultural economics and extension, faculty of Science and Agriculture at the University of Fort Hare.\n\n### 2.5. Data Analysis\n\nData was first analyzed using descriptive statistics to summarize the characteristics of the sample, including age distribution, education levels, climate information sources, and ICT use. To identify the factors influencing the adoption of ICT-based climate information, a binary logistic regression model was employed. Stata\u002FSE 15.1 (Stata Corp LLC) was used for the analysis.\n\n#### 2.5.1. Logistic Regression Model\n\nThe dependent variable was a binary indicator of whether a farmer accessed climate information via ICT (1) or through human-based sources (0). The probability (\n\n$P_{i}$\n) that farmers receive climate information via ICT platforms is represented as\n\n$$\nY_{i } = \\beta_{0} + \\sum_{i = 1}^{n} \\beta_{i} X_{i ,}\n$$\n\n(1)\n\nThe equation represents a binary choice, which involves the estimation of the probability of receiving climate information via ICT platforms (Y) as a function of independent variables (X).\n\n$\\beta_{0 }$\nis constant and\n\n$Y_{i }$\nis equal to one 1 when farmers receive ICT-based climate information and 0 if through human-based sources. The logit model uses a logistic cumulative distributive function to estimate, P given by\n\n$$\nP = \\left(\\right. Y = \\frac{1}{X} \\left.\\right) = \\frac{e^{y}}{1 + e^{y}}\n$$\n\n(2)\n\n$$\nP = \\left(\\right. Y = \\frac{0}{X} \\left.\\right) = 1 - \\frac{e^{y}}{1 + e^{y}}\n$$\n\n(3)\n\n$$\nY = \\mathsf{\\beta}_{1} X_{1} + \\mathsf{\\beta}_{2} X_{2} + \\ldots + \\mathsf{\\beta}_{k} X = \\sum_{i = 1}^{k} \\mathsf{\\beta}_{i} X_{i ,}\n$$\n\n(4)\n\nwhere k represents the number of explanatory predictors that are to be included in the analysis. The model is as follows:\n\n$$\nY = \\mathit{Ln} \\left(\\right. \\frac{P}{1 - P} \\left.\\right) = \\beta_{0} + \\beta_{k} + \\epsilon ,\n$$\n\n(5)\n\nwhere Y = farmer accessed climate information via ICT; Ln\n\n$\\left(\\right. \\frac{P}{1 - P} \\left.\\right)$\nthe ratio of probability of accessing climate information via ICT (p) to receiving it through human-based sources (1 − P); β = slope of coefficient;\n\n$X_{k}$\n= vector of the independent variables presented in [Table 2](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8114#table_body_display_sustainability-18-08114-t002); ε = error term.\n\n**Table 2.** Independent variables and expected signs in ICT adoption model.\n\n#### 2.5.2. Measuring Agronomic Decision\n\nThe Agronomic Decision Index (ADI) was employed to assess the extent of agronomic decisions made by smallholder farmers. This index serves as a tool to quantify the degree to which each household adopts key agronomic practices. While the existing literature commonly measures agronomic decision-making by simply noting whether a farmer made a decision or not [[17](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8114#B17-sustainability-18-08114)], this approach does not capture the depth of adoption. In contrast, ADI provides a more comprehensive measure. Each agronomic decision was coded as 1 if undertaken by the farmer and 0 otherwise. The index for each farmer was then calculated as shown in Equation (6):\n\n$$\nA D I = \\frac{D_{1} + D_{2} + D_{3} + D_{4} + D_{5} + D_{6} + D_{7}}{7}\n$$\n\n(6)\n\nwhere D1 to D7 include decisions on land preparation, planting date decis","Sustainability","2026-08-08T22:00:00Z",64,{"impact":59,"substance":60,"depth":16,"authority":59,"freshness":61,"relevant":21,"comment":62},12,20,2,"论文聚焦南非小农气候信息获取，对农业信息化有参考价值，但地域性强，时效性低。",[64],{"name":55,"url":52},[26,66,67,29,68,69,30,70],"数字乡村","农业信息化","气候信息","ICT采纳","发展中国家",[72,73],"农业信息化 发展中国家 数字乡村 数字农业","农业信息化 发展中国家","农业信息化发展中国家数字乡村数字农业-539","2026-08-15T00:02:55.675693Z",{"id":77,"title":78,"url":79,"summary":80,"summary_zh":81,"content":8,"source_name":82,"source_url":79,"published_at":83,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":84,"score_detail":85,"sources":91,"tags":93,"search_phrases":96,"slug":99,"view_count":35,"doi":100,"paper":101,"created_at":112},3345,"E-commerce digitalization for sustainable agricultural and rural development: models and pathways","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1743839","This study adopts the Technology-Organization-Environment (TOE) framework as its core meso-level integrated explanatory framework, embedding digital empowerment theory to guide variable selection and causal logic. Meanwhile, it classifies the core conditional variables into technological capabilities, organizational capabilities, and environmental\u002Fstructural factors, avoiding the stacking of practical dimensions in variable selection. We find that sustainable agricultural and rural development (SARD) outcomes are not driven by single factors but by the synergistic effect of multiple configurations. Analysis identifies three distinct pathways: digital technology and agile response-driven, service and channel optimization, and comprehensive synergy. The most effective pathway synergistically combines high channel integration, high digitalization of service experience, high marketing response agility, and high precision in consumer insight. These pathways enhance agricultural marketing efficiency and advance SARD across economic, social, and environmental dimensions. Furthermore, substitution effects exist among some auxiliary factors; for instance, depth of digital technology application and precision of consumer insight can be functionally equivalent in the digital technology and agile response-driven pathway. The core theoretical contribution of this study is breaking through the traditional linear cognition of single-factor driving in the research of digital agriculture and SARD, which is prevalent in both domestic and international academia. By adopting the fuzzy-set Qualitative Comparative Analysis (fsQCA) method, we identify and theorize three typical configurational driving archetypes of e-commerce-driven SARD, namely Technology-Agile type, Service-Optimized type and Comprehensive Synergy type, reveal the mechanisms of multiple concurrent causality and equifinal paths in the digital empowerment of SARD, supplement the configurational analysis perspective for the digital empowerment theory, and provide micro-practical support for the sustainable transition theory in the context of global digital agriculture and platformization development. We recommend that agricultural enterprises strengthen digital technology, build distinctive product identities based on consumer insights, and enhance service experiences to foster sustainable transitions.","本研究以技术-组织-环境(TOE)框架为核心的中层整合解释框架，嵌入数字赋能理论以指导变量选择与因果逻辑。同时，将核心条件变量归类为技术能力、组织能力和环境\u002F结构因素，避免变量选择中实践维度的堆叠。研究发现，农业农村可持续发展(SARD)成效并非由单一因素驱动，而是多重条件组合的协同效应所致。分析识别出三条差异化路径：数字技术与敏捷响应驱动型、服务与渠道优化型、综合协同型。其中最有效的路径协同组合了高渠道整合度、高服务体验数字化、高营销响应敏捷性和高消费者洞察精准度。这些路径提升了农产品营销效率，并在经济、社会和环境维度上推进了SARD。此外，部分辅助因素之间存在替代效应；例如，在数字技术与敏捷响应驱动型路径中，数字技术应用深度与消费者洞察精准度可在功能上等效。本研究的核心理论贡献在于突破了国内外学术界在数字农业与SARD研究中普遍存在的单因素驱动的传统线性认知。通过采用模糊集定性比较分析(fsQCA)方法，我们识别并理论化了电子商务驱动SARD的三种典型组态驱动原型，即技术-敏捷型、服务-优化型和综合协同型，揭示了数字赋能SARD中多重并发因果与等效路径的机制，为数字赋能理论补充了组态分析视角，并为全球数字农业与平台化发展背景下的可持续转型理论提供了微观实践支撑。我们建议农业企业强化数字技术，基于消费者洞察构建特色产品标识，并提升服务体验以促进可持续转型。","Frontiers in Sustainable Food Systems","2026-09-23T00:00:00Z",77,{"impact":86,"substance":87,"depth":16,"authority":88,"freshness":89,"relevant":21,"comment":90},16,21,13,9,"基于TOE框架与fsQCA方法揭示电商驱动农业农村可持续发展的三条组态路径，方法新颖、结论有理论增量，对数字乡村与农村电商实践具参考价值。",[92],{"name":82,"url":79},[26,27,66,94,95],"可持续农业","fsQCA",[97,98],"农村电商 数字赋能 可持续发展","电商 农业营销 数字化转型","农村电商数字赋能可持续发展-3345","10.3389\u002Ffsufs.2026.1743839",{"doi":100,"openalex_id":102,"authors":103,"venue":82,"cited_by_count":35,"oa_url":79,"card":106,"direction":43,"ingested_from":111},"W7214123656",[104],{"name":105,"orcid":8},"Qian Shan",{"tldr":107,"method":108,"finding":109,"direction":43,"opportunity":110},"基于TOE框架与fsQCA，识别电商数字化驱动农业农村可持续发展的三条组态路径。","TOE框架、数字赋能理论、fsQCA方法，分析多条件组态。","高渠道整合、高服务体验数字化、高营销响应敏捷与高消费者洞察精准组合最有效，存在替代效应。","可探究不同区域或平台情境下组态路径的适用边界，以及替代效应的动态演化机制。","openalex","2026-09-24T23:30:08.046331Z",{"id":114,"title":115,"url":116,"summary":117,"summary_zh":8,"content":8,"source_name":118,"source_url":8,"published_at":119,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":84,"score_detail":120,"sources":122,"tags":124,"search_phrases":127,"slug":130,"view_count":35,"doi":8,"paper":131,"created_at":138},3124,"Divide or Bridge? The Heterogeneous Effects of Digital Village Participation on Rural Residents' Happiness（鸿沟抑或桥梁？数字乡村参与对农村居民幸福感的异质性影响）","https:\u002F\u002Fwww.ebiotrade.com\u002Fnewsf\u002F2026-9\u002F20260919000408204.htm","Frontiers in Psychology 发表利用中国乡村振兴调查（CRRS）数据实证检验数字乡村参与对农村居民幸福感影响的研究。提升农村居民幸福感是中国乡村振兴战略的关键目标。研究方法采用 CRRS 调查数据进行实证检验；结果表明数字乡村参与与农村居民幸福感呈正相关；分维度分析揭示数字基础设施、数字治理和日常生活数字化对农村居民幸福感具有显著正向效应，而农村经济数字化的影响在统计上不显著；机制分析表明数字乡村参与通过缓解信贷约束和增加社会互动来提升农村居民幸福感；异质性分析显示数字素养较高的农村居民更能将数字参与转化为幸福感提升，而数字素养较低群体这一效应不显著。研究为缩小农村数字鸿沟提供经验证据，并为推动精准化、差异化的数字乡村发展提供政策启示。","Frontiers in Psychology","2026-09-19T00:00:00Z",{"impact":86,"substance":87,"depth":16,"authority":88,"freshness":89,"relevant":21,"comment":121},"基于CRRS数据的实证研究，揭示数字乡村参与对农村居民幸福感的异质性影响，结论扎实且具政策参考价值，值得进入每日精选。",[123],{"name":118,"url":116},[66,28,125,30,126],"乡村振兴","农村居民幸福感",[128,129],"CRRS 数字乡村 幸福感","数字素养 农村居民 幸福感","CRRS数字乡村幸福感-3124",{"doi":8,"openalex_id":8,"authors":132,"venue":8,"cited_by_count":35,"oa_url":8,"card":133,"direction":43,"ingested_from":45},[],{"tldr":134,"method":135,"finding":136,"direction":43,"opportunity":137},"基于CRRS数据实证检验数字乡村参与对农村居民幸福感的异质性影响。","中国乡村振兴调查（CRRS）数据，实证回归与机制、异质性分析。","数字参与提升幸福感，但经济数字化不显著，低数字素养群体获益有限。","可探究数字素养培育干预如何放大数字乡村的幸福感效应，缩小群体鸿沟。","2026-09-22T00:05:38.499296Z",{"id":140,"title":141,"url":142,"summary":143,"summary_zh":8,"content":144,"source_name":145,"source_url":8,"published_at":146,"category":147,"cover_url":8,"hotness":12,"is_selected":13,"score":148,"score_detail":149,"sources":153,"tags":155,"search_phrases":158,"slug":161,"view_count":35,"doi":8,"paper":8,"created_at":162},3090,"数智活水润乡村——人民论坛网深度解读《数字乡村高质量发展行动计划(2026—2030年)》","https:\u002F\u002Fnews.cyol.com\u002Fgb\u002Fqingping\u002Farticles\u002F2026-09\u002F22\u002Fcontent_6zE780Sd0q.html","9-22 中青在线刊发人民论坛网署名文章《数智活水润乡村》。文章系统解读中央网信办、农业农村部、工信部联合印发的《数字乡村高质量发展行动计划(2026—2030 年)》：从田间\"新农具\"到助农增收直播间\"新农活\"，数字技术全方位赋能乡村治理、产业发展与民生提质。8 项主要发展指标中，到 2030 年农村网络零售额将从 2025 年的 3 万亿元提升到 3.5 万亿元；农村成年人具备初级及以上数字素养与技能的占比要提升至 55%。文章强调数字兴则乡村兴，AI 数字人主播、智能语音政策宣讲员、村级政务智能机器人将共同支撑数字乡村建设全面提速。","近日，中央网信办、农业农村部、工业和信息化部联合印发《数字乡村高质量发展行动计划（2026—2030年）》，明确了“十五五”时期推进数字乡村高质量发展的思路目标、重点任务和政策举措。如今，从高效便捷的田间“新农具”，到助农增收的直播间“新农活”，数字技术全方位赋能乡村治理、产业发展与民生提质，为乡村全面振兴注入强劲数智动能。\n\n推进数字乡村建设向纵深发展，不止于乡村网络基础设施的全面升级，更在于智能数字工具深度扎根乡村基层治理各场景，让乡村治理更高效、更精细、更便民。各地乡村积极活用人工智能优势，让其化身专属政策宣讲员，依托智能语音、方言适配等功能，常态化解读惠农补贴、医保社保、乡村建设等各类惠民政策，打破时空限制，将政策条文转化为接地气、听得懂的家常话语，让惠民政策直达民心。\n\n同时，智能机器人搭载智能导办、材料预审、信息推送等功能，深度融入村级政务服务体系，助力村民高频事项“全程网办、便捷快办”，大幅提升乡村政务服务效率。在乡村应急预警、网格管理、人居环境整治等工作中，智能监测体系精准助力乡村精细化治理，持续优化乡村治理模式，以科技力量筑牢乡村善治根基，让数字化治理红利惠及千家万户。\n\n在很多地方，数字技术深入乡村产业一线，成为助力农户增收、激活乡村业态的新力量。依托数字化技术优势，AI数字人主播打破传统直播间的时间、人力限制，可全天候值守电商直播间，生动推介乡村特色农产品、展示非遗手工技艺、传播乡土文旅资源，让藏在深山田野的优质物产、特色文化走出乡村、走向全国。\n\n在数智化工具的赋能加持下，乡村数字经济持续蓬勃发展，2025年农村网络零售额已突破3万亿元，乡村电商新业态不断壮大，乡村主播、农货选品师等新职业持续涌现。数字技术有效补齐乡村电商人才缺口、降低乡村创业门槛，搭建起高效畅通的农产品上行通道，让线上流量转化为产业增量、农户收益，以数字新业态激活乡村产业新活力，为产业振兴赋能增效。\n\n随着数字乡村建设持续深化，乡村数字素养培育工作稳步推进，到2030年我国农村成年人具备初级及以上数字素养与技能的占比要提升至55%，越来越多村民将熟练运用数字工具、拥抱数字红利。\n\n数字兴则乡村兴。各地要持续用好数字技术这把“金钥匙”，深耕乡村应用场景、拓宽赋能边界，让智能新农具扎根田野、数字新农活落地生根，持续释放数字乡村发展红利，全方位助力农业提质、农民增收，为乡村全面振兴注入源源不断的新动能。（唐代远）\n\n【责任编辑：郭艳丽】","中青在线·人民论坛网","2026-09-21T23:00:00Z","报道",84,{"impact":150,"substance":60,"depth":151,"authority":88,"freshness":89,"relevant":21,"comment":152},27,15,"三部门联合印发数字乡村五年行动计划，属全国性政策解读，含3万亿网络零售额、2030年数字素养55%等关键数据，时效性强，值得进入每日精选。",[154],{"name":145,"url":142},[27,66,156,157,28],"乡村治理","农业人工智能",[159,160],"中央网信办 农业农村部 数字乡村","农业人工智能 乡村治理 农村电商 数字乡村","中央网信办农业农村部数字乡村-3090","2026-09-22T00:05:32.821988Z",{"id":164,"title":165,"url":166,"summary":167,"summary_zh":8,"content":168,"source_name":169,"source_url":8,"published_at":170,"category":147,"cover_url":8,"hotness":12,"is_selected":13,"score":171,"score_detail":172,"sources":175,"tags":177,"search_phrases":178,"slug":180,"view_count":35,"doi":8,"paper":8,"created_at":181},3031,"人民论坛网：数智活水润乡村——\"十五五\"数字乡村高质量发展的思路目标与重点任务","https:\u002F\u002Fwww.rmlt.com.cn\u002F2026\u002F0921\u002F756085.shtml","中央网信办、农业农村部、工业和信息化部联合印发《数字乡村高质量发展行动计划（2026—2030年）》，明确\"十五五\"时期推进数字乡村高质量发展的思路目标、重点任务和政策举措。各地乡村积极活用人工智能优势化身专属政策宣讲员；智能机器人搭载智能导办、材料预审、信息推送等功能深度融入村级政务服务体系；乡村数字经济持续蓬勃发展，2025年农村网络零售额已突破3万亿元，乡村电商新业态不断壮大，乡村主播、农货选品师等新职业持续涌现；到2030年我国农村成年人具备初级及以上数字素养与技能的占比要提升至55%。","## 【好评中国·新角色】数智活水润乡村\n\n2026-09-21 07:31 来源：  人民论坛网  作者： 唐代远\n\n近日，中央网信办、农业农村部、工业和信息化部联合印发《数字乡村高质量发展行动计划（2026—2030年）》，明确了“十五五”时期推进数字乡村高质量发展的思路目标、重点任务和政策举措。如今，从高效便捷的田间“新农具”，到助农增收的直播间“新农活”，数字技术全方位赋能乡村治理、产业发展与民生提质，为乡村全面振兴注入强劲数智动能。\n\n![Image 1: 图片1](https:\u002F\u002Fupload.rmlt.com.cn\u002F2026\u002F0920\u002F1789896898817.png)\n\n在山东省聊城市茌平区信发现代农业产业园智能玻璃温室大棚，工作人员在操作智能水肥机。新华社记者 陈晔华 摄\n\n推进数字乡村建设向纵深发展，不止于乡村网络基础设施的全面升级，更在于智能数字工具深度扎根乡村基层治理各场景，让乡村治理更高效、更精细、更便民。各地乡村积极活用人工智能优势，让其化身专属政策宣讲员，依托智能语音、方言适配等功能，常态化解读惠农补贴、医保社保、乡村建设等各类惠民政策，打破时空限制，将政策条文转化为接地气、听得懂的家常话语，让惠民政策直达民心。\n\n同时，智能机器人搭载智能导办、材料预审、信息推送等功能，深度融入村级政务服务体系，助力村民高频事项“全程网办、便捷快办”，大幅提升乡村政务服务效率。在乡村应急预警、网格管理、人居环境整治等工作中，智能监测体系精准助力乡村精细化治理，持续优化乡村治理模式，以科技力量筑牢乡村善治根基，让数字化治理红利惠及千家万户。\n\n在很多地方，数字技术深入乡村产业一线，成为助力农户增收、激活乡村业态的新力量。依托数字化技术优势，AI数字人主播打破传统直播间的时间、人力限制，可全天候值守电商直播间，生动推介乡村特色农产品、展示非遗手工技艺、传播乡土文旅资源，让藏在深山田野的优质物产、特色文化走出乡村、走向全国。\n\n在数智化工具的赋能加持下，乡村数字经济持续蓬勃发展，2025年农村网络零售额已突破3万亿元，乡村电商新业态不断壮大，乡村主播、农货选品师等新职业持续涌现。数字技术有效补齐乡村电商人才缺口、降低乡村创业门槛，搭建起高效畅通的农产品上行通道，让线上流量转化为产业增量、农户收益，以数字新业态激活乡村产业新活力，为产业振兴赋能增效。\n\n随着数字乡村建设持续深化，乡村数字素养培育工作稳步推进，到2030年我国农村成年人具备初级及以上数字素养与技能的占比要提升至55%，越来越多村民将熟练运用数字工具、拥抱数字红利。\n\n数字兴则乡村兴。各地要持续用好数字技术这把“金钥匙”，深耕乡村应用场景、拓宽赋能边界，让智能新农具扎根田野、数字新农活落地生根，持续释放数字乡村发展红利，全方位助力农业提质、农民增收，为乡村全面振兴注入源源不断的新动能。（唐代远）\n\n[![Image 2](https:\u002F\u002Fimg.rmlt.com.cn\u002Ftemplates\u002Frmlt2013\u002Fimg\u002Frmlt_logo.jpg)](http:\u002F\u002Fwww.rmlt.com.cn\u002F)\n\n[责任编辑：曲统昱]","人民论坛网","2026-09-21T00:00:00Z",85,{"impact":173,"substance":60,"depth":151,"authority":19,"freshness":12,"relevant":21,"comment":174},26,"紧扣三部委数字乡村行动计划，含2025年农村网络零售额破3万亿、2030年数字素养55%等关键数据，政策解读与场景案例兼具，时效性强，值得进入每日精选。",[176],{"name":169,"url":166},[27,66,156,157,28],[179,160],"农村网络零售额 3万亿","农村网络零售额3万亿-3031","2026-09-21T00:04:32.338547Z",{"id":183,"title":184,"url":185,"summary":186,"summary_zh":187,"content":8,"source_name":118,"source_url":185,"published_at":188,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":189,"score_detail":190,"sources":193,"tags":195,"search_phrases":197,"slug":200,"view_count":35,"doi":201,"paper":202,"created_at":220},2959,"Divide or bridge? The heterogeneous effects of digital village participation on rural residents’ happiness","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffpsyg.2026.1893504","Introduction Enhancing rural residents’ happiness is a key objective of China’s rural revitalization strategy. Methods Using data from the China Rural Revitalization Survey (CRRS), this study empirically examines the relationship between digital village participation on rural residents’ happiness. Results The results show that digital village participation is positively associated with rural residents’ happiness. Dimensional-specific analyses further reveals that digital infrastructure, digital governance, and the digitalization of daily life exert significant positive effects on rural residents’ happiness, whereas the effect of rural economic digitalization is statistically insignificant. The mechanism analysis indicates that digital village participation improves rural residents’ happiness by alleviating credit constraints and increasing social interaction. The heterogeneity analysis reveals that rural residents with higher digital literacy are better able to translate digital participation into gains in happiness, whereas the effect is insignificant among those with lower levels of digital literacy. Discussion This study provides empirical evidence for narrowing the rural digital divide and offers policy implications for promoting targeted and differentiated digital village development.","引言 提升农村居民幸福感是中国乡村振兴战略的重要目标。方法 本研究利用中国乡村振兴调查（CRRS）数据，实证检验了数字乡村参与与农村居民幸福感之间的关系。结果 结果表明，数字乡村参与与农村居民幸福感呈正相关。分维度分析进一步显示，数字基础设施、数字治理和日常生活数字化对农村居民幸福感具有显著正向影响，而农村经济数字化的影响在统计上不显著。机制分析表明，数字乡村参与通过缓解信贷约束和增加社会互动提升农村居民幸福感。异质性分析显示，数字素养较高的农村居民更能将数字参与转化为幸福感的提升，而在数字素养较低的群体中该效应不显著。讨论 本研究为缩小农村数字鸿沟提供了实证依据，并为推进有针对性、差异化的数字乡村发展提供了政策启示。","2026-09-18T00:00:00Z",76,{"impact":86,"substance":87,"depth":191,"authority":88,"freshness":89,"relevant":21,"comment":192},17,"基于全国性农户调查的实证研究，揭示数字乡村参与对农民幸福感的异质性影响，对数字乡村政策有参考价值。",[194],{"name":118,"url":185},[66,28,125,30,196],"农户幸福感",[198,199],"中国乡村振兴调查 CRRS 数字乡村","农户幸福感 乡村振兴 数字乡村 数字素养","中国乡村振兴调查CRRS数字乡村-2959","10.3389\u002Ffpsyg.2026.1893504",{"doi":201,"openalex_id":203,"authors":204,"venue":118,"cited_by_count":35,"oa_url":185,"card":216,"direction":43,"ingested_from":111},"W7213536926",[205,207,209,212,214],{"name":206,"orcid":8},"Ren Zhou",{"name":208,"orcid":8},"Cancan Zhang",{"name":210,"orcid":211},"Jingbo Li","https:\u002F\u002Forcid.org\u002F0000-0001-5960-806X",{"name":213,"orcid":8},"Yao MengYuan",{"name":215,"orcid":8},"Long Fan",{"tldr":217,"method":135,"finding":218,"direction":43,"opportunity":219},"基于CRRS数据实证检验数字乡村参与对农村居民幸福感的影响及异质性。","数字乡村参与提升幸福感，通过缓解信贷约束和增加社交互动，但经济数字化不显著。","可探究数字素养门槛下数字乡村参与对幸福感的非均衡影响及弥合数字鸿沟的干预路径。","2026-09-19T23:30:45.100468Z"]