[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-542":3,"related-542":64},{"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":23,"tags":25,"primary_topic":8,"secondary_topics":34,"classification":35,"search_phrases":58,"slug":61,"view_count":62,"doi":8,"paper":8,"created_at":63},542,"Can the Digital Economy Enhance the Export Competitiveness of Agricultural Products? — An Empirical Analysis Based on Panel Data from 30 Chinese Provinces","https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8280","基于 2014—2023 年中国 30 个省份面板数据,采用双向固定效应模型考察数字经济与农产品出口竞争力的关系,并用中介效应模型与门槛效应模型揭示机制与非线性。结果显示数字经济显著正向提升农产品出口竞争力;农业产业结构升级、农业技术创新、农业劳动力转移构成三条中介路径;效应在中部地区与粮食主产区更强,且呈非线性关系。文章为强化数字基础设施、培育农业数字人才与优化要素配置以释放数字经济潜力提供了政策依据。",null,"## 1. Introduction\n\nAs the new generation of information technology revolution—represented by big data, artificial intelligence, and the Internet of Things—sweeps across the globe, the digital economy is reshaping the landscape and trajectory of the world economy, becoming a core engine driving global economic recovery and growth [[1](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8280#B1-sustainability-18-08280)]. In recent years, China has attached great importance to the enabling role of the digital economy in agriculture, successively issuing guiding documents such as the Strategic Outline for the Development of Digital Villages and the Digital Rural Agricultural Development Plan (2022–2025). Against this backdrop, China’s agricultural economy has achieved leapfrog development. However, according to data published in the China Agricultural Products Import and Export Annual Statistical Report, China’s agricultural product imports reached as high as USD 215.16 billion in 2024, while exports amounted to only USD 103.01 billion, resulting in a trade deficit of USD 112.15 billion—nearly double that of 2018. This indicates that China’s agricultural products have a high degree of external dependence, and the prospects for export trade and international competitiveness remain far from optimistic. Moreover, as modern agricultural production transitions from a phase prioritizing output to one prioritizing quality, people have placed higher demands on the quality of agricultural products. The contradiction between the traditional low-value-added agricultural production structure and the international consumer market has become increasingly prominent [[2](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8280#B2-sustainability-18-08280)], severely hindering the realization of China’s strategic goal of transforming from a “large trading nation” to a “strong trading nation.” Therefore, how to harness the disruptive force of the digital economy to enable the high-quality development of agricultural product exports—and to solve the long-standing problems of low value addition, information asymmetry, and tightening environmental constraints, thereby building sustained and stable international competitive advantages—has become a major issue of both theoretical value and practical significance.\n\n## 2. Literature Review\n\n### 2.1. Research on the Digital Economy\n\nSince Tapscott (1996) [[3](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8280#B3-sustainability-18-08280)] introduced the concept of the “digital economy,” its core has consistently revolved around the restructuring of information generation, transmission, and processing methods through digital forms, aiming to enhance efficiency and reduce transaction costs (Ren and He, 2022) [[4](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8280#B4-sustainability-18-08280)]. The digital economy is essentially a structural transformation resulting from the deep embedding of digital technologies into various sectors of the national economy, manifesting as a new economic form characterized by digital infrastructure as the foundation, digital platforms as the carrier, and data elements as the core driving force (Xu and Zhang, 2020) [[5](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8280#B5-sustainability-18-08280)]. The G20 Digital Economy Development and Cooperation Initiative identifies digitized knowledge and information as key factors of production, a definition that has been widely adopted.\n\nDue to differences in statistical calibers and the virtuality and high permeability of the digital economy (Wen et al., 2019) [[6](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8280#B6-sustainability-18-08280)], there is no unified methodology for its measurement, and it faces technical constraints. Existing research primarily follows two paradigms: calculating value added based on national economic accounting, and constructing multi-dimensional indicator systems for comprehensive evaluation. Domestic studies predominantly adopt the comprehensive index method, such as Guan et al. (2020) constructing a provincial-level evaluation system [[7](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8280#B7-sustainability-18-08280)]; the Digital Financial Inclusion Index (Guo et al., 2020) is also widely used [[8](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8280#B8-sustainability-18-08280)]. Indicator weighting generally employs the entropy method or principal component analysis (Zhang and Ye, 2017) [[9](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8280#B9-sustainability-18-08280)]. This paper, referencing existing studies and considering the specific implementation pathways of agricultural digitization, constructs an indicator system from three dimensions: digital infrastructure, digital industrialization, and industrial digitization.\n\n### 2.2. Research on the Export Competitiveness of Agricultural Products\n\nThe measurement methods for the export competitiveness of agricultural products mainly include the Diamond Model, the Constant Market Share Model, and comprehensive evaluation indicator systems. International market share, Revealed Comparative Advantage index, and Trade Competitiveness index are widely adopted (Pan et al., 2021) [[10](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8280#B10-sustainability-18-08280)]. In terms of measurement results, Yu et al. (2016) found that China’s exports to South Asia are at a disadvantage [[11](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8280#B11-sustainability-18-08280)]; Yang and Tian (2022), through a comparison among China, Japan, and South Korea, found that China’s exports are primarily low- and medium-technology products [[12](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8280#B12-sustainability-18-08280)]; Shuai et al. (2003) pointed out that while exports are growing, competitiveness is weakening [[13](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8280#B13-sustainability-18-08280)]; in terms of product categories, vegetables and fruits outperform grains (Mao and Feng, 2007) [[14](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8280#B14-sustainability-18-08280)]. Regarding influencing factors, the marginal contribution of traditional factors is diminishing, while the enabling effects of modern factors such as technology, information, and data are becoming prominent (Wu et al., 2023) [[15](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8280#B15-sustainability-18-08280)]. Trade policy adjustments exert significant impacts (Narayan and Bhattacharya, 2019) [[16](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8280#B16-sustainability-18-08280)], and technological progress is a key pathway (Li and Ding, 2016) [[17](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8280#B17-sustainability-18-08280)]. Although it may increase production costs in the short term, it has a significant positive promoting effect in the long run (Zhang and Hu, 2013) [[18](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8280#B18-sustainability-18-08280)]. Upon reviewing the relevant literature, it is evident that existing studies primarily analyze the impact mechanisms of agricultural product exports through their constituent elements, lacking research that incorporates the digital economy, influencing factors, and conditional factors into a unified analytical framework.\n\n### 2.3. Research on the Impact of the Digital Economy on the Export Competitiveness of Agricultural Products\n\nExisting studies have focused on the promoting role of digital tools in agricultural trade. Fan (2020) found that Internet popularization can shorten customs clearance time and reduce costs [[19](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8280#B19-sustainability-18-08280)]; Tang and Li (2023) found that digital trade platforms can generate positive incentives [[20](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8280#B20-sustainability-18-08280)]; Carlos Arnade (2017) found that digital platforms can reduce fixed entry costs for exports [[21](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8280#B21-sustainability-18-08280)]; Qi et al. (2023) found that networked sales platforms can enhance production and sales efficiency [[22](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8280#B22-sustainability-18-08280)]. However, most of these studies analyze the digital economy as a whole variable, with fewer conducting differentiated internal structural tests. In terms of transmission pathways, Zhu et al. (2019) confirmed that informatization levels have a positive impact on agricultural total factor productivity [[23](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8280#B23-sustainability-18-08280)]; Ma et al. (2019) confirmed that digital platforms can reduce agricultural product transaction costs [[24](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8280#B24-sustainability-18-08280)]; Bai and Huang (2021) argued that digital platforms can generate quality premiums for agricultural products [[25](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8280#B25-sustainability-18-08280)].\n\nAlthough the existing literature on the digital economy enabling agricultural product exports provides valuable insights, certain limitations remain: a lack of research incorporating the digital economy, mediation mechanisms, and threshold effects into a unified framework; and insufficient systematic testing of regional differences and conditional factors. Future research needs to integrate threshold effect models with regional heterogeneity analysis to deeply reveal the differentiated characteristics and threshold conditions of the digital economy in enabling the export competitiveness of agricultural products.\n\nA review of the existing literature reveals that previous studies have left room for further exploration in the following aspects: (1) Most studies have focused on the linear association between the digital economy and agricultural trade, with few embedding it within a unified analytical framework of “influencing factors—transmission pathways—boundary conditions” to examine its indirect mechanisms and nonlinear characteristics. (2) Discussions on regional heterogeneity have largely been confined to mean comparisons across the eastern, central, and western macro-regions, lacking a nuanced examination of structural dimensions in agricultural production, such as grain functional zones. (3) Constrained by the narrowness of research perspectives, few studies have integrated mediation mechanisms and threshold effects into a coherent empirical framework, making it difficult to comprehensively uncover the “black box” of how the digital economy is associated with agricultural export competitiveness.\n\nAccordingly, the marginal contributions of this paper are threefold. First, we construct a multiple-mediation framework of “digital economy → (industrial structure upgrading\u002Ftechnological innovation\u002Flabor transfer) → agricultural export competitiveness,” thereby opening the “black box” of the transmission pathways through which the digital economy is associated with export competitiveness. Second, we introduce trade openness as a threshold variable to reveal the “nonlinear leap” in this association as external market conditions evolve. Third, we conduct heterogeneity analyses from both geographic regional and grain functional zone perspectives, providing more granular empirical evidence for differentiated policy design. These three contributions together constitute the incremental value of this paper relative to the existing literature, helping to deepen the systematic understanding of the relationship between the digital economy and agricultural trade, while offering an extensible analytical framework for future research.\n\n## 3. Theoretical Analysis and Research Hypotheses\n\n### 3.1. The Direct Impact of the Digital Economy on the Export Competitiveness of Agricultural Products\n\nAgainst the backdrop of the rapid penetration of agricultural digitization, the digital economy has become an endogenous driving force for rural economic development. Its direct impact on the export competitiveness of agricultural products is primarily reflected in the following three aspects: (1) In agricultural production, the digital economy can promote the intelligent, intensive, and precise development of traditional agriculture [[26](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8280#B26-sustainability-18-08280)]. Internet of Things technologies, characterized by information perception, can accurately and promptly collect agricultural production data, enabling farmers to extract effective information from production data and achieve precise regulation of agricultural production. Meanwhile, the digital economy enhances the level of agricultural mechanization and automation, greatly improving production efficiency, reducing labor intensity and production costs, and ensuring the stability and consistency of agricultural product quality. (2) In agricultural capital circulation, the digital economy effectively alleviates the difficulties of costly and inaccessible financing faced by agricultural production through inclusive finance, mobile payments, and online credit. This enables agricultural enterprises to invest in advanced technologies, equipment, and high-quality inputs, breaking through capital constraints and avoiding agricultural cyclical problems, thereby providing the necessary financial support for enhancing the export competitiveness of agricultural products [[27](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8280#B27-sustainability-18-08280)]. (3) In agricultural product export circulation, the digital economy breaks through traditional temporal and spatial constraints, enabling exporting enterprises to directly reach global consumers and realize a series of trade processes such as online precision marketing, trade negotiations, contract signing, export customs declaration, and inspection and quarantine. Simultaneously, the development of the digital economy enhances market transparency, facilitating farmers and agricultural exporting enterprises to adjust production strategies in a timely manner, changing their status as “price takers” and enhancing their bargaining power in factor and product markets, thereby improving the export competitiveness of agricultural products.\n\nFurthermore, the enhancing effect of the digital economy on the export competitiveness of agricultural products may exhibit heterogeneity. First, provinces (municipalities) in different geographical locations differ in terms of policy support and resource allocation. The eastern and central regions tend to receive more policy support and resource allocation, helping them establish more comprehensive infrastructure and service systems in the digital economy field, thereby enhancing the quality and quantity of agricultural products. In contrast, the western region may be at a disadvantage in resource acquisition, facing issues such as digital technology monopolies, imperfect infrastructure, and information trade barriers. However, it may also exhibit unique advantages in agricultural production, operation, and circulation due to shorter decision-making chains and more flexible policy implementation [[28](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8280#B28-sustainability-18-08280)]. Second, different provinces (municipalities) differ in terms of economic development levels and agricultural production modes. Major grain-producing areas typically possess abundant cultivated land resources, comprehensive infrastructure, and mature agricultural production systems, and also frequently benefit from key national policy support, further promoting the enhancing effect of the digital economy on the export competitiveness of agricultural products. Non-major grain-producing areas, constrained by geographical location and other factors, are at a disadvantage in terms of production scale, industrial structure, and product quality [[29](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8280#B29-sustainability-18-08280)]. Based on this, this paper proposes the following hypothesis:\n\n**H1.**\n\nThe digital economy can enhance the export competitiveness of agricultural products, and this enhancing effect exhibits regional heterogeneity.\n\n### 3.2. Transmission Mechanisms of the Digital Economy’s Impact on the Export Competitiveness of Agricultural Products\n\nThe digital economy can indirectly enhance the export competitiveness of agricultural products through three pathways: upgrading of the agricultural industrial structure, agricultural technological innovation, and agricultural labor transfer.\n\nFirst, there is a positive synergistic relationship with the upgrading of agricultural industrial structure. The digital economy enhances the efficiency of information allocation, strengthens the market’s regulatory capacity over agricultural factors, alleviates information gaps between producers and consumers, reduces factor misallocation, and promotes the coordinated development of various sub-sectors within agriculture, laying the foundation for the rationalization of the industrial structure. Meanwhile, the deep application of technologies such as the Internet of Things and big data drives the entire agricultural industry chain toward digital and intelligent evolution, breaks down traditional industrial barriers, fosters the development of new business forms, and promotes the upgrading of agriculture toward high value addition. The rationalization and upgrading of the industrial structure jointly provide solid support for the export competitiveness of agricultural products.\n\nSecond, there is a statistically positive association with the enhancement of agricultural technological innovation. The digital economy reduces the costs of information acquisition and transactions for technological innovation, enabling innovation entities to more conveniently access cutting-edge technologies and market dynamics. Digital village construction enhances the digital literacy of agricultural practitioners and promotes the implementation and transformation of technological innovation outcomes. Technological innovation, on the one hand, enhances the level of agricultural mechanization, automation, and intelligence, strengthens the synergy among various industries, and promotes the evolution of agricultural product exports toward higher quality; on the other hand, it extends the industrial chain, promotes the transformation of agricultural products toward deep processing and high value addition, and significantly enhances their international market competitiveness.\n\nThird, there is a statistically positive association with the expansion of agricultural labor transfer. Digital technologies break down information barriers in the labor market and reduce job search costs. Flexible employment opportunities provided by Internet platforms accelerate the transfer of agricultural labor to non-agricultural sectors. Meanwhile, new business forms fostered by the digital economy create abundant employment demand, promote the optimal allocation of production factors, and enhance agricultural production efficiency. The income growth effect brought by labor transfer, through the income elasticity mechanism, stimulates the upgrading of agricultural product consumption, indirectly promoting the evolution of the agricultural industrial structure toward high value addition and enhancing export competitiveness.\n\nIn summary, this paper proposes hypothesis H2: The digital economy indirectly enhances the export competitiveness of agricultural products by promoting the upgrading of the agricultural industrial structure, stimulating agricultural technological innovation, and facilitating labor transfer. Based on this, this paper proposes the following hypothesis:\n\n**H2.**\n\nThe digital economy enhances the export competitiveness of agricultural products by promoting the upgrading of the agricultural industrial structure, stimulating agricultural technological innovation, and facilitating labor transfer.\n\n### 3.3. Nonlinear Impact of the Digital Economy on the Export Competitiveness of Agricultural Products\n\nThe improvement of China’s agricultural product export competitiveness is not only related to the level of digital economy development but ","Sustainability","2026-08-11T22:00:00Z","论文",10,false,72,{"impact":17,"substance":18,"depth":17,"authority":19,"freshness":20,"relevant":21,"comment":22},18,22,12,2,1,"基于省级面板数据的实证研究，探讨数字经济对农产品出口竞争力的影响，数据详实，结论有参考价值，但时效性较低。",[24],{"name":10,"url":6},[26,27,28,29,30,31,32,33],"数字乡村","乡村振兴","数字经济","中介效应","门槛效应","农产品出口","农业产业结构","中国30省",[],{"status":36,"locked":14,"version":37,"method":38,"evidence":39},"unclassified","2026-10-22.2","rules",{"candidates":40,"agricultural_evidence":56,"reason":57},[41,46,51],{"code":42,"score":20,"supported":14,"title":43,"abstract":44,"tags":45},"I6",[],[],[26,28],{"code":47,"score":21,"supported":14,"title":48,"abstract":49,"tags":50},"E5",[],[],[31],{"code":52,"score":21,"supported":14,"title":53,"abstract":54,"tags":55},"G",[],[],[27],true,"缺少足够的主题证据",[59,60],"农业产业结构 农产品出口 中介效应 乡村振兴","农业产业结构 农产品出口","农业产业结构农产品出口中介效应乡村振兴-542",8,"2026-08-15T00:02:55.799820Z",{"total":65,"page":21,"page_size":65,"items":66},6,[67,122,170,235,294,341],{"id":68,"title":69,"url":70,"summary":71,"summary_zh":8,"content":72,"source_name":73,"source_url":8,"published_at":74,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":75,"score_detail":76,"sources":80,"tags":82,"primary_topic":8,"secondary_topics":87,"classification":88,"search_phrases":116,"slug":119,"view_count":65,"doi":120,"paper":8,"created_at":121},544,"电商对城乡融合发展的影响效应与路径分析","https:\u002F\u002Flxbwk.njournal.sdu.edu.cn\u002FCN\u002F10.6040\u002Fj.issn.1671-9352.0.2025.343","本研究构建电商-产业-城乡发展逻辑分析框架,综合评价指标体系测度山东省 16 个地级市 2014—2023 年城乡融合发展水平,并以中介效应模型检验电商发展的影响效应。研究显示,山东省城乡融合发展水平总体上升,但存在多维差异,经济融合与生态融合为主要增长动力;中介效应检验表明,电商发展能够显著促进城乡融合,并通过产业结构升级的部分中介效应实现,中介效应占比 48.7%。","[1] 邱志萍,姚婷婷. 电子商务“双试点”政策对区域经济差距的影响研究[J]. 兰州学刊, 2024(12): 46-63. 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Boosting rural vitality: exploring pathways for county-level urban-rural integration to promote comprehensive rural revitalization[J]. Study & Exploration, 2025(2): 13-22.\n\n[9] Cheng Yu, et al. The impact of the urban digital economy on Chinas carbon intensity: spatial spillover and mediating effect[J]. Resources, Conservation and Recycling, 2023, 189: 106762.\n\n[10] 林聚任. 新城乡空间重构与城乡融合发展[J]. 山东大学学报(哲学社会科学版), 2022(1): 72-81. Lin Juren. New urban-rural space reconstruction and urban-rural integration development[J]. Journal of Shandong University(Philosophy and Social Sciences), 2022(1): 72-81.\n\n[11] Yi Jiahui. How does digital economy development affect renewable energy innovation[J]. Renewable and Sustainable Energy Reviews, 2024, 192: 114221.\n\n[12] 周广亮,翟晓格,张迪. 数字经济赋能城乡融合的空间逻辑与实践方略: 基于空间社会学的考量[J]. 郑州大学学报(哲学社会科学版), 2025, 58(2): 22-27. Zhou Guangliang, Zhai Xiaoge, Zhang Di. The spatial logic and practical strategy of digital economy empowering urban-rural integration: based on the consideration of spatial sociology[J]. Journal of Zhengzhou University(Philosophy and Social Sciences), 2025, 58(2): 22-27.\n\n[13] 郭亮亮,林永然. 农村公共服务高质量发展赋能乡村振兴的作用机制研究[J]. 数学的实践与认识, 2025, 55(8): 69-81. Guo Liangliang, Lin Yongran. Research on the mechanism of empowering rural revitalization with high quality development of rural public services[J]. Mathematics in Practice and Theory, 2025, 55(8): 69-81.\n\n[14] 何亚芬,潘依玲,谢花林. 生态产品价值实现与乡村文化振兴双向赋能的机制与路径: 基于“人-文-术-业-制”五维协同视角[J]. 自然资源学报, 2025, 40(11): 2979-2998. He Yafen, Pan Yiling, Xie Hualin. The mechanism and pathway of bidirectional empowerment between value realization of ecological products and rural cultural revitalization: based on the \"human-culture-technology-industry-institution\" five-dimensional synergy perspective[J]. Journal of Natural Resources, 2025, 40(11): 2979-2998.\n\n[15] 金文成,王霞,何安华. 推进城乡融合发展: 经验、 挑战及对策[J]. 农业经济问题, 2025(2): 4-14. Jin Wencheng, Wang Xia, He Anhua. Promoting integrated urban-rural development: experience, challenges, and responses[J]. Issues in Agricultural Economy, 2025(2): 4-14.\n\n[16] 张子珍,邢赵婷. 数字经济下城乡融合系统高质量协调发展核心内涵及动态演化研究[J]. 统计与信息论坛, 2023, 38(3): 84-96. Zhang Zizhen, Xing Zhaoting. Study on the core connotation and dynamic evolution of high-quality coordinated development of urban-rural integration system under digital economy[J]. Statistics & Information Forum, 2023, 38(3): 84-96.\n\n[17] Sun Bing. Impact of digital finance on energy-based carbon intensity: evidence from mediating effects perspective[J]. Journal of Environmental Management, 2023, 327: 116832.\n\n[18] 李利华,曹梦,谭乐怡,等. 区域物流空间网络结构演变与作用机制: 以湖南省为例[J]. 经济地理, 2025, 45(8): 139-151. Li Lihua, Cao Meng, Tan Leyi, et al. Evolution and mechanism of regional logistics spatial network structure: a case study of Hunan Province[J]. Economic Geography, 2025, 45(8): 139-151.\n\n[19] 郭锦墉,刘晓婧,赖萍. 社区电商对农村家庭消费结构的影响[J]. 商业经济研究, 2025(7): 88-92. Guo Jinyong, Liu Xiaojing, Lai Ping. The impact of community e-commerce on rural household consumption structure[J]. Journal of Commercial Economics, 2025(7): 88-92.\n\n[20] 程明,方青. 乡村振兴与新型城镇化战略耦合机理研究: 基于城乡要素流动的视角[J]. 华东经济管理, 2023, 37(5): 1-8. Cheng Ming, Fang Qing. Research on the coupling mechanism of rural revitalization and new urbanization strategy: from the perspective of urban-rural factor flow[J]. East China Economic Management, 2023, 37(5): 1-8.\n\n[21] 何茜,温涛,王小华. 农村金融服务创新与农户包容性增收: 基于政府引导和市场主导的双重视角[J]. 金融监管研究, 2025(8): 40-59. He Qian, Wen Tao, Wang Xiaohua. Innovation of rural financial services and inclusive income increase for farmers: a dual perspective based on government guidance and market leadership[J]. Financial Regulation Research, 2025(8): 40-59.\n\n[22] 郭浪,汪兰林,周茜,等. 乡村振兴背景下农村电子商务四方主体演化博弈分析[J]. 数学的实践与认识, 2023, 53(6): 109-119. Guo Lang, Wang Lanlin, Zhou Qian, et al. Evolutionary game analysis of four main bodies in rural e-commerce amidst the backdrop of rural revitalization[J]. Mathematics in Practice and Theory, 2023, 53(6): 109-119.\n\n[23] 徐永辉,吴柏钧. 产业转移、市场潜能与城乡融合: 基于空间杜宾模型的探讨[J]. 技术经济与管理研究, 2023(10): 106-110. Xu Yonghui, Wu Baijun. Industrial transfer, market potential and urban-rural integration: based on spatial Dubin model[J]. Journal of Technical Economics & Management, 2023(10): 106-110.\n\n[24] 郭亚军. 一种新的动态综合评价方法[J]. 管理科学学报, 2002(2): 49-54. Guo Yajun. A new dynamic comprehensive evaluation method[J]. Journal of Management Sciences in China, 2002(2): 49-54.\n\n[25] 钟雨妮,冯健. 互联网使用对农民户籍市民化的影响: 基于新零工经济的中介效应[J]. 地理研究, 2025, 44(6): 1638-1654. Zhong Yuni, Feng Jian. The impact of internet use on the hukou-based citizenization of rural populations: mediating effect of the new gig economy[J]. Geographical Research, 2025, 44(6): 1638-1654.","山东大学学报(理学版)","2026-08-11T16:00:00Z",68,{"impact":77,"substance":17,"depth":78,"authority":19,"freshness":20,"relevant":21,"comment":79},20,16,"论文系统梳理电商对城乡融合的影响，但时效性差，且为文献综述，创新性有限。",[81],{"name":73,"url":70},[83,26,27,29,84,85,86],"农村电商","城乡融合","产业结构升级","省域面板",[],{"status":89,"locked":14,"version":37,"method":38,"evidence":90},"needs_review",{"candidates":91,"agricultural_evidence":14,"reason":115},[92,98,102,106,111],{"code":93,"score":94,"supported":56,"title":95,"abstract":96,"tags":97},"G6",11,[84],[84],[],{"code":47,"score":21,"supported":14,"title":99,"abstract":100,"tags":101},[],[],[83],{"code":52,"score":21,"supported":14,"title":103,"abstract":104,"tags":105},[],[],[27],{"code":107,"score":21,"supported":14,"title":108,"abstract":109,"tags":110},"G5",[],[],[84],{"code":42,"score":21,"supported":14,"title":112,"abstract":113,"tags":114},[],[],[26],"农业相关性需要复核",[117,118],"产业结构升级 中介效应 乡村振兴 农村电商","产业结构升级 中介效应","产业结构升级中介效应乡村振兴农村电商-544","10.6040\u002Fj.issn.1671-9352.0.2025.343","2026-08-15T00:02:55.854188Z",{"id":123,"title":124,"url":125,"summary":126,"summary_zh":8,"content":8,"source_name":127,"source_url":8,"published_at":128,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":129,"score_detail":130,"sources":135,"tags":137,"primary_topic":8,"secondary_topics":141,"classification":142,"search_phrases":154,"slug":157,"view_count":158,"doi":159,"paper":160,"created_at":169},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":78,"substance":131,"depth":17,"authority":132,"freshness":133,"relevant":21,"comment":134},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。",[136],{"name":127,"url":125},[28,138,139,32,140],"农业高质量发展","区域异质性","新疆农业",[],{"status":36,"locked":14,"version":37,"method":38,"evidence":143},{"candidates":144,"agricultural_evidence":56,"reason":57},[145,149],{"code":42,"score":21,"supported":14,"title":146,"abstract":147,"tags":148},[],[],[28],{"code":150,"score":21,"supported":14,"title":151,"abstract":152,"tags":153},"J2",[],[],[138],[155,156],"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":159,"openalex_id":8,"authors":161,"venue":8,"cited_by_count":158,"oa_url":8,"card":162,"direction":166,"ingested_from":168},[],{"tldr":163,"method":164,"finding":165,"direction":166,"opportunity":167},"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":171,"title":172,"url":173,"summary":174,"summary_zh":175,"content":8,"source_name":176,"source_url":173,"published_at":177,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":178,"score_detail":179,"sources":182,"tags":184,"primary_topic":188,"secondary_topics":194,"classification":195,"search_phrases":214,"slug":217,"view_count":20,"doi":218,"paper":219,"created_at":234},4996,"Translating the Visual Language of Jinshan Peasant Painting into Narrative Illustrations of \"New Farmers\": A Design Transformation Study","https:\u002F\u002Fdoi.org\u002F10.54097\u002Fyykkqh83","Jinshan peasant painting is a typical work of modern Chinese folk art. The visual language of Japanese art is flat and exaggerated, with pure colours, whole compositions and strong decorative patterns. Currently, it lacks cultural background and is mainly used by older generations; therefore, it has failed to attract the interest of young people. The research subject is the visual language of Jinshan peasant painting, the narrative theme is \"New Farmers\" for rural revitalization, and the creative medium is narrative illustration; this study will explore how the language of traditional folk painting can be transformed in contemporary design. Based on the literature review and creative practice, the visual grammar of Jinshan peasant painting has been divided into four parts: form, colour, composition and schema; a method of \"visual analysis - feature extraction - design transformation - creative practice\" has been introduced, and six narrative illustrations have been created under the sub-themes of live-streaming for agricultural aid, rural study tours, intangible cultural heritage (ICH) tourism, returning home to start businesses, smart agriculture and the new rural landscape. Therefore, it can be proposed that the visual language of Jinshan peasant painting should be integrated into contemporary narrative illustration to retain its folk aesthetic qualities and strengthen narrativity and communication power, providing a practical model for the living inheritance of intangible cultural heritage and visual representation of rural revitalization.","金山农民画是中国现代民间艺术的典型作品。日本艺术的视觉语言具有平面化、夸张化、色彩纯粹、构图完整、装饰性强等特点。目前，它缺乏文化底蕴，主要受众为年长一代；因此，未能引起年轻人的兴趣。本研究以金山农民画的视觉语言为研究对象，以乡村振兴背景下的“新农民”为叙事主题，以叙事性插画为创作媒介；探讨传统民间绘画语言在当代设计中如何转化。基于文献综述与创作实践，将金山农民画的视觉语法分为造型、色彩、构图和图式四个部分；引入“视觉分析—特征提取—设计转化—创作实践”的方法，并在助农直播、乡村研学、非遗旅游、返乡创业、智慧农业和新农村景观六个子主题下创作了六幅叙事性插画。因此，可以提出将金山农民画的视觉语言融入当代叙事性插画，以保留其民间美学特质并强化叙事性与传播力，为非物质文化遗产的活态传承与乡村振兴的视觉表征提供实践范式。","Highlights in Art and Design","2026-10-13T00:00:00Z",58,{"impact":62,"substance":17,"depth":180,"authority":133,"freshness":62,"relevant":21,"comment":181},15,"以金山农民画视觉语言转化为新农人叙事插画的设计研究，方法清晰、案例具体，对非遗活态传承与乡村文化数字化表达有参考价值，但属艺术设计领域，产业影响有限。",[183],{"name":176,"url":173},[26,185,27,186,187],"智慧农业","金山农民画","非遗传承",{"code":189,"slug":190,"name":191,"path":192,"parent_code":193},"I1","smart-agriculture","智慧农业总论","\u002Ftopic\u002Fdigital-agriculture\u002Fsmart-agriculture","I",[],{"status":196,"locked":14,"version":37,"method":38,"evidence":197},"classified",{"candidates":198,"agricultural_evidence":56},[199,205,210],{"code":189,"score":200,"supported":56,"title":201,"abstract":202,"tags":204},7,[],[185,203],"smart agriculture",[185],{"code":52,"score":206,"supported":56,"title":207,"abstract":208,"tags":209},4,[],[27],[27],{"code":42,"score":21,"supported":14,"title":211,"abstract":212,"tags":213},[],[],[26],[215,216],"金山农民画 新农人 叙事插画","金山农民画 乡村振兴 数字乡村 智慧农业","金山农民画新农人叙事插画-4996","10.54097\u002Fyykkqh83",{"doi":218,"openalex_id":220,"authors":221,"venue":176,"cited_by_count":158,"oa_url":173,"card":227,"direction":232,"ingested_from":233},"W7221788564",[222,225],{"name":223,"orcid":224},"L. Zeng","https:\u002F\u002Forcid.org\u002F0009-0008-1316-3892",{"name":226,"orcid":8},"Lin Zhu",{"tldr":228,"method":229,"finding":230,"direction":166,"opportunity":231},"将金山农民画视觉语言转化为新农人叙事插画，探索传统民艺当代设计转化。","文献综述与创作实践，按形式、色彩、构图、图式四部分提取视觉语法。","金山农民画融入当代叙事插画可保留民俗美学并增强叙事与传播力。","可结合数字媒体与交互设计，探索非遗视觉语言在智慧农业传播中的动态化与年轻化应用。","智慧农业 \u002F 农业物联网","openalex","2026-10-15T23:30:11.729940Z",{"id":236,"title":237,"url":238,"summary":239,"summary_zh":8,"content":8,"source_name":240,"source_url":8,"published_at":241,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":242,"score_detail":243,"sources":247,"tags":249,"primary_topic":252,"secondary_topics":256,"classification":257,"search_phrases":282,"slug":285,"view_count":206,"doi":8,"paper":286,"created_at":293},4782,"农户参与电子商务能否促进共同富裕——来自中国10省农户调查数据的经验证据","https:\u002F\u002Fwww.ebiotrade.com\u002Fnewsf\u002F2026-10\u002F20261008084343175.htm","基于2020年中国乡村振兴综合调查CRRS数据,使用10省2508个农户样本实证检验农户参与电子商务对共同富裕的影响。基准回归及PSM、Tobit、IV等稳健性检验均显示显著促进效应。中部地区估计效应最大,对低收入家庭和低教育家庭估计效应更大,机制主要通过提升农村信贷可得性、增强信息获取能力两条路径实现。","生物通 报道 MDPI Agriculture 2026-10-08","2026-10-08T00:00:00Z",82,{"impact":18,"substance":244,"depth":17,"authority":245,"freshness":65,"relevant":21,"comment":246},23,13,"基于10省2508户调查数据的实证研究，方法规范、结论可靠，对数字乡村与农村电商政策有参考价值。",[248],{"name":240,"url":238},[83,26,27,250,251],"共同富裕","农户增收",{"code":52,"slug":253,"name":254,"path":255,"parent_code":8},"rural-services","农业服务与乡村发展","\u002Ftopic\u002Frural-services",[],{"status":258,"locked":14,"version":37,"method":38,"evidence":259},"partial",{"candidates":260,"agricultural_evidence":56},[261,265,269,274,278],{"code":52,"score":206,"supported":56,"title":262,"abstract":263,"tags":264},[],[27],[27],{"code":47,"score":21,"supported":14,"title":266,"abstract":267,"tags":268},[],[],[83],{"code":270,"score":21,"supported":14,"title":271,"abstract":272,"tags":273},"G4",[],[],[250],{"code":93,"score":21,"supported":14,"title":275,"abstract":276,"tags":277},[],[],[251],{"code":42,"score":21,"supported":14,"title":279,"abstract":280,"tags":281},[],[],[26],[283,284],"CRRS 农户调查 电子商务","农村电商 共同富裕 农户","CRRS农户调查电子商务-4782",{"doi":8,"openalex_id":8,"authors":287,"venue":8,"cited_by_count":158,"oa_url":8,"card":288,"direction":166,"ingested_from":168},[],{"tldr":289,"method":290,"finding":291,"direction":166,"opportunity":292},"基于10省2508户调查数据，实证检验农户参与电商对共同富裕的促进效应。","使用2020年CRRS数据，采用PSM、Tobit、IV等回归方法。","电商显著促进共同富裕，中部效应最大，对低收入和低教育家庭更明显。","可探究电商促进共同富裕的长期动态效应及数字鸿沟的调节作用。","2026-10-13T00:08:38.266069Z",{"id":295,"title":296,"url":297,"summary":298,"summary_zh":8,"content":8,"source_name":299,"source_url":8,"published_at":300,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":301,"score_detail":302,"sources":304,"tags":306,"primary_topic":310,"secondary_topics":311,"classification":312,"search_phrases":329,"slug":332,"view_count":316,"doi":8,"paper":333,"created_at":340},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",80,{"impact":17,"substance":18,"depth":17,"authority":132,"freshness":62,"relevant":21,"comment":303},"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。",[305],{"name":299,"url":297},[26,28,307,308,309],"粮食主产区","粮食生产韧性","农业技术创新",{"code":52,"slug":253,"name":254,"path":255,"parent_code":8},[],{"status":258,"locked":14,"version":37,"method":38,"evidence":313},{"candidates":314,"agricultural_evidence":56},[315,320,325],{"code":52,"score":316,"supported":56,"title":317,"abstract":318,"tags":319},3,[],[27],[],{"code":321,"score":20,"supported":14,"title":322,"abstract":323,"tags":324},"A8",[],[],[307,308],{"code":42,"score":20,"supported":14,"title":326,"abstract":327,"tags":328},[],[],[26,28],[330,331],"数字经济 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