[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-1189":3,"related-1189":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":30,"secondary_topics":36,"classification":37,"search_phrases":55,"slug":58,"view_count":21,"doi":8,"paper":59,"created_at":63},1189,"Spatio-Temporal Differentiation and Impediments to Agricultural and Rural Modernization Under Regional Coordination: Based on Three Major Economic Circles in Shandong Province (区域协调下农业农村现代化的时空分异与障碍因素:基于山东省三大经济圈)","https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F17\u002F8904","MDPI Sustainability 2026, 18(17), 8904, 2026年8月31日发表,作者来自山东农业大学经济管理学院。基于山东省16市2014—2023年面板数据,采用GMI和LMI模型研究三大经济圈时空演变和空间相关性;Dagum系数分解区域差距;障碍度模型识别关键阻碍因素。山东省农业农村现代化遵循波动但快速增长轨迹,具有明显空间等级:胶东>鲁南>省会。空间聚集类型HH和LL主要出现在胶东和鲁南;类型HL的空间异常值包括德州、济南和济宁,LH类型特征的是日照和东垦。山东省农业农村现代化的持续约束因素包括水土流失综合治理水平、农村社区治理支出、农产品产业化水平和农产品地理标志;水土流失综合治理水平是三大经济圈的共同障碍因素。",null,"## 1. Introduction\n\nModernizing agriculture and rural areas is central to the broader advancement and quality of Chinese modernization. As the principal aim of the rural revitalization strategy, its development trajectory has long shown pronounced spatial non-equilibrium characteristics [[1](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F17\u002F8904#B1-sustainability-18-08904)]. In response, the central “No. 1 Document” of 2026 proposed to “promote rural revitalization in an orderly and zoned manner by category”, providing top-level design and strategic planning for the coordinated regional development of agricultural and rural modernization. Existing research indicates that, since the implementation of China’s regional development strategy, regional disparities in agricultural and rural modernization have narrowed; however, regional development remains unbalanced and inadequate [[2](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F17\u002F8904#B2-sustainability-18-08904)]. Under the regional coordinated development strategy, promoting synchronized regional advancement in agricultural and rural modernization—and shifting from isolated, point-like initiatives to zonal, integrated planning—is crucial for steadily advancing comprehensive rural revitalization [[3](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F17\u002F8904#B3-sustainability-18-08904),[4](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F17\u002F8904#B4-sustainability-18-08904)]. The “Comprehensive Rural Revitalization Plan (2024–2027)” issued by the Central Committee of the Communist Party of China and the State Council in 2025 calls for coordinating different regions and defining phased key tasks and their implementation sequence. Promoting coordinated regional development of agricultural and rural modernization is therefore essential: it improves resource allocation efficiency, addresses shortfalls in agricultural and rural sectors, and is the only viable path to steady, comprehensive rural revitalization.\n\nConstructing a scientific evaluation index system is a prerequisite for accurately measuring and comprehensively analyzing the development level of regional agricultural and rural modernization. Existing studies typically treat agricultural and rural modernization as an integrated whole, in which agricultural modernization and rural modernization are coupled, coexist and interact in a coordinated manner [[5](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F17\u002F8904#B5-sustainability-18-08904),[6](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F17\u002F8904#B6-sustainability-18-08904)]. Some researchers, however, classified agricultural modernization as an industrial category and constructed its indicator system around goals such as ensuring the effective supply of key agricultural products and promoting the upgrading and sustainable development of the agricultural industrial structure [[7](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F17\u002F8904#B7-sustainability-18-08904)]. By contrast, rural modernization is framed at the regional level and assessed through dimensions such as rural economic development, cultural construction, living environment, infrastructure and governance capacity [[8](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F17\u002F8904#B8-sustainability-18-08904)]. Agricultural modernization primarily addressed rural productive forces, whereas rural modernization concerned rural production relations. The dialectic between these forces and relations therefore implied that agricultural modernization was the foundation and prerequisite for rural modernization, while rural modernization provided support and backing for agricultural modernization [[9](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F17\u002F8904#B9-sustainability-18-08904)]. As the literature has deepened, some scholars have added a third dimension—farmers’ modernization—to indicator systems, incorporating measures of farmers’ income, consumption and urban–rural disparities [[10](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F17\u002F8904#B10-sustainability-18-08904),[11](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F17\u002F8904#B11-sustainability-18-08904)].\n\nClarifying regional development disparities and identifying their driving factors are key to reducing imbalances in the regional modernization of agriculture and rural areas. Most existing studies of regional differences began at the national level or focused on a single province. They divided areas with similar geographical characteristics and then used spatial models such as SAR, SEM, and SDM to examine the spatial spillover effects of agricultural and rural modernization in each region [[12](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F17\u002F8904#B12-sustainability-18-08904),[13](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F17\u002F8904#B13-sustainability-18-08904),[14](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F17\u002F8904#B14-sustainability-18-08904)]. Some studies have shown that areas with advanced agricultural and rural modernization and those with high economic development are spatially coupled to some extent. Moreover, coordinated regional development has been able to raise the modernization level of agriculture and rural areas in less-developed regions [[15](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F17\u002F8904#B15-sustainability-18-08904),[16](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F17\u002F8904#B16-sustainability-18-08904)]. However, economic connectivity and governance coordination, the two pillars of regional coordinated development [[17](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F17\u002F8904#B17-sustainability-18-08904)], struggle to fulfill their roles because of constraints imposed by administrative divisions and geographical boundaries. Research into the factors influencing agricultural and rural modernization has principally been conducted along two lines of enquiry: internal constraints and external drivers. Concerning internal constraints, scholars have predominantly employed the obstacle degree model; by measuring indices such as factor contribution, index deviation and obstacle degree, they have identified the primary barriers to agricultural and rural modernization across different regions [[18](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F17\u002F8904#B18-sustainability-18-08904),[19](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F17\u002F8904#B19-sustainability-18-08904),[20](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F17\u002F8904#B20-sustainability-18-08904)]. Concerning external drivers, studies have concentrated on three domains—fiscal input, human capital and digital technology—and have used bidirectional fixed-effects and mediating-effect models to elucidate how these drivers have acted on the modernization of agriculture and rural areas [[21](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F17\u002F8904#B21-sustainability-18-08904),[22](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F17\u002F8904#B22-sustainability-18-08904)].\n\nExisting research has laid a solid theoretical foundation for this paper. However, most of the current studies on the modernization development level of agriculture and rural areas in Shandong have focused on the provincial scale or a single city [[23](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F17\u002F8904#B23-sustainability-18-08904),[24](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F17\u002F8904#B24-sustainability-18-08904)]. In 2020, Shandong explicitly proposed implementing a regional development strategy centered on three major economic circles of the Provincial Capital, Jiaodong, and Lunan, which is an important institutional measure to promote coordinated development across the province. As a new spatial form of urbanization, the economic circle has been proven to promote regional coordinated development and urban–rural integration [[25](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F17\u002F8904#B25-sustainability-18-08904)]. Its collaborative principle of dismantling administrative barriers and integrating regional resources plays a vital supporting role in the coordinated development of agricultural and rural modernization in Shandong, and provides a crucial spatial scale for regions to assess their development positioning. However, most studies of agricultural and rural modernization analyzed development levels and spatio-temporal evolution at the national or provincial scale. Few examined horizontal comparisons of regional spatial correlations, the sources of structural differences, or the hindering factors. To fill this gap, this paper selected the three major economic circles in Shandong Province as the spatial unit and adopted a horizontal perspective. We applied the GMI and LMI statistics, the Dagum coefficient, and an obstacle degree model to conduct multidimensional comparative analyses of spatial correlation effects, the structure of regional differences, and obstacle factors. The study aimed to provide theoretical support and policy guidance for promoting coordinated agricultural and rural modernization across Shandong’s three economic circles.\n\n## 2. Methodology and Index Selection\n\n### 2.1. Model Construction\n\n#### 2.1.1. Multi-Index Comprehensive Measurement\n\nThis study adopted the Critic weight analysis method to assign weights to the indicators, quantifying the contribution of the indicators to the evaluation system and avoiding the bias of subjective weighting. The scores of the modernization development levels of agriculture and rural areas in Shandong, the three major economic circles and 16 prefecture-level cities were obtained by using the multiple linear weighting method.\n\nThe formula for calculating the score of the STH element is:\n\n$$\nQ_{s} = \\sum_{j = 1}^{m} X_{ij}^{'} \\times w_{j}\n$$\n\n(1)\n\nIn this specification,\n\n$X_{ij}^{'}$\ndenotes the value of the original data after standardization by the extreme value method,\n\n$w_{j}$\nis the weight of the corresponding indicator,\n\n$Q_{s}$\nis the comprehensive score of the STH element, and m is the total number of indicators covered by this element. The formula for the total score (G) of the modernization level of agriculture and rural areas is:\n\n$$\nG = \\sum_{s = 1}^{3} Q_{s}\n$$\n\n(2)\n\n#### 2.1.2. GMI and LMI\n\nTo analyze the spatial dependence or differences in the modernization levels of agriculture and rural areas among neighboring cities, this study calculated the global and local autocorrelation degrees through the GMI and the LMI.\n\nTo reveal the local spatial agglomeration pattern, the distribution of abnormal states, and their significance, this study further combined the Moran scatter plot with the LISA value. The calculation formulas for GMI and LMI are respectively:\n\n$$\nG M I = \\frac{\\sum_{i = 1}^{n} \\sum_{j \\neq 1}^{n} \\left[W_{i j} \\left(X_{i} - \\bar{X}\\right) \\left(X_{i} - \\bar{X}\\right)\\right]}{S^{2} \\times \\sum_{i = 1}^{n} \\sum_{j \\neq 1}^{n} W_{i j}}\n$$\n\n(3)\n\n$$\nL M I = \\frac{X_{i} - \\bar{X}}{S^{2}} \\sum_{j = 1}^{n} \\left[W_{i j} \\left(W_{i j} - \\bar{X}\\right)\\right]\n$$\n\n(4)\n\nIn the above formula, n represents the total number of spatial units,\n\n$X_{i}$\nand\n\n$X_{j}$\nare respectively the comprehensive evaluation values of the modernization development level of agriculture and rural areas of units,\n\n$\\bar{X}$\nis the average evaluation value of all units,\n\n$S^{2}$\nis their variance, and\n\n$W_{i j}$\nis the spatial weight. When calculating GMI and LMI, the Queen adjacency weight is adopted as the spatial weight to give the significance level. When GMI is positive and approaches 1, the degree of agglomeration is higher. LMI > 0 indicates high-level or low-level city agglomeration, which is represented in the first quadrant (HH) and the third quadrant (LL) in the Moran scatter plot. When GMI is negative and approaches −1, the global variance is higher. LMI \u003C 0 indicates that high levels are surrounded by low-level cities or low levels are surrounded by high-level cities, which are respectively in the 4th quadrant (HL) and the 2nd quadrant (LH) in the Moran scatter plot. If GMI = 0, it indicates that there is no spatial correlation; that is, there is no regular distribution.\n\nThis study conducted tests using standardized Z-values to determine a certain significant level of GMI. The calculation formula is as follows:\n\n$$\nZ = \\left[I - E \\left(I\\right)\\right] \u002F V a r \\left(I\\right)\n$$\n\n(5)\n\nIn the above formula, I represents GMI, E(I) and Var(I) respectively represent its mathematical expectation and variance. A significant Z value indicates the occurrence of significant clustering, while a negative Z value indicates the absence of significant clustering.\n\n#### 2.1.3. Dagum Coefficient\n\nMost existing studies used the Theil index, Herfindahl index and Dagum coefficient to explore regional differences. However, the first two cannot reflect the overlapping parts of differences between and within groups. Therefore, this paper used the Dagum coefficient to measure and decompose the differences in the modernization development levels of agriculture and rural areas within and between the three major economic circles in order to explore the sources of the differences. The overall difference was decomposed into three parts: intra-circle difference, inter-circle difference and hypervariable density. The measurement formula of the overall coefficient is:\n\n$$\nG = \\frac{1}{2 n^{2} u} \\sum_{j = 1}^{k} \\sum_{h = 1}^{k} \\sum_{i = 1}^{n_{j}} \\sum_{r = 1}^{n_{k}} \\left|y_{i j} - y_{h r}\\right|\n$$\n\n(6)\n\nIn the formula above, k denotes the quantity of regional groups, specifically the three primary economic circles; n signifies the total spatial units;\n\n$n_{j}$\nand\n\n$n_{h}$\ndenote the spatial unit quantities in the JTH and HTH economic circles correspondingly.\n\n$y_{i j}$\nand\n\n$y_{h r}$\nrespectively stand for the overall scores of the agricultural and rural modernization level of the i-th prefecture-level city in the JTH economic circle and the RTH prefecture-level city in the h-th economic circle. u represents the mean comprehensive score of the agricultural and rural modernization level across all prefecture-level cities.\n\n#### 2.1.4. The Obstacle Degree Model\n\nThe obstacle degree model calculates the obstacle degree for each evaluation index, identifying and analyzing the primary obstacle factors. The model is structured as follows:\n\n$$\nO_{i j} = \\frac{\\left(1 - x_{i j}\\right) w_{j}}{\\sum_{j}^{n} \\left(1 - x_{i j}\\right) w_{j}}\n$$\n\n(7)\n\n$$\nO_{i r} = \\sum_{j = 1}^{q} O_{i r}\n$$\n\n(8)\n\nwhere q denotes the number of indicators;\n\n$1 - X_{i j}$\nrepresents the indicator deviation, signifying the variance between the standardized value\n\n$X_{i j}$\nderived from the extreme value method for each indicator and its optimal goal.\n\n$w_{j}$\nsignifies the indicator’s contribution degree.\n\n$O_{i r}$\nrepresents the final obstacle degree of the RTH element layer or criterion layer of the i-th evaluation object.\n\n### 2.2. Index Selection\n\nDrawing on existing studies [[26](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F17\u002F8904#B26-sustainability-18-08904),[27](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F17\u002F8904#B27-sustainability-18-08904)] and aligned with the central objectives set out in the 2026 Central Document No. 1 to enhance agricultural production, raise farmers’ incomes and improve rural living standards, this study developed a framework with three core dimensions: agricultural modernization, rural modernization and farmers’ welfare. The assessment framework for agricultural and rural modernization comprised eight components and twenty-four specific indicators, detailed in [Table 1](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F17\u002F8904#table_body_display_sustainability-18-08904-t001), with indicators and their rationales given at each level.\n\n**Table 1.** Indicator system for evaluating the level of agricultural and rural modernization.\n\nTo align with green agricultural production and water-saving irrigation goals, the evaluation indicators included fertilizer and pesticide application intensity, water consumption per 10,000 yuan of GDP, and the effective irrigation rate. To promote rural industrial integration, the indicators covered agricultural socialized services, the degree of agricultural product industrialization, geographical indication agricultural products, and adjustments to the rural industrial structure. For rural governance and urban–rural integration, the indicators comprised the level of urbanization, rural community governance, social security, and the equalization of urban–rural health and public services. To support harmonious villages and control soil erosion, the indicators included per capita park green space and a comprehensive soil erosion governance index. Finally, to optimize rural cultural services in line with the Rural Comprehensive Revitalization Plan (2024–2027), the indicators measured cultural and entertainment provision by cultural stations per 10,000 people.\n\n### 2.3. Data Sources\n\nData were compiled from official sources, including statistical yearbooks, bulletins, and government websites for Shandong Province and its 16 prefecture-level cities. Because Laiwu City merged into Jinan City in 2019, Laiwu data for 2014–2018 were merged into Jinan’s records. Minor discrepancies and missing values were resolved by interpolation to maintain dataset continuity and reliability. The calculations reported in [Table 2](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F17\u002F8904#table_body_display_sustainability-18-08904-t002), [Table 3](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F17\u002F8904#table_body_display_sustainability-18-08904-t003) and [Table 4](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F17\u002F8904#table_body_display_sustainability-18-08904-t004) used the official statistical data cited above. To ensure scientific rigor and reliability, we standardized the original data. We applied the extreme-value method to resolve inconsistencies in dimensions, units, scales, and positive–negative attributes, thereby ensuring comparability within a unified framework. We conducted spatial analysis and mapping with ArcGIS 10.8 and decomposed regional differences using the Dagum coefficient method.\n\n**Table 2.** Level of agricultural and rural modernization development in various cities of Shandong Province (2014–2023).\n\n**Table 3.** Overall Moran index for the development level of agricultural and rural modernization in Shandong Province (2014–2023).\n\n**Table 4.** Dagum coefficient and decomposition in Shandong Province (2014–2023).\n\n## 3. Empirical Results\n\n### 3.1. Spatio-Temporal Evolution Characteristics\n\nAfter quantifying the contribution degree of indicators based on the Critic weight analysis method, the entropy method was used to test the robustness of the conclusions. The results are presented in [Table 1](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F17\u002F8904#table_body_display_sustainability-18-08904-t001). As shown in [Table 2](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F17\u002F8904#table_body_display_sustainability-18-08904-t002), agricultural and rural modernization in Shandong Province—spanning three major economic circles and 16 cities—from 2014 to 2023 has increased markedly. Indicator-weighted analysis showed an average annual growth rate of 18.50 co%. This rise reflected the strategic emphasis of the Rural Revitalization Strategy, whose coordinated implementation has driven sustained improvements and optimizations across multiple dimensions of modernization in Shandong Province.\n\nAs shown in [Figure 1](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F17\u002F8904#fig_body_display_sustainability-18-08904-f001), the years 2014, 2017, 2020, and 2023 were selected as the observation years, and the natural breaks method in ArcGIS software was used to map the spatial distribution. The spatial distribution followed a clear southeast-to-northwest decline in development levels. High values clustered in Jiaodong and extended into the Lunan. Jiaodong recorded the highest level, 0.423, while Lunan registered 0.403. By contrast, Provincial Capital had the lowest level, 0.341.\n\n**Figure 1.** Spatial distribution of agricultural and rural modernization levels in Shandong Province. Note: The natural breaks method in ArcGIS software was used to map the spatial distribution.\n\nIn terms of the change trend, the Provincial Capital circle recorded the highest average annual growth rate at 5.60%, followed by Lunan at 5.45% and Jiaodong at 4.34%. All three circles therefore displayed significant and persistent disparities in urba","Sustainability 2026, 18(17), 8904","2026-08-31T08:00:00Z","论文",10,false,68,{"impact":17,"substance":17,"depth":18,"authority":19,"freshness":20,"relevant":21,"comment":22},18,16,12,4,1,"基于山东省三大经济圈，研究农业农村现代化的时空分异与障碍因素，为区域协调发展提供实证参考。",[24],{"name":10,"url":6},[26,27,28,29],"山东","农业农村现代化","区域协调","时空分异",{"code":31,"slug":32,"name":33,"path":34,"parent_code":35},"E5","branding-commerce","品牌流通与电商","\u002Ftopic\u002Ffood-supply\u002Fbranding-commerce","E",[],{"status":38,"locked":14,"version":39,"method":40,"evidence":41},"classified","2026-10-22.2","rules",{"candidates":42,"agricultural_evidence":45},[43,49],{"code":44,"score":19,"supported":45,"title":46,"abstract":47,"tags":48},"J2",true,[27],[27],[27],{"code":31,"score":50,"supported":45,"title":51,"abstract":52,"tags":54},3,[],[53],"地理标志",[],[56,57],"农业农村现代化 区域协调 时空分异 山东","农业农村现代化 区域协调","农业农村现代化区域协调时空分异山东-1189",{"doi":8,"openalex_id":8,"authors":60,"venue":8,"cited_by_count":61,"oa_url":8,"card":8,"direction":8,"ingested_from":62},[],0,"agent","2026-09-01T00:03:40.104973Z",{"total":65,"page":21,"page_size":65,"items":66},6,[67,123,176,208,275,323],{"id":68,"title":69,"url":70,"summary":71,"summary_zh":8,"content":72,"source_name":73,"source_url":8,"published_at":74,"category":75,"cover_url":8,"hotness":13,"is_selected":45,"score":76,"score_detail":77,"sources":82,"tags":84,"primary_topic":89,"secondary_topics":90,"classification":91,"search_phrases":118,"slug":121,"view_count":61,"doi":8,"paper":8,"created_at":122},5254,"国务院《加快农业农村现代化\"十五五\"规划》:实施农村电商高质量发展工程","https:\u002F\u002Fwww.huarong.gov.cn\u002F33159\u002F37006\u002F37008\u002F37045\u002F37323\u002Fcontent_2414974.html","国务院印发加快农业农村现代化\"十五五\"规划,深挖农业农村数字生产力,引导各类主体加快农业数智化升级,实施农村电商高质量发展工程,加快农村电商迭代升级,规范发展农产品直播带货,开展\"数商兴农\",健全农产品加工技术研发体系,大力发展农产品精深加工、综合利用。","ʮͳŻ򲼾֡˳Ӧ˿ṹ仯ʹׯݱֻƣ滮ʵЧʵϸׯ࣬ȷصǿռƺͷòܿء֧ѡλڡҵĴƬƬΪԪƽ滮桢ʩˡŻģͲֽṹЭͬƽռȲչȫۺΡ\n\nʮģǿũʩ͹ܻʵʩṵִ̃幤̡ռ䡣չһũ幫·жƽũ幫·˸չƽ繩ˮһ廯йˮģС͹ˮ̹淶裬ƽũ幩ˮͳܡԪִũԴϵƽũũʩǷΧ֧ũĵʩƶͻںϷչƶִ˾ũ裬½͸Ӧѳ̻ũûʩʵʩչжֻ绯ܻˮƽ彨ʵʩƣʵ彨嵥ĿƶȣȫũʩܻЧơǿʩ衣","华容县人民政府(2026-10-14)","2026-10-14T00:00:00Z","政策",86,{"impact":78,"substance":79,"depth":17,"authority":80,"freshness":65,"relevant":21,"comment":81},27,22,13,"国务院层面“十五五”农业农村现代化规划明确实施农村电商高质量发展工程，政策层级高、条款具体，值得进入每日精选。",[83],{"name":73,"url":70},[85,86,87,27,88],"农村电商","数字乡村","十五五规划","数商兴农",{"code":31,"slug":32,"name":33,"path":34,"parent_code":35},[],{"status":38,"locked":14,"version":39,"method":40,"evidence":92},{"candidates":93,"agricultural_evidence":45},[94,98,102,108,113],{"code":31,"score":80,"supported":45,"title":95,"abstract":96,"tags":97},[85],[85],[85,88],{"code":44,"score":19,"supported":45,"title":99,"abstract":100,"tags":101},[27],[27],[27],{"code":103,"score":50,"supported":45,"title":104,"abstract":105,"tags":107},"E1",[],[106],"农产品加工",[],{"code":109,"score":21,"supported":14,"title":110,"abstract":111,"tags":112},"I6",[],[],[86],{"code":114,"score":21,"supported":14,"title":115,"abstract":116,"tags":117},"J1",[],[],[87],[119,120],"国务院 十五五规划 农村电商","农村电商 高质量发展工程","国务院十五五规划农村电商-5254","2026-10-19T00:07:31.421518Z",{"id":124,"title":125,"url":126,"summary":127,"summary_zh":8,"content":128,"source_name":129,"source_url":8,"published_at":130,"category":131,"cover_url":8,"hotness":13,"is_selected":14,"score":15,"score_detail":132,"sources":136,"tags":138,"primary_topic":143,"secondary_topics":144,"classification":145,"search_phrases":171,"slug":174,"view_count":61,"doi":8,"paper":8,"created_at":175},5415,"2026年全国农产品产销大会北部片区10月22日临沂启幕 专设AI赋能批发市场专题","https:\u002F\u002Fwww.jiemian.com\u002Farticle\u002F15210871.html","由商务部主办的2026年全国农产品产销大会（北部片区）定于10月22—25日在临沂国际博览中心举办，是该国家级产销平台首次落地山东。大会覆盖北部片区15个省（区、市）及新疆生产建设兵团，集聚供应商1200余家、采购商1500余家，规模创历届新高，策划农产品电商标准化建设、AI赋能农产品批发市场转型升级等20多场活动，并设直播电商助农专区。临沂前8个月农产品加工企业实现企业家数与营收「双超2500」，产销大会的AI与电商专题为数字农业流通环节提供了对接平台。","本届大会以“农商互联携手 助力乡村振兴”为主题，采用“1场开幕式+3场主题活动+N场系列对接活动”的总体架构。30多场活动涵盖北部片区优质农产品推介与产销对接、“畅联北部”全国农产品大市场建设和协同发展、农产品电商标准化建设暨品牌打造、北方农产品内外贸一体化与出口合作交流、AI赋能农产品流通、上合及RCEP国家农产品推介等议题。\n\n展馆设置上，规划了乡村振兴省际馆、助农生态企业馆、山东生态食品融合馆3个主题馆和公共服务区，展品涵盖粮油、果蔬、畜禽、地理标志产品、绿色有机食品、农机器械等全品类，实现“北部好物”一站集采。\n\n值得关注的是，大会在对接模式上做了不少创新。会前即开展供需预匹配，供需双方带着需求、带着产品参会；会中组织多轮一对一、一对多精准商务洽谈；会后持续留存对接渠道，做到“大会闭幕、对接不停”。同时引入电商平台、新媒体达人资源，开展巡馆直播、品牌专场带货，打通线上线下双通道。\n\n对外方面，大会依托山东的上合示范区和RCEP地方经贸合作机制平台，定向邀约上合组织国家、RCEP境外采购商参会，推动北部片区农产品既深耕国内大市场，又拓展国际市场。","界面新闻 2026-10-20","2026-10-20T00:00:00Z","报道",{"impact":79,"substance":18,"depth":80,"authority":133,"freshness":134,"relevant":21,"comment":135},9,8,"全国性农产品产销对接大会，专设AI赋能批发市场专题并融入电商直播与跨境采购，具行业参考价值，但属会议预告类报道、信息增量有限。",[137],{"name":129,"url":126},[86,139,140,141,142],"农业人工智能","产销对接","农产品电商","农产品流通",{"code":31,"slug":32,"name":33,"path":34,"parent_code":35},[],{"status":38,"locked":14,"version":39,"method":40,"evidence":146},{"candidates":147,"agricultural_evidence":45},[148,152,156,162,167],{"code":31,"score":65,"supported":45,"title":149,"abstract":150,"tags":151},[],[141],[140,142,141],{"code":103,"score":50,"supported":45,"title":153,"abstract":154,"tags":155},[],[106],[],{"code":157,"score":50,"supported":45,"title":158,"abstract":159,"tags":161},"I1",[],[160],"数字农业",[],{"code":163,"score":21,"supported":14,"title":164,"abstract":165,"tags":166},"I2",[],[],[139],{"code":109,"score":21,"supported":14,"title":168,"abstract":169,"tags":170},[],[],[86],[172,173],"临沂 农产品产销大会","AI赋能 批发市场","临沂农产品产销大会-5415","2026-10-21T00:09:54.436890Z",{"id":177,"title":178,"url":179,"summary":180,"summary_zh":8,"content":181,"source_name":182,"source_url":8,"published_at":183,"category":131,"cover_url":8,"hotness":13,"is_selected":45,"score":184,"score_detail":185,"sources":188,"tags":190,"primary_topic":194,"secondary_topics":195,"classification":196,"search_phrases":203,"slug":206,"view_count":61,"doi":8,"paper":8,"created_at":207},5251,"商务部等7部门部署品质电商\"五优\"行动 推动电商平台下沉赋能","http:\u002F\u002Fwww.jinchuan.gov.cn\u002Fzfxxgk\u002Fxzbmxxgk\u002Fzfbmxxgk\u002Fqswj\u002Ffdzdnrgk\u002Fgzdt\u002Fart\u002F2026\u002Fart_4eba5a9c8bc94d8b96e17aeb0abc4d7e.html","商务部等7部门印发品质电商\"五优\"行动,深入实施数商兴农和农村电商高质量发展,推动电商平台完善县域服务设施、增加绿色有机名特优新和地理标志农产品供给、对接农业品牌精品培育计划,建设中国消费名品方阵;并推动人工智能与电商深度融合、创新智能体等电商服务新模式。","（四）提升商家品质运营能力。深入开展电子商务惠民惠企活动，做优全国电子商务公共服务网，面向中小商家举办定制化培训。利用电子商务国家专业技术人员继续教育基地、“云上大讲堂”等载体开发公益性品质电商课程。引导地方建立健全电商产业园区质量管理服务体系，引入专业可信的质量检测等服务，结合园区内中小制造企业、跨境电商、直播电商等商家需求，针对性开展质量管理、标准应用、诚信合规、品牌建设等主题培训。\n\n（五）创新发展电商消费品牌。加快电商领域消费品牌建设，构建品牌库、孵化库等分级服务体系，为品牌成长提供系统化支撑。深入实施“数商兴农”和农村电商高质量发展、“互联网+”农产品出村进城工程，推动电商平台完善县域服务设施，提升本地化服务能力，增加绿色、有机、名特优新和地理标志农产品供给，发展农产品区域公用品牌，对接农业品牌精品培育计划，让更多源头好物直连消费者。继续深化数字化助力消费品工业“三品”行动，建设中国消费名品方阵，支持符合条件的消费品生产制造企业申报专精特新企业。\n\n（六）赋能品质商家市场开拓。开展“电商+产业带”培育行动，鼓励各地规划布局电商选品中心，重点支持具有核心技术、原创设计的中小卖家对接电商渠道，提升品牌知名度。发挥电商平台作用，依托订单直采、外贸优品专区等渠道，支持外贸企业拓展国内市场，扩大外贸优品消费。支持电商相关产品研发和服务创新，推动人工智能与电商深度融合，创新智能体等电商服务新模式，提升用户体验。开展“产业电商惠企对接”，推动一批产业带企业与电商平台达成合作，促进产业升级，形成经济新增长点。","金川区人民政府(2026-10-15)","2026-10-15T00:00:00Z",85,{"impact":186,"substance":79,"depth":17,"authority":80,"freshness":65,"relevant":21,"comment":187},26,"七部门联合部署品质电商“五优”行动，含数商兴农、县域电商服务设施、农产品区域公用品牌等实质条款，全国性政策层级高，值得进入每日精选。",[189],{"name":182,"url":179},[85,88,191,192,193],"农产品品牌","电商平台","品质电商",{"code":31,"slug":32,"name":33,"path":34,"parent_code":35},[],{"status":38,"locked":14,"version":39,"method":40,"evidence":197},{"candidates":198,"agricultural_evidence":45},[199],{"code":31,"score":133,"supported":45,"title":200,"abstract":201,"tags":202},[],[85,53],[191,85,88],[204,205],"商务部 品质电商 五优行动","数商兴农 农产品出村进城","商务部品质电商五优行动-5251","2026-10-19T00:07:31.152933Z",{"id":209,"title":210,"url":211,"summary":212,"summary_zh":213,"content":8,"source_name":214,"source_url":211,"published_at":215,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":216,"score_detail":217,"sources":220,"tags":222,"primary_topic":227,"secondary_topics":228,"classification":229,"search_phrases":255,"slug":258,"view_count":21,"doi":259,"paper":260,"created_at":274},4793,"Geographical indication adoption and county employment dynamics in China: stacked DID evidence on rural-urban and regional heterogeneity","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1967743","Geographical indications (GIs) are widely promoted as place-based institutions that can strengthen rural economies. Yet existing evidence is mixed on whether GI benefits translate into broad-based local employment gains, and whether impacts differ across regions with unequal market access and factor mobility. Using a county-year panel for China spanning 2000–2023 and three overlapping GI channels (protected products, agricultural GI registration, and trademark registration), we estimate dynamic employment responses to GI adoption with stacked difference-in-differences designs that address staggered treatment timing. Rural employment rates rise following GI adoption and remain higher several years after designation, whereas urban employment effects are smaller and more heterogeneous. Macro-regional analyses indicate that rural gains are concentrated in Western China, while Central China exhibits weak or negative rural responses at longer horizons. For urban employment, estimates are imprecise in the East and Central regions and turn negative in the West at 5-year horizons. Province-level results reinforce substantial heterogeneity but are sensitive to treated support and inference limitations. The findings clarify when and where GIs function as effective rural development instruments and motivate more place-sensitive GI governance that complements certification with market access, processing capacity, and local labor demand.","地理标志（geographical indications, GIs）被广泛推崇为能够增强农村经济的地方性制度。然而，现有证据对于地理标志收益能否转化为广泛的本地就业增长，以及其影响在不同市场准入和要素流动性不均的地区之间是否存在差异，仍莫衷一是。本文使用涵盖2000—2023年中国县级面板数据以及三个相互重叠的地理标志渠道（受保护产品、农产品地理标志登记和商标注册），通过堆叠双重差分设计解决处理时间交错问题，估计地理标志采纳的动态就业响应。地理标志采纳后，农村就业率上升，且在认定数年后仍保持较高水平，而城镇就业效应较小且更具异质性。宏观区域分析表明，农村收益集中在中国西部，而中部地区在较长时期内的农村响应较弱甚至为负。对于城镇就业，东部和中部地区的估计不精确，西部地区在5年期限上转为负值。省级层面的结果印证了显著的异质性，但对处理组支持情况和推断局限性较为敏感。本文的发现厘清了地理标志在何时、何地能够作为有效的农村发展工具发挥作用，并推动更具地方敏感性的地理标志治理，将认证与市场准入、加工能力和本地劳动力需求相配套。","Frontiers in Sustainable Food Systems","2026-10-12T00:00:00Z",81,{"impact":17,"substance":79,"depth":218,"authority":80,"freshness":133,"relevant":21,"comment":219},19,"基于2000—2023年县域面板与堆叠DID方法，揭示地理标志对农村就业的异质性影响，方法扎实、结论有政策参考价值，但属学术论文而非即时资讯。",[221],{"name":214,"url":211},[223,224,53,225,226],"乡村振兴","县域经济","区域差异","农村就业",{"code":31,"slug":32,"name":33,"path":34,"parent_code":35},[],{"status":38,"locked":14,"version":39,"method":40,"evidence":230},{"candidates":231,"agricultural_evidence":45},[232,240,244,250],{"code":233,"score":234,"supported":45,"title":235,"abstract":236,"tags":239},"G",7,[],[237,238],"农村发展","rural development",[223],{"code":31,"score":20,"supported":45,"title":241,"abstract":242,"tags":243},[],[53],[53],{"code":245,"score":50,"supported":45,"title":246,"abstract":247,"tags":249},"I4",[],[248],"GIS",[],{"code":251,"score":21,"supported":14,"title":252,"abstract":253,"tags":254},"G4",[],[],[224],[256,257],"地理标志 县域就业 中国","乡村振兴 农村就业 区域差异 县域经济","地理标志县域就业中国-4793","10.3389\u002Ffsufs.2026.1967743",{"doi":259,"openalex_id":261,"authors":262,"venue":214,"cited_by_count":61,"oa_url":211,"card":267,"direction":271,"ingested_from":273},"W7221548155",[263,265],{"name":264,"orcid":8},"Yingju Zhang",{"name":266,"orcid":8},"Jumin Zhao",{"tldr":268,"method":269,"finding":270,"direction":271,"opportunity":272},"用堆叠DID评估中国地理标志采纳对县域城乡就业的动态影响及区域异质性。","2000-2023年县域面板数据，三种GI渠道，堆叠双重差分法。","GI采纳后农村就业率上升且持续，城市效应较小；西部农村增益集中，中部长期偏弱。","数字乡村与农业信息化","可探究GI与数字市场接入、加工能力协同如何放大农村就业效应，并关注中部负向机制。","openalex","2026-10-13T23:30:06.923434Z",{"id":276,"title":277,"url":278,"summary":279,"summary_zh":8,"content":280,"source_name":281,"source_url":8,"published_at":282,"category":131,"cover_url":8,"hotness":13,"is_selected":14,"score":283,"score_detail":284,"sources":288,"tags":290,"primary_topic":293,"secondary_topics":294,"classification":295,"search_phrases":318,"slug":321,"view_count":21,"doi":8,"paper":8,"created_at":322},4764,"农村电商成推动乡村振兴重要引擎","https:\u002F\u002Fwww.toutiao.com\u002Farticle\u002F7694491261629268520","围绕《加快农业农村现代化十五五规划》和2026年中央一号文件部署,分析农村电商高质量发展路径。文章以陕西平利村播等案例展示订单农业加标准赋能加品牌升级模式,论证手机成为新农具、直播成为新农活、数据成为新农资的转型逻辑,指出农村电商正推动县域消费从边缘地带走向战略前沿。","**当前，我国乡村消费品零售额占社会消费品零售总额的比重稳步提升，县域地区正从消费版图的“边缘地带”加速走向“战略前沿”，县域消费逐渐成为我国驱动内需增长的重要引擎。《加快农业农村现代化“十五五”规划》指出，实施农村电商高质量发展工程，加快农村电商迭代升级，规范发展农产品直播带货，开展“数商兴农”。2026年中央一号文件明确提出“推动电商平台下沉赋能”，乡村电商正推动乡村经济从“外部输血”向“内生造血”深度转型，成为激活乡村资源、培育本土主体、提高乡村经济发展韧性的关键支撑。**\n\n## 重塑农业生产方式\n\n农村电商根基在产业，关键在链条，绝不仅仅是给农产品挪了一个“网上摊位”。传统农业长期面临“种什么、怎么种、种多少”三大难题，丰产不丰收的现象屡见不鲜。随着农村电商快速发展，“产地直采”“定制生产”等新模式正在快速兴起，不少地方农产品依托网上订单，采用“订单农业+标准赋能+品牌升级”模式，通过定制种植标准、输出技术指导、共建特色品牌，推动农产品从“按经验种”转向“按订单种”。数字技术深度嵌入农业生产链条，农业生产方式从传统经验判断转向数据驱动，从粗放管理转向精细管控，从碎片化经营转向集约化生产，消除了农民群众“卖货难”的后顾之忧，让小农户融入了大产业，对接上大市场。\n\n手机由此成了新农具，直播成了新农活，数据成了新农资。在陕西省安康市平利县，主播手拿一块八仙“块块糖”在直播间对着镜头：“咬上一口，酥脆香甜，天星米、核桃和苏麻的香味在嘴里慢慢化开，越嚼越香。过年过节、走亲访友，都是绝佳的伴手礼……”主播介绍，产品以前只靠线下批发零售，销路窄，山货走不出去。现在通过直播，产品远销上海、广东等地，上个月线上销售额突破了3万元。这一改变，离不开“平利村播”搭建的平台。近年来，该县摸排电商人才需求，建立动态人才台账，通过分层分级渐进式培养，构建起“基础培训+进阶提升+精英精进”的人才培养体系。优质的村播培育平台，既助力本土涉农企业转型升级，也为普通村民开辟了增收新路。\n\n专家表示，电商助农的主角永远是土地和农民。从最初回应网友的购买需求开启直播，到如今发展乡村订单农业，新农人们的发展之路见证了“主播+合作社+农户”模式的成功。围绕乡村特色产业，以乡村合作社为载体，整合资源、规范生产，将更加有力地推动特色农产品从“有品相”转向“有品牌”，变“零散卖”为“规模销”，从而带动乡亲们在家门口就业，实现兴一业、富一方。\n\n## 促进农民稳定增收\n\n农村电商发展拓宽了农产品销售渠道，激活了农民主体性，成为农民增收致富的有效抓手。长期以来，不少农产品面临“藏在深山无人识”的困境，销售渠道单一。如今，鲜为人知的土特产，通过网络走出大山；农民自己当主播，带火“网红”农货。越来越多农民“扛得了锄头、玩得了直播”。每件农产品都打上标签、可追溯源头，原汁原味的特产、满满诚意的乡情引得消费者纷纷下单。农村电商发展，既让农民“离土不离乡”，实现就近就业，更是把更多收益留在乡村、留给农民。从“卖得掉”到“卖得好”，从“按筐卖”到“按个卖”，从“卖原料”到“卖品牌”，好产品卖出了好价钱，实打实装进了农民口袋。而且，不少“村播”带火了乡村旅游，把绿水青山转化为金山银山，开辟了农民增收新空间。\n\n今夏，台风“巴威”逼近福建福清，果农刘云明4000斤葡萄集中成熟，若不及时抢收与销售恐遭风毁。接到求助后，当地多单位联合行动，次日农技人员入园抢收，融媒开启助农直播，社群团购、干部代销、经销商包销多方发力，短短几小时就搭建起应急销售网络。不到一天，原本可能烂在果园里的4000斤葡萄全部售罄。这类真实发生的案例，印证着网络助农实实在在的价值。\n\n专家指出，“新农人”群体虽具有较强的数字应用意愿，但其数字素养不足、应用层次较浅，也造成了其利用数字技术发展乡村产业“心有余而力不足”的局面。要解决这一困境，必须提升“新农人”的数字应用素养，使其能够依靠数字技术获得实实在在的增收。基层党组织和政府要着力构建分层分级的精准化培训体系。针对不同的“新农人”群体，开展农业全产业链技术技能培训，把智慧农业、农产品网络销售、手机应用技能等内容纳入培训课程体系。\n\n## 畅通城乡双向流动\n\n农村电商发展，正以数字化、平台化的独特优势，成为畅通城乡要素双向流动、激活乡村振兴内生活力的关键纽带。以往，商品流通主要是从城市流向农村，农产品走出大山并不容易。现在农村现代物流配送体系不断完善、电商平台加速下沉、城乡交通网络不断织密，农产品实现“产地直发”，通过全程冷链、预先设置揽收点等方式，有效缩短在途时间、减少损耗保鲜问题。从人才流动看，农村电商催生了下乡电商人才、乡村主播、数字农业技术员等“新农人”群体，把手机作为“新农具”，把直播变成“新农活”，把土地种上“云端”。\n\n近年来，农村电商快速发展，我国基本建立起县、乡、村三级电子商务服务体系和物流配送体系，在拓宽农产品销路、促进农村消费中发挥的作用愈发凸显。相关数据显示，2025年，农村网络零售额、农产品网络零售额分别为3万亿元、7833.1亿元。物流网络日趋完善，农村物流“最后一公里”持续打通，2025年，全国县级物流配送中心覆盖率达100%。电商已不再只是销售通道，而是深度嵌入乡村振兴、产业升级，成为推动就业增收的重要引擎，让越来越多的基层群众搭上了“数字快车”。\n\n直播间架在乡村地头，网线连通广阔市场。刚刚过去的9月，浙江嘉兴举办了“数商兴农·嘉品共富”2026嘉兴数字乡村消费季活动。据不完全统计，活动期间该市开展直播超4300场，实现销售额超1.78亿元。从田间地头到“云端货架”，数字经济正加速重构当地乡村消费场景。消费季期间，嘉兴鼓励特色农产品通过主流电商、即时配送和社区团购平台开展线上销售，让乡村好物从自产自销加快走向“线上直销”。其中，海盐县举办葡萄直播专场，主推国家地理标志产品，销售葡萄2014公斤，实现销售额11万元；海宁市组织15家农村电商企业参与活动，聚焦花卉园艺、本土特色农产品开展直播，累计直播超600场，线上销售额突破2000万元；嘉兴经开区组织6家商家开展助农直播20场，发放消费优惠券600万元，直接带动销售额2000万元。\n\n专家指出，不再单纯追求卖得多，而是向卖得稳、卖得好转变，正是电商助农努力突破的方向。通过地标认证、品质严选，把正宗产地、产品标准摆在明面上，补齐农产品的信任短板。与此同时，产地供应链、仓储冷链、分级分选这些看不见的硬功夫，也要同步跟上。直播间只是对外展示的窗口，真正的底气藏在田间分选、包装发货的每一个环节。手机可以成为新农具，但不能替代田间劳作、车间生产；直播可以拓宽销路，但走红市场的关键还在于品质。","中国食品报 2026-10-09","2026-10-09T00:00:00Z",73,{"impact":285,"substance":17,"depth":18,"authority":13,"freshness":286,"relevant":21,"comment":287},24,5,"全国性政策与数据支撑的农村电商综合报道，案例与信源较扎实，但属趋势性综述，时效略滞后。",[289],{"name":281,"url":278},[85,86,291,88,292],"县域消费","农产品直播",{"code":31,"slug":32,"name":33,"path":34,"parent_code":35},[],{"status":38,"locked":14,"version":39,"method":40,"evidence":296},{"candidates":297,"agricultural_evidence":45},[298,302,306,310,314],{"code":31,"score":80,"supported":45,"title":299,"abstract":300,"tags":301},[85],[85],[85,88],{"code":233,"score":134,"supported":45,"title":303,"abstract":304,"tags":305},[223],[],[],{"code":44,"score":50,"supported":45,"title":307,"abstract":308,"tags":309},[],[27],[],{"code":251,"score":21,"supported":14,"title":311,"abstract":312,"tags":313},[],[],[291],{"code":109,"score":21,"supported":14,"title":315,"abstract":316,"tags":317},[],[],[86],[319,320],"平利村播 农村电商","嘉兴 数商兴农 直播","平利村播农村电商-4764","2026-10-13T00:08:33.942402Z",{"id":324,"title":325,"url":326,"summary":327,"summary_zh":8,"content":8,"source_name":328,"source_url":8,"published_at":329,"category":75,"cover_url":8,"hotness":13,"is_selected":45,"score":330,"score_detail":331,"sources":336,"tags":338,"primary_topic":341,"secondary_topics":342,"classification":343,"search_phrases":350,"slug":352,"view_count":61,"doi":8,"paper":8,"created_at":353},4618,"商务部等7部门发布关于实施品质电商五优行动的通知","https:\u002F\u002Fwww.toutiao.com\u002Farticle\u002F7694864762768720420\u002F","商务部、中央网信办、国家发改委、工信部、农业农村部、市场监管总局、邮政局7部门联合印发《关于实施品质电商五优行动的通知》。重点任务包括:加强品质电商主体培育、建立全链路品控体系;深入实施数商兴农和互联网+农产品出村进城工程,增加绿色、有机、名特优新和地理标志农产品供给;纠治自动跟价、全网最低价等无序竞争,围绕618、双11等节点规范网络消费环境。","中新经纬 2026-10-10","2026-10-10T00:00:00Z",94,{"impact":332,"substance":333,"depth":17,"authority":334,"freshness":13,"relevant":21,"comment":335},28,23,15,"七部门联合发文，含数商兴农、农产品出村进城等实质条款，全国性政策层级高、时效新，值得进入每日精选。",[337],{"name":328,"url":326},[85,88,193,339,340],"农产品出村进城","网络消费环境",{"code":31,"slug":32,"name":33,"path":34,"parent_code":35},[],{"status":38,"locked":14,"version":39,"method":40,"evidence":344},{"candidates":345,"agricultural_evidence":45},[346],{"code":31,"score":286,"supported":45,"title":347,"abstract":348,"tags":349},[],[53],[85,88],[205,351],"农产品出村进城 网络消费环境 农村电商 品质电商","数商兴农农产品出村进城-4618","2026-10-11T00:09:35.998753Z"]