[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-4793":3,"related-4793":92},{"id":4,"title":5,"url":6,"summary":7,"summary_zh":8,"content":9,"source_name":10,"source_url":6,"published_at":11,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":15,"score_detail":16,"sources":24,"tags":26,"primary_topic":32,"secondary_topics":38,"classification":39,"search_phrases":71,"slug":74,"view_count":22,"doi":75,"paper":76,"created_at":91},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。",null,"Frontiers in Sustainable Food Systems","2026-10-12T00:00:00Z","论文",10,false,81,{"impact":17,"substance":18,"depth":19,"authority":20,"freshness":21,"relevant":22,"comment":23},18,22,19,13,9,1,"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。",[25],{"name":10,"url":6},[27,28,29,30,31],"乡村振兴","县域经济","地理标志","区域差异","农村就业",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},"E5","branding-commerce","品牌流通与电商","\u002Ftopic\u002Ffood-supply\u002Fbranding-commerce","E",[],{"status":40,"locked":14,"version":41,"method":42,"evidence":43},"classified","2026-10-22.2","rules",{"candidates":44,"agricultural_evidence":48},[45,54,59,66],{"code":46,"score":47,"supported":48,"title":49,"abstract":50,"tags":53},"G",7,true,[],[51,52],"农村发展","rural development",[27],{"code":33,"score":55,"supported":48,"title":56,"abstract":57,"tags":58},4,[],[29],[29],{"code":60,"score":61,"supported":48,"title":62,"abstract":63,"tags":65},"I4",3,[],[64],"GIS",[],{"code":67,"score":22,"supported":14,"title":68,"abstract":69,"tags":70},"G4",[],[],[28],[72,73],"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":75,"openalex_id":77,"authors":78,"venue":10,"cited_by_count":83,"oa_url":6,"card":84,"direction":88,"ingested_from":90},"W7221548155",[79,81],{"name":80,"orcid":9},"Yingju Zhang",{"name":82,"orcid":9},"Jumin Zhao",0,{"tldr":85,"method":86,"finding":87,"direction":88,"opportunity":89},"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",{"total":93,"page":22,"page_size":93,"items":94},6,[95,162,199,243,296,332],{"id":96,"title":97,"url":98,"summary":99,"summary_zh":9,"content":9,"source_name":100,"source_url":9,"published_at":101,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":15,"score_detail":102,"sources":106,"tags":108,"primary_topic":113,"secondary_topics":114,"classification":115,"search_phrases":148,"slug":151,"view_count":93,"doi":9,"paper":152,"created_at":161},3959,"农村电商发展的\"绿水青山\"效应：来自县域的证据","http:\u002F\u002Fwww.qikanzj.com\u002Fhek\u002Fhznydxxbshkxb\u002Fmulu\u002F559252.html","陈苏（江西财经大学）、崔凯玲（厦门大学）、潘丹（江西财经大学）使用2000-2019年1884个中国县域面板数据，将电子商务进农村综合示范政策视作政府支持农村电商发展的一项准自然实验，基于卫星反演技术获取农业生态环境质量数据，采用多期双重差分模型评估农村电商发展对农业生态环境质量的影响效应。结果表明：农村电商发展显著提高农业生态环境质量，具有明显的\"绿水青山\"效应，且这一效应在长期内可持续；机制分析发现农村电商通过推动农业绿色生产、提高农村信息化程度提高农业生态环境质量。","华中农业大学学报（社科版）·2026年","2026-09-15T00:00:00Z",{"impact":18,"substance":103,"depth":19,"authority":104,"freshness":61,"relevant":22,"comment":105},23,14,"基于1884个县域面板与卫星反演数据的多期DID研究，实证农村电商的农业生态环境改善效应，方法扎实、结论有政策价值，但时效性偏弱。",[107],{"name":100,"url":98},[109,110,28,111,112],"农村电商","数字乡村","农业绿色发展","农业生态环境",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[],{"status":40,"locked":14,"version":41,"method":42,"evidence":116},{"candidates":117,"agricultural_evidence":48},[118,123,129,133,138,143],{"code":33,"score":119,"supported":48,"title":120,"abstract":121,"tags":122},12,[109],[109],[109],{"code":124,"score":61,"supported":48,"title":125,"abstract":126,"tags":128},"H6",[],[127],"农业生态",[],{"code":67,"score":22,"supported":14,"title":130,"abstract":131,"tags":132},[],[],[28],{"code":134,"score":22,"supported":14,"title":135,"abstract":136,"tags":137},"H4",[],[],[111],{"code":139,"score":22,"supported":14,"title":140,"abstract":141,"tags":142},"H8",[],[],[111],{"code":144,"score":22,"supported":14,"title":145,"abstract":146,"tags":147},"I6",[],[],[110],[149,150],"农村电商 农业生态环境","农业生态环境 农业绿色发展 农村电商 县域经济","农村电商农业生态环境-3959",{"doi":9,"openalex_id":9,"authors":153,"venue":9,"cited_by_count":83,"oa_url":9,"card":154,"direction":158,"ingested_from":160},[],{"tldr":155,"method":156,"finding":157,"direction":158,"opportunity":159},"基于1884个县域面板数据，评估农村电商发展对农业生态环境质量的影响。","多期双重差分模型，卫星反演农业生态环境数据，电子商务进农村示范政策。","农村电商显著且持续提升农业生态环境质量，通过绿色生产和信息化实现。","农业绿色发展与碳","可探究农村电商对农业碳排放、生物多样性等具体生态指标的异质性影响及空间溢出效应。","agent","2026-10-02T11:53:16.323798Z",{"id":163,"title":164,"url":165,"summary":166,"summary_zh":9,"content":167,"source_name":168,"source_url":9,"published_at":169,"category":170,"cover_url":9,"hotness":13,"is_selected":48,"score":171,"score_detail":172,"sources":176,"tags":178,"primary_topic":183,"secondary_topics":184,"classification":185,"search_phrases":193,"slug":196,"view_count":197,"doi":9,"paper":9,"created_at":198},3681,"农业农村部等三部门联合实施农业品牌保护专项行动","http:\u002F\u002Fcredit.tianshui.gov.cn\u002F640.news.detail.dhtml?news_id=57406","农业农村部、市场监管总局、国家知识产权局近日联合印发《农业品牌保护专项行动实施方案(2026—2027年)》，围绕品牌质量安全监管、商标专利执法、不正当竞争查处、知识产权行政保护四大重点任务，建立全链条保护体系，严厉打击涉农商标侵权、地理标志假冒和网络销售违法假冒行为。","近日，农业农村部、市场监管总局和国家知识产权局联合印发《农业品牌保护专项行动实施方案（2026—2027年）》，提出完善部门协同保护机制，健全覆盖农业品牌培育、管理、使用、推广的全链条保护体系，增强消费信心、提升品牌价值。\n\n本次专项行动围绕四大重点任务展开。在品牌农产品质量安全监管执法方面，全面落实承诺达标合格证制度，健全问题通报和协查机制，强化产地准出分类监管。\n\n在打击涉农商标、专利领域违法行为方面，严厉查处涉农商标侵权、地理标志侵权、假冒专利等违法行为，强化对农产品网络销售、直播带货中侵权假冒行为的查处力度，严厉打击恶意抢注或侵犯老字号商标、驰名商标的行为。\n\n在打击不正当竞争行为方面，要求重点查处擅自使用知名区域公用品牌、地理标志品牌等特有的和近似的名称、包装、装潢等混淆行为，重点查处经营者对其商品性能、功能、质量、销售状况、用户评价、曾获荣誉等作虚假或者引人误解的商业宣传，以及通过商业诋毁等方式损害竞争对手的行为。\n\n在涉农知识产权行政保护方面，支持农业品牌主体通过商标、专利、地理标志、植物新品种等多维度知识产权布局，强化品牌权益保护。推动知识产权公共服务机构聚焦重点农业产业，提供维权咨询、侵权判定、纠纷调解等专业化公益服务，提升农业品牌主体知识产权管理能力。","信用中国·天水","2026-09-23T07:08:00Z","政策",85,{"impact":173,"substance":18,"depth":174,"authority":20,"freshness":93,"relevant":22,"comment":175},27,17,"三部门联合印发的全国性农业品牌保护专项行动方案，条款具体、任务明确，对农业品牌建设与涉农知识产权保护具有较强指导价值。",[177],{"name":168,"url":165},[179,29,180,181,182],"农业品牌","市场监管","知识产权保护","品牌强农",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[],{"status":40,"locked":14,"version":41,"method":42,"evidence":186},{"candidates":187,"agricultural_evidence":48},[188],{"code":33,"score":189,"supported":48,"title":190,"abstract":191,"tags":192},5,[],[29],[179,29],[194,195],"农业农村部 市场监管总局 国家知识产权局","知识产权保护 农业品牌 品牌强农 地理标志","农业农村部市场监管总局国家知识产权局-3681",2,"2026-09-29T00:08:17.566411Z",{"id":200,"title":201,"url":202,"summary":203,"summary_zh":9,"content":204,"source_name":205,"source_url":9,"published_at":206,"category":170,"cover_url":9,"hotness":13,"is_selected":14,"score":207,"score_detail":208,"sources":212,"tags":214,"primary_topic":218,"secondary_topics":219,"classification":220,"search_phrases":238,"slug":241,"view_count":189,"doi":9,"paper":9,"created_at":242},3377,"农业农村部、市场监管总局、国家知识产权局联合印发《农业品牌保护专项行动实施方案（2026—2027年）》","https:\u002F\u002Fxy.baoding.gov.cn\u002Fnews\u002Fcontent\u002F890127250274385920","近日三部门联合印发《农业品牌保护专项行动实施方案（2026—2027年）》，部署四大重点任务：一是品牌农产品质量安全监管执法，全面落实承诺达标合格证制度；二是打击涉农商标、专利领域违法行为，重点查处地理标志侵权、假冒专利及农产品网络销售、直播带货中侵权假冒行为；三是打击不正当竞争行为；四是涉农知识产权行政保护，支持品牌主体通过商标、专利、地理标志、植物新品种等多维度知识产权布局，强化品牌权益保护。","*   [![Image 1](https:\u002F\u002Fxy.baoding.gov.cn\u002Fhebei\u002Fbaoding\u002Fimages\u002Fnav\u002Fnav-home.png)首页](https:\u002F\u002Fxy.baoding.gov.cn\u002F)\n*   [![Image 2](https:\u002F\u002Fxy.baoding.gov.cn\u002Ffile\u002Fueditorgroup\u002Fbaoding\u002Fueditor\u002Fjsp\u002Fupload\u002Fimage\u002F2023\u002F04\u002F23\u002F1682213910310088719.png)信用动态](https:\u002F\u002Fxy.baoding.gov.cn\u002Fnews\u002Findex\u002F102)\n*   [![Image 3](https:\u002F\u002Fxy.baoding.gov.cn\u002Ffile\u002Fueditorgroup\u002Fbaoding\u002Fueditor\u002Fjsp\u002Fupload\u002Fimage\u002F2023\u002F04\u002F23\u002F1682213924351033562.png)政策法规](https:\u002F\u002Fxy.baoding.gov.cn\u002Fnews\u002Findex\u002F106)\n*   [![Image 4](https:\u002F\u002Fxy.baoding.gov.cn\u002Ffile\u002Fueditorgroup\u002Fbaoding\u002Fueditor\u002Fjsp\u002Fupload\u002Fimage\u002F2026\u002F06\u002F29\u002F1782694629349035186.png)信用公示](https:\u002F\u002Fxy.baoding.gov.cn\u002Fxushuiqu\u002Fcredit\u002Fcreditpublicity\u002F595546555902066688)\n*   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B6%E4%BA%A7%E7%94%9F%E4%BF%A1%E7%94%A8%E6%8A%A5%E5%91%8A%E7%AD%89%E4%BF%A1%E7%94%A8%E4%BA%A7%E5%93%81%2C%E4%B8%BA%E6%94%BF%E5%BA%9C%E5%90%84%E9%83%A8%E9%97%A8%E3%80%81%E5%85%AC%E5%85%B1%20%E4%BA%8B%E4%B8%9A%E5%8D%95%E4%BD%8D%E3%80%81%E9%87%91%E8%9E%8D%E6%9C%BA%E6%9E%84%E6%8F%90%E4%BE%9B%E4%BF%A1%E7%94%A8%E4%BF%A1%E6%81%AF%E7%9A%84%E6%9F%A5%E8%AF%A2%E5%92%8C%E5%BA%94%E7%94%A8%E5%B7%A5%E4%BD%9C%E3%80%82%2C%E4%BF%A1%E7%94%A8%E4%B8%AD%E5%9B%BD%EF%BC%88%E6%B2%B3%E5%8C%97%E4%BF%9D%E5%AE%9A%EF%BC%89%2C%E4%BF%A1%E7%94%A8&pics=https%3A%2F%2Fxy.baoding.gov.cn%2Fhebei%2Fbaoding%2Fimages%2Fnav%2Fnav-home.png)\n\n近日，农业农村部、市场监管总局和国家知识产权局联合印发《农业品牌保护专项行动实施方案（2026—2027年）》，提出完善部门协同保护机制，健全覆盖农业品牌培育、管理、使用、推广的全链条保护体系，增强消费信心、提升品牌价值。\n\n本次专项行动围绕四大重点任务展开。在品牌农产品质量安全监管执法方面，全面落实承诺达标合格证制度，健全问题通报和协查机制，强化产地准出分类监管。\n\n在打击涉农商标、专利领域违法行为方面，严厉查处涉农商标侵权、地理标志侵权、假冒专利等违法行为，强化对农产品网络销售、直播带货中侵权假冒行为的查处力度，严厉打击恶意抢注或侵犯老字号商标、驰名商标的行为。\n\n在打击不正当竞争行为方面，要求重点查处擅自使用知名区域公用品牌、地理标志品牌等特有的和近似的名称、包装、装潢等混淆行为，重点查处经营者对其商品性能、功能、质量、销售状况、用户评价、曾获荣誉等作虚假或者引人误解的商业宣传，以及通过商业诋毁等方式损害竞争对手的行为。\n\n在涉农知识产权行政保护方面，支持农业品牌主体通过商标、专利、地理标志、植物新品种等多维度知识产权布局，强化品牌权益保护。推动知识产权公共服务机构聚焦重点农业产业，提供维权咨询、侵权判定、纠纷调解等专业化公益服务，提升农业品牌主体知识产权管理能力。\n\n[【打印本页】](javascript:print();)[【关闭窗口】](javascript:window.opener=null;window.open('','_self');window.close();)\n\n[![Image 19](https:\u002F\u002Fxy.baoding.gov.cn\u002Fhebei\u002Fbaoding\u002Fimages\u002Fbs_0403.png)](http:\u002F\u002Fbszs.conac.cn\u002Fsitename?method=show&id=B9C45121CFF3E804E05310291AAC8168)\n\n![Image 20](https:\u002F\u002Fxy.baoding.gov.cn\u002Fhebei\u002Fbaoding\u002Fimages\u002Fcommon\u002Fjiucuo.png?v=1306000043)\n\n[互动交流](https:\u002F\u002Fxy.baoding.gov.cn\u002FmessageBoard)  \n[联系我们](https:\u002F\u002Fxy.baoding.gov.cn\u002Fnews\u002Findex\u002F445868384748306432)  \n[网站地图](https:\u002F\u002Fxy.baoding.gov.cn\u002FsiteMap)\n\n主办单位：保定市行政审批局（政务服务管理办公室）  \n[主体备案号：冀ICP备18006804号 网站备案号：冀ICP备18006804号-4](https:\u002F\u002Fbeian.miit.gov.cn\u002F)政府网站标识码：1306000043 版权所有 侵权必究   \n[![Image 21](https:\u002F\u002Fxy.baoding.gov.cn\u002Ffile\u002Fueditorgroup\u002Fbaoding\u002Fueditor\u002Fjsp\u002Fupload\u002Fimage\u002F2024\u002F07\u002F10\u002F1720590074755032591.png)冀公网安备 13060602001211号](http:\u002F\u002Fwww.beian.gov.cn\u002Fportal\u002FregisterSystemInfo?recordcode=13060602001211)地址：河北省保定市乐凯北大街3088号电谷科技中心1号楼保定市民服务中心","新华网（保定信用转载）2026-09-22","2026-09-22T00:00:00Z",86,{"impact":173,"substance":18,"depth":209,"authority":20,"freshness":210,"relevant":22,"comment":211},16,8,"三部门联合印发农业品牌保护两年行动方案，属全国性政策部署，条款与部门分工明确，对农业品牌与地理标志保护有直接指导意义，值得进入每日精选。",[213],{"name":205,"url":202},[215,29,216,182,217],"知识产权","专项行动","农业品牌保护",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[],{"status":40,"locked":14,"version":41,"method":42,"evidence":221},{"candidates":222,"agricultural_evidence":48},[223,227,233],{"code":33,"score":55,"supported":48,"title":224,"abstract":225,"tags":226},[],[29],[29],{"code":228,"score":61,"supported":48,"title":229,"abstract":230,"tags":232},"E4",[],[231],"农产品质量",[],{"code":234,"score":22,"supported":14,"title":235,"abstract":236,"tags":237},"F1",[],[],[215],[239,240],"农业农村部 市场监管总局 国家知识产权局 农业品牌","农业品牌保护 专项行动 品牌强农 地理标志","农业农村部市场监管总局国家知识产权局农业品牌-3377","2026-09-25T00:09:26.888100Z",{"id":244,"title":245,"url":246,"summary":247,"summary_zh":248,"content":9,"source_name":10,"source_url":246,"published_at":206,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":249,"score_detail":250,"sources":252,"tags":254,"primary_topic":257,"secondary_topics":258,"classification":259,"search_phrases":274,"slug":277,"view_count":61,"doi":278,"paper":279,"created_at":295},3265,"Factors associated with farmers’ multidimensional participation in e-commerce","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1936130","Introduction As an important ICT-enabled business model, rural e-commerce has attracted growing attention, yet existing studies predominantly focus on binary adoption while overlooking heterogeneity in farmers’ participation depth, participation breadth, and platform choice. This study examines the multidimensional characteristics of farmers’ e-commerce participation. Methods Using data from 2,508 farm households in the 2020 China Rural Revitalization Survey, this study examines factors associated with four dimensions of e-commerce participation and uses ISM to identify the hierarchy of factors associated with participation decisions. Results (1) E-commerce training is positively associated with participation decision, depth, and breadth and with the probabilities of choosing social and traditional e-commerce. The household head’s education is positively associated with participation decision, depth, and breadth and negatively associated with the probability of remaining offline. In contrast, age is negatively associated with participation decision and depth and with the probabilities of choosing social and traditional e-commerce. (2) Cultivated land area is positively associated with participation decision and depth and with the probabilities of choosing social and traditional e-commerce. Organizational participation is positively associated with participation decision and depth, while average household education is positively associated with participation decision, depth, and breadth. Village e-commerce service stations are positively associated with participation decision and depth and with the probability of choosing social e-commerce. Local non-farm industrial development is positively associated only with participation breadth. (3) Within the ISM hierarchy of factors associated with participation decisions, e-commerce training is identified as a surface direct factor; organizational participation and village e-commerce service stations as shallow indirect factors; cultivated land area and average household education as middle-level indirect factors; and the household head’s age and education as deep-seated root factors. Discussion These findings demonstrate the multidimensional nature of farmers’ e-commerce participation and show that the same factor may have differentiated associations across dimensions. Policies should therefore shift from general encouragement to dimension-specific support through targeted training, organizational services, village e-commerce facilities, resource matching, and locally adapted industrial support.","引言 作为信息通信技术赋能的重要商业模式，农村电商日益受到关注，但现有研究多聚焦于二元采纳，忽视了农户参与深度、参与广度和平台选择方面的异质性。本研究考察农户电商参与的多维特征。方法 利用2020年中国乡村振兴调查中2508户农户的数据，本研究考察电商参与四个维度的相关因素，并运用ISM识别参与决策相关因素的层级结构。结果 （1）电商培训与参与决策、参与深度和参与广度呈正相关，且与选择社交电商和传统电商的概率呈正相关。户主受教育程度与参与决策、参与深度和参与广度呈正相关，与保持线下的概率呈负相关。相反，年龄与参与决策和参与深度呈负相关，且与选择社交电商和传统电商的概率呈负相关。（2）耕地面积与参与决策和参与深度呈正相关，且与选择社交电商和传统电商的概率呈正相关。组织参与与参与决策和参与深度呈正相关，而家庭平均受教育程度与参与决策、参与深度和参与广度呈正相关。村级电商服务站与参与决策和参与深度呈正相关，且与选择社交电商的概率呈正相关。本地非农产业发展仅与参与广度呈正相关。（3）在参与决策相关因素的ISM层级结构中，电商培训被识别为表层直接因素；组织参与和村级电商服务站为浅层间接因素；耕地面积和家庭平均受教育程度为中层间接因素；户主年龄和受教育程度为深层根源因素。讨论 这些发现表明农户电商参与的多维性质，并显示同一因素在不同维度上可能具有差异化关联。因此，政策应从普遍鼓励转向通过针对性培训、组织服务、村级",78,{"impact":209,"substance":18,"depth":17,"authority":20,"freshness":21,"relevant":22,"comment":251},"基于2508户全国调查数据，揭示农户电商参与的多维异质性及ISM因素层级，对数字乡村政策有实证参考价值。",[253],{"name":10,"url":246},[109,110,27,255,256],"电商培训","农户参与",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[],{"status":40,"locked":14,"version":41,"method":42,"evidence":260},{"candidates":261,"agricultural_evidence":48},[262,266,270],{"code":33,"score":55,"supported":48,"title":263,"abstract":264,"tags":265},[],[109],[109],{"code":46,"score":55,"supported":48,"title":267,"abstract":268,"tags":269},[],[27],[27],{"code":144,"score":22,"supported":14,"title":271,"abstract":272,"tags":273},[],[],[110],[275,276],"中国乡村振兴调查 农村电商","农户 电商参与 多维","中国乡村振兴调查农村电商-3265","10.3389\u002Ffsufs.2026.1936130",{"doi":278,"openalex_id":280,"authors":281,"venue":10,"cited_by_count":83,"oa_url":246,"card":290,"direction":88,"ingested_from":90},"W7214016500",[282,284,286,288],{"name":283,"orcid":9},"Mingyang Yin",{"name":285,"orcid":9},"Zhengyin Li",{"name":287,"orcid":9},"Juan Xie",{"name":289,"orcid":9},"Yan Yan",{"tldr":291,"method":292,"finding":293,"direction":88,"opportunity":294},"基于2508户调查数据，分析农户电商参与决策、深度、广度和平台选择的多维影响因素。","2020中国乡村振兴调查数据，ISM解释结构模型分析影响因素层级。","电商培训、教育、耕地面积等对参与各维度影响不同，年龄和教育是深层根源因素。","可探究不同参与维度对农户收入与福利的差异化影响，以及平台选择的行为机制。","2026-09-23T23:30:07.352722Z",{"id":297,"title":298,"url":299,"summary":300,"summary_zh":9,"content":301,"source_name":302,"source_url":9,"published_at":303,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":304,"score_detail":305,"sources":307,"tags":309,"primary_topic":314,"secondary_topics":315,"classification":316,"search_phrases":327,"slug":330,"view_count":61,"doi":9,"paper":9,"created_at":331},512,"Can Certification of Geographical Indication Agricultural Products Promote Agricultural Green Total Factor Productivity? Moderation and Threshold Effects from China","https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8265","Chunlan Zou与Zaijin Zou(西南林业大学经济管理学院)基于2012—2023年中国31个省份面板数据,采用双向固定效应模型估计基准效应,调节效应模型检验农业产业集聚作用,面板门槛回归捕捉潜在非线性关系。研究表明:地理标志农产品认证显著提高AGTFP,每个认证在1%显著性水平上提高AGTFP约0.001单位;农业产业集聚正向调节这一关系,认证效应仅在高集聚地区显著;认证效应呈门槛依赖型,低于农业发展水平0.048时呈显著负效应-0.0023,高于时呈显著正效应0.0015。","## 1. Introduction\n\nThe green transformation of agriculture is a central pillar of China’s agricultural modernization agenda. At the end of 2024, the Ministry of Agriculture and Rural Affairs officially issued the Guiding Opinions on Accelerating the Comprehensive Green Transformation of Agricultural Development and Promoting Ecological Revitalization in Rural Areas, marking a new, more systematic phase of China’s agricultural green transformation [[1](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8265#B1-sustainability-18-08265)]. The Plan for Accelerating the Construction of an Agricultural Powerhouse (2024–2035) further emphasizes the need to enhance total factor productivity in agriculture and to build a modern production system that is both resource-efficient and environmentally friendly [[2](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8265#B2-sustainability-18-08265)]. This policy momentum, however, contrasts sharply with the persistent challenges that remain in practice.\n\nDespite this policy momentum, the gap between policy ambition and practical implementation remains substantial. According to the China Agricultural Green Development Report 2024, total agricultural fertilizer application nationwide reached 49.88 million metric tons in 2024. This figure indicates continued pressure on agricultural pollution control and, correspondingly, considerable room for improvement in Agricultural Green Total Factor Productivity (AGTFP). It also suggests that technological progress and increased use of inputs alone are insufficient to achieve a fundamental breakthrough in agriculture’s green transformation. Institutional mechanisms that combine regulatory constraints with market-based incentives are equally indispensable.\n\nAgainst this backdrop, a notable tension has emerged in China’s agricultural sector. The number of registered Geographical Indication (GI) products reached approximately 82,000 in 2024, a year-on-year increase of 7% [[3](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8265#B3-sustainability-18-08265)]. Yet agricultural non-point source pollution continues to impose a heavy environmental burden. The Outline of the 15th Five-Year Plan for National Economic and Social Development explicitly identifies green and branded agriculture as strategic priorities for agricultural modernization, calling for the vigorous development of GI products and distinctive agricultural brands [[4](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8265#B4-sustainability-18-08265)]. This juxtaposition raises a question of both theoretical and practical urgency: can GI certification—an institution originally designed to protect origin-specific product quality—simultaneously boost agricultural output and reduce pollution, thereby contributing to AGTFP improvement? Addressing this question is the central motivation of the present study.\n\nA substantial body of literature has examined the determinants of AGTFP, which can be broadly grouped into four strands. The first strand focuses on digital technology and financial innovation. Studies show that digital village construction [[5](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8265#B5-sustainability-18-08265)], digital inclusive finance [[6](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8265#B6-sustainability-18-08265)], and agricultural technological innovation and modernization [[7](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8265#B7-sustainability-18-08265)] enhance AGTFP by improving information accessibility, resource allocation efficiency, and innovation capacity. The second strand examines policy and institutional factors, including environmental regulation [[8](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8265#B8-sustainability-18-08265)], fiscal support for agriculture [[9](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8265#B9-sustainability-18-08265)], agricultural insurance [[10](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8265#B10-sustainability-18-08265)], and farmland transfer rights [[11](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8265#B11-sustainability-18-08265)]. These studies consistently find that the effectiveness of such policy instruments varies considerably across regional and institutional contexts [[12](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8265#B12-sustainability-18-08265),[13](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8265#B13-sustainability-18-08265)]. The third strand investigates industrial development and factor endowments, including agricultural industrial agglomeration [[14](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8265#B14-sustainability-18-08265)], agricultural product trade [[15](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8265#B15-sustainability-18-08265)], rural population aging [[16](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8265#B16-sustainability-18-08265)], and agricultural socialized services [[17](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8265#B17-sustainability-18-08265),[18](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8265#B18-sustainability-18-08265)]. This research shows that structural transformations in the agricultural economy can affect AGTFP through multiple pathways, with some studies reporting positive effects and others reporting negative or insignificant effects [[19](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8265#B19-sustainability-18-08265),[20](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8265#B20-sustainability-18-08265)]. The fourth strand considers macroeconomic factors, such as market conditions and urbanization, which also shape AGTFP at the aggregate level [[21](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8265#B21-sustainability-18-08265)]. Collectively, this literature has identified diverse technological, institutional, structural, and macroeconomic drivers of AGTFP, though most studies examine these determinants in isolation, leaving the role of market-based quality certification schemes such as GI largely unexplored.\n\nResearch on GI agricultural products has predominantly focused on the economic effects of certification. A substantial body of research confirms that GI certification raises farm household income, primarily through price premiums and improved market access [[22](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8265#B22-sustainability-18-08265)]. Other studies link GI certification to rural industrial development [[23](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8265#B23-sustainability-18-08265)] and county-level economic growth [[24](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8265#B24-sustainability-18-08265)], emphasizing the roles of brand value and agritourism in stimulating local economies [[25](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8265#B25-sustainability-18-08265)]. A smaller but growing body of literature examines the link between GI certification and environmentally sustainable production at the farm level. Several studies find that certified producers adopt environmentally friendly inputs and practices significantly more often than non-certified producers [[26](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8265#B26-sustainability-18-08265)]. These findings suggest that GI certification has meaningful implications for sustainable production. However, few studies have systematically examined the effects of GI certification on AGTFP specifically, and the conditions under which its potential environmental benefits are realized remain underexplored.\n\nIntegrating these two research streams reveals a critical blind spot. Although existing research has established that GI certification shapes producer behavior and that structural and institutional factors drive AGTFP, no systematic framework has yet been developed to examine whether GI certification can function as an institutional driver of green productivity improvement. Three questions remain unanswered. Does GI certification, as a formal institutional arrangement, exert a meaningful effect on AGTFP? If so, under what regional conditions is this effect realized—and why does it appear to vary so markedly across contexts? And is the relationship between certification and green productivity truly linear and homogeneous, or might it exhibit threshold-dependent non-linearities that prior studies have been unable to detect? Accordingly, this study draws on provincial panel data from China spanning 2012 to 2023 and employs a two-way fixed-effects model, a moderation model, and a panel threshold regression model to conduct a systematic empirical analysis.\n\nThis study offers three principal contributions to the existing literature. First, we integrate Geographical Indication (GI) certification into the analytical framework for AGTFP determinants. Unlike prior research that primarily focuses on command-and-control policy instruments such as environmental regulations [[8](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8265#B8-sustainability-18-08265),[9](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8265#B9-sustainability-18-08265)], this study conceptualizes GI certification as a market-based institutional mechanism. From an institutional economics perspective, we show that GI certification functions as a governance tool that embeds environmental constraints into production standards, thereby extending the institutional dimension of AGTFP research beyond conventional policy instruments [[20](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8265#B20-sustainability-18-08265)].\n\nSecond, we move beyond aggregate-level analysis to explain regional heterogeneity in certification outcomes by introducing agricultural industrial agglomeration as a moderating variable. We theorize that industrial agglomeration amplifies the green productivity effects of GI certification through two interrelated channels: improved factor supply conditions and the diffusion of green technology. This helps explain regional variations in policy effectiveness and offers empirical grounding for coordinating GI promotion with industrial policy.\n\nThird, this study identifies non-linearities in the certification effect that prior empirical studies have largely overlooked. Using a panel threshold regression model, we identify a critical agricultural development threshold: below this threshold, GI certification has a statistically significant negative effect on AGTFP, whereas above it, the effect reverses and becomes statistically significant and positive. This finding challenges the implicit assumption that certification effects are linear and homogeneous across regions and provides evidence supporting more targeted, region-specific design of agricultural green transformation policies.\n\n## 2. Theoretical Framework and Research Hypotheses\n\n### 2.1. The Direct Effect of GI Agricultural Product Certification on AGTFP\n\nGeographical Indication (GI) certification is more than a market label; it is an institutional system with a built-in green development orientation, typically requiring products to originate from a specific region and adhere to traditional ecological production standards that limit chemical inputs and protect the production environment. Because this green transformation occurs at the source, Agricultural Green Total Factor Productivity (AGTFP)—which integrates traditional inputs such as land, labor, and machinery while accounting for reductions in fertilizers, pesticides, and plastic mulch—provides an suitable indicator for capturing the resulting environmental and economic performance.\n\nAs illustrated in the “direct effect” section of [Figure 1](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8265#fig_body_display_sustainability-18-08265-f001), this study identifies three interrelated channels through which GI certification affects AGTFP: standard constraints, market incentives, and collective organization.\n\n**Figure 1.** Mechanism framework of GI agricultural products and AGTFP.\n\nFirst, the certification standards system imposes binding constraints on production inputs at the source. GI certification is governed by national standards and local regulations covering the production environment, cultivation techniques, and input use, with core requirements including pollutant limits and maximum pesticide residue levels [[27](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8265#B27-sustainability-18-08265)]. Through the credible-commitment mechanism of granting and revoking certification status, producers who violate input standards face certification disqualification and the loss of premium revenues, creating endogenous incentives for compliance. This constrains the use of pesticides and fertilizers, directly regulates pollution-generating behavior, and improves the coordination between origin-environment protection and factor-use efficiency—collectively driving AGTFP improvement.\n\nSecond, market price premiums provide sustained economic incentives for green production. Because information asymmetry prevents consumers from independently verifying product quality and ecological attributes—a problem long recognized in the signaling literature on quality uncertainty [[28](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8265#B28-sustainability-18-08265)]—GI certification serves as an officially endorsed quality signal that reduces search costs and raises consumers’ willingness to pay, generating stable premiums. When the long-term returns from retaining these premiums exceed the short-term gains from non-compliance, producers rationally reduce chemical inputs and adopt greener production methods, directly improving AGTFP. This mechanism’s effectiveness, however, depends on consumers’ ability to identify green attributes and on the maturity of market-based reputation systems.\n\nThird, drawing on the theory of collective action and knowledge spillovers [[29](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8265#B29-sustainability-18-08265)], the collective certification application process fosters coordinated constraints on green production at the regional level. Because GI applications are submitted on behalf of regional producers by cooperatives or industry associations, dispersed farm households, cooperatives, and agribusinesses must adopt unified production standards. This common regulatory framework accelerates the diffusion of green technologies, enables centralized processing of agricultural waste, and internalizes externalities that arise from fragmented, decentralized management—reducing redundant resource use and promoting AGTFP growth through improved technical efficiency and regional factor allocation. Based on the above analysis, we propose the following hypothesis:\n\n**H1.**\n\nGI agricultural product certification has a positive and significant effect on agricultural green total factor productivity.\n\n### 2.2. The Moderating Role of Agricultural Industrial Agglomeration in the Relationship Between GI Certification and AGTFP\n\nThe direct channels discussed in [Section 2.1](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8265#sec2dot1-sustainability-18-08265) do not operate in isolation from the broader industrial environment. As illustrated in the moderating-effect component of [Figure 1](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8265#fig_body_display_sustainability-18-08265-f001), the extent to which certification’s green incentives translate into actual productivity gains depends critically on the level of agricultural industrial agglomeration surrounding certified producers. Two interrelated channels underlie this moderating role: a factor supply channel rooted in agglomeration economies, and a technology diffusion channel rooted in knowledge spillover theory.\n\nFrom the factor-supply perspective, agglomeration economy theory suggests that the spatial concentration of production activities improves factor market efficiency by lowering transaction costs and enhancing resource matching [[30](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8265#B30-sustainability-18-08265),[31](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8265#B31-sustainability-18-08265)]. Realizing the productivity effects of GI certification requires not only willingness but also the capacity to comply: producers need adequate financial resources, technological inputs, and human capital to implement certification standards effectively. In regions with higher industrial agglomeration, factor markets are more developed and resource acquisition is more accessible, providing the resources needed to convert certification compliance into genuine efficiency gains. Conversely, where agglomeration is low, factor market segmentation and restricted mobility create binding financial and technological constraints, leaving certified producers unable to implement green production standards in practice and diminishing certification’s net effect on AGTFP.\n\nFrom the technology-diffusion perspective, knowledge spillover theory holds that geographic proximity facilitates the transmission of tacit knowledge, which attenuates rapidly with distance [[32](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8265#B32-sustainability-18-08265),[33](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8265#B33-sustainability-18-08265)]. Green agricultural production relies heavily on tacit, hard-to-codify knowledge—such as site-specific cultivation techniques and input management experience—that spreads primarily through direct interaction. Industrial agglomeration reduces information transmission costs and provides an effective channel for such knowledge to diffuse between certified and non-certified producers. In regions with higher agglomeration density, more frequent interaction among producers lowers the marginal cost of adopting new green technologies, amplifying the overall effect of GI certification on AGTFP. In regions with lower agglomeration density, by contrast, dispersed producers weaken learning and demonstration effects among producers, leaving green production knowledge localized and adoption costs high, such that the spillover benefits fail to materialize.\n\nTaken together, these two channels indicate that industrial agglomeration does not merely provide a favorable context for GI certification—it actively amplifies certification’s green productivity effects through both factor supply and knowledge diffusion. The moderating role of agglomeration is therefore structural rather than incidental: it determines the extent to which the institutional incentives embedded in GI certification are converted into realized productivity gains. Based on the above analysis, we propose the following hypothesis:\n\n**H2.**\n\nThe positive effect of GI agricultural product certification on AGTFP is strengthened as agricultural industrial agglomeration increases.\n\n### 2.3. The Non-Linear Effect of GI Agricultural Product Certification on AGTFP\n\nThe direct and moderating effects discussed in [Section 2.1](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8265#sec2dot1-sustainability-18-08265) and [Section 2.2](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8265#sec2dot2-sustainability-18-08265) suggest that the green productivity effects of GI certification are neither universal nor uniform. As illustrated in the threshold-effect component of [Figure 1](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8265#fig_body_display_sustainability-18-08265-f001), this relationship may also exhibit structural non-linearity that varies with the level of regional agricultural development, giving rise to two distinct regimes: a sub-threshold regime in which certification suppresses AGTFP, and a supra-threshold regime in which its positive effects are activated. This pattern reflects institutional complementarity: GI certification cannot generate green productivity effects in isolation but requires complementary conditions—adequate infrastructure, functioning market access, and accessible factor supply—to activate its embedded incentives [[34](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F16\u002F8265#B34-sustainability-18-08265)]. These conditions do not accumulate gradually but form in a threshold-dependent manner; below a critical level of agricultural development, key complementary conditions remain absent and the certification system’s incentive structure breaks down, whereas above it, these conditions become sufficiently developed to unlock the institution’s full potential.\n\nBelow the threshold, the inhibitory effect operates ","Sustainability 2026-08-12","2026-08-11T16:00:00Z",72,{"impact":17,"substance":18,"depth":17,"authority":119,"freshness":197,"relevant":22,"comment":306},"论文探讨地理标志认证对农业绿色全要素生产率的影响，主题相关，有实证数据，但发表于MDPI期刊，权威性一般，且非最新发布。",[308],{"name":302,"url":299},[310,311,29,312,313],"中国","门槛效应","Sustainability","绿色全要素生产率",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[],{"status":40,"locked":14,"version":41,"method":42,"evidence":317},{"candidates":318,"agricultural_evidence":48},[319,323],{"code":33,"score":55,"supported":48,"title":320,"abstract":321,"tags":322},[],[29],[29],{"code":134,"score":22,"supported":14,"title":324,"abstract":325,"tags":326},[],[],[313],[328,329],"绿色全要素生产率 地理标志 门槛效应 中国","绿色全要素生产率 地理标志","绿色全要素生产率地理标志门槛效应中国-512","2026-08-13T23:53:47.475503Z",{"id":333,"title":334,"url":335,"summary":336,"summary_zh":9,"content":337,"source_name":338,"source_url":9,"published_at":339,"category":170,"cover_url":9,"hotness":13,"is_selected":14,"score":171,"score_detail":340,"sources":345,"tags":347,"primary_topic":351,"secondary_topics":352,"classification":353,"search_phrases":367,"slug":370,"view_count":55,"doi":9,"paper":9,"created_at":371},343,"农业农村部答复第3633号建议:支持特色农产品品牌建设与市场开拓","https:\u002F\u002Fwww.moa.gov.cn\u002Fgovpublic\u002FSCYJJXXS\u002F202608\u002Ft20260810_6486538.htm","针对王连增代表提出的特色农产品品牌建设和市场开拓建议,农业农村部经商商务部、市场监管总局、供销合作总社答复:印发《农业品牌精品培育计划(2022—2025年)》培育一批精品品牌,已建立123个国家地理标志保护示范区,持续优化信贷直通车服务、完善农业信贷担保体系、扩大农业农村有效投资。下一步将组织产销对接、品牌推介、消费促进等标志性活动,编制'十五五'全国农产品产地市场体系发展规划,持续推动产地冷藏保鲜设施、集配中心和产后处理能力建设,深化执法改革打击冒用质量标志与制售假劣农资违法行为。","农业农村部加大龙头企业、农民合作社等主体培育力度,指导建立完善利益联结机制,带动农民增收和产业提质。一是增强农民合作社服务带动农户发展能力。依托新型农业经营主体辅导员队伍,指导农民合作社开展品种培优、品质提升、品牌打造和标准化生产。二是引导龙头企业加强与农户的利益联结。印发《分类培育壮大农业企业工作方案》,明确分行业培育龙头企业、全产业链打造“链主”企业、强化联农带农等重点任务,促进农业企业做强做大,引导农业企业建立更加紧密的利益联结机制。总结推广龙头企业联农带农的5大模式、10种类型、20个案例,引导龙头企业通过订单收购、收益分成、就近就业、联合合作等形式,加强与农户的利益联结。三是发展多种联农带农机制。指导各地以优势特色产业集群、农业产业强镇等农业产业融合发展项目建设为契机,推广订单农业、保底分红、股份合作等多种联农带农机制,引导农民深度嵌入产业链,分享产业链增值收益。","农业农村部网站 2026-08-10","2026-08-10T00:00:00Z",{"impact":341,"substance":342,"depth":343,"authority":343,"freshness":13,"relevant":22,"comment":344},25,20,15,"农业农村部官方答复，涉及品牌建设与联农带农机制，政策层级高，内容具体，时效性强。",[346],{"name":338,"url":335},[348,349,29,350],"品牌建设","农产品","产销对接",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[],{"status":40,"locked":14,"version":41,"method":42,"evidence":354},{"candidates":355,"agricultural_evidence":48},[356,361],{"code":33,"score":174,"supported":48,"title":357,"abstract":359,"tags":360},[358],"农产品品牌",[358,29],[350,348,29],{"code":362,"score":61,"supported":48,"title":363,"abstract":364,"tags":366},"G3",[],[365],"农业信贷",[],[368,369],"产销对接 品牌建设 地理标志 农产品","产销对接 品牌建设","产销对接品牌建设地理标志农产品-343","2026-08-10T23:54:40.861686Z"]