[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-198":3,"related-198":67},{"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":31,"secondary_topics":37,"classification":38,"search_phrases":62,"slug":65,"view_count":19,"doi":8,"paper":8,"created_at":66},198,"以数促质:数字乡村建设赋能农业新质生产力的影响研究","https:\u002F\u002Fd.wanfangdata.com.cn\u002Fperiodical\u002Fdndxxb-zxsh202603009","利用中国2013-2023年省级面板数据,对数字乡村建设与农业新质生产力的关系及其作用机制进行理论分析与实证检验。研究发现:数字乡村建设显著促进农业新质生产力发展;通过推动数字普惠金融发展和促进农业技术进步两个中介渠道发挥作用;在中西部地区数字乡村建设能够推动农业新质生产力发展;在财政支农水平较高地区通过提升数字普惠金融水平、在农业产业链延伸水平较高地区通过促使农业技术进步,机制作用更显著。研究为各地因地制宜制定数字乡村建设政策、提升农业新质生产力提供理论与实证支撑。",null,"检测到您正在使用 Safari 浏览器，可能影响导出功能的正常使用，建议您下载 [Google Chrome](https:\u002F\u002Fwww.google.cn\u002Fintl\u002Fzh-CN\u002Fchrome\u002F)、 [Microsoft 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[10.3969\u002Fj.issn.1671-511X.2026.03.009](https:\u002F\u002Fd.wanfangdata.com.cn\u002Fperiodical\u002Fdndxxb-zxsh202603009)\n\n以\"数\"促\"质\":数字乡村建设赋能农业新质生产力的影响研究\n\n 文摘阅读 60\n\n 下载 1\n\n 导出题录 0\n\n 被引 0\n\n[张建平 1](https:\u002F\u002Fd.wanfangdata.com.cn\u002Fperiodical\u002Fdndxxb-zxsh202603009)[蔡嘉慧 2](https:\u002F\u002Fd.wanfangdata.com.cn\u002Fperiodical\u002Fdndxxb-zxsh202603009)[许润达 3](https:\u002F\u002Fd.wanfangdata.com.cn\u002Fperiodical\u002Fdndxxb-zxsh202603009)\n\n1.[江苏第二师范学院 商学院,江苏 南京 211200](https:\u002F\u002Fd.wanfangdata.com.cn\u002Fperiodical\u002Fdndxxb-zxsh202603009)2.[吉林大学 东北亚学院,吉林 长春 130012](https:\u002F\u002Fd.wanfangdata.com.cn\u002Fperiodical\u002Fdndxxb-zxsh202603009)3.[南京大学 商学院,江苏 南京 210023](https:\u002F\u002Fd.wanfangdata.com.cn\u002Fperiodical\u002Fdndxxb-zxsh202603009)\n\n[在线阅读](https:\u002F\u002Fd.wanfangdata.com.cn\u002Fperiodical\u002Fdndxxb-zxsh202603009)[下载](https:\u002F\u002Foss.wanfangdata.com.cn\u002Ffile\u002Fdownload\u002Fperio_dndxxb-zxsh202603009.aspx)[评审材料](https:\u002F\u002Fd.wanfangdata.com.cn\u002Fperiodical\u002Fdndxxb-zxsh202603009)\n\n引用\n\n收藏\n\n分享\n\n打印\n\n摘要：利用中国2013-2023 年省级面板数据,对数字乡村建设与农业新质生产力的关系及其作用机制进行理论分析与实证检验,研究发现:(1)数字乡村建设显著促进农业新质生产力发展.(2)数字乡村建设通过推动数字普惠金融发展和促进农业技术进步来发展农业新质生产力.(3)在中西部地区,数字乡村建设能够推动农业新质生产力发展;在财政支农水平较高的地区,数字乡村建设通过提升数字普惠金融水平推动农业新质生产力发展;在农业产业链延伸水平较高的地区,数字乡村建设通过促使农业技术进步推动农业新质生产力发展.研究结论为各地因地制宜制定数字乡村建设政策、提升农业新质生产力提供了有力的理论逻...\n\n关键词：\n\n[数字乡村建设](https:\u002F\u002Fd.wanfangdata.com.cn\u002Fperiodical\u002Fdndxxb-zxsh202603009)[农业新质生产力](https:\u002F\u002Fd.wanfangdata.com.cn\u002Fperiodical\u002Fdndxxb-zxsh202603009)[数字普惠金融](https:\u002F\u002Fd.wanfangdata.com.cn\u002Fperiodical\u002Fdndxxb-zxsh202603009)[农业技术进步](https:\u002F\u002Fd.wanfangdata.com.cn\u002Fperiodical\u002Fdndxxb-zxsh202603009)\n\n机标分类号：\n\nF306(农业经济理论)F832.35(金融、银行)TH161(机械制造工艺)\n\n资助基金：\n\n[中国博士后科学基金](https:\u002F\u002Fs.wanfangdata.com.cn\u002Fperiodical?q=%E5%9F%BA%E9%87%91%3A%E4%B8%AD%E5%9B%BD%E5%8D%9A%E5%A3%AB%E5%90%8E%E7%A7%91%E5%AD%A6%E5%9F%BA%E9%87%91) ( 2025M771829 ) [江苏省软科学研究项目](https:\u002F\u002Fs.wanfangdata.com.cn\u002Fperiodical?q=%E5%9F%BA%E9%87%91%3A%E6%B1%9F%E8%8B%8F%E7%9C%81%E8%BD%AF%E7%A7%91%E5%AD%A6%E7%A0%94%E7%A9%B6%E9%A1%B9%E7%9B%AE) ( BR2025025 ) [江苏省社会科学基金青年项目](https:\u002F\u002Fs.wanfangdata.com.cn\u002Fperiodical?q=%E5%9F%BA%E9%87%91%3A%E6%B1%9F%E8%8B%8F%E7%9C%81%E7%A4%BE%E4%BC%9A%E7%A7%91%E5%AD%A6%E5%9F%BA%E9%87%91%E9%9D%92%E5%B9%B4%E9%A1%B9%E7%9B%AE) ( 24MLC004 ) [江苏省高校社科联发展专项课题](https:\u002F\u002Fs.wanfangdata.com.cn\u002Fperiodical?q=%E5%9F%BA%E9%87%91%3A%E6%B1%9F%E8%8B%8F%E7%9C%81%E9%AB%98%E6%A0%A1%E7%A4%BE%E7%A7%91%E8%81%94%E5%8F%91%E5%B1%95%E4%B8%93%E9%A1%B9%E8%AF%BE%E9%A2%98) ( 25GSB-039 ) \n\n文献发表日期：\n\n 2026-05-20 \n\n在线出版日期：\n\n 2026-07-06 （万方平台首次上网日期，不代表文献的发表时间）\n\n页数：\n\n11 ( 78-88 )\n\n英文信息\n\n![Image 9](https:\u002F\u002Fc.wanfangdata.com.cn\u002F\u002Fimages\u002FPeriodicalImages\u002Fdndxxb-zxsh\u002Fdndxxb-zxsh.jpg)\n\n[](https:\u002F\u002Fd.wanfangdata.com.cn\u002Fperiodical\u002Fdndxxb-zxsh202603009)\n\n[东南大学学报（哲学社会科学版）](https:\u002F\u002Fc.wanfangdata.com.cn\u002Fmagazine\u002Fdndxxb-zxsh)\n\n CSTPCD  北大核心  CSSCI  AMI \n\nISSN：1671-511X \n\n年,卷(期)：[2026,28(3)](https:\u002F\u002Fc.wanfangdata.com.cn\u002Fmagazine\u002Fdndxxb-zxsh?tabId=article&publishYear=2026&issueNum=3)\n\n所属栏目：[经济决策与企业管理](https:\u002F\u002Fc.wanfangdata.com.cn\u002Fmagazine\u002Fdndxxb-zxsh\u002F?tabId=column&yearType=all&ztext=%E7%BB%8F%E6%B5%8E%E5%86%B3%E7%AD%96%E4%B8%8E%E4%BC%81%E4%B8%9A%E7%AE%A1%E7%90%86 \"经济决策与企业管理\")\n\n相关文献  换一换\n\n1.[农业数字化赋能农业新质生产力的效应研究](https:\u002F\u002Fd.wanfangdata.com.cn\u002Fperiodical\u002Fhnkx202601020 \"农业数字化赋能农业新质生产力的效应研究\")[夏静怡](https:\u002F\u002Fs.wanfangdata.com.cn\u002Fpaper?q=%E4%BD%9C%E8%80%85:%22%E5%A4%8F%E9%9D%99%E6%80%A1%22 \"夏静怡\") 等; 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2026-07-06上网","2026-07-06T00:00:00Z","论文",10,false,71,{"impact":17,"substance":18,"depth":17,"authority":19,"freshness":20,"relevant":21,"comment":22},18,20,13,2,1,"核心期刊论文，基于省级面板数据实证分析数字乡村建设对农业新质生产力的影响，数据详实、结论可靠，但发表时间较早，时效性低。",[24],{"name":10,"url":6},[26,27,28,29,30],"数字乡村","农业新质生产力","中介效应","省级面板","数字普惠金融",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},"I6","digital-village","数字乡村与数据要素","\u002Ftopic\u002Fdigital-agriculture\u002Fdigital-village","I",[],{"status":39,"locked":14,"version":40,"method":41,"evidence":42},"classified","2026-10-22.2","rules",{"candidates":43,"agricultural_evidence":46},[44,50,57],{"code":32,"score":45,"supported":46,"title":47,"abstract":48,"tags":49},12,true,[26],[26],[26],{"code":51,"score":52,"supported":46,"title":53,"abstract":54,"tags":56},"G3",4,[],[55],"财政支农",[30],{"code":58,"score":21,"supported":14,"title":59,"abstract":60,"tags":61},"J2",[],[],[27],[63,64],"农业新质生产力 数字普惠金融 中介效应 数字乡村","农业新质生产力 数字普惠金融","农业新质生产力数字普惠金融中介效应数字乡村-198","2026-08-04T01:15:47.409908Z",{"total":68,"page":21,"page_size":68,"items":69},6,[70,117,162,192,223,273],{"id":71,"title":72,"url":73,"summary":74,"summary_zh":8,"content":75,"source_name":76,"source_url":8,"published_at":77,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":78,"score_detail":79,"sources":83,"tags":85,"primary_topic":90,"secondary_topics":91,"classification":92,"search_phrases":108,"slug":111,"view_count":52,"doi":8,"paper":112,"created_at":116},1033,"数字乡村建设对农业新质生产力的影响效应与作用机制——基于2012—2023年30省份面板数据","http:\u002F\u002Fwww.qikanvip.com\u002Fqkml\u002F127584.html","原文标题:数字乡村建设对农业新质生产力的影响效应与作用机制。作者:杜一鸣、贾慧静、王强(西安交通大学马克思主义学院等)。基于2012—2023年中国30个省份的面板数据,采用双向固定效应模型,实证检验数字乡村建设对农业新质生产力的影响,并引入中介效应模型和调节效应模型考察农村创新创业活跃度的中介作用以及农村产业融合的调节效应。研究结果表明:数字乡村建设可以显著促进农业新质生产力提升,且这种促进作用在'胡焕庸线'以东地区、非粮食主产区及农业新质生产力水平较高的地区更为显著;农村创新创业活跃度发挥了部分中介作用;农村产业融合对数字乡村建设与农业新质生产力之间的关系具有显著的正向调节作用。","0\n\n发表咨询在线!\n\n###### ![Image 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[统计与决策2026年第01期](http:\u002F\u002Fwww.qikanvip.com\u002Fqkml\u002F2026T01T15982\u002F)\n3.   [数字乡村建设对农业新质生产力的影响效应与作用机制](http:\u002F\u002Fwww.qikanvip.com\u002Fqkml\u002F127584.html)\n\n# 统计与决策2026年第01期：数字乡村建设对农业新质生产力的影响效应与作用机制\n\n来源：[期刊VIP网](http:\u002F\u002Fwww.qikanvip.com\u002F)时间： 2026年8月28日 星期五\n\n* * *\n\n作者：杜一鸣;贾慧静;王强;\n\n单位：西安交通大学马克思主义学院;延安大学政法与公共管理学院;温州理工学院经济与管理学院;\n\n**摘要：**在加快培育新质生产力的背景下，数字乡村建设已成为推动农业现代化和农业生产力提升的重要路径，但其对农业新质生产力的作用路径与内在机制仍有待系统考察。文章基于2012—2023年中国30个省份的面板数据，采用双向固定效应模型，实证检验数字乡村建设对农业新质生产力的影响，并进一步引入中介效应模型和调节效应模型，考察农村创新创业活跃度的中介作用以及农村产业融合的调节效应。研究结果表明：数字乡村建设可以显著促进农业新质生产力提升，且这种促进作用在“胡焕庸线”以东地区、非粮食主产区及农业新质生产力水平较高的地区更为显著。从作用机制看，农村创新创业活跃度在数字乡村建设与农业新质生产力之间发挥了部分中介作用，数字要素投入通过激发农村创新创业活动加速了新质劳动者、新质劳动资料与新质劳动对象的形成与升级。此外，农村产业融合对数字乡村建设与农业新质生产力之间的关系具有显著的正向调节作用，农村产业融合水平越高，数字乡村建设对农业新质生产力的赋能作用越强。\n\n**关键词：**数字乡村建设;;农业新质生产力;;农村创新创业活跃度;;产业融合\n\n**基金资助：**浙江省哲学社会科学规划“省市合作”课题（25SSHZ079YB）\n\n##### 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方向：包装设计、装帧设计 ##### 了解适投期刊 #### 方向：新媒体、家具、陶瓷、旅游 ##### 了解适投期刊 #### 方向：非遗、戏剧、服装、书法 ##### 了解适投期刊 #### 方向：体育、教育 ##### 了解适投期刊](javascript:void(0))\n\n[站长统计](https:\u002F\u002Fwww.cnzz.com\u002Fstat\u002Fwebsite.php?web_id=1255393057 \"站长统计\")\n\n[理工科核心资源库](http:\u002F\u002Fwww.qikanvip.com\u002Fhot.html)","统计与决策 2026(1)","2026-08-20T16:00:00Z",76,{"impact":18,"substance":80,"depth":17,"authority":81,"freshness":20,"relevant":21,"comment":82},22,14,"基于省级面板数据的实证研究，探讨数字乡村建设对农业新质生产力的影响机制，数据详实、方法规范，但发表于2026年第1期，时效性较低。",[84],{"name":76,"url":73},[26,27,28,86,87,88,89],"双向固定效应","30省份面板","产业融合","胡焕庸线",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":14,"version":40,"method":41,"evidence":93},{"candidates":94,"agricultural_evidence":46},[95,99,104],{"code":32,"score":45,"supported":46,"title":96,"abstract":97,"tags":98},[26],[26],[26],{"code":100,"score":21,"supported":14,"title":101,"abstract":102,"tags":103},"G4",[],[],[88],{"code":58,"score":21,"supported":14,"title":105,"abstract":106,"tags":107},[],[],[27],[109,110],"农业新质生产力 双向固定效应 30省份面板 中介效应","农业新质生产力 双向固定效应","农业新质生产力双向固定效应30省份面板中介效应-1033",{"doi":8,"openalex_id":8,"authors":113,"venue":8,"cited_by_count":114,"oa_url":8,"card":8,"direction":8,"ingested_from":115},[],0,"agent","2026-08-28T00:07:02.181336Z",{"id":118,"title":119,"url":120,"summary":121,"summary_zh":8,"content":122,"source_name":123,"source_url":8,"published_at":124,"category":125,"cover_url":8,"hotness":13,"is_selected":46,"score":126,"score_detail":127,"sources":133,"tags":135,"primary_topic":139,"secondary_topics":140,"classification":141,"search_phrases":157,"slug":160,"view_count":114,"doi":8,"paper":8,"created_at":161},4623,"专家解读|提升乡村建设信息化水平,助力数字乡村高质量发展新征程","https:\u002F\u002Fwww.toutiao.com\u002Farticle\u002F7694591827630653987\u002F","中央网信办、农业农村部、工信部联合印发的《数字乡村高质量发展行动计划(2026—2030年)》明确十五五乡村建设信息化任务。截至2025年底,全国行政村5G通达率达95%,农村宽带用户2.04亿户,农村网民3.14亿人,农村互联网普及率69.5%,较十三五末提升13.6个百分点;远程医疗网络覆盖全国所有市县,农村中小学校(含教学点)互联网接入率达100%。","“十五五”时期是网络强国建设夯实基础、全面发力的关键时期，也是基本实现农业农村现代化的关键时期。近日，中央网信办、农业农村部、工业和信息化部印发《数字乡村高质量发展行动计划（2026—2030年）》（以下简称《行动计划》），以强农惠农富农为目标，对“十五五”时期数字乡村发展重点任务作出系统部署。乡村建设信息化是数字乡村建设的重点领域和关键环节，是直接关乎农民群众获得感、幸福感、安全感的基础性工程，对推进农村基本具备现代生活条件，激发乡村发展内生动力具有重要作用。\n\n一、把握当前数字乡村发展的新机遇新挑战\n\n近年来，我国数字乡村建设取得显著成效，特别是乡村建设信息化水平大幅提升，乡村基础设施和信息服务加快从“用得上”到“用得起”“用得好”转变，让广大农民群众在信息化发展中有更多获得感、幸福感、安全感。截至2025年底，全国行政村5G通达率已达95%，农村宽带用户总数达2.04亿户；农村网民规模达3.14亿人，农村地区互联网普及率达69.5%，较“十三五”末期提升13.6个百分点；远程医疗服务网络已覆盖全国所有市县，农村中小学校（含教学点）互联网接入率达100%。但对照数字乡村高质量发展的目标，还存在一些短板弱项，距离农民群众对美好生活期待还存在差距，需要加快推进乡村建设信息化，推动数字乡村发展迈上新台阶。\n\n一方面，乡村信息服务的供需适配性还有待提升。农村以及偏远地区的诊疗服务和教育资源分布不平衡、供给不充分现象还较为明显。“一老一小”、残疾人等重点人群的适老化、无障碍数字服务能力不足，乡村数字文化内容形式还较为单一，针对小农户等农业主体的轻量化数字金融产品供给有限，农村生态环境、农村污染源、土地利用的信息化监测水平不高，农村群众和基层干部的数字素养与技能水平还有待提升。另一方面，人工智能快速迭代发展为乡村建设带来宝贵机遇。当前我国大模型产品性能位居全球前列，人形机器人等规模化量产持续加速，智能体应用数量快速增长，推动乡村基础设施和信息服务数字化智能化升级，为乡村建设信息化提供了新动能。\n\n二、充分认识推进乡村建设信息化的重要意义\n\n习近平总书记指出，全面建设社会主义现代化国家，最艰巨最繁重的任务仍在农村。乡村建设信息化关系着数字乡村发展的成效和“底色”，是实现强农惠农富农目标的必由之路，通过充分运用人工智能、大数据、区块链等新一代信息技术，赋能乡村公共服务发展和生态人居环境改善，不断满足农民群众美好生活新期待的重要途径，对于加快数字乡村高质量发展具有重要意义和时代价值。\n\n一是缩小城乡公共服务差距。通过优化和完善信息服务，推动教育、医疗等优质资源下沉覆盖，推动打破城乡资源共享和双向流动壁垒，让农村群众在家门口就能够享受到便利普惠的公共服务，不断提升城乡基本公共服务均等化水平。\n\n二是推进乡村精神文明建设。通过推动乡村数字文化发展，激发乡村本土文化创作人才热情，丰富乡村优秀网络文化作品供给，推动培育文明乡风、良好家风、淳朴民风，满足农村群众对高质量精神文化生活的追求和期盼。同时，数智技术为农耕文化、非遗民俗、古村落遗产等乡村文化资源打造了永久保存与全域传播载体，促进中华优秀农耕文明创造性转化、创新性发展，为乡村文化守住根脉，为故土记忆留住“乡愁”。\n\n三是改善乡村生态人居环境。通过建设完善生态环境监测网络体系，系统部署物联网传感器、遥感监测等设备和智能分析系统，实现对农村生活环境及空气质量等重要指标的实时监测与智能预警，探索农村人居环境管理新模式，推动乡村生态环境治理从“被动响应”向“主动预防”转变。\n\n三、聚焦重点方向推进乡村建设信息化\n\n《行动计划》明确，“十五五”时期要聚焦乡村数字教育、乡村数字健康、重点人群信息服务保障、乡村普惠金融、乡村数字文化、智慧美丽乡村等重点方向，构建深度覆盖、普惠便捷、协同高效的乡村建设信息化体系，加速补齐系统性短板，释放数字惠民效能。\n\n一是提升乡村数字教育水平。农村和偏远地区的义务教育水平还存在薄弱环节，教育资源面临着供给不足的局面。要通过充分利用国家中小学智慧教育平台等平台资源，持续扩大优质教育资源的覆盖范围，推动优质课程向农村、偏远地区延伸。要合理利用人工智能等技术赋能乡村课堂教学，支持有条件的乡村学校部署智能教育终端、教育智能体等。要实施数字化赋能教师发展行动，常态化开展农村教师数字素养与技能培训，全面提升农村教师数字化教学能力。\n\n二是提升乡村数字健康服务水平。我国大量优质医疗资源还集中在县级以上行政区域，乡村医疗资源面临着人才、设备、运营、能力等结构性短板。同时，随着我国农村人口老龄化加剧，对长期慢病管理、康复护理、老年健康服务需求快速增长。要推进紧密型县域医共体信息化建设，打通县、乡、村三级医疗机构数据壁垒，提升医疗资源联动共享水平。要推广人工智能在乡村医疗服务中的应用，完善远程会诊、慢病管理线上服务网络，优化农村医保智能终端配置，促进医疗资源加速下沉。\n\n三是提升重点人群信息服务水平。我国农村还存在大量老年人和留守儿童，在数字接入服务、使用习惯等方面需求差异较大，需要乡村信息服务具备更强的包容性。要充分运用信息技术强化这些重点人群主动发现和精准救助能力，更好打通民政、医保、残联、养老等数据渠道，深入推进政务、医疗、金融、文化等各类数字服务的适老化、无障碍改造，建设更有温度的乡村信息服务体系。\n\n四是提升乡村数字普惠金融服务水平。小农户、新型农业经营主体等乡村经济“毛细血管”普遍面临融资难、融资贵、风控弱等问题，传统金融服务在覆盖广度和响应速度上难以满足其灵活、小额、高频的需求。要积极开展政银企农融资对接，引导金融机构立足农业生产周期、农户经营规模创新数字信贷、保险等产品，开发特色农业保险、农产品价格保险等适配农村经济活动特征和居民需求的产品，推动数字技术在农业保险全流程中的应用，提升农村普惠金融服务覆盖和使用水平。\n\n五是提升乡村数字文化发展水平。当前，乡村数字文化内容和渠道还较为缺乏，乡村文化活力还有待释放。要积极扶持“三农”题材的优秀网络文化作品创作，加快培育乡村本土文化创作人才队伍，激发网络文化作品创作活力。要提升乡村文化场所数字化应用水平，发挥县级融媒体中心等作用，打造乡村数字传播矩阵，拓宽乡土文化线上传播和优质文化资源下沉渠道。要开展农村文物资源、非遗传承人等数字化建档，推动非遗资源与数字文旅、乡村旅游深度融合，以数字技术传承和创新利用乡土文化资源。\n\n六是提升智慧美丽乡村建设水平。当前，一些地区乡村人居环境治理还存在监测手段粗放、管理响应滞后、运维机制不健全等问题，难以满足宜居宜业和美乡村建设要求。要推动构建“天空地海”一体化生态环境监测网络体系，强化农村污染源监测评估，支撑自然资源开发利用和生态保护修复工作，推动解决农村生态环境污染问题。要健全人居环境问题在线受理与响应机制，优化供水水质监测体系，推进生活污水设施数字化改造升级，梳理农房相关信息数据，持续改善农村人居环境。\n\n当前，我国数字乡村加快迈向高质量发展阶段。要立足乡村实际、坚持因地制宜、分类施策，提升乡村建设信息化水平，充分发挥以人工智能为代表的新一代信息技术作用，更好赋能乡村生产、生活和治理方式转型升级，推动农村基本具备现代生活条件，不断满足农民群众对美好生活的新期待，奋力书写数字乡村高质量发展新篇章，为全面推进乡村振兴、加快农业农村现代化注入持久数字力量。\n\n作者：王 江 中国网络空间研究院院长","闪电新闻\u002F中国网信网 2026-10-09","2026-10-09T00:00:00Z","报道",92,{"impact":128,"substance":129,"depth":17,"authority":130,"freshness":131,"relevant":21,"comment":132},28,23,15,8,"中央三部门联合印发数字乡村五年行动计划，含5G通达率95%等关键数据与六大重点方向，权威性与信息增量俱佳，值得进入每日精选。",[134],{"name":123,"url":120},[26,136,30,137,138],"农业人工智能","乡村建设信息化","智慧美丽乡村",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":14,"version":40,"method":41,"evidence":142},{"candidates":143,"agricultural_evidence":46},[144,148,152],{"code":32,"score":45,"supported":46,"title":145,"abstract":146,"tags":147},[26],[26],[26],{"code":51,"score":21,"supported":14,"title":149,"abstract":150,"tags":151},[],[],[30],{"code":153,"score":21,"supported":14,"title":154,"abstract":155,"tags":156},"I2",[],[],[136],[158,159],"乡村建设信息化 5G通达率","乡村建设信息化 农业人工智能 数字普惠金融 智慧美丽乡村","乡村建设信息化5G通达率-4623","2026-10-11T00:09:36.413889Z",{"id":163,"title":164,"url":165,"summary":166,"summary_zh":8,"content":167,"source_name":168,"source_url":8,"published_at":8,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":78,"score_detail":169,"sources":171,"tags":173,"primary_topic":178,"secondary_topics":179,"classification":180,"search_phrases":187,"slug":190,"view_count":20,"doi":8,"paper":8,"created_at":191},910,"数字乡村建设驱动宜居宜业和美乡村发展的整合框架：基于2013-2022中国省级面板数据","http:\u002F\u002Fwww.qikanvip.com\u002Fqkml\u002F157810.html","中国矿业大学（北京）共同富裕研究院杨璐璐、盖延凯、赵晶晶基于2013—2022年中国省级面板数据，构建数字生态系统理论视角下\"四维要素—三元互动\"整合模型，运用工具变量与动态面板模型应对内生性问题。研究发现：数字乡村建设及其各维度对和美乡村发展具有显著促进效应且结论稳健，乡村建设四维要素相互协同形成系统合力是关键；机制检验显示，乡村建设驱动绿色技术创新与农业产业集聚形成链式传导机制，驱动数字治理水平形成正向调节机制；上述路径在西部地区表现尤为突出。","0\n\n发表咨询在线!\n\n###### ![Image 1](https:\u002F\u002Fwww20.53kf.com\u002Fimg\u002Fupload\u002F10171130\u002Fmobile\u002Ftemp\u002Fmobile_53kf_1519890059.gif)\n\n您身边的学术顾问\n\n![Image 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[现代财经(天津财经大学学报)2026年第05期](http:\u002F\u002Fwww.qikanvip.com\u002Fqkml\u002F2026T05T16111\u002F)\n3.   [数字乡村建设如何驱动宜居宜业和美乡村发展?](http:\u002F\u002Fwww.qikanvip.com\u002Fqkml\u002F157810.html)\n\n# 现代财经(天津财经大学学报)2026年第05期：数字乡村建设如何驱动宜居宜业和美乡村发展?\n\n来源：[期刊VIP网](http:\u002F\u002Fwww.qikanvip.com\u002F)时间： 2026年8月24日 星期一\n\n* * *\n\n作者：杨璐璐;盖延凯;赵晶晶;\n\n单位：中国矿业大学(北京)共同富裕研究院;中国矿业大学(北京)文法学院;\n\n**摘要：**数字乡村是乡村振兴的战略方向，也是推进宜居宜业和美乡村建设的必由之路。本文聚焦数字乡村建设如何驱动宜居宜业和美乡村发展这一核心问题，基于2013—2022年中国省级面板数据，构建数字生态系统理论视角下“四维要素—三元互动”整合模型，并用工具变量与动态面板模型应对内生性问题，从协同演化视角分析数字乡村建设推动宜居宜业和美乡村发展的内在机制。研究发现，数字乡村建设及其各维度对和美乡村发展具有显著促进效应且结论稳健，乡村建设四维要素相互协同形成系统合力是关键。机制检验发现，乡村建设驱动绿色技术创新与农业产业集聚形成链式传导机制，驱动数字治理水平形成正向调节机制。具体而言，数字资金投入通过技术路径发挥作用，数字基础设施通过产业路径发挥作用，数字产业与服务则通过治理调节下的“技术—产业”传导路径发挥作用。异质性检验发现，上述路径在西部地区表现尤为突出。研究结论为构建数字乡村协同共生发展模式，并建立因地制宜、分类推进的差异化发展机制，提供了理论依据与实践路径。\n\n**关键词：**数字乡村;;和美乡村;;链式中介效应;;协同演化\n\n**基金资助：**北京市社会科学基金重点项目(青年学术带头人项目)(24DTR033)\n\n##### 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\"站长统计\")\n\n[理工科核心资源库](http:\u002F\u002Fwww.qikanvip.com\u002Fhot.html)","现代财经（天津财经大学学报）2026年第5期",{"impact":18,"substance":80,"depth":17,"authority":81,"freshness":20,"relevant":21,"comment":170},"基于省级面板数据的实证研究，为数字乡村建设提供理论框架与政策参考，但时效性较低。",[172],{"name":168,"url":165},[26,29,174,175,176,177],"和美乡村","宜居宜业","链式中介","协同演化",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":14,"version":40,"method":41,"evidence":181},{"candidates":182,"agricultural_evidence":46},[183],{"code":32,"score":45,"supported":46,"title":184,"abstract":185,"tags":186},[26],[26],[26],[188,189],"协同演化 和美乡村 宜居宜业 数字乡村","协同演化 和美乡村","协同演化和美乡村宜居宜业数字乡村-910","2026-08-24T00:06:13.298942Z",{"id":193,"title":194,"url":195,"summary":196,"summary_zh":8,"content":197,"source_name":198,"source_url":8,"published_at":8,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":199,"score_detail":200,"sources":202,"tags":204,"primary_topic":209,"secondary_topics":210,"classification":211,"search_phrases":218,"slug":221,"view_count":68,"doi":8,"paper":8,"created_at":222},340,"数字乡村建设对农业经济韧性的影响研究——基于2014—2023年中国30个省区市面板数据","https:\u002F\u002Fd.wanfangdata.com.cn\u002Fperiodical\u002Fynnydxxb-s202608016","在数字化快速发展背景下,作者基于2014—2023年中国30个省区市面板数据,运用双向固定效应模型和中介效应模型,系统考察数字乡村建设对农业经济韧性的影响与传导机制。研究发现:数字乡村建设显著提升农业经济韧性,且这种正向效应在自然灾害频发区、粮食主产区及高数字乡村试点区表现更为突出;传导机制主要通过促进农业技术创新实现。建议继续推进数字乡村建设,强化农业技术创新,实施差异化扶持政策以增强农业经济韧性。基金项目:安徽省社会科学创新发展研究课题(2024AH050264)。","检测到您正在使用 Safari 浏览器，可能影响导出功能的正常使用，建议您下载 [Google Chrome](https:\u002F\u002Fwww.google.cn\u002Fintl\u002Fzh-CN\u002Fchrome\u002F)、 [Microsoft 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[10.12371\u002Fj.ynau(s).202603058](https:\u002F\u002Fd.wanfangdata.com.cn\u002Fperiodical\u002Fynnydxxb-s202608016)\n\n数字乡村建设对农业经济韧性的影响研究\n\n 文摘阅读 11\n\n 下载 0\n\n 导出题录 0\n\n 被引 0\n\n[潘和平](https:\u002F\u002Fd.wanfangdata.com.cn\u002Fperiodical\u002Fynnydxxb-s202608016)[胡熠](https:\u002F\u002Fd.wanfangdata.com.cn\u002Fperiodical\u002Fynnydxxb-s202608016)[章蓓蓓](https:\u002F\u002Fd.wanfangdata.com.cn\u002Fperiodical\u002Fynnydxxb-s202608016)\n\n[安徽建筑大学 经济与管理学院,安徽 合肥 230022](https:\u002F\u002Fd.wanfangdata.com.cn\u002Fperiodical\u002Fynnydxxb-s202608016)\n\n[在线阅读](https:\u002F\u002Fd.wanfangdata.com.cn\u002Fperiodical\u002Fynnydxxb-s202608016)[下载](https:\u002F\u002Foss.wanfangdata.com.cn\u002Ffile\u002Fdownload\u002Fperio_ynnydxxb-s202608016.aspx)[评审材料](https:\u002F\u002Fd.wanfangdata.com.cn\u002Fperiodical\u002Fynnydxxb-s202608016)\n\n引用\n\n收藏\n\n分享\n\n打印\n\n摘要：在数字化快速发展的时代背景下,数字乡村建设正日益成为增强农业经济韧性、推动农业高质量发展的关键力量.基于 2014-2023年中国 30个省区市面板数据,运用双向固定效应模型和中介效应模型,系统考察数字乡村建设对农业经济韧性的影响与传导机制.研究结果表明:数字乡村建设显著提升农业经济韧性,且这种正向效应在自然灾害频发区、粮食主产区及高数字乡村试点区表现更为突出,其传导机制主要通过促进农业技术创新实现.据此,应继续推进数字乡村建设,强化农业技术创新,实施差异化扶持政策以增强农业经济韧性.\n\n关键词：\n\n[数字乡村建设](https:\u002F\u002Fd.wanfangdata.com.cn\u002Fperiodical\u002Fynnydxxb-s202608016)[农业经济韧性](https:\u002F\u002Fd.wanfangdata.com.cn\u002Fperiodical\u002Fynnydxxb-s202608016)[农业技术创新](https:\u002F\u002Fd.wanfangdata.com.cn\u002Fperiodical\u002Fynnydxxb-s202608016)[传导机制](https:\u002F\u002Fd.wanfangdata.com.cn\u002Fperiodical\u002Fynnydxxb-s202608016)\n\n分类号：\n\nF323(中国农业经济)\n\n资助基金：\n\n[安徽省社会科学创新发展研究课题](https:\u002F\u002Fs.wanfangdata.com.cn\u002Fperiodical?q=%E5%9F%BA%E9%87%91%3A%E5%AE%89%E5%BE%BD%E7%9C%81%E7%A4%BE%E4%BC%9A%E7%A7%91%E5%AD%A6%E5%88%9B%E6%96%B0%E5%8F%91%E5%B1%95%E7%A0%94%E7%A9%B6%E8%AF%BE%E9%A2%98) ( 2024AH050264 ) \n\n文献发表日期：\n\n 2026-08-31 \n\n在线出版日期：\n\n 2026-07-24 （万方平台首次上网日期，不代表文献的发表时间）\n\n页数：\n\n8 ( 136-143 )\n\n英文信息\n\n![Image 7](https:\u002F\u002Fc.wanfangdata.com.cn\u002F\u002Fimages\u002FPeriodicalImages\u002Fynnydxxb-s\u002Fynnydxxb-s.jpg)\n\n[](https:\u002F\u002Fd.wanfangdata.com.cn\u002Fperiodical\u002Fynnydxxb-s202608016)\n\n[云南农业大学学报](https:\u002F\u002Fc.wanfangdata.com.cn\u002Fmagazine\u002Fynnydxxb-s)\n\n CSCD  AMI \n\nISSN：1004-390X\n\n年,卷(期)：[2026,20(8)](https:\u002F\u002Fc.wanfangdata.com.cn\u002Fmagazine\u002Fynnydxxb-s?tabId=article&publishYear=2026&issueNum=8)\n\n所属栏目：[农业农村现代化](https:\u002F\u002Fc.wanfangdata.com.cn\u002Fmagazine\u002Fynnydxxb-s\u002F?tabId=column&yearType=all&ztext=%E5%86%9C%E4%B8%9A%E5%86%9C%E6%9D%91%E7%8E%B0%E4%BB%A3%E5%8C%96 \"农业农村现代化\")\n\n相关文献  换一换\n\n1.[数字乡村建设对新型农村集体经济发展的影响研究](https:\u002F\u002Fd.wanfangdata.com.cn\u002Fperiodical\u002Fjxnyxb202607016 \"数字乡村建设对新型农村集体经济发展的影响研究\")[翟福意](https:\u002F\u002Fs.wanfangdata.com.cn\u002Fpaper?q=%E4%BD%9C%E8%80%85:%22%E7%BF%9F%E7%A6%8F%E6%84%8F%22 \"翟福意\") 等; [江西农业学报](https:\u002F\u002Fc.wanfangdata.com.cn\u002Fmagazine\u002Fjxnyxb \"江西农业学报\");2026\n\n2.[数字乡村建设对农业经济韧性的影响——基于产业结构升级调节效应](https:\u002F\u002Fd.wanfangdata.com.cn\u002Fperiodical\u002Fybxyxb202502002 \"数字乡村建设对农业经济韧性的影响——基于产业结构升级调节效应\")[陈丽宇;](https:\u002F\u002Fs.wanfangdata.com.cn\u002Fpaper?q=%E4%BD%9C%E8%80%85:%22%E9%99%88%E4%B8%BD%E5%AE%87%22 \"陈丽宇\")[宜宾学院学报](https:\u002F\u002Fc.wanfangdata.com.cn\u002Fmagazine\u002Fybxyxb \"宜宾学院学报\");2025\n\n3.[乡村数字基础设施对农业经济韧性的影响分析](https:\u002F\u002Fd.wanfangdata.com.cn\u002Fperiodical\u002Flyjj202512002 \"乡村数字基础设施对农业经济韧性的影响分析\")[曹楚涵](https:\u002F\u002Fs.wanfangdata.com.cn\u002Fpaper?q=%E4%BD%9C%E8%80%85:%22%E6%9B%B9%E6%A5%9A%E6%B6%B5%22 \"曹楚涵\") 等; [林业经济](https:\u002F\u002Fc.wanfangdata.com.cn\u002Fmagazine\u002Flyjj \"林业经济\");2025\n\n4.[数字乡村对农业经济韧性影响机制——基于城乡融合中介效应分析](https:\u002F\u002Fd.wanfangdata.com.cn\u002Fperiodical\u002Fzgnjh202511045 \"数字乡村对农业经济韧性影响机制——基于城乡融合中介效应分析\")[郅建迪](https:\u002F\u002Fs.wanfangdata.com.cn\u002Fpaper?q=%E4%BD%9C%E8%80%85:%22%E9%83%85%E5%BB%BA%E8%BF%AA%22 \"郅建迪\") 等; [中国农机化学报](https:\u002F\u002Fc.wanfangdata.com.cn\u002Fmagazine\u002Fzgnjh \"中国农机化学报\");2025\n\n5.[数字乡村建设对中国农业韧性的影响机制——基于中介效应和门槛效应模型的实证研究](https:\u002F\u002Fd.wanfangdata.com.cn\u002Fperiodical\u002Fhljdwjm202503008 \"数字乡村建设对中国农业韧性的影响机制——基于中介效应和门槛效应模型的实证研究\")[李小玉;](https:\u002F\u002Fs.wanfangdata.com.cn\u002Fpaper?q=%E4%BD%9C%E8%80%85:%22%E6%9D%8E%E5%B0%8F%E7%8E%89%22 \"李小玉\")[对外经贸](https:\u002F\u002Fc.wanfangdata.com.cn\u002Fmagazine\u002Fhljdwjm \"对外经贸\");2025\n\n[![Image 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\"调节效应\")[数字乡村](https:\u002F\u002Fd.wanfangdata.com.cn\u002Fperiodical\u002Fynnydxxb-s202608016 \"数字乡村\")[城乡融合](https:\u002F\u002Fd.wanfangdata.com.cn\u002Fperiodical\u002Fynnydxxb-s202608016 \"城乡融合\")\n\n相关学者\n\n[廖信林](https:\u002F\u002Fd.wanfangdata.com.cn\u002Fperiodical\u002Fynnydxxb-s202608016 \"廖信林\")[安徽财经大学](https:\u002F\u002Fd.wanfangdata.com.cn\u002Fperiodical\u002Fynnydxxb-s202608016 \"安徽财经大学\")\n\n[黄洁萍](https:\u002F\u002Fd.wanfangdata.com.cn\u002Fperiodical\u002Fynnydxxb-s202608016 \"黄洁萍\")[北京理工大学](https:\u002F\u002Fd.wanfangdata.com.cn\u002Fperiodical\u002Fynnydxxb-s202608016 \"北京理工大学\")\n\n[王培培](https:\u002F\u002Fd.wanfangdata.com.cn\u002Fperiodical\u002Fynnydxxb-s202608016 \"王培培\")[山东管理学院](https:\u002F\u002Fd.wanfangdata.com.cn\u002Fperiodical\u002Fynnydxxb-s202608016 \"山东管理学院\")\n\n[钱晨](https:\u002F\u002Fd.wanfangdata.com.cn\u002Fperiodical\u002Fynnydxxb-s202608016 \"钱晨\")[南京农业大学](https:\u002F\u002Fd.wanfangdata.com.cn\u002Fperiodical\u002Fynnydxxb-s202608016 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136-143",72,{"impact":17,"substance":80,"depth":17,"authority":45,"freshness":20,"relevant":21,"comment":201},"基于省级面板数据的实证研究，结论可靠，但时效性较差。",[203],{"name":198,"url":195},[26,205,28,206,207,208],"农业经济韧性","30省面板","农业技术创新","云南农业大学学报",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":14,"version":40,"method":41,"evidence":212},{"candidates":213,"agricultural_evidence":46},[214],{"code":32,"score":45,"supported":46,"title":215,"abstract":216,"tags":217},[26],[26],[26],[219,220],"云南农业大学学报 农业技术创新 农业经济韧性 中介效应","云南农业大学学报 农业技术创新","云南农业大学学报农业技术创新农业经济韧性中介效应-340","2026-08-09T23:54:49.601668Z",{"id":224,"title":225,"url":226,"summary":227,"summary_zh":8,"content":228,"source_name":229,"source_url":8,"published_at":230,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":231,"score_detail":232,"sources":234,"tags":236,"primary_topic":239,"secondary_topics":240,"classification":247,"search_phrases":268,"slug":271,"view_count":131,"doi":8,"paper":8,"created_at":272},197,"Digital Village Development and Agricultural Carbon Reduction in China: Evidence from Provincial Panel Data(中国数字乡村发展与农业碳减排:来自省级面板数据的证据)","https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F14\u002F7482","基于2014-2023年中国30个省份平衡面板数据,文章考察了数字乡村发展与农业投入品相关碳排放的关系。研究构建了由8个标准化指标组成的复合数字乡村指数,采用双向固定效应模型进行实证估计。结果显示,在控制经济、财政、技术、监管等多重因素后,数字乡村发展与农业碳排放显著负相关,使用农村电商代理变量和替代性指标检验后结论依然稳健。异质性分析表明,在农村受教育水平较高、中部地区及粮食主产区,负相关关系更强。研究认为数字乡村建设能够支撑农业低碳转型,前提是数字基础设施转化为有效的产业应用、公共服务、人力资本开发和生产组织改善。","## 1. Introduction\n\nClimate change, ecological degradation, and the continued growth of greenhouse gas (GHG) emissions continue to place considerable pressure on global sustainable development. Carbon mitigation is not only an environmental issue but also a strategic development goal for China. The country has announced that before 2030, it will reach peak carbon dioxide emissions, and before 2060, it will become carbon neutral [[1](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F14\u002F7482#B1-sustainability-18-07482)]. While emissions from sectors based primarily on CO 2 combustion from fossil fuels are different from agricultural emissions, this means that achieving national climate targets will not be possible without mitigation measures in all parts of the economy, not just in heavy industry, power generation and transport [[2](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F14\u002F7482#B2-sustainability-18-07482)]. It is, hence, essential for policies concerning agricultural and rural progress to be incorporated into the holistic framework of climate governance in China.\n\nWhen compared with manufacturing, electricity generation, transportation or construction, agriculture is sometimes considered a relatively low-carbon industry. However, this perception might not consider the significant carbon footprint of today’s food production. The current agricultural system relies on chemical fertilisers, pesticides, plastic mulch, machinery powered by diesel, and irrigation and tillage systems. These inputs and practices are sources of emissions during their manufacture and distribution and also during their use on-farm; they are significant contributors to agricultural carbon emissions [[3](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F14\u002F7482#B3-sustainability-18-07482)]. Fossil energy is also required during irrigation and land management operations, which can also have an impact on the soil carbon cycle and consequently increase the climate change footprint of agriculture [[4](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F14\u002F7482#B4-sustainability-18-07482)]. The spatial distribution of agricultural emissions in China is uneven, and high emissions are frequently found in the north. This trend is due to variations in natural resource endowments, crop composition, production technologies, intensities of production inputs, and local policies [[5](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F14\u002F7482#B5-sustainability-18-07482)]. Earlier empirical studies have also revealed that the performance of emissions varies widely across regions, suggesting that mitigating policies should be flexible and locally tailored instead of managed at the national level [[6](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F14\u002F7482#B6-sustainability-18-07482)]. Technological progress and the change of the organisation of agricultural production have been important means of achieving a low-carbon transition in agriculture in this context [[7](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F14\u002F7482#B7-sustainability-18-07482)].\n\nRural economies are changing in the context of digitalisation all over the world. The collection, transfer, interpretation and utilisation of agricultural information is transforming through big data analysis, Internet of Things (IoT) equipment, mobile communication networks, remote sensing technologies, cloud-based platforms, and digital service systems. Evidence from the international literature shows that data-intensive farming can lead to better resource allocation and a reduction in the waste of resources [[8](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F14\u002F7482#B8-sustainability-18-07482)]. Smart farming systems can help to better manage water, fertilisers, pesticides and machinery [[9](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F14\u002F7482#B9-sustainability-18-07482)]. However, rural digital transformation is not merely the introduction of new equipment into agricultural production. It also transforms agricultural extension, institutions at the local level, market linkages, farmers’ behaviour in managing business, and the linkages among farmers, service providers, firms and consumers [[10](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F14\u002F7482#B10-sustainability-18-07482)].\n\nThe impacts of digital agriculture are quite varied at the national and regional levels. In many high-income countries, sensor-based systems, IoT applications and automated control technologies have been adopted for large-scale commercial farming. In these situations, digital solutions have shown the potential to optimise input usage and create tangible gains in emissions reductions [[11](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F14\u002F7482#B11-sustainability-18-07482)]. On the other hand, there is still a significant gap in agriculture mechanisation, according to data from many low- and middle-income economies. Digitalisation is limited by weak rural infrastructure, fragmented farms, limited financial access and a lack of technical support to achieve environmental gains [[12](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F14\u002F7482#B12-sustainability-18-07482)]. Such disparities reveal that the climatic effects brought by digital farming hinge on plot scale, institutional arrangement, human capital stock and matched service infrastructures. The digital village strategy in China has emerged in an agricultural landscape dominated by smallholders. It is not the “smart-farm” model that has been adopted by many advanced economies, nor is it the more nascent digital agriculture model in many low-income economies. It, thus, serves as a valuable case study to explore the linkages between rural digitalisation and agricultural carbon mitigation in the context of a developing country.\n\nIn China, digital village development is not limited to access to the internet or the construction of hardware. It is a holistic rural transformation approach integrating digital infrastructure, digital industry, public services, financial inclusion, logistics systems and e-governance. According to comparisons among different provinces, it is known that the development of the digital village is still in an imbalanced state in China [[13](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F14\u002F7482#B13-sustainability-18-07482)]. Recent evaluation studies also indicate a close relationship between digital rural development results and rural revitalisation outcomes and governance capacity [[14](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F14\u002F7482#B14-sustainability-18-07482)]. The advancement of the rural digital economy has further facilitated industrial upgrading and the restructuring of local production and organisational patterns [[15](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F14\u002F7482#B15-sustainability-18-07482)]. Digital platforms have made the farmers’ market more accessible, brought agricultural products into circulation faster and have helped rural household income and welfare [[16](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F14\u002F7482#B16-sustainability-18-07482)].\n\nHowever, the environmental implications of digital village development remain insufficiently understood. From a macro perspective, the digital economy promotes green total factor productivity through three channels: knowledge spillover, optimised resource allocation and industrial structure transformation [[17](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F14\u002F7482#B17-sustainability-18-07482)]. In China, internet development has impacted energy consumption in three ways: energy use efficiency, the nature of energy consumption, and industrial transformation [[18](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F14\u002F7482#B18-sustainability-18-07482)]. International evidence also suggests that digitalisation can contribute to energy transition, but the impact is contingent on the quality of local governance and institutional capacity [[19](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F14\u002F7482#B19-sustainability-18-07482)]. Based on the empirical studies conducted in China, energy intensity and emissions may be reduced by digitalisation if the conditions are suitable [[20](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F14\u002F7482#B20-sustainability-18-07482)]. Digitalisation in agriculture has the potential to lower carbon intensity through structural change and technological innovation [[21](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F14\u002F7482#B21-sustainability-18-07482)]. Digital village development can also enhance information flow and the land use of cultivated lands, which can help greener land use transformation [[22](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F14\u002F7482#B22-sustainability-18-07482)]. There is recent research evidence that digitalisation in the countryside can enhance the green performance of agricultural production; however, direct evidence on input-related agricultural carbon emissions remains limited [[23](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F14\u002F7482#B23-sustainability-18-07482)].\n\nInternational studies have highlighted the importance of institutional arrangements and rural human capital in determining the potential of turning digital tools into low-carbon farming practices [[24](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F14\u002F7482#B24-sustainability-18-07482),[25](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F14\u002F7482#B25-sustainability-18-07482)]. Many developing economies are confronted with two pressures: on the one hand, rural digitalisation remains underdeveloped, while on the other hand, agricultural production relies on carbon-intensive inputs. The lessons learned from China suggest that digitalisation can contribute to emission reduction and green transition if it is integrated into relevant policy systems, service systems, and production systems; thus, the country is able to offer empirical references for nations confronting similar development challenges [[20](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F14\u002F7482#B20-sustainability-18-07482),[21](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F14\u002F7482#B21-sustainability-18-07482),[26](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F14\u002F7482#B26-sustainability-18-07482)].\n\nDespite growing interest in the environmental consequences of digitalisation, several gaps remain. First, much of the existing literature examines the general digital economy, urban digitalisation, or isolated digital–agricultural technologies, while fewer studies focus on digital village development as a multidimensional rural transformation process that integrates infrastructure, industrial applications, public services, digital finance, logistics, and rural e-commerce. Second, agricultural carbon emissions from the input side and the field-operation side have been less directly discussed in many studies, while agricultural green total factor productivity, carbon intensity, and pollution indicators are used as outcome variables. Third, there is scarce evidence regarding the circumstances in which digital village development is more strongly connected to agricultural carbon mitigation, including its relationship to rural education, the region in which it is implemented, grain-functional areas, and mechanisation. Fourth, there is a need for increased transparency in the construction of the composite digital village indicators, including indicator selection, PCA loadings, and the contribution of various digital dimensions.\n\nThe following question guides this study: is digital village development associated with lower agricultural carbon emissions across China? A multidimensional digital village development index is constructed from eight standardised indicators to answer this question. PCA diagnostics and a PCA-based alternative index are further used to examine the validity and sensitivity of the index construction. To estimate the relationship between digital village development and agricultural carbon emissions, this study utilises balanced panel datasets covering 30 provincial regions from 2014 to 2023. Empirical analysis consists of two-way fixed-effects models, multiple robustness tests, heterogeneity analysis, and an additional instrumental-variable exercise (reported in the [Appendix A](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F14\u002F7482#app1-sustainability-18-07482)) and exploratory subgroup analysis with regard to potential mechanisms.\n\nThis study contributes to the literature in three ways. First, it links digital village development with agricultural climate governance by examining input-related agricultural carbon emissions rather than only rural income, industrial upgrading, or agricultural green total factor productivity. Unlike recent prefecture-level or county-level studies that usually focus on the rural digital economy or agricultural green productivity, this study treats the digital village as a multidimensional policy and development framework and directly examines input-related agricultural carbon emissions. Second, it constructs a multidimensional digital village index from eight standardised indicators and reports additional PCA diagnostics, including component loadings, variance contribution, and the KMO statistic. It also uses a recomputed PCA-based index as a sensitivity check, thereby improving the transparency and reproducibility of index construction. Third, it examines heterogeneous associations across rural education levels, regions, grain-functional areas, and mechanisation conditions and provides mechanism-related evidence based on different agricultural carbon-emission sources.\n\nChina’s digital village strategy has a distinctive institutional context. It has developed in a smallholder-dominated agricultural system but is supported by national rural revitalisation policies, public investment in digital infrastructure, the rapid expansion of rural e-commerce, digital inclusive finance, and logistics networks. This differs from the capital-intensive smart-farming model in many high-income economies and from more fragmented digital–agriculture initiatives in some low-income economies. Therefore, the findings should not be interpreted as mechanically generalisable to all countries. Rather, they provide analytical evidence for developing economies seeking to combine rural digital inclusion, agricultural modernisation, and low-carbon transition under smallholder conditions.\n\nThe remainder of this paper is organised as follows. [Section 2](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F14\u002F7482#sec2-sustainability-18-07482) reviews the related literature. [Section 3](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F14\u002F7482#sec3-sustainability-18-07482) develops the theoretical framework and research hypotheses. [Section 4](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F14\u002F7482#sec4-sustainability-18-07482) describes the data, variables, and empirical models. [Section 5](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F14\u002F7482#sec5-sustainability-18-07482) presents the empirical results. [Section 6](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F14\u002F7482#sec6-sustainability-18-07482) discusses the findings. [Section 7](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F14\u002F7482#sec7-sustainability-18-07482) concludes the paper and provides policy implications.\n\n## 2. Literature Review\n\n### 2.1. Digital Village Development and Rural Transformation\n\nDigital village development is a comprehensive process of rural transformation which involves the connectivity of infrastructure, digital industrial activities, service delivery and the modernisation of governance. Digital tools improve agricultural production efficiency through real-time data gathering, remote farm supervision, precision agricultural management and data-driven decision-making [[27](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F14\u002F7482#B27-sustainability-18-07482)]. A special characteristic of digitalisation in the rural areas of China is the fast development of rural e-business, especially the growth of the ‘Taobao villages’ linked to big online platforms [[28](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F14\u002F7482#B28-sustainability-18-07482)]. These new rural economic models are examples of the way that digital marketplaces can connect geographically dispersed producers with national consumer markets and encourage local entrepreneurship [[28](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F14\u002F7482#B28-sustainability-18-07482),[29](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F14\u002F7482#B29-sustainability-18-07482)]. Advancement in the development of digital villages helps bridge the income gap between urban and rural residents. It enables rural populations to gain easier access to information, employment opportunities, financial services, logistics systems and public service facilities [[29](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F14\u002F7482#B29-sustainability-18-07482)]. New evidence from the provinces shows that digital village development can also help to foster agricultural green growth [[30](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F14\u002F7482#B30-sustainability-18-07482)].\n\nThe majority of studies published so far agree that digital village development can bring about economic and social benefits and that the impact on the environment is more complex [[17](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F14\u002F7482#B17-sustainability-18-07482),[21](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F14\u002F7482#B21-sustainability-18-07482),[22](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F14\u002F7482#B22-sustainability-18-07482)]. Increased digital infrastructure can, on the one hand, lead to a higher electricity demand and a higher use of digital equipment in rural areas. Conversely, there are applications in the fields of precision agriculture, rural logistics, e-commerce and extension that could help to decrease the overuse of agricultural inputs, enhance coordination and lower agricultural carbon emissions [[22](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F14\u002F7482#B22-sustainability-18-07482)].\n\nThe environmental impact overall will hinge on how the implementation of digital infrastructure is followed by productive applications and service innovations that impact decisions in agricultural production. International experiences demonstrate that digitalisation in rural areas can take several forms in different countries. In the high-income context of Western Europe, digital technologies are frequently used in large mechanised agriculture, but their use is still dependent on the social, political and institutional situation in rural communities [[31](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F14\u002F7482#B31-sustainability-18-07482)]. In many of the settings in which digital benefits are explored in developing contexts, these services are also critical, including mobile money, input markets, extension networks, and reliable infrastructure. Smallholder dominance might also constrain the environmental benefits of applications of digital technology, unless service systems can be developed to address scale constraints [[32](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F14\u002F7482#B32-sustainability-18-07482)]. These differences indicate that the size of the farm, institutional conditions and service capacity play a key role in whether or not rural digitalisation can make a positive contribution to carbon reduction.\n\n### 2.2. Agricultural Carbon Emissions: Measurement, Drivers, and Mitigation\n\nIn the agricultural carbon-accounting literature in China, emissions are often estimated based on the inputs and field operations of agricultural production processes [[3](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F14\u002F7482#B3-sustainability-18-07482),[5](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F14\u002F7482#B5-sustainability-18-07482),[7](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F14\u002F7482#B7-sustainability-18-07482)]. The use of chemical fertilisers, pesticides and plastic mulch films continues to be a significant source of the carbon footprint of Chinese agriculture [[33](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F14\u002F7482#B33-sustainability-18-07482)]. Other practices such as diesel, irrigation and tillage are also important because they are closely related to energy use and field management. Agricultural emissions of carbon are highly location- and time-dependent and are influenced by land resources, planting systems, mechanisation, environmental policies and input levels [[34](https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F14\u002F7482#B34-sustainability-18-07482)].\n\nDigitalisation has increasingly been regarded as a potential pathway for greener agricultural development. Digital technologies offer the potential to better allocate reso","Sustainability 18(14):7482 2026-07-22","2026-07-22T00:00:00Z",74,{"impact":18,"substance":80,"depth":17,"authority":45,"freshness":20,"relevant":21,"comment":233},"基于省级面板数据实证研究数字乡村对农业碳减排的影响，方法严谨，结论具有政策参考价值，但发表于近两周前，时效性较低。",[235],{"name":229,"url":226},[26,237,29,86,238],"农业碳减排","可持续发展",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[241],{"code":242,"slug":243,"name":244,"path":245,"parent_code":246},"H4","carbon","农业碳与绿色低碳","\u002Ftopic\u002Fenvironment\u002Fcarbon","H",{"status":39,"locked":14,"version":40,"method":41,"evidence":248},{"candidates":249,"agricultural_evidence":46},[250,255,261],{"code":32,"score":18,"supported":46,"title":251,"abstract":253,"tags":254},[26,252],"digital village",[26],[26],{"code":242,"score":130,"supported":46,"title":256,"abstract":258,"tags":260},[257],"农业碳",[259,257],"碳排放",[237],{"code":262,"score":263,"supported":46,"title":264,"abstract":265,"tags":267},"E5",3,[],[266],"农村电商",[],[269,270],"双向固定效应 农业碳减排 可持续发展 数字乡村","双向固定效应 农业碳减排","双向固定效应农业碳减排可持续发展数字乡村-197","2026-08-04T01:15:47.389860Z",{"id":274,"title":275,"url":276,"summary":277,"summary_zh":8,"content":278,"source_name":279,"source_url":8,"published_at":280,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":281,"score_detail":282,"sources":285,"tags":287,"primary_topic":291,"secondary_topics":292,"classification":293,"search_phrases":304,"slug":307,"view_count":13,"doi":8,"paper":8,"created_at":308},196,"数字乡村发展政策的共同富裕效应研究——来自中国县域面板数据的经验证据","https:\u002F\u002Fd.wanfangdata.com.cn\u002Fperiodical\u002Fncjj202604012","基于数字乡村发展政策这一准自然实验,统计中国2011-2022年2675个县域面板数据,系统考察数字乡村发展政策对共同富裕的影响效应及其作用机制。研究发现:数字乡村发展政策把数字技术和数字平台嵌入农业生产各环节与乡村生活各领域,能够有效提升农民收入水平、缓解农村内部收入不平等、缩小城乡收入差距。机制分析表明作用机制为产业融合-组织培育-经济机会,即政策不仅能够赋能农业接二连三,催生一批懂技术、会经营的经营主体,还可拓展非农就业机会,助力共同富裕。","检测到您正在使用 Safari 浏览器，可能影响导出功能的正常使用，建议您下载 [Google Chrome](https:\u002F\u002Fwww.google.cn\u002Fintl\u002Fzh-CN\u002Fchrome\u002F)、 [Microsoft 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[10.3969\u002Fj.issn.1003-7470.2026.04.012](https:\u002F\u002Fd.wanfangdata.com.cn\u002Fperiodical\u002Fncjj202604012)\n\n数字乡村发展政策的共同富裕效应研究——来自中国县域面板数据的经验证据\n\n 文摘阅读 12\n\n 下载 0\n\n 导出题录 0\n\n 被引 0\n\n[邓金钱](https:\u002F\u002Fd.wanfangdata.com.cn\u002Fperiodical\u002Fncjj202604012)[李潇](https:\u002F\u002Fd.wanfangdata.com.cn\u002Fperiodical\u002Fncjj202604012)\n\n[兰州大学经济学院 甘肃兰州 730000](https:\u002F\u002Fd.wanfangdata.com.cn\u002Fperiodical\u002Fncjj202604012)\n\n[在线阅读](https:\u002F\u002Fd.wanfangdata.com.cn\u002Fperiodical\u002Fncjj202604012)[下载](https:\u002F\u002Foss.wanfangdata.com.cn\u002Ffile\u002Fdownload\u002Fperio_ncjj202604012.aspx)[评审材料](https:\u002F\u002Fd.wanfangdata.com.cn\u002Fperiodical\u002Fncjj202604012)\n\n引用\n\n收藏\n\n分享\n\n打印\n\n摘要：数字乡村系统性地重塑了乡村的经济结构与社会生态,为实现共同富裕提供了前所未有的新机遇.本文采用\"数字乡村发展政策\"这一准自然实验,统计中国 2011-2022年 2675个县域的面板数据,系统考察了数字乡村发展政策对共同富裕的影响效应及其作用机制.研究发现:数字乡村发展政策把数字技术和数字平台嵌入农业生产各环节与乡村生活各领域,能够有效提升农民收入水平,缓解农村内部收入不平等、缩小城乡收入差距,有助于实现共同富裕.机制分析表明,数字乡村发展政策影响共同富裕的作用机制为\"产业融合-组织培育-经济机会\",即数字乡村发展政策不仅能够赋能农业\"接二连三\",催生一批懂技术、会经...\n\n关键词：\n\n[数字乡村](https:\u002F\u002Fd.wanfangdata.com.cn\u002Fperiodical\u002Fncjj202604012)[共同富裕](https:\u002F\u002Fd.wanfangdata.com.cn\u002Fperiodical\u002Fncjj202604012)[农民收入](https:\u002F\u002Fd.wanfangdata.com.cn\u002Fperiodical\u002Fncjj202604012)[农村内部收入不平等](https:\u002F\u002Fd.wanfangdata.com.cn\u002Fperiodical\u002Fncjj202604012)[城乡收入差距](https:\u002F\u002Fd.wanfangdata.com.cn\u002Fperiodical\u002Fncjj202604012)\n\n分类号：\n\nF323.8(中国农业经济)\n\n资助基金：\n\n[中央高校基本科研业务费文科振兴计划B类团队项目](https:\u002F\u002Fs.wanfangdata.com.cn\u002Fperiodical?q=%E5%9F%BA%E9%87%91%3A%E4%B8%AD%E5%A4%AE%E9%AB%98%E6%A0%A1%E5%9F%BA%E6%9C%AC%E7%A7%91%E7%A0%94%E4%B8%9A%E5%8A%A1%E8%B4%B9%E6%96%87%E7%A7%91%E6%8C%AF%E5%85%B4%E8%AE%A1%E5%88%92B%E7%B1%BB%E5%9B%A2%E9%98%9F%E9%A1%B9%E7%9B%AE) ( 2024lzujbkyqm018 ) \n\n文献发表日期：\n\n 2026-07-01 \n\n在线出版日期：\n\n 2026-07-17 （万方平台首次上网日期，不代表文献的发表时间）\n\n页数：\n\n14 ( 104-117 )\n\n英文信息\n\n![Image 7](https:\u002F\u002Fc.wanfangdata.com.cn\u002F\u002Fimages\u002FPeriodicalImages\u002Fncjj\u002Fncjj.jpg)\n\n[](https:\u002F\u002Fd.wanfangdata.com.cn\u002Fperiodical\u002Fncjj202604012)\n\n[农村经济](https:\u002F\u002Fc.wanfangdata.com.cn\u002Fmagazine\u002Fncjj)\n\n CSTPCD  北大核心  CSSCI  AMI \n\nISSN：1003-7470\n\n年,卷(期)：[2026(4)](https:\u002F\u002Fc.wanfangdata.com.cn\u002Fmagazine\u002Fncjj?tabId=article&publishYear=2026&issueNum=4)\n\n所属栏目：[城乡融合](https:\u002F\u002Fc.wanfangdata.com.cn\u002Fmagazine\u002Fncjj\u002F?tabId=column&yearType=all&ztext=%E5%9F%8E%E4%B9%A1%E8%9E%8D%E5%90%88 \"城乡融合\")\n\n相关文献  换一换\n\n1.[县域创业活动促进农民增收的效应研究——基于1 746个县域的面板数据分析](https:\u002F\u002Fd.wanfangdata.com.cn\u002Fperiodical\u002Fahnykx202611040 \"县域创业活动促进农民增收的效应研究——基于1 746个县域的面板数据分析\")[马林靖](https:\u002F\u002Fs.wanfangdata.com.cn\u002Fpaper?q=%E4%BD%9C%E8%80%85:%22%E9%A9%AC%E6%9E%97%E9%9D%96%22 \"马林靖\") 等; [安徽农业科学](https:\u002F\u002Fc.wanfangdata.com.cn\u002Fmagazine\u002Fahnykx \"安徽农业科学\");2026\n\n2.[数字技术驱动甘肃乡村产业与县域经济协同发展的机制与路径研究](https:\u002F\u002Fd.wanfangdata.com.cn\u002Fperiodical\u002Fshidjm202606025 \"数字技术驱动甘肃乡村产业与县域经济协同发展的机制与路径研究\")[李沂铭;](https:\u002F\u002Fs.wanfangdata.com.cn\u002Fpaper?q=%E4%BD%9C%E8%80%85:%22%E6%9D%8E%E6%B2%82%E9%93%AD%22 \"李沂铭\")[时代经贸](https:\u002F\u002Fc.wanfangdata.com.cn\u002Fmagazine\u002Fshidjm \"时代经贸\");2026\n\n3.[四川县域经济高质量发展助推共同富裕的策略研究](https:\u002F\u002Fd.wanfangdata.com.cn\u002Fperiodical\u002Fjjyjdk202609009 \"四川县域经济高质量发展助推共同富裕的策略研究\")[余声启;](https:\u002F\u002Fs.wanfangdata.com.cn\u002Fpaper?q=%E4%BD%9C%E8%80%85:%22%E4%BD%99%E5%A3%B0%E5%90%AF%22 \"余声启\")[经济研究导刊](https:\u002F\u002Fc.wanfangdata.com.cn\u002Fmagazine\u002Fjjyjdk 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2026-07-17上网","2026-07-17T00:00:00Z",81,{"impact":283,"substance":80,"depth":17,"authority":81,"freshness":20,"relevant":21,"comment":284},25,"基于大规模县域面板数据的实证研究，揭示数字乡村政策对共同富裕的促进作用，具有较高学术价值和政策参考意义，但发表时间较早。",[286],{"name":279,"url":276},[26,288,289,28,290],"共同富裕","县域面板","农业政策",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":14,"version":40,"method":41,"evidence":294},{"candidates":295,"agricultural_evidence":46},[296,300],{"code":32,"score":45,"supported":46,"title":297,"abstract":298,"tags":299},[26],[26],[26],{"code":100,"score":21,"supported":14,"title":301,"abstract":302,"tags":303},[],[],[288],[305,306],"中介效应 共同富裕 农业政策 县域面板","中介效应 共同富裕","中介效应共同富裕农业政策县域面板-196","2026-08-04T01:15:47.369167Z"]