涉农数智技术采纳现状与现实挑战:基于两套具有代表性农户调查的研究
基于两套代表性农户调查,揭示数智技术采纳现状与挑战,数据详实,结论可靠,但发表于5天前,时效性较低。
易红梅等基于两套具有代表性的全国农户调查数据,系统分析涉农数智技术的采纳现状与现实挑战,为理解数字技术与农业农村深度融合提供实证依据。
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Smart Agriculture ›› 2026, Vol. 8 ›› Issue (3): 51-66.doi: 10.12133/j.smartag.SA202601001
涉农数智技术采纳现状与现实挑战:基于两套具有代表性农户调查的研究
易红梅 1, 何煦 1, 智华勇 1, 黄季焜 1(
), 陈曦 2
-
- 北京大学现代农学院/中国农业政策研究中心,北京 100871,中国
-
台州科技职业学院,浙江 台州 318020,中国
-
收稿日期:2025-12-31出版日期:2026-05-30 -
作者简介:易红梅,博士,教授,研究方向为农业经济学、数字技术、农村人力资本。E-mail:[email protected] -
通信作者:黄季焜,博士,教授,研究方向为农业经济学、发展经济学。E-mail:[email protected]
Adoption and Challenges of Digital and Intelligent Technologies in Agriculture: Evidence from Two Representative Household Surveys
YI Hongmei 1, HE Xu 1, ZHI Huayong 1, HUANG Jikun 1(
), CHEN Xi 2
-
- School of Advanced Agricultural Sciences, China Center for Agricultural Policy, Peking Univeristy, Beijing 100871, China
-
Taizhou Vocational College of Sicence Technology, Taizhou 318020, China
Received:2025-12-31Online:2026-05-30Foundation items:Project of Peking University Institute of Advanced Agricultural Sciences (Weifang, Shandong)About author:YI Hongmei, E-mail: [email protected]Corresponding author:HUANG Jikun, E-mail: [email protected]
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摘要/Abstract
摘要:
【目的/意义】 评估涉农数智技术在中国农业农村微观生产主体中的采纳现状,识别涉农数智技术应用在农业农村未来发展中面临的主要挑战。 【方法】 基于两套具有代表性的农户调查数据,首先使用描述性统计方法刻画了各类涉农数智技术在中国农业农村的采纳情况;进一步结合文献综述,梳理了技术采纳的潜在影响及其作用机制,并进一步联系理论与实践,分析了这些数智技术在普及过程中面临的挑战及其成因。 【结果和讨论】 研究表明,非嵌入式数智技术在农业中的应用总体呈现“重生活、轻生产”的特征。农业主要决策者智能手机使用率已达76%,但其主要用于社交与娱乐(如微信、抖音、快手),在农业生产、销售及政策信息获取中的应用明显不足;约三分之二的受访者未关注农业类公众号,78%的受访者表示较少通过智能手机获取农业政策信息。在电商与数字金融领域,农户“消费端参与较多、生产端应用不足”的特征同样突出:2023年约52%的农户有网购行为,但通过网络销售农产品的比例仅为0.32%,开展网络贷款的农户占比亦不足2%。与之形成对比的是,嵌入式数智技术在农业生产中的扩散相对较快。以无人机和北斗导航为代表的技术已在关键生产环节中得到应用:2023年约8%的农户在植保环节使用无人机,粮食主产区无人机植保作业覆盖耕地面积占比达39.3%,且主要依托社会化服务体系实现;配备北斗导航的农机占比按农户数量与耕地面积加权分别达到8%和12.5%。进一步分析表明,非嵌入式数智技术应用不足,主要受制于农户认知与数字素养约束、基础设施条件及政策支持不足;而嵌入式技术的加速扩散,则与其成本下降、社会化服务组织发展以及行业标准逐步完善密切相关。 【结论】 总体来看,中国农业农村数智化转型正在起步阶段。推动农业农村数智化转型,需积极提升农户数字素养、培育高人力资本水平的新型农业经营主体,继续推动农业适度规模化发展,培育社会化服务主体,加强服务供给能力,从而实现更广泛、更有效的数智技术普及与农业现代化提升。
关键词:数智技术,数智化转型,农业社会化服务,农村电商,数字金融,北斗导航,无人机
Abstract:
[Objective] In recent years, China has issued a series of policy documents, which emphasize digital transformation as a key driver for deepening the integration of digital and intelligent technologies (DITs) with the agricultural and rural economy, promoting high-quality agricultural development, and advancing the goal of building a strong agricultural sector. However, the ultimate impact of these technologies depends not only on their potential effectiveness but also on the extent to which they are adopted by farmers. Against this backdrop, the aim of this research is to assess the current adoption of agricultural DITs among agricultural producers in China and to identify the main challenges facing their application in the future development of agriculture and rural areas. [Methods] Using two representative household survey datasets—the China Agriculture and Rural Development Survey and a 2023 survey of farmers in major grain-producing regions—this study employs descriptive statistics to document the adoption of various DITs. Then they were combined with a review of the literature to examine the potential impacts and underlying mechanisms of technology adoption, and to analyze the challenges and their causes in the diffusion of these technologies by linking theory with practice. [Results and Discussions] The results showed that, for non-embedded digital technologies, smartphone use among primary agricultural decision-makers was widespread, with an average penetration rate of 76%. The most frequently used applications were WeChat, TikTok, and Kuaishou. Despite the high usage of WeChat, its application in agricultural production and marketing remains limited: about two-thirds of respondents report rarely or never following agriculture-related official accounts. Similarly, access to agricultural policy information via smartphones was limited, with approximately 78% of respondents indicating that they seldom or only occasionally followed such information. In terms of e-commerce, about 52% of rural households engaged in online shopping in 2023, but very few used online channels for sales: only 0.32% sold agricultural products and 0.15% sold other goods online. In digital finance, only 27% of surveyed households were aware that loans could be applied for online, and the share that had actually applied for online loans in the past two years was even lower, at around 2%. By contrast, embedded digital technologies, such as drones and Beidou-based navigation systems, were more widely used in agricultural production. Data from nine provinces show that about 8% of farmers used drones for crop protection in 2023, reflecting a clear upward trend. In major grain-producing regions, drones covered 39.3% of cultivated land for plant protection, largely through service outsourcing. In addition, the share of farmers using machinery equipped with Beidou navigation systems, weighted by the number of households and cultivated land area, reaches 8% and 12.5%, respectively. Building on these findings, the study analyzes the relatively low adoption of non-embedded technologies in agricultural settings from the perspectives of farmer awareness, digital literacy, infrastructure, and policy support. It also explores the diffusion of embedded technologies from the angles of cost, agricultural organization (particularly the development of service providers), and industry standards. [Conclusions] Overall, China's agricultural and rural digital transformation is still at an early stage. The adoption of non-embedded applications in agricultural production and marketing remains very limited, while the use of embedded technologies exhibits substantial heterogeneity across farm sizes and application contexts. In addition, although smallholders rarely invest in digital machinery themselves, they can still benefit from digital transformation through outsourced services and socialized service provision. Further analysis suggests that advancing agricultural digitalization requires improving farmers' digital literacy, fostering new agricultural business entities with higher human capital, promoting the development of appropriately scaled farming, and strengthening the capacity of service providers. These measures are essential to enable broader and more effective diffusion of DITs and to support agricultural modernization.
Key words:digital and intelligent technologies (DITs),digital-intelligent transformation,agricultural socialized services,rural e-commerce,digital finance,Beidou navigation,drones
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引用本文
易红梅, 何煦, 智华勇, 黄季焜, 陈曦. 涉农数智技术采纳现状与现实挑战:基于两套具有代表性农户调查的研究[J]. 智慧农业(中英文), 2026, 8(3): 51-66.
YI Hongmei, HE Xu, ZHI Huayong, HUANG Jikun, CHEN Xi. Adoption and Challenges of Digital and Intelligent Technologies in Agriculture: Evidence from Two Representative Household Surveys[J]. Smart Agriculture, 2026, 8(3): 51-66.
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[图/表 17](javascript:;)
表 1
九省调查样本量及户权重
| 区域 | 省份 | 县(市)/个 | 乡(镇)/个 | 村/个 | 农户/个 | 户权重 |
|---|---|---|---|---|---|---|
| 合计 | 57 | 136 | 288 | 3 080 | — | |
| 东北 | 辽宁 | 5 | 10 | 10 | 200 | 1/1 800 |
| 华北 | 河北 | 5 | 10 | 10 | 200 | 1/1 800 |
| 山东 | 10 | 30 | 60 | 600 | 1/5 400 | |
| 华东 | 浙江 | 5 | 10 | 20 | 200 | 1/1 800 |
| 华中 | 湖北 | 5 | 10 | 20 | 200 | 1/1 800 |
| 江西 | 12 | 36 | 108 | 1 080 | 1/9 720 | |
| 华南 | 广东 | 5 | 10 | 20 | 200 | 1/1 800 |
| 西南 | 四川 | 5 | 10 | 20 | 200 | 1/1 800 |
| 西北 | 陕西 | 5 | 10 | 20 | 200 | 1/1 800 |
表 1
表 2
主要农业决策者的性别、年龄和受教育水平
| 特征 | 东北 | 华北 | 华东 | 华中 | 华南 | 西南 | 西北 | 合计 |
|---|---|---|---|---|---|---|---|---|
| 男性占比/% | 85 | 84 | 86 | 82 | 78 | 61 | 86 | 81 |
| 年龄/岁 | 63.43 | 61.28 | 67.22 | 63.15 | 62.58 | 59.36 | 60.42 | 62.25 |
| 受教育水平/年 | 8.60 | 7.84 | 6.51 | 7.47 | 7.47 | 7.10 | 8.37 | 7.65 |
| 样本数量 | 120 | 662 | 92 | 921 | 144 | 165 | 187 | 2 291 |
表 2
表 3
农业主要决策者的性别差异
| 特征 | 女 | 男 | P 值 |
|---|---|---|---|
| 年龄/岁 | 59.73 | 62.82 | 0.001 |
| (10.20) | (10.01) | ||
| 受教育水平/年 | 6.82 | 7.81 | 0.001 |
| (5.97) | (4.24) | ||
| 样本数量 | 425 | 1 866 |
表 3
表 4
农业主要决策者使用智能手机的比例 ( %)
| 区域 | 合计 | 男 | 女 |
|---|---|---|---|
| 东北 | 80.8 | 78.4 | 94.4 |
| 华北 | 77.0 | 77.8 | 73.7 |
| 华东 | 55.4 | 58.2 | 38.5 |
| 华中 | 72.6 | 74.2 | 69.8 |
| 华南 | 75.7 | 72.3 | 87.5 |
| 西南 | 82.4 | 80.2 | 85.9 |
| 西北 | 82.9 | 84.4 | 74.1 |
| 全样本合计 | 76.3 | 76.3 | 76.6 |
表 4
图1
农业主要决策者智能手机上常用的App分布

图1
图2
各区域农业主要决策者中常用App为微信的比例

图2
表5
各区域农业主要决策者使用微信的频率 ( %)
| 区域 | 基本不用 | 偶尔使用 | 经常使用或每天都使用 | 合计 |
|---|---|---|---|---|
| 东北 | 1.2 | 19.3 | 79.5 | 100 |
| 华北 | 3.2 | 12.4 | 84.4 | 100 |
| 华东 | 4.9 | 19.5 | 75.6 | 100 |
| 华中 | 1.7 | 15.0 | 83.3 | 100 |
| 华南 | 5.0 | 11.0 | 84.0 | 100 |
| 西南 | 3.2 | 10.2 | 86.6 | 100 |
| 西北 | 1.3 | 3.4 | 95.3 | 100 |
| 全样本合计 | 2.6 | 11.9 | 85.5 | 100 |
表5
图3
各区域使用微信的农业主要决策者中使用朋友圈和关注朋友圈中销售信息的比例

图3
表6
各区域使用微信的农业主要决策者关注农业公众号的比例 ( %)
| 区域 | 基本不用 | 偶尔使用 | 经常使用 或每天都在使用 | 合计 |
|---|---|---|---|---|
| 东北 | 50.6 | 33.7 | 15.7 | 100 |
| 华北 | 64.6 | 23.2 | 12.2 | 100 |
| 华东 | 68.3 | 17.1 | 14.6 | 100 |
| 华中 | 67.7 | 21.5 | 10.8 | 100 |
| 华南 | 75.0 | 17.0 | 8.0 | 100 |
| 西南 | 77.0 | 15.8 | 7.2 | 100 |
| 西北 | 58.4 | 23.5 | 18.1 | 100 |
| 全样本合计 | 66.1 | 21.7 | 12.2 | 100 |
表6
表7
各区域农业主要决策者用手机关注农业政策的比例 ( %)
| 区域 | 基本不用 | 偶尔使用 | 经常使用 或每天都在使用 | 合计 |
|---|---|---|---|---|
| 东北 | 38.5 | 35.4 | 26.1 | 100 |
| 华北 | 53.7 | 26.7 | 19.6 | 100 |
| 华东 | 58.9 | 19.6 | 21.5 | 100 |
| 华中 | 56.0 | 28.5 | 15.5 | 100 |
| 华南 | 59.6 | 18.4 | 22.0 | 100 |
| 西南 | 58.8 | 28.7 | 12.5 | 100 |
| 西北 | 30.3 | 31.0 | 38.7 | 100 |
| 全样本合计 | 50.7 | 27.4 | 21.9 | 100 |
表7
图4
各区域农业主要决策者对“用手机查看农业信息对农业生产是否有帮助”的看法

图4
表 8
2023年样本农户电商参与与网络贷款情况
| 区域 | 2023年进行过网购的农户占比/% | 2023年有网络销售活动的农户/% | 知道可以通过网络进行贷款的农户占比/% | 2022—2023年通过网络贷过款的农户占比/% | 其中1,2022—2023年网贷农户的网贷数量/笔 | 其中2,2022—2023年通过网络分期付款的网贷农户占比/% |
|---|---|---|---|---|---|---|
| 农产品 | 其他商品 | |||||
| 东北 | 40.0 | 0.5 | 0.0 | 29.5 | 2.0 | 1.0 |
| 华北 | 43.5 | 0.2 | 0.6 | 27.7 | 2.0 | 1.1 |
| 华东 | 50.5 | 0.0 | 0.0 | 13.0 | 2.0 | 2.0 |
| 华中 | 57.9 | 0.3 | 0.1 | 21.1 | 2.0 | 1.4 |
| 华南 | 51.5 | 1.5 | 0.0 | 23.8 | 1.9 | 1.7 |
| 西南 | 57.0 | 0.0 | 0.0 | 29.5 | 2.0 | 1.0 |
| 西北 | 66.3 | 0.0 | 0 | 49.5 | 1.9 | 1.8 |
| 全样本合计 | 52.0 | 0.3 | 0.2 | 27.0 | 2.0 | 1.5 |
表 8
图5
不同网贷渠道占所有网贷批次的比例

图5
图6
各区域使用无人机进行植保作业的农户比例

图6
图7
各区域2023年使用无人机进行除草、施肥和播种作业的农户比例

图7
表9
粮食主产区样本中无人机的应用现状
| 无人机使用途径 | 大规模户/% | 小规模户/% | 全样本 (未加权)/% | 全样本 (按照户数占比加权)/% | 全样本 (按面积占比加权)/% |
|---|---|---|---|---|---|
| 自家是否有植保无人机 | 5 | 0 | 2.5 | 0.3 | 3.9 |
| (22) | (0) | ||||
| 使用植保无人机社会化服务 | 42 | 12 | 26 | 13.6 | 35.4 |
| (49) | (32) | ||||
| 样本数量 | 320 | 328 | 648 | 648 | 648 |
表9
表10
粮食主产区样本中北斗导航技术的应用现状
| 北斗导航技术的使用途径 | 大规模户/% | 小规模户/% | 全样本(未加权)/% | 全样本(按照户数占比加权)/% | 全样本(按面积占比加权)/% |
|---|---|---|---|---|---|
| 自家是否有农机 | 82 | 41 | 61.5 | 43.2 | 73.0 |
| (39) | (0.49) | ||||
| 自家农机是否装北斗导航(仅限自家有农机的户) | 16 | 0 | 0.08 | 0.8 | 12.5 |
| (37) | (0) | ||||
| 耕种收环节是否使用农机社会化服务 | 76 | 79 | 77.5 | 78.8 | 76.7 |
| (43) | (41) | ||||
| 耕地环节使用的社会化服务提供的农机是否装北斗导航 | 33 | 18 | 25.5 | 18.8 | 29.7 |
| (47) | (39) | ||||
| 播种环节使用的社会化服务提供的农机是否装北斗导航 | 30 | 17 | 22.4 | 17.7 | 19.9 |
| (46) | (38) | ||||
| 收获环节使用的社会化服务提供的农机是否装北斗导航 | 27 | 26 | 26.5 | 26.1 | 26.8 |
| (44) | (44) | ||||
| 样本数量 | 320 | 328 | 648 | 648 | 648 |
表10



## 可视化 0