摘要
文章采用内容分析法对2021—2023年我国省级层面相关部门出台的140份休闲农业政策文件进行量化研究,构建“政策工具—参与主体”二维分析框架,剖析“十四五”以来我国省级层面休闲农业政策制定的特点,研究发现:当前我国休闲农业政策在工具选择上以混合型政策工具和强制性政策工具为主,自愿性政策工具相对较少;重点集中在对财政奖补、金融支持和试点示范等子工具的应用上,忽视对征税收费政策的使用;对农村集体经济组织、高校科研院所、金融机构和游客的关注不足,激励措施欠缺;政策工具的使用与参与者间的组合配置存在路径依赖,参与者的核心诉求未能在政策中得到充分体现。未来,应在此基础上,均衡政策工具使用结构,适配子工具使用频率,兼顾各参与方利益。
This article employed content analysis to quantitatively study 140 leisure agriculture policy documents issued by relevant departments at the provincial level in China from 2021 to 2023,constructing a two-dimensional analytical framework of"policy tools-participating entities".It dissected the characteristics of leisure agriculture policy formulation at the provincial level in China since the"14th Five-Year Plan".The research discovered that:At present,China's leisure agriculture policies predominantly utilized mixed policy tools and mandatory policy tools,with a relatively smaller proportion of voluntary policy tools;the focus was mainly on the application of sub-tools such as financial rewards and subsidies,financial support,and pilot demonstrations,while the utilization of taxation and fee-charging policies was overlooked;there is inadequate attention to rural collective economic organizations,university research institutes,financial institutions,and tourists,coupled with a lack of incentive measures;the combination and configuration of policy tools and participants exhibited path dependence,and the core demands of participants were not fully reflected in the policies.Going forward,based on these findings,it will be essential to balance the utilization structure of policy tools,adjust the frequency of sub-tool usage,and take into consideration the interests of all stakeholders.
作者
郭宇轩
朱启佳
陆川
Guo Yuxuan;Zhu Qijia;Lu Chuan(Jiangsu Academy of Agricultural Sciences,Nanjing,210014 China)
出处
《农业科技管理》
2024年第6期43-47,125,共6页
Management of Agricultural Science and Technology
基金
江苏省社科应用研究精品工程社会教育(社科普及)专项课题(23SJC-43)。
关键词
休闲农业
政策工具
参与主体
政策文本分析
Leisure agriculture
Policy tools
Participating entities
Policy text analysis
