我国农业面源污染治理政策协同网络演化

张紫伊; 虎陈霞; 连纲; 杨琰瑛

文章摘要

我国农业面源污染治理政策协同网络演化

Evolution of the collaborative network of agricultural non-point source pollution control policies in China

Received:January 27, 2025

DOI：10.13254/j.jare.2025.0063

中文关键词: 农业面源污染治理，政策工具，社会网络，部门合作，网络演化，层级协同

英文关键词: agricultural non-point source pollution control, policy tool, social network, sector cooperation, network evolution, hierarchical collaboration

基金项目:国家社会科学基金项目（20BJY085）

Author Name	Affiliation	E-mail
ZHANG Ziyi	School of Economics and Management, China Jiliang University, Hangzhou 310018, China
HU Chenxia	School of Economics and Management, China Jiliang University, Hangzhou 310018, China
LIAN Gang	Ecological and Environmental Monitoring Center of Zhejiang Province, Hangzhou 310010, China
YANG Yanying	Agro-Environmental Protection Institute, Ministry of Agriculture and Rural Affairs, Tianjin 300191, China	yangyanying@caas.cn

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中文摘要:

为分析农业面源污染治理过程中各职能部门的协作机制以及现行政策工具的应用特征，探讨如何构建更完善的治理政策体系，从而为提升农业面源污染防治成效提供决策参考。本研究选取了1984—2022年的农业面源污染治理相关政策文本，使用文本分析法和社会网络分析法对政策发布部门与政策工具的关系展开深入研究。结果表明：政策信息挖掘方面确定了26个政策发布部门，其涵盖中央、省（自治区）、市（县）级，同时划分出命令-控制型、经济激励型、自愿型三类共29项政策工具。核心边缘分析表明不同部门通过使用相同的政策工具提高政策实施强度，核心网络中政府部门使用命令-控制型和自愿型工具多于经济激励型工具，而经济激励型工具应用形式单一、缺乏激励。合作网络分析则表明部门合作网络包含26个节点、146条连线，存在3个派系。中央部门中，农业农村部和生态环境部是核心部门；地方部门中，省农业农村厅和省生态环境厅作用关键，中央和地方部门间无跨级合作。其中中央部门派系包含12个部门，规模最大，以鼓励引导为主，自愿型工具使用频次高；省级部门派系使用政策工具多样，对“标准量化限制”重视度高。研究表明，命令-控制型和自愿型工具在网络中重要程度较高，而经济激励型工具应用相对不足。此外，相较地方部门，中央部门缺乏对“标准量化限制”工具的重视。

英文摘要:

This study aims to explore how to build a more complete governance policy system by analyzing the collaboration mechanism among various functional departments and the application characteristics of current policy tools in the process of agricultural non-point source pollution control, so as to provide decision-making references for improving the effectiveness of agricultural non-point source pollution prevention and control. This paper selected policy texts on agricultural non-point source pollution control from 1984 to 2022, and used text analysis and social network analysis to conduct an in-depth study on the relationship between policy-issuing departments and policy tools. The results showed that 26 policy issuing departments were identified through policy information mining. These departments covered the central, provincial（autonomous region）and municipal（county）levels. A total of 29 policy instruments were divided into three categories：command-control type, economic incentive type and voluntary type. The core edge analysis showed that different sectors could improve the intensity of policy implementation by using the same policy tools. The government departments in the core network used more command-control and voluntary tools than economic incentive tools, and the economic incentive tools were applied in a single form and lack incentives. The analysis of the cooperation network showed that the departmental cooperation network contained 26 nodes, 146 connections, and 3 factions. Among the central departments, the Ministry of Agriculture and Rural Affairs and the Ministry of Ecology and Environment were the core departments. Among the local departments, the Provincial Department of Agriculture and Rural Affairs and the Provincial Department of Ecology and Environment played a key role, and there was no cross-level cooperation between the central and local departments. Among them, the central department faction included 12 departments, which was the largest scale. Its main function was to encourage and guide, and the frequency of use of voluntary tools was high. Provincial-level departments used a variety of policy tools and attached great importance to“quantitative constraints on standards”. These results show that command-control and voluntary tools are more important in the network, while economic incentive tools are relatively underused. In addition, the central sector has paid less attention to the“quantitative constraints of standards”tool than the local sector.

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