社区低碳发展的公众参与决策和协同治理研究

In the context of global climate change and city low-carbon development, community low-carbon development has attracted the attention of the world. Community low-carbon development is a social activity involving many stakeholders, so research on public participation and collaborative governance cannot be ignored. However, the theoretical literature on community low-carbon development is insufficient as to how to introduce public participation mechanism and carry out collaborative governance in the process of community low-carbon development. This project integrates public participation theory, multi-center governance theory, social cognition theory, and draws on interdisciplinary methods of Social Network Analysis (SNA), Network Analysis Process (NAP) and GA-BP neural network in order to explore public participation decision-making model and multi-agent collaborative governance path under China's national conditions. First, the project makes a comprehensive analysis of the subject and object elements of community low-carbon development. SNA is applied to construct social network structure and identify the key low-carbon agents. ANP is applied to construct network hierarchical structure model. Second, based on public participation theory, the project constructs public participation low-carbon decision-making model to explore the influence mechanism and rules of carbon emission and public satisfaction. Third, the low-carbon satisfaction and expectation of the low-carbon stakeholders are measured and research on collaborative governance is carried out based on multi-agent low-carbon cognitive perspective. Finally, the theoretical model is integrated, verified and applied in the case study.

在全球气候变化、城市低碳发展的背景下，社区低碳发展已成为国际热点，社区低碳发展是一项涉及到众多利益相关者的社会活动，不可忽视对公众参与和协同治理的研究。如何在社区低碳发展过程中引入公众参与机制、开展协同治理研究，是社区低碳发展理论文献的薄弱之处。本课题综合公众参与理论、多主体治理理论、社会认知理论，借鉴社会网络分析法、网络分析法、遗传神经网络等多学科交叉技术方法，旨在探索适应我国国情的社区低碳发展公众参与决策模型与多主体协同治理方法。首先，综合分析社区低碳发展的主客体，运用社会网络分析法绘制社会网络结构图，识别关键低碳主体，运用网络分析法构建低碳指标网络层次结构模型；其次，借鉴公众参与理论，构建公众参与低碳决策模型，探索社区碳排放和公众满意度的影响机理与规律；再次，基于多主体低碳认知视角，分析主体的低碳期望与满意度，开展社区低碳协同治理研究；最后，对理论模型进行集成、验证与应用。

面临气候变化的严峻挑战，城市低碳发展已成为既定趋势，社区作为承载人们生活和居住的主要场所，是城市低碳发展的重要空间载体和减少碳排放的基本单元。社区低碳发展是一项涉及众多利益相关者的社会活动，不可忽视对低碳主体和协同治理的研究。本项目具体研究内容：1）综合分析社区低碳发展的主客体，运用社会网络分析法绘制社会网络结构图，识别关键低碳主体，运用网络分析法构建低碳指标网络层次结构模型；2）借鉴公众参与理论，构建公众参与低碳决策模型，探索社区碳排放和公众满意度的影响机理与规律；3）基于多主体低碳认知视角，分析主体的低碳期望与满意度，开展社区低碳协同治理研究。项目选取社区低碳发展的核心问题“公众参与决策和协同治理”作为研究对象，从社区低碳发展的要素识别与分析、社区低碳发展的方案决策、社区的低碳治理与优化三大核心问题出发，识别社区低碳发展的关键因素，构建社区低碳发展的公众参与决策模型，探索社区碳排放和公众满意度的影响机理与规律，并基于多主体低碳认知的视角开展社区低碳协同治理研究。项目综合考虑我国城市社区发展对公众参与决策和协同治理的迫切需求，为我国城市社区可持续发展提供了理论依据。研究成果表明：1）社区低碳运营的关键主体为政府、居民以及开发商，所对应的关键影响因素分别为“技术应用的顶层规划设计和部门未能统筹”、“低碳社区服务较少且功能尚不够完善”、“未能及时对运营中存在的问题进行逐项整改并督查问责”；2）通过对GA-BP神经网络模型检验，结果与现场测量打分结果一致，证实了应用MATLAB工具箱建立的公众参与低碳决策模型是有效的；3）借鉴Meme理论开展的图谱分析表明，该方法能够直观、定量的解析社区的低碳水平。.