School of Management Engineering, Shandong Jianzhu University, PR China.
China Railway 14TH Bureau Group Co., Ltd, PR China.
Waste Manag. 2021 May 1;126:684-693. doi: 10.1016/j.wasman.2021.03.056. Epub 2021 Apr 17.
Urban development generates large amounts of construction and demolition waste, and the enactment of various policies is an important way to increase resource efficiency. It is urgent to analyse the choices and effects of construction and demolition waste disposal policies around the world. This study analyses and compares the implementation effects of various construction and demolition waste disposal policies and provides suggestions on the selection and formulation of different disposal method policies. A BP neural network and an agent-based model are used to construct a simulation model for the implementation effects of construction and demolition waste disposal policies. The average acceptance willingness is analysed for the three disposal methods of reduction, reuse and recycling under the different policies based on questionnaire survey data. Simulation results show that the implementation effect of the incentive policy as a single policy is superior, and the comprehensive implementation effect of the guidance-incentive-mandatory policy as a combined policy is superior. The implementation effect of combined policies is better than that of single policies. The policies suitable for different disposal methods are inconsistent. Information interaction can effectively improve the implementation effects of different construction and demolition waste disposal policies, especially for single policies. This study innovatively compares the various construction and demolition waste disposal policies and explain the interaction during their implementation. The findings can help the government formulate policies at different stages of construction and demolition waste management and provide a new approach to policy simulation research.
城市发展产生了大量的建筑和拆除垃圾，制定各种政策是提高资源效率的重要途径。分析全球建筑和拆除垃圾处理政策的选择和效果迫在眉睫。本研究分析和比较了各种建筑和拆除垃圾处理政策的实施效果，并就不同处理方法政策的选择和制定提供了建议。本文使用 BP 神经网络和基于主体的模型构建了建筑和拆除垃圾处理政策实施效果的仿真模型。基于问卷调查数据，分析了不同政策下减少、再利用和回收三种处理方法的平均接受意愿。模拟结果表明，激励政策作为单一政策的实施效果较好，指导-激励-强制政策作为组合政策的综合实施效果较好。组合政策的实施效果优于单一政策。适合不同处理方法的政策并不一致。信息交互可以有效提高不同建筑和拆除垃圾处理政策的实施效果，特别是对单一政策。本研究创新性地比较了各种建筑和拆除垃圾处理政策，并解释了实施过程中的相互作用。研究结果可以帮助政府在建筑和拆除垃圾管理的不同阶段制定政策，并为政策模拟研究提供新途径。
