A dynamic model for assessing the effects of management strategies on the reduction of construction and demolition waste

Abstract

During the past few decades, construction and demolition (C&D) waste has received increasing attention from construction practitioners and researchers worldwide. A plethora of research regarding C&D waste management has been published in various academic journals. However, it has been determined that existing studies with respect to C&D waste reduction are mainly carried out from a static perspective, without considering the dynamic and interdependent nature of the whole waste reduction system. This might lead to misunderstanding about the actual effect of implementing any waste reduction strategies. Therefore, this research proposes a model that can serve as a decision support tool for projecting C&D waste reduction in line with the waste management situation of a given construction project, and more importantly, as a platform for simulating effects of various management strategies on C&D waste reduction. The research is conducted using system dynamics methodology, which is a systematic approach that deals with the complexity - interrelationships and dynamics - of any social, economic and managerial system. The dynamic model integrates major variables that affect C&D waste reduction. In this paper, seven causal loop diagrams that can deepen understanding about the feedback relationships underlying C&D waste reduction system are firstly presented. Then a stock-flow diagram is formulated by using software for system dynamics modeling. Finally, a case study is used to illustrate the validation and application of the proposed model. Results of the case study not only built confidence in the model so that it can be used for quantitative analysis, but also assessed and compared the effect of three designed policy scenarios on C&D waste reduction. One major contribution of this study is the development of a dynamic model for evaluating C&D waste reduction strategies under various scenarios, so that best management strategies could be identified before being implemented in practice.