The issues of energy crisis, environmental degradation, and climate change present a severe challenge to the sustainable development in China. The development of green building (GB) is considered one of the most popular strategies toward a sustainable construction industry. Apart from advanced green technologies, consumers’ purchasing intention toward green housing (GH) plays a crucial role in the large-scale promotion of GB. However, which determinants significantly affect consumers’ purchasing intention remain unclear, especially for the young generation in developing countries. This study attempts to investigate young consumers’ purchasing intention of GH in China. On the basis of extended theory of planned behavior (TPB), seven constructs are identified, and nine hypotheses are proposed. A total of 241 responses were collected from the questionnaire survey, and structural equation modeling was employed to test the proposed hypotheses. Governmental incentives are affirmed to be the most important determinant, followed by consumers’ attitude toward behavior and subjective norm. Perceived behavioral control is an insignificant determinant for young consumers to purchase GH. In addition, subjective knowledge has an indirect effect through attitude toward behavior. Environmental concern also confirms an indirect effect through attitude toward behavior and subjective norm toward purchasing intention, respectively. Thus, the government is implied to play a crucial role in GH promotion at this stage.

The environmental impacts caused by construction waste have attracted increasing attention in recent years. The effective management of construction waste is essential in order to reduce negative environmental influences. Construction waste management (CWM) can be viewed as a complex adaptive system, as it involves not only various factors (e.g., social, economic, and environmental), but also different stakeholders (such as developers, contractors, designers, and governmental departments) simultaneously. System dynamics (SD) and agent-based modeling (ABM) are the two most popular approaches to deal with the complexity in CWM systems. However, the two approaches have their own advantages and drawbacks. The aim of this research is to conduct a comprehensive review and develop a novel model for combining the advantages of both SD and ABM. The research findings revealed that two options can be considered when combining SD with ABM; the two options are discussed.