|Title||Rethinking low-cost green building material selection process in the design of low-impact green housing developments|
Since 1950, the world population has increased by more than double. The sprawling demographic shift due to continuous migration from rural to urban areas in developing countries imposes socio-economic and environmental pressures to the urban areas. Apparently, the high demand for housing and the unsustainable construction practices underlying its production in recent times constitute issues that merit the attention of low-impact green housing developments. The feasibility of such developments also lies in the effective use of low-cost green building materials and components (LCGBMCs),primarily because of their potential to conserve energy use, reduce life-cycle
Until recently however, only very few of these products have been widely established in mainstream, on account that most designers are constrained by their vaguely informed knowledge as to their sustainability impacts during the early stages of the design decision-making process, when most of the important decisions relating to sustainability are made. With the scale of complexity on how to incorporate sustainability principles in the early stages of the material selection decision-making process, and quest to stimulate the motivation for their use in a wider industry context, a clear gap is identified.
Drawing on the concept of sustainability, this research aims to narrow the underlying gap by exploring and evaluating the significance of an integrated
The information gathered from the analysis with inputs elicited from experienced professionals are used to develop a Multi-Criteria Material Selection Decision Support System (MSDSS), and later refined with
This study concludes that by addressing integration of sustainability principles into the material selection decision making processes at the early stages of the design, better support will be provided to key decision makers with the expectation of improved understanding and better informed choices, hence stimulate the motivation for more use of LCGBMCs in a wider industry context. The limitations of the study are highlighted and future research directions to better exploit the model capabilities are proposed.