A Decision Support System for the Selection of Low-Cost Green Building Materials

Background: For the past ten years, researchers have sought effective ways of exploring the possibilities of constructing homes more efficiently by using low-cost green building materials and components, as they produce less toxic waste and also perform very well in terms of cost and energy reduction in use, over their life cycle. Yet, despite these efforts and the benefits that associate their use, the patronage in housing construction appears to be relatively low when compared to conventional building products. The analysis of the literature study showed little evidence to justify the assumption that there are tools of demonstrable reliability for designers to assess the sustainability of such materials or their applicability and utility in the design of low-cost green housing projects. Nevertheless, questions remain regarding how designers should evaluate their relative impacts in the presence of multidimensional factors; hence underscores the need to investigate how informed decision-making in the material selection process could reduce decision-making failures, and encourage greater industry acceptance during the planning and design stage(s) of residential housing projects.
Aims: This article set(s) out to determine how the understanding of the principles of best practices associated with the impacts of low-cost green building materials could be improved to fulfill the objective of their greater use in mainstream housing. To achieve this aim, a DSS is presented in this paper as a means to aid and inform design and building professionals in their choice of materials for low-cost green residential housing projects.
Study Design: The study employed exploratory study design approach using literature reviews, and networking with domain experts and practitioners. This was followed by a series of questionnaire surveys and knowledge-mining interviews.
Place and Duration of Study: This study was carried out in some selected housing construction firms in the UK over a two-month period of March and April 2012.
Methodology: The study conducted in-depth interviews that consisted of 10 participants, involving a sample of practicing architects, engineers, material specifiers, and a host of building professionals that influence material choice decisions in the UK housing construction industry. In order to elicit the ‘‘most important’’ factors, a semi-structured questionnaire survey was conducted among 480 executives of some selected expert builder and developer companies, with an overall response rate of 52.1%.
Results: The analysis of the questionnaire survey provided a list of ‘‘most important’’ decision factors having significant impacts on the process of material selection for low-cost green residential housing development. The value for Cronbach’s alpha was estimated at 0.781, showing strong evidence that all reliability coefficients of 55 out of 60 factors were acceptable, and internally consistent.
Conclusion: This study posits that an improved approach for integrating data associated with the impacts of low-cost green materials from heterogeneous databases and other information sources may likely reduce decision-making failures in the selection process; hence engender their wider-scale use in mainstream housing.