Sustainable building material selection: A QFD- and ELECTRE III-embedded hybrid MCGDM approach with consensus building. (October 2019) - Chen, Zhen-Song; Martínez, Luis; Chang, Jian-Peng; Wang, Xian-Jia; Xionge, Sheng-Hua; Chin, Kwai-Sang
Abstract: Industrialization and urbanization have led to the rapid development of the building industry. To alleviate the adverse impact on the environment, natural resources, health and comfort of inhabitants, sustainable principles have been incorporated into the design, construction, decoration, operation, and maintenance of buildings. Among all these endeavors, sustainable building material selection is diffusely regarded as the simplest and most essential way of achieving sustainability. To this end, this paper develops a novel hybrid multi-criteria group decision making model for sustainable building material selection under uncertainty. The information representation construction used for alternative-criteria assessments in this model is a brand-new notion called Basic Uncertain Linguistic Information, which is capable of handling the qualitative performance estimates as well as its partial reliability. Multiple stakeholders are usually responsible for sustainable building material selection, and therefore, the fact that multiple perspectives are involved in the collective decision-making efforts is revealed by a Consensus Reaching Process to reach a decision reflecting at least a majority-based agreement among them. The Quality Function Deployment -based approach to determining comprehensive importance ratings of assessment criteria is further proposed to take into account diversifying sustainable building material requirements from different stakeholders. Subsequently, the ELECTRE III methodology, which models the heterogeneity and non-compensation among assessment criteria as well as their qualitative essence, is introduced to determine the ultimate priorities of alternative sustainable building materials. Finally, sensitive and comparative analyses are performed to verify the advantages of the proposed model in comparison with several existing methodologies.