The careful consideration and choice of Sustainable Architectural Glass Material (SAGM) is a crucial step towards reducing energy consumption and enhancing the overall sustainability of buildings. However, the current techniques employed for selecting SAGM do not take into account the aspect of sustainability in the ultimate adoption of material solutions, as perceived by the stakeholders. This study aims to develop a comprehensive evaluation criteria system and introduce a group decision support framework that utilizes Building Information Modeling technology to facilitate the selection of SAGM in large-scale projects, in accordance with the demands of various stakeholders. The proposed framework is utilized to address a selection problem related to SAGM faced by a large construction corporation in Wuhan. The findings indicate that the criteria of daylighting and thermal insulation performance hold significant importance, with insulating glass being a subtype of SAGM exhibiting superior performance. Ultimately, the proposed model is subjected to sensitivity and comparative analyses to validate its advantages over several existing methodologies. The proposed model in this study offers practitioners an optimized methodology for the selection of SAGM, while also providing a framework for the selection of other sustainable building materials.

Building green airports can be regarded as among the most promising routes to sustainable development of ecosystems and human health. This study aims at addressing the problem of green airport plan selection under an uncertain context by developing an uncertain multiattribute group decision making (MAGDM) model. In the proposed model, the assessment information is characterized in the form of a proportional hesitant 2-tuple linguistic term set (PH2TLTS), which incorporates in binary form linguistic information that can accurately quantify subjective assessment information provided under uncertainty. The weights of assessment attributes of green airport plans are obtained automatically through a nonlinear programming model, which enhances the robustness of the decision-making method. Subsequently, on the basis of PH2TLTSs, three distance measures are proposed: the proportional hesitant 2-tuple linguistic Jaccard distance (PH2TLJD), the supplementary proportional hesitant 2-tuple linguistic normalized Minkowski distance (SPH2TLNMD) and the cluster-based proportional hesitant 2-tuple linguistic normalized Minkowski distance (CBPH2TLNMD). The TOPSIS-based comparison method proposed here can better determine the priorities of PH2TLTSs. The ranking and selection of green airport plans are derived using the PH2TL-VIKOR model. Finally, a case study accompanied by sensitivity and comparative analyses is performed to verify the rationality and feasibility of the proposed model.