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In the elicitation of decision makers' fuzzy and uncertain assessments, linguistic terms are natural and efficient as the preference modeling tools. Although the linguistic variables are available, they would not be operational without any detailed quantification. Motivated by the flexibility of information granularity, this paper develops information granules to represent linguistic terms in the form of intervals and interval type-2 fuzzy sets (IT2FSs) in best worst method (BWM). The development is aimed at minimizing inconsistency in the decision making (DM) process to ensure the rationality of the assessments provided by decision makers. Furthermore, the input and output based consistencies of BWM are considered. The granulation of entries of pairwise comparison vectors are the foundation of BWM to formulate an optimization problem where particle swarm optimization (PSO) algorithm serves as the optimization framework. Both individual and group decision making (GDM) scenarios are taken into consideration. For the GDM process, a performance index for measuring the group consensus is also proposed. Several examples and validity analysis are covered to illustrate the major ideas of this study. Finally, as a case study, a recommendation of the sequence of visiting tourist attractions in Wuhan and the corresponding comparative analysis are represented. • A granular computing-based method in BWM framework is proposed. • Construction of granular linguistic information to represent preference information of DMs is given. • A novel Euclidean distance function to measure the agreement among the group is proposed. • A case study of scenic spots recommendation in Wuhan with online reviews is exhibited. [ABSTRACT FROM AUTHOR]

Building information modeling (BIM) maturity models occupy a crucial role in guiding BIM-reliant stakeholders and enterprises to identify BIM capabilities and facilitate process improvements. Nevertheless, few quantitative BIM maturity models are available for the measurement and improvement of BIM utilization performance. This study designs a refined assessment system for the maturity measurement of BIM-based projects during the design and construction stages. The advocated BIM maturity model combines a probability distribution function aggregation paradigm and a large-scale group decision-making framework to provide an expert-based assessment system for evaluating project-based BIM performance. The case study of the Corning Gen 10.5 glass substrate production line workshop in Wuhan demonstrates the feasibility and effectiveness of the proposed model. This paper establishes a generalizable structural framework that can potentially facilitate BIM maturity analysis in a portfolio of projects or the industry as a whole and will generate fresh insight into designing quantitative BIM maturity models across various contexts. • We design a refined assessment system for BIM maturity measurement. • We redefine the BIM maturity levels and provide corresponding descrpitions. • We propose a BIM maturity model based on PDF aggregation and LSGDM. [ABSTRACT FROM AUTHOR]