The values and barriers of Building Information Modeling (BIM) implementation combination evaluation in smart building energy and efficiency

With the continuous increase in the number of buildings, the phenomenon of excessively high energy consumption becomes more and more serious. It is particularly important to reduce the energy consumption during the operation of the whole life cycle of the building. Building Information Modeling (BIM) technology is based on the relevant parameters of construction projects, and uses digital information simulation to establish building information models. It is one of the technical means of building energy consumption analysis and energy saving management, that can be explained as the main reason for stakeholders to guide energy and efficiency changes of the driving factor in buildings. We start co-occurrence statistics and type analysis based on the co-occurrence context analysis, construct the co-occurrence information that affects the values and barriers combination of BIM implementation for smart building energy and efficiency, and chose the expert database of the Green Construction and Intelligent Building Branch (GCIBB) of China Construction Association, that obtained 104 samples through modified snowball sampling, using exploratory factor analysis with factor load linear functions, and combined factor variance contribution rate weights. We created index function of the values and barriers combination of BIM implementation in smart building energy and efficiency, and classified and calculated the comprehensive score of each factor according to the ranking evaluation index, and mapped its practical significance. The results show that the 18 combined evaluation indicators proposed in this paper are suitable for evaluating the three elements of benefit, efficiency and quality of smart buildings, and can achieve continuous optimization of building energy consumption. The constructed multi-factor combination evaluation model, the extracted common factor variance cumulative contribution rate is greater than 80%. (C) 2022 The Author(s). Published by Elsevier Ltd.