Building Information Modelling (BIM) is an innovation that is transforming practices within the Architectural, Engineering, Construction and Operation (AECO) sectors. Many studies have investigated the process of BIM adoption and diffusion and in particular, the drivers affecting adoption at different levels, ranging from individual and team through organisations and supply chains to whole market level. However, in-depth investigations of the stages of the BIM adoption process and the drivers, factors and determinants affecting such stages are still lacking. A comprehensive classification and integration of adoption drivers and factors is absent as these are disjointedly identified across disparate studies. There is also limited attention to the key terms and concepts (i.e. readiness, implementation, diffusion, adoption) in this area of study. This aim in this paper is twofold: (1) to develop and validate a Unified BIM Adoption Taxonomy (UBAT); and (2) to identify the taxonomy's constructs (i.e. three driver clusters and their 17 factors) that have influence on the first three stages of the BIM adoption process namely, awareness, interest, and decision stages, and compare their effects on each of the stages. The research uses: a systematic literature review and knowledge synthesisation to develop the taxonomy; a confirmatory factor analysis for its validation; and an ordinal logistic regression to test the effect of the UBAT's constructs on the BIM adoption process within the UK Architectural sector using a sample of 177 organisations. The paper is primarily intended to enhance the reader's understanding of the BIM adoption process and the constructs that influence its stages. The taxonomy and its sets of drivers and determinants can be used to perform various analyses of the BIM adoption process, delivering evidence and insights for decision makers within organisations and across whole market when formulating BIM diffusion strategies.

No abstract

To date a comprehensive analysis of interactions among BIM adoption factors, stages of the BIM adoption process, and time (e.g. time intervals of a national BIM initiative) is still lacking. This research aims to profile BIM adoption by mapping such interactions. The analysis is performed for the UK Architecture sector, which was represented with a sample of 177 organisations. To achieve the profiling of BIM adoption in the UK architecture sector, the study uses the outcomes from two types of inferential analysis: an ordinal logistic regression test to identify the 11 top factors influencing the BIM adoption process; and correlation analysis among the 11 top factors at different stages of the BIM adoption process (i.e. awareness, intention, and decision) and across three time intervals (i.e. pre-2011 as the time interval preceding the announcement of the UK BIM mandate, 2011-2016 as the time interval for the implementation of the UK national BIM strategy, and post-2016 as the time interval within which the mandate entered into effect). Capturing the interactions involved in the profiling of micro BIM adoption and assimilating the outcomes in a single model unravel a further understanding of the BIM adoption process. In particular, the results reveal a dynamic behaviour characterising the micro BIM adoption process where: (1) correlated pairs of adoption factors have a varying level of influence within each adoption stage; (2) the factors involved in each pair generally change across the two dimensions (stages of adoption, and time horizon); and (4) the pairs of factors influencing adoption stages over time often combine constructs from the three clusters of drivers identified in [1] (i.e. Innovation/BIM Characteristics,

Several factors affect the process of BIM adoption within organisations (i.e. micro BIM adoption). An extensive collection of such factors were included in a unified BIM adoption taxonomy published in Ahmed and Kassem (2018). These factors are distributed across three areas of adoption drivers: the characteristics of the innovation itself (i.e., BIM), the external environment, and the internal environment of the adopting organisation. BIM adoption is a multistaged process that entails varying interactions between factors from across the three driver areas and the stages of the BIM adoption process. Hence, this study argues for an improved understanding of the adoption topic beyond the current level offered by common approaches such as ranking factors affecting adoption (conceived as a single decision/milestone) and analysing correlations. In particular, there is a need to analyse the complex inter-dependencies between factors affecting the adoption process and its individual stages (i.e., awareness, intention, decision, etc.). This paper aims to understand these inter-dependencies by considering the micro BIM adoption as a complex system. The paper investigates the relative levels of influence between the factors affecting the system and classifies such factors in cause and effect factors at different stages of the adoption process. To achieve this objective, the research employs the Fuzzy Decision Making Trial and Evaluation Laboratory (F-DEMATEL) method. The application of the F-DEMATEL considered the top 11 factors (as identified in Ahmed and Kassem, 2018) that affect BIM adoption within the UK Architecture sector. The F-DEMATEL was applied for the entire adoption process as a 'single' system (i.e. without separating it into multiple stages) and for each individual stage (i.e. awareness, intention, and decision). The results from the F-DEMATEL (i.e., classification of factors into cause and effect groups and into four quadrants, and their interrelationships) provided a new understanding of the BIM adoptions process. These results can be used to tailor and prioritise BIM implementation actions and investments when develop micro BIM adoption strategies.