Micro BIM Adoption: Identifying Cause and Effect Factors and Analysing their Inter-dependencies using a Fuzzy DEMATEL Approach

Abstract

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.