Abstract
The recent adoption of building information modelling (BIM), and the quest to decarbonise our built environment, has impacted several segments of the supply chain, including design and engineering practitioners, prompting the need to redefine the construction personnel positions along with associated skills and competencies. The research informs ways in which practitioners can fully embrace the potential of BIM for energy efficiency to promote sustainable interventions by improving existing training practices and identifying new training requirements as BIM evolves and as practitioners’ ICT (Information and Communications Technology) maturity levels improve. This is achieved by adopting a novel text-mining approach which analyses social media alongside secondary sources of evidence to establish a level of correlation between BIM roles and skills. The use of ontological dependency analysis has helped to understand the degree of correlation of skills with roles as a method to inform training and educational programmes. A key outcome from the research is a semantic web-based mining environment which determines BIM roles and skills, as well as their correlation factor, with an application for energy efficiency. The paper also evidences that (a) construction skills and roles are dynamic in nature and evolve over time, reflecting the digital transformation of the Construction industry, and (b) the importance of socio-organisational aspects in construction skills and related training provision.Graphic abstract
Highlights
We report the outcome of the analysis involving frequency, association, and importance of roles and skills based on the methodology presented in the previous section
This paper elaborates on an in-depth analysis of primary sources of evidence for the identification of roles and associated skills necessary for improving the implementation of building information modelling (BIM) for energy efficiency training in the construction market
This involved the analysis of a large corpus of documents and Twitter data using text-mining techniques to extract BIM roles and skills as well as to infer their associations and linkages
Summary
Given the forecast of growth in the global construction market of over 70% by 2025 (Robinson 2013), the industry is faced with the challenge and opportunity to reduce energy demand, improve process efficiency, and reduce carbon emissions in line with the Energy Performance of Buildings Directive (2010/31/ EU) (Li et al 2019). In this context, energy efficiency demands adapted technology solutions, strategies (including training and education), and policy-making approaches which should be embraced by the entire supply chain across the whole life cycle of a project. The training and education landscape in construction exhibits the following characteristics (Palm and Thollander 2010; Chai and Yeo 2012; Alhamami et al 2020):
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