Strategies for enhancing construction digitalisation: a machine learning-based sensitivity analysis

Abstract

Purpose – To achieve digitalisation, construction organisations need strategies to help align existing business structures with emerging digital technologies. To this end, this paper presents the findings of an assessment of the strategies required for construction digitalisation using South Africa as a point of reference. Design/methodology/approach – The study adopted a mixed-method design using a Delphi and questionnaire survey, while the critical strategies for digital construction were identified using three different machine learning (ML)-based sensitivity analyses. Findings – The study, through factor analysis, found five major groups of strategies: (1) understanding the construction market, (2) creating a digital culture, (3) technology deployment and assessment, (4) communication management and (5) finance. However, the three ML-based sensitivity analyses all revealed that technology deployment and assessment, as well as understanding the construction market, are the two most important strategies for construction digitalisation in South Africa. Originality/value – The paper offers practical guidelines for construction organisations to be digitalised. It also offers methodological contributions to using ML in survey studies within construction. Theoretically, the study provides a foundation for future studies on strategies for construction digitalisation – an aspect that has received less attention in the current construction digitalisation discourse.