Localising global construction delay risk factors: an optimisation-enhanced expert consensus framework for the Australian construction industry

Purpose This study aims to investigate how globally identified construction delay factors can be translated into a framework that accurately reflects Australian project conditions. It aims to develop a validated set of delay risks by integrating systematic evidence synthesis with expert elicitation and optimisation-based consensus analysis. Design/methodology/approach A systematic literature review consolidated 103 global delay factors, refined to 55 using a relevance-based filtering approach. Semi-structured interviews with senior Australian practitioners were conducted to assess contextual severity. Inter-rater agreement was measured using Kendall's Coefficient of Concordance (W), and a Genetic Algorithm (GA) was applied to optimise expert weighting and maximise consensus reliability, producing a statistically robust prioritisation. Findings The optimisation process achieved strong expert agreement and generated a refined set of delay risks tailored to Australian project conditions. The most influential delays stem from governance and design-related issues, including late owner decisions, documentation delays, unclear drawings, and coordination challenges, alongside labour constraints and subcontractor performance. Cross-validation and triangulation with recent Australian studies confirmed the stability and contextual relevance of the final framework. Practical implications The 22-factor framework provides practitioners with a clear basis for identifying and prioritising delay risks within Australian projects. By guiding planning and design decisions, it helps reduce schedule uncertainty and improve the predictability of project delivery. Originality/value This research advances construction risk analysis by introducing an optimisation-enhanced localisation method that integrates global evidence, expert judgement, and evolutionary algorithms to produce a validated delay risk framework for Australia. The combined use of GA-based expert weighting and Kendall's W strengthens consensus reliability and offers a transparent methodological innovation to the field.