The impact of cognitive bias on project success

The construction industry is a dynamic environment characterised by uncertainties and complexities. This challenging nature of construction projects makes project managers' decision processes susceptible to cognitive biases that adversely impact project success. The devastating impact of failed construction projects has massive financial implications for project stakeholders and the UK economy. Hence, this study investigates the effects of cognitive bias on the decision-making processes in construction projects in the United Kingdom. The research adopted an explanatory sequential mixed-methods approach that combines quantitative surveys and focus group discussions to explore the prevalence of cognitive biases among project managers and how these biases impact project outcomes sub-optimally. The study focused on optimism bias, availability error and loss aversion as the predominant biases in construction projects. The quantitative findings identified the latent factors for the emergence of cognitive bias as project management practices, team dynamics, professional regression, and external influences. These factors significantly influence decision-making across the different construction project phases. Remarkably, the study identified similar parallel levels of biases within the three decision-making phases examined; the initiation and planning phases exhibit comparable levels of bias as the execution and closing phases. In addition, the study identifies a high perceived effectiveness and usage of debiasing techniques among project managers. The qualitative insights support the quantitative findings, highlighting the widespread recognition of cognitive biases and the unanimous endorsement of debiasing strategies within the construction industry. The study developed a cognitive debiasing protocol to mitigate biases and enhance rational decision-making in construction projects. The practical implications for the research findings are that project managers can understand the underlying factors for the emergence of cognitive bias and adopt proactive measures for the challenges presented by cognitive bias at the different project phases. The findings highlight the need for targeted interventions and industry-specific debiasing strategies. The study provides a foundation for future research to explore individual differences and cross-cultural influences in bias mitigation and the integration of artificial intelligence in mitigating cognitive biases within construction projects.