Critical Factors Affecting Fast-Track Construction Management for Infrastructure Projects: Validated Scale Development and K-Means Clustering Algorithms Insights

The fast-track project concept has become crucial in today’s competitive business landscape, driven by escalating market demands. This research aims to pinpoint success-determining factors in such projects, a quest initiated through an extensive literature review and further explored via structured interviews and questionnaires. This study unfolds in multiple phases, beginning with interviews of five experts with over 25 years of experience validating 10 critical factors: planning, scheduling, customer commitment, communication, risk management, technology adoption, project skills, material management, activity breakdown, and leadership. Subsequent phases involve quantitative approaches, including a survey with 125 respondents, predominantly Filipino professionals with substantial construction experience, and a follow-up phase with 200 Filipino respondents. These phases leverage principal component and confirmatory factor analysis, alongside machine learning techniques like K-means clustering, to analyze each success factor’s significance and perception variations. The analysis found high component loadings above 0.6 for critical success factors, confirmed by Cronbach’s Alpha values within the acceptable range of 0.6 to 0.8, but faced challenges in model fit, indicated by mixed results in Confirmatory Factor Analysis with communalities below 0.4 and inconsistent appropriate indices. The paper also looks into the application of the K-means clustering algorithm. Finally, it lays the groundwork for future research, emphasizing the need for diverse, experienced perspectives in understanding fast-track project dynamics.