Hybrid Statistical Analysis of Critical Alignment Factors in Modular Integrated Construction

While modular integrated construction (MiC) offers an efficient and sustainable approach to construction projects, the precise alignment of modules during onsite installation remains a critical challenge. Despite its significance, current research lacks a comprehensive understanding of the factors affecting module alignment and their relationships, particularly in the context of Hong Kong and Mainland China's construction industry. To address this crucial knowledge gap, this study employs a mixed-method approach, combining expert discussions and literature review to develop a questionnaire survey. Through this systematic process, 18 factors were identified and categorized into four key constructs: module feature-related, worker-related, equipment-related, and weather-related factors. The study utilized partial least squares structural equation modeling (PLS-SEM) and Ginni's mean to evaluate the relationships and to determine the stationary factors that affect module alignment in MiC. The findings from PLS-SEM revealed that the four identified factors significantly influence module alignment, with an R2 value of 98.3%, while Ginni's mean analysis identified the condition of the rigging equipment as the key stationary factor. This study offers insights to academia and industry professionals in the MiC industry to assist in developing evidence-based strategies to mitigate the impact of factors affecting alignment in MiC.