Abstract

Abstract Offsite construction has been identified as an effective approach for enhancing the sustainability of the construction industry. However, due to the fragmented production processes of offsite construction, quality defect control has become a significant challenge in the promotion of offsite construction projects. Offsite construction projects involve multiple interdependent stakeholders in close collaboration. These stakeholders play various roles in quality management and have different degrees of impact on the occurrence of quality defects. To enhance quality defect management in offsite construction projects, it is important to evaluate the different stakeholder impacts on the occurrence of quality defect. Through impact evaluations, critical stakeholders can be identified and their responsibilities clarified with respect to project quality, thereby motivating these key stakeholders to improve their quality defect control. In this study, we developed an evaluation model using the Bayesian network approach to measure stakeholder impacts on defect occurrence in offsite construction projects. Quality defects and stakeholder-related factors that might incur defects were modeled as a Bayesian network and the dependencies among network nodes examined. Then, the stakeholder impacts on the occurrence of quality defects were evaluated using Bayesian analysis. Finally, this Bayesian-network-based evaluation model was applied to a real project in Shenzhen, China. The results indicate that use of precast components with quality defects, misoperations by construction workers, and ineffective quality inspection and testing during onsite assembly and construction were the major factors affecting quality defect control. Additionally, in this case study, we found the contractor to have the highest level of impact on the occurrence of quality defects. This study contributes to the fields of stakeholder impact evaluation and quality defect analysis, and links defect management with key project stakeholders.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.