Bayesian Network Analysis of Risk Factors Impacting Progress in Old Residential Area Renovation Projects

In this study, a Bayesian network method was utilized to establish a Bayesian network model, determine the relative importance of key influencing factors of the old residential communities renovation project progress risks, and quantitatively analyze the interaction of each identified factor. Through the reverse reasoning function of the Bayesian network model, the most likely factors and the most likely cause chain of delays in the progress of the renovation project of old residential areas were summarized. By modeling the probabilistic relationships among various risk factors, BNs enable project managers to make informed decisions and proactively address potential issues. The finding underscores the versatility and effectiveness of BNs in different aspects of renovation projects from structural integrity to financial risks. Moreover, public disputes, particularly in renovation projects are significant impediments to timely project completion. Future research should focus on developing more robust frameworks for stakeholder engagement and conflict management to further enhance project outcomes.