Developing a Bayesian belief network model for quantifying and predicting claim causes-related schedule delays

Abstract

Nowadays, construction claims have become an inevitable part of the construction project, and they have a serious impact on the project schedule. This study aims to develop a Bayesian belief network (BBN) model for quantifying and predicting claim cause-related schedule delays in Vietnam. Based on data from survey questionnaires and interviews with experts, 23 critical claim causes of construction project schedule delays and 17 significant cause-effect relationship pairs were found and used to build the BBNs models. The results obtained from the BBNs models are good at quantifying the probability of schedule delays in three different case study projects. In the case study of a transportation project, for example, there is a major delay of 34 months, which is about 38.64% of the original length of the project. The model predicted that there is a 69% chance that the project’s schedule delay will be more than 20% of the original length. Using these BBNs models, industry practitioners can prevent claim causes-related schedule delays early. This approach is general and can be applied to any construction project in other countries with small adjustments, especially in the case of developing countries similar to Vietnam.