Cash flow forecasting with risk consideration using Bayesian Belief Networks (BBNS)

Abstract

Cash-flow management is very important for contractors given that inadequate cash resources typically are the main causes for bankruptcy of construction companies. In comparison to most other industries, the construction industry is severely plagued by risk, and the success of construction projects usually depends on valuating all risks. However, conventional methods suggested by extant research on cash flow forecasting do not consider comprehensive identification of risk factors, interactions between the factors, and simultaneous occurrences of the factors. This study introduced a simple and appropriate probabilistic cash flow forecasting model using Bayesian Belief Networks (BBNs) to avoid bankruptcy of contractors by considering influence diagrams and risk factors that affect a project. Workability and reliability of the proposed approach was tested on an important building construction project in Iran as a real case study, and the results indicated that the model performed well.