Developing a Bayesian belief network model for prediction of R&D project success

Abstract

The project success is critical to the business performance in the era of fierce competition and globalization. The basis for project success lies in the capabilities of managing risks effectively. Innovation has always been considerably risky; however, managing Research and Development (R&D) project risks has become even more important given today’s tight schedules and limited resources. Risk management has to be an integral part of the development process. The purpose of this research is to develop a model to assess and estimate the risk exposure of an R&D project. A risk quantification model based on the Bayesian belief network is proposed, which is effective in capturing the interaction between various risk factors. The aim of this model is to empower the project managers to predict the failure risk probability of R&D projects.