Risk assessment modeling for knowledge based and startup projects based on feasibility studies: A Bayesian network approach

The start of any business requires investment. The risks involved in this pathway are one of the biggest barriers in each investment. Feasibility studies are one of the most common methods in analyzing an investment plan, but this method does not respond to the risk value of any plan. Therefore the present study aims to calculate the risk of a project through a feasibility study. To this end, Bayesian networks have attracted much attention as a powerful method for modeling decision making under uncertainty conditions in different domains. This paper presents a Bayesian network modeling framework that obtains the project risk by calculating uncertainty in net present value of projects. This model provides a powerful method for analyzing risk scenarios and their impact on the project success. This model can be used as a basis for assessing the risks of innovative projects whose feasibility study has been performed. (C) 2021 Elsevier B.V. All rights reserved.

Automated summary

This paper introduces a Bayesian network modeling framework for calculating project risk, providing a powerful tool for analyzing risk scenarios and their impact on project success.