Risk Assessment Model for Innovative Projects Based on Fuzzy Sets and Bayesian Networks

With the rapidly changing economic environment and inherent market conditions, risk assessment is becoming a major priority for companies involved in innovative projects. Innovative projects are characterized by great uncertainty and their success largely depends on a variety of factors. To improve the quality of risk assessment for such projects, it is essential that you use methods that consider the complex relationships between many variables. This paper suggests a model based on fuzzy sets and Bayesian networks that allows you to effectively analyse and manage the risks of innovative projects. Using fuzzy sets can help you take into account the uncertainty in the data and work with fuzzy information, which is of prime importance, as there are a lot of diverse data that must be considered in innovative projects. With Bayesian networks, you can model probabilistic relationships between risks and project factors, which gives you a more accurate idea of potential risks and helps you predict possible scenarios for the project. Our model represents an innovative approach to assessing the risks of innovative projects and contributes to more effective risk management and informed decision-making in the case of complex projects. It can also facilitate sustainable development of the innovation sector and increase the competitiveness of companies due to the more efficient use of resources and a higher probability of successful innovative initiatives in the long run.