Fuzzy Ontologies in ERP Implementation Cost Estimation –A Literature Review

For many years, estimating the costs of ERP system implementations has remained a significant challenge in IT project management due to the high degree of uncertainty and complexity inherent in such projects. In recent years, numerous approaches have been proposed to improve cost estimation accuracy at the early stages of projects, including methods based on fuzzy ontologies. This paper presents a comprehensive review of the current state of knowledge on fuzzy ontologies (both Type-1 and Type-2) and their applications in the cost estimation of IT projects, with a particular focus on ERP system implementations. The article discusses key concepts in fuzzy ontology modelling and the development of this field over recent years, as well as examples of fuzzy ontology implementations in software cost estimation. Alternative approaches to ERP implementation cost estimation are also presented—ranging from traditional algorithmic models to recently popular artificial intelligence (AI) -based techniques. Furthermore, the paper introduces available AI tools and techniques that may enhance fuzzy ontologies in this application domain. In the discussion, a critical comparison is made between the effectiveness of fuzzy ontologies and other AI-based methods in ERP implementation cost estimation, highlighting their advantages, limitations and potential directions for future research.