Innovative decision-making modelling for risk analysis in industrial informatization of infrastructure project

Abstract

Rapid economic growth has driven the increasing scale and complexity of infrastructure projects, introducing significant challenges associated with uncertainty and risk. Approaches relying primarily on engineering judgment lack the capacity to effectively capture and quantify these uncertainties in complex project environments. This study introduces a novel multi-criteria decision-making approach utilizing spherical fuzzy sets to enhance the informatization and integration of risk management processes in industrial contexts. The proposed approach integrates multi-source evaluations, enabling the accurate calculation of criteria weights and fostering robust information processing capabilities. Through sensitivity and comparative analyzes, the developed approach demonstrates its effectiveness in managing multi-source risk assessments, facilitating informed decision-making. A decision clarity index is introduced to quantitatively assess the impact of varying decision-making conditions on risk source identification. This study advances industrial information integration by integrating mathematical models with risk management practices, offering a structured approach and practical strategies to enhance decision-support systems for infrastructure projects in complex industrial environments.