Knowledge management system as an efficient and sustainable strategy to minimize uncertainty in the process of risk assessment

Abstract

Risk assessors could adopt qualitative, semi-quantitative, or quantitative approaches to analyze various risks; the combination of these approaches alleviates the shortcomings of risk assessment techniques, namely uncertainty, knowledge dimension, and time dynamics when techniques are used alone. The knowledge dimension plays a pivotal role in these shortcomings, as knowledge reduces uncertainty (United States Environmental Protection Agency [EPA], n.d.-a) and the timely knowledge update of global trends and emerging risks is expected to resolve the issue of time dynamics (another cause of uncertainty) by reassessing risks and characterizing risk data over a time interval (Wassénius & Crona, 2022). However, substantial research and development are required to generate adequate modeling and analytical methods to deal with different and complex systems. Based on the literature review and industry best practices, the study develops a risk assessment knowledge management system framework that focuses on the root of the shortcomings of risk assessment techniques, namely the knowledge dimension; this strategy is efficient and sustainable by indirectly addressing the unresolved issues of uncertainty and time dynamics through the knowledge dimension. The conceptual framework minimizes the uncertainty (the root of risk) in the decision-making process of selecting the appropriate risk assessment tools and effectively implementing them.