Composite Indicators Used in Measuring Hybrid Threats

Abstract

Abstract The article aims to highlight the usefulness of composite indicators applications as an analytical tool in guiding national security policies related to multidimensional phenomena revealing its role in measuring hybrid threats - as part of global risks. The qualitative and quantitative research shows that the use of composite indicators in measuring hybrid threats at country level is a relatively new topic, that has enjoyed increased interest since 2021. The originality lies in the way it is putted in evidence the link between the composite nature of hybrid threats, and the composite indicators in order the argue the role using this modern tool in the process of forecasting the risks with national impact, by using SWOT analysis. To highlight the relevance of composite indicators in measuring hybrid threats to peace and security, we have chosen to compare the results of measurement made by Normandia Index. The outcomes demonstrate upward trend in hybrid threat values (cybercrime, economic crises, disinformation, energy insecurity and terrorism) at the UE-27 level (as one country), comparative to the world level situation, between 2019-2022. We concluded that using composite indicators in measuring hybrid threats represents an analytical strategical level method that could play a role as an early warning engine to support policy makers and, also as a facilitator instrument of the planning process country level to avoid strategic surprises and prevent security risks. Considering the geopolitical clashes of power poles and the unpredictable situation of the socioeconomic environment, we have concluded that future steps of the research should be related with the dynamics of hybrid threats at the global level. An important contribution could be brought by the development of new systems for interpreting measurement by specialized software, and by the identification of appropriate calculation formulas to reduce misinterpretation due to the lack of real data provided.