Using Demographic Features for the Prediction of Basic Human Values Underlying Stakeholder Motivation

Human behavior plays a significant role within the domain of information security. The Conflicting Incentives Risk Analysis (CIRA) method focuses on stakeholder motivation to analyze risks resulting from the actions of key decision makers. In order to enhance the real-world applicability of the method, it is necessary to characterize relevant stakeholders by their motivational profile, without relying on direct psychological assessment methods. Thus, the main objective of this study was to assess the utility of demographic features-that are observable in any context-for deriving stakeholder motivational profiles. To this end, this study utilized the European Social Survey, which is a high-quality international database, and is comprised of representative samples from 23 European countries. The predictive performances of a pattern-matching algorithm and a machine-learning method are compared to establish the findings. Our results show that demographic features are marginally useful for predicting stakeholder motivational profiles. These findings can be utilized in settings where interaction between a stakeholder and an analyst is limited, and the results provide a solid benchmark baseline for other methods, which focus on different classes of observable features for predicting stakeholder motivational profiles.