Forecasting Financial Literacy Levels with Respect to Consumer Shopping Behaviour

Contemporary consumer society is deeply intertwined with the concepts of money and shopping, which are closely related yet often studied separately. Despite their interconnectedness, there is a notable gap in research that simultaneously addresses financial literacy as a tool for effective money management and informed shopping decisions. This study investigates the relationship between these concepts through theoretical analysis and an empirical survey conducted in the Slovak Republic. Given the similarities in business environments across V4 countries, we posit that our findings may have broader applicability. Survey results were analysed using selected statistical methods, including the chi-square test of independence, to test hypotheses related to financial literacy. Where dependencies were identified, contingency coefficients were used to quantify their strength. Additionally, predictive models of financial literacy levels of two types were developed. Firstly, models were created for both predictive and explanatory purposes using the CHAID classification tree and logistic regression demonstrating high performance, clarity, and interpretability. Secondly, several prediction models using advanced machine learning techniques were created for highly precise predictions of financial literacy levels.