Exploring multilevel data with deep learning and XAI: The effect of personal-care advertising spending on subjective happiness

Abstract

International business research often links the cultural and institutional characteristics of countries to the features of the individuals inhabiting these countries. A distinct approach to analyzing such multilevel problems with deep learning and explainable artificial intelligence methods is presented, using country characteristics as explicit spatial coordinates. Deep learning is tolerant of noise and faults and can approximate arbitrarily complex mathematical structures by developing multiple abstractions. An applied example demonstrates the applicability of this approach by exploring the effect of personal-care advertising spending in 27 countries on the subjective happiness of 376,442 individuals, indicating a statistically significant positive effect, albeit with a trivial effect size.