Multilevel Hierarchical Bayesian Modeling of Cross-National Factors in Vehicle Sales

Abstract

SUVs (sport utility vehicles), as a car segment, have become a foundation within the automotive industry due to their versatility, which is used by a wide range of customers. Recognising the complex interplay between geographical and economic conditions across countries, we delve into cross-national factors that significantly influence SUV sales. This article presents an analysis of the global sales of SUVs (sport utility vehicles) using multilevel hierarchical Bayesian modelling. We identify key predictors of SUV sales, including the effects of fuel prices, income levels and geographical aspects. We prepared four statistical models that differ in their probability distribution or hierarchical internal structure. The last presented model, with Student’s t-distribution and separate distribution for unique alpha parameter values, turned out to be the best one. Our analysis contributes to a deeper understanding of the automotive market dynamics, and it can also assist manufacturers and policymakers in designing effective sales strategies.