journal article·2024-07-20Open access

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

Monika Sukiennik, Jerzy Baranowski

Applied Sciences· Volume 14· Issue 14

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.
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Research context

OpenAlex topics: Advanced Statistical Methods and Models · Forecasting Techniques and Applications · Statistical Methods and Bayesian Inference

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Automatic Control & Robotics, AGH University of Kraków, 30-059 Kraków, Poland

Funding

National Science Centre · AGH’s Research University Excellence Initiative

References (18)

Show source-provided references
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