Luxury Car Data Analysis: A Literature Review

Pegah Barakati (), Flavio Bertini, Emanuele Corsi, Maurizio Gabbrielli and Danilo Montesi
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Pegah Barakati: Department of Computer Science and Engineering, University of Bologna, 40126 Bologna, Italy
Flavio Bertini: Department of Mathematical, Physical and Computer Sciences, University of Parma, 43124 Parma, Italy
Emanuele Corsi: Department of Computer Science and Engineering, University of Bologna, 40126 Bologna, Italy
Maurizio Gabbrielli: Department of Computer Science and Engineering, University of Bologna, 40126 Bologna, Italy
Danilo Montesi: Department of Computer Science and Engineering, University of Bologna, 40126 Bologna, Italy

Data, 2024, vol. 9, issue 4, 1-20

Abstract: The concept of luxury, considering it a rare and exclusive attribute, is evolving due to technological advances and the increasing influence of consumers in the market. Luxury cars have always symbolized wealth, social status, and sophistication. Recently, as technology progresses, the ability and interest to gather, store, and analyze data from these elegant vehicles has also increased. In recent years, the analysis of luxury car data has emerged as a significant area of research, highlighting researchers’ exploration of various aspects that may differentiate luxury cars from ordinary ones. For instance, researchers study factors such as economic impact, technological advancements, customer preferences and demographics, environmental implications, brand reputation, security, and performance. Although the percentage of individuals purchasing luxury cars is lower than that of ordinary cars, the significance of analyzing luxury car data lies in its impact on various aspects of the automotive industry and society. This literature review aims to provide an overview of the current state of the art in luxury car data analysis.

Keywords: car data analysis; luxury cars data analysis; luxury car data literature; car data; monetization; literature review (search for similar items in EconPapers)
JEL-codes: C8 C80 C81 C82 C83 (search for similar items in EconPapers)
Date: 2024
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