Business Analytics in the Automotive Industry: A Bibliometric Analysis from 2020 – 2025

Business Analytics in the Automotive Industry: A Bibliometric Analysis from 2020 – 2025

Mohamad Zulhelmi Othman¹, Erne Suzila Kassim², Emi Normalina Omar^3*, Iffan Maflahah⁴

¹Proton Centre of Excellence Westbound Expressway 47600 Subang Jaya Subang Jaya Selangor Malaysia

^2,3Universiti Teknologi MARA Kampus Puncak Alam Selangor, Malaysia

⁴Department of Agroindustrial Technology, University of Trunojoyo Madura Bangkalan, East Java   Indonesia

*corresponding author

Publication Information

Journal Title: International Journal of Research and Innovation in Social Science (IJRISS)
Author(s): Othman, Mohamad Zulhelmi ;Kassim, Erne Suzila ;Omar*, Emi Normalina ,;Maflahah, Iffan
Published On: 12/10/2025
Volume: 9
Issue: 9
First Page: 4092
Last Page: 4104
ISSN: 2454-6186

Cite this Article Othman, Mohamad Zulhelmi ;Kassim, Erne Suzila ;Omar*, Emi Normalina ,;Maflahah, Iffan ;Business Analytics in the Automotive Industry: A Bibliometric Analysis from 2020 – 2025, Volume 9  Issue 9, International Journal of Research and Innovation in Social Science (IJRISS),4092-4104, Published on 12/10/2025, Available at https://rsisinternational.org/journals/ijriss/articles/business-analytics-in-the-automotive-industry-a-bibliometric-analysis-from-2020-2025/

Abstract

This study examines the shifting role of business analytics within the automotive sector, focusing on research from 2020 to 2025. Given the rapid rise of digitalization, artificial intelligence, and data-driven methods, the authors aim to chart prevailing research directions, highlight key thematic concerns, and point out overlooked areas. Drawing from nearly 300 Scopus-indexed articles and conference proceedings, the analysis leverages VOS viewers to visualize the research landscape through network, overlay, and density maps. The findings reveal five main thematic clusters, with recurring attention to decision making, machine learning, Industry 4.0, and the Internet of Things. Much of the literature centers on operational and strategic improvements within automotive organizations. That said, topics such as electric vehicles, smart cities, and customer analytics remain notably underrepresented. While the field is clearly moving toward sustainable and intelligent systems, there is a distinct lack of focus on consumer behavior and analytics specific to electric vehicles. In summary, business analytics appears deeply embedded in core automotive functions, yet there is a clear need for future research to address consumer engagement and regional challenges particularly in emerging markets. It is important to note that the study’s scope was limited to English-language publications within the business and management domain, potentially leaving out significant technical contributions.

Keywords: Business Analytics,  Automotive Industry, Bibliometric Analysis, Machine Learning, Digital Transformation