Transforming the automotive industry: Defining, clustering, and efficiency analysis of the next-generation automotive ecosystem

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Authors: Minjung Shon, Joon Kim, Hongbum Kim
Cited by: 1
References: 72

Abstract

Using firm-level data, this study explores how next-generation automotive innovations are reshaping the automotive industry. The sector is now transitioning from a previously defined vertically integrated supply chain into a more horizontal ecosystem in which multiple companies collaborate to build next-generation vehicles. To define and categorize this ecosystem, this study classifies firms into three major groups of electric vehicles (EVs), autonomous vehicles (AVs), and general automotive technologies (GATs) by employing K-means clustering based on patent data. This study then measures firm efficiency in each ecosystem using meta-frontier analysis to compare their technical efficiency over the periods 2017-2019 and 2020-2022. The results show that the EV ecosystem led the initial growth while the GAT ecosystem continued to make steady progress. Later, the AV ecosystem exhibited remarkable technological innovation and efficiency gains. These findings indicate that efficiency dynamics and technology gaps differ systematically across ecosystems, reflecting heterogeneous innovation trajectories within the broader industrial transformation. Overall, our findings clarify the growth potential and trajectories in the automotive industry, thereby providing insights for stakeholders seeking to navigate this rapidly changing landscape and contributing to a clearer understanding of the next-generation automotive ecosystem.

Fields of Study & Subjects

Innovation Diffusion and Forecasting Efficiency Analysis Using DEA Digital Transformation in Industry

Publication details

Journal / source
PLoS ONE
Publisher
Public Library of Science (PLoS)
Volume
21
Issue
2
Pages
e0343135–e0343135
Publication date
23 February 2026
Language
EN