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

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.

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Publication Details

Journal
PLoS ONE
Published
2026-02-23
DOI
https://doi.org/10.1371/journal.pone.0343135
Primary Topic
Innovation Diffusion and Forecasting
Type
article
Field-Weighted Citation Impact
0.00
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article

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

Hongbum Kim, Minjung Shon, Joon Kim
PLoS ONE
Innovation Diffusion and Forecasting
article

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

Hongbum Kim, Minjung Shon, Joon Kim
article en

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.

PLoS ONEVol. 21(2)
Gachon University (KR), Kyonggi University (KR), Korea Institute of Industrial Technology (KR)
Industry, innovation and infrastructure
Openalex Percentile: Top 51%
Innovation Diffusion and Forecasting
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