Exploring Time-Based Characteristics of the E-Car Market for Effective Market Segmentation

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In recent years, the electric car (e-car) market has seen noticeable growth attributed to technological advancements and new research offering multiple innovation possibilities for businesses, which should effectively bring new technologies to market, create added value for customers, and capture value for manufacturers. Leveraging data-driven methods and analytics within the e-car market is instrumental in guiding decision-making processes and facilitating the development of new value propositions and services. This study aims to provide insights into the evolution of e-car features, identify potential market segments, and support data-driven decision-making in business and marketing research. Our analysis focuses on e-car data from 2010-2023, utilizing data-driven techniques such as principal component analysis, clustering, trend analysis, and enrichment analysis. The trend analysis considers the series start year of e-car models and their corresponding summarized features as principal components and examines changes over time. Hierarchical cluster analysis then allows us to identify distinct segments in the e-car market, while enrichment analysis with respect to the series start year and brand helps us understand the latest innovations in different segments. Our analysis reveals a potential trend in the e-car market, suggesting a shift towards medium- and medium-large-sized cars that offer improved range, speed, and lower energy consumption. Additionally, the identified six clusters as the latest segments, which, in conjunction with the trend analysis, present opportunities for optimizing product development and identifying new market spaces. Managers can utilize the findings of this study to explore future market opportunities.

Original languageEnglish
Pages (from-to)64-76
Number of pages13
JournalProcedia Computer Science
Publication statusPublished - 2024
Event5th International Conference on Industry 4.0 and Smart Manufacturing, ISM 2023 - Lisbon, Portugal
Duration: 22 Nov 202324 Nov 2023


  • e-car data
  • factor analysis
  • PCA
  • segmentation
  • trend analysis


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