Proposal of a Classification Method for Brazilian Automotive Companies Using the Principal Components Analysis

Paulo Sergio Gonçalves de Oliveira (), Luciano Ferreira da Silva (), Pedro Teixeira de Araujo (), Guilherme Fernandes Gomes Reis () and Marco Antônios Soares Gomes Otero ()
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Paulo Sergio Gonçalves de Oliveira: Universidade Anhembi Morumbi
Luciano Ferreira da Silva: Universidade Nove de Julho
Pedro Teixeira de Araujo: Centro Universitário de Belo Horizonte – UNIBH
Guilherme Fernandes Gomes Reis: Centro Universitário de Belo Horizonte – UNIBH
Marco Antônios Soares Gomes Otero: Centro Universitário de Belo Horizonte – UNIBH

SN Operations Research Forum, 2025, vol. 6, issue 4, 1-26

Abstract: Abstract This article proposes a method for classifying Brazilian companies according to the concepts of Industry 4.0. To do so, research was carried out on the websites of automotive companies affiliated with Anfavea (Brazilian Association of Motor Vehicle Manufacturers), using the ElasticSearch software. This tool allows scanning large textual databases, including websites. The search found 137,382 occurrences in documents belonging to the companies’ websites. To develop the classification, principal component analysis was used, by limiting it to two components, which together explain 90.98% of the total variation. The components are named tools and innovations; using this, data was divided into quadrants represented by the x and y axes of the chart. The first quadrant is considered “low in tools (y) and low in innovations (x)”, where 12 companies were classified, with highlights being Renault and Ford. In the second quadrant, “low in tools and high in innovations (x)”, only the company Komatsu was classified. In the third quadrant, companies that have “high classification” were classified as “high tools” and “high in innovations”, represent by Volkswagen, Stellantis, and Scania. In the fourth quadrant, companies were classified as on-highway and Volvo, with high use of innovations and low use of Industry 4.0 tools.

Keywords: 4th Industrial Revolution; Artificial Intelligence; Internet of Things; Advanced automation; Automotive companies (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s43069-025-00552-8

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