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Mining the Automotive Industry: A Network Analysis of Corporate Positioning and Technological Trends

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  • Stoehr, Niklas
  • Braesemann, Fabian
  • Zhou, Shi

Abstract

The digital transformation is driving revolutionary innovations and new market entrants threaten established sectors of the economy such as the automotive industry. Following the need for monitoring shifting industries, we present a network-centred analysis of car manufacturer web pages. Solely exploiting publicly-available information, we con- struct large networks from web pages and hyperlinks. The network properties disclose the internal corporate positioning of the three largest automotive manufacturers, Toyota, Volkswagen and Hyundai with respect to innovative trends and their international outlook. We tag web pages concerned with topics like e-mobility & environment or autonomous driving, and investigate their relevance in the network. Toyota and Hyundai are concerned with e-mobility throughout large parts of their web page network; Volkswagen devotes more specialized sections to it, but reveals a strong focus on autonomous driving. Sentiment analysis on individual web pages uncovers a relationship between page linking and use of positive language, particularly with respect to innovative trends. Web pages of the same country domain form clusters of different size in the network that reveal strong correlations with sales market orientation. Our approach is highly transparent, reproducible and data driven, and could be used to gain complementary insights into innovative strategies of firms and competitive landscapes.

Suggested Citation

  • Stoehr, Niklas & Braesemann, Fabian & Zhou, Shi, 2019. "Mining the Automotive Industry: A Network Analysis of Corporate Positioning and Technological Trends," SocArXiv bu5zs_v1, Center for Open Science.
    • Handle: RePEc:osf:socarx:bu5zs_v1
    DOI: 10.31219/osf.io/bu5zs_v1
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    1. Adan Ortiz-Cordova & Bernard J. Jansen, 2012. "Classifying web search queries to identify high revenue generating customers," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(7), pages 1426-1441, July.
    2. Fabian Braesemann & Niklas Stoehr & Mark Graham, 2019. "Global networks in collaborative programming," Regional Studies, Regional Science, Taylor & Francis Journals, vol. 6(1), pages 371-373, January.
    3. Swaminathan, Anand & Hoetker, Glenn & Mitchell, Will, 2002. "Network Structure and Business Survival: The Case of U.S. Automobile Component Suppliers," Working Papers 02-0105, University of Illinois at Urbana-Champaign, College of Business.
    4. Adan Ortiz‐Cordova & Bernard J. Jansen, 2012. "Classifying web search queries to identify high revenue generating customers," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 63(7), pages 1426-1441, July.
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