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Data-Driven Business Models from an Internal Automotive OEM Perspective: Categories and Challenges

In: Digital Innovation and Organizational Transformation

Author

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  • Norbert Michael Homner

    (Friedrich-Alexander Universität Erlangen-Nürnberg, Digital Industrial Service Systems)

Abstract

The automotive industry is undergoing a profound shift driven by digitalization, prompting the emergence of data-driven business models (DDBMs). As the original equipment manufacturers (OEMs) have already realised a number of DDBMs, their role in the traditional automotive industry is of great interest. This study investigates DDBMs within the European automotive sector, addressing two key objectives: a categorization of existing internal OEM DDBMs and internal OEM challenges. Interviews were made with sixteen automotive experts from four OEMs and two OEM suppliers, working in DDBM-related departments. Hence, five internal OEM DDBM categories were identified: Technical, Product Optimization, Marketing Analysis, Selling Raw Data, and Customer Services. The seven detected challenges that hinder DDBM development include legal constraints, technical complexities, organizational culture, and data knowledge gaps. These findings were guided by theoretical contributions to DDBMs in Information Systems (IS) and practical contributions such as DDBM advices for OEMs.

Suggested Citation

  • Norbert Michael Homner, 2026. "Data-Driven Business Models from an Internal Automotive OEM Perspective: Categories and Challenges," Lecture Notes in Information Systems and Organization, in: Christoph M. Flath & Gunther Gust & Frédéric Thiesse & Axel Winkelmann (ed.), Digital Innovation and Organizational Transformation, pages 155-170, Springer.
    • Handle: RePEc:spr:lnichp:978-3-032-08483-5_11
    DOI: 10.1007/978-3-032-08483-5_11
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