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

Norbert Michael Homner ()
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Norbert Michael Homner: Friedrich-Alexander Universität Erlangen-Nürnberg, Digital Industrial Service Systems

A chapter in Digital Innovation and Organizational Transformation, 2026, pp 155-170 from Springer

Abstract: 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.

Keywords: Data-driven business models; Automotive industry; Interview series; Market-based view (search for similar items in EconPapers)
Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:spr:lnichp:978-3-032-08483-5_11

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DOI: 10.1007/978-3-032-08483-5_11

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