Business Model Innovation in Manufacturing Firms: Exploring the Driving Forces of Digital Transformation

Yannick A. Mies and J. Piet Hausberg
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Yannick A. Mies: Department of Technology and Innovation Management, University of Osnabrueck, Rolandstraße 8, 49078 Osnabrueck, Germany
J. Piet Hausberg: Department of Technology and Innovation Management, University of Osnabrueck, Rolandstraße 8, 49078 Osnabrueck, Germany†Cassini Consulting AG. Bennigsen-Platz, 140474 Düsseldorf, Germany

International Journal of Innovation and Technology Management (IJITM), 2023, vol. 20, issue 07, 1-27

Abstract: The adoption of digital technology has become a critical factor in the context of innovation management. The process of digital transformation leads to the realization of concrete business improvements that promote the innovation of entire business models. So far, it has remained unexplored what drives this business model innovation, especially when looking at digitally savvy firms from the manufacturing industry. This study aims to identify the key drivers of digital transformation of business models based on a systematic literature review. A four-step review approach draws on the findings from a core sample of 51 articles from two databases and results in the description of four key drivers for digital transformation of business models, namely ubiquitous connectivity, functional dematerialization, relational decentralization, and flexible scalability. Finally, a conceptual framework of four digital business model archetypes (lighthouse supplier, service enthusiast, data scientist, and platform owner) is proposed that considers a manufacturing firm’s business model exposure to the identified digital transformation drivers. While this study is limited to theoretical findings, it likewise provokes valuable follow-up thoughts for empirical academic work and practitioners from the manufacturing industries.

Keywords: Business model innovation; digital transformation; systematic literature review (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1142/S0219877023500487

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