DIGITAL BUSINESS MODELS A LITERATURE-BASED TAXONOMY AND RESEARCH AVENUES

Bernd W. Wirtz, M. MÃœLLER Wilhelm and Paul F. Langer ()
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Bernd W. Wirtz: German University of Administrative Sciences Speyer, Germany
M. MÃœLLER Wilhelm: German University of Administrative Sciences Speyer, Germany
Paul F. Langer: German University of Administrative Sciences Speyer, Germany

International Journal of Innovation Management (ijim), 2023, vol. 27, issue 07n08, 1-76

Abstract: Digital technologies and connectivity offer unprecedented opportunities for businesses to adapt and reinvent themselves to gain and sustain competitive advantage. Digital transformation and business model innovation have generated a large body of research in recent years due to their great practical importance. This study critically evaluates this extensive literature and aims to capture different understandings of digital business models (DBMs), identify knowledge gaps and highlight perspectives for further research. To achieve this, the literature review deductively filters out the most relevant 626 studies. For this purpose, the literature is clustered into the areas of “definition and terminology†, “classification and taxonomy†, “technology†, “configuration, structures and processes†, “drivers and determinants†and “results and impacts†. The most important scientific results and approaches are discussed and corresponding implications are derived from previous research in order to summarise the most important findings and perspectives for science and practice.

Keywords: Digital transformation; change management; disruptive technologies; artificial intelligence; literature analysis; theoretical overview; research agenda (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1142/S1363919623300039

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