Preparedness for Data-Driven Business Model Innovation: A Knowledge Framework for Incumbent Manufacturers

Author:

Tripathi Shailesh1ORCID,Bachmann Nadine12ORCID,Brunner Manuel13ORCID,Jodlbauer Herbert1ORCID

Affiliation:

1. Josef Ressel Centre for Data-Driven Business Model Innovation, University of Applied Sciences Upper Austria, Wehrgrabengasse 1–3, 4400 Steyr, Austria

2. Faculty of Behavioural, Management and Social Sciences, Entrepreneurship and Technology Management, University of Twente, Drienerlolaan 5, 7522 NB Enschede, The Netherlands

3. CRET-LOG—Centre de Recherche sur le Transport et la Logistique, Aix Marseille Université, Avenue Gaston Berger 413, F-13625 Aix-en-Provence, France

Abstract

This study investigates data-driven business model innovation (DDBMI) for incumbent manufacturers, underscoring its importance in various strategic and managerial contexts. Employing topic modeling, the study identifies nine key topics of DDBMI. Through qualitative thematic synthesis, these topics are further refined, interpreted, and categorized into three levels: Enablers, value creators, and outcomes. This categorization aims to assess incumbent manufacturers’ preparedness for DDBMI. Additionally, a knowledge framework is developed based on the identified nine key topics of DDBMI to aid incumbent manufacturers in enhancing their understanding of DDBMI, thereby facilitating the practical application and interpretation of data-driven approaches to business model innovation.

Funder

Austrian Federal Ministry for Digital and Economic Affairs

National Foundation for Research, Technology and Development

Christian Doppler Research Association

Publisher

MDPI AG

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