Applied Sciences (Apr 2024)

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

  • Shailesh Tripathi,
  • Nadine Bachmann,
  • Manuel Brunner,
  • Herbert Jodlbauer

DOI
https://doi.org/10.3390/app14083454
Journal volume & issue
Vol. 14, no. 8
p. 3454

Abstract

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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.

Keywords