A Reference Model for Data-driven Business Model Innovation Initiatives in Incumbent Firms

Publikation: Beiträge in SammelwerkenAufsätze in KonferenzbändenForschungbegutachtet


In the past decade, we have witnessed the rise of big data analytics to a well-established phenomenon in business and academic fields. Novel opportunities appear for organizations to maximize the value from data through improved decision making, enhanced value propositions and new business models. The latter two are investigated by scholars as part of an emerging research field of data-driven business model (DDBM) innovation. Aiming to deploy DDBM innovation, companies start initiatives to either renovate their existing BM or develop a new DDBM. Responding to the recent calls for further research on design knowledge for DDBM innovation, we developed a reference model for DDBM innovation initiatives. Building upon a design science research approach and the Work System Theory as a kernel theory and a set of design principles, we propose a reference model comprising a static and a dynamic view. Our results are based on a research study with empirical insights from 18 companies, 19 cases and 16 expert interviews as well as theoretical grounding from a systematic literature research on key concepts of DDBM innovation. The developed reference model fills a gap mentioned in the DDBM innovation literature and provides practical guidance for companies.
TitelECIS 2022 proceedings
Anzahl der Seiten15
VerlagAIS eLibrary
ISBN (elektronisch)978-1-958200-02-5
PublikationsstatusErschienen - 2022
Veranstaltung30th European Conference on Information Systems - ECIS 2022: New horizons in digitally united societies - West University of Timisoara, Timisoara, Rumänien
Dauer: 18.06.202224.06.2022
Konferenznummer: 30


  • Wirtschaftsinformatik - Chatbots, Conversational Agents, Education, Learning, Literature Review, Pedagogical Conversational Agents