Author:
Stahl Bastian,Häckel Björn,Leuthe Daniel,Ritter Christian
Abstract
AbstractDriven by digital technologies, manufacturers aim to tap into data-driven business models, in which value is generated from data as a complement to physical products. However, this transformation can be complex, as different archetypes of data-driven business models require substantially different business and technical capabilities. While there are manifold contributions to research on technical capability development, an integrated and aligned perspective on both business and technology capabilities for distinct data-driven business model archetypes is needed. This perspective promises to enhance research’s understanding of this transformation and offers guidance for practitioners. As maturity models have proven to be valuable tools in capability development, we follow a design science approach to develop a maturity model for the transformation toward archetypal data-driven business models. To provide an integrated perspective on business and technology capabilities, the maturity model leverages a layered enterprise architecture model. By applying and evaluating in use at two manufacturers, we find two different transformation approaches, namely ‘data first’ and ‘business first’. The resulting insights highlight the model’s integrative perspective’s value for research to improve the understanding of this transformation. For practitioners, the maturity model allows a status quo assessment and derives fields of action to develop the capabilities required for the aspired data-driven business model.
Publisher
Springer Science and Business Media LLC
Subject
Management of Technology and Innovation,General Economics, Econometrics and Finance,General Business, Management and Accounting
Reference116 articles.
1. Appelbaum, Steven H. 1997. Socio-technical systems theory: an intervention strategy for organizational development. Management Decision 35(6):452–463. https://doi.org/10.1108/00251749710173823.
2. Astill, Jake, Rozita A. Dara, Malcolm Campbell, Jeffrey M. Farber, Evan D. Fraser, Shayan Sharif, and Rickey Y. Yada. 2019. Transparency in food supply chains: A review of enabling technology solutions. Trends in Food Science & Technology 91:240–247. https://doi.org/10.1016/j.tifs.2019.07.024.
3. Azkan, Can, Lennart Iggena, Frederik Möller, and Boris Otto. 2021. Towards design principles for data-driven services in industrial environments. In Proceedings of the 54th Hawaii International Conference on System Sciences, ed. Tung Bui
4. Baltuttis, Dennik, Björn Häckel, Claudius M. Jonas, Anna M. Oberländer, Maximilian Röglinger, and Johannes Seyfried. 2022. Conceptualizing and assessing the value of Internet of things solutions. Journal of Business Research 140:245–263. https://doi.org/10.1016/j.jbusres.2021.10.063.
5. Baskerville, Richard, Abayomi Baiyere, Shirley Gregor, Alan Hevner, and Matti Rossi. 2018. Design science research contributions: Finding a balance between artifact and theory. Journal of the Association for Information Systems 19(5):358–376. https://doi.org/10.17705/1jais.00495.
Cited by
4 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献