Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/289513 
Erscheinungsjahr: 
2023
Quellenangabe: 
[Journal:] Schmalenbach Journal of Business Research (SBUR) [ISSN:] 2366-6153 [Volume:] 75 [Issue:] 3 [Year:] 2023 [Pages:] 303-343
Verlag: 
Springer, Heidelberg
Zusammenfassung: 
Driven 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.
Schlagwörter: 
Data analytics
Data-driven business models
Data-driven services
Enterprise architecture
Manufacturing
JEL: 
L60
O14
O32
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