Prerequisites and Causal Recipes for Manufacturers’ IT-Enabled Service Innovation Success

For manufacturing firms, success in innovating IT-enabled services is a critical antecedent to benefiting from the digital servitization of their business models. Digital servitization literature has explored mechanisms for success in innovating IT-enabled services, indicating that the phenomenon is...

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Veröffentlicht in:Communications of the Association for Information Systems 2024, Vol.55 (1), p.205-256
Hauptverfasser: Brosig, Christoph, Gräubig, Dix M., Strahringer, Susanne, Westner, Markus
Format: Artikel
Sprache:eng
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Zusammenfassung:For manufacturing firms, success in innovating IT-enabled services is a critical antecedent to benefiting from the digital servitization of their business models. Digital servitization literature has explored mechanisms for success in innovating IT-enabled services, indicating that the phenomenon is multifaceted and needs to be explained from multiple theoretical perspectives. We derive a conceptual model for success in innovating IT-enabled services covering its multifaceted nature by referring to knowledge-based and organizational control theory. We test this model using qualitative cases of IT-enabled service innovation initiatives in manufacturing firms and use set-theoretic analyses to account for the multifaceted nature of the phenomenon. The necessary condition analysis yields that a certain degree of service innovation capabilities is a prerequisite for success. With the results of a qualitative comparative analysis, we obtain five solution terms as causal recipes for success in innovating IT-enabled services. Our results contribute to research by offering a theory-based approach that explains the multiplicity of success in IT-enabled service innovation. Practitioners benefit from our results by understanding prerequisites and causal recipes for success while learning from unsuccessful initiatives in innovating IT-enabled services of manufacturing firms. Our study is also an example of how to rigorously calibrate qualitative data using a structured approach.
ISSN:1529-3181
1529-3181
DOI:10.17705/1CAIS.05509