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Capturing Value from Data: Exploring Factors Influencing Revenue Model Design for Data-Driven Services

Enders, Tobias; Schüritz, Ronny; Frey, Wiebke

Abstract:
In recent years organizations have started utilizing big data and advanced analytics not just to support decision-making to raise process efficiencies, but also to engage in new data-driven services. These data-driven services complement the current product and service portfolio and create additional value for customers. In order to capture the value created, organizations need to design sustainable revenue models consisting of a revenue (how) and pricing (how much) mechanism. In order to develop a deeper understanding of one part of the decision-making process on revenue models, we apply a qualitative study and analyze the results through the lens of rational choice theory. Based on the interviews, we derived four factors – service characteristics, provider interests, customer interests, and market factors - influencing the design. By this, we contribute to the general understanding of the design of revenue models and enable further investigation into this field of research.


Zugehörige Institution(en) am KIT Karlsruhe Service Research Institute (KSRI)
Publikationstyp Proceedingsbeitrag
Jahr 2019
Sprache Englisch
Identifikator KITopen-ID: 1000091819
Erschienen in Proceedings of 14th International Conference on Wirtschaftsinformatik (Wi 2019): Human Practice.Digital Ecologies.Our Future.
Veranstaltung 14. Internationale Tagung Wirtschaftsinformatik (WI 2019), Siegen, Deutschland, 23.02.2019 – 27.02.2019
Schlagworte big data, business model, revenue model, revenue mechanism
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