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Hier finden Sie von Know-Center MitarbeiterInnen verfasste wissenschaftliche Publikationen

2019

Breitfuß Gert, Fruhwirth Michael, Pammer-Schindler Viktoria, Stern Hermann, Dennerlein Sebastian

The Data-Driven Business Value Matrix - A Classification Scheme for Data-Driven Business Models

32nd Bled eConference, University of Maribor, Faculty of Organizational Sciences, HUMANIZING TECHNOLOGY FOR A SUSTAINABLE SOCIETY JUNE 16 – 19, 2019, BLED, SLOVENIA,, Andreja Pucihar, PhD, et al., University of Maribor Press, Bled, Slovenia, 2019

Konferenz
Increasing digitization is generating more and more data in all areas ofbusiness. Modern analytical methods open up these large amounts of data forbusiness value creation. Expected business value ranges from process optimizationsuch as reduction of maintenance work and strategic decision support to businessmodel innovation. In the development of a data-driven business model, it is usefulto conceptualise elements of data-driven business models in order to differentiateand compare between examples of a data-driven business model and to think ofopportunities for using data to innovate an existing or design a new businessmodel. The goal of this paper is to identify a conceptual tool that supports datadrivenbusiness model innovation in a similar manner: We applied three existingclassification schemes to differentiate between data-driven business models basedon 30 examples for data-driven business model innovations. Subsequently, wepresent the strength and weaknesses of every scheme to identify possible blindspots for gaining business value out of data-driven activities. Following thisdiscussion, we outline a new classification scheme. The newly developed schemecombines all positive aspects from the three analysed classification models andresolves the identified weaknesses.
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