Publikationen

Hier finden Sie von Know-Center MitarbeiterInnen verfasste wissenschaftliche Publikationen

2018

Iacopo Vagliano, Franziska Günther, Mathias Heinz, Aitor Apaolaza, Irina Bienia, Breitfuß Gert, Till Blume, Chrysa Collyda, Fessl Angela, Sebastian Gottfried, Hasitschka Peter, Jasmin Kellermann, Thomas Köhler, Annalouise Maas, Vasileios Mezaris, Ahmed Saleh, Andrzej Skulimowski, Thalmann_TU Stefan, Markel Vigo, Wertner Alfred, Michael Wiese, Ansgar Scherp

Open Innovation in the Big Data Era with the MOVING Platform: An Integrated Working and Training Approach for Data-savvy Information Professionals

IEEE Mulitmedia, IEEE, 2018

Journal
In the Big Data era, people can access vast amounts of information, but often lack the time, strategies and tools to efficiently extract the necessary knowledge from it. Research and innovation staff needs to effectively obtain an overview of publications, patents, funding opportunities, etc., to derive an innovation strategy. The MOVING platform enables its users to improve their information literacy by training how to exploit data mining methods in their daily research tasks. Through a novel integrated working and training environment, the platform supports the education of data-savvy information professionals and enables them to deal with the challenges of Big Data and open innovation.
2018

Fruhwirth Michael, Breitfuß Gert, Pammer-Schindler Viktoria

Exploring challenges in data-driven business model innovation from Austrian enterprises

Proceedings in XXIX ISPIM Innovation Conference, Stockholm, 2018

Konferenz
The increasing amount of generated data and advances in technology and data analytics and are enablers and drivers for new business models with data as a key resource. Currently established organisations struggle with identifying the value and benefits of data and have a lack of know-how, how to develop new products and services based on data. There is very little research that is narrowly focused on data-driven business model innovation in established organisations. The aim of this research is to investigate existing activities within Austrians enterprises with regard to exploring data-driven business models and challenges encountered in this endeavour. The outcome of the research in progress paper are categories of challenges related to organisation, business and technology, established organisations in Austria face during data-driven business model innovation
2018

Cuder Gerald, Breitfuß Gert, Kern Roman

E-Mobility and Big Data - Data Utilization of Charging Operations

Proceedings of XXIX ISPIM Conference, Stockholm, 2018

Konferenz
Electric vehicles have enjoyed a substantial growth in recent years. One essential part to ensure their success in the future is a well-developed and easy-to-use charging infrastructure. Since charging stations generate a lot of (big) data, gaining useful information out of this data can help to push the transition to E-Mobility. In a joint research project, the Know-Center, together with the has.to.be GmbH applied data analytics methods and visualization technologies on the provided data sets. One objective of the research project is, to provide a consumption forecast based on the historical consumption data. Based on this information, the operators of charging stations are able to optimize the energy supply. Additionally, the infrastructure data were analysed with regard to "predictive maintenance", aiming to optimize the availability of the charging stations. Furthermore, advanced prediction algorithms were applied to provide services to the end user regarding availability of charging stations.
2018

Lassnig Markus, Stabauer Petra, Breitfuß Gert, Mauthner Katrin

Geschäftsmodellinnovationen im Zeitalter von Digitalisierung und Industrie 4.0

HMD Praxis der Wirtschaftsinformatik Wirtschaftsinformatik, Stefan Meinhard, Karl-Michael Popp, Springer Fachmedien Wiesbaden, Wiesbaden, 2018

Journal
Zahlreiche Forschungsergebnisse im Bereich Geschäftsmodellinnovationenhaben gezeigt, dass über 90% aller Geschäftsmodelle der letzten50 Jahre aus einer Rekombination von bestehenden Konzepten entstanden sind.Grundsätzlich gilt das auch für digitale Geschäftsmodellinnovationen. Angesichtsder Breite potenzieller digitaler Geschäftsmodellinnovationen wollten die Autorenwissen, welche Modellmuster in der wirtschaftlichen Praxis welche Bedeutung haben.Deshalb wurde die digitale Transformation mit neuen Geschäftsmodellen ineiner empirischen Studie basierend auf qualitativen Interviews mit 68 Unternehmenuntersucht. Dabei wurden sieben geeignete Geschäftsmodellmuster identifiziert, bezüglichihres Disruptionspotenzials von evolutionär bis revolutionär klassifiziert undder Realisierungsgrad in den Unternehmen analysiert.Die stark komprimierte Conclusio lautet, dass das Thema Geschäftsmodellinnovationendurch Industrie 4.0 und digitale Transformation bei den Unternehmenangekommen ist. Es gibt jedoch sehr unterschiedliche Geschwindigkeiten in der Umsetzungund im Neuheitsgrad der Geschäftsmodellideen. Die schrittweise Weiterentwicklungvon Geschäftsmodellen (evolutionär) wird von den meisten Unternehmenbevorzugt, da hier die grundsätzliche Art und Weise des Leistungsangebots bestehenbleibt. Im Gegensatz dazu gibt es aber auch Unternehmen, die bereits radikale Änderungenvornehmen, die die gesamte Geschäftslogik betreffen. Entsprechend wird imvorliegenden Artikel ein Clustering von Geschäftsmodellinnovatoren vorgenommen – von Hesitator über Follower über Optimizer bis zu Leader in Geschäftsmodellinnovationen
2018

Breitfuß Gert, Berger Martin, Doerrzapf Linda

Innovation Milieus for Mobility – Analysis of Innovation Lab Approaches for the Establishment of Urban Mobility Labs in Austria

TRA Vienna 2018 - Transport Research Arena, 2018

Konferenz
The initiative „Urban Mobility Labs“ (UML), driven by the Austrian Ministry of Transport, Innovation and Technology, was started to support the setup of innovative and experimental environments for research, testing, implementation and transfer of mobility solutions. This should happen by incorporating the scientific community, citizens and stakeholders in politics and administration as well as other groups. The emerging structural frame shall enhance the efficiency and effectivity of the innovation process. In this paper insights and in-depth analysis of the approaches and experiences gained in the eight UML exploratory projects will be outlined. These projects were analyzed, systematized and enriched with further considerations. Furthermore, their knowledge growth as user-centered innovation environments was documented during the exploratory phase.
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