Hochstrasser Carina, Herburger Michael, Plasch Michael, Lackner Ulrike, Breitfuß Gert
2022
Kurzfristige Störungen und langfristige Veränderungen führen zunehmend zu Störungen in der interorganisatorischen Logistik. Daher müssen widerstandsfähige Strukturen aufgebaut und durch datengestützte Entscheidungen überwacht werden. Da es im aktuellen Geschäftsumfeld jedoch nicht ausreicht, eigene Informations- und Datensätze zu generieren und zu verarbeiten, müssen Datenaustauschkonzepte wie Datenkreise entwickelt werden. Ziel dieses Beitrags ist es, die Bedürfnisse und Anforderungen der Stakeholder an einen Datenkreis in den Anwendungsbereichen Logistik und Resilienz zu untersuchen. Zu diesem Zweck wurde ein Mixed-Methods-Ansatz durchgeführt, der eine Stakeholder-Analyse und die Entwicklung von Anwendungsfällen mittels qualitativer (Workshops und Experteninterviews) und quantitativer (Online-Befragung) Methoden umfasst.
Breitfuß Gert, Disch Leonie, Santa Maria Gonzalez Tomas
2022
The present paper aims to validate commonly used business analysis methods to obtain input for an early phase business model regarding feasibility, desirability, and viability. The research applies a case study approach, exploring the early-phase development of an economically sustainable business model for an open science discovery platform.
Martin Ebel, Santa Maria Gonzalez Tomas, Breitfuß Gert
2022
Business model patterns are a common tool in business model design. We provide a theoretical foundation for their use within the framework of analogical reasoning as an important cognitive skill for business model innovation. Based on 12 innovation workshops with students and practitioners, we discuss scenarios of pattern card utilization and provide insights on its evaluation.Martin Ebel, Tomas Santa Maria Gert Breitfuss PUBLISHED
Dumouchel Suzane, Blotiere Emilie, Breitfuß Gert, Chen Yin, Di Donato Francesca, Eskevich Maria, Forbes Paula, Georgiadis Haris, Gingold Arnaud, Gorgaini Elisa, Morainville Yoann, de Paoli Stefano, Petitfils Clara, Pohle Stefanie, Toth-Czifra Erzebeth
2020
Social sciences and humanities (SSH) research is divided across a wide array of disciplines, sub-disciplines and languages. While this specialisation makes it possible to investigate the extensive variety of SSH topics, it also leads to a fragmentation that prevents SSH research from reaching its full potential. The TRIPLE project brings answers to these issues by developing an innovative discovery platform for SSH data, researchers’ projects and profiles. Having started in October 2019, the project has already three main achievements that are presented in this paper: 1) the definition of main features of the GOTRIPLE platform; 2) its interoperability; 3) its multilingual, multicultural and interdisciplinary vocation. These results have been achieved thanks to different methodologies such as a co-design process, market analysis and benchmarking, monitoring and co-building. These preliminary results highlight the need of respecting diversity of practices and communities through coordination and harmonisation.
Breitfuß Gert, Fruhwirth Michael, Wolf-Brenner Christof, Riedl Angelika, Ginthör Robert, Pimas Oliver
2020
In the future, every successful company must have a clear idea of what data means to it. The necessary transformation to a data-driven company places high demands on companies and challenges management, organization and individual employees. In order to generate concrete added value from data, the collaboration of different disciplines e.g. data scientists, domain experts and business people is necessary. So far few tools are available which facilitate the creativity and co-creation process amongst teams with different backgrounds. The goal of this paper is to design and develop a hands-on and easy to use card-based tool for the generation of data service ideas that supports the required interdisciplinary cooperation. By using a Design Science Research approach we analysed 122 data service ideas and developed an innovation tool consisting of 38 cards. The first evaluation results show that the developed Data Service Cards are both perceived as helpful and easy to use.
Fruhwirth Michael, Breitfuß Gert, Pammer-Schindler Viktoria
2020
The availability of data sources and advances in analytics and artificial intelligence offers the opportunity for organizationsto develop new data-driven products, services and business models. Though, this process is challenging for traditionalorganizations, as it requires knowledge and collaboration from several disciplines such as data science, domain experts, orbusiness perspective. Furthermore, it is challenging to craft a meaningful value proposition based on data; whereas existingresearch can provide little guidance. To overcome those challenges, we conducted a Design Science Research project toderive requirements from literature and a case study, develop a collaborative visual tool and evaluate it through severalworkshops with traditional organizations. This paper presents the Data Product Canvas, a tool connecting data sources withthe user challenges and wishes through several intermediate steps. Thus, this paper contributes to the scientific body ofknowledge on developing data-driven business models, products and services.
Dumouchel Suzanne, Blotiere Emilie, Barbot Laure, Breitfuß Gert, Chen Yin, Di Donato Francesca, Forbes Paula, Petifils Clara, Pohle Stefanie
2020
SSH research is divided across a wide array of disciplines, sub-disciplines, and languages. While this specialisation makes it possible to investigate the extensive variety of SSH topics, it also leads to a fragmentation that prevents SSH research from reaching its full potential. Use and reuse of SSH research is suboptimal, interdisciplinary collaboration possibilities are often missed partially because of missing standards and referential keys between disciplines. By the way the reuse of data may paradoxically complicate a relevant sorting and a trust relationship. As a result, societal, economic and academic impacts are limited. Conceptually, there is a wealth of transdisciplinary collaborations, but in practice there is a need to help SSH researchers and research institutions to connect them and support them, to prepare the research data for these overarching approaches and to make them findable and usable. The TRIPLE (Targeting Researchers through Innovative Practices and Linked Exploration) project is a practical answer to the above issues, as it aims at designing and developing the European discovery platform dedicated to SSH resources. Funded under the European Commission program INFRAEOSC-02-2019 “Prototyping new innovative services”, thanks to a consortium of 18 partners, TRIPLE will develop a full multilingual and multicultural solution for the discovery and the reuse of SSH resources. The project started in October 2019 for a duration of 42 months thanks to European funding of 5.6 million €.
Lassnig Markus, Stabauer Petra, Breitfuß Gert, Müller Julian
2019
Zahlreiche Forschungsergebnisse im Bereich Geschäftsmodellinnovationen haben gezeigt, dass über 90 Prozent aller Geschäftsmodelle der letzten 50 Jahre aus einer Rekombination von bestehenden Konzepten entstanden sind. Grundsätzlich gilt das auch für digitale Geschäftsmodellinnovationen. Angesichts der Breite potenzieller digitaler Geschäftsmodellinnovationen wollten die Autoren wissen, welche Modellmuster in der wirtschaftlichen Praxis welche Bedeutung haben. Deshalb wurde die digitale Transformation mit neuen Geschäftsmodellen in einer empirischen Studie basierend auf qualitativen Interviews mit 68 Unternehmen untersucht. Dabei wurden sieben geeignete Geschäftsmodellmuster identifiziert, bezüglich ihres Disruptionspotenzials von evolutionär bis revolutionär klassifiziert und der Realisierungsgrad in den Unternehmen analysiert.Die stark komprimierte Conclusio lautet, dass das Thema Geschäftsmodellinnovationen durch Industrie 4.0 und digitale Transformation bei den Unternehmen angekommen ist. Es gibt jedoch sehr unterschiedliche Geschwindigkeiten in der Umsetzung und im Neuheitsgrad der Geschäftsmodellideen. Die schrittweise Weiterentwicklung von Geschäftsmodellen (evolutionär) wird von den meisten Unternehmen bevorzugt, da hier die grundsätzliche Art und Weise des Leistungsangebots bestehen bleibt. Im Gegensatz dazu gibt es aber auch Unternehmen, die bereits radikale Änderungen vornehmen, die die gesamte Geschäftslogik betreffen (revolutionäre Geschäftsmodellinnovationen). Entsprechend wird im vorliegenden Artikel ein Clustering von Geschäftsmodellinnovatoren vorgenommen – von Hesitator über Follower über Optimizer bis zu Leader in Geschäftsmodellinnovationen.
Breitfuß Gert, Berger Martin, Doerrzapf Linda
2019
The Austrian Federal Ministry for Transport, Innovation and Technology created an initiative to fund the setup and operation of Living Labs to provide a vital innovation ecosystem for mobility and transport. Five Urban Mobility Labs (UML) located in four urban areas have been selected for funding (duration 4 years) and started operation in 2017. In order to cover the risk of a high dependency of public funding (which is mostly limited in time), the lab management teams face the challenge to develop a viable and future-proof UML Business Model. The overall research goal of this paper is to get empirical insights on how a UML Business Model evolves on a long-term perspective and which success factors play a role. To answer the research question, a method mix of desk research and qualitative methods have been selected. In order to get an insight into the UML Business Model, two circles of 10 semi-structured interviews (two responsible persons of each UML) are planned. The first circle of the interviews took place between July 2018 and January 2019. The second circle of interviews is planned for 2020. Between the two rounds of the survey, a Business Model workshop is planned to share and create ideas for future Business Model developments. Based on the gained research insights a comprehensive list of success factors and hands-on recommendations will be derived. This should help UML organizations in developing a viable Business Model in order to support sustainable innovations in transport and mobility.
Fruhwirth Michael, Breitfuß Gert, Müller Christiana
2019
Die Nutzung von Daten in Unternehmen zur Analyse und Beantwortung vielfältiger Fragestellungen ist “daily business”. Es steckt aber noch viel mehr Potenzial in Daten abseits von Prozessoptimierungen und Business Intelligence Anwendungen. Der vorliegende Beitrag gibt einen Überblick über die wichtigsten Aspekte bei der Transformation von Daten in Wert bzw. bei der Entwicklung datengetriebener Geschäftsmodelle. Dabei werden die Charakteristika von datengetriebenen Geschäftsmodellen und die benötigten Kompetenzen näher beleuchtet. Vier Fallbeispiele österreichischer Unternehmen geben Einblicke in die Praxis und abschließend werden aktuelle Herausforderungen und Entwicklungen diskutiert.
Breitfuß Gert, Fruhwirth Michael, Pammer-Schindler Viktoria, Stern Hermann, Dennerlein Sebastian
2019
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.
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
2018
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.
Fruhwirth Michael, Breitfuß Gert, Pammer-Schindler Viktoria
2018
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
Cuder Gerald, Breitfuß Gert, Kern Roman
2018
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.
Lassnig Markus, Stabauer Petra, Breitfuß Gert, Mauthner Katrin
2018
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
Breitfuß Gert, Berger Martin, Doerrzapf Linda
2018
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.
Breitfuß Gert, Kaiser Rene_DB, Kern Roman, Kowald Dominik, Lex Elisabeth, Pammer-Schindler Viktoria, Veas Eduardo Enrique
2017
Proceedings of the Workshop Papers of i-Know 2017, co-located with International Conference on Knowledge Technologies and Data-Driven Business 2017 (i-Know 2017), Graz, Austria, October 11-12, 2017.
Stabauer Petra, Breitfuß Gert, Lassnig Markus
2017
Nowadays digitalization is on everyone’s mind and affecting all areas of life. The rapid development of information technology and the increasing pervasiveness of digitalization represent new challenges to the business world. The emergence of the so-called fourth industrial revolution and the Internet of Things (IoT) confronts existing firms with changes in numerous aspects of doing business. Not only information and communication technologies are changing production processes through increasing automation. Digitalization can affect products and services itself. This could lead to major changes in a company’s value chain and as a consequence affects the company’s business model. In the age of digitalization, it is no longer sufficient to change single aspects of a firm’s business strategy, the business model itself needs to be the subject of innovation. This paper presents how digitalization affects business models of well-established companies in Austria. The results are demonstrated by means of two best practice case studies. The case studies were identified within an empirical research study funded by the Austrian Ministry for Transport, Innovation and Technology (BMVIT). The selected best practice cases presents how digitalization affects a firm’s business model and demonstrates the transformation of the value creation process by simultaneously contributing to sustainable development.
de Reuver Mark, Tarkus Astrid, Haaker Timber, Breitfuß Gert, Roelfsema Melissa, Kosman Ruud, Heikkilä Marikka
2017
In this paper, we present two design cycles for an online platform with ICT-enabled tooling that supports business model innovation by SMEs. The platform connects the needs of the SMEs regarding BMI with tools that can help to solve those needs and questions. The needs are derived from our earlier case study work (Heikkilä et al. 2016), showing typical BMI patterns of the SMEs needs - labelled as ‘I want to’s - about what an entrepreneur wants to achieve with business model innovation. The platform provides sets of integrated tools that can answer the typical ‘I want to’ questions that SMEs have with innovating their business models.
Stern Hermann, Dennerlein Sebastian, Pammer-Schindler Viktoria, Ginthör Robert, Breitfuß Gert
2017
To specify the current understanding of business models in the realm of Big Data, we used a qualitative approach analysing 25 Big Data projects spread over the domains of Retail, Energy, Production, and Life Sciences, and various company types (SME, group, start-up, etc.). All projects have been conducted in the last two years at Austria’s competence center for Data-driven Business and Big Data Analytics, the Know-Center.