Ubiquitous Personal Computing
Ubiquitous Personal Computing


Portrait of Viktoria Pammer-Schindler Kontakt send
Viktoria Pammer-Schindler Research Area Manager
Portrait of Hermann Stern Kontakt send
Hermann Stern Business Area Manager
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Understand and design for data-driven business from the perspectives of business models, technology-enhanced (organizational) learning and knowledge management.

Our goal is to understand practice together with technological tools in data-driven business, to design innovative, interactive and intelligent systems grounded in this understanding, and to evaluate the impact of novel technology on work practice, business processes, and overall business models.

Research Focus

Data-Driven Business Models – We aim to support the process of identifying data-driven business opportunities. We build tools and a framework for data-driven business innovation. In particular, we study and co-design data platforms and markets.

Data-Driven and Reflective Learning – We aim to innovate workplace learning with technology, to connect learning at different organizational levels. We explore the role of data within learning technologies, i.e. for learning analytics, reflection, and adaptive learning interventions.

Knowledge Sharing and Protection – We aim to examine the balance between sharing and protection of knowledge in intra-organisational collaboration. We develop concepts and tools that allow organisations to choose and enact their knowledge sharing policies in light of privacy, confidentiality and IPR considerations.


Selected results

  • Challenges in data-driven business model innovation

    We have interviewed companies who are in the process of implementing data-driven business model innovation processes. Challenges arise on the organisational, legal, and technological level. The crux in data-driven business business model innovation is that it requires interdisciplinary knowledge and collaboration.

  • Semi-Automatic Digital Workspace

    Many processes are defined by, or start with, a non-structured textual description. Examples are product specifications, or project contracts. We have co-designed with stakeholders a digital workspace that is initialised with a single document; and automatically pre-filled using natural language processing and textmining methods with applicable norms, regulations, templates, and results from similar processes. This speeds up the set-up time of knowledge workers, and supports compliance with complex, global, and fast-changing norms. The digital workspace also allows documentation of the ongoing process, thus filling an organisation’s knowledge base, and facilitates handover between different departments in a single organisational process.

  • Virtualising training

    In global environments, both in-house training and training of customers often requires extensive travel times, and inefficient face-2-face times. We are exploring and designing different virtual training and blended learning set-ups, and evaluating the impact on work and learning efficiency. Face-2-face training is more immersive, more interactive, and less prone to disruption than virtual training.

  • Learning from Experience

    We have explored data as basis for learning from experience via adaptive learning support. We have developed theory-inspired reflection interventions which have been integrated in multiple use cases, ranging from IT consulting to b2b call center work, and expert professional training in the medical domain. In the case of b2b call centers for instance, we could show that interactive, collaborative mood tracking facilitated peer and management support within the team, and could observe an increased customer satisfaction – a key performance indicator in call centers.

  • Challenges for learning in Industry 4.0

    We have explored the challenges for learning and knowledge management in Industry 4.0. There is a shared understanding that work in Industry 4.0 will increasingly be knowledge work; and industrial workforce will need in-situ live decision making and engaging, flexible learning support.

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