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Business Analytics & Datengetriebene Organisationen

Übersicht

Wie müssen Unternehmen ihre Prozesse, Entscheidungsstrukturen und Geschäftsmodelle anpassen, um mit Business Analytics, Data Science und Machine Learning Wettbewerbsvorteile aufzubauen? Wir untersuchen wie Unternehmen die datengetriebene Transformation bewerkstelligen und wie dieser Prozess erfolgreich gemanaged werden kann.


Schwerpunkte

  • Aufbau und Gestaltung datengetriebener Organisationen
  • Gestaltungen datenbasierter Innovationen und Geschäftsprozesse und -modelle
  • Implementierung von Business Analytics in Unternehmen
  • Datenkompetenzen für Manager
  • Akzeptanz und wirtschaftlicher Nutzen von Business Analytics, Data Science, und künstlicher Intelligenz
  • Validität und Fairness algorithmischer Entscheidungen
  • Daten- und API-basierte Geschäftsmodelle zur Monetarisierung von Daten
  • Messung des Wertes von Daten

Projekte

Learning Algorithms for Discrimination Free Innovation Funding Activities

The goal of the project is to evaluate the extent to which investment algorithms in new venture funding discriminate women entrepreneurs as well as the effectiveness of approaches to debiasing algorithms.

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Procurement Intelligence: Data-driven total cost and resilience optimization for purchasing

Efforts to contain the spread of COVID-19 have kickstarted an economic crisis throwing off the balance of international supply chains. Swiss companies seeking to remain globally competitive will find themselves between conflicting priorities of resilience enhancement and cost reduction. Purchasers from various industries face increasingly complex decisions (e.g. supplier selection, make-or-buy, etc.) under aspects of value contributions, incl. risk, compliance, and sustainability issues.

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Publikationen

Telemedicine services may improve the quality of life of individuals while also reducing the costs of service provisioning. They represent an important but as yet understudied type of complex services that integrates many stakeholders acting in service value networks. These complex services typically comprise a combination of information technology (IT) services and highly person-oriented, non-IT services, and are characterized by long service delivery periods. In such an environment, it is particularly difficult to generate successful and sustainable business models, which are necessary for the widespread provision of telemedicine services. Following a design research approach, we develop and evaluate the CompBizMod framework, a morphological box allowing for: (1) the analysis, description, and classification of telemedicine business models, (2) the identification of white spots for future business opportunities, (3) and the identification of patterns for successful business models. We contribute to the literature by presenting a specific business model framework and identifying three business model patterns in the telemedicine industry. We exhibit how business models for complex services can be decomposed into their constituent elements and present an easy and replicable approach for identifying business model patterns in a given industry.

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