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Institut für Wirtschaftsinformatik

Universität St.Gallen (HSG)

Das Institut für Wirtschaftsinformatik (IWI-HSG) ist mit seinen fünf Lehrstühlen eines der grössten Institute der Universität St.Gallen. Seit mehr als 30 Jahren forschen wir zu Geschäftsmodellen und der Anwendung digitaler Technologien.

Forschung

Mit dem St Galler House of Digital Business verfolgt das IWI einen ganzheitlichen Ansatz zur Strukturierung der Digitalisierung in Unternehmen. Wir sind in Forschung und Praxis international bestens vernetzt. Als eines der führenden Institute der Wirtschaftsinformatik in Europa stehen wir für hoch relevante Themen, von der Grundlagenforschung über angewandte Forschung bis hin zu Transfer und Weiterbildung.

Lehre

Neben der Forschung macht die Lehre einen wesentlichen Bestandteil unseres Engagements aus: Die Lehrveranstaltungen, die von unseren Dozierenden angeboten werden, sind für alle Studiengänge der School of Management von grosser Bedeutung. Der Erfolg unseres akademischen Nachwuchses steht für unsere Forschungs- und Lehrleistung.

Weiterbildung

Dem IWI-HSG angegliedert ist der Nachdiplomstudiengang Executive Master in Business Engineering (EMBE HSG), der CAS HSG Big Data and Artificial Intelligence for Managers, CAS Digital Innovation & Business Transformation, sowie das Executive Diploma HSG IT Business Management.

Lehre & Master in Business Innovation (MBI)

Das IWI-HSG bietet verschiedene Kurse auf Bachelor-, Master- und Doktorats-Stufe an und betreut das Master-Programm in Business Innovation (MBI)

Events

Research Talk Dr. Monika Malinova Mandelburger (WU Wien)

26. April 2021

Standort: Via Zoom, Müller-Friedberg-Strasse 8, St. Gallen

Datum: 26.04.2021, 11:00

Dr. Monika Malinova Mandelburger “Cognitive diagram understanding and task performance in systems analysis and design”

Diagrams play an important role in Systems Analysis and Design (SAD). So far, cognitive research on diagram criteria in relation to task performance has been fragmented. The aim of this talk is to (1) discuss the cognitive processing steps involved during understanding and task performance with diagrams, (2) discuss criteria for such diagrams to best support cognitive processing and (3) demonstrate the support effective diagrams provide for performing SAD tasks. First, we present a theoretical cognitive framework of task performance with diagrams called CogniDia. It integrates different cognitive theories from research on diagrams in software engineering and information systems. Second, we present findings from a literature review on criteria for effective cognitive processing of diagrams. Third, we use the theoretical cognitive framework CogniDia to investigate how diagrams support the SAD process effectively.

Monika Malinova is a postdoctoral researcher with the Institute for Information Business at the Vienna University of Economics and Business (WU Vienna), Austria. She obtained her PhD degree in 2016 from WU Vienna. Her PhD thesis was awarded the Dr. Maria Schaumayer award for an excellent dissertation of 2016.  In 2015 Monika was awarded the Internationalization Program Scholarship from the Dr. Maria Schaumayer Foundation. Since January 2018 Monika is a Hertha Firnberg Fellow funded by the FWF Austrian Science Fund. The Hertha Firnberg is a program offered to highly qualified female scientists who are working towards a career in universities. Monika’s research interests include business process management, process innovation, and conceptual modeling. Her research has been published in MIS Quarterly, BPMJ, ICIS and ECIS, among others.

Research Talk Dominik Gutt

6. May 2021

Standort: Universität St. Gallen, Dufourstrasse 50, 9000 St. Gallen

Dominik Gutt,  Assistant Professor at Rotterdam School of Management; “The Rise of Robo-Reviews – The Effects of Chatbot-Mediated Review Elicitation on Online Reviews”

Chatbots have been introduced as a new way to receive product reviews. However, little is known how the chatbot-mediated solicitation influences review characteristics such as the valence or the helpfulness. We conduct four studies to narrow this literature gap. Our results show that (1) chatbot-mediated review elicitation leads to a positivity bias in ratings, particularly strong for low-quality products; (2) chatbot-mediated reviews negatively impact a range of review dimensions (e.g., helpfulness) mainly due to decreased review length, (3) the positivity bias varies depending on the level of anthropomorphism in the chatbot and the nature of the survey deployer (seller vs. platform), and can be explained by audience tuning due to social presence. Our research is among the first to uncover a link between chatbot use, review valence, and other valuable review