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Data-driven Service Design und Management

Was macht Google, Facebook & Co so erfolgreich? Sie verstehen es, Lücken in der Leistungserbringung existierender Geschäftsmodelle zu identifizieren und sie durch neue digitale Innovationen zu schliessen. In diesem Kontext spielen Service Innovation und Design eine immer grössere Rolle, da durch die fortschreitende Digitalisierung Kunden oft nicht allein ein Produkt, sondern auch die damit verbundenen ‑ zunehmend auch auf Daten basierenden ‑ Services erwerben. Die Verlagerung des Angebotsportfolios hin zu einer Kombination aus Produkten und Services, die sogenannte «Servitization», bietet Unternehmen die Möglichkeit neue Märkte und Kundengruppen zu erschliessen, den Kunden näher an sich zu binden und sich durch individuelle Angebote von der Konkurrenz abzuheben. In dieser Veranstaltung werden wir unter anderem den Stand der Forschung hinsichtlich der digitalen Transformation hin zu mehr Services kennenlernen, uns mit verschiedenen Herangehensweisen für die Entwicklung und das Management von digitalen Services vertraut machen sowie anhand von Beispielen aus der Praxis die erfolgreiche Einführung von IT‑basierten Serviceinnovationen untersuchen. Zusätzlich werden wir in Kooperation mit namhaften Praxispartnern in Teams einen digitalen Service entwickeln und designen.

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Business Analytics und Data Science Applications

Daten sind das neue Öl! Daten sind eine neue Asset-Klasse! Solche und ähnliche Aussagen sind heute allgegenwärtig und sollen das grosse wirtschaftliche Potenzial von Data Science und künstlicher Intelligenz veranschaulichen. "Smarte" Produkte und Dienstleistungen sind bereits heute allgegenwärtig und werden in Zukunft eine immer grössere Rolle in unserem Privat- und Arbeitsleben spielen. So galten beispielsweise selbstfahrende Autos vor 10 Jahren noch als technische Utopie; heute wartet man auf die flächendeckende Markteinführung. Übergeordnetes Ziel des Kurses ist es, Studierende in die Lage zu versetzen, mittels Big Data, Data Science, Machine Learning & Co betriebswirtschaftliche Probleme lösen zu können. Dafür verfolgt der Kurs ein Fallstudien-orientiertes Kursdesign. In jeder Fallstudie wird auf Basis einer konkreten betriebswirtschaftlichen Problemstellung eine prototypische Anwendung entwickelt, um z.B. die finanzielle Performance, operative Effizienz oder die Effektivität von betriebswirtschaftlichen Massnahmen zu verbessern. Im Rahmen der Fallstudien werden eine Vielzahl von unterschiedlichen Algorithmen und Analyse-Ansätzen besprochen und eingeübt. Die Fallstudien stammen dabei in der Regel aus dem Kontext von führenden Internet- und Technologie-Unternehmen, wie z.B. Facebook, Linkedin, Netflix, Orange oder Zalando. Diese Fallbeispiele umfassen dabei u.a. die Vorhersage von Weinqualität, Vorhersage von zukünftigen Kundenverhalten, das Erstellen von Kaufempfehlungen oder die automatisierte Identifikation von Fake News. Studierende lernen dabei den Umgang mit grossen unstrukturierten Datenmengen.

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Business-to-IT-Innovation: Was (zukünftige) Managerinnen und Manager wissen sollten

Grundlagen der Gestaltung (Analyse und Modellierung) Gestaltung von Unternehmens- / Geschäftsstrategien Gestaltung von Digitalisierungsstrategien Gestaltung von IT-Strategien Gestaltung der digitalen Transformation Gestaltung von Programmen und Projekten für die Digitale Transformation Gestaltung von Ablauf- und Aufbauorganisationen Gestaltung von Informationssystemen

Master in Business Innovation

Das IWI-HSG betreut das Master-Programm in Business Innovation (MBI).  Möchten Sie als Führungskraft die Zukunft innovativ gestalten? Der Master in Business Innovation zeigt Ihnen, wie Sie die Potenziale der digitalen Transformation erfolgreich nutzen.

    Falls Sie Fragen bezüglich des Masters in Business Innovation haben, freuen wir uns auf Ihre Kontaktaufnahme.






    Abschlussarbeiten

    Sie können bei uns Bachelor- und Masterarbeiten zu den Themengebieten des IWI-HSG schreiben. Falls Sie interessiert sind, wenden Sie sich bitte direkt an den Referenten bzw. die Referentin.

     

    Nachfolgend finden Sie eine Übersicht aktueller Themen. Sollten Sie weitere Ideen haben, kommen Sie auch gerne auf uns zu.

    Level:
    Bachelor/Master
    Kontakt:
    Philipp Gordetzki

    Why:
    Digital innovation platforms are popular solutions for engaging consumers in the innovation process for several reasons: faster innovation, higher quality ideas, and lower costs are just some of the benefits. Nevertheless, there is currently still a need for improvement. Ideas are developed and evaluated by people like you and me, who tend to suffer from barriers to creativity, such as cognitive fixation, aversion to novelty, and reluctance to leave the path of least resistance.
    After the ideation process, evaluating a large number of ideas is a difficult task for human experts. AI can solve this problem by automatically analyzing ideas with regard to their novelty, degree of elaboration, and innovativeness. Your task is to investigate how an AI can analyse existing feedback and provide guidance during evaluation. We provide you with an extensive real-world dataset containing over 100,000 ideas with comments.

    How?

    • Analyse the comments in the dataset to understand how humans provide feedback
    • Utilize modern technologies such as BERT or GPT to train an AI to learn how to provide feedback
    • Optionally apply your solution in a real-world experiment to test your solution

    Key-Facts:

    • Close supervision, with regular review meetings, feedback discussions, etc.
    • Thesis can start immediately but should be completed within the next ±6 months
    • If the work is worth publishing, you will be listed as an author

    If you are interested, send your CV, transcript of records, and a brief description of your motivation to Philipp Gordetzki (). Looking forward to hearing from you! 🙂

    Level:
    Bachelor
    Kontakt:
    Philipp Gordetzki

    Why:
    Digital innovation platforms are popular solutions for engaging consumers in the innovation process for several reasons: faster innovation, higher quality ideas, and lower costs are just some of the benefits. Nevertheless, there is currently still a need for improvement. Ideas are developed and evaluated by people like you and me, who tend to suffer from barriers to creativity, such as cognitive fixation, aversion to novelty, and reluctance to leave the path of least resistance.
    Your task is to identify how AI can be utilized on innovation platforms. You identify previous use-cases and describe challenges to guide further research.

    How?

    • Thesis that conducts a systematic literature review on use cases of AI on innovation platforms using the methodology of Webster and Watson (2002) and Vom Brocke et al. (2009; 2015)

    Key-Facts:

    • Close supervision, with regular review meetings, feedback discussions, etc.
    • Thesis can start immediately but should be completed within the next ±6 months
    • If the work is worth publishing, you will be listed as an author

    If you are interested, send your CV, transcript of records, and a brief description of your motivation to Philipp Gordetzki (). Looking forward to hearing from you! 🙂

    Level:
    Bachelor/Master
    Kontakt:
    Philipp Gordetzki

    Why:
    Digital innovation platforms are popular solutions for engaging consumers in the innovation process for several reasons: faster innovation, higher quality ideas, and lower costs are just some of the benefits. Nevertheless, there is currently still a need for improvement. Ideas are developed and evaluated by people like you and me, who tend to suffer from barriers to creativity, such as cognitive fixation, aversion to novelty, and reluctance to leave the path of least resistance.
    During the ideation process, feedback is crucial but costly for human editors. AI can solve this problem by automatically providing high-quality feedback to enhance human creativity. Your task is to investigate how an AI can learn from human feedback. We provide you with an extensive real-world dataset containing over 100,000 ideas with comments.

    How?

    • Analyse the comments in the dataset to understand how humans provide feedback
    • Utilize modern technologies such as BERT or GPT to train an AI to learn how to provide feedback
    • Optionally apply your solution in a real-world experiment to test your solution

    Key-Facts:

    • Close supervision, with regular review meetings, feedback discussions, etc.
    • Thesis can start immediately but should be completed within the next ±6 months
    • If the work is worth publishing, you will be listed as an author

    If you are interested, send your CV, transcript of records, and a brief description of your motivation to Philipp Gordetzki (). Looking forward to hearing from you! 🙂

    Level:
    Bachelor/Master
    Kontakt:
    Philipp Gordetzki

    Why:
    Digital innovation platforms are popular solutions for engaging consumers in the innovation process for several reasons: faster innovation, higher quality ideas, and lower costs are just some of the benefits. Nevertheless, there is currently still a need for improvement. Ideas are developed and evaluated by people like you and me, who tend to suffer from barriers to creativity, such as cognitive fixation, aversion to novelty, and reluctance to leave the path of least resistance.
    Understanding what makes an idea new and exciting is crucial for generating and evaluating innovation. AI can solve this problem by automatically predicting the novelty of an idea. Your task is to investigate existing innovation ideas and apply text mining to assess originality. Next, an AI can learn the patterns behind novelty. We provide you with an extensive real-world dataset containing over 100,000 ideas with comments.

    How?

    • Analyse the ideas in the dataset and find patterns and clusters
    • Utilize text mining to generate measurements for novelty and conceptualize a novelty score that an AI can predict
    • Optionally apply your solution in a real-world experiment to test your solution

    Key-Facts:

    • Close supervision, with regular review meetings, feedback discussions, etc.
    • Thesis can start immediately but should be completed within the next ±6 months
    • If the work is worth publishing, you will be listed as an author

    If you are interested, send your CV, transcript of records, and a brief description of your motivation to Philipp Gordetzki (). Looking forward to hearing from you! 🙂

    Level:
    Bachelor/Master
    Kontakt:
    Philipp Gordetzki

    Why:
    Digital innovation platforms are popular solutions for engaging consumers in the innovation process for several reasons: faster innovation, higher quality ideas, and lower costs are just some of the benefits. Nevertheless, there is currently still a need for improvement. Ideas are developed and evaluated by people like you and me, who tend to suffer from barriers to creativity, such as cognitive fixation, aversion to novelty, and reluctance to leave the path of least resistance.
    AI can help users conceptualize an innovative idea by providing automatic feedback or cognitive stimulation. Different AI-supported writing methods exist today, e.g., spelling checks such as Grammarly. Your task is to create an AI-supported user journey on an innovation platform. You can build an experiment with our team to test your hypotheses and compare different methods.

    How?

    • Conceptualize a user journey with different support opportunities for an AI
    • Implement prototypes of such support opportunities in our experiment platform
    • Test your solution in a real-world experiment

    Key-Facts:

    • Close supervision, with regular review meetings, feedback discussions, etc.
    • Thesis can start immediately but should be completed within the next ±6 months
    • If the work is worth publishing, you will be listed as an author

    If you are interested, send your CV, transcript of records, and a brief description of your motivation to Philipp Gordetzki (). Looking forward to hearing from you! 🙂

    Level:
    Bachelor
    Kontakt:
    Philipp Gordetzki

    Why:
    Digital innovation platforms are popular solutions for engaging consumers in the innovation process for several reasons: faster innovation, higher quality ideas, and lower costs are just some of the benefits. Nevertheless, there is currently still a need for improvement. Ideas are developed and evaluated by people like you and me, who tend to suffer from barriers to creativity, such as cognitive fixation, aversion to novelty, and reluctance to leave the path of least resistance.
    AI can help users to overcome these barriers. In the past, AI was successfully used in various domains of human creativity, e.g., creating music, images, or novels. As innovation is a challenging creativity process, we aim to support humans in a hybrid approach. Your task is to investigate previous use-cases of AI to increase human creativity and identify gaps and opportunities for further research.

    How?

    • Thesis that conducts a systematic literature review on the topic of hybrid creativity using the methodology of Webster and Watson (2002) and Vom Brocke et al. (2009; 2015)

    Key-Facts:

    • Close supervision, with regular review meetings, feedback discussions, etc.
    • Thesis can start immediately but should be completed within the next ±6 months
    • If the work is worth publishing, you will be listed as an author

    If you are interested, send your CV, transcript of records, and a brief description of your motivation to Philipp Gordetzki (). Looking forward to hearing from you! 🙂

    Level:
    MA
    Kontakt:
    Fumi Kurihara

    Have you ever wondered how matchmaking platforms affect user engagement? If so, this thesis topic is for you. We are currently looking for a Master student to conduct a qualitative study (i.e. conduct interviews) that explores how different users engage with each other on matchmaking platforms. Your findings will have practical implications, including providing recommendations to platform providers.

    This study is part of a larger project that is conducted in collaboration with Copenhagen Business School (CBS).

    If you are interested, please send an email to . We look forward to hearing back from you!

    Starting date: As soon as possible

    Level:
    Master
    Kontakt:
    Eva Ritz

    Why:
    The current rise of online learning environments, such as massive open online courses or learning management systems comes with many new opportunities. Therefore, now is the time to leave behind the one-size-fits all mentality in education. The individualization of online trainings (e.g. cousera courses) enables users to learn exactly their required knowledge, within their own pace and style. This individualization can take learners in a “flow state”, in which they are intrinsically motivated, loose self-consciousness, and experience timelessness. The goal of this research project is to find out more about how to evoke such a flow state in learning.

    How?
    • Master thesis that conducts a systematic literature review on the topic of flow experience in online learning using the methodology of Webster and Watson (2002) and Vom
    Brocke et al. (2009; 2015) OR
    • Master thesis that conducts an Experiment with EEG to measure flow states in individualized learning in close consultation with me

    Key-Facts:

    • Close supervision, with regular review meetings, feedback discussions, etc.
    • Thesis can start immediately, but should be completed within the next ±6 months
    • If the work is worth publishing, you will be listed as author

    If you are interested, send your CV, transcript of records and a brief description of your motivation to Eva Ritz (). Looking forward to hear from you! 🙂

    Individueller Themenvorschlag

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            Ihre Bewerbung für eine Abschlussarbeit

            Danke für Ihr Interesse, Ihre Abschlussarbeit am Lehrstuhl von Prof. Dr. Jan Marco Leimeister zu schreiben. Wir betreuen gerne Studierende, die sich für unsere Forschungsthemen begeistern und die bisher gute akademische Leistungen erbracht haben. Weil wir eine grosse Anzahl an Bewerbungen bekommen, können wir nur jene berücksichtigen, die gut zu unseren Forschungsgebieten passen. Mehr zu unseren Forschungsgebieten erfahren Sie auf dieser Webseite. Um sich zu bewerben, können Sie eines der Themen in Betracht ziehen, an denen wir arbeiten oder Sie können ein eigenes Thema vorschlagen.



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              Doktoratsstudium
              Ph.D. in Management – Fachrichtung Business Innovation

              Alle ordentlichen Professoren des IWI-HSG betreuen Promotionen. Zudem bietet das Institut Kurse auf der Doktorandenstufe an.

              Das Doktoratsprogramm in Betriebswirtschaftslehre ist in eine Kursphase und eine Dissertationsphase gegliedert. In der Kursphase sind zwei Pflichtkurse und mindestens zwei Methoden-/Fachkurse aus den Doktoratsprogrammen der Universität St. Gallen oder der Global School in Empirical Research zu besuchen. Nach Abgabe der Vorstudie beginnt die Dissertationsphase. In dieser sind mindestens zwei dissertationsbegleitende Seminare/Kolloquien zu absolvieren. Ein weiterer Methodenkurs oder ein weiteres Seminar kann phasenunabhängig belegt werden.