Offered Subjects

Focus on students of Business Informatics

Unfortunately, due to the high requests for our topics we have a high occupancy rate (see theses in process). Especially if we don't pro-actively publish offered subjects for theses, we need to focus on students of the business informatic degrees, in order to still gurantee adequate supervision. For students of other degree programs we recommend to contact professors of their own degree program in order to find a suitable tutor for their thesis.

Offered subjects by the chair

Here you will find all the topics offered by the Chair for Bachelor's and Master's Theses. If no topics are offered, an application with your own topic is possible at any time.

Original Title: Governance in GenAI-Plattformen

Governance in GenAI platforms

Type:
  • Master Thesis Business Information Systems
Status:
offered
Tutor:

Abstract

Recent advances in artificial intelligence (AI) have enabled a shift from data-driven, discriminative tasks to more complex, creative applications through generative AI (GenAI). With deep generative models, GenAI can create novel and realistic content in various formats such as text, images or programming code based on simple user instructions. These AI services are provided on platforms that are enhanced by complementary offerings or enable new services in bundles. For example, platforms such as ChatGPT offer the integration of other platforms via plug-ins, or generative AI tools can be integrated into company information systems. Against this background, the thesis examines governance mechanisms used for orchestration on various GenAI platforms using a cross-case study.
To conduct the study, the chair provides an initial list of GenAI companies and an overview of possible governance mechanisms. The aim of the work is to create a morphological box that reflects the possible forms of governance mechanisms. In the case of a Master's thesis, the morphology should also be evaluated in expert interviews.

Start literature:

  • Strobel, Gero; Banh, Leonardo; Möller, Frederik; Schoormann, Thorsten: Exploring Generative Artificial Intelligence: A Taxonomy and Types. In: Proceedings of the 57th Hawaii International Conference on System Sciences (HICSS). Hawaii, USA 2024
  • Banh, Leonardo; Strobel, Gero: Generative artificial intelligence. In: Electronic Markets, Jg. 33 (2023) Nr. 63. doi:10.1007/s12525-023-00680-1
  • Hein, Andreas (2020): Digital Platform Ecosystems: Emergence and Value Co-Creation Mechanisms. Technischen Universität München, München.
  • Jacobides, Michael G.; Cennamo, Carmelo; Gawer, Annabelle (2018): Towards a theory of ecosystems. In Strat. Mgmt. J. 39 (8), pp. 2255–2276. DOI: 10.1002/smj.2904.
  • Tiwana, Amrit (2014): Platform Ecosystems: Elsevier, Kapitel 6
  • Hein, Andreas; Schreieck, Maximilian; Wiesche, Manuel; Krcmar, Helmut (2016): Multiple-Case Analysis on Governance Mechanisms of Multi-Sided Platforms. In : Multikonferenz Wirtschaftsinformatik. Ilmenau, Germany.
  • Staub, Nicola; Haki, Kazem; Aier, Stephan; Winter, Robert (2022): Governance Mechanisms in Digital Platform Ecosystems: Addressing the Generativity-Control Tension. In Communications of the Association for Information Systems 51 (1), pp. 906–939. DOI: 10.17705/1CAIS.05137.

Original Abstract:

Die jüngsten Fortschritte in der künstlichen Intelligenz (KI) haben eine Verschiebung von datengesteuerten, diskriminierenden Aufgaben hin zu komplexeren, kreativen Anwendungen durch generative KI (GenAI) ermöglicht. Mit tiefgreifenden generativen Modellen kann GenAI basierend auf einfachen Benutzeranweisungen neuartige und realistische Inhalte in verschiedenen Formaten wie Texten, Bildern oder Programmiercode erstellen. Diese KI-Dienste werden auf Plattformen bereitgestellt, die durch komplementäre Angebote erweitert oder in Bündeln neue Dienstleistungen ermöglichen. So bieten beispielsweise Plattformen wie ChatGPT die Integration anderer Plattformen über Plug-ins an, oder generative KI-Tools lassen sich in Unternehmensinformationssysteme integrieren. Vor diesem Hintergrund untersucht die Arbeit Governance-Mechanismen, die zur Orchestrierung auf verschiedenen GenAI-Plattformen eingesetzt werden, anhand einer fallübergreifenden Studie. Im Falle einer Masterarbeit sollte die Morphologie auch in Experteninterviews evaluiert werden.

Zur Durchführung der Studie stellt der Lehrstuhl eine initiale Liste von GenAI-Unternehmen sowie eine Übersicht möglicher Governance-Mechanismen bereit. Ziel der Arbeit ist die Erstellung eines morphologischen Kastens, der die möglichen Ausprägungen der Governance-Mechanismen widerspiegelt.

Startliteratur:

  • Strobel, Gero; Banh, Leonardo; Möller, Frederik; Schoormann, Thorsten: Exploring Generative Artificial Intelligence: A Taxonomy and Types. In: Proceedings of the 57th Hawaii International Conference on System Sciences (HICSS). Hawaii, USA 2024
  • Banh, Leonardo; Strobel, Gero: Generative artificial intelligence. In: Electronic Markets, Jg. 33 (2023) Nr. 63. doi:10.1007/s12525-023-00680-1
  • Hein, Andreas (2020): Digital Platform Ecosystems: Emergence and Value Co-Creation Mechanisms. Technischen Universität München, München.
  • Jacobides, Michael G.; Cennamo, Carmelo; Gawer, Annabelle (2018): Towards a theory of ecosystems. In Strat. Mgmt. J. 39 (8), pp. 2255–2276. DOI: 10.1002/smj.2904.
  • Tiwana, Amrit (2014): Platform Ecosystems: Elsevier, Kapitel 6
  • Hein, Andreas; Schreieck, Maximilian; Wiesche, Manuel; Krcmar, Helmut (2016): Multiple-Case Analysis on Governance Mechanisms of Multi-Sided Platforms. In : Multikonferenz Wirtschaftsinformatik. Ilmenau, Germany.
  • Staub, Nicola; Haki, Kazem; Aier, Stephan; Winter, Robert (2022): Governance Mechanisms in Digital Platform Ecosystems: Addressing the Generativity-Control Tension. In Communications of the Association for Information Systems 51 (1), pp. 906–939. DOI: 10.17705/1CAIS.05137.