Value Co-Creation in AI Platform Ecosystems

Thesis (MA)

Advisor(s): Michael Weber (mic.weber@tum.de)

Context

Many organizations turn to external service providers to facilitate the adoption of Artificial Intelligence (AI) technologies (Weber et al., 2021). There is a wide range of services available, such as pretrained AI models, computational engines for model training, and supportive tools for data annotation (Lins et al., 2021). Some of those services are bundled and centrally offered on AI platforms (Geske et al., 2021). These platforms typically connect multiple actors, such as users, software firms, and data providers, and thereby form digital platform ecosystems (Hein et al., 2020). Besides providing services to isolated customers, AI platforms also inhibit the potential to enable value co-creation (Hein et al., 2019). For example, by enabling crowdsourced data annotations or federated machine learning, multiple parties can collaborate to collectively advance AI adoption. However, the potential for value co-creation in AI platform ecosystems and the underlying dynamics have thus far been overlooked in Information Systems (IS) research and thus represent an open research issue (Geske et al., 2021).

To address this gap, researchers from the Krcmar Lab started to engage in an embedded case study in the context of healthcare. The healthcare context is particularly interesting because of its many promising AI applications and the openness of its actors to collaborate for the benefits of overall healthcare. We started to analyze three AI platforms that focus on different aspects of AI adoption and employ different business models. The goal of this thesis is to continue this ongoing case study. For this, it will be necessary to collect new interview data in the healthcare context and advance emergent findings on value co-creation in AI platform ecosystems.

Task(s)

  • Review literature in the respective field
  • Conduct interviews with platform owners and complementors
  • Conceptualize value co-creation mechanisms in AI platform ecosystems
  • Discuss implications for Information Systems research

Requirements

  • High degree of autonomy and individual responsibility
  • Good communicative skills
  • Interest and first experience in the fields of digital platforms and AI
  • Expertise in qualitative research and very good grades are beneficial

Further Information

The thesis can be written in English or German. The topic can also be adapted to your interests. If you have further questions, please do not hesitate to contact me directly. Please send your application including our application form, a current transcript of records, and your CV to mic.weber@tum.de. Please note that we can only consider applications with complete documents. 

References

Geske, F., Hofmann, P., Lämmermann, L., Schlatt, V., & Urbach, N. (2021). Gateways to Artificial Intelligence: Developing a Taxonomy for AI Service Platforms. Paper presented at the European Conference on Information Systems.

Hein, A., Weking, J., Schreieck, M., Wiesche, M., Böhm, M., & Krcmar, H. (2019). Value co-creation practices in business-to-business platform ecosystems. Electronic Markets, 29(3), 503-518.

Hein, A., Schreieck, M., Riasanow, T., Setzke, D. S., Wiesche, M., Böhm, M., & Krcmar, H. (2020). Digital platform ecosystems. Electronic Markets, 30(1), 87-98.

Lins, S., Pandl, K. D., Teigeler, H., Thiebes, S., Bayer, C., & Sunyaev, A. (2021). Artificial Intelligence as a Service. Business & Information Systems Engineering, 63(4), 441-456.

Weber, M., Beutter, M., Weking, J., Böhm, M., & Krcmar, H. (2021). AI Startup Business Models. Business & Information Systems Engineering, 1-19.