Bachelor and master theses

Platform ecosystems involve key actors, including platform owners, users, producers, third-party developers, and regulators. Previous research has explored the dynamics among these actors, focusing on aspects like network effects, value co-creation, competition, collaboration, user duality, and governance structures. Recently, decentralized platform ecosystems have emerged, functioning without a central authority, employing, for instance, blockchain technology for enhanced security and transparency. These ecosystems facilitate peer-to-peer interactions, enabling direct resource sharing among users. Participants often engage in self-governance through community voting, fostering collaboration while enhancing user privacy and data control. This evolution prompts new research questions concerning power dynamics, governance, and user privacy. A final thesis could address these aspects further.

Supervision: Prof. Dr. Thomas Kude

Level: Bachelor / Master

Methodology: Literature Review / Empirical Investigation

Literature:

• Clough, D. R., & Wu, A. (2022). Artificial intelligence, data-driven learning, and the decentralized structure of platform ecosystems. Academy of Management Review, 47(1).
• Parker, G., & van Alstyne, M. (2008). Managing Platform Ecosystems. ICIS 2008 Proceedings, 53.

As platforms gather vast amounts of personal data, users risk exposure to identity theft, surveillance, and misuse of their information. Moreover, centralization often creates single points of failure, making platforms vulnerable to cyberattacks. How can platforms enhance data security while maintaining user trust? What frameworks can be developed to ensure user privacy rights in compliance with regulations? Exploring these questions could allow students to explore in their final thesis how to manage privacy and security concerns in platform ecosystems.

Supervision: Prof. Dr. Thomas Kude

Level: Bachelor / Master

Methodology: Literature Review / Empirical Investigation

Literature:

• Bélanger, F., and Crossler, R. E. 2011. Privacy in the Digital Age: A Review of Information Privacy Research in Information Systems. MIS Quarterly, 35(4).
• Culnan, M. J., and Williams, C. C. 2009. How Ethics Can Enhance Organizational Privacy: Lessions Fom the Choicepoint and TJX Data Breaches. MIS Quarterly, 33(4).
• Teubner, T., & Flath, C. M. (2019). Privacy in the sharing economy. Journal of the Association for Information Systems, 20(3).

The emergence of Artificial Intelligence (AI) as a new player in the corporate environment has introduced significant uncertainties, especially regarding the potential displacement of human labour. Many organizations currently lack a clear legal framework to navigate this transition, leaving them to develop their own strategies for integrating AI technologies. This situation raises important ethical questions about the impact of AI on employment and the workplace environment. To address these challenges, the debate is all about AI Governance, but how does AI Governance unfold in organizations? This interesting research question could be addressed in a final thesis.

Supervision: Prof. Dr. Thomas Kude

Level: Master

Methodology: Empirical Investigation

Literature:

• Mäntymäki, M., Minkkinen, M., Birkstedt, T., & Viljanen, M. (2022). Defining organizational AI governance. AI and Ethics, 2(4), 603–609.
• Mäntymäki, M., Minkkinen, M., Zimmer, M., Birkstedt, T., & Viljanen, M. (2023). Designing an AI governance framework: From research-based premises to meta-requirements. ECIS 2023 Research Papers.

Data do not automatically become useful information or organizational value. To be understood, shared, and reused, they need to be generated, cleaned, structured, documented, interpreted, and embedded into specific contexts of use.

In this topic area, students therefore examine data work as a sociotechnical process through which data are mobilized and made usable by actors, IT systems, standards, platforms, and organizational routines. The central question is how data acquire meaning along their journey through organizations or data ecosystems and become connected to value generation. Possible thesis projects may focus on metadata, documentation, data quality, responsibilities, the translation of data across contexts, or the role of data stewards, business units, and IT.

Supervision: Stefanie Ulschmid

Level: Bachelor / Master

Methodology: Literature Review / Empirical Investigation

Literature:

• Leonelli, S. (2020). Learning from data journeys. In Data journeys in the sciences (pp. 1-24). Cham: Springer International Publishing.
• Jarvenpaa, S. L., & Essén, A. (2023). Data sustainability: Data governance in data infrastructures across technological and human generations. Information and Organization, 33(1), 100449.
• Oliveira, M. I., Barros Lima, G. D. F., & Farias Lóscio, B. (2019). Investigations into data ecosystems: a systematic mapping study. Knowledge and Information Systems, 61(2), 589-630.

Platformization, what we define as the increasing adoption of digital platforms by organizations, is transforming operational processes and structures within companies. This shift enables greater efficiency through streamlined communication, enhanced collaboration, and improved data management. However, in highly regulated sectors like healthcare and education, this transformation presents unique challenges. Organizations must navigate compliance with stringent regulations while leveraging the benefits of digital platforms. This necessitates a re-evaluation of data governance policies, privacy considerations, and security measures. So far, limited research has been conducted in this field, presenting an opportunity for a final thesis to explore it further, e.g. what are the implications of “Platformization” for highly regulated sectors, such as healthcare and education? How can AI be used in healthcare and/or education?

Supervision: Stefanie Badmann

Level: Bachelor / Master

Methodology: Empirical Investigation

Literature:

• Ozalp, H., Ozcan, P., Dinckol, D., Zachariadis, M., & Gawer, A. (2022). “Digital Colonization” of Highly Regulated Industries: An Analysis of Big Tech Platforms’ Entry into Health Care and Education. California Management Review, 64(4), 78–107.
• Setia, P., Soh, F., & Deng, K. (2020). Platformizing organizations: a synthesis of the literature. Oxford Research Encyclopedia of Business and Management.

Data are a central foundation of digital value creation, yet they never fully represent organizations, markets, or customers. This topic area examines how firms nevertheless create and capture value from data by connecting data-based analyses, models, and algorithmic systems with organizational contexts of decision-making, coordination, and value creation.

The central question is how data, despite their selectivity and context-dependence, become value-relevant objects, models, and bases for decision-making. Possible thesis projects may examine data-driven business models, AI-based automation, data governance, decision support, organizational capabilities, or the limits of data-based value creation.

Supervision: Stefanie Ulschmid

Level: Bachelor / Master

Methodology: Literature Review / Empirical Investigation

Literature:

• Alaimo, C., Kallinikos, J., & Aaltonen, A. (2020). Data and value. In Handbook of digital innovation (pp. 162-178). Edward Elgar Publishing.
• Constantiou, I., Joshi, M., & Stelmaszak, M. (2023). Organizations as digital enactment systems: A theory of replacement of humans by digital technologies in organizational scanning, interpretation, and learning. Journal of the Association for Information Systems, 24(6), 1770-1798.
• Xu, D., Indulska, M., Someh, I. A., & Shanks, G. (2024). Time to reassess data value: The many faces of data in organizations. The Journal of Strategic Information Systems, 33(4), 101863.

Content moderation on platforms is a central issue in the digital world. Platform operators are responsible for striking a balance between freedom of expression and protection against harmful or inappropriate content. Platforms are increasingly using algorithm-based moderation systems to identify and remove unwanted content. This raises the question of how effective these systems are and what impact they have on the user experience and engagement on platforms. Algorithmic moderation and human intervention can lead to different outcomes in different contexts, which also influences user trust in the platforms. Particularly on platforms such as Reddit or social networks, where user interaction is paramount, the question of accountability and transparency in moderation decisions poses new challenges. On platforms such as live-streaming services and social media channels, content moderation significantly influences the dynamics of user participation. A potential thesis could explore how content moderation through algorithms and human intervention shapes user behavior, platform governance, and social norms on digital platforms.

Supervision: Stefanie Badmann

Level: Bachelor / Master

Methodology: Literature Review / Empirical Investigation

Literature:

• He, Q., Hong, Y., & Raghu, T. S. (2025). Platform Governance with Algorithm-Based Content Moderation: An Empirical Study on Reddit. Information Systems Research, 36(2), 1078–1095. https://doi.org/10.1287/isre.2021.0036
• Zhang, X., Wei, Z., Du, Q., & Zhang, Z. (2026). Social Media Moderation and Content Generation: Evidence From User Bans. MIS Quarterly, 50(1), 211–242. https://doi.org/10.25300/MISQ/2025/18108
• Zhao, K., Hong, Y., Ma, T., Lu, Y., & Hu, Y. (2025). Lost in the Crowd: How Group Size and Content Moderation Shape User Engagement in Live Streaming. Information Systems Research, 36(4), 2076–2095. doi.org/10.1287/isre.2022.0086

Since the the pandemic, a significant number of office employees have become familiar with platform-based teamwork, making virtual collaboration an integral part of the modern work experience. Today, it is nearly unimaginable for teams to operate without some form of online interaction. Various tools, particularly cloud-based solutions, have emerged to facilitate this collaboration, enhancing communication and productivity across geographically dispersed teams. This shift to digital teamwork not only transforms traditional workplace dynamics but also opens a rich field of research opportunities for a final thesis in this field, which could address the role of digital platforms for teamwork in organizations.

Supervision: Stefanie Badmann

Level: Bachelor / Master

Methodology: Literature Review / Empirical Investigation

Literature:

• Barley, S. R., Bechky, B. A., & Milliken, F. J. (2017). The Changing Nature of Work: Careers, Identities, and Work Lives in the 21st Century. Academy of Management Discoveries, 3(2).
• Kude, T., Mithas, S., Schmidt, C. T., & Heinzl, A. (2019). How Pair Programming Influences Team Performance: The Role of Backup Behavior, Shared Mental Models, and Task Novelty. Information Systems Research, 30(4), 1145–1163.
• Kude, T.,  Foerderer, J.,  Mithas, S., &  Heinzl, A. (2023).  How deadline orientation and architectural modularity influence software quality and job satisfaction. Journal of Operations Management, 1– 24.

Digital infrastructures connect organizations, actors, technical systems, and data sources. They enable new forms of coordination, governance, and value creation, while also creating dependencies, control problems, and questions of digital sovereignty.

In this topic area, students therefore examine digital infrastructures not merely as technical systems, but as sociotechnical orders. The central question is under what conditions digital infrastructures can be designed to be open, controllable, sustainable, and responsible. Possible thesis projects may focus on governance frameworks (e.g., polycentric governance arrangements), open source, interoperability, trace data, smart cities, mobility, energy, public administration, or sustainability-related infrastructures.

This topic area is suitable for literature-based, conceptual, or empirical theses.

Supervision:  Stefanie Ulschmid

Level: Bachelor / Master

Methodology: Literature Review / Empirical Investigation

Literature:

• Constantinides, P., Henfridsson, O., & Parker, G. G. (2018). Introduction—platforms and infrastructures in the digital age. Information Systems Research, 29(2), 381-400.
• Veit, D. J., & Thatcher, J. B. (2023). Digitalization as a problem or solution? Charting the path for research on sustainable information systems. Journal of Business Economics, 93(6), 1231-1253.
• Zuboff, S. (2022). Surveillance capitalism or democracy? The death match of institutional orders and the politics of knowledge in our information civilization. Organization Theory, 3(3).

This thesis topic explores the evolving role of the press and traditional media as indispensable intermediaries in ensuring accurate information and fostering informed local communities. While local journalism is critical for democracy and social cohesion, it faces increasing challenges from the dominance of digital platforms and the rise of social media, where misinformation can spread unchecked. Your research will examine how traditional media can adapt to remain relevant, the innovations needed to sustain local journalism, or the potential strategies to counteract the misinformation challenges posed by social media.

Supervision:  Prof. Dr. Thomas Kude

Level: Bachelor / Master

Methodology: Literature Review / Empirical Investigation / Design Science

Literature:

• Abbasi, A., Greenwood, B. N., Mazmanian, M., Miranda, S., & Seamans, R. Call for Papers: Special Issue-The Institutional Press in the Digital Age.
• Kitchens, B., Johnson, S. L., & Gray, P. (2020). Understanding echo chambers and filter bubbles: The impact of social media on diversification and partisan shifts in news consumption. MIS quarterly, 44(4).
• Matherly, T., & Greenwood, B. N. (2022). No news is bad news: The internet, corruption, and the decline of the fourth estate. Corruption, and the Decline of the Fourth Estate (September 8, 2022).

This topic starts from the premise that many of the traditional teaching and assessment methods in higher education have already become or will likely become obsolete in the near future. For example, asking a relatively simple question for a take-home assignment may not be adequate anymore. Instead of rejecting such developments, this thesis takes a positive stance and aims to explore how higher education needs to evolve in order to make the best possible use of AI tools. How can platforms and tools be used and designed? How do these platforms and tools complement personal, in-class interaction? How can student-led research projects and academic writing evolve and how can student contributions be assessed?

Supervision:  Prof. Dr. Thomas Kude / Stefanie Badmann

Level: Bachelor / Master

Methodology: Literature Review / Empirical Investigation / Design Science

Literature:

• Betts, M., & Rosemann, M. (2022). The New Learning Economy: Thriving Beyond Higher Education. Routledge.
• Crompton, H., & Burke, D. (2023). Artificial intelligence in higher education: the state of the field. International Journal of Educational Technology in Higher Education, 20(1), 22.
• Komljenovic, J. (2021). The rise of education rentiers: digital platforms, digital data and rents. Learning, Media and Technology, 46(3), 320–332.

Are you eager to explore the realm of digital platforms and their impact on firms, industries, and society, but find that none of our suggested topics align with your interests? Perhaps you have a company partner in mind for collaboration? If you believe your interests align with our research focus, please share your ideas with us through the contact field below, providing a brief description (approx. 500-1,000 words) of what you have planned for your final thesis.

Level: Bachelor / Master

Methodology: Literature Review / Empirical Investigation

Literature:

• De Reuver, M., Sørensen, C., & Basole, R. C. (2018). The Digital Platform: A Research Agenda.Journal of Information Technology, 33(2), 124–135.