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.

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.

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.

Level: Master

Methodology: Empirical Investigation

Literature:

• M?ntym?ki, M., Minkkinen, M., Birkstedt, T., & Viljanen, M. (2022). Defining organizational AI governance. AI and Ethics, 2(4), 603–609.
• M?ntym?ki, 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.

Datafication refers to the process of converting various aspects of life and society into data. This includes the collection, analysis, and transformation of information into digital formats, which can then be quantified and used for various purposes. Datafication is a central component of data analysis and data-driven decision-making in many areas, including businesses. The way data is produced, combined and interpreted has severe implications for how information and knowledge is created within firms and ultimately even shapes how organizations are structured. Students could explore this phenomenon and its implications further in their final thesis.

Level: Bachelor / Master

Methodology: Literature Review / Empirical Investigation

Literature:

• Alaimo, C., & Kallinikos, J. (2021). Managing by data: Algorithmic categories and organizing. Organization Studies, 42(9).
• Alaimo, C., & Kallinikos, J. (2022). Organizations decentered: Data objects, technology and knowledge. Organization Science, 33(1).
• Flyverbom, M., & Murray, J. (2018). Datastructuring—Organizing and curating digital traces into action. Big Data & Society. 5(2).

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?

Level: 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.

Platform Work refers to the phenomenon where digital platforms facilitate individuals in offering their services or labour directly to clients or consumers. This shift empowers workers by providing flexible employment opportunities, enabling them to choose when and how they work. As a result, the nature of work is evolving, moving away from traditional employment models towards Gig-Work or Freelancing arrangements. This transformation introduces both advantages and challenges. While workers benefit from increased autonomy and diversified income streams, they also face uncertainties such as fluctuating demand, lack of job security, and limited access to benefits. Moreover, platform work raises significant research questions about worker rights, labour regulation, and the implications for social safety nets. A final thesis in this research area could explore how platform-mediated work unfolds and what the drivers of success are.

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).
• Baygi, R. M., Introna, L. D., & Ostovar, M. (2024). Beyond Categories: A Flow-oriented Approach to Social Justice on Online Labour Platforms. MIS Quarterly. published online.
• M?hlmann, M., Zalmanson, L., Henfridsson, O., & Gregory, R. W. (2021). Algorithmic Management of Work on Online Labor Platforms: When Matching Meets Control. MIS Quarterly, 45(4).

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.

Level: Bachelor / Master

Methodology: Literature Review / Empirical Investigation

Literature:

• Foerderer, J., Kude, T., Schuetz, S., & Heinzl, A. (2017). Knowledge Boundaries in Enterprise Software Platform Development: Antecedents and Consequences for Platform Governance (SSRN Scholarly Paper No. 2872209).
• 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.

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., S?rensen, C., & Basole, R. C. (2018). The Digital Platform: A Research Agenda.Journal of Information Technology, 33(2), 124–135.