Navigating the Complexities of Data Ecosystems: A Qualitative Comparative Analysis Approach
Thesis (MA)
Advisor(s): Philipp Kernstock (philipp.kernstock@tum.de)
Introduction
In today's digital age, data has emerged as a pivotal asset, driving innovation and transformation across various sectors of society and industry. As data becomes more ubiquitous, organizations are increasingly venturing beyond their boundaries to share and consume data, giving rise to intricate data ecosystems (Gelhaar et al., 2023). These ecosystems, as conceptualized by Oliveira and Lóscio (2018) and Oliveira et al. (2019), facilitate value creation for individual actors and broader collaborations. They are not merely technological constructs but represent a confluence of technological, organizational, and societal dimensions (Azkan et al., 2022).
The transformation towards data ecosystems is evident across domains, from personalized medicine to industrial manufacturing. Such ecosystems are becoming the backbone of data-driven innovation, with real-world implications ranging from new business models to governance challenges. Legislative initiatives, such as the European Data Strategy and Singapore's Trusted Data Sharing Framework, underscore the global momentum towards fostering these ecosystems. These initiatives aim to make data usable beyond the internal boundaries of an organization, promoting data-driven innovation and addressing challenges like digital trust. Data ecosystems, with their intricate configurations and dynamics, are at the forefront of the data-driven digital revolution.
In light of these developments, it becomes imperative to delve deep into the challenges and decisions associated with data ecosystems. This research aims to use a Qualitative Comparative Analysis (QCA) approach to examine a broad spectrum of data ecosystems, understanding their configurations, dynamics, and implications for organizations and society at large.
Research Objectives of the master’s thesis could include:
- To explore the multilateral relationships within data ecosystems.
- To understand the governance structures and institutional arrangements that underpin data ecosystems.
- To investigate the tensions and decisions organizations face when participating in data ecosystems, especially in the context of data sharing and sovereignty.
Potential Research Questions guiding the thesis are:
- What are the common configurations of relationships, governance structures, and institutional arrangements in successful data ecosystems?
- How do organizations navigate the tensions and decisions associated with data sharing, sovereignty, and participation in data ecosystems?
- What are the implications of different governance models, such as data intermediation services, on the dynamics of data ecosystems?
Other research questions to be pursued in the thesis can be suggested and discussed.
Requirements
- Interest in current topics of digital platforms and ecosystems
- Ability/willingness to learn to collect and analyze large data sets
- High degree of autonomy and individual responsibility
- Experience in and willingness to conduct scientific studies
- Structured, reliable, and self-motivated work style
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 philipp.kernstock@tum.de. Please note that we can only consider applications with complete documents.
References
Azkan, C., Möller, F., Ebel, M., Iqbal, T., Otto, B., & Poeppelbuss, J. (2022). Hunting the Treasure: Modeling Data Ecosystem Value Co-Creation. 43rd International Conference on Information Systems, Copenhagen.
Gelhaar, J., Müller, P., Bergmann, N., & Dogan, R. (2023). Motives and incentives for data sharing in industrial data ecosystems: an explorative single case study. Proceedings of the 56th Hawaii International Conference on System Sciences.
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, 589-630.
Oliveira, M. I., & Lóscio, B. (2018). What is a data ecosystem? dg.o '18: Proceedings of the 19th Annual International Conference on Digital Government Research: Governance in the Data Age, 1-9. https://doi.org/10.1145/3209281.3209335