Felix Eigelshoven

Associate Researcher

Felix Eigelshoven is an affiliated researcher at the Weizenbaum Institute in Berlin and at the Blockchain Research Lab in Hamburg, with a passion for exploring the uses cases of tokenization and the future role of decentralized digital assets. Alongside his research, Felix works as a Technology Innovation Strategy Manager at Accenture, where he focuses on the tokenization of digital assets within the European market.

Felix received a Bachelor of Science in Economics from Goethe University Frankfurt am Main and a Master of Science in Information Systems from the University of Potsdam, where he also conducted research at Stellenbosch University. Throughout his career as a researcher, Felix worked on various research topics such as the sustainability of consensus algorithms within public blockchains, market manipulation within crypto markets, and the development of digital asset standards.

His current research topics includes the role of decentralized digital assets in the Metaverse and the social and economic implications. Furthermore, he focuses on the development of a taxonomy for digitals assets and the evaluation of the use of digital assets in the metaverse based on actual smart contract interactions.




A Taxonomy of Digital Assets in the Metaverse

The metaverse, a term initially coined by science fiction author Neal Stephenson in his science fiction novel Snow crash, refers to a collective, persistent and immersive spectrum of digitally enhances worlds. This shared space is created by the convergence of the physical and digital worlds based on various emerging technologies such as Blockchain, AR or VR. Digital assets within this world, such as avatars, virtual real estate, and non-fungible tokens (NFTs), as well as cryptocurrencies play a crucial role providing users with the means to interact and transact within virtual environments. However, the lack of a comprehensive taxonomy for these digital assets has resulted in confusion and ambiguity within the field. The project aims to address this issue by developing a taxonomy of digital assets in the metaverse. By conducting a systematic literature review the project tries to identify key characteristics, such as intrinsic value and ownership, that are commonly used to classify these assets. Based on these characteristics, the project shall result in a taxonomy of digital asset which should provide a clear framework for understanding the various types and subtypes of digital assets in the metaverse, and furthermore should serve as a useful reference for researchers, practitioners, and policymakers working in this emerging field. Due to the lack of consensus and clear definitions for these assets, which could lead to challenges in their regulation and management, the project furthermore aims to create a research agenda to further develop a standardised taxonomy of the metaverse, including the exploration of their economic value and potential socio-economic impact from a holistic sustainable point of view.

An Empirical Study of Digital Asset Use in the Metaverse based on Smart Contract Interactions

Based on the results of project 1, the second project aims to empirically evaluate the use of digital assets in the metaverse based on actual smart contract interactions. Smart contracts, self-executing contracts with the terms of the agreement between buyer and seller being directly written into lines of code, are increasingly being used to facilitate the transaction and interaction with digital assets. The study therefor will analyze a broad range of smart contract data to provide a comprehensive view of the types of digital assets that are commonly used, the specific metaverse digital ecosystem in which they are used, and the nature of the transactions taking place. The findings provide valuable insights into the current state of smart contract interactions with digital assets in the metaverse and can inform the development of future research and policy in this emerging field. Analyzing digital assets based on their smart contract interactions plays an important role for understanding the current state of the token economy, its socio-economic impacts and for developing effective strategies for its future growth and development. By using a broad range of data and adopting a neutral perspective, this study will provide a comprehensive and unbiased view of the actual interactions with digital assets in variety of emerging digital ecosystems and its implications for our society.



Ullrich, A., Vladova, G., Eigelshoven, F., & Renz, A. (2022). Data mining of scientific research on artificial intelligence in teaching and administration in higher education institutions: a bibliometrics analysis and recommendation for future research. Discover Artificial Intelligence2(1), 16. https://doi.org/10.1007/s44163-022-00031-7

Eigelshoven, F., Ullrich, A., & Parry, D. A. (2021). Cryptocurrency market manipulation: A systematic literature review. In International Conference on Information Systems. https://aisel.aisnet.org/icis2021/fintech/fintech/1

Schmidt, K., Ullrich, A., & Eigelshoven, F. (2021). From Exploitative Structures towards Data subject-Inclusive Personal Data Markets-a Systematic literature Review. In  Proceedings of the 29th European Conference on Information Systems (ECIS), An Online AIS Conference, June 14-16, 2021. Research Papers. 60. https://aisel.aisnet.org/ecis2021_rp/60

Eigelshoven, F., Ullrich, A., & Bender, B. (2020). Public blockchain–a systematic literature review on the sustainability of consensus algorithms. Proceedings of the 28th European Conference on Information Systems (ECIS), An Online AIS Conference, June 15-17, 2020. https://aisel.aisnet.org/ecis2020_rp/202

Thim, C., Ullrich, A., Eigelshoven, F., Gronau, N., & Ritter, A. C. (2020). Crowdsourcing bei industriellen Innovationen− Lösungsansätze und Herausforderung für KMU. I40M, 36(6), 39-47. https://doi.org/10.30844/I40M_20-6_S9-13

Eigelshoven, F., Ullrich, A., & Gronau, N. (2020). Konsens-Algorithmen von Blockchain–Eine Betrachtung der Nachhaltigkeit der Konsensfindung. I40M36(1), 29-32. https://doi.org/10.30844/I40M_20-1_S29-32