Felix Eigelshoven

Assoziierter Forscher

Felix Eigelshoven ist assoziierter Gastwissenschaftler am Weizenbaum-Institut in Berlin und am Blockchain Research Lab in Hamburg. Seine Leidenschaft gilt der Erforschung von Anwendungsfällen der Tokenisierung und der Rolle von dezentralen digitalen Assets. Neben seiner Forschertätigkeit arbeitet Felix als Technology Innovation Strategy Manager bei Accenture, wo er sich auf die Tokenisierung von digitalen Vermögenswerten auf dem europäischen Markt konzentriert.

Felix erhielt seinen Bachelor of Science in Wirtschaftswissenschaften von der Goethe-Universität Frankfurt am Main und seinen Master of Science in Wirtschaftsinformatik von der Universität Potsdam, wo er außerdem an der Universität Stellenbosch forschte. Während seiner wissenschaftlichen Laufbahn arbeitete Felix an verschiedenen Forschungsthemen wie der Erfoschung der Nachhaltigkeit von Konsensalgorithmen von Public Blockchains, Marktmanipulation in Kryptomärkten und der Entwicklung von Standards für digitale Vermögenswerte.

Zu seinen aktuellen Forschungsthemen gehören die Rolle von dezentralen digitalen Vermögenswerten im Metaverse und deren sozialen und wirtschaftlichen Auswirkungen. Darüber hinaus konzentriert er sich auf die Entwicklung einer Taxonomie für digitale Vermögenswerte und die Evaluierung der Nutzung von digitalen Vermögenswerten im Metaverse auf der Grundlage realer Smart-Contract-Interaktionen.




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

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