Designing a Blockchain-Based Data Market and Pricing Data to Optimize Data Trading and Welfare

ABSTRACT

While a wealth of potentially valuable data is generated and stored every year, many businesses suffer from inefficiencies, information asymmetries, and high storage costs, and lack knowledge on how to monetize their data assets. Blockchain is said to offer crucial building blocks to enable a verified, traceable exchange and trading with sensitive data goods and to address current challenges. While the technology’s potentials for decentralized data markets have been discussed, the question of how to realize it to optimize trading and welfare remains open. Applying design-science research methods and computational simulation to a real-world business-oriented blockchain project, this study proposes a market model. By adopting the consortium blockchain, we are thinking outside the confines of tokens tied to a blockchain when applying blockchain to the data trading market. Our marketplace is designed outside the speculative tokens space and can focus on the data trading marketplace. We evaluate the effects of different pricing functions on market welfare and trading in on-chain data goods. The results indicate that data trading and welfare can be maximized through a logarithmic pricing function. Further, in a market of heterogeneous agents, unexpectedly, we observe a tipping point in transaction fees above which market operations collapse. Monitoring the market’s consumer price elasticity helps us to avoid this collapse node, and we can also impact it by controlling transaction costs. Academics and practitioners can learn about the idiosyncrasies of blockchain in market design and operation.

KEYWORDS AND PHRASES:

• Blockchain
• data market design
• distributed ledger
• information pricing
• data monetization
• data trading
• data pricing
• consortium blockchain

Acknowledgments

The authors thank the cardossier association and especially its member firms AMAG Import AG, Audatex Schweiz GmbH, Auto-I-Dat AG, and AXA for their time and participation in workshops and interviews, as well as their valuable inputs. We also thank Mirko Richter, who conducted his master’s thesis during the course of this project and supported us in our data collection and analysis.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

¹ For simplicity, and without loss of generality, we consider that buyers are only interested in published records.

Additional information

Notes on contributors

Ingrid Bauer-Hänsel

Ingrid Bauer-HÄnsel ([email protected]; corresponding author) is an assistant professor at the University of St. Gallen, Switzerland.. She holds an M.Sc. in information systems from the Copenhagen Business School, and a Ph.D. from the University of Zürich. Her research focuses on interorganizational systems, decentralized data platforms and markets, and token systems. She led the industry collaboration on this project.

Qianyu Liu

Qianyu Liu ([email protected]) is a Ph.D. student in the Blockchain & Distributed Ledger Technologies group at the University of Zurich, Switzerland. Her research focuses on consortium blockchain and blockchain applications.

Claudio J. Tessone

Claudio J. Tessone ([email protected]) is a professor in Blockchain & Distributed Ledger Technologies at the University of Zurich and chairman of the UZH Blockchain Center. His main interests are complex socioeconomic and sociotechnical systems from an interdisciplinary perspective, aiming at unveiling links between microscopic agent behaviors, the rules they follow, and a system’s emerging global properties. Blockchain-based systems, cryptocurrencies, and other digital tokens are pillars of his current activities. This includes crypto-economics, big data blockchain analytics and forensics, and the analysis of economic incentives, which are fundamental to multiple blockchain platforms. He also directs the interdisciplinary UZH Summer School: Deep Dive into Blockchain and co-directs the Certificate of Advanced Studies on Blockchain at the University of Zurich.

Gerhard Schwabe

Gerhard Schwabe ([email protected]) is a professor in the Department of Informatics at the University of Zurich, where he leads the information management research group. He received his doctoral and postdoctoral education at the University of Hohenheim, Germany. Dr. Schwabe researches the intersection of collaborative technologies and information management. He has studied collaboration in commercial and government organizations at the granularity of dyads, small teams, large teams, organizations, communities, and social networks, frequently in collaboration with companies and public organizations. He has published numerous papers in major journals and conference proceedings, focusing on information systems and computer science.