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

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 block chain 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.