Web3 Adoption, Bit by Bit: A Quantitative Analysis of User Adoption of NFT-Enabled Web3 Applications

Abstract

This thesis investigates user adoption of NFT-enabled Web3 applications. The objective of this study is to identify the most significant factors that influence user adoption of NFT-enabled Web3 applications in gaming, sports collectibles, and metaverse categories. This paper employed a quantitative research design and utilized data from decentralized applications built on public blockchain infrastructure to conduct a comprehensive empirical analysis of the subject matter. A least squares dummy variable (LSDV) regression model, with panel data of daily observations across 12 NFT applications from 1st January 2020 to 31st December 2022, was used to analyze the data. The study identified several independent variables that have a statistically significant relationship with the dependent variable, the number of unique buyers. These variables include cryptocurrency markets, macro indicators from traditional financial markets, scalability of the underlying blockchain, and security of the application. The study concludes that these parameters are the most significant factors influencing user adoption of NFT-based applications in gaming, sports collectibles, and metaverse categories. Through a comprehensive empirical analysis, this study contributes to the growing body of knowledge on user adoption in NFT-enabled Web3 applications and provides recommendations for companies building such applications. As the NFT-enabled Web3 applications continue to evolve, it will be important for companies to stay attuned to the identified factors and to adapt their user adoption strategies accordingly. The future of Web3 is promising, but success will depend on companies’ ability to understand and leverage the key factors influencing user adoption.