Design of blockchain applications and its impact on user behaviors
Network structure is essential for understanding the interactions and overall behavior of complex systems. Over the past decade, blockchain networks have attracted over 3 trillion dollars in assets, with hundreds of millions of users worldwide. This research seeks to explore the factors driving...
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Format: | Thesis-Doctor of Philosophy |
Language: | English |
Published: |
Nanyang Technological University
2024
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Online Access: | https://hdl.handle.net/10356/181233 |
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Institution: | Nanyang Technological University |
Language: | English |
Summary: | Network structure is essential for understanding the interactions and
overall behavior of complex systems. Over the past decade, blockchain
networks have attracted over 3 trillion dollars in assets, with
hundreds of millions of users worldwide. This research seeks to
explore the factors driving such widespread adoption, particularly in
the context of decentralized applications. It addresses key questions:
What motivates users to adopt blockchain technology? How does trust
propagate through these networks? And how can we better understand and
predict the value dynamics within these rapidly evolving ecosystems?
Additionally, the study examines how decentralized systems influence
user behavior across various platforms. The thesis also investigates
trader behavior in perpetual futures contracts through a
Systematization of Knowledge (SoK) approach. In 2023, the 24-hour
trading volume of perpetual futures contracts across all exchanges
exceeded 100 billion dollars, accounting for more than half of total
trading volume across blockchain products and exchanges. This raises
an important question: Why do users trust decentralized applications
with such significant sums of money? The research examines trader
dynamics on centralized (CEXs) and decentralized exchanges (DEXs),
proposing four models to classify exchange operations. Empirical
analysis shows that the relationship between market volatility and
trader activity varies significantly based on the exchange’s
mechanical design. Moreover, it reveals that in Virtual Automated
Market Making (VAMM) models, open interest impacts price volatility
differently for long and short positions. |
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