Level: BA, MA 
Responsible person: Dr. Mark C. Ballandies
keywords: ABM/ agent-based modeling, crypto-economics, token engineering 

Blockchain-based token incentives have been shown to motivate individuals to achieve extraordinary outcomes, such as building global infrastructures and decentralizing governance and finance applications. Unlike traditional monetary incentives, token incentives have the potential to enhance intrinsic motivation, which positively influences human creativity and endurance—qualities essential for addressing global challenges. 

While initial experimental research has highlighted the promise of token incentives, it has also revealed potential pitfalls and complexities, particularly concerning interaction effects when multiple token incentives are employed. This thesis builds upon previous studies by conceptualizing and implementing an agent-based model to analyze the impact of blockchain-based token incentives on human motivation and key system metrics, such as information sharing, work performed, and innovation generated. 

The aim is to identify optimal token configurations that maximize these metrics across multiple dimensions, providing valuable insights to the fields of token engineering and cryptoeconomics. Furthermore, this research has practical implications, offering guidance to practitioners on effective token configurations. 

If this thesis is pursued as a bachelor's thesis, knowledge of agent-based models or a strong motivation and ability to quickly learn them is expected. 

[1] Ballandies, M.C., 2022. To incentivize or not: impact of blockchain-based cryptoeconomic tokens on human information sharing behavior. IEEE Access, 10, pp.74111-74130.