Paper Number
ICIS2025-2011
Paper Type
Complete
Abstract
Decentralized Finance (DeFi) markets exhibit sharp volatility and user behaviors that defy classical models of rationality. Recent data reveals Total Value Locked (TVL) swings of over 50% in DeFi protocols in response to market sentiment shifts, suggesting decision-making shaped by sentiment and uncertainty rather than traditional economic models. This paper proposes Quantum Decision Theory (QDT) as a framework for analyzing DeFi user behavior under ambiguity and conflicting information. QDT concepts such as superposition, interference, and quantum probability offer insights into yield farming, cross-chain bridging, and governance participation. We develop a conceptual model linking DeFi environments to user cognition through QDT, explaining anomalies such as extreme sentiment amplification, paradoxical risk preferences, and market cascades. This research contributes to IS literature by introducing non-classical decision theory to blockchain research, identifying ‘cognitive risk’ factors and suggesting interfaces that account for quantum-like decision patterns as design concerns for DeFi protocols.
Recommended Citation
Chaturvedi, Alok R. and Guru Muniasamy, Ilango, "Beyond Rationality and Noise: Understanding DeFi User Behavior through Quantum Decision Theory" (2025). ICIS 2025 Proceedings. 6.
https://aisel.aisnet.org/icis2025/blockchain/blockchain/6
Beyond Rationality and Noise: Understanding DeFi User Behavior through Quantum Decision Theory
Decentralized Finance (DeFi) markets exhibit sharp volatility and user behaviors that defy classical models of rationality. Recent data reveals Total Value Locked (TVL) swings of over 50% in DeFi protocols in response to market sentiment shifts, suggesting decision-making shaped by sentiment and uncertainty rather than traditional economic models. This paper proposes Quantum Decision Theory (QDT) as a framework for analyzing DeFi user behavior under ambiguity and conflicting information. QDT concepts such as superposition, interference, and quantum probability offer insights into yield farming, cross-chain bridging, and governance participation. We develop a conceptual model linking DeFi environments to user cognition through QDT, explaining anomalies such as extreme sentiment amplification, paradoxical risk preferences, and market cascades. This research contributes to IS literature by introducing non-classical decision theory to blockchain research, identifying ‘cognitive risk’ factors and suggesting interfaces that account for quantum-like decision patterns as design concerns for DeFi protocols.
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