Paper Number
ICIS2025-1414
Paper Type
Complete
Abstract
The rapid growth of Decentralized Finance (DeFi) introduced significant complexity in on-chain transaction patterns, creating challenges in understanding user intent. Our research employed grounded theory methodology to develop a comprehensive taxonomy of DeFi transaction intents through the analysis of semistructured interviews with DeFi users, official tutorials of the platform, and community forum discussions. Beyond taxonomic classification, we proposed an integrated theoretical framework that explained the formation mechanisms of user intent (i.e., motivation), the systematic classification of expressed intents, and the action mechanisms through which abstract intent transformed into on-chain execution. The findings provide both academic insights into emergent DeFi behavior patterns and practical implications for protocol developers, regulators, and analytics seeking to better understand and serve DeFi users.
Recommended Citation
Mao, Qian'ang; Zhang, Yuxuan; Chen, Jiaman; and Yan, Jiaqi, "From Motivation to Execution: A Grounded Theory Study of the DeFi Transaction Intent Taxonomy" (2025). ICIS 2025 Proceedings. 3.
https://aisel.aisnet.org/icis2025/fintech/fintech/3
From Motivation to Execution: A Grounded Theory Study of the DeFi Transaction Intent Taxonomy
The rapid growth of Decentralized Finance (DeFi) introduced significant complexity in on-chain transaction patterns, creating challenges in understanding user intent. Our research employed grounded theory methodology to develop a comprehensive taxonomy of DeFi transaction intents through the analysis of semistructured interviews with DeFi users, official tutorials of the platform, and community forum discussions. Beyond taxonomic classification, we proposed an integrated theoretical framework that explained the formation mechanisms of user intent (i.e., motivation), the systematic classification of expressed intents, and the action mechanisms through which abstract intent transformed into on-chain execution. The findings provide both academic insights into emergent DeFi behavior patterns and practical implications for protocol developers, regulators, and analytics seeking to better understand and serve DeFi users.
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Comments
22-FinTech