Paper Number
2659
Paper Type
Short
Description
Public blockchains with smart contract functionality have revolutionized IT operations by enabling fully algorithmic processes and providing high transparency through real-time and detailed information disclosure. Yet, the impact of this IT operational model on user engagement remains largely unexplored. Leveraging the context of stablecoin platforms, particularly in light of the Terra-LUNA crisis, we construct a large-scale individual-level panel dataset from April 12 to June 1, 2022, and apply a cross-platform difference-in-differences approach. We find that, during crises, users can effectively distinguish between algorithmic and institutional IT operations, as well as their respective types of operational transparency. We also find that the presence of attackers switches user preferences for operational transparency. Higher levels of transparency, characterized by frequent and detailed information disclosures, may be perceived as catalysts for attacks in the post-crisis period, significantly impacting user engagement.
Recommended Citation
Jin, Siyuan; CAI, Yuying; Qiu, Luying Iris; and Tam, Kar Yan, "Operational Transparency in the Blockchain Era: Examining the Impact of Different Types and Levels on User Engagement" (2024). ICIS 2024 Proceedings. 2.
https://aisel.aisnet.org/icis2024/user_behav/user_behav/2
Operational Transparency in the Blockchain Era: Examining the Impact of Different Types and Levels on User Engagement
Public blockchains with smart contract functionality have revolutionized IT operations by enabling fully algorithmic processes and providing high transparency through real-time and detailed information disclosure. Yet, the impact of this IT operational model on user engagement remains largely unexplored. Leveraging the context of stablecoin platforms, particularly in light of the Terra-LUNA crisis, we construct a large-scale individual-level panel dataset from April 12 to June 1, 2022, and apply a cross-platform difference-in-differences approach. We find that, during crises, users can effectively distinguish between algorithmic and institutional IT operations, as well as their respective types of operational transparency. We also find that the presence of attackers switches user preferences for operational transparency. Higher levels of transparency, characterized by frequent and detailed information disclosures, may be perceived as catalysts for attacks in the post-crisis period, significantly impacting user engagement.
Comments
21-UserBehavior