Open Collections

Zhang, Jundong

University of British Columbia

Although contact tracing apps are effective in containing the impacts of COVID-19, their centralized management model cause significant user concerns about privacy and information security. Blockchain-based contact tracing apps have received increasing attention as a better alternative. However, the adoption of blockchain-based solutions is slow. This paper investigates how user perceptions and technical features of blockchain-based contact tracing apps individually and jointly influence users' adoption intention in the short and long term. The collection of apps and users is viewed as a Complex Adaptive System. An Agent-Based Modeling technique is adopted in this paper, where users are regarded as agents. In addition, agents are adaptive to the environment and interact with each other according to behavioral rules. Via a trust-centered lens, several simulation studies were conducted with different pre-determined parameters to investigate the impacts of various characteristics of users and solutions. Finally, survey-based validations and sensitivity analyses were conducted to validate the rationality of the model. The results show that both cognitive and emotional trusts of the users are positive and crucial to the adoption diffusion. Regarding app characteristics, compatibility level and scalability resistance could positively affect adoption. Moreover, service providers can choose to invest in highly connected communities. This study takes the first step to developing a dynamic diffusion model of blockchain-based COVID-19 contact tracing apps. In addition, it provides theoretical and practical implications to facilitate the implementation of blockchain-based solutions.

Text

2023-03-30

Attribution-NonCommercial-NoDerivatives 4.0 International

http://hdl.handle.net/2429/84115

Business Administration - Management Information Systems

University of British Columbia

UBCV

http://creativecommons.org/licenses/by-nc-nd/4.0/