Algorithmic Resistance and Online Privacy: Extending the Meta-UTAUT Model with Particular Privacy Concerns
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Keywords:
algorithmic resistance intention, privacy concerns, Meta-UTAUT, perceived benefits
Abstract
This study delved into the perceived benefits and privacy concerns individuals face when interacting with algorithms, and explored their relation to algorithmic resistance. Based on technology acceptance research and online privacy studies, an extended Meta-UTAUT model was proposed. A total of 434 valid samples were obtained in China. The results show that perceived benefits (including performance expectancy, effort expectancy, social influence, and facilitating conditions) are negatively related to algorithmic resistance attitude. Moreover, concerns for technology and financial privacy are positively related to algorithmic resistance intention.This result identifies the aspects of privacy highly esteemed in the interaction between individuals and algorithms. Finally, the contributions, practical and theoretical significance, and limitations of this study were discussed.
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Published
2025-03-31
How to Cite
Shao, Z. (2025, March 31). Algorithmic Resistance and Online Privacy: Extending the Meta-UTAUT Model with Particular Privacy Concerns. International Journal of Applied Science, 8(1), p72. https://doi.org/https://doi.org/10.30560/ijas.v8n1p72
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