Document (#43618)

Author

Fox, G.
Werff, L. van der
Rosati, P.
Takako Endo, P.
Lynn, T.

Title

Examining the determinants of acceptance and use of mobile contact tracing applications in Brazil : an extended privacy calculus perspective

Source

Journal of the Association for Information Science and Technology. 73(2022) no.7, S.944-967

Year

2022

Abstract

Mobile contact tracing applications have emerged as a potential solution to track and reduce the transmission of viruses such as Covid-19. These applications require the disclosure of potentially sensitive personal information thus generating understandable implications for personal privacy. This research aims to determine the factors driving acceptance of these applications, with acceptance represented by three distinct variables, namely usage intentions, willingness to disclose personal data, and willingness to rely on health advice. The study examines the influence of perceived privacy, social influence, and benefits on acceptance of contact tracing applications among a sample of 1,114 Brazilian citizens. The study leverages social contract theory to demonstrate the importance of perceived control and perceived surveillance in the formation of individuals' perceptions of privacy. Integrating privacy calculus theory with social contract theory to include reciprocity and social influence, our findings suggest that perceived privacy, reciprocal benefits, and social influence all positively influence individuals' intentions to download or continue the use of contact tracing applications, while intentions to disclose information are influenced by adoption intentions, perceived privacy, and reciprocal benefits and individuals' willingness to rely on contact tracing applications for health advice is influenced by reciprocal benefits and disclosure intentions.

Content

Vgl.: https://asistdl.onlinelibrary.wiley.com/doi/10.1002/asi.24602.

Location

Brasilien

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5. Martin, K.; Shilton, K.: Why experience matters to privacy : how context-based experience moderates consumer privacy expectations for mobile applications (2016) 0.25

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