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Mobile application security: Role of perceived privacy as the predictor of security perceptions

Author

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  • Balapour, Ali
  • Nikkhah, Hamid Reza
  • Sabherwal, Rajiv

Abstract

Despite mobile applications being at the frontier of mobile computation technologies, security issues pose a threat to their adoption and diffusion. Recent studies suggest that security violations could be mitigated through improved security behaviors and attitudes, not just through better technologies. Existing literature on behavioral security suggests that one of the main predictors of users’ perceptions of security is their perceived privacy concerns. Using communication privacy management theory (CPM), this study examines the effects of privacy-related perceptions, such as privacy risk and the effectiveness of privacy policies, on the security perceptions of mobile app users. To empirically test the proposed theoretical model, two survey studies were conducted using mobile apps requesting less sensitive information (n = 487) and more sensitive information (n = 559). The findings show that the perceived privacy risk negatively influences the perceived security of the mobile apps; the perceived effectiveness of a privacy policy positively influences user perceptions of mobile app security; and perceived privacy awareness moderates the effect of perceived privacy risk on the perceived security of mobile apps. The results also suggest that users have different privacy-security perceptions based on the information sensitivity of the mobile apps. Theoretical and practical implications are discussed.

Suggested Citation

  • Balapour, Ali & Nikkhah, Hamid Reza & Sabherwal, Rajiv, 2020. "Mobile application security: Role of perceived privacy as the predictor of security perceptions," International Journal of Information Management, Elsevier, vol. 52(C).
    • Handle: RePEc:eee:ininma:v:52:y:2020:i:c:s0268401219309041
    DOI: 10.1016/j.ijinfomgt.2019.102063
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    Cited by:

    1. Ma, Chao & Wu, Jingyi & Sun, Heyuan & Zhou, Xin & Sun, Xiyan, 2023. "Enhancing user experience in digital payments: A hybrid approach using SEM and neural networks," Finance Research Letters, Elsevier, vol. 58(PB).
    2. Hong, Ying & Hu, Jiangting & Zhao, Yaxin, 2023. "Would you go invisible on social media? An empirical study on the antecedents of users' lurking behavior," Technological Forecasting and Social Change, Elsevier, vol. 187(C).
    3. Siqin, Tana & Yang, Lu & Chung, Sai-Ho & Wen, Xin, 2024. "Cross-channel influences in mobile-app-website e-commerce supply chains: When to weaken the influence?," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 182(C).
    4. Ibrahim Mutambik & John Lee & Abdullah Almuqrin & Waleed Halboob & Taha Omar & Ahmad Floos, 2022. "User concerns regarding information sharing on social networking sites: The user’s perspective in the context of national culture," PLOS ONE, Public Library of Science, vol. 17(1), pages 1-27, January.
    5. Shixingyue Hu & Yazao Yang, 2024. "Safety of female ride-hailing passengers: Perception and prevention," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-18, December.
    6. Arenas, Álvaro & Ray, Gautam & Hidalgo, Antonio & Urueña, Alberto, 2024. "How to keep your information secure? Toward a better understanding of users security behavior," Technological Forecasting and Social Change, Elsevier, vol. 198(C).
    7. Azman Ong, Mohd Hanafi & Yusri, Muhammad Yassar & Ibrahim, Nur Syafikah, 2023. "Use and behavioural intention using digital payment systems among rural residents: Extending the UTAUT-2 model," Technology in Society, Elsevier, vol. 74(C).

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