Document Type

Article

Publication Date

1-2020

Abstract

Privacy threats in a social media-enabled application (app) can originate from either the institution or other app users. Although privacy in social media is well studied, the role of social (peer) privacy concerns is largely unknown and most privacy studies on mobile apps focus on initial adoption and ignore long-term behavioral outcomes. Drawing on the privacy calculus theory, this study examines the impact of both institutional and social privacy concerns on long-term user engagement with social media-enabled apps. Findings from the analysis of 354 survey responses reveal that both institutional and social privacy concerns decrease engagement. Regarding the antecedents, the perceived sensitivity of information increases institutional privacy concerns. However, social privacy concerns are influenced by the perception of risk and control. Moreover, while the impacts of social and enjoyment benefits are expectedly positive, the perception of efficiency benefits decreases engagement. These findings are further investigated and validated through a follow-up text analysis study, suggesting that users who enjoy the functionality of these apps are more likely to express social privacy concerns and minimize their engagement. This study contributes to the literature of privacy on mobile apps by unraveling the intricate dynamics of privacy concerns and benefits in the social mobile era.

Comments

This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

© 2019 Published by Elsevier.

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Publication Title

Computers in Human Behavior

DOI

10.1016/j.chb.2020.106260

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