Intention To Disclose Personal Information Via Mobile Applications: A Privacy Calculus Perspective

ASU Author/Contributor (non-ASU co-authors, if there are any, appear on document)
Charlie Chen Ph.D, Professor (Creator)
Appalachian State University (ASU )
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Abstract: This study aimed to investigate the issue of consumer intention to disclose personal information via mobile applications (apps). Drawing on the literature of privacy calculus theory, this research examined the factors that influence the trade-off decision of receiving perceived benefits and being penalized with perceived risks through the calculus lens. In particular, two paths of the direct effects on perceived benefits and risks that induce the ultimate intention to disclose personal information via mobile apps were proposed and empirically tested. The analysis showed that self-presentation and personalized services positively influence consumers’ perceived benefits, which in turn positively affects the intention to dis- close personal information. Perceived severity and perceived control serve as the direct antecedents of perceived risks that negatively affect the intention of consumers to disclose personal information. Compared with the perceived risks, the perceived benefits more strongly influence the intention to disclose personal information. This study extends the literature on privacy concerns to consumer intention to disclose personal information by theoretically developing and empirically testing four hypotheses in a research model. Results were validated in the mobile context, and implications and discussions were presented.

Additional Information

Wang, T., et al. (2016). "Intention to disclose personal information via mobile applications: A privacy calculus perspective." International Journal of Information Management 36(4): 531-542. j.ijinfomgt.2016.03.003. Publisher version of record available at:
Language: English
Date: 2016
Privacy calculus, Intention to disclose, Privacy concerns, Information privacy, Mobile applications

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