Fig. 1. Research model. 3.2. Boundary coordination and turbulence Examples of the personal information that apps request are: (a) loca- tion; (b) contact lists and calendars; (c) photos and videos; (d) micro- phone; and (e) credit card information (Wottrich et al., 2018). Allowing an app to access such personal information can jeopardize user privacy (King & Jessen, 2010) through the misuse of personal information, selling users’ information to marketing and financial institutions without the users’ permission,’ insider disclosure, unauthorized access, and information theft (Dinev & Hart, 2006). In fact, mobile apps often make it mandatory for the user to share some private information to benefit from the basic functionalities of apps (Wottrich et al., 2018). On the other hand, users know that there is a chance of privacy invasion even with safeguards in place (Hong & Thong, 2013). Therefore, users must assess how the possible privacy risks would affect them when managing their privacy boundaries. Respondent demographics. Table 1 More sensitive information app users: Descriptives, Reliabilities, Average Variance Extracted, and Correlations. 5.D. = Standard deviation; CR = Composite Reliability; a = Chronbach’s Alpha; PA = Privacy Awareness; PR = Privacy Risk; PPE = Perceived Effectiveness of Privacy Policy; PS = Perceived Security. ** p < 0.01. * p < 0.05. The diagonal represents the square root of the AVE. Less sensitive information app users: Descriptives, Reliabilities, Average Variance Extracted, and Correlations. 5.D. = Standard deviation; CR = Composite Reliability; a = Chronbach’s Alpha; PA = Privacy Awareness; PR = Privacy Risk; PPE = Perceived Effectiveness « Privacy Policy; PS = Perceived Security. ** p < 0.01. * p < 0.05. The diagonal represents the square root of the AVE. Fig. 3. Interaction plots. Results of analysis. Table 4 Note: For the second survey, we changed mobile banking applications to Evernote * Dropped. Table Al PPE = Perceived effectiveness of privacy policy; PR = Perceived privacy risk; PA = Perceived privacy awareness; PS = Perceived security of mobile app. Principal Component Analysis. Table B1 References Acquisti, A., & Gross, R. (2006). Imagined communities: Awareness, information sharing, an privacy on the facebook. International workshop on privacy enhancing technologies. Rerlin Heidelhero: Snrincer26—58_ Appendix B
