Empirical evaluation of the revised technology acceptance model
Management Science
Software security and privacy risks in mobile e-commerce
Communications of the ACM
Evolution of mobile location-based services
Communications of the ACM - Mobile computing opportunities and challenges
Internet Users' Information Privacy Concerns (IUIPC): The Construct, the Scale, and a Causal Model
Information Systems Research
Privacy and Rationality in Individual Decision Making
IEEE Security and Privacy
What drives mobile commerce? An empirical evaluation of the revised technology acceptance model
Information and Management
Internet users' perceptions of 'privacy concerns' and 'privacy actions'
International Journal of Human-Computer Studies
An Extended Privacy Calculus Model for E-Commerce Transactions
Information Systems Research
Communications of the ACM - Urban sensing: out of the woods
ICMB '08 Proceedings of the 2008 7th International Conference on Mobile Business
Examining Trust in Information Technology Artifacts: The Effects of System Quality and Culture
Journal of Management Information Systems
The Role of Push-Pull Technology in Privacy Calculus: The Case of Location-Based Services
Journal of Management Information Systems
Does the technology acceptance model predict actual use? A systematic literature review
Information and Software Technology
HICSS '11 Proceedings of the 2011 44th Hawaii International Conference on System Sciences
Imagined communities: awareness, information sharing, and privacy on the facebook
PET'06 Proceedings of the 6th international conference on Privacy Enhancing Technologies
| Hi-index | 0.00 |
The use of mobile applications continues to experience exponential growth. Using mobile apps typically requires the disclosure of location data, which often accompanies requests for various other forms of private information. Existing research on information privacy has implied that consumers are willing to accept privacy risks for relatively negligible benefits, and the offerings of mobile apps based on location-based services (LBS) appear to be no different. However, until now, researchers have struggled to replicate realistic privacy risks within experimental methodologies designed to manipulate independent variables. Moreover, minimal research has successfully captured actual information disclosure over mobile devices based on realistic risk perceptions. The purpose of this study is to propose and test a more realistic experimental methodology designed to replicate real perceptions of privacy risk and capture the effects of actual information disclosure decisions. As with prior research, this study employs a theoretical lens based on privacy calculus. However, we draw more detailed and valid conclusions due to our use of improved methodological rigor. We report the results of a controlled experiment involving consumers (n=1025) in a range of ages, levels of education, and employment experience. Based on our methodology, we find that only a weak, albeit significant, relationship exists between information disclosure intentions and actual disclosure. In addition, this relationship is heavily moderated by the consumer practice of disclosing false data. We conclude by discussing the contributions of our methodology and the possibilities for extending it for additional mobile privacy research.