Privacy in e-commerce: examining user scenarios and privacy preferences
Proceedings of the 1st ACM conference on Electronic commerce
E-privacy in 2nd generation E-commerce: privacy preferences versus actual behavior
Proceedings of the 3rd ACM conference on Electronic Commerce
Collaborative filtering with privacy via factor analysis
SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
Who wants to know what when? privacy preference determinants in ubiquitous computing
CHI '03 Extended Abstracts on Human Factors in Computing Systems
An Empirical Examination of the Concern for Information Privacy Instrument
Information Systems Research
Collaborative Filtering with Privacy
SP '02 Proceedings of the 2002 IEEE Symposium on Security and Privacy
HICSS '04 Proceedings of the Proceedings of the 37th Annual Hawaii International Conference on System Sciences (HICSS'04) - Track 7 - Volume 7
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
Location disclosure to social relations: why, when, & what people want to share
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Personalization versus Privacy: An Empirical Examination of the Online Consumer's Dilemma
Information Technology and Management
SVD-based collaborative filtering with privacy
Proceedings of the 2005 ACM symposium on Applied computing
Online information disclosure: Motivators and measurements
ACM Transactions on Internet Technology (TOIT)
Development of measures of online privacy concern and protection for use on the Internet
Journal of the American Society for Information Science and Technology
End-user privacy in human-computer interaction
Foundations and Trends in Human-Computer Interaction
Investigating Privacy Attitudes and Behavior in Relation to Personalization
Social Science Computer Review
Crowdsourcing user studies with Mechanical Turk
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Recommendation Agents for Electronic Commerce: Effects of Explanation Facilities on Trusting Beliefs
Journal of Management Information Systems
Timing is everything?: the effects of timing and placement of online privacy indicators
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Electronic Commerce Research
The Role of Push-Pull Technology in Privacy Calculus: The Case of Location-Based Services
Journal of Management Information Systems
Privacy-enhanced web personalization
The adaptive web
Context awareness by case-based reasoning in a music recommendation system
UCS'07 Proceedings of the 4th international conference on Ubiquitous computing systems
Privacy in Context: Technology, Policy, and the Integrity of Social Life
Privacy in Context: Technology, Policy, and the Integrity of Social Life
The impact of social navigation on privacy policy configuration
Proceedings of the Sixth Symposium on Usable Privacy and Security
AppAware: which mobile applications are hot?
Proceedings of the 12th international conference on Human computer interaction with mobile devices and services
With a little help from my friends: can social navigation inform interpersonal privacy preferences?
Proceedings of the ACM 2011 conference on Computer supported cooperative work
Utilizing implicit feedback and context to recommend mobile applications from first use
Proceedings of the 2011 Workshop on Context-awareness in Retrieval and Recommendation
The Effect of Online Privacy Information on Purchasing Behavior: An Experimental Study
Information Systems Research
A user-centric evaluation framework for recommender systems
Proceedings of the fifth ACM conference on Recommender systems
PET'04 Proceedings of the 4th international conference on Privacy Enhancing Technologies
Towards mobile intelligence: Learning from GPS history data for collaborative recommendation
Artificial Intelligence
User-selectable interactive recommendation system in mobile environment
Multimedia Tools and Applications
Explaining the user experience of recommender systems
User Modeling and User-Adapted Interaction
Helping users with information disclosure decisions: potential for adaptation
Proceedings of the 2013 international conference on Intelligent user interfaces
Location sharing privacy preference: analysis and personalized recommendation
Proceedings of the 19th international conference on Intelligent User Interfaces
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Recommender systems increasingly use contextual and demographical data as a basis for recommendations. Users, however, often feel uncomfortable providing such information. In a privacy-minded design of recommenders, users are free to decide for themselves what data they want to disclose about themselves. But this decision is often complex and burdensome, because the consequences of disclosing personal information are uncertain or even unknown. Although a number of researchers have tried to analyze and facilitate such information disclosure decisions, their research results are fragmented, and they often do not hold up well across studies. This article describes a unified approach to privacy decision research that describes the cognitive processes involved in users’ “privacy calculus” in terms of system-related perceptions and experiences that act as mediating factors to information disclosure. The approach is applied in an online experiment with 493 participants using a mock-up of a context-aware recommender system. Analyzing the results with a structural linear model, we demonstrate that personal privacy concerns and disclosure justification messages affect the perception of and experience with a system, which in turn drive information disclosure decisions. Overall, disclosure justification messages do not increase disclosure. Although they are perceived to be valuable, they decrease users’ trust and satisfaction. Another result is that manipulating the order of the requests increases the disclosure of items requested early but decreases the disclosure of items requested later.