A Captology Study on Behavior Model for Persuasive Ubiquitous Technology (original) (raw)
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The popularization of smartphones has brought about substantial changes in location-based services (LBS). Advances in wireless communication technology have allowed affordable data service fees, and current smartphones are equipped with GPS; as a consequence, LBS applications are emerging as next-generation 'killer apps.' However, the diffusion of LBS has raised privacy concerns due to the potential abuse of location information. This study aims to validate a research model focusing on privacy concerns as moderators of the post-adoptive behaviors associated with LBS applications. Based on risky shift phenomenon research, the study seeks to test the effects of the major variables of UTAUT on LBS usage intention and actual use, as well as examine how these relationships differ according to the level of an individual's privacy concerns. We test the hypotheses using a survey with 234 users of LBS applications. The research findings support the hypotheses regarding the effects of performance expectancy and effort expectancy on LBS usage intention but do not support the hypothesis regarding the effect of social influence. In addition, the causal path from usage intention to actual use was significant. Group comparisons showed that the moderating effect of privacy concerns on performance expectancy and continuous usage intension is stronger in conjunction with low-privacy concerns, as shown in previous LBS research; however, the moderating effect on social influence and usage intention is stronger in conjunction with high privacy concerns. This finding can be explained by the risky shift phenomenon. Implications are discussed regarding the dual roles of privacy concerns in the post-adoptive behaviors of LBS users.
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As with all the major advances in information and communication technology, ubiquitous computing (ubicomp) introduces new risks to individual privacy. Our analysis of privacy protection in ubicomp has identified four layers through which users must navigate: the regulatory regime they are currently in, the type of ubicomp service required, the type of data being disclosed, and their personal privacy policy. We illustrate and compare the protection afforded by regulation and by some major models for user control of privacy. We identify the shortcomings of each and propose a model which allows user control of privacy levels in a ubicomp environment. Our model balances the user's privacy preferences against the applicable privacy regulations and incorporates five types of user controlled "noise" to protect location privacy by introducing ambiguities. We also incorporate an economics-based approach to assist users in balancing the trade-offs between giving up privacy and receiving ubicomp services. We conclude with a scenario and heuristic evaluation which suggests that regulation can have both positive and negative influences on privacy interfaces in ubicomp and that social translucence is an important heuristic for ubicomp privacy interface functionality.