Jeff H. Smith’s research while affiliated with Miami University and other places

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Publications (1)


Information Privacy and Correlates: An Empirical Attempt to Bridge and Distinguish Privacy-Related Concepts
  • Article

May 2013

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836 Reads

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444 Citations

Tamara Dinev

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Jeff H. Smith

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Paul Hart

Privacy is one of the few concepts that has been studied across many disciplines, but is still difficult to grasp. The current understanding of privacy is largely fragmented and discipline-dependent. This study develops and tests a framework of information privacy and its correlates, the latter often being confused with or built into definitions of information privacy per se. Our framework development was based on the privacy theories of Westin and Altman, the economic view of the privacy calculus, and the identity management framework of Zwick and Dholakia. The dependent variable of the model is perceived information privacy. The particularly relevant correlates to information privacy are anonymity, secrecy, confidentiality, and control. We posit that the first three are tactics for information control; perceived information control and perceived risk are salient determinants of perceived information privacy; and perceived risk is a function of perceived benefits of information disclosure, information sensitivity, importance of information transparency, and regulatory expectations. The research model was empirically tested and validated in the Web 2.0 context, using a survey of Web 2.0 users. Our study enhances the theoretical understanding of information privacy and is useful for privacy advocates, and legal, management information systems, marketing, and social science scholars.

Citations (1)


... Items (compared to human TA) References Perceived privacy differences I feel like I have more privacy when I use AI TA I am much more comfortable with the amount of privacy I have when using AI TA I think my privacy is more likely to be preserved when using AI TA (Dinev & Hart, 2006;Dinev et al., 2013;Fox et al., 2022) Perceived fairness differences AI TA is more consistent in their dealings with all students Generally, AI TA treats all students in a fairer and balanced way The assistance AI TA provides to students is more unbiased Overall, AI TA tries to meet students' needs more fairly (Beugre & Baron, 2001;Carr, 2007) Perceived service attitude differences AI TA act more friendly AI TA solve the problems more patiently AI TA show more enthusiastic service AI TA always think of students while serving (Kuo, 2009) Psychological safety differences I am less afraid to be myself when interacting with AI TA I am less afraid to express my opinions when interacting with AI TA AI TA provides a more speechsafe environment (Y. Zhang et al., 2010) Content courtesy of Springer Nature, terms of use apply. ...

Reference:

Human vs. AI: What makes students prefer to self-disclosure to AI teaching assistant? The effect of psychological safety and relationship norms
Information Privacy and Correlates: An Empirical Attempt to Bridge and Distinguish Privacy-Related Concepts
  • Citing Article
  • May 2013