Advisor

Warkentin, Merrill.

Committee Member

Collier, Joel E.

Committee Member

Marett, Kent.

Committee Member

Crossler, Robert E.

Committee Member

Otondo, Robert F.

Date of Degree

5-1-2017

Document Type

Dissertation - Open Access

Major

Business Information Systems

Degree Name

Doctor of Philosophy

Abstract

Personal mobile devices (PMDs) initiated a multi-dimensional paradigmatic shift in personal computing and personal information collection fueled by the indispensability of the Internet and the increasing functionality of the devices. From 2005 to 2016, the perceived necessity of conducting transactions on the Internet moved from optional to indispensable. The context of these transactions changes from traditional desktop and laptop computers, to the inclusion of smartphones and tablets (PMDs). However, the traditional privacy calculus published by (Dinev and Hart 2006) was conceived before this technological and contextual change, and several core assumptions of that model must be re-examined and possibly adapted or changed to account for this shift. This paradigm shift impacts the decision process individuals use to disclose personal information using PMDs. By nature of their size, portability, and constant proximity to the user, PMDs collect, contain, and distribute unprecedented amounts of personal information. Even though the context within which people are sharing information has changed significantly, privacy calculus research applied to PMDs has not moved far from the seminal work by Dinev and Hart (2006). The traditional privacy calculus risk-benefit model is limited in the PMD context because users are unaware of how much personal information is being shared, how often it is shared, or to whom it is shared. Furthermore, the traditional model explains and predicts intent to disclose rather than actual disclosure. However, disclosure intentions are a poor predictor of actual information disclosure. Because of perceived indispensability of the information and the inability to assess potential risk, the deliberate comparison of risks to benefits prior to disclosure—a core assumption of the traditional privacy calculus—may not be the most effective basis of a model to predict and explain disclosure. The present research develops a Personal Mobile Device Privacy Calculus model designed to predict and explain disclosure behavior within the specific context of actual disclosure of personal information using PMDs.

URI

https://hdl.handle.net/11668/16646

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