Date of Award

Spring 1-1-2014

Document Type

Thesis

Degree Name

Master of Science (MS)

First Advisor

Scott J. Savage

Second Advisor

Douglas Sicker

Third Advisor

David Reed

Abstract

The research estimates the value of online Smartphone privacy using Statistical regression models. Evidences examine that consumers are forced to provide their personal information for some monetary benefits. The research targets the Smartphone application market because of its increasing privacy challenges in the current application environment. It discusses the reasons for the need of intense research in this endeavor. In depth analysis on each of the "privacy permissions" that invoke consumer's personal information is conducted. Results show that consumers value privacy so much that they are willing to pay $6.78 for concealing location information, $2.29 to restrict access to camera, $3.13 for concealing billing information, and $4.99 to conceal their browsing history. The consumers are also willing to pay $2.62 for the apps that provide them functionalities using their calendar information. Consumers value app rating so much that they are willing to pay $2.37 for an app having one rating higher, which implies that they are reluctant to try new apps with low rating.

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