Towards Models of the Economic Value of Interdependent Privacy in Social App Adoption Scenarios
Open Access
- Author:
- Pu, Yu
- Graduate Program:
- Information Sciences and Technology
- Degree:
- Doctor of Philosophy
- Document Type:
- Dissertation
- Date of Defense:
- December 06, 2016
- Committee Members:
- Jens Grossklags, Dissertation Advisor/Co-Advisor
Jens Grossklags, Committee Chair/Co-Chair
Mary Beth Rosson, Committee Member
Peng Liu, Committee Member
S. Sundar Shyam, Outside Member - Keywords:
- Third-party Social Apps
App Data Collection Context
Interdependent Privacy
Value of Privacy
Conjoint Analysis
Structural Equation Modeling
Online Survey Study
Sharing Anonymity - Abstract:
- In the context of third-party social apps, the problem of interdependency of privacy refers to users making app adoption decisions which cause the collection and utilization of personal information of users’ friends. In contrast, users’ friends have typically little or no direct influence over these decision-making processes. While the issue of interdependent privacy grows in practical importance, only a limited number of research studies have appeared on this subject. To address this literature gap, in this dissertation, we discuss three studies that address the problem space of interdependent privacy in social app adoption scenarios. More specifically, this dissertation focuses on quantifying and explaining the monetary value which app users place on their friends’ information, i.e., value of interdependent privacy. In Study 1, we conduct a full-profile conjoint analysis study with two treatment conditions which vary the app data collection context (i.e., to which degree the functionality of the app makes it necessary for the app developer to collect friends’ information). Analyzing the data, we are able to quantify how much monetary value app users place on their friends’ and their own personal information in each context. Combining these valuations with the responses to a comprehensive survey, we apply structural equation modeling (SEM) analysis to investigate the roles of privacy concern, its antecedents, as well as app data collection context to work towards a model of interdependent privacy for the scenario of social app adoption. Complementing Study 1, our second study aims to further explain the valuation of interdependent privacy. In particular, research indicates that social capital, which is an immaterial resource that can yield positive social outcomes, plays an important role in individuals’ decision-making. Motivated by these works, we investigate the complex and still undetermined relationship between interdependent privacy value and social capital. In addition, in order to gain a comprehensive understanding of interdependent privacy valuation, our study also examines its relationships with factors such as individuals’ number of friends within SNSs, and demographics. With Study 3, we explore important contextual factors that affect the value which app users attribute to their friends’ information. In particular, we focus on understanding the impact of sharing anonymity (i.e., whether disclosure of friends’ information is anonymous) on the valuation of interdependent privacy. To address this research goal, we conduct a between-subject, choice- based conjoint analysis study with 4 treatments (2 sharing anonymity × 2 context relevance). Our study confirms the important role that sharing anonymity plays in interdependent privacy valuation. Our research contributes to a better understanding of individuals’ attitudes and behaviors towards interdependent privacy issues associated with social apps. Based on this understanding, we offer insights, such as suggestions to redesign app permission systems, as well as to introduce new privacy polices, for better addressing individuals’ own and their friends’ privacy preferences.