This study seeks to clarify the nature of control in the context of information privacy to generate insights into the effects of different privacy assurance approaches on context-specific concerns for information privacy. We theorize that such effects are exhibited through mediation by perceived control over personal information and develop arguments in support of the interaction effects involving different privacy assurance approaches (individual self-protection, industry self-regulation, and government legislation). We test the research model in the context of location-based services using data obtained from 178 individuals in Singapore. In general, the results support our core assertion that perceived control over personal information is a key factor affecting context-specific concerns for information privacy. In addition to enhancing our theoretical understanding of the link between control and privacy concerns, these findings have important implications for service providers and consumers as well as for regulatory bodies and technology developers.
To date, many important threads of information privacy research have developed, but these threads have not been woven together into a cohesive fabric. This paper provides an interdisciplinary review of privacy-related research in order to enable a more cohesive treatment. With a sample of 320 privacy articles and 128 books and book sections, we classify previous literature in two ways: (1) using an ethics-based nomenclature of normative, purely descriptive, and empirically descriptive, and (2) based on their level of analysis: individual,group, organizational, and societal.Based upon our analyses via these two classification approaches, we identify three major areas in which previous research contributions reside: the conceptualization of information privacy, the relationship between information privacy and other constructs, and the contextual nature of these relationships.As we consider these major areas, we draw three overarching conclusions. First, there are many theoretical developments in the body of normative and purely descriptive studies that have not been addressed in empirical research on privacy. Rigorous studies that either trace processes associated with, or test implied assertions from, these value-laden arguments could add great value. Second, some of the levels of analysis have received less attention in certain contexts than have others in the research to date. Future empirical studies-both positivist and interpretive-could profitably be targeted to these under-researched levels of analysis. Third, positivist empirical studies will add the greatest value if they focus on antecedents to privacy concerns and on actual outcomes. In that light, we recommend that researchers be alert to an overarching macro model that we term APCO (Antecedents ? Privacy Concerns ? Outcomes).
Location-based services (LBS) use positioning technologies to provide individual users with reachability and accessibility that would otherwise not be available in the conventional commercial realm. While LBS confer greater connectivity and personalization on consumers, they also threaten users' information privacy through granular tracking of their preferences, behaviors, and identity. To address privacy concerns in the LBS context, this study extends the privacy calculus model to explore the role of information delivery mechanisms (pull and push) in the efficacy of three privacy intervention approaches (compensation, industry self-regulation, and government regulation) in influencing individual privacy decision making. The research model was tested using data gathered from 528 respondents through a quasi-experimental survey method. Structural equations modeling using partial least squares validated the instrument and the proposed model. Results suggest that the effects of the three privacy intervention approaches on an individual's privacy calculus vary based on the type of information delivery mechanism (pull and push). Results suggest that providing financial compensation for push-based LBS is more important than it is for pull-based LBS. Moreover, this study shows that privacy advocates and government legislators should not treat all types of LBS as undifferentiated but could instead specifically target certain types of services.