The Moderating Influence of Privacy Concern on the Efficacy of Privacy Assurance Mechanisms for Building Trust: A Multiple-Context Investigation

Privacy policy statements and privacy-assurance cues are among the most important website features that online providers use to alleviate web customers’ privacy concern. This study examines the moderating role of privacy concern on how the quality of privacy policy statements and privacy assurance cues contribute to increased trust, and the subsequent decision to disclose private information online. The results of this study show distinct behavioral differences between how individuals with high versus low privacy concern form their trust to disclose private information across different contexts. The paper adds to the trust literature by highlighting the influence of the customer’s level of privacy concern (as who) and of the context (as where). The paper also adds to the Elaboration Likelihood Model Theory (ELM) by demonstrating the combined moderating roles of context and degree of involvement (privacy concern)

EXPLORING THREAT-SPECIFIC PRIVACY ASSURANCES IN THE CONTEXT OF CONNECTED VEHICLE APPLICATIONS

Connected vehicles enable a wide range of use cases, often facilitated by smartphone apps and involving extensive processing of driving-related data. Since information about actual driving behavior or even daily routines can be derived from this data, the question of privacy arises. We explore the impact of privacy assurances on driving data sharing concerns. Specifically, we consider two data-intensive cases: usage-based insurance and traffic hazard warning apps. We conducted two experimental comparisons to investigate whether and how privacy-related perceptions about vehicle data sharing can be altered by different types of text-based privacy assurances on fictional app store pages. Our results are largely inconclusive, and we did not find clear evidence that text-based privacy guarantees can significantly alter privacy concerns and download intentions. Our results suggest that general and threat-specific privacy assurance statements likely yield no or only negligible benefits for providers of connected vehicle apps regarding user perceptions

Privacy in Online Social Networking: Applying a Privacy Calculus Model

The penetration rate continues to grow for social networking sites where individuals join a virtual community to socialize, make connections, and share opinions with those who have similar interests, while revealing personal information. However, online social networking presents a unique context with distinct privacy challenges. To understand information disclosure behavior in this context, we apply the extended privacy calculus model, developed by Dinev and Hart (2006a), which addresses the trade-off between the expected costs of privacy risk beliefs and the benefits of confidence and placement beliefs on the willingness to provide personal information. We further extend this model to include specific types of personal information, based on our proposed taxonomy of information integral to social networking. To test our research model, a questionnaire will be administered to undergraduate students, drawn from the mid-Atlantic U.S. For hypothesis testing, structural equations modeling will be used. The completion of this research-in-progress study is expected to contribute to our understanding of the types of information revealed in online social networking

Challenges Posed by Locational Data Privacy

With the growth of innovative positioning technologies, research into individuals’ behavioral challenges posed by location-based services has become increasingly popular in recent years. Scholars from various social sciences and management disciplines have attempted to address such challenges in order to understand and mitigate concerns for locational-data privacy. In view of the broad applicability of location-based services, we conduct a review of eight prominent IS journals to investigate and understand individuals’ behavioral challenges in using such services. Our review reveals that perception of individuals’ locational-data privacy is constantly influenced by their respective social norms, social reality, and cultural background as well as their current geographical or locational factor. In light of this finding, we outline possible directions and opportunities for further IS research around three philosophical approaches- “positivist”, “interpretivist”, and “critical”- with the aim of enriching our discussion of how and why individuals’ social reality and cultural factors influence their perception of locational- data privacy

Segmenting travelers based on responses to nudging for information disclosure

Digital technologies shape travel environments. Noticing online privacy issues, consumers can hold distinct attitudes towards disclosing personal information to service providers. We conducted a panel survey to gauge travelers’ willingness to share personal information with service providers, provided with different types of nudges. Based on the results of clustering analysis, two segments were identified: travelers who are reasonably willing to share (Privacy Rationalists) and those who are reluctant to share (Privacy Pessimists). This study provides empirical evidence of privacy segmentations in the travel context, which has not been reported before and thus deserves more attention from both researchers and practitioners

Impacts of Store Trust Antecedents on Willingness to Disclose Personal Data in Online Shopping

Personal data disclosure is crucially important to modern business, and specifically – to online stores. It is largely predicted by the willingness to disclose personal data that significantly varies among emerging economies due to impacts of numerous factors. One of the important factors that impacts willingness to disclose personal data in online shopping is trust in an online store. However, the importance of trust in a store partly occurs because it mediates effects of other antecedents. This study conceptualizes three groups of important antecedents: personal, infrastructural and store-related factors. The study tests indirect effects of the most typical factors from each group: general trust (personal factor), legal regulations (infrastructural factor) and presence of an off-line selling channel in addition to the online channel offered by a store (e-store factor) on willingness to disclose personal data online. The findings show that all these factors, mediated by store trust, have significant positive effects on willingness to disclose personal data. The findings contribute to the knowledge of the groups of factors that impact willingness to disclose personal data online and help to set directions for future research.Acknowledgement: this project has received funding from the Research Council of Lithuania (LMTLT), Agreement No S-MIP-19-1

Understanding Perceived Privacy: A Privacy Boundary Management Model

Consumer data is asset to organizations. Analysis of consumers’ transactional data helps organizations to understand customer behaviors and preferences. Before organizations could capitalize on these data, they ought to have effective plans to address consumers’ privacy concerns because violation of consumer privacy brings long-term reputational damage to organizations. This paper proposes and tests a Privacy Boundary Management Model that explains how consumers formulate and manage their privacy boundary. Survey data was collected from 98 users of online banking websites who have used the system for a minimum of six months. The PLS results showed that the model accounts for high variance in perceived privacy. Three elements of the FIPs (notice, access, and enforcement) have significant impact on perceived effectiveness of privacy policy. Perceived effectiveness in turns significantly influences privacy control and privacy risks. Privacy control affects perceived privacy and trust while privacy risk influences privacy concern and perceived privacy. Privacy concern has a negative relationship with perceived privacy and trust has a positive relationship with perceived privacy. The findings have novel implications for organizations and policy makers