A Discrepancy between Objective and Perceived Privacy Risks? Understanding Messaging Service’s Discontinuance Usage

The number of users discontinuing messaging services due to perceived privacy risks has grown rapidly in recent months. Still, research on privacy risks in this context has not received much attention. We aim to examine the impact of objective and perceived privacy risks on discontinuance usage. To determine the level of objective privacy risks, we analyze the privacy policy of the messaging service WhatsApp. So far, we identify aggregation, secondary use, identification, and increased accessibility to be the most prevalent objective risks. We propose a longitudinal design to capture individuals’ perceived privacy risks and test the influence of both risk dimensions on the discontinued use of messaging services. We contribute to literature by disentangling the interplay of objective and perceived privacy risks on discontinuance

PERCEIVED PRIVACY VIOLATIONS THROUGH UNAUTHORIZED SECONDARY USE – DIVING INTO USERS’ PERCEPTIONS AND RESPONSES

We see more and more incidents where users’ information collected by digital services is shared with external parties. Users becoming aware of such information (mis-)uses may perceive a privacy violation. In this study, we want to understand when, why, and how such external unauthorized secondary use (EUSU) is perceived as a privacy violation and what consequences such a perception entails. Employing the Critical Incident Technique (CIT), we inductively derive characteristics of real-world incidents of perceived privacy violations through EUSU and users’ perceptions and responses thereto. We present preliminary results of our qualitative data analysis as well as potential contributions of this research-in-progress study. As a next step, we plan to relate characteristics with responses through Qualitative Comparative Analysis (QCA)

Perceived privacy violations through unauthorized secondary use - diving into user's perceptions and responses

We see more and more incidents where users’ information collected by digital services is shared with external parties. Users becoming aware of such information (mis-)uses may perceive a privacy violation. In this study, we want to understand when, why, and how such external unauthorized secondary use (EUSU) is perceived as a privacy violation and what consequences such a perception entails. Employing the Critical Incident Technique (CIT), we inductively derive characteristics of real-world incidents of perceived privacy violations through EUSU and users’ perceptions and responses thereto. We present preliminary results of our qualitative data analysis as well as potential contributions of this research-in-progress study. As a next step, we plan to relate characteristics with responses through Qualitative Comparative Analysis (QCA)

Using Active Privacy Transparency to Mitigate the Tension Between Data Access and Consumer Privacy

Recently, news exposure about privacy practices has brought substantial negative effects on companies’ reputation and trust, which, in essence, reflects the escalating tension between data access and privacy protection that companies are currently facing. Accordingly, we design an active privacy transparency measure and implement it on our self-developed app. Through a two-task experiment, we simultaneously explore the profound and immediate effects of privacy transparency on firms and the underlying mechanisms. Results from our analyses show that active privacy transparency significantly mitigates users perceived psychological contract violations, which in turn helps companies prevent negative word-of-mouth and loss of trust. Moreover, it also ensures companies’ immediate access to user data, and the moderating role of privacy literacy provides an explanation for this insignificant effect and previous inconsistent findings. More interestingly, we find that active privacy transparency might better elicit users’ actual privacy preferences and help companies identify their targeted users

It takes a society to protect children's privacy rights

Privacy-related research spans multiple disciplines and is centuries old. The topic of children's privacy is a complicated and multi-faceted area of privacy research. The responsibility for teaching children about privacy usually falls on their parents' and carers' shoulders. This responsibility can be quite challenging for them to embrace, with rapidly changing technological advances across the globe and difficulties being exacerbated by the combined efforts of multinational organizations striving to gather their data. This research attempts, first, to explore the concept of privacy in the existing research literature, and particularly in the online context. The authors then seek to identify the challenges faced by parents related to their children's privacy. In particular: (1) what are the difficulties with respect to citizens' understanding what privacy means, and (2) in conveying its import to children? We conclude that everyone has a role to play in shoring up our children's privacy. It starts with the parents, but involves every one of us

Empirical Test Guidelines for Content Validity: Wash, Rinse, and Repeat until Clean

Empirical research in information systems relies heavily on developing and validating survey instruments. However, researchers’ efforts to evaluate content validity of survey scales are often inconsistent, incomplete, or unreported. Thjs paper defines and describes the most significant facets of content validity and illustrates the mechanisms through which multi-item psychometric scales capture a latent construct’s content. We discuss competing methods and propose new methods to assemble a comprehensive set of metrics and methods to evaluate content validity. The resulting recommendations for researchers evaluating content validity emphasize an iterative pre-study process (wash, rinse, and repeat until clean) to objectively establish “fit for purpose” when developing and adapting survey scales. A sample pre-study demonstrates suitable methods for creating confidence that scales reliably capture the theoretical essence of latent constructs. We demonstrate the efficacy of these methods using a randomized field experiment

Essays on Individuals’ Information Assessment, Information Disclosure, Participation, and Response Behaviors in Online Health Communities

The emergence of online health communities (OHCs) has enabled the use of information technologies to address some social and health needs including but not limited to emotional, social, and health-related issues. This information age has encouraged user generated (UG) content, which facilitates both peer-to-peer and business-to-peer interconnections. This rich and active information epoch (i.e., OHCs) is distinct in that value is generated when peers or participants—who may be content generators and/or content consumers—interact together by exchanging information and receiving supports aimed at addressing their specific needs; and this is made possible through the online platforms or support groups acting as the intermediary among users. In this dissertation, I explore the dynamics that take place in OHCs by answering varied sets of questions and addressing and stretching different scholarly discourses including individuals’ information assessment, information disclosure, participation, and response behaviors in OHCs from a variety of theoretical perspectives including disclosure decision-making model and social presence theory, using diverse methodologies such as text analytics, two-stage least squares regression technique, decision trees analysis, and vector autoregression models in the OHC context. The overarching research question is: How does assessment of information and receiver influence patients’ disclosure ability and what user information disclosure mechanisms elicit effective support behaviors in online health communities? Patients with different disease types visit OHCs to get support and this support is made possible because patients participate by interacting with peers and providing responses to each other’s discussion. Support behaviors, especially in the OHC context, is a concept that covers facets such as, provision of response; interactivity or participation in discussions; relationship management; and offering helpful, appropriate, and relevant feedback responses to meet specific information, social, or emotional needs (Huang et al., 2019; Nambisan et al., 2016; Chen et al., 2019). By exploring the research question and with the unique features that these OHC platforms exhibit—the sharing of information, participation, and receiving of supports—these essays make the following contributions. Theoretically, the findings reveal that a patient’s disease type, the sensitivity of information being disclosed, and patient’s expectation of a response show unique effects on disclosure efficacy. These factors constitute mechanisms by which patients in OHCs are motivated to disclose health information in granular forms that elicit effective community responses and feedback. This information exchange mechanisms thereby, facilitate active community participation through giving or receiving of support, and thus, fostering a dynamic interplay between individuals’ disclosure and response behaviors in the online context. Practically, online health community managers can design their platforms to provide automated and customizable tools that improve patients’ information density and information breadth skills for effective response generation; and from the results, platform management can better understand users that are motivated to participate through giving, thereby encouraging those that are weak in receiving. Also, platform managers can improve the skills of those who are weak in giving for users that are motivated to participate through receiving. Essay 1: Promoting Participants’ Information Disclosure and Response Behaviors in Online Health Communities: Disclosure Decision-Making Model Perspective In this first essay, I extend the literature on information disclosure and the disclosure decision-making model (DD-MM) by examining the factors that influence information disclosure (disclosure efficacy) and the effects of disclosure efficacy on the response users receive (response efficacy) at the granular level. Until now, both concepts—disclosure efficacy and response efficacy have been conceptualized as single constructs. This current study breaks new grounds and broaden the DD-MM model by postulating that the subconstructs have different antecedents and consequences. By examining the relationships between the subconstructs of information assessment, disclosure efficacy, and response efficacy using the two-stage least squares regression method, the results reveal some insightful dynamics, otherwise not possible with unidimensional constructs. Essay 2: Investigation of non-linear effects of first impression cues on participation in online health communities: A decision tree induction theory development approach One notable phenomenon that prior literature has extensively explored in OHC platforms is user participation, which is a necessary condition for platform sustainment and value generation. Extant research has studied user participation as a form of giving, that is, how much users participate in online platforms by generating content (e.g., posting messages, replying to messages, or posting pictures).However, participation in OHC platforms can also take the form of receiving (the consumption for content that has been generated – e.g., reading other’s posts, gaining knowledge and support), and this has witnessed little attention in prior research. This third study argues that the giving and receiving participation is a reaction to user initial participation. In this second essay, based on social presence theory (SPT), I use decision tree analysis to interrogate the effect of first impression in the initial posts on users’ giving and receiving participation. The findings provide meaningful insights for advancing research and for assisting platform managers on what to focus on to encourage users’ giving or receiving participation on their platforms. Essay 3: User Two-way Communication Efficacy Behaviors in Online Health Communities: A Longitudinal Study In this second essay, I crack into some unsupported relationships between disclosure efficacy and response efficacy shown in the previous study, which could be due to the use of cross-sectional data in the analysis, giving nonsignificant findings. Over time, it is possible that the effectiveness of the response that disclosers receive could determine whether users will further disclose or not. For example, if a discloser does not receive valuable response that addresses his or her needs, he or she may stop posting or disclosing information on the platform, thus, leading to lurking behaviors or less recommendations for others to join the online platform. This current study proposes a two-way relationship between disclosure efficacy and response efficacy of users’ interactions in online health communities instead of looking at only the one-way relationship from disclosure efficacy to response efficacy (which showed some insignificant results). From an econometric perspective, time has been shown to play a dynamic role on variables and their relationships. Thus, this current paper uses dynamic vector autoregression (VAR) modeling technique with a longitudinal data set to investigate the one-way and two-way relationships between disclosure efficacy and response efficacy and their dimensions (information density and information breadth) and (information persuasiveness and response persuasiveness), respectively. The analysis reveals a recursive relationship between disclosure efficacy and response efficacy and some of their dimensions. This is a departure from some prior literature that proposed a static linear order in end-user information consumption. The significance of the nonlinear recursive relationship is marked extension of the DD-MM model by establishing the reenforcing effect of its key variables