KNOWLEDGE SHARING IN A SMOKING CESSATION ONLINE COMMUNITY: A PRIVACY CALCULUS PERSPECTIVE

The paper presents a study design intended to disentangle the various components of social support and privacy concerns related to knowledge-sharing in a smoking cessation online health community from a privacy calculus perspective. In the research model, social support confers benefits of informational support, emotional support, esteem support, and network support, all of which have a positive effect on knowledge-sharing behaviour therein. The privacy concerns, articulated in terms of risks, entail threat appraisals (perceived severity and perceived vulnerability) and coping appraisals (response efficacy and self-efficacy). Threat appraisals negatively affect knowledge-sharing in the smoking cessation OHC, whereas coping appraisals have a positive effect on the sharing. Under privacy calculus theory, the risk-benefit analysis determines individual users’ knowledge-sharing behaviour in a smoking cessation OHC. The individual user’s smoking cessation OHC usage experience and the stage of smoking cessation are set as moderators in the proposed research model to explore user differences in knowledge sharing behaviour in the smoking cessation OHC. This study may contribute to a comprehensive understanding of the core antecedents to knowledge-sharing in smoking cessation OHCs

Communicating Personal Health Information in Virtual Health Communities: An Integration of Privacy Calculus Model and Affective Commitment

Health consumers such as patients and caregivers often join virtual health communities (VHCs) to seek and provide health-related information and emotional support. To do so, they converse with other individuals in platforms such as public discussion boards and blogs. During these online conversations, people may communicate their personal health information (PHI) to others. A potential driver for this form of revealing PHI is the immediate positive outcomes that it can provide for contributors and the community. PHI disclosure, however, can entail privacy risks and concerns for community members, which may ultimately hamper their participation in those communities. Moreover, one’s emotional attachment to a VHC (namely, affective commitment) may influence one’s PHI sharing behaviors in that community. Thus, to understand how various factors impact communicating PHI in public VHC discussions, we drew on the privacy calculus model and the notion of affective commitment, developed a theoretical model, and empirically tested the model. To do so, we administered a survey to individuals from three different populations including students, faculty, and staff at a large university and visitors to clinics. We performed a set of hierarchical moderated multiple regressions on the dataset. The results revealed that privacy concerns along with expected personal and community-related outcomes of communicating PHI affected willingness to communicate PHI in public VHC discussions. The results, however, refuted the hypothesized direct and moderating effects of affective commitment on willingness to share PHI in these virtual platforms. The findings of this study provide contributions to research and practice

Digital Health Innovation: Exploring Adoption of COVID-19 Digital Contact Tracing Apps

With the outbreak of COVID-19, contact tracing is becoming a used intervention to control the spread of this highly infectious disease. This article explores an individual's intention to adopt COVID-19 digital contact tracing (DCT) apps. A conceptual framework developed for this article combines the procedural fairness theory, dual calculus theory, protection motivation theory, theory of planned behavior, and Hofstede's cultural dimension theory. The study adopts a quantitative approach collecting data from 714 respondents using a random sampling technique. The proposed model is tested using structural equation modeling. Empirical results found that the perceived effectiveness of privacy policy negatively influenced privacy concerns, whereas perceived vulnerability had a positive influence. Expected personal and community-related outcomes of sharing information positively influenced attitudes toward DCT apps, while privacy concerns had a negative effect. The intention to adopt DCT apps were positively influenced by attitude, subjective norms, and privacy self-efficacy. This article is the first to empirically test the adoption of DCT apps of the COVID-19 pandemic and contributes both theoretically and practically toward understanding factors influencing its widespread adoption

Extending the generalizability and pragmatic contributions to solve privacy paradox

Privacy issue has increasingly become an integral part of organizations and businesses that operate within the digital era. However, heretofore, there is a lack of a systematic literature review to help scholars to integrate what has been done in previous studies when privacy issues were addressed especially the privacy paradox that still perplexes both academia and practitioners alike. Furthermore, with the inconsistency of findings regarding the privacy paradox, there is also a need to support researchers in recognizing the substantial constructs to improve the results of their empirical papers. Therefore, this paper aims to serve as an integrated review to congregate constructs that can help scholars to improve the generalizability and pragmatic contributions when addressing privacy paradox issue. Besides the conclusion that there is a lack of empirical papers on privacy paradox published in the business, management and marketing journal publications, we also synthesize constructs such as the population of the study, methodology, cross-cultural aspect and context of the study to improve the extent of the generalizability and practical contributions of empirical paper related to the privacy paradox. The limitations and implications of this study are also discussed at the end of this paper

Understanding the Impact of Perceived Negative Consequences on Personal Health Information Disclosure: The Case of Ghana

In developing countries increased investments in electronic health record (EHR) systems are fueling efforts to digitize personal health information (PHI). However, in countries where widespread diseases such as HIV/AIDS are heavily stigmatized, people may not want to disclose their health information fearing that digitization may lead to privacy loss and negative consequences should unintended others know about their infection. Drawing on the privacy calculus, this study will use a scenario-based survey approach to examine the impacts of particular negative consequences (i.e. emotional, economic, social consequences) alongside trust and privacy concerns on individuals’ PHI disclosure decisions in digitized settings. The results are expected to provide insights into the impact of negative consequences and yield recommendations to practice on addressing such concerns about the privacy management of people’s PH

Do Individuals in Developing Countries Care about Personal Health Information Privacy? An Empirical Investigation

As developing countries migrate to electronic healthcare (e-health) systems, emerging case studies suggest concerns are being raised about the privacy and security of personal health information (PHI) (e.g., Bedeley & Palvia, 2014; Willyard, 2010). However, there is lack of consideration of PHI privacy in the development of e-health systems in these countries as developers and policy makers assume that individuals are in greater need of healthcare and may not care about issues such as privacy (Policy Engagement Network [PEN], 2010). To better understand these assumptions and concerns individuals may have about the digitization of their PHI, this study examined individuals’ privacy concerns regarding the use of electronic health record (EHR) systems by hospitals for storing and managing PHI. A survey was conducted on a sample of 276 individuals in Ghana, a Sub-Saharan African country. We analysed the dataset using t-test and analysis of variance (ANOVA). Contradicting the assumption underlying e-health systems development, the results demonstrated that whilst individuals are less concerned about the collection of their PHI by hospitals, they are highly concerned about unauthorised secondary use, errors, and unauthorize access regarding their PHI stored in EHR systems. These concerns are especially greater for individuals with high computer experience and those who are extremely concerned about their health. Furthermore, compared with women and older individuals (35 years or older), men and younger individuals (aged 18-24) are more concerned about the collection of their PHI by hospitals. Implications for research and practice are discussed

Examining Users’ Information Disclosure and Audience Support Response Dynamics in Online Health Communities: An Empirical Study

Online healthcare communities (OHCs) facilitate two-way interaction. Examining users’ information disclosure-audience support response dynamics can reveal insights for fostering a supportive environment, community engagement, bond formation, knowledge sharing, and sustained participation in OHCs. We propose a structural vector autoregression (SVAR) model of user disclosure and response dynamics in OHCs. Based on the health disclosure decision-making model and daily time series data, we examine the two-way interaction of two dimensions of disclosure efficacy with audience support response acceptance. Findings of the impulse response functions reveal that user information density leads to positive support response acceptance, whereas support response acceptance reduces the information density of a user post over time. Further, higher information efficacy leads to more support response acceptance with long run improved information efficacy. Theoretically, findings extend the disclosure decision-making model in OHCs. Practically, the results provide insights for OHC management to facilitate two-way dynamic users’ interactions

Examining Users’ Information Disclosure and Audience Support Response Dynamics in Online Health Communities: An Empirical Study

Online healthcare communities (OHCs) facilitate two-way interaction. Examining users’ information disclosure-audience support response dynamics can reveal insights for fostering a supportive environment, community engagement, bond formation, knowledge sharing, and sustained participation in OHCs. We propose a structural vector autoregression (SVAR) model of user disclosure and response dynamics in OHCs. Based on the health disclosure decision-making model and daily time series data, we examine the two-way interaction of two dimensions of disclosure efficacy with audience support response acceptance. Findings of the impulse response functions reveal that user information density leads to positive support response acceptance, whereas support response acceptance reduces the information density of a user post over time. Further, higher information efficacy leads to more support response acceptance with long run improved information efficacy. Theoretically, findings extend the disclosure decision-making model in OHCs. Practically, the results provide insights for OHC management to facilitate two-way dynamic users’ interactions

Social Media Analytics and Information Privacy Decisions: Impact of User Intimate Knowledge and Co-ownership Perceptions

Social media analytics has been recognized as a distinct research field in the analytics subdomain that is developed by processing social media content to generate important business knowledge. Understanding the factors that influence privacy decisions around its use is important as it is often perceived to be opaque and mismanaged. Social media users have been reported to have low intimate knowledge and co-ownership perception of social media analytics and its information privacy decisions. This deficiency leads them to perceive privacy violations if firms make privacy decisions that conflict with their expectations. Such perceived privacy violations often lead to business disruptions caused by user rebellions, regulatory interventions, firm reputation damage, and other business continuity threats. Existing research had developed theoretical frameworks for multi-level information privacy management and called for empirical testing of which constructs would increase user self-efficacy in negotiating with firms for joint social media analytics decision making. A response to this call was studied by measuring the constructs in the literature that lead to normative social media analytics and its information privacy decisions. The study model was developed by combining the relevant constructs from the theory of psychological ownership in organizations and the theory of multilevel information privacy. From psychological ownership theory, the impact that intimate knowledge had on co-ownership perception of social media analytics was added. From the theory of multi-level information privacy, the impact of co-ownership perception on the antecedents of information privacy decisions: the social identity assumed, and information privacy norms used were examined. In addition, the moderating role of the cost and benefits components of the privacy calculus on the relationship between information privacy norms and expected information privacy decisions was measured. A quantitative research approach was used to measure these factors. A web-based survey was developed using survey items obtained from prior studies that measured these constructs with only minor wording changes made. A pilot-study of 34 participants was conducted to test and finalize the instrument. The survey was distributed to adult social media users in the United States of America on a crowdsourcing marketplace using a commercial online survey service. 372 responses were accepted and analyzed. The partial least squares structural equation modeling method was used to assess the model and analyze the data using the Smart partial least squares 3 statistical software package. An increase in intimate knowledge of social media analytics led to higher co-ownership perception among social media users. Higher levels of co-ownership perception led to higher expectation of adoption of a salient social identity and higher expected information privacy norms. In addition, higher levels of expectation of social information privacy norm use led to normative privacy decisions. Higher levels of benefit estimation in the privacy calculus negatively moderated the relationship between social norms and privacy decision making. Co-ownership perception did not have a significant effect on the cost estimation in social media analytics privacy calculus. Similarly, the cost estimation in the privacy calculus did not have a significant effect on the relationship between information privacy norm adoption and the expectation of a normative information privacy decision. The findings of the study are a notable information systems literature contribution in both theory and practice. The study is one of the few to further develop multilevel information privacy theory by adding the intimate knowledge construct. The study model is a contribution to literature since its one of first to combine and validate elements of psychological ownership in organization theory to the theory of multilevel information privacy in order to understand what social media users expect when social media analytics information privacy decisions are made. The study also contributes by suggesting approaches practitioners can use to collaboratively manage their social media analytics information privacy decisions which was previously perceived to be opaque and under examined. Practical suggestions social media firms could use to decrease negative user affectations and engender deeper information privacy collaboration with users as they seek benefit from social media analytics were offered