User information security behavior has been an area of growing demand in information systems (IS) research. Unfortunately, most of the previous research done in user information security behavior have been in broad contexts, therefore creating a gap in the literature of similar research that focuses on specific emerging technologies and trends. With the growing reliance on mobile devices to increase the flexibility, speed and efficiency in how we work, communicate, shop, seek information and entertain ourselves, it is obvious that these devices have become data warehouses and platform for data in transit. This study was an empirical and quantitative study that gathered data leveraging a web-survey. Prior to conducting the survey for the main data collection, a Delphi study and pilot study were conducted. Convenience sampling was the category of nonprobability sampling design used to gather data. The 7-Point Likert Scale was used on all survey items. Pre-analysis data screening was conducted prior to data analysis. The Partial Least Square Structural Equation Modeling (PLS-SEM) was used to analyze the data gathered from a total of 390 responses received. The results of this study showed that perceived threat severity has a negative effect on protection motivation, while perceived threat susceptibility has a positive effect on protection motivation. Contrarily, the results from this study did not show that perceived response cost influences protection motivation. Response efficacy and mobile self-efficacy had a significant positive influence on protection motivation. Mobile device security usage showed to be significantly influenced positively by protection motivation. This study brings additional insight and theoretical implications to the existing literature. The findings reveal the PMT’s capacity to predict user behavior based on threat and coping appraisals within the context of mobile device security usage. Additionally, the extension of the PMT for the research model of this study implies that mobile devices users also can take recommended responses to protect their devices from security threats.

The popularization of professional virtual communities (PVCs) as a platform for people to share experiences and knowledge has produced a paradox of convenience versus security. The desire to communicate results in disclosure where users experience ongoing professional and social interaction. Excessive disclosure and unsecured user security behavior in PVCs increase users’ vulnerability to technology threats. Nefarious entities frequently use PVCs such as LinkedIn to launch digital attacks. Hence, users are faced with a gamut of technology threats that may cause harm to professional and personal lives. Few studies, however, have examined users’ information security behavior and their motivation to engage in technology threat avoidance behavior in a PVC. This study tested a professional virtual community technology threat avoidance model empirically. The model was developed from the conceptualization of different aspects of the technology threat avoidance theory, social cognitive theory, and involvement theory through an integrated approach. This quantitative study employed a random sampling methodology. Prior to collecting data for the main study an expert panel review and a pilot study were conducted. A web-based survey designed with a 5-point Likert scale was distributed to 1285 LinkedIn members to gather self-reported data on users’ technology threat avoidance behavior. Confirmatory factor analysis (CFA) and structural equation modeling (SEM) were used to analyze the data gathered from 380 respondents. The results of the data analysis revealed that perceived susceptibility, perceived severity, and information security knowledge sharing are strong predictors of avoidance motivation. Information security knowledge sharing had the most significant predicting effect on avoidance motivation in PVCs. Also, self-efficacy, group norms, and avoidance motivation all have a significant predicting effect on users’ information security avoidance behavior in PVCs. However, information security experience and safeguarding measure cost do not have a significant predicting effect on users’ information security avoidance motivation. This study makes significant contributions to the IS body of knowledge and has implications for practitioners and academics. This study offers a comprehensive model through the integration of behavioral and cognitive theories to better understand user information security behavior in PVCs. The model also identifies essential elements to motivate users to engage in technology threat avoidance behavior.