In today’s business world, information security is a top strategic issue. The security issues faced by organizations are complex and addressing them can be expensive. Key findings from previous research suggest that informal methods of enhancing employees’ security awareness are effective and inexpensive. This study builds on previous research and introduces seven hypotheses related to informal security advice sharing in organizations. The model was tested on 334 currently employed technology-using professionals in security conscious organizations. The results indicated that employees’ attitudes, perception of security climate, and perceptions about accountability affected their sharing of security advice. Their desire to earn a reputation was more pronounced with high self-efficacy. The direct association of desire to earn reputation and self-efficacy toward security advice sharing was not supported by data. These findings suggest that higher self-efficacy employees motivated to earn a reputation will likely facilitate the information security advice sharing process in a workplace.

While there has been considerable research related to distance learning, there is surprisingly little research into the role stress plays in distance learning. Therefore, in this paper, we investigated two types of stress: distress and eustress. Using a combination of stress theory and the job and demand resources theory, we developed a research model to predict distance learning satisfaction and continuance intentions. Results from 525 full-time students engaging in distance learning indicate general support for our research model. Our findings clearly indicate that 1) both distress and eustress are associated with distance learning continuance intentions, 2) these impacts are mediated by distance learning satisfaction, and 3) distress has a stronger effect than eustress. Our findings can assist advisors and faculty in helping students understand whether distance learning is a good idea for them.

This study investigates antecedents to and outcomes of two stress reactions, telework distress (detrimental stress), and telework eustress (beneficial stress) using a model derived from an integration of the transactional model of stress with the job-demands and resources model. The model includes a person antecedent (resilience), and three environment antecedents (work-family conflict, work overload, and autonomy). These factors should influence experienced distress and eustress, which, in turn, affect telework outcomes (telework satisfaction, exhaustion, perceived performance, and perceived productivity. The model is evaluated using a sample of 329 Chinese teleworkers. This study findings indicate that resilience, work-family conflict, and work overload affect experienced distress, while resilience and autonomy affect experienced eustress. Experienced distress influenced satisfaction, exhaustion, and perceived performance; eustress had effects on all four outcomes. Interestingly, resilience had the largest total effect sizes on telework outcomes.

Computer-based communication technologies are increasingly important to personal and organizational communication. One important factor related to the adoption and diffusion of communication innovations is critical mass. Critical mass influences the adoption and diffusion of interactive communication innovations, both through network externalities and through sustainability of the innovation. Unfortunately, critical mass is difficult to measure and is typically only demonstrable after the critical mass point has been reached. Potential adopters’ perceptions of critical mass also may be important to adoption decisions. In this paper, we extend this thinking using a synthesis of the Theory of Reasoned Action and Diffusion of Innovation theory by developing a research model. The model is empirically tested using survey data that are analyzed using partial least squares. The focal innovation is instant messaging. Results indicate that perceived critical mass influences use intentions directly and through perceptions of the characteristics of the innovation. The perceived innovation characteristics impact attitude toward use, which in turn impacts use intentions. The model predicts a sizable and significant portion of both attitudes and use intentions. Further, perceived critical mass is able to explain a significant portion of the variance in each perceived innovation characteristic. Implications for research and practice are discussed.