Dr Junyi (Amy) Xie

Rule enforcement is a crucial part of the frontline service employee’s role that, if mishandled, can have serious consequences for employees, customers and the organization. However, there is very little knowledge about both its drivers and outcomes in the service literature. This study contributes to the organizational frontlines literature by developing a comprehensive framework of the drivers and consequences of service rule enforcement. Our conceptual model identifies organizational, individual, and situational variables that influence service rule enforcement and sheds light on the employee-related, customer-related, and organization-related consequences of rule enforcement. In conceptualizing service rule enforcement, we address the notions of enforcement/non-enforcement, the extent and consistency of enforcement, and rule enforcement styles. We also propose that rule enforcement can have both positive and negative consequences. Finally, we provide a research agenda that proposes ideas for future studies in this area.

Navigating the increasingly uncertain business world requires organizations and employees to be highly adaptive to threats and changes. During COVID-19, the dual threats to health and job security have been especially salient for frontline employees. Drawing on the job demands-resources (JD-R) model, we investigated individual and organizational mindfulness as valuable resources, which influence employee outcomes of preventative behaviors, emotional exhaustion, and job performance both directly, and indirectly through threat appraisals. We find that individual and organizational mindfulness influence threat appraisals in a "counterbalanced manner": individual mindfulness decreases threat appraisals, while organizational mindfulness heightens the perceived threat of contracting COVID-19. The threat to health further serves as a double-edged sword, predicting both emotional exhaustion and preventative behaviors, while job insecurity impairs all employee outcomes. Based on these findings, we provide key implications for research and practice, and future research directions.

With the advance of the Internet of Things (IoT) and smart sensor networks, accurate understanding of complex data via interface icons is critical for effective decision making, operation management and monitoring. In order to understand how the different domain experience among icon designers and users affects icon recognition and preference level among users, this paper takes environmental and operational sensors as a case study and organises two icon design workshops, in which icon recognition and preference tests are conducted based on the standard ISO 9186 methodology. Results reveal that differences in domain experience among designers and users do not impose a significant impact on users' icon recognition levels. However, users new to the domain significantly prefer icons created by designers who share similar levels of domain experience with them. It provides a little reference for future environmental and operational sensor Graphical User Interface icon designers, decision makers, scientists and engineers to improve the icon design process.