This study begins with Budnick et al.'s (2020) argument that fear of missing out (FoMO), which has traditionally been treated as a negative interpersonal variable, can have both negative and positive effects in the workplace context(workplace FoMO). The purpose of this study is, first, to empirically confirm the ambivalent impact of workplace FoMO through its negative impact on job burnout and its positive impact on self-improvement. Second, we examine the differential role of two subtypes of work-related rumination, emotional rumination and problem-solving pondering, in the development of the ambivalent effects of workplace FoMO. The results showed that, first, higher workplace FoMO was associated with higher levels of both job burnout and self-improvement, confirming Budnick et al.'s (2020) ambivalent impact of workplace FoMO. Second, in the process of ambivalent effects of workplace FoMO on burnout and self-improvement, emotional rumination increased burnout in employees, while problem-solving pondering decreased emotional rumination and increased self-improvement. The academic implication of this study is that it empirically confirms the ambivalent effects and mechanisms of workplace FoMO, and the practical implication is that it shows that workplace FoMO can be linked to positive outcomes by paying attention to employees' workplace FoMO and supporting their self-improvement at the organizational level.
In this research, we aim to conceptualize and develop a scale to measure Korean workers’ multidimensional attitudes toward the application of artificial intelligence (AI) technology in the workplace. Based on three studies, we developed and validated the Korean version of Attitudes towards Artificial Intelligence Application at Work (K-AAAW) scale, adapted from the English version of the AAAW. Results showed that the 27-item scale consists of six dimensions: perceived humanlikeness, perceived adaptability, perceived quality, AI use anxiety, perceived job insecurity, and personal utility. In Study 1, we conducted item reduction and identified a multidimensional structure of K-AAAW. In Study 2, the six-dimensional factor structure was identified using a separate sample of working adults, and external validity evidence was examined by examining the relationships between the six factors of K-AAAW and personality factors and organizational variables. In Study 3, we examined K-AAAW’s predictive validity evidence by exploring the relationships between the K-AAAW factors and job applicants’ attitudes towards organizations that incorporated AI in the recruitment processes. In Study 3, we additionally examined the convergent and discriminant validity evidence by comparing the K-AAAW scale with an existing scale measuring attitudes towards AI as well as general job attitudes. The results indicate that the K-AAAW scale is a valid scale with good psychometric properties. The K-AAAW scale provides opportunities to understand and investigate Korean workers’ attitudes towards AI application at work. Based on these results, we discuss research implications, and suggest future research directions.