Mia Ayu Gusti

Apart from physical health problems, the COVID-19 outbreak also affected psychological health, causing extreme fear of this pandemic. Thus, this study aims to investigate the relationship between nurse performance and the fear of COVID-19 mediated by job insecurity and job satisfaction with conservation of resources theory as the lens. Data from 260 nurses were collected through an online structured questionnaire and analyzed using structural equation modeling-partial least squares. The direct effect findings show that COVID-19 fear influences job insecurity (p < 0.05) but does not influence job satisfaction and nurse performance (p > 0.05). Besides, job insecurity significantly influences job satisfaction and nurse performance (p < 0.05). On the other hand, job satisfaction has no effect on nurse performance (p > 0.05). Then, the indirect effect results show that job insecurity fully mediates the influence of COVID-19 fear on job satisfaction and nurse performance (p < 0.05). Likewise, job satisfaction partially mediates the influence of job insecurity on nurse performance (p < 0.05) but does not mediate the fear of COVID-19 on nurse performance (p > 0.05). These findings provide evidence that the fear of COVID-19 plays an essential role for job insecurity, influencing job satisfaction and nurse performance. These results can develop strategies for better human resource management in nursing staff and provide pragmatic insight into the impact of the COVID-19 pandemic.

Acknowledgment
The authors thank Universitas Negeri Padang for its support in completing this article. We also thank all members for their support and cooperation.

The “new normal” era has made remote work the new standard, making the use of artificial intelligence (AI) increasingly important. Therefore, this study aims to investigate employee perceptions of change leadership in the application of AI that affects employee engagement and productivity according to the resource-based view (RBV). Of the 467 respondents who worked in the banking industry in West Sumatra province, Indonesia, only 359 met the eligibility requirements. The partial least squares (PLS) analysis shows a direct relationship between AI and employee engagement (p < 0.05) and productivity (p < 0.05), as well as employee engagement and employee productivity (p < 0.05). The effect of AI on employee productivity is mediated by employee engagement (p < 0.05), but the moderating effect provided by change leadership is not significant (p > 0.05) in increasing employee productivity. These findings will help managers create a positive work environment through the application of AI, resulting in higher employee engagement and productivity. Specifically, these findings help organizations integrate AI more effectively and provide managers with a comprehensive understanding of the considerations needed to increase productivity through employee engagement for organizational competitiveness.

Acknowledgment
The authors thank Universitas Negeri Padang for helping finish this article. We also appreciate the cooperation and support of each member.