Alpon Satrianto

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.

Banking performance has developed rapidly accompanied by technological advances that can simplify banking services and transactions by adopting a priority scale aimed at identifying dynamically moving stock price returns and exploring banking quality and capacity as a manifestation of well-organized bank performance. This research aims to determine the effect of bank performance on stock price returns in European high-income countries. The analysis of the panel data method using the Common Effect Model (CEM) approach is considered capable of answering the objectives of this research. Research data were obtained from the World Bank and International Monetary Fund for 10 European countries (Denmark, Finland, France, Italy, Norway, Poland, Spain, Sweden, Switzerland and the UK) from 2002 to 2021. The research results prove that return on assets significantly affects stock price returns, while bank deposits to GDP, bank branches per 100,000 adults, and bank Z-score do not significantly affect stock returns. The control variables: exchange rate and interest rates do not significantly affect stock prices. The results of this research provide empirical evidence that bank performance through return on assets tends to have a positive impact on share price returns, which indicates that investors pay attention to this indicator. These findings underline the importance of bank management, and macroeconomic conditions and monetary policy must be considered in a broader context to provide long-term benefits for shareholders through overall market trust mechanisms so that high stock price returns can be achieved.

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.