Egy Juniardi
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Artificial intelligence for employee engagement and productivity
Mia Ayu Gusti, Alpon Satrianto
, Candrianto
, Egy Juniardi
, Halkadri Fitra
doi: http://dx.doi.org/10.21511/ppm.22(3).2024.14
Problems and Perspectives in Management Volume 22, 2024 Issue #3 pp. 174-184
Views: 1877 Downloads: 331 TO CITE АНОТАЦІЯThe “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. -
Structural equation modeling to evaluate the financial performance of Indonesian conventional commercial banks
Mia Ayu Gusti, Alpon Satrianto
, Candrianto
, Egy Juniardi
, Heppy Setya Prima
doi: http://dx.doi.org/10.21511/bbs.20(2).2025.08
As financial intermediary institutions, banks operate in a dynamic and complex environment influenced by internal and external factors and various risks that impact their financial performance. This study aims to examine the influence of bank-specific and macroeconomic variables that affect credit risk and Indonesian conventional commercial banks’ financial performance. Structural equation modeling is used to analyze time series data from quarter 1993 to quarter 2023. This analysis covers conventional commercial banks registered in Indonesia, namely Bank Mandiri, Bank Rakyat Indonesia, Bank Negara Indonesia, and Bank Tabungan Negara. The results of the study indicate that conventional commercial banks in Indonesia can manage their specific variables effectively so that financial performance increases and non-performing loans decrease. In addition, the stability of economic conditions contributes to an increase in the volume of available loans, allowing commercial banks to earn higher income from loan interest. Therefore, the banking sector can benefit from some recommendations made in this study, especially concerning conventional commercial banks in Indonesia.
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