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Article Details

Vol. 1 No. 3 (2026): May

The Impact of Artificial Emotional Intelligence in Supporting Human Resource Managers' Decisions by Mediating Knowledge Sharing Behaviors

https://doi.org/10.35912/ambus.v1i3.4131

Abstract

Purpose: This study explores the impact of emotional intelligence (EI) capabilities among leaders at the Ministry of Construction and Housing on the practice of transformational leadership within the framework of wisdom.

Research Methodology: This study aims to explore the impact of emotional intelligence capabilities among leaders at the Ministry of Construction and Housing on the practice of transformational leadership within the framework of wisdom.

Results: This study aimed to explore the impact of emotional intelligence capabilities among leaders at the Ministry of Construction and Housing on the practice of transformational leadership within the framework of wisdom.

Conclusions: This study explored the impact of emotional intelligence capabilities among leaders at the Ministry of Construction and Housing on the practice of transformational leadership within the framework of wisdom.

Limitations: This study focused solely on leaders within the Ministry of Construction and Housing, and the sample was limited to a specific group of senior leaders (i.e., the Ministry of Housing and Construction Councils). Thus, the findings may not be generalizable to all types of leadership across various institutions.

Contributions: This study contributes to the understanding of the role of emotional intelligence in enhancing transformational leadership practices and offers valuable recommendations for improving leadership development processes within the Ministry of Construction and Housing.

Keywords

Emotional AI Important Role Decisions

How to Cite

Daim, A. A. S. A. . (2026). The Impact of Artificial Emotional Intelligence in Supporting Human Resource Managers’ Decisions by Mediating Knowledge Sharing Behaviors. Advances in Management and Business Studies, 1(3), 169–184. https://doi.org/10.35912/ambus.v1i3.4131

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References

  1. Alsop, R., & Heinsohn, N. (2005). Measuring empowerment in practice: Structuring analysis and framing indicators (Vol. 3510): World Bank Publications.
  2. Alwali, J., & Alwali, W. (2025). Linking AI-driven HRM and emotional intelligence to leadership effectiveness and employee performance. Leadership & Organization Development Journal, 1-21. doi:https://doi.org/10.1108/LODJ-05-2025-0358
  3. Aman-Ullah, A., Mehmood, W., Amin, S., & Abbas, Y. A. (2022). Human capital and organizational performance: A moderation study through innovative leadership. Journal of Innovation & Knowledge, 7(4), 100261. doi:https://doi.org/10.1016/j.jik.2022.100261
  4. Ardelt, M. (2004). Wisdom as expert knowledge system: A critical review of a contemporary operationalization of an ancient concept. Human development, 47(5), 257-285. doi:https://doi.org/10.1159/000079154
  5. Baba, M., & Siddiqi, M. (2018). Emotional intelligence and Transformational Leadership: A Review of Empirical Studies.
  6. Creswell, J. (2003). W. Research Design, Qualitative and Quantitative Aproaches: Jakarta: KIK Press.
  7. Daniel, C. (2019). The Effects of Human Capital Development on Organizational Performance. International Journal of Scientific Research and Management, 7. doi:https://doi.org/10.18535/ijsrm/v7i1.em03
  8. Dutande, P., Baid, U., & Talbar, S. (2021). LNCDS: A 2D-3D cascaded CNN approach for lung nodule classification, detection and segmentation. Biomedical signal processing and control, 67, 102527. doi:https://doi.org/10.1016/j.bspc.2021.102527
  9. Dwivedi, D. (2025). Emotional Intelligence and Artificial Intelligence Integration Strategies for Leadership Excellence. Advances in Research, 26, 84-94. doi:https://doi.org/10.9734/air/2025/v26i11235
  10. Faruqui, N., Yousuf, M. A., Whaiduzzaman, M., Azad, A., Barros, A., & Moni, M. A. (2021). LungNet: A hybrid deep-CNN model for lung cancer diagnosis using CT and wearable sensor-based medical IoT data. Computers in Biology and Medicine, 139, 104961. doi:https://doi.org/10.1016/j.compbiomed.2021.104961
  11. Fatima, A., Imran, R., & Awan, S. H. (2011). Emotional intelligence and transformational leadership: finding gender differences. World Applied Sciences Journal, 14(11), 1734-1743.
  12. Fernandez-Perez, V., & Martin-Rojas, R. (2022). Emotional competencies as drivers of management students’ academic performance: The moderating effects of cooperative learning. The International Journal of Management Education, 20(1), 100600. doi:https://doi.org/10.1016/j.ijme.2022.100600
  13. Firdaus, M., Rosita, W., Diyanto, H., & Supratikta, H. (2023). Optimizing Organizational Performance through Strategic Human Capital Management. Ascarya: Journal of Islamic Science, Culture, and Social Studies, 3, 151-157. doi:https://doi.org/10.53754/iscs.v3i2.634
  14. Hossain, A. (2025). Emotional and Artificial Intelligence: Narrative of Human and Machine Relation. Transactions on Engineering and Computing Sciences, 13, 01-53. doi:https://doi.org/10.14738/tmlai.1305.19324
  15. Hur, Y., van den Berg, P. T., & Wilderom, C. P. M. (2011). Transformational leadership as a mediator between emotional intelligence and team outcomes. The Leadership Quarterly, 22(4), 591-603. doi:https://doi.org/10.1016/j.leaqua.2011.05.002
  16. Kapoor, A., & Verma, V. (2024). EMOTION AI: UNDERSTANDING EMOTIONS THROUGH ARTIFICIAL INTELLIGENCE. International Journal of Engineering Science and Humanities, 14, 223-232. doi:https://doi.org/10.62904/0vcbvb24
  17. Khan, S. A., Nazir, M., Khan, M. A., Saba, T., Javed, K., Rehman, A., . . . Awais, M. (2019). Lungs nodule detection framework from computed tomography images using support vector machine. Microscopy research and technique, 82(8), 1256-1266. doi:https://doi.org/10.1002/jemt.23275
  18. Khare, S. K., Blanes-Vidal, V., Nadimi, E. S., & Acharya, U. R. (2024). Emotion recognition and artificial intelligence: A systematic review (2014–2023) and research recommendations. Information Fusion, 102, 102019. doi:https://doi.org/10.1016/j.inffus.2023.102019
  19. Molina, D., Déniz-Déniz, M., & García-Cabrera, A. (2019). The HR decision-maker’s emotional intelligence and SME performance. Management Research Review, ahead-of-print. doi:https://doi.org/10.1108/MRR-10-2018-0373
  20. Narendran, S., Jaiswal, R., Rai, M., Yadav, A., Mishra, A., & Haralayya, D. (2024). Exploring The Impact Of Emotional Intelligence On Leadership Effectiveness: A Meta-Analysis In Management Studies. Educational Administration Theory and Practice journal, 30, 1668-1673. doi:https://doi.org/10.53555/kuey.v30i4.1728
  21. Narimisaei, J., Naeim, M., Imannezhad, S., Samian, P., & Sobhani, M. (2024). Exploring emotional intelligence in artificial intelligence systems: a comprehensive analysis of emotion recognition and response mechanisms. Annals of medicine and surgery, 86(8), 4657-4663. doi:https://doi.org/10.1097/MS9.0000000000002315
  22. O'Connor, P. J., Hill, A., Kaya, M., & Martin, B. (2019). The measurement of emotional intelligence: A critical review of the literature and recommendations for researchers and practitioners. Frontiers in psychology, 10, 429307. doi:https://doi.org/10.3389/fpsyg.2019.01116
  23. Rahiddin, R. N. N., Hashim, U. R. a., Ismail, N. H., Salahuddin, L., Choon, N. H., & Zabri, S. N. (2020). Classification of wood defect images using local binary pattern variants. International Journal of Advances in Intelligent Informatics, 6(1), 36-45. doi:http://dx.doi.org/10.26555/ijain.v6i1.392
  24. Salovey, P., & Mayer, J. D. (1990). Emotional intelligence. Imagination, cognition and personality, 9(3), 185-211. doi:https://doi.org/10.2190/DUGG-P24E-52WK-6CDG
  25. Saragih, H. J. R., & Sarjito, A. (2026). Rethinking emotional AI in human resource development: insights from burnout detection and empathy technologies. Human Resource Development International, 1-23. doi:https://doi.org/10.1080/13678868.2026.2622066
  26. Singh, A., Gera, D., Saxena, I., Jha, R., Kaur, R., & Barik, S. (2025). The Role of Emotional Intelligence in Enhancing Leadership Effectiveness: A Conceptual Perspective. Journal of Marketing & Social Research, 2, 470-474. doi:https://jmsr-online.com/article/the-role-of-emotional-intelligence-in-enhancing-leadership-effectiveness-a-conceptual-perspective-296/?utm_source=chatgpt.com
  27. Singh, M., & Indu, S. (2023). Denoising of palm leaf manuscripts using Gaussian filter and conservative smoothing. ADVANCES IN MANUFACTURING TECHNOLOGIES AND APPLICATION OF ARTIFICIAL INTELLIGENCE: AMTAAI 2021, 2521(1), 050005. doi:https://doi.org/10.1063/5.0142237
  28. Vicini, S., Bortolotto, C., Rengo, M., Ballerini, D., Bellini, D., Carbone, I., . . . Faggioni, L. (2022). A narrative review on current imaging applications of artificial intelligence and radiomics in oncology: Focus on the three most common cancers. La radiologia medica, 127(8), 819-836. doi:https://doi.org/10.1007/s11547-022-01512-6
  29. Watkin, C. (2000). Developing emotional intelligence. International Journal of selection and assessment, 8(2), 89-92. doi:https://doi.org/10.3390/encyclopedia4010037
  30. Zulfiqar, F., Bajwa, U. I., & Mehmood, Y. (2023). Multi-class classification of brain tumor types from MR images using EfficientNets. Biomedical signal processing and control, 84, 104777. doi:https://doi.org/10.1016/j.bspc.2023.104777

Authors

Ali Abdul Salam Abdul Daim
Al Iraqia University/ College of Islamic Sciences, Iraq

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Vol. 1 No. 3 (2026): May
Section: Articles
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