Neuroscience in HR : Employee Behavior Analysis to Optimize Performance

Authors

  • Sumiati Sumiati Universitas 17 Agustus 1945 Surabaya

DOI:

https://doi.org/10.54066/ijmre-itb.v3i2.3135

Keywords:

Emotional intelligence, Employee performance, Neuroscience factors, Work motivation

Abstract

This study aims to analyze the effect of work motivation, neuroscience factors, emotional intelligence, and job type on employee performance. This research uses quantitative methods with multiple linear regression approaches. Data was collected from 100 respondents who work in various industrial sectors. The results showed that emotional intelligence and work motivation have a significant influence on employee performance, while neuroscience factors and job type did not show a significant influence. The F-test yields a value of 21,795 with a significance of 0.000, which indicates that simultaneously, the independent variables in this model have a significant effect on employee performance. The R-Square value of 0.479 indicates that 47.9% of the variation in employee performance can be explained by the variables used in the model, while 52.1% is explained by other factors outside this model.  The results of this study indicate that companies need to improve employees' work motivation and emotional intelligence to optimize their performance. In addition, this study recommends exploring additional variables that may affect employee performance to improve the accuracy of the prediction model.

References

A Critical Review of Motivational Theories in Management and their Role in Modern Era. (2021). https://doi.org/10.52783/trs.v7i5-1.1405

Bajwa, R. R., Rahim, R., Mukhtar, M. A., & Akmal, H. (2024). Examining the link between stress management strategies and employee performance in high-pressure industries. Review of Applied Management and Social Sciences, 7(4), 915–927. https://doi.org/10.47067/ramss.v7i4.422

Bigliassi, M., Cabral, D. F., & Evans, A. C. (2025). Improving brain health via the central executive network. The Journal of Physiology. https://doi.org/10.1113/jp287099

Bokhari, S. S. A., & Ghaffar, A. (2024). Emerging trends in human resource management: Exploring digital transformation, employee well-being, and remote work paradigms. Journal for Business Education and Management, 4(2), 1–16. https://doi.org/10.56596/jbem.v4i2.139

Bose, S., & Mohanty, S. (2024). Interrelationship between motivation with job satisfaction and productivity parameter by talent acquisition team: A case study. Paper Asia, 40(4b), 19–30. https://doi.org/10.59953/paperasia.v40i4b.107

Dalalana, C. R., Antunes Neto, J. M. F., & Fracarolli, R. L. (2024). Application of neuroscience in organizations from the perspective of leadership training: A literature review. IOSR Journal of Business and Management. https://doi.org/10.9790/487x-2609092433

Deci, E. L., Olafsen, A. H., & Ryan, R. M. (2017). Self-determination theory in work organizations: The state of a science. Social Science Research Network, 4(1), 19–43. https://doi.org/10.1146/ANNUREV-ORGPSYCH-032516-113108

Ferreira, S., Rodrigues, M. A., Mateus, C., Rodrigues, P. P., & Rocha, N. (2025). Interventions based on biofeedback systems to improve workers’ psychological well-being, mental health, and safety: A systematic literature review (Preprint). https://doi.org/10.2196/preprints.70134

Frisina, M. E. (2024). Best behaviors: Leveraging neuroscience to enhance leadership skills. Frontiers of Health Services Management, 41(2), 4–12. https://doi.org/10.1097/hap.0000000000000205

Ghosh, O., & Kumar, B. (2024). The brain at work (pp. 1–14). IGI Global. https://doi.org/10.4018/979-8-3693-1858-4.ch001

Jeni, A., & Reddy, K. J. (2024). Enhancing neurocognitive skills for effective leadership and decision-making (pp. 208–226). IGI Global. https://doi.org/10.4018/979-8-3693-1858-4.ch012

Khushk, A., Liu, Z., Xu, Y., & Liu, H. (2025). Impact of multifaceted morality on employee well-being: A systematic literature review. The International Journal of Organizational Analysis. https://doi.org/10.1108/ijoa-03-2024-4326

Knights, J. (2024). The neuroscience of leadership (pp. 39–50). Informa. https://doi.org/10.4324/9781003409007-6

Kulshrestha, P., & Kulshrestha, D. (2024). Significant impact of neuroscience in developing a new talent acquisition strategy (pp. 257–271). IGI Global. https://doi.org/10.4018/979-8-3693-1785-3.ch017

Lakshmi Priya, M. D., & Jayalakshmi, G. (2024). Exploring innovative practices in digital human resource management. Advances in Logistics, Operations, and Management Science Book Series, 137–156. https://doi.org/10.4018/979-8-3373-1137-1.ch007

Lee, C. (2024). Artificial neural networks (ANNs) and machine learning (ML) modeling employee behavior with management towards the economic advancement of workers. Sustainability, 16(21), 9516. https://doi.org/10.3390/su16219516

Mathur, M., Pramanik, B., Rosalyn, S., Thulaseedharan, A., Mirzani, Y., & Namdeo, S. (2024). Ethical implications of AI in HRM: Balancing efficiency and privacy in employee monitoring systems. Nanotechnology Perceptions, 4490–4496. https://doi.org/10.62441/nano-ntp.vi.3870

McCreedy, R. T. W. (2024). Change on the brain? The neuroscience of organizational transformation. International Journal of Applied Research in Management and Economics, 7(3), 30–44. https://doi.org/10.33422/ijarme.v7i3.1402

Neural mechanisms of decision making. (2023). Physics Subject Headings (PhySH). https://doi.org/10.29172/2fc1722f-3725-4f4b-8c0c-4c05c97204b2

Putri, A. H., Rohimah, N., Elizafitriani, A., & Merdiaty, N. (2024). Model stres kerja dan dampaknya pada produktivitas: Analisis literatur. Deleted Journal, 3(1), 266–275. https://doi.org/10.61132/observasi.v3i1.962

Rachmawati, E., Sumartono, E., Rini, A. S., Wiliana, E., & Faqih, M. (2024). The interplay between employee motivation, work-life balance, and job satisfaction in enhancing workplace productivity. Global International Journal of Innovative Research, 2(6), 1383–1396. https://doi.org/10.59613/global.v2i6.211

Restrepo, A. P. M., & Valencia, M. R. (2014). Motivating employees: Beyond the carrot-and-stick techniques. AD-Minister, 24, 143–160. http://www.scielo.org.co/scielo.php?script=sci_arttext&pid=S1692-02792014000100008&lng=en

Saputrabey, M. A., Sepriyanti, Y., Riyanto, R., Moeins, A., & Zen, Y. (2025). Enhancing digital motivation work and its effect on digital target-based employee performance at regional revenue agency of DKI Jakarta province. Edelweiss Applied Science and Technology, 9(1), 968–980. https://doi.org/10.55214/25768484.v9i1.4296

Sharma, V., & R, V. (2024). Analyzing the relationship between employee motivation and job satisfaction. Shanlax International Journal of Management. https://doi.org/10.34293/management.v11is1-mar.8048

Wei, J. (2024). The role of motivation in decision-making and underlying neural mechanism. Communications in Humanities Research, 40(1), 100–106. https://doi.org/10.54254/2753-7064/40/20242333

Downloads

Published

2025-03-13

How to Cite

Sumiati Sumiati. (2025). Neuroscience in HR : Employee Behavior Analysis to Optimize Performance. International Journal of Management Research and Economics, 3(2), 92–103. https://doi.org/10.54066/ijmre-itb.v3i2.3135