Neuroscience in HR : Employee Behavior Analysis to Optimize Performance

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.

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Publication Details

Journal
International Journal of Management Research and Economics
Published
2025-03-13
DOI
https://doi.org/10.54066/ijmre-itb.v3i2.3135
Primary Topic
Business, Innovation, and Economy
Type
article
Field-Weighted Citation Impact
0.00
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article

Neuroscience in HR : Employee Behavior Analysis to Optimize Performance

Sumiati Sumiati
International Journal of Management Research and Economics
Business, Innovation, and Economy
article

Neuroscience in HR : Employee Behavior Analysis to Optimize Performance

Sumiati Sumiati
article en

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.

International Journal of Management Research and EconomicsVol. 3(2)
Universitas 17 Agustus 1945 Surabaya (ID)
Openalex Percentile: Top 91%
Business, Innovation, and Economy
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