Analysis of Employee Competencies and Identification of High-Performance Employees Based on Individual Competency Using Self-Organizing Maps

Majid Ayyoobi

doi:10.63053/ijmea.49

Authors

Majid Ayyoobi Department of Management,Birjand Branch,Islamic Azad University, Birjand, Iran

DOI:

https://doi.org/10.63053/ijmea.49

Keywords:

Employee Competencies, High-Performance Employees, Self-Organizing Map, Individual Competency

Abstract

This study examines employee competencies and identifies high-performance employees by analyzing individual competency metrics. Using a self-organizing map (SOM) with 2000 nodes, network training and evaluation were conducted through the Viscovery Profiler software. The assessment incorporated both an evaluation center and a 360-degree performance evaluation, ensuring a comprehensive analysis of employee competencies. Hierarchical clustering (SOM Ward Clusters) determined segmentation, with clusters evaluated for key performance indicators such as personality fit, teamwork, creativity, decision-making, and leadership. Statistical tests, including the Kappa correlation coefficient and Pearson correlation, assessed the alignment between the two evaluation methods. While the Kappa test revealed no direct relationship between clusters from both methods, the Pearson correlation coefficient (0.481) indicated a significant positive relationship between competency scores and performance evaluation. These findings highlight the reliability of assessment center evaluations in predicting real-world performance, aiding organizations in talent management and employee development.

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