Employee Segmentation by Measuring the Attitude of ‘Intention to Stay’: A Machine Learning Approach

Authors

  • Ramkumar S. GITAM School of Business, GITAM University, Bangalore, Karnataka, India
  • Karthika P. Department of Management, College of Business and Economics, Kebri Dehar University, Ethiopia
  • D. Dilip VIT Business School, Vellore Institute of Technology, Vellore, Tamil Nadu, India
  • Mahesh Singh ATMS-SBS Swiss Business School, Ras AI Khaimah, UAE

Keywords:

Attrition, Retention, Intention to Stay, Cluster Analysis, Employee Segmentation

Abstract

This study aims to segment the employees based on their attitude towards more extended stay in the organization. Employees' attitude differs despite having an elite HR system and administration. However, identifying the factors that influence the employees' attitude towards their stay is crucial to retaining them. Hence, this study measures their attitudes regarding working conditions, supervision, compensation and benefits, task assignments, amenities, grievance handling system, and other HR operating factors. As a result, this study uncovers the position of employees into different segments based on this measurement task. The samples are drawn from the shop-floor and operation level of employees working in a textile company with more than 500 crores as annual turnover.

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Published

23.02.2024

How to Cite

S., R. ., P., K. ., Dilip, D. ., & Singh, M. . (2024). Employee Segmentation by Measuring the Attitude of ‘Intention to Stay’: A Machine Learning Approach. International Journal of Intelligent Systems and Applications in Engineering, 12(17s), 443–449. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/4903

Issue

Vol. 12 No. 17s (2024)

Section

Research Article

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