Strategic management of employee churn: Leveraging machine learning for sustainable development and competitive advantage in emerging markets
Poorva Agrawal
Department of Computer Science and Engineering, Symbiosis Institute of Technology Nagpur Campus, Constitue of Symbiosis International (Deemed University), Pune, India
Search for more papers by this authorSeema Ghangale
Symbiosis Institute of Operations Management, Nashik, Constitute of Symbiosis International (Deemed University), Pune, India
Search for more papers by this authorCorresponding Author
Bablu Kumar Dhar
Business Administration Division, Mahidol University International College, Mahidol University, Salaya, Nakhon Pathom, Thailand
Department of Business, Daffodil International University, Dhaka, Bangladesh
Correspondence
Bablu Kumar Dhar, Mahidol University International College, Business Administration Division, Mahidol University, Salaya, Thailand.
Email: [email protected]
Search for more papers by this authorNilesh Nirmal
Institute of Nutrition, Mahidol University, Salaya, Nakhon Pathom, Thailand
Search for more papers by this authorPoorva Agrawal
Department of Computer Science and Engineering, Symbiosis Institute of Technology Nagpur Campus, Constitue of Symbiosis International (Deemed University), Pune, India
Search for more papers by this authorSeema Ghangale
Symbiosis Institute of Operations Management, Nashik, Constitute of Symbiosis International (Deemed University), Pune, India
Search for more papers by this authorCorresponding Author
Bablu Kumar Dhar
Business Administration Division, Mahidol University International College, Mahidol University, Salaya, Nakhon Pathom, Thailand
Department of Business, Daffodil International University, Dhaka, Bangladesh
Correspondence
Bablu Kumar Dhar, Mahidol University International College, Business Administration Division, Mahidol University, Salaya, Thailand.
Email: [email protected]
Search for more papers by this authorNilesh Nirmal
Institute of Nutrition, Mahidol University, Salaya, Nakhon Pathom, Thailand
Search for more papers by this authorAbstract
Employee churn or attrition presents significant challenges, especially in emerging markets, where it can disrupt business operations and inflate recruitment costs. This research leverages machine learning techniques to predict employee churn, focusing on developing sustainable and inclusive retention strategies that enhance business competitiveness. By analyzing a range of predictive algorithms and key variables associated with churn, the study identifies the most effective models for predicting attrition. A comprehensive exploratory data analysis was conducted using an indigenous machine learning model, offering practical insights for human resource management in emerging markets. The findings align with the sustainable development goals (SDGs), promoting decent work, and economic growth. This study contributes to business strategy by proposing data-driven solutions for workforce stability and sustainable development.
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