ISM Fuzzy Technique for Management Decision Making to Reduce Employee Turnover: A Study of Indian Manufacturing Industry

Ms. Akshata Bhat; Dr. Sagar Patil; Dr. Jayanti Belur

doi:https://doi.org/10.17492/jpi.manthan.v9i2.922202

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ISM Fuzzy Technique for Management Decision Making to Reduce Employee Turnover: A Study of Indian Manufacturing Industry

Akshata Bhat, Sagar Patil, Jayanti Belur

Vol 9 , Issue 2 , July - December 2022 | Pages: 16-39 | Research Paper

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https://doi.org/10.17492/jpi.manthan.v9i2.922202

Published Online: December 31, 2022

Author Details ( * ) denotes Corresponding author

1. * Akshata Bhat, Student, School of Management Studies and Research, KLE Technological University, Hubballi, Karnataka, India (akshatabbhat@gmail.com)

2. Sagar Patil, Associate Professor, School of Management Studies and Research, KLE Technological University, Hubballi, Karnataka, India (sagarpatil@kletech.ac.in)

3. Jayanti Belur, Placement Officer, IISC, IISC, Bangalore, Bangalore, Karnataka, India (jayantibelur@iisc.ac.in)

The purpose of this study is to examine the factors influencing employee turnover in the context of manufacturing industry. The study used existing literature to understand the relationship among these factors by using Interpretive Structural Modeling (ISM). Crocc-Impact Matrix Multiplication Applied to Classification (MICMAC) analysis was also used to classify the factors. The data were collected from primary and secondary sources. The results indicates that work-environment and career growth were critical factors followed by compensation, training and development, reward and recognition, job security, job stress, work-life balance, etc. In order to reduce employee turnover, the manufacturing sectors can mull over employee relations with colleagues and external job opportunities and emphasize job security, job stress, and work-life balance. The fuzzy-MICMAC results showed that the dependent factors were external job opportunities, job stress, job security, and work-life balance. As the study primarily uses experts’ opinion, the probability of collecting views was restricted.

Keywords

Employee Turnover; Interpretive Structural Modeling; Manufacturing Sector; Fuzzy; MICMAC

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