Please use this identifier to cite or link to this item: https://gnanaganga.inflibnet.ac.in:8443/jspui/handle/123456789/1081
Title: Modelling the Impact of Demographic Variables on Employee Motivation Levels in Automobile Industry
Authors: Ruchi Nayyar, Poonam Arora
Keywords: Automobile industry, Motivation
Machine learning
Motivation
Issue Date: 2020
Publisher: Indian Journal of Computer Science
Abstract: Motivation of employees is one of the most critical components for an organization to be effective and efficient. Employee motivation is presented in the form of commitment, job satisfaction, high energy levels, willingness to take challenging assignments, and innovation while they are working for their organizations. It becomes very important for organizations to devise strategies and ways through which they can motivate and retain their employees. The present study is aimed to predict the motivation level of employees in automobile industry on the basis of their demographic variables using machine learning algorithms. The motivation level is measured by structured questionnaire with 70 items on the scale. The sample was collected from employees in automobile sector in Delhi/NCR region with a sample size of 340 employees. Analysis of the sampled data revealed that the machine learning algorithm is able to depict the motivation levels of employees on the basis of age, gender, and designation.
URI: http://gnanaganga.inflibnet.ac.in:8080/jspui/handle/123456789/1081
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