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DC Field | Value | Language |
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dc.contributor.author | Ruchi Nayyar, Poonam Arora | - |
dc.date.accessioned | 2023-09-12T10:55:30Z | - |
dc.date.available | 2023-09-12T10:55:30Z | - |
dc.date.issued | 2020 | - |
dc.identifier.uri | http://gnanaganga.inflibnet.ac.in:8080/jspui/handle/123456789/1081 | - |
dc.description.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. | en_US |
dc.language.iso | en_US | en_US |
dc.publisher | Indian Journal of Computer Science | en_US |
dc.subject | Automobile industry, Motivation | en_US |
dc.subject | Machine learning | en_US |
dc.subject | Motivation | en_US |
dc.title | Modelling the Impact of Demographic Variables on Employee Motivation Levels in Automobile Industry | en_US |
dc.type | Article | en_US |
Appears in Collections: | Article Archives |
Files in This Item:
File | Description | Size | Format | |
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Modelling the Impact of Demographic Variables.pdf Restricted Access | Modelling the Impact of Demographic Variables | 426.54 kB | Adobe PDF | View/Open Request a copy |
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