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Sustainable training practices: predicting job satisfaction and employee behavior using machine learning techniques
This study evaluates Sustainable Training Practices (STP) that promote organizational growth and ensure the attainment of sustainable HRM objectives. First, we employ Structural Equation Modelling to identify relationships between STP, Psychological Contract Fulfilment, Job Satisfaction, and Organiz...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Palgrave Macmillan UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10245367/ http://dx.doi.org/10.1057/s41291-023-00234-5 |
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author | Gupta, Akriti Chadha, Aman Tiwari, Vijayshri Varma, Arup Pereira, Vijay |
author_facet | Gupta, Akriti Chadha, Aman Tiwari, Vijayshri Varma, Arup Pereira, Vijay |
author_sort | Gupta, Akriti |
collection | PubMed |
description | This study evaluates Sustainable Training Practices (STP) that promote organizational growth and ensure the attainment of sustainable HRM objectives. First, we employ Structural Equation Modelling to identify relationships between STP, Psychological Contract Fulfilment, Job Satisfaction, and Organizational Citizenship Behavior. Next, we build a predictive model using the RF Regression Supervised Machine Learning technique to identify the key predictors. Our findings indicate that employee happiness, expectation fulfilment, and behavior are highly dependent on the STPs offered to them. In addition, we find that machine learning is crucial because it reveals hidden features that are sometimes overlooked by conventional methods. |
format | Online Article Text |
id | pubmed-10245367 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Palgrave Macmillan UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-102453672023-06-08 Sustainable training practices: predicting job satisfaction and employee behavior using machine learning techniques Gupta, Akriti Chadha, Aman Tiwari, Vijayshri Varma, Arup Pereira, Vijay Asian Bus Manage Original Article This study evaluates Sustainable Training Practices (STP) that promote organizational growth and ensure the attainment of sustainable HRM objectives. First, we employ Structural Equation Modelling to identify relationships between STP, Psychological Contract Fulfilment, Job Satisfaction, and Organizational Citizenship Behavior. Next, we build a predictive model using the RF Regression Supervised Machine Learning technique to identify the key predictors. Our findings indicate that employee happiness, expectation fulfilment, and behavior are highly dependent on the STPs offered to them. In addition, we find that machine learning is crucial because it reveals hidden features that are sometimes overlooked by conventional methods. Palgrave Macmillan UK 2023-06-07 /pmc/articles/PMC10245367/ http://dx.doi.org/10.1057/s41291-023-00234-5 Text en © Springer Nature Limited 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Original Article Gupta, Akriti Chadha, Aman Tiwari, Vijayshri Varma, Arup Pereira, Vijay Sustainable training practices: predicting job satisfaction and employee behavior using machine learning techniques |
title | Sustainable training practices: predicting job satisfaction and employee behavior using machine learning techniques |
title_full | Sustainable training practices: predicting job satisfaction and employee behavior using machine learning techniques |
title_fullStr | Sustainable training practices: predicting job satisfaction and employee behavior using machine learning techniques |
title_full_unstemmed | Sustainable training practices: predicting job satisfaction and employee behavior using machine learning techniques |
title_short | Sustainable training practices: predicting job satisfaction and employee behavior using machine learning techniques |
title_sort | sustainable training practices: predicting job satisfaction and employee behavior using machine learning techniques |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10245367/ http://dx.doi.org/10.1057/s41291-023-00234-5 |
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