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A Two-Stage SEM—Artificial Neural Network Analysis of the Engagement Impact on Employees’ Well-Being
Employees’ engagement (EE) and well-being (WB) are considered two interesting issues by many scientific researchers and practitioners within organizations. Most research confirms a positive correlation between EE and WB. EE is an essential premise for specific dimensions of employees’ WB. At the sam...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9224337/ https://www.ncbi.nlm.nih.gov/pubmed/35742574 http://dx.doi.org/10.3390/ijerph19127326 |
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author | Popescu, Luminita Bocean, Claudiu George Vărzaru, Anca Antoaneta Avram, Costin Daniel Iancu, Anica |
author_facet | Popescu, Luminita Bocean, Claudiu George Vărzaru, Anca Antoaneta Avram, Costin Daniel Iancu, Anica |
author_sort | Popescu, Luminita |
collection | PubMed |
description | Employees’ engagement (EE) and well-being (WB) are considered two interesting issues by many scientific researchers and practitioners within organizations. Most research confirms a positive correlation between EE and WB. EE is an essential premise for specific dimensions of employees’ WB. At the same time, satisfied and physically and mentally healthy employees increase EE, both EE and WB thus being fundamental to individual and organizational performance. This paper aims to evaluate the relationships between EE and WB and between the dimensions of these two complex constructs. These relationships were assessed based on data obtained from a sample of 269 employees in Romania, using as a method a mix of analyses based on structural equation modeling (SEM) and artificial neural network analysis (ANN). The results highlighted a positive two-way relationship between EE and WB. Among the dimensions of EE, motivation and work environment are those that ensure a more pronounced perception of WB by the employee. Emotional WB, occupational WB, and social WB are the dimensions of WB with a significant influence on the general level of EE. |
format | Online Article Text |
id | pubmed-9224337 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-92243372022-06-24 A Two-Stage SEM—Artificial Neural Network Analysis of the Engagement Impact on Employees’ Well-Being Popescu, Luminita Bocean, Claudiu George Vărzaru, Anca Antoaneta Avram, Costin Daniel Iancu, Anica Int J Environ Res Public Health Article Employees’ engagement (EE) and well-being (WB) are considered two interesting issues by many scientific researchers and practitioners within organizations. Most research confirms a positive correlation between EE and WB. EE is an essential premise for specific dimensions of employees’ WB. At the same time, satisfied and physically and mentally healthy employees increase EE, both EE and WB thus being fundamental to individual and organizational performance. This paper aims to evaluate the relationships between EE and WB and between the dimensions of these two complex constructs. These relationships were assessed based on data obtained from a sample of 269 employees in Romania, using as a method a mix of analyses based on structural equation modeling (SEM) and artificial neural network analysis (ANN). The results highlighted a positive two-way relationship between EE and WB. Among the dimensions of EE, motivation and work environment are those that ensure a more pronounced perception of WB by the employee. Emotional WB, occupational WB, and social WB are the dimensions of WB with a significant influence on the general level of EE. MDPI 2022-06-15 /pmc/articles/PMC9224337/ /pubmed/35742574 http://dx.doi.org/10.3390/ijerph19127326 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Popescu, Luminita Bocean, Claudiu George Vărzaru, Anca Antoaneta Avram, Costin Daniel Iancu, Anica A Two-Stage SEM—Artificial Neural Network Analysis of the Engagement Impact on Employees’ Well-Being |
title | A Two-Stage SEM—Artificial Neural Network Analysis of the Engagement Impact on Employees’ Well-Being |
title_full | A Two-Stage SEM—Artificial Neural Network Analysis of the Engagement Impact on Employees’ Well-Being |
title_fullStr | A Two-Stage SEM—Artificial Neural Network Analysis of the Engagement Impact on Employees’ Well-Being |
title_full_unstemmed | A Two-Stage SEM—Artificial Neural Network Analysis of the Engagement Impact on Employees’ Well-Being |
title_short | A Two-Stage SEM—Artificial Neural Network Analysis of the Engagement Impact on Employees’ Well-Being |
title_sort | two-stage sem—artificial neural network analysis of the engagement impact on employees’ well-being |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9224337/ https://www.ncbi.nlm.nih.gov/pubmed/35742574 http://dx.doi.org/10.3390/ijerph19127326 |
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