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Performance shaping factors for future sustainable energy management: A new integrated approach

The current literature suggests that a lack of integration between engineering for performance shaping factors (PSFs) and workplace energy management (WEM) is a significant barrier to improving energy management practices (EMP) and power plant efficiency. The study identified three research objectiv...

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Autores principales: Ajmi, Ahmed Ali, Mahmood, Noor Shakir, Jamaludin, Khairur Rijal, Talib, Hayati Habibah Abdul, Sarip, Shamsul, Kaidi, Hazilah Mad
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10412885/
https://www.ncbi.nlm.nih.gov/pubmed/37576275
http://dx.doi.org/10.1016/j.heliyon.2023.e18438
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author Ajmi, Ahmed Ali
Mahmood, Noor Shakir
Jamaludin, Khairur Rijal
Talib, Hayati Habibah Abdul
Sarip, Shamsul
Kaidi, Hazilah Mad
author_facet Ajmi, Ahmed Ali
Mahmood, Noor Shakir
Jamaludin, Khairur Rijal
Talib, Hayati Habibah Abdul
Sarip, Shamsul
Kaidi, Hazilah Mad
author_sort Ajmi, Ahmed Ali
collection PubMed
description The current literature suggests that a lack of integration between engineering for performance shaping factors (PSFs) and workplace energy management (WEM) is a significant barrier to improving energy management practices (EMP) and power plant efficiency. The study identified three research objectives in response to this research gap: (1) conduct a systematic literature review to analyze current studies; (2) develop a novel integrative model capable of predicting EMP; and (3) test the novel model's validity and reliability through an empirical study in thermal power plants. In this study, a group of academic and energy experts designed research instruments to achieve the study's objectives, which were then pilot-tested. Partial least square structural equation modeling was utilized to analyze the data in this study. The study successfully developed a new model for future sustainable energy management in power plants and a new model integrating the PSFs and WEM to predict power plant energy performance, aiming to enhance communication between operators and EMP in power plants. The model exhibited exceptional explanatory and predictive abilities, yielding a strong fit. Furthermore, the incorporation of success factors associated with PSFs positively influenced the EMP. The data set followed a normal distribution, confirming the model's reliability and validity. Significantly, this study achieved a breakthrough by being the first to integrate success factors for PSFs and WEM in thermal power plants, thus effectively addressing an unexplored area of research. However, the inconsistencies in the current studies emphasize the necessity for additional investigations into the strategy of PSFs in EMP within power plants.
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spelling pubmed-104128852023-08-11 Performance shaping factors for future sustainable energy management: A new integrated approach Ajmi, Ahmed Ali Mahmood, Noor Shakir Jamaludin, Khairur Rijal Talib, Hayati Habibah Abdul Sarip, Shamsul Kaidi, Hazilah Mad Heliyon Research Article The current literature suggests that a lack of integration between engineering for performance shaping factors (PSFs) and workplace energy management (WEM) is a significant barrier to improving energy management practices (EMP) and power plant efficiency. The study identified three research objectives in response to this research gap: (1) conduct a systematic literature review to analyze current studies; (2) develop a novel integrative model capable of predicting EMP; and (3) test the novel model's validity and reliability through an empirical study in thermal power plants. In this study, a group of academic and energy experts designed research instruments to achieve the study's objectives, which were then pilot-tested. Partial least square structural equation modeling was utilized to analyze the data in this study. The study successfully developed a new model for future sustainable energy management in power plants and a new model integrating the PSFs and WEM to predict power plant energy performance, aiming to enhance communication between operators and EMP in power plants. The model exhibited exceptional explanatory and predictive abilities, yielding a strong fit. Furthermore, the incorporation of success factors associated with PSFs positively influenced the EMP. The data set followed a normal distribution, confirming the model's reliability and validity. Significantly, this study achieved a breakthrough by being the first to integrate success factors for PSFs and WEM in thermal power plants, thus effectively addressing an unexplored area of research. However, the inconsistencies in the current studies emphasize the necessity for additional investigations into the strategy of PSFs in EMP within power plants. Elsevier 2023-07-23 /pmc/articles/PMC10412885/ /pubmed/37576275 http://dx.doi.org/10.1016/j.heliyon.2023.e18438 Text en © 2023 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Research Article
Ajmi, Ahmed Ali
Mahmood, Noor Shakir
Jamaludin, Khairur Rijal
Talib, Hayati Habibah Abdul
Sarip, Shamsul
Kaidi, Hazilah Mad
Performance shaping factors for future sustainable energy management: A new integrated approach
title Performance shaping factors for future sustainable energy management: A new integrated approach
title_full Performance shaping factors for future sustainable energy management: A new integrated approach
title_fullStr Performance shaping factors for future sustainable energy management: A new integrated approach
title_full_unstemmed Performance shaping factors for future sustainable energy management: A new integrated approach
title_short Performance shaping factors for future sustainable energy management: A new integrated approach
title_sort performance shaping factors for future sustainable energy management: a new integrated approach
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10412885/
https://www.ncbi.nlm.nih.gov/pubmed/37576275
http://dx.doi.org/10.1016/j.heliyon.2023.e18438
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