Partial Least Square Structural Equation Modeling (PLS-SEM) / Nur Zainie Abd Hamid

Structural Equation Modeling (SEM) is a multivariate statistical analysis tool that is increasingly used to analyze structural relationship by the researcher in the business field. Two primary SEM techniques are Covariance-based Structural Equation Modeling (CB-SEM) and Partial Least Squares Structu...

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Main Author: Abd Hamid, Nur Zainie
Format: Book Section
Language:English
Published: Faculty of Business & Management, Universiti Teknologi MARA (UiTM) Cawangan Kedah 2020
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Online Access:https://ir.uitm.edu.my/id/eprint/47723/1/47723.pdf
https://ir.uitm.edu.my/id/eprint/47723/
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Institution: Universiti Teknologi Mara
Language: English
id my.uitm.ir.47723
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spelling my.uitm.ir.477232023-03-12T23:55:16Z https://ir.uitm.edu.my/id/eprint/47723/ Partial Least Square Structural Equation Modeling (PLS-SEM) / Nur Zainie Abd Hamid Abd Hamid, Nur Zainie HF Commerce Business Structural Equation Modeling (SEM) is a multivariate statistical analysis tool that is increasingly used to analyze structural relationship by the researcher in the business field. Two primary SEM techniques are Covariance-based Structural Equation Modeling (CB-SEM) and Partial Least Squares Structural Equation Modeling (PLS-SEM). CB-SEM is primarily used to confirm or reject theories by determining how well a proposed theoretical model can estimate the covariance matrix for a sample dataset. On the other hand, PLS-SEM is primarily used to develop theories in exploratory research by explaining the variance in the dependent variables when examining the model. Faculty of Business & Management, Universiti Teknologi MARA (UiTM) Cawangan Kedah 2020 Book Section PeerReviewed text en https://ir.uitm.edu.my/id/eprint/47723/1/47723.pdf Partial Least Square Structural Equation Modeling (PLS-SEM) / Nur Zainie Abd Hamid. (2020) In: FBM INSIGHTS Universiti Teknologi MARA Cawangan Kedah Vol. 1. Faculty of Business & Management, Universiti Teknologi MARA (UiTM) Cawangan Kedah, UiTM Cawangan Kedah, pp. 21-23. ISBN 2716-599X (Submitted)
institution Universiti Teknologi Mara
building Tun Abdul Razak Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Mara
content_source UiTM Institutional Repository
url_provider http://ir.uitm.edu.my/
language English
topic HF Commerce
Business
spellingShingle HF Commerce
Business
Abd Hamid, Nur Zainie
Partial Least Square Structural Equation Modeling (PLS-SEM) / Nur Zainie Abd Hamid
description Structural Equation Modeling (SEM) is a multivariate statistical analysis tool that is increasingly used to analyze structural relationship by the researcher in the business field. Two primary SEM techniques are Covariance-based Structural Equation Modeling (CB-SEM) and Partial Least Squares Structural Equation Modeling (PLS-SEM). CB-SEM is primarily used to confirm or reject theories by determining how well a proposed theoretical model can estimate the covariance matrix for a sample dataset. On the other hand, PLS-SEM is primarily used to develop theories in exploratory research by explaining the variance in the dependent variables when examining the model.
format Book Section
author Abd Hamid, Nur Zainie
author_facet Abd Hamid, Nur Zainie
author_sort Abd Hamid, Nur Zainie
title Partial Least Square Structural Equation Modeling (PLS-SEM) / Nur Zainie Abd Hamid
title_short Partial Least Square Structural Equation Modeling (PLS-SEM) / Nur Zainie Abd Hamid
title_full Partial Least Square Structural Equation Modeling (PLS-SEM) / Nur Zainie Abd Hamid
title_fullStr Partial Least Square Structural Equation Modeling (PLS-SEM) / Nur Zainie Abd Hamid
title_full_unstemmed Partial Least Square Structural Equation Modeling (PLS-SEM) / Nur Zainie Abd Hamid
title_sort partial least square structural equation modeling (pls-sem) / nur zainie abd hamid
publisher Faculty of Business & Management, Universiti Teknologi MARA (UiTM) Cawangan Kedah
publishDate 2020
url https://ir.uitm.edu.my/id/eprint/47723/1/47723.pdf
https://ir.uitm.edu.my/id/eprint/47723/
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