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Journal articles on the topic 'SEM: Partial least squares'

Author: Grafiati

Published: 7 June 2025

Last updated: 2 August 2025

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1

Zulkifli, Raudhah, Nazim Aimran, Sayang Mohd Deni, and Fatin Najihah Badarisam. "A comparative study on the performance of maximum likelihood, generalized least square, scale-free least square, partial least square and consistent partial least square estimators in structural equation modeling." International Journal of Data and Network Science 6, no. 2 (2022): 391–400. http://dx.doi.org/10.5267/j.ijdns.2021.12.015.

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Structural equation modeling offers various estimation methods for estimating parameters. The most used method in covariance-based structural equation modeling (CB-SEM) is the maximum likelihood (ML) estimator. The ML estimator is typically used when fitting models with normally distributed data. The growth of partial least squares path modeling (PLS-PM), including consistent partial least squares (PLSc), has also been noticed by researchers in the SEM fields. The PLSc has elevated interest in the scholastic setting in measuring the performance of various estimation methods in structural equat

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F. Hair Jr, Joe, Marko Sarstedt, Lucas Hopkins, and Volker G. Kuppelwieser. "Partial least squares structural equation modeling (PLS-SEM)." European Business Review 26, no. 2 (2014): 106–21. http://dx.doi.org/10.1108/ebr-10-2013-0128.

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Purpose – The authors aim to present partial least squares (PLS) as an evolving approach to structural equation modeling (SEM), highlight its advantages and limitations and provide an overview of recent research on the method across various fields. Design/methodology/approach – In this review article, the authors merge literatures from the marketing, management, and management information systems fields to present the state-of-the art of PLS-SEM research. Furthermore, the authors meta-analyze recent review studies to shed light on popular reasons for PLS-SEM usage. Findings – PLS-SEM has exper

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Hair, Joseph F., Marko Sarstedt, and Christian M. Ringle. "Rethinking some of the rethinking of partial least squares." European Journal of Marketing 53, no. 4 (2019): 566–84. http://dx.doi.org/10.1108/ejm-10-2018-0665.

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PurposePartial least squares structural equation modeling (PLS-SEM) is an important statistical technique in the toolbox of methods that researchers in marketing and other social sciences disciplines frequently use in their empirical analyses. The purpose of this paper is to shed light on several misconceptions that have emerged as a result of the proposed “new guidelines” for PLS-SEM. The authors discuss various aspects related to current debates on when or when not to use PLS-SEM, and which model evaluation metrics to apply. In addition, this paper summarizes several important methodological

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Nitzl, Christian, Jose L. Roldan, and Gabriel Cepeda. "Mediation analysis in partial least squares path modeling." Industrial Management & Data Systems 116, no. 9 (2016): 1849–64. http://dx.doi.org/10.1108/imds-07-2015-0302.

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Purpose Indirect or mediated effects constitute a type of relationship between constructs that often occurs in partial least squares (PLS) path modeling. Over the past few years, the methods for testing mediation have become more sophisticated. However, many researchers continue to use outdated methods to test mediating effects in PLS, which can lead to erroneous results. One reason for the use of outdated methods or even the lack of their use altogether is that no systematic tutorials on PLS exist that draw on the newest statistical findings. The paper aims to discuss these issues. Design/met

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Lorenzo, Hadrien, Olivier Cloarec, Rodolphe Thiébaut, and Jérôme Saracco. "Data‐driven sparse partial least squares." Statistical Analysis and Data Mining: The ASA Data Science Journal 15, no. 2 (2021): 264–82. http://dx.doi.org/10.1002/sam.11558.

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Xu, Chuangwen, and Hualing Chen. "Milling tool wear forecast based on the partial least-squares regression analysis." Structural Engineering and Mechanics 31, no. 1 (2009): 57–74. http://dx.doi.org/10.12989/sem.2009.31.1.057.

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Usakli, Ahmet, and Kemal Gurkan Kucukergin. "Using partial least squares structural equation modeling in hospitality and tourism." International Journal of Contemporary Hospitality Management 30, no. 11 (2018): 3462–512. http://dx.doi.org/10.1108/ijchm-11-2017-0753.

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PurposeThe purpose of this study is to review the use of partial least squares-structural equation modeling (PLS-SEM) in the field of hospitality and tourism and thereby to assess whether the PLS-SEM-based papers followed the recommended application guidelines and to investigate whether a comparison of journal types (hospitality vs tourism) and journal qualities (top-tier vs other leading) reveal significant differences in PLS-SEM use.Design/methodology/approachA total of 206 PLS-SEM based papers published between 2000 and April 2017 in the 19 SSCI-indexed hospitality and tourism journals were

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Henseler, Jörg, Christian M. Ringle, and Marko Sarstedt. "Testing measurement invariance of composites using partial least squares." International Marketing Review 33, no. 3 (2016): 405–31. http://dx.doi.org/10.1108/imr-09-2014-0304.

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Purpose – Research on international marketing usually involves comparing different groups of respondents. When using structural equation modeling (SEM), group comparisons can be misleading unless researchers establish the invariance of their measures. While methods have been proposed to analyze measurement invariance in common factor models, research lacks an approach in respect of composite models. The purpose of this paper is to present a novel three-step procedure to analyze the measurement invariance of composite models (MICOM) when using variance-based SEM, such as partial least squares (

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Putra, Wawas Bangun Tegar Sunaryo. "Permasalahan, Kepercayaan Umum dan Prosedur Penggunaan Partial Least Squares Structural Equation Modeling Pada Penelitian Bisnis." South Asian Journal of Social Studies and Economics 14, no. 1 (2022): 1–20. https://doi.org/10.5281/zenodo.6545357.

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Partial least squares structural equation modeling atau biasa disebut sebagai PLS-SEM dikembangkan bukan tanpa alasan. PLS-SEM dikembangkan sebagai alternatif untuk covariance-based SEM, yang memungkinkan peneliti untuk menjalankan penelitian exploratory. Selain itu, PLS-SEM dinilai mampu memberikan fleksibilitas terkait dengan karakteristik data, kompleksitas model maupun model spesifikasi. Tak ayal, PLS-SEM menjadi metode paling sering digunakan dalam banyak bidang di penelitian bisnis. Namun demikian, banyak dari peneliti yang menggunakan PLS-SEM secara tidak tepat bahkan berekspektasi lebi

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Khan, Gohar F., Marko Sarstedt, Wen-Lung Shiau, Joseph F. Hair, Christian M. Ringle, and Martin P. Fritze. "Methodological research on partial least squares structural equation modeling (PLS-SEM)." Internet Research 29, no. 3 (2019): 407–29. http://dx.doi.org/10.1108/intr-12-2017-0509.

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Purpose The purpose of this paper is to explore the knowledge infrastructure of methodological research on partial least squares structural equation modeling (PLS-SEM) from a network point of view. The analysis involves the structures of authors, institutions, countries and co-citation networks, and discloses trending developments in the field. Design/methodology/approach Based on bibliometric data downloaded from the Web of Science, the authors apply various social network analysis (SNA) and visualization tools to examine the structure of knowledge networks of the PLS-SEM domain. Specifically

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Gemar, Pablo, German Gemar, and Vanesa Guzman-Parra. "Modeling the Sustainability of Bank Profitability Using Partial Least Squares." Sustainability 11, no. 18 (2019): 4950. http://dx.doi.org/10.3390/su11184950.

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This study sought to develop a model that can predict banks’ profitability and help the corporate governing bodies of financial institutions to define strategies that address possible adverse scenarios. The partial least squares approach to structural equation model (SEM) was used to process data on the 100 largest banks in the world by volume of assets, between 2011 and 2015, as well as macroeconomic variables of the countries in which the banks were headquartered. A model able to predict the banks’ profitability was created using the latent variables of capital adequacy, operations, asset qu

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Shiau, Wen-Lung, Marko Sarstedt, and Joseph F. Hair. "Internet research using partial least squares structural equation modeling (PLS-SEM)." Internet Research 29, no. 3 (2019): 398–406. http://dx.doi.org/10.1108/intr-10-2018-0447.

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Leguina, Adrian. "A primer on partial least squares structural equation modeling (PLS-SEM)." International Journal of Research & Method in Education 38, no. 2 (2015): 220–21. http://dx.doi.org/10.1080/1743727x.2015.1005806.

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Marliana, Reny Rian. "PARTIAL LEAST SQUARE-STRUCTURAL EQUATION MODELING PADA HUBUNGAN ANTARA TINGKAT KEPUASAN MAHASISWA DAN KUALITAS GOOGLE CLASSROOM BERDASARKAN METODE WEBQUAL 4.0." Jurnal Matematika, Statistika dan Komputasi 16, no. 2 (2019): 174. http://dx.doi.org/10.20956/jmsk.v16i2.7851.

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AbstractThis paper studied a relationship between the quality of google classroom and student satisfaction. The quality of google classroom measured based on the Webqual 4.0 which is consists of four variables i.e. information quality, service interaction quality, user interface quality and usability. The relationship modeling between these latent variables and the student satisfaction was done by using the Partial Least Square-Structural Equation Modeling (PLS-SEM). Estimation parameters of the model used PLS-SEM algorithm and Ordinary Least Square (OLS) method. Data was collected using a que

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Serrato González, Hugo, Ignacio Méndez Ramírez, and Odette Lobato Calleros. "The sampling design effect on partial least squares algorithm." RECI Revista Iberoamericana de las Ciencias Computacionales e Informática 5, no. 9 (2016): 84. http://dx.doi.org/10.23913/reci.v5i9.44.

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The objective of this article is to analyze the effect of the probability sampling’s selection on the estimated results in Structural Equation Modeling (SEM) using the Partial Least Squares (PLS) algorithm.The idea leading this work is to estimate the satisfaction level of government service users in a large and dispersed population, for which a sample design with an equal selection probability is not a feasible option. This study is based on the analysis of the sampling distributions of estimators under different sampling designs.It is shown that the probability of selection of the units behi

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Hult, G. Tomas M., Joseph F. Hair, Dorian Proksch, Marko Sarstedt, Andreas Pinkwart, and Christian M. Ringle. "Addressing Endogeneity in International Marketing Applications of Partial Least Squares Structural Equation Modeling." Journal of International Marketing 26, no. 3 (2018): 1–21. http://dx.doi.org/10.1509/jim.17.0151.

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Partial least squares structural equation modeling (PLS-SEM) has become a key method in international marketing research. Users of PLS-SEM have, however, largely overlooked the issue of endogeneity, which has become an integral component of regression analysis applications. This lack of attention is surprising because the PLS-SEM method is grounded in regression analysis, for which numerous approaches for handling endogeneity have been proposed. To identify and treat endogeneity, and create awareness of how to deal with this issue, this study introduces a systematic procedure that translates c

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Lenggogeni, Sari. "Why Is The Partial Least Square Important For Tourism Studies." International Journal of Tourism, Heritage and Recreation Sport 1, no. 2 (2019): 7–15. http://dx.doi.org/10.24036/ijthrs.v1i2.27.

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Although the multiple regression method has been applied to exploratory research on most tourism studies, there is lack of understanding on studies that present a well-justified rationale in choosing a robust statistical tool for data analysis. This research note aims to review why tourism researchers are encouraged to use the Partial Least Squares Structural Equation Modelling (PLS-SEM) method to address this research problem. This article provides rationale, comparisons among techniques for multiple regression-based papers and suggestions for tourism researchers to justify why PLS-SEM is imp

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Cepeda-Carrion, Gabriel, Juan-Gabriel Cegarra-Navarro, and Valentina Cillo. "Tips to use partial least squares structural equation modelling (PLS-SEM) in knowledge management." Journal of Knowledge Management 23, no. 1 (2019): 67–89. http://dx.doi.org/10.1108/jkm-05-2018-0322.

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PurposeStructural equation modelling (SEM) has been defined as the combination of latent variables and structural relationships. The partial least squares SEM (PLS-SEM) is used to estimate complex cause-effect relationship models with latent variables as the most salient research methods across a variety of disciplines, including knowledge management (KM). Following the path initiated by different domains in business research, this paper aims to examine how PLS-SEM has been applied in KM research, also providing some new guidelines how to improve PLS-SEM report analysis.Design/methodology/appr

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Adi, Arini Annisa, Mohammad Masjkur, and Erfiani Erfiani. "Penerapan Structural Equation Modelling-Partial Least Squares pada Faktor Kemiskinan di Jawa Tengah." Xplore: Journal of Statistics 11, no. 2 (2022): 84–95. http://dx.doi.org/10.29244/xplore.v11i2.875.

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Jumlah penduduk miskin di Jawa Tengah pada Maret 2020 sebesar 3,98 juta orang (11,41%), peringkat kedua terbesar di Pulau Jawa. Angka jumlah penduduk miskin yang relatif tinggi menjadi prioritas bagi pemerintah untuk menanggulangi kemiskinan. Salah satu cara penanggulangan kemiskinan adalah dengan mengetahui faktor kemiskinan. Penelitian ini bertujuan untuk mengidentifikasi faktor kemiskinan di Jawa Tengah menggunakan metode Structural Equation Modelling-Partial Least Squares (SEM-PLS). Data yang digunakan dalam penelitian ini adalah data kabupaten/kota di Jawa Tengah tahun 2020. Pada kasus in

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Thien, Lei Mee, and Meow Yem Tan. "KEPIMPINAN DISTRIBUTIF, KEADAAN DALAM SEKOLAH, DAN KOMITMEN GURU UNTUK BERUBAH: SATU ANALISA PARTIAL LEAST SQUARES[DISTRIBUTIVE LEADERSHIP, IN-SCHOOL CONDITION, AND TEACHERS’ COMMITMENT TO CHANGE: A PARTIAL LEAST SQUARES ANALYSIS]." Journal of Nusantara Studies (JONUS) 4, no. 1 (2019): 159. http://dx.doi.org/10.24200/jonus.vol4iss1pp159-185.

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Kajian ini bertujuan untuk mengkaji hubungan antara kepimpinan distributif terhadap komitmen guru untuk berubah dengan keadaan dalam sekolah sebagai mediator. Kajian ini menggunakan reka bentuk kajian kuantitatif dengan kaedah tinjauan. Sampel kajian terdiri daripada 357 orang guru-guru sekolah menengah yang dipilih secara rawak daripada 20 buah sekolah di Daerah Seberang Perai Utara dan Seberang Perai Tengah di Pulau Pinang, Malaysia. Pendekatan Partial Least Squares Structural Equation Modeling (PLS-SEM) dengan perisian SmartPLS 3.2.7 digunakan untuk penganalisaan data. Dapatan kajian ini me

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Richter, Nicole F., Gabriel Cepeda, José L. Roldán, and Christian M. Ringle. "European management research using Partial Least Squares Structural Equation Modeling (PLS-SEM)." European Management Journal 33, no. 1 (2015): 1–3. http://dx.doi.org/10.1016/j.emj.2014.12.001.

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Richter, Nicole Franziska, Gabriel Cepeda, José Luis Roldán, and Christian M. Ringle. "European management research using partial least squares structural equation modeling (PLS-SEM)." European Management Journal 34, no. 6 (2016): 589–97. http://dx.doi.org/10.1016/j.emj.2016.08.001.

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Miftahuddin, Miftahuddin, Retno Wahyuni Putri, Ichsan Setiawan, and Rina Suryani Oktari. "MODELING OF SEA SURFACE TEMPERATURE BASED ON PARTIAL LEAST SQUARE - STRUCTURAL EQUATION." MEDIA STATISTIKA 14, no. 2 (2021): 170–82. http://dx.doi.org/10.14710/medstat.14.2.170-182.

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Variability of Sea Surface Temperature (SST) is one of the climatic features that influence global and regional climate dynamics. Missing data (gaps) in the SST dataset are worth investigating since they may statistically alter the value of the SST change. The partial least square-structural equation modeling (PLS-SEM) approach is used in this work to estimate the causality relationships between exogenous and endogenous latent variables. The findings of this study, which are significant indicators that have a loading factor value > 0.7 are as follows: i) sea surface temperature (oC) as a me

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Yuan, Ke-Hai, and Lifang Deng. "Equivalence of Partial-Least-Squares SEM and the Methods of Factor-Score Regression." Structural Equation Modeling: A Multidisciplinary Journal 28, no. 4 (2021): 557–71. http://dx.doi.org/10.1080/10705511.2021.1894940.

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Xu, Lihua, Read Diket, and Thomas Brewer. "Predicting student performance via NAEP secondary art analysis using partial least squares SEM." Arts Education Policy Review 119, no. 4 (2017): 231–42. http://dx.doi.org/10.1080/10632913.2017.1327382.

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George, Benjamin, and Victor Prybutok. "Development of a polar extreme method for use in partial least squares SEM." Quality & Quantity 49, no. 2 (2014): 471–88. http://dx.doi.org/10.1007/s11135-014-0004-0.

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Latif, Imam Sofarudin, Rujianto Eko Saputro, and Azhari Shouni Barkah. "Technology Acceptance Model TAM using Partial Least Squares Structural Equation Modeling PLS- SEM." Journal of Information Systems and Informatics 7, no. 2 (2025): 1376–99. https://doi.org/10.51519/journalisi.v7i2.1104.

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The rapid advancement of digital technologies necessitates a deeper focus on user acceptance and satisfaction, particularly within the framework of the Technology Acceptance Model (TAM), analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). This systematic literature review examines 36 articles published between 2020 and 2025, revealing that factors such as trust, system quality, perceived enjoyment, service quality, and technological self-efficacy significantly influence user satisfaction. These external variables enhance the explanatory power of TAM, providing a richer

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Paris, Muhammad Amin. "PERBANDINGAN ANTARA UNWEIGHTED LEAST SQUARES (ULS) DAN PARTIAL LEAST SQUARES (PLS) DALAM PEMODELAN PERSAMAAN STRUKTURAL (STUDI KASUS MODEL ANALISIS PRESTASI BELAJAR MAHASISWA TAHUN PERTAMA PROGRAM STUDI S1 MATEMATIKA FMIPA-INSTUTUT PERTANIAN BOGOR)." Jurnal Pendidikan Matematika 2, no. 1 (2017): 21. http://dx.doi.org/10.18592/jpm.v2i1.1165.

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Structural Equation Modeling (SEM) is one of multivariate techniques that can estimates a series of interrelated dependence relationships from a number of endogenous and exogenous variables, as well as latent (unobserved) variables simultaneously. Estimation of Parameter methods that is often applied in SEM are Maximum Likelihood (ML), Weighted Least Squares (WLS), Unweighted Least Squares (ULS), Generalized Least Squares (GLS) and Partial Least Squares (PLS). This research aims to compare ULS method and PLS method in estimating parameter model of achievement of student learning in first year

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Allen, Genevera I., Christine Peterson, Marina Vannucci, and Mirjana Maletić-Savatić. "Regularized partial least squares with an application to NMR spectroscopy." Statistical Analysis and Data Mining: The ASA Data Science Journal 6, no. 4 (2012): 302–14. http://dx.doi.org/10.1002/sam.11169.

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Algi Ardiyansyah and Endang Iryanti. "The Effect Of Work Discipline and Work Environment On Employee Loyalty Of The Post Office Operations Division Main Branch Surabaya 60000." Green Inflation: International Journal of Management and Strategic Business Leadership 1, no. 4 (2024): 288–95. http://dx.doi.org/10.61132/greeninflation.v1i4.138.

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The goal of this study is to determine how employee loyalty is affected by work environment and discipline in the operations division of the Surabaya Main Branch Post Office 60000. Primary data from questionnaires given to respondents served as the basis for this study. Structural Equation Model-Partial Least Square (SEM-PLS) is a statistical analysis tool used in research data processing that use partial least squares analysis methodologies. According to the study’s findings, employee loyalty is positively impacted by work environment and discipline.

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Mukid, Moch Abdul, Bambang Widjanarko Otok, and Agus Suharsono. "Segmentation in Structural Equation Modeling Using a Combination of Partial Least Squares and Modified Fuzzy Clustering." Symmetry 14, no. 11 (2022): 2431. http://dx.doi.org/10.3390/sym14112431.

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The application of a structural equation modeling (SEM) assumes that all data follow only one model. This assumption may be inaccurate in certain cases because individuals tend to differ in their responses, and failure to consider heterogeneity may threaten the validity of the SEM results. This study focuses on unobservable heterogeneity, where the difference between two or more data sets does not depend on observable characteristics. In this study, we propose a new method for estimating SEM parameters containing unobserved heterogeneity within the data and assume that the heterogeneity arises

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Ross, James, Leslie Nuñez, and Chinh Chu Lai. "Partial least squares structural equation modeling of chemistry attitude in introductory college chemistry." Chemistry Education Research and Practice 19, no. 4 (2018): 1270–86. http://dx.doi.org/10.1039/c7rp00238f.

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Students’ decisions to enter or persist in STEM courses is linked with their affective domain. The influence of factors impacting students’ affective domain in introductory college chemistry classes, such as attitude, is often overlooked by instructors, who instead focus on students’ mathematical abilities as sole predictors of academic achievement. The current academic barrier to enrollment in introductory college chemistry classes is typically a passing grade in a mathematics prerequisite class. However, mathematical ability is only a piece of the puzzle in predicting preparedness for colleg

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Cepeda-Carrión, Gabriel, Joseph F. Hair, Christian M. Ringle, José Luis Roldán, and Jerónimo García-Fernández. "Guest editorial: Sports management research using partial least squares structural equation modeling (PLS-SEM)." International Journal of Sports Marketing and Sponsorship 23, no. 2 (2022): 229–40. http://dx.doi.org/10.1108/ijsms-05-2022-242.

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Gye-Soo, Kim. "Partial Least Squares Structural Equation Modeling(PLS-SEM): An application in Customer Satisfaction Research." International Journal of u- and e- Service, Science and Technology 9, no. 4 (2016): 61–68. http://dx.doi.org/10.14257/ijunesst.2016.9.4.07.

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Mooi, Zhi Yin. "Mobile-social media shopping: a partial least squares-structural equation modelling (PLS-SEM) approach." International Journal of Modelling in Operations Management 7, no. 1 (2018): 1. http://dx.doi.org/10.1504/ijmom.2018.095659.

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Mooi, Zhi Yin. "Mobile-social media shopping: a partial least squares-structural equation modelling (PLS-SEM) approach." International Journal of Modelling in Operations Management 7, no. 1 (2018): 1. http://dx.doi.org/10.1504/ijmom.2018.10016850.

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Magno, Francesca, Fabio Cassia, and Christian M. Ringle. "Guest editorial: Using partial least squares structural equation modeling (PLS-SEM) in quality management." TQM Journal 36, no. 5 (2024): 1237–41. http://dx.doi.org/10.1108/tqm-06-2024-426.

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Ali, Faizan, Woo Gon Kim, Jun (Justin) Li, and Cihan Cobanoglu. "A comparative study of covariance and partial least squares based structural equation modelling in hospitality and tourism research." International Journal of Contemporary Hospitality Management 30, no. 1 (2018): 416–35. http://dx.doi.org/10.1108/ijchm-08-2016-0409.

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Purpose Structural equation modelling (SEM) has increasingly been used by hospitality and tourism researchers to examine complex relationships. This paper aims to highlight the benefits and limitations of SEM for hospitality and tourism research and compare its two main approaches, i.e. covariance-based SEM (CB-SEM) and partial least squares-SEM (PLS-SEM). Design/methodology/approach By using a comparative approach, this study parallels SEM’s two main approaches, i.e. CB-SEM and PLS-SEM, using three different examples from hospitality and tourism industry. Both the approaches are compared side

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Jin, Yanmin, Lingling Wei, Bin Wang, Xiongfeng Yan, Shijie Liu, and Xiaohua Tong. "Constrained Building Boundary Simplification Based on Partial Total Least Squares Method." Sensors and Materials 32, no. 12 (2020): 4559. http://dx.doi.org/10.18494/sam.2020.3133.

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Perdana, Petrolis Nusa, Diah Armeliza, Hera Khairunnisa, and Hafifah Nasution. "Research Data Processing Through Structural Equation Model-Partial Least Square (SEM-PLS) Method." Jurnal Pemberdayaan Masyarakat Madani (JPMM) 7, no. 1 (2023): 44–50. http://dx.doi.org/10.21009/jpmm.007.1.05.

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Structural Equation Modeling (SEM) is one type of multivariate analysis in the social sciences. Multivariate analysis is the application of statistical methods to analyze several research variables simultaneously. This community service activity was held and aimed at the academic community (lecturers and students) from partner campuses of the Faculty of Economics, State University of Jakarta, they are FEB UHAMKA, STIE Indonesia, and Tempo Polytechnic with the aim of providing knowledge about research methodologies, especially the Structural Equation Modeling method (SEM) – Partial Least Square

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Afthanorhan, Asyraf, Zainudin Awang, and Nazim Aimran. "Five Common Mistakes for Using Partial Least Squares Path Modeling (PLS-PM) in Management Research." Contemporary Management Research 16, no. 4 (2020): 255–78. http://dx.doi.org/10.7903/cmr.20247.

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The value of Partial Least Squares Path Modeling (PLS-PM) in management research has now been acknowledged, although the PLS-PM was developed for a reason. First, the PLS-PM was developed as an alternative to Covariance based Structural Equation Modeling (CBSEM) when exploratory research is conducted. As far as this method concerned, many researchers are misused or overuse the application of PLS-PM without understanding the basic knowledge in structural equation modeling. Thus, the purpose of this paper is to discuss the five common mistakes (data distributions, sample size limitations, unsati

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Nor, Azima Ahmad, Ismail Azman, and Md Sham Fariza. "The Impact of Perceived Organizational Support on Organizational Commitment." International Journal of Recent Technology and Engineering (IJRTE) 9, no. 4 (2020): 421–25. https://doi.org/10.35940/ijrte.D5038.119420.

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This study measure the relationship between perceived organizational support and organizational commitment. Data were collected from 100 government employee in Malaysia in a cross-sectional study using survey method. The partial least squares structural equation model (PLS-SEM) version 3.3 was used for data analysis to test on convergent validity. The outcomes of testing hypothesis using Smart Partial Least Squares (Smart PLS) path model analysis reveals two findings, first: supervisor support significantly positive with organizational commitment. Second, co-workers support significantly posit

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Amriza, Rona Nisa Sofia, and Khairun Nisa Meiah Ngafidin. "ANALISIS PENGARUH PLATFORM SOSIAL MEDIA TERHADAP PENYEBARAN INFORMASI BENCANA." JSiI (Jurnal Sistem Informasi) 8, no. 2 (2021): 82–87. http://dx.doi.org/10.30656/jsii.v8i2.3639.

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Abstrak- Sosial media menjadi platform yang sangat berperan dalam menyebarkan informasi, berita, dan memberikan informasi bencana secara cepat dan tepat. Banyak informasi berharga yang dapat diperoleh dalam platform ini. Penelitian ini menganalisis pengaruh platform sosial media terhadap intensi masyarakat untuk menyebarkan informasi bencana yang dipengaruhi oleh mediator personal yaitu altruisme dan efikasi diri. Penelitian ini mengobservasi penyebab seseorang memiliki intensi untuk menyebarkan informasi bencana. Structural Equation Modeling Partial Least Squares (SEM-PLS) digunakan untuk mel

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Chin, Wynne, Jun-Hwa Cheah, Yide Liu, Hiram Ting, Xin-Jean Lim, and Tat Huei Cham. "Demystifying the role of causal-predictive modeling using partial least squares structural equation modeling in information systems research." Industrial Management & Data Systems 120, no. 12 (2020): 2161–209. http://dx.doi.org/10.1108/imds-10-2019-0529.

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PurposePartial least squares structural equation modeling (PLS-SEM) has become popular in the information systems (IS) field for modeling structural relationships between latent variables as measured by manifest variables. However, while researchers using PLS-SEM routinely stress the causal-predictive nature of their analyses, the model evaluation assessment relies exclusively on criteria designed to assess the path model's explanatory power. To take full advantage of the purpose of causal prediction in PLS-SEM, it is imperative for researchers to comprehend the efficacy of various quality cri

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Hossain, Md Moazzem, Manzurul Alam, Mohammed Alamgir, and Amirus Salat. "Factors affecting business graduates' employability–empirical evidence using partial least squares (PLS)." Education + Training 62, no. 3 (2020): 292–310. http://dx.doi.org/10.1108/et-12-2018-0258.

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PurposeThe purpose of this paper is to examine the relationship between skills and employability of business graduates. The study also examines the moderating effect of ‘social mobility factors’ in the ‘skills–employability’ relationship.Design/methodology/approachA quantitative positivist approach was undertaken to test the hypotheses. Business graduates from two universities in a developing country responded to a questionnaire about their perceptions of different sets of employability factors. Partial least squares (PLS)-based structural equation modelling (SEM) was used to examine the relat

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Salarzadeh Jenatabadi, Hashem, Che Wan Jasimah Bt Wan Mohamed Radzi, and Nadia Samsudin. "Associations of Body Mass Index with Demographics, Lifestyle, Food Intake, and Mental Health among Postpartum Women: A Structural Equation Approach." International Journal of Environmental Research and Public Health 17, no. 14 (2020): 5201. http://dx.doi.org/10.3390/ijerph17145201.

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As postpartum obesity is becoming a global public health challenge, there is a need to apply postpartum obesity modeling to determine the indicators of postpartum obesity using an appropriate statistical technique. This research comprised two phases, namely: (i) development of a previously created postpartum obesity modeling; (ii) construction of a statistical comparison model and introduction of a better estimator for the research framework. The research model displayed the associations and interactions between the variables that were analyzed using the Structural Equation Modeling (SEM) meth

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Chinnaraju, Arunraju. "Partial least squares structural equation modeling (PLS-SEM) in the AI Era: Innovative methodological guide and framework for business research." Magna Scientia Advanced Research and Reviews 13, no. 2 (2025): 062–108. https://doi.org/10.30574/msarr.2025.13.2.0048.

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<strong>This is the author-archived version of the article titled</strong><em>“Partial Least Squares Structural Equation Modeling (PLS-SEM) in the AI Era: Innovative Methodological Guide and Framework for Business Research”</em>,published in <em>Magna Scientia Advanced Research and Reviews</em>, Vol. 13, Issue 2, 2025. The official published version is available at: https://doi.org/10.30574/msarr.2025.13.2.0048 URL: https://magnascientiapub.com/journals/msarr/sites/default/files/MSARR-2025-0048.pdf Metadata: https://arcr-debug.github.io/pls-sem-ai-article/This version has been depo

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Chinnaraju, Arunraju. "Partial least squares structural equation modeling (PLS-SEM) in the AI Era: Innovative methodological guide and framework for business research." Magna Scientia Advanced Research and Reviews 13, no. 2 (2025): 062–108. https://doi.org/10.5281/zenodo.15331201.

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<strong>This is the author-archived version of the article titled</strong><em>“Partial Least Squares Structural Equation Modeling (PLS-SEM) in the AI Era: Innovative Methodological Guide and Framework for Business Research”</em>,published in <em>Magna Scientia Advanced Research and Reviews</em>, Vol. 13, Issue 2, 2025. The official published version is available at: https://doi.org/10.30574/msarr.2025.13.2.0048 URL: https://magnascientiapub.com/journals/msarr/sites/default/files/MSARR-2025-0048.pdf Metadata: https://arcr-debug.github.io/pls-sem-ai-article/This version has been depo

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Dalowar, Hossan Ayesha Aktar Qing Zhang. "A Study on Partial Least Squares Structural Equation Modeling (PLS-SEM) as Emerging Tool in Action Research." LC International Journal of STEM (ISSN: 2708-7123) 1, no. 4 (2021): 130–46. https://doi.org/10.5281/zenodo.11488980.

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Structural equation modeling (SEM) depicts one of the most salient research methods across a variety of disciplines, including educational management. Recent research advocates the use of partial least squares structural equation modeling (PLS-SEM) as an attractive tool in action research. The purpose of this paper is to systematically examine how PLS-SEM has been applied in action research with the aim of investigating the effect of teacher’s leadership styles (transformational and transaction) and student’s motivational factors (intrinsic and extrinsic) on student engagement for

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Tirta, I. Made, Nawal Ika Susanti, and Yuliani Setia Dewi. "Structural Equation Modeling of the Factors Affecting the Nutritional Status of Children Under Five in Banyuwangi Region using Recursive (one-way) GSCA." Jurnal ILMU DASAR 16, no. 1 (2015): 1. http://dx.doi.org/10.19184/jid.v16i1.534.

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Structural Equation Modeling is one among popular multivariate analysis, especially applied in pschology and marketing. There are two main types of Structural Equation Modeling namely covariance-based or CB-SEM and variance-based or Partial Least Square (PLS)- SEM. Both types have advantages and disadvantage. To overcome its limitation, Generalized Structured Component Analysis (GSCA) was then proposed as an extension of PLS-SEM. In estimating the parameters, GSCA uses Alternating Least Squares (ALS) and in estimating the standard error of the parameter estimates it uses the bootstrap method.

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