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Progress in partial least squares structural equation modeling use in logistics and supply chain management in the last decade: a structured literature review
PurposeThis study aims to evaluate the usage of partial least squares structural equation modeling (PLS-SEM) in journals related to logistics and supply chain management (LSCM).Design/methodology/approachBased on a structured literature review approach, the authors reviewed 401 articles in the field...
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Published in: | International journal of physical distribution & logistics management 2024-10, Vol.54 (7/8), p.673-704 |
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container_end_page | 704 |
container_issue | 7/8 |
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container_title | International journal of physical distribution & logistics management |
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creator | Wang, Siqi Cheah, Jun-Hwa Wong, Chee Yew Ramayah, T. |
description | PurposeThis study aims to evaluate the usage of partial least squares structural equation modeling (PLS-SEM) in journals related to logistics and supply chain management (LSCM).Design/methodology/approachBased on a structured literature review approach, the authors reviewed 401 articles in the field of LSCM applying PLS-SEM published in 15 major journals between 2014 and 2022. The analysis focused on reasons for using PLS-SEM, measurement model and structural model evaluation criteria, advanced analysis techniques and reporting practices.FindingsLSCM researchers sometimes did not clarify the reasons for using PLS-SEM, such as sample size, complex models and non-normal distributions. Additionally, most articles exhibit limited use of measurement models and structural model evaluation techniques, leading to inappropriate use of assessment criteria. Furthermore, progress in the practical implementation of advanced analysis techniques is slow, and there is a need for improved transparency in reporting analysis algorithms.Originality/valueThis study contributes to the field of LSCM by providing clear criteria and steps for using PLS-SEM, enriching the understanding and advancement of research methodologies in this field. |
doi_str_mv | 10.1108/IJPDLM-06-2023-0200 |
format | article |
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The analysis focused on reasons for using PLS-SEM, measurement model and structural model evaluation criteria, advanced analysis techniques and reporting practices.FindingsLSCM researchers sometimes did not clarify the reasons for using PLS-SEM, such as sample size, complex models and non-normal distributions. Additionally, most articles exhibit limited use of measurement models and structural model evaluation techniques, leading to inappropriate use of assessment criteria. 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The analysis focused on reasons for using PLS-SEM, measurement model and structural model evaluation criteria, advanced analysis techniques and reporting practices.FindingsLSCM researchers sometimes did not clarify the reasons for using PLS-SEM, such as sample size, complex models and non-normal distributions. Additionally, most articles exhibit limited use of measurement models and structural model evaluation techniques, leading to inappropriate use of assessment criteria. Furthermore, progress in the practical implementation of advanced analysis techniques is slow, and there is a need for improved transparency in reporting analysis algorithms.Originality/valueThis study contributes to the field of LSCM by providing clear criteria and steps for using PLS-SEM, enriching the understanding and advancement of research methodologies in this field.</description><subject>Algorithms</subject><subject>Criteria</subject><subject>Evaluation</subject><subject>Least squares</subject><subject>Literature reviews</subject><subject>Logistics</subject><subject>Modelling</subject><subject>Structural equation modeling</subject><subject>Structural models</subject><subject>Supply chain management</subject><subject>Supply chains</subject><issn>0960-0035</issn><issn>1758-664X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><recordid>eNp1Uc1O3DAQtqoidYE-QS-Weg4d2xvH6a2i0IIWsQeQuFmOPdk1yibBdqh4m30WnqyOthw49DSjme9H-j5CvjA4YwzUt6vr9c_VTQGy4MBFARzgA1mwqlSFlMuHj2QBtYQCQJSfyHGMjwDAasEXZL8OwyZgjNT3dDQhedPRDk1MND5NJn9oTGGyaQr5gfmU_NDT3eCw8_2GThEz83XfDRsfk7eRmt7ROI1j90Lt1mTVnenNBnfYp9kjbZF2s7xDaxx-p-Z1_-aAjnY-YTDzTgM-e_xzSo5a00X8_G-ekPvLi7vz38Xq9tfV-Y9VYcWyTIVhCprGMeVknq0A1YqchXLY1K3jJa-aijnZVqquK9ZklBXcLpWxvFwy58QJ-XrQHcPwNGFM-nGYQp8ttWBMSmClYhklDigbhhgDtnoMfmfCi2ag5yr0oQoNUs9V6LmKzOIHVk4hx-j-Q3rXn_gL1DGRoQ</recordid><startdate>20241017</startdate><enddate>20241017</enddate><creator>Wang, Siqi</creator><creator>Cheah, Jun-Hwa</creator><creator>Wong, Chee Yew</creator><creator>Ramayah, T.</creator><general>Emerald Publishing Limited</general><general>Emerald Group Publishing Limited</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7TA</scope><scope>8FD</scope><scope>JG9</scope><orcidid>https://orcid.org/0000-0002-4933-1770</orcidid><orcidid>https://orcid.org/0000-0001-8440-9564</orcidid><orcidid>https://orcid.org/0000-0001-6237-0099</orcidid><orcidid>https://orcid.org/0000-0002-7580-7058</orcidid></search><sort><creationdate>20241017</creationdate><title>Progress in partial least squares structural equation modeling use in logistics and supply chain management in the last decade: a structured literature review</title><author>Wang, Siqi ; Cheah, Jun-Hwa ; Wong, Chee Yew ; Ramayah, T.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c345t-a180bbd18d60bbf308f32028deb9fd2527b71d6f789971bd60c32c48ac2541dd3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Algorithms</topic><topic>Criteria</topic><topic>Evaluation</topic><topic>Least squares</topic><topic>Literature reviews</topic><topic>Logistics</topic><topic>Modelling</topic><topic>Structural equation modeling</topic><topic>Structural models</topic><topic>Supply chain management</topic><topic>Supply chains</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Wang, Siqi</creatorcontrib><creatorcontrib>Cheah, Jun-Hwa</creatorcontrib><creatorcontrib>Wong, Chee Yew</creatorcontrib><creatorcontrib>Ramayah, T.</creatorcontrib><collection>CrossRef</collection><collection>Materials Business File</collection><collection>Technology Research Database</collection><collection>Materials Research Database</collection><jtitle>International journal of physical distribution & logistics management</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Wang, Siqi</au><au>Cheah, Jun-Hwa</au><au>Wong, Chee Yew</au><au>Ramayah, T.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Progress in partial least squares structural equation modeling use in logistics and supply chain management in the last decade: a structured literature review</atitle><jtitle>International journal of physical distribution & logistics management</jtitle><date>2024-10-17</date><risdate>2024</risdate><volume>54</volume><issue>7/8</issue><spage>673</spage><epage>704</epage><pages>673-704</pages><issn>0960-0035</issn><eissn>1758-664X</eissn><abstract>PurposeThis study aims to evaluate the usage of partial least squares structural equation modeling (PLS-SEM) in journals related to logistics and supply chain management (LSCM).Design/methodology/approachBased on a structured literature review approach, the authors reviewed 401 articles in the field of LSCM applying PLS-SEM published in 15 major journals between 2014 and 2022. The analysis focused on reasons for using PLS-SEM, measurement model and structural model evaluation criteria, advanced analysis techniques and reporting practices.FindingsLSCM researchers sometimes did not clarify the reasons for using PLS-SEM, such as sample size, complex models and non-normal distributions. Additionally, most articles exhibit limited use of measurement models and structural model evaluation techniques, leading to inappropriate use of assessment criteria. Furthermore, progress in the practical implementation of advanced analysis techniques is slow, and there is a need for improved transparency in reporting analysis algorithms.Originality/valueThis study contributes to the field of LSCM by providing clear criteria and steps for using PLS-SEM, enriching the understanding and advancement of research methodologies in this field.</abstract><cop>Bradford</cop><pub>Emerald Publishing Limited</pub><doi>10.1108/IJPDLM-06-2023-0200</doi><tpages>32</tpages><orcidid>https://orcid.org/0000-0002-4933-1770</orcidid><orcidid>https://orcid.org/0000-0001-8440-9564</orcidid><orcidid>https://orcid.org/0000-0001-6237-0099</orcidid><orcidid>https://orcid.org/0000-0002-7580-7058</orcidid></addata></record> |
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language | eng |
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source | Emerald:Jisc Collections:Emerald Subject Collections HE and FE 2024-2026:Emerald Premier (reading list) |
subjects | Algorithms Criteria Evaluation Least squares Literature reviews Logistics Modelling Structural equation modeling Structural models Supply chain management Supply chains |
title | Progress in partial least squares structural equation modeling use in logistics and supply chain management in the last decade: a structured literature review |
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