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Key Issues on Partial Least Squares (PLS) in Operations Management Research: A Guide to Submissions

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Key Issues on Partial Least Squares (PLS) in Operations Management Research: A Guide to Submissions

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dc.contributor.author Marin-Garcia, Juan A. es_ES
dc.contributor.author Alfalla-Luque, Rafaela es_ES
dc.date.accessioned 2021-01-12T21:02:11Z
dc.date.available 2021-01-12T21:02:11Z
dc.date.issued 2019 es_ES
dc.identifier.issn 2013-0953 es_ES
dc.identifier.uri http://hdl.handle.net/10251/158834
dc.description.abstract [EN] Purpose: This work aims to systematise the use of PLS as an analysis tool via a usage guide or recommendation for researchers to help them eliminate errors when using this tool. Design/methodology/approach: A recent literature review about PLS and discussion with experts in the methodology. Findings: This article considers the current situation of PLS after intense academic debate in recent years, and summarises recommendations to properly conduct and report a research work that uses this methodology in its analyses. We particularly focus on how to: choose the construct type; choose the estimation technique (PLS or CB-SEM); evaluate and report the measurement model; evaluate and report the structural model; analyse statistical power. Research limitations: It was impossible to cover some relevant aspects in considerable detail herein: presenting a guided example that respects all the report recommendations presented herein to act as a practical guide for authors; does the specification or evaluation of the measurement model differ when it deals with first-order or second-order constructs?; how are the outcomes of the constructs interpreted with the indicators being measured with nominal measurement levels?; is the Confirmatory Composite Analysis approach compatible with recent proposals about the Confirmatory Tetrad Analysis (CTA)? These themes will the object of later publications. Originality/value: We provide a check list of the information elements that must contain any article using PLS. Our intention is for the article to act as a guide for the researchers and possible authors who send works to the JIEM (Journal of Industrial and Engineering Management). This guide could be used by both editors and reviewers of JIEM, or other journals in this area, to evaluate and reduce the risk of bias (Losilla, Oliveras, Marin-Garcia & Vives, 2018) in works using PLS as an analysis procedure. es_ES
dc.language Inglés es_ES
dc.publisher Omnia Publisher SL es_ES
dc.relation.ispartof Journal of Industrial Engineering and Management es_ES
dc.rights Reconocimiento - No comercial (by-nc) es_ES
dc.subject PLS-SEM es_ES
dc.subject Partial Least Squares es_ES
dc.subject Operations management es_ES
dc.subject Reporting standards es_ES
dc.subject.classification ORGANIZACION DE EMPRESAS es_ES
dc.title Key Issues on Partial Least Squares (PLS) in Operations Management Research: A Guide to Submissions es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.3926/jiem.2944 es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Organización de Empresas - Departament d'Organització d'Empreses es_ES
dc.description.bibliographicCitation Marin-Garcia, JA.; Alfalla-Luque, R. (2019). Key Issues on Partial Least Squares (PLS) in Operations Management Research: A Guide to Submissions. Journal of Industrial Engineering and Management. 12(2):219-240. https://doi.org/10.3926/jiem.2944 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.3926/jiem.2944 es_ES
dc.description.upvformatpinicio 219 es_ES
dc.description.upvformatpfin 240 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 12 es_ES
dc.description.issue 2 es_ES
dc.relation.pasarela S\401180 es_ES


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