Amanda E. Legate, Christian M. Ringle, Joseph F. Hair Jr.
{"title":"PLS-SEM: A method demonstration in the R statistical environment","authors":"Amanda E. Legate, Christian M. Ringle, Joseph F. Hair Jr.","doi":"10.1002/hrdq.21517","DOIUrl":null,"url":null,"abstract":"<p>In line with calls to stimulate methodological diversity and support evidence-based human resource development (HRD) through quantitative competencies, we present a methods demonstration leveraging open-source tools and lesser-known quantitative research methods to support the HRD research community and applied HRD in the workplace. In this paper, we provide an informative introduction to partial least squares structural equation modeling (PLS-SEM). We discuss PLS-SEM application trends in the field of HRD, present key characteristics of the method, and demonstrate up-to-date metrics and evaluation guidelines using an illustrative model. Our PLS-SEM demonstration and explanations can serve as a valuable resource for practitioners concerned with substantiating results for organizational stakeholders and support researchers in methodological decision-making while avoiding common pitfalls associated with less familiar methods. Our step-by-step demonstration is conducted in open-source software and accompanied by explicitly coded operations so that readers can easily replicate the illustrative analyses presented.</p>","PeriodicalId":47803,"journal":{"name":"Human Resource Development Quarterly","volume":"35 4","pages":"501-529"},"PeriodicalIF":4.0000,"publicationDate":"2023-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Human Resource Development Quarterly","FirstCategoryId":"91","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/hrdq.21517","RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"INDUSTRIAL RELATIONS & LABOR","Score":null,"Total":0}
引用次数: 0
Abstract
In line with calls to stimulate methodological diversity and support evidence-based human resource development (HRD) through quantitative competencies, we present a methods demonstration leveraging open-source tools and lesser-known quantitative research methods to support the HRD research community and applied HRD in the workplace. In this paper, we provide an informative introduction to partial least squares structural equation modeling (PLS-SEM). We discuss PLS-SEM application trends in the field of HRD, present key characteristics of the method, and demonstrate up-to-date metrics and evaluation guidelines using an illustrative model. Our PLS-SEM demonstration and explanations can serve as a valuable resource for practitioners concerned with substantiating results for organizational stakeholders and support researchers in methodological decision-making while avoiding common pitfalls associated with less familiar methods. Our step-by-step demonstration is conducted in open-source software and accompanied by explicitly coded operations so that readers can easily replicate the illustrative analyses presented.
期刊介绍:
Human Resource Development Quarterly (HRDQ) is the first scholarly journal focused directly on the evolving field of human resource development (HRD). It provides a central focus for research on human resource development issues as well as the means for disseminating such research. HRDQ recognizes the interdisciplinary nature of the HRD field and brings together relevant research from the related fields, such as economics, education, management, sociology, and psychology. It provides an important link in the application of theory and research to HRD practice. HRDQ publishes scholarly work that addresses the theoretical foundations of HRD, HRD research, and evaluation of HRD interventions and contexts.