[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-0-en-105":3,"doc-seo-626843-105":59,"doc-detail-626843-en":130},{"code":4,"msg":5,"data":6},0,"success",[7,13,18,23,28,33,38,43,48,51,55],{"id":8,"doc_module":4,"doc_module_name":9,"category_name":10,"show_sort_weight":11,"slug":12},1,"Document","Story & Novel",90,"story-novel",{"id":14,"doc_module":4,"doc_module_name":9,"category_name":15,"show_sort_weight":16,"slug":17},2,"Literature",80,"literature",{"id":19,"doc_module":4,"doc_module_name":9,"category_name":20,"show_sort_weight":21,"slug":22},4,"Exam",70,"exam",{"id":24,"doc_module":4,"doc_module_name":9,"category_name":25,"show_sort_weight":26,"slug":27},5,"Comic",60,"comic",{"id":29,"doc_module":4,"doc_module_name":9,"category_name":30,"show_sort_weight":31,"slug":32},6,"Technology",50,"technology",{"id":34,"doc_module":4,"doc_module_name":9,"category_name":35,"show_sort_weight":36,"slug":37},7,"Healthcare",40,"healthcare",{"id":39,"doc_module":4,"doc_module_name":9,"category_name":40,"show_sort_weight":41,"slug":42},8,"Research & Report",30,"research-report",{"id":44,"doc_module":4,"doc_module_name":9,"category_name":45,"show_sort_weight":46,"slug":47},9,"Religion & Spirituality",20,"religion-spirituality",{"id":46,"doc_module":4,"doc_module_name":9,"category_name":49,"show_sort_weight":46,"slug":50},"World Cup","world-cup",{"id":52,"doc_module":4,"doc_module_name":9,"category_name":53,"show_sort_weight":52,"slug":54},10,"Lifestyle","lifestyle",{"id":56,"doc_module":4,"doc_module_name":9,"category_name":57,"show_sort_weight":24,"slug":58},19,"General","general",{"code":4,"msg":60,"data":61},"ok",{"site_id":62,"language":63,"slug":64,"title":65,"keywords":66,"description":67,"schema_data":68,"social_meta":123,"head_meta":125,"extra_data":127,"updated_unix":129},105,"en","when-to-use-and-how-to-report-the-results-of-pls-sem","When to use and how to report the results of PLS-SEM","","This paper provides a comprehensive, yet concise, overview of the considerations and metrics required for PLS-SEM analysis and result reporting. It first summarizes preliminary considerations, including reasons for choosing PLS-SEM, recommended sample size in selected contexts, distributional assumptions, the role of secondary data, statistical power, and goodness-of-fit testing. It then covers evaluation metrics and rules of thumb, adding guidelines for PLSpredict, model-comparison metrics, and robustness checks.",{"@graph":69,"@context":122},[70,84,105],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":40,"@type":76,"position":81},"https://docshare.wps.com/document/research-report/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/when-to-use-and-how-to-report-the-results-of-pls-sem/626843/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/when-to-use-and-how-to-report-the-results-of-pls-sem/626843.png","ImageObject",300,407,{"name":92,"@type":93},"RuangKosong","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-30","2026-10-21",true,{"@type":102,"interactionType":103,"userInteractionCount":29},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"What preliminary considerations does the paper cover before reporting PLS-SEM results?","Question",{"text":112,"@type":113},"It summarizes reasons for choosing PLS-SEM, recommended sample size in selected contexts, distributional assumptions, use of secondary data, statistical power, and the need for goodness-of-fit testing.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"Which PLS-SEM evaluation metrics and rules of thumb are emphasized?",{"text":117,"@type":113},"The paper explains established PLS-SEM evaluation criteria and the rules of thumb for assessing results, including updated guidance on applying newly proposed metrics.",{"name":119,"@type":110,"acceptedAnswer":120},"What new guidelines and additional methods does the overview include?",{"text":121,"@type":113},"It includes guidelines for using PLSpredict for out-of-sample prediction, metrics for model comparisons, and several complementary methods to check the robustness of the results.","https://schema.org",{"og:url":83,"og:type":124,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":126,"canonical":83},"index,follow",{"doc_id":128,"site_id":62},626843,1792685853,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":29,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":139,"language":140,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":141,"faqs":142,"seo_title":143,"seo_description":67,"update_tm":144,"read_time":145},962090883219,"https://ap-avatar.wpscdn.com/davatar_276721f389ce27ea32af1340a28f341c","Downloaded 19:09 19 December 2018 (PT)by Tulane University At   \n\n| \u003Cbr>European Business Review | |\n| --- | --- |\n| When to use and how to report the results of PLS-SEM\u003Cbr>Joe F Hair, Jeffrey Joe Risher, Marko Sarstedt, Christian M Ringle,\u003Cbr>Article information:\u003Cbr>To cite this document:\u003Cbr>Joe F Hair, Jeffrey Joe Risher, Marko Sarstedt, Christian M Ringle, \"When to use and how to report the results of PLS-SEM\", European Business Review, [https://doi.org/10.1108/EBR-11-2018-0203](https://doi.org/10.1108/EBR-11-2018-0203)\u003Cbr>Permanent link to this document:\u003Cbr>[https://doi.org/10.1108/EBR-11-2018-0203](https://doi.org/10.1108/EBR-11-2018-0203)\u003Cbr>Downloaded on: 19 December 2018, At: 19:09 (PT)\u003Cbr>References: this document contains references to 0 other documents.\u003Cbr>To copy this document: permissions@[emeraldinsight.com](emeraldinsight.com)\u003Cbr>Access to this document was granted through an Emerald subscription provided by emerald-srm:402646 []\u003Cbr>For Authors\u003Cbr>If you would like to write for this, or any other Emerald publication, then please use our Emerald for Authors service information about how to choose which publication to write for and submission guidelines are available for all. Please [visit www.emeraldinsight.com/authors](visit www.emeraldinsight.com/authors) for more information.\u003Cbr>[About Emerald www.emeraldinsight.com](About Emerald www.emeraldinsight.com)\u003Cbr>Emerald is a global publisher linking research and practice to the benefit of society. The company manages a portfolio of more than 290 journals and over 2,350 books and book series volumes, as well as providing an extensive range of online products and additional customer resources and services.\u003Cbr>Emerald is both COUNTER 4 and TRANSFER compliant. The organization is a partner of the Committee on Publication Ethics (COPE) and also works with Portico and the LOCKSS initiative for digital archive preservation.\u003Cbr>*Related content and download information correct at time of download . |  |\n\nDownloaded 19:09 19 December 2018 (PT)by Tulane University At   \nWhen to use and how to report the results of PLS-SEM  \nAbstract  \nPurpose – This paper provides a comprehensive, yet concise, overview of the considerations and metrics required for PLS-SEM analysis and result reporting. Preliminary considerations are summarized first, including reasons for choosing PLS-SEM, recommended sample size in selected contexts, distributional assumptions, use of secondary data, statistical power, and the need for goodness-of-fit testing. Next, the metrics, as well as the rules of thumb, that should be applied to assess the PLS-SEM results are covered. Besides covering established PLS-SEM evaluation criteria, the overview includes new guidelines for applying (1) PLSpredict, a novel approach for assessing a model’s out-of-sample prediction, (2) metrics for model comparisons, and (3) several complementary methods for checking the results’ robustness.  \nDesign/methodology/approach – This paper provides an overview of previously and recently proposed metrics, as well as rules of thumb, for evaluating the results of research, based on the application of PLS-SEM.  \nFindings – Most of the previously applied metrics for evaluating PLS-SEM results are still relevant, but scholars need to be knowledgeable about recently proposed metrics (e.g., model comparison criteria) and methods (e.g., endogeneity assessment, latent class analyses, PLSpredict) and when and how to apply them.  \nResearch limitations/implications – Methodological developments associated with PLS-SEMare rapidly emerging. The metrics reported in this paper are useful for current applications, but scholars need to continuously seek the latest developments in the PLS-SEM method.  \nOriginality/value – In light of more recent research and methodological developments in the PLS-SEM domain, guidelines for the method’s use need to be continuously extended and updated. This paper is the most current and comprehensive summary of the PLS-S","cbCaib2t229iUUgB","https://ap.wps.com/l/cbCaib2t229iUUgB","pdf",749123,39,"English","# Abstract\n# Introduction\n# Purpose\n## Design/methodology/approach\n## Findings\n## Research limitations/implications\n## Originality/value\n# Keywords","[{\"question\":\"What preliminary considerations does the paper cover before reporting PLS-SEM results?\",\"answer\":\"It summarizes reasons for choosing PLS-SEM, recommended sample size in selected contexts, distributional assumptions, use of secondary data, statistical power, and the need for goodness-of-fit testing.\"},{\"question\":\"Which PLS-SEM evaluation metrics and rules of thumb are emphasized?\",\"answer\":\"The paper explains established PLS-SEM evaluation criteria and the rules of thumb for assessing results, including updated guidance on applying newly proposed metrics.\"},{\"question\":\"What new guidelines and additional methods does the overview include?\",\"answer\":\"It includes guidelines for using PLSpredict for out-of-sample prediction, metrics for model comparisons, and several complementary methods to check the robustness of the results.\"}]","When to use and how to report the results of PLS-SEM | PDF",1792541299,98]