Mastering Partial Least Squares Structural Equation Modeling Pls Sem With Smartpls In 38 Hours

Partial least squares is a new approach in structural equation modeling that can pay dividends when theory is scarce, correct model specifications are uncertain, and predictive accuracy is paramount. Marketers can use PLS to build models that measure latent variables such as socioeconomic status, perceived quality, satisfaction, brand attitude, buying intention, and customer loyalty. When applied correctly, PLS can be a great alternative to existing covariance-based SEM approaches. Dr. Ken Kwong-Kay Wong wrote this reference guide with graduate students and marketing practitioners in mind. Coupled with business examples and downloadable datasets for practice, the guide includes step-by-step guidelines for advanced PLS-SEM procedures in SmartPLS, including: CTA-PLS, FIMIX-PLS, GoF (SRMR, dULS, and dG), HCM, HTMT, IPMA, MICOM, PLS-MGA, PLS-POS, PLSc, and QEM. Filled with useful illustrations to facilitate understanding, you’ll find this guide a go-to tool when conducting marketing research. “This book provides all the essentials in comprehending, assimilating, applying and explicitly presenting sophisticated structured models in the most simplistic manner for a plethora of Business and Non-Business disciplines.” — Professor Siva Muthaly, Dean of Faculty of Business and Management at APU.

Partial least squares structural equation modeling (PLS-SEM) has become a standard approach for analyzing complex inter-relationships between observed and latent variables. Researchers appreciate the many advantages of PLS-SEM such as the possibility to estimate very complex models and the method’s flexibility in terms of data requirements and measurement specification. This practical open access guide provides a step-by-step treatment of the major choices in analyzing PLS path models using R, a free software environment for statistical computing, which runs on Windows, macOS, and UNIX computer platforms. Adopting the R software’s SEMinR package, which brings a friendly syntax to creating and estimating structural equation models, each chapter offers a concise overview of relevant topics and metrics, followed by an in-depth description of a case study. Simple instructions give readers the “how-tos” of using SEMinR to obtain solutions and document their results. Rules of thumb in every chapter provide guidance on best practices in the application and interpretation of PLS-SEM.

The third edition of A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) guides readers through learning and mastering the techniques of this approach in clear language. Authors Joseph H. Hair, Jr., G. Tomas M. Hult, Christian Ringle, and Marko Sarstedt use their years of conducting and teaching research to communicate the fundamentals of PLS-SEM in straightforward language to explain the details of this method, with limited emphasis on equations and symbols. A running case study on corporate reputation follows the different steps in this technique so readers can better understand the research applications. Learning objectives, review and critical thinking questions, and key terms help readers cement their knowledge. This edition has been thoroughly updated, featuring the latest version of the popular software package SmartPLS 3. New topics have been added throughout the text, including a thoroughly revised and extended chapter on mediation, recent research on the foundations of PLS-SEM, detailed descriptions of research summarizing the advantages as well as limitations of PLS-SEM, and extended coverage of advanced concepts and methods, such as out-of-sample versus in-sample prediction metrics, higher-order constructs, multigroup analysis, necessary condition analysis, and endogeneity.

This edited volume brings together some of the best papers from the 2022 Conference on Partial Least Squares Structural Equation Modeling (PLS-SEM), held at the Babeș-Bolyai University, Cluj, Romania. The volume seeks to expand the current research on PLS-SEM and promote the method’s application in the scientific community. It gathers research from scholars in many different fields who work on the advancement of PLS-SEM and who apply the method to explain and predict behavioral phenomena. Researchers today can draw on a wide array of different PLS-SEM-based algorithms, complementary methods, and model evaluation metrics. Tying in with these developments, the first part of this book documents methodological advances of PLS-SEM, which extend the researchers’ current toolbox of methods. The following parts demonstrate state-of-the-art applications of PLS-SEM in various fields such as consumer behavior, hospitality, human resource management, entrepreneurship, and organizational behavior. Special emphasis is placed on studies that apply complementary methods to offer a more nuanced analysis of the research questions.

"A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM), by Hair, Hult, Ringle, and Sarstedt, provides a concise yet very practical guide to understanding and using PLS structural equation modeling (PLS-SEM). PLS-SEM is evolving as a statistical modeling technique and its use has increased exponentially in recent years within a variety of disciplines, due to the recognition that PLS-SEM's distinctive methodological features make it a viable alternative to the more popular covariance-based SEM approach. This text includes extensive examples on SmartPLS software, and is accompanied by multiple data sets that are available for download from the accompanying website (www.pls-sem.com). "--Publisher's website.

This book presents powerful tools for integrating interrelated composites--such as capabilities, policies, treatments, indices, and systems--into structural equation modeling (SEM). Jörg Henseler introduces the types of research questions that can be addressed with composite-based SEM and explores the differences between composite- and factor-based SEM, variance- and covariance-based SEM, and emergent and latent variables. Using rich illustrations and walked-through data sets, the book covers how to specify, identify, estimate, and assess composite models using partial least squares path modeling, maximum likelihood, and other estimators, as well as how to interpret findings and report the results. Advanced topics include confirmatory composite analysis, mediation analysis, second-order constructs, interaction effects, and importance–performance analysis. Most chapters conclude with software tutorials for ADANCO and the R package cSEM. The companion website includes data files and syntax for the book's examples, along with presentation slides.

This book pulls together robust practices in Partial Least Squares Structural Equation Modeling (PLS-SEM) from other disciplines and shows how they can be used in the area of Banking and Finance. In terms of empirical analysis techniques, Banking and Finance is a conservative discipline. As such, this book will raise awareness of the potential of PLS-SEM for application in various contexts. PLS-SEM is a non-parametric approach designed to maximize explained variance in latent constructs. Latent constructs are directly unobservable phenomena such as customer service quality and managerial competence. Explained variance refers to the extent we can predict, say, customer service quality, by examining other theoretically related latent constructs such as conduct of staff and communication skills. Examples of latent constructs at the microeconomic level include customer service quality, managerial effectiveness, perception of market leadership, etc.; macroeconomic-level latent constructs would be found in contagion of systemic risk from one financial sector to another, herd behavior among fund managers, risk tolerance in financial markets, etc. Behavioral Finance is bound to provide a wealth of opportunities for applying PLS-SEM. The book is designed to expose robust processes in application of PLS-SEM, including use of various software packages and codes, including R. PLS-SEM is already a popular tool in marketing and management information systems used to explain latent constructs. Until now, PLS-SEM has not enjoyed a wide acceptance in Banking and Finance. Based on recent research developments, this book represents the first collection of PLS-SEM applications in Banking and Finance. This book will serve as a reference book for those researchers keen on adopting PLS-SEM to explain latent constructs in Banking and Finance.

“In Omni-Channel Retailing, Ken Wong has captured the essential technologies and tools that we use everyday to provide our customers with the products they want, through the channel that best serves their needs.” -David Markwell, Chief Technology and Analytics Officer, Loblaw Companies Ltd. “Ken Wong has crafted a formidable yet highly approachable guide that every retail business, large, medium and small, should devour. Retailers who want to do more than survive will find Omni-Channel Retailing an indispensable roadmap to winning and keeping customers.” -David Agnew, President, Seneca College “Dr. Ken Wong provides an outlook that is current to today’s Retail industry. His contemporary insights provide relevance to all those interested in learning more about Omni-Channel Retailing.” -Dr. Seung Hwan (Mark) Lee, Director, Professor, Retail Management, TRSM, Ryerson University “There is no space for ‘silos’ or functional borders within the organization. All have to be integrated to deliver the best and consistent customer experience. Omni-Channel Retailing explores this strategy, provides proven examples of success, and delivers practical advice to help today’s retailers.” -Perry Oosting, Former CEO, Clergerie Paris The COVID-19 pandemic is rewriting the rules of retail. A growing number of shoppers now rely on same-day delivery, curbside pickup, in-home/in-car delivery, and AI-powered drive-thru to get their goods. To accommodate such a paradigm shift, retailers must undertake significant changes in their business models to become digitally enabled and data-driven. Omni-Channel Retailing is written to help retailers and retail students understand the importance of delivering a seamless, cohesive, and contextual customer experience throughout the shopping journey. This book addresses today’s retailers’ challenges and gives new ideas for implementation. Relevant activities and discussion topics are included to help readers master the concepts.