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The book is designed to expose robust processes in application of PLS-SEM, including use of various software packages and codes, including R. Behavioral Finance is bound to provide a wealth of opportunities for applying PLS-SEM. 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. Examples of latent constructs at the microeconomic level include customer service quality, managerial effectiveness, perception of market leadership, etc. 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.
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Latent constructs are directly unobservable phenomena such as customer service quality and managerial competence. PLS-SEM is a non-parametric approach designed to maximize explained variance in latent constructs. As such, this book will raise awareness of the potential of PLS-SEM for application in various contexts. In terms of empirical analysis techniques, Banking and Finance is a conservative discipline. 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. Partial Least Squares Structural Equation Modeling Book Review: Finally, Chapter 13 presents a post-hoc analysis IPMA with graphical and academic interpretation. Chapter 12 presents rule of thumb for the assessment of structural model and academic interpretation of structural model. In structural model assessment five main steps are discussed namely Collinearity, assessing Significance of hypothesised relationships, Coefficient of determination, Effect size analysis and predictive relevance. Moving further, Chapter 7 is started from structural model significance and depicted graphical presentation of structural equation model assessment. Chapter 6 presents academic interpretation of measurement model. Four steps of measurement model are discussed namely Internal Consistency Reliability, Indicator Reliability, Convergent Validity and assessment of Discriminant Validity. Next to this measurement model is discussed in detailed.
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The first chapter presents a discussion on selection of CB-SEM or PLS-SEM and also provides rule of thumb in selecting CB-SEM and PLS-SEM. The aim of this book is to provide basic guideline about Structural Equation Modeling (SEM) using SmartPLS. Structural Equation Modeling Using SmartPLS Book Review: “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. Filled with useful illustrations to facilitate understanding, you’ll find this guide a go-to tool when conducting marketing research. 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. Ken Kwong-Kay Wong wrote this reference guide with graduate students and marketing practitioners in mind. When applied correctly, PLS can be a great alternative to existing covariance-based SEM approaches. 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. 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. Mastering Partial Least Squares Structural Equation Modeling Pls Sem with Smartpls in 38 Hours Book Review: