Partial Least Squares Structural Equation Modeling and Complementary Methods in Business Research

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Partial Least Squares Structural Equation Modeling and Complementary Methods in Business Research is written by XinYing Chew and published by Springer Nature. It's available with International Standard Book Number or ISBN identification 3032010551 (ISBN 10) and 9783032010551 (ISBN 13).

This book offers a practical and accessible guide to Partial Least Squares Structural Equation Modeling (PLS-SEM) in business research, while addressing its limitations by integrating complementary methods such as artificial neural networks (ANN), fuzzy-set qualitative comparative analysis (fsQCA), and multi-criteria decision-making (MCDM). It supports early-career researchers, postgraduate students, and practitioners in navigating complex models, predictive analytics, and latent construct measurement. By focusing on emerging business issues like digital transformation, metaverse, and sustainability, this book delivers clear, applied insights. Readers gain not only foundational knowledge of PLS-SEM but also strategies for enhancing research rigor, prediction, and decision-making using hybrid approaches. This is a timely and essential resource for scholars aiming to advance their methodological toolkit for impactful and actionable business research.