9783032010544 - Partial Least Squares Structural Equation Modeling and Complementary Methods in Business Research: 67 (Information Systems Engineering and Management, 67) de Chew, ... (9 resultados)

Hardcover. Condición: new. Hardcover. 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Buch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.

Hardcover. Condición: Brand New. 500 pages. 9.26x6.11x9.49 inches. In Stock.

Condición: New.

Condición: new. Questo è un articolo print on demand.

Buch. Condición: Neu. Partial Least Squares Structural Equation Modeling and Complementary Methods in Business Research | Xinying Chew (u. a.) | Buch | Information Systems Engineering and Management | xvii | Englisch | 2025 | Springer | EAN 9783032010544 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand.

Buch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 204 pp. Englisch.

Condición: New. Print on Demand.

Condición: New. PRINT ON DEMAND.