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

Artikelnummer: 978-3-032-01055-1
Einband: PDF
Verfügbarkeit: Download, sofort verfügbar (Link per E-Mail)
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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.

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.

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VerlagSpringer Nature Switzerland
EinbandPDF
Erscheinungsjahr2025
Seitenangabe183 S.
AusgabekennzeichenEnglisch
AbbildungenXVII, 183 p. 17 illus., 15 illus. in color.
Masse6'165 KB
PlattformPDF
ReiheInformation Systems Engineering and Management; Intelligent Technologies and Robotics; Intelligent Technologies and Robotics
AutorChew, Xinying / Gatea Atiyah, Abbas / Alnoor, Alhamzah / Abbas, Sammar / Muhsen, Yousif Raad / Bayram, Gül Erkol

Alle Bände der Reihe "Information Systems Engineering and Management; Intelligent Technologies and Robotics; Intelligent Technologies and Robotics (R0)"

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