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Partial Least Squares Structural Equation Modeling (PLS-SEM) has emerged as a powerful and versatile analytical method in the social sciences, business, and management research. Unlike covariance-based SEM, which emphasizes model fit and theory testing, PLS-SEM is primarily prediction-oriented and particularly suitable for exploratory studies, complex models, and situations where data do not meet strict distributional assumptions. This chapter provides a comprehensive overview of the PLS-SEM approach, offering readers a conceptual foundation before delving into technical applications in later chapters.

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Partial Least Squares Structural Equation Modeling

  • 章节

  • 发表日期：

    2025年

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  • XinYing Chew,
  • Abbas Gatea Atiyah,
  • Alhamzah Alnoor,
  • Sammar Abbas,
  • Yousif Raad Muhsen,
  • Gül Erkol Bayram

摘要

Partial Least Squares Structural Equation Modeling (PLS-SEM) has emerged as a powerful and versatile analytical method in the social sciences, business, and management research. Unlike covariance-based SEM, which emphasizes model fit and theory testing, PLS-SEM is primarily prediction-oriented and particularly suitable for exploratory studies, complex models, and situations where data do not meet strict distributional assumptions. This chapter provides a comprehensive overview of the PLS-SEM approach, offering readers a conceptual foundation before delving into technical applications in later chapters.