[PLS-SEM Book] A Primer on PLS-SEM (2nd Ed.)

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Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2017). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). 2nd Edition. Thousand Oaks: Sage.

(Trích Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2017). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). 2nd Edition. Thousand Oaks: Sage)

Mục lục sách

Chapter 1: An Introduction to Structural Equation Modeling

• Chapter Preview
• What Is Structural Equation Modeling?
• Considerations in Using Structural Equation Modeling
• • Composite Variables
  • Measurement
  • Measurement Scales
  • Coding
  • Data Distributions
• Structural Equation Modeling With Partial Least Squares Path Modeling
• • Path Models With Latent Variables
  • Measurement Theory
  • Structural Theory
• PLS-SEM, CB-SEM, and Regressions Based on Sum Scores
• • Data Characteristics
  • Model Characteristics
• Organization of Remaining Chapters
• Summary
• Review Questions
• Critical Thinking Questions
• Key Terms
• Suggested Readings

Chapter 2: Specifying the Path Model and Examining Data

• Chapter Preview
• Stage 1: Specifying the Structural Model
• • Mediation
  • Moderation
  • Higher-Order and Hierarchical Component Models
• Stage 2: Specifying the Measurement Models
• • Reflective and Formative Measurement Models
  • Single-Item Measures and Sum Scores
• Stage 3: Data Collection and Examination
• • Missing Data
  • Suspicious Response Patterns
  • Outliers
  • Data Distribution
• Case Study Illustration: Specifying the PLS-SEM Model
• • Application of Stage 1: Structural Model Specification
  • Application of Stage 2: Measurement Model Specification
  • Application of Stage 3: Data Collection and Examination
• Path Model Creation Using the SmartPLS Software
• Summary
• Review Questions
• Critical Thinking Questions
• Key Terms
• Suggested Readings

Chapter 3: Path Model Estimation

• Chapter Preview
• Stage 4: Model Estimation and the PLS-SEM Algorithm
• • How the Algorithm Works
  • Statistical Properties
  • Algorithmic Options and Parameter Settings to Run the Algorithm
  • Results
• Case Study Illustration: PLS Path Model Estimation (Stage 4)
• • Model Estimation
  • Estimation Results
• Summary
• Review Questions
• Critical Thinking Questions
• Key Terms
• Suggested Readings

Chapter 4: Assessing PLS-SEM Results Part I: Evaluation of Reflective Measurement Models

• Chapter Preview
• Overview of Stage 5: Evaluation of Measurement Models
• Stage 5a: Assessing Results of Reflective Measurement Models
• Internal Consistency Reliability
• Convergent Validity
• Discriminant Validity
• Case Study Illustration—Reflective Measurement Models
• Running the PLS-SEM Algorithm
• Reflective Measurement Model Evaluation
• Summary
• Review Questions
• Critical Thinking Questions
• Key Terms
• Suggested Readings

Chapter 5: Assessing PLS-SEM Results Part II: Evaluation of the Formative Measurement Models

• Chapter Preview
• Stage 5b: Assessing Results of Formative Measurement Models
• • Step 1: Assess Convergent Validity
  • Step 2: Assess Formative Measurement Models for Collinearity Issues
  • Step 3: Assess the Significance and Relevance of the Formative Indicators
  • Bootstrapping Procedure
  • Bootstrap Confidence Intervals
• Case Study Illustration—Evaluation of Formative Measurement Models
• • Extending the Simple Path Model
  • Reflective Measurement Model Evaluation
  • Formative Measurement Model Evaluation
• Summary
• Review Questions
• Critical Thinking Questions
• Key Terms
• Suggested Readings

Chapter 6: Assessing PLS-SEM Results Part III: Evaluation of the Structural Model

• Chapter Preview
• Stage 6: Assessing PLS-SEM Structural Model Results
• • Step 1: Collinearity Assessment
  • Step 2: Structural Model Path Coefficients
  • Step 3: Coefficient of Determination (R2 Value)
  • Step 4: Effect Size f2
  • Step 5: Blindfolding and Predictive Relevance Q2
  • Step 6: Effect Size q2
• Case Study Illustration—How Are PLS-SEM Structural Model Results Reported?
• Summary
• Review Questions
• Critical Thinking Questions
• Key Terms
• Suggested Readings

Chapter 7: Mediator and Moderator Analysis

• Chapter Preview
• Mediation
• • Introduction
  • Types of Mediation Effects
  • Testing Mediating Effects
  • Measurement Model Evaluation in Mediation Analysis
  • Multiple Mediation
  • Case Study Illustration
• Moderation
• • Introduction
  • Types of Moderator Variables
  • Modeling Moderating Effects
  • Creating the Interaction Term
  • Results Interpretation
  • Moderated Mediation and Mediated Moderation
  • Case Study Illustration
• Summary
• Review Questions
• Critical Thinking Questions
• Key Terms
• Suggested Readings

Chapter 8: Outlook on Advanced Methods

• Chapter Preview
• Importance-Performance Map Analysis
• Hierarchical Component Models
• Confirmatory Tetrad Analysis
• Dealing With Observed and Unobserved Heterogeneity
• • Multigroup Analysis
  • Uncovering Unobserved Heterogeneity
• Measurement Model Invariance
• Consistent Partial Least Squares
• Summary
• Review Questions
• Critical Thinking Questions
• Key Terms
• Suggested Readings

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