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Title Applying partial least squares in tourism and hospitality research / editors: Faizan Ali, S. Mostafa Rasoolimanesh, Cihan Cobanoglu.
Imprint Bingley, UK : Emerald Publishing Limited, [2019]
Edition First edition.

Subject Hospitality industry -- Research.
Alt Name Ali, Faizan,
Rasoolimanesh, S. Mostafa,
Cobanoglu, Cihan,
Description 1 online resource
Edition First edition.
Bibliography Note Includes bibliographical references and index.
Contents Cover; Title; Copyright; Contents; Preface; References; Foreword; References; About the Authors; Chapter 1 Minimum Sample Size Estimation in PLS-SEM: An Application in Tourism and Hospitality Research; Introduction; Illustrative Study; Power, Effect Size, and Minimum Sample Size; The Monte Carlo Simulation Method; Classic Methods: 10-Times Rule and Minimum R2; The 10-Times Rule Method; The Minimum R2 Method; New Methods: Inverse Square Root and Gamma-Exponential; The Inverse Square Root Method; The Gamma-Exponential Method; The New Methods in WarpPLS
Minimum Sample Size Estimation After Data Collection and AnalysisMinimum Sample Size Estimation Before Data Collection and Analysis; Discussion and Conclusion; Acknowledgments; References; Chapter 2 New Guidelines for the Use of PLS Path Modeling in Hospitality, Travel, and Tourism Research; 1. Introduction; 2. Partial Least Squares Path Modeling; 3. The Use of PLS-PM in Different Types of HTT Research; 3.1. Causal Research; 3.2. Predictive Research; 3.3. Descriptive Research; 3.4. Exploratory Research; 4. Discussion and Implications; Notes; References
Chapter 3 Predictions from Partial Least Squares Models1. Introduction; 2. How to Predict from PLS Models; 2.1. Generating Predictions from PLS-PM; 2.2. Earliest Versus Direct Antecedents Approaches; 3. Evaluating Predictions from PLS Models; 3.1. In-sample Versus Out-of-sample; 3.2. Cross Validation; 3.3. Predictive Metrics; 3.4. Benchmarks; 4. Evaluating Predictive Performance; 5. Using PLSpredict (An Empirical Example); 5.1. Predictive Value of Model; 5.2. Predictive Value of Proposed Versus Alternative Models; 5.3. Evaluating the Prediction Residuals; 5.4. Predictive Validity
5.5. Discussion of Empirical Example6. Looking Ahead; Acknowledgments; References; Chapter 4 PLS Path Modeling in Hospitality and Tourism Research: The Golden Age and Days of Future Past; 1. Introduction; 2. Recent Advances in PLS-PM; 2.1. Consistent PLS (PLSc); 2.2. Hierarchical Component Analysis; 2.3. Nonlinear Analysis; 2.4. Multigroup Analysis; 2.5. Moderation-Mediation Analysis; 2.6. Unobserved Heterogeneity; 2.7. Confirmatory Tetrad Analysis (CTA-PLS); 2.8. PLS Predict; 2.9. Importance-Performance Map Analysis; 3. Methodology
4. Critical Issues in the Use of PLS-PM in Hospitality and Tourism Research4.1. Reasons for Using PLS-PM; 4.2. Model Descriptive Statistics; 4.3. Sampling Characteristics; 4.4. Technical Reporting; 4.5. Reported Formative Measurement Metrics; 4.6. Reported Reflective Measurement Metrics; 4.7. Reported Structural Model Metrics; 4.8. Additional Considerations and Supplementary Analyses; 4.9. How to Improve the Use of PLS-PM in Future; 5. Conclusions; References; Chapter 5 Hotel Employees' Use of Smartphones and Performance: Reflective-Formative Estimation Approach; Introduction
Note Literature Review and Theory Development
Summary Ten chapters discuss key aspects of advanced PLS analysis and its practical applications, covering new guidelines and improvements in the use of PLS-PM as well as various individual topics.
Note Online resource; title from digital title page (viewed on January 03, 2019).
ISBN 9781787567016 (electronic book)
178756701X (electronic book)
9781787566996 (electronic book)
1787566994 (electronic book)
OCLC # 1078569023
Additional Format Print version: Ali, Faizan. Applying Partial Least Squares in Tourism and Hospitality Research. Bingley : Emerald Publishing Limited, 2018 9781787567009

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