TY  - BOOK
AU  - Ali,Faizan
AU  - Rasoolimanesh,S.Mostafa
AU  - Cobanoglu,Cihan
TI  - Applying partial least squares in tourism and hospitality research
SN  - 9781787567016
AV  - TX911 .A67 2019
U1  - 647.9407 23
PY  - 2019///]
CY  - Bingley, UK
PB  - Emerald Publishing Limited
KW  - Hospitality industry
KW  - Research
KW  - Accueil (Tourisme)
KW  - Recherche
KW  - MATHEMATICS
KW  - General
KW  - bisacsh
KW  - fast
KW  - Least squares
KW  - Structural equation modeling
KW  - Tourism
KW  - Mathematical models
KW  - Electronic books
N1  - Literature Review and Theory Development; Includes bibliographical references and index; 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
N2  - 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
UR  - https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=1868310
ER  -