Cutting Edge Research Methods in Hospitality and Tourism:
Cutting Edge Research Methods in Hospitality and Tourism sits at the forefront of fast-paced developments in the tourism and hospitality industry, highlighting the importance of applied and pure research to address the theoretical and practical problems and gaps
Gespeichert in:
1. Verfasser: | |
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Format: | Elektronisch E-Book |
Sprache: | English |
Veröffentlicht: |
Bingley
Emerald Publishing Limited
2023
|
Ausgabe: | 1st ed |
Schlagworte: | |
Online-Zugang: | DE-2070s |
Zusammenfassung: | Cutting Edge Research Methods in Hospitality and Tourism sits at the forefront of fast-paced developments in the tourism and hospitality industry, highlighting the importance of applied and pure research to address the theoretical and practical problems and gaps |
Beschreibung: | Description based on publisher supplied metadata and other sources |
Beschreibung: | 1 Online-Ressource (223 Seiten) |
ISBN: | 9781804550656 |
Internformat
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505 | 8 | |a Intro -- Half Title Page -- Title Page -- Copyright Page -- Contents -- List of Figures and Tables -- About the Contributors -- Chapter 1: Introduction -- References -- Chapter 2: Which SEM to Use and What to Report? A Comparison of CB-SEM and PLS-SEM -- 1. Introduction -- 2. Literature Review -- 2.1. Why Use SEM? -- 2.2. The Two Types of SEM -- 2.3. Choosing Between CB-SEM and PLS-SEM -- 2.3.1. Philosophy of Measurement -- 2.3.2. The Aim of the Analysis: To Explain Or to Predict? -- 2.3.3. The Measurement of Constructs: Reflective, Formative, and Composite Measurement -- 2.3.4. Data Distribution -- 2.3.5. Sample Size -- 2.3.6. Secondary or Archival Data -- 2.3.7. Statistical Power -- 2.3.8. Model Complexity -- 2.3.9. Goodness-of-Fit -- 2.3.10. Single-item Constructs -- 2.3.11. Metric Versus Non-metric Data -- 2.3.12. Additional Considerations -- 2.4. Guidelines for Applying CB-SEM -- 2.5. Guidelines for Applying PLS-SEM -- 3. Conclusion -- References -- Chapter 3: Using PLS-SEM to Test for the Moderation Effects of Continuous Variables in Hospitality and Tourism Studies -- Introduction -- Applying the Product Term Method in PLS-SEM and Interpreting Results -- An Example in Hospitality and Tourism Research -- Extending the Product Term Method in PLS-SEM: The Two-step and Orthogonalizing Approaches and their Applications in Hospitality and Tourism -- Conclusion and Recommendations -- References -- Appendix -- Chapter 4: Econometric Analysis in Hospitality and Tourism Management -- 1. Introduction -- 2. Basic Econometric Models -- 2.1. Cross-sectional Models -- 2.2. Time-series Models -- 2.3. Panel Data Models -- 3. Major Topics in Econometrics -- 3.1. Endogeneity -- 3.2. Multi-equation Modeling -- 3.3. Causal Inference Modeling -- 3.4. Spatial Econometrics -- 4. Major Application Issues -- 4.1. Variable Selection -- 4.2. Non-linear Effect | |
505 | 8 | |a 4.3. Coefficient Interpretation -- 4.4. Estimation of Standard Errors -- 4.5. Sample Selection, Clustering, and Outliers -- 5. Conclusions and Recommendations -- References -- Chapter 5: Tourism Growth, Income Inequality and the Dependence Between Their Quantiles: Evidence from Quantile on Quantile Approach -- 1. Introduction -- 2. Literature Review -- 3. Data -- 4. Methodology -- 5. Empirical Results -- 5.1. QnQ Approach Estimation -- 5.2. Validation of the QQR Technique -- 6. Conclusion and Policy Implications -- References -- Chapter 6: Network Analysis in Tourism and Hospitality: A Comprehensive Review -- 1. Introduction -- 2. SNA: Nuclear Concepts and Definitions -- 3. The Use of SNA in Tourism and Hospitality Studies -- 3.1. The Role of Networks in Tourism and Hospitality -- 3.2. Existing Studies and Approaches -- 4. How to Develop SNA in Tourism and Hospitality Studies: A Practical Application to Tourism Innovation Network of Douro, Portugal -- 4.1. Step 1: Defining the Population, Sampling, and Collecting Data -- 4.2. Step 2: Computing Data -- 4.3. Step 3: Data Analysis -- 4.3.1. The Structure of Douro's Innovation Network -- 4.3.2. Position of Individual Actors: Analysis of Centrality -- 4.3.2.1. Degree Centrality -- 4.3.2.2. Betweenness -- 4.3.2.3. Closeness -- 4.3.2.4. Network Centralization -- 4.3.3. Network Connectivity and Cohesion -- 4.3.3.1. Density -- 4.3.3.2. Distance -- 4.3.3.3. Maximum Flow -- 4.3.3.4. Clustering Coefficient -- 5. Conclusion and Recommendations -- References -- Chapter 7: "Why Not Study What Tourists Actually Do, Instead of Asking Them What They Think They Do?" A Call for More Experiments in Tourism and Hospitality Research -- Introduction -- The Need for a Broader Implementation of Methods: A Literature Review -- Tracking Technologies -- Trip Planning Exercises -- Experiences and Implications from Data Collection | |
505 | 8 | |a Tracking Mobility -- Trip Planning Exercise -- Conclusions and Recommendations -- References -- Chapter 8: Guideline for Application of fuzzy-set Qualitative Comparative Analysis (fsQCA) in Tourism and Hospitality Studies -- 1. Introduction -- 2. Literature Review -- 2.1. Fuzzy-set Qualitative Comparative Analysis -- 2.2. Calibration of Fuzzy Sets -- 2.3. Truth Tables -- 2.4. Sufficient and Necessary Conditions -- 2.5. Logical AND, Logical OR, Logical NOT -- 3. Step-by-step Guideline for fsQCA -- 4. Illustrative Example -- 5. Conclusion and Recommendations -- References -- Appendix 1. Raw Results for Sufficient Configurations for Residents' Perceptions -- Appendix 2. Raw Results for Sufficient Configurations for Residents' Perceptions -- Appendix 3 -- Chapter 9: Application of Necessary Condition Analysis (NCA) in Hospitality and Tourism Research -- 1. Introduction -- 2. The Necessity Logic of Causality -- 3. The Logic of NCA and its Components -- 4. An Illustrative Example of NCA: Health-related Safety Perception and Travel Intention -- 4.1. Formulation of Necessary Condition Hypothesis -- 4.2. Data Collection -- 4.3. Data Analysis -- 4.3.1. Visual Inspection -- 4.3.2. Ceiling Line Techniques -- 4.3.3. Evaluating NCA Parameters -- 4.3.4. Bottleneck Table -- 5. Applying NCA in Hospitality and Tourism Research -- 5.1. (Re)analyze Existing Necessity Statements in Hospitality and Tourism with NCA -- 5.2. Find "Must-Have" Critical Success Factors in Hospitality and Tourism -- 5.3. Where to Apply NCA in Hospitality and Tourism? -- 6. Conclusion -- References -- Chapter 10: Netnography and Its Potential for Studies in Tourism and Hospitality -- Introduction -- Outline of the Netnographic Approach -- Netnographic Method: Distinction of "Online Ethnography" and "Ethnography of the Virtual" -- Methodological Advantages of the Netnographic Approach | |
505 | 8 | |a Application of the Netnographic Approach in Hospitality and Tourism Research -- Illustration Example: A Cross-cultural Netnographic Study on Disappointing Travel Experiences -- Conclusions and Recommendations -- References -- Chapter 11: Conclusions -- References -- Index | |
520 | |a Cutting Edge Research Methods in Hospitality and Tourism sits at the forefront of fast-paced developments in the tourism and hospitality industry, highlighting the importance of applied and pure research to address the theoretical and practical problems and gaps | ||
650 | 4 | |a Tourism | |
700 | 1 | |a Rasoolimanesh, S. Mostafa |e Sonstige |4 oth | |
700 | 1 | |a Jahani, Shiva |e Sonstige |4 oth | |
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Datensatz im Suchindex
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contents | Intro -- Half Title Page -- Title Page -- Copyright Page -- Contents -- List of Figures and Tables -- About the Contributors -- Chapter 1: Introduction -- References -- Chapter 2: Which SEM to Use and What to Report? A Comparison of CB-SEM and PLS-SEM -- 1. Introduction -- 2. Literature Review -- 2.1. Why Use SEM? -- 2.2. The Two Types of SEM -- 2.3. Choosing Between CB-SEM and PLS-SEM -- 2.3.1. Philosophy of Measurement -- 2.3.2. The Aim of the Analysis: To Explain Or to Predict? -- 2.3.3. The Measurement of Constructs: Reflective, Formative, and Composite Measurement -- 2.3.4. Data Distribution -- 2.3.5. Sample Size -- 2.3.6. Secondary or Archival Data -- 2.3.7. Statistical Power -- 2.3.8. Model Complexity -- 2.3.9. Goodness-of-Fit -- 2.3.10. Single-item Constructs -- 2.3.11. Metric Versus Non-metric Data -- 2.3.12. Additional Considerations -- 2.4. Guidelines for Applying CB-SEM -- 2.5. Guidelines for Applying PLS-SEM -- 3. Conclusion -- References -- Chapter 3: Using PLS-SEM to Test for the Moderation Effects of Continuous Variables in Hospitality and Tourism Studies -- Introduction -- Applying the Product Term Method in PLS-SEM and Interpreting Results -- An Example in Hospitality and Tourism Research -- Extending the Product Term Method in PLS-SEM: The Two-step and Orthogonalizing Approaches and their Applications in Hospitality and Tourism -- Conclusion and Recommendations -- References -- Appendix -- Chapter 4: Econometric Analysis in Hospitality and Tourism Management -- 1. Introduction -- 2. Basic Econometric Models -- 2.1. Cross-sectional Models -- 2.2. Time-series Models -- 2.3. Panel Data Models -- 3. Major Topics in Econometrics -- 3.1. Endogeneity -- 3.2. Multi-equation Modeling -- 3.3. Causal Inference Modeling -- 3.4. Spatial Econometrics -- 4. Major Application Issues -- 4.1. Variable Selection -- 4.2. Non-linear Effect 4.3. Coefficient Interpretation -- 4.4. Estimation of Standard Errors -- 4.5. Sample Selection, Clustering, and Outliers -- 5. Conclusions and Recommendations -- References -- Chapter 5: Tourism Growth, Income Inequality and the Dependence Between Their Quantiles: Evidence from Quantile on Quantile Approach -- 1. Introduction -- 2. Literature Review -- 3. Data -- 4. Methodology -- 5. Empirical Results -- 5.1. QnQ Approach Estimation -- 5.2. Validation of the QQR Technique -- 6. Conclusion and Policy Implications -- References -- Chapter 6: Network Analysis in Tourism and Hospitality: A Comprehensive Review -- 1. Introduction -- 2. SNA: Nuclear Concepts and Definitions -- 3. The Use of SNA in Tourism and Hospitality Studies -- 3.1. The Role of Networks in Tourism and Hospitality -- 3.2. Existing Studies and Approaches -- 4. How to Develop SNA in Tourism and Hospitality Studies: A Practical Application to Tourism Innovation Network of Douro, Portugal -- 4.1. Step 1: Defining the Population, Sampling, and Collecting Data -- 4.2. Step 2: Computing Data -- 4.3. Step 3: Data Analysis -- 4.3.1. The Structure of Douro's Innovation Network -- 4.3.2. Position of Individual Actors: Analysis of Centrality -- 4.3.2.1. Degree Centrality -- 4.3.2.2. Betweenness -- 4.3.2.3. Closeness -- 4.3.2.4. Network Centralization -- 4.3.3. Network Connectivity and Cohesion -- 4.3.3.1. Density -- 4.3.3.2. Distance -- 4.3.3.3. Maximum Flow -- 4.3.3.4. Clustering Coefficient -- 5. Conclusion and Recommendations -- References -- Chapter 7: "Why Not Study What Tourists Actually Do, Instead of Asking Them What They Think They Do?" A Call for More Experiments in Tourism and Hospitality Research -- Introduction -- The Need for a Broader Implementation of Methods: A Literature Review -- Tracking Technologies -- Trip Planning Exercises -- Experiences and Implications from Data Collection Tracking Mobility -- Trip Planning Exercise -- Conclusions and Recommendations -- References -- Chapter 8: Guideline for Application of fuzzy-set Qualitative Comparative Analysis (fsQCA) in Tourism and Hospitality Studies -- 1. Introduction -- 2. Literature Review -- 2.1. Fuzzy-set Qualitative Comparative Analysis -- 2.2. Calibration of Fuzzy Sets -- 2.3. Truth Tables -- 2.4. Sufficient and Necessary Conditions -- 2.5. Logical AND, Logical OR, Logical NOT -- 3. Step-by-step Guideline for fsQCA -- 4. Illustrative Example -- 5. Conclusion and Recommendations -- References -- Appendix 1. Raw Results for Sufficient Configurations for Residents' Perceptions -- Appendix 2. Raw Results for Sufficient Configurations for Residents' Perceptions -- Appendix 3 -- Chapter 9: Application of Necessary Condition Analysis (NCA) in Hospitality and Tourism Research -- 1. Introduction -- 2. The Necessity Logic of Causality -- 3. The Logic of NCA and its Components -- 4. An Illustrative Example of NCA: Health-related Safety Perception and Travel Intention -- 4.1. Formulation of Necessary Condition Hypothesis -- 4.2. Data Collection -- 4.3. Data Analysis -- 4.3.1. Visual Inspection -- 4.3.2. Ceiling Line Techniques -- 4.3.3. Evaluating NCA Parameters -- 4.3.4. Bottleneck Table -- 5. Applying NCA in Hospitality and Tourism Research -- 5.1. (Re)analyze Existing Necessity Statements in Hospitality and Tourism with NCA -- 5.2. Find "Must-Have" Critical Success Factors in Hospitality and Tourism -- 5.3. Where to Apply NCA in Hospitality and Tourism? -- 6. Conclusion -- References -- Chapter 10: Netnography and Its Potential for Studies in Tourism and Hospitality -- Introduction -- Outline of the Netnographic Approach -- Netnographic Method: Distinction of "Online Ethnography" and "Ethnography of the Virtual" -- Methodological Advantages of the Netnographic Approach Application of the Netnographic Approach in Hospitality and Tourism Research -- Illustration Example: A Cross-cultural Netnographic Study on Disappointing Travel Experiences -- Conclusions and Recommendations -- References -- Chapter 11: Conclusions -- References -- Index |
ctrlnum | (ZDB-30-PQE)EBC7176902 (ZDB-30-PAD)EBC7176902 (ZDB-89-EBL)EBL7176902 (OCoLC)1361682141 (DE-599)BVBBV049874480 |
dewey-full | 658 |
dewey-hundreds | 600 - Technology (Applied sciences) |
dewey-ones | 658 - General management |
dewey-raw | 658 |
dewey-search | 658 |
dewey-sort | 3658 |
dewey-tens | 650 - Management and auxiliary services |
discipline | Wirtschaftswissenschaften |
edition | 1st ed |
format | Electronic eBook |
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How to Develop SNA in Tourism and Hospitality Studies: A Practical Application to Tourism Innovation Network of Douro, Portugal -- 4.1. Step 1: Defining the Population, Sampling, and Collecting Data -- 4.2. Step 2: Computing Data -- 4.3. Step 3: Data Analysis -- 4.3.1. The Structure of Douro's Innovation Network -- 4.3.2. Position of Individual Actors: Analysis of Centrality -- 4.3.2.1. Degree Centrality -- 4.3.2.2. Betweenness -- 4.3.2.3. Closeness -- 4.3.2.4. Network Centralization -- 4.3.3. Network Connectivity and Cohesion -- 4.3.3.1. Density -- 4.3.3.2. Distance -- 4.3.3.3. Maximum Flow -- 4.3.3.4. Clustering Coefficient -- 5. Conclusion and Recommendations -- References -- Chapter 7: "Why Not Study What Tourists Actually Do, Instead of Asking Them What They Think They Do?" 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id | DE-604.BV049874480 |
illustrated | Not Illustrated |
indexdate | 2024-09-19T05:22:06Z |
institution | BVB |
isbn | 9781804550656 |
language | English |
oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-035213938 |
oclc_num | 1361682141 |
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owner | DE-2070s |
owner_facet | DE-2070s |
physical | 1 Online-Ressource (223 Seiten) |
psigel | ZDB-30-PQE ZDB-30-PQE HWR_PDA_PQE |
publishDate | 2023 |
publishDateSearch | 2023 |
publishDateSort | 2023 |
publisher | Emerald Publishing Limited |
record_format | marc |
spelling | Okumus, Fevzi Verfasser aut Cutting Edge Research Methods in Hospitality and Tourism 1st ed Bingley Emerald Publishing Limited 2023 ©2023 1 Online-Ressource (223 Seiten) txt rdacontent c rdamedia cr rdacarrier Description based on publisher supplied metadata and other sources Intro -- Half Title Page -- Title Page -- Copyright Page -- Contents -- List of Figures and Tables -- About the Contributors -- Chapter 1: Introduction -- References -- Chapter 2: Which SEM to Use and What to Report? A Comparison of CB-SEM and PLS-SEM -- 1. Introduction -- 2. Literature Review -- 2.1. Why Use SEM? -- 2.2. The Two Types of SEM -- 2.3. Choosing Between CB-SEM and PLS-SEM -- 2.3.1. Philosophy of Measurement -- 2.3.2. The Aim of the Analysis: To Explain Or to Predict? -- 2.3.3. The Measurement of Constructs: Reflective, Formative, and Composite Measurement -- 2.3.4. Data Distribution -- 2.3.5. Sample Size -- 2.3.6. Secondary or Archival Data -- 2.3.7. Statistical Power -- 2.3.8. Model Complexity -- 2.3.9. Goodness-of-Fit -- 2.3.10. Single-item Constructs -- 2.3.11. Metric Versus Non-metric Data -- 2.3.12. Additional Considerations -- 2.4. Guidelines for Applying CB-SEM -- 2.5. Guidelines for Applying PLS-SEM -- 3. Conclusion -- References -- Chapter 3: Using PLS-SEM to Test for the Moderation Effects of Continuous Variables in Hospitality and Tourism Studies -- Introduction -- Applying the Product Term Method in PLS-SEM and Interpreting Results -- An Example in Hospitality and Tourism Research -- Extending the Product Term Method in PLS-SEM: The Two-step and Orthogonalizing Approaches and their Applications in Hospitality and Tourism -- Conclusion and Recommendations -- References -- Appendix -- Chapter 4: Econometric Analysis in Hospitality and Tourism Management -- 1. Introduction -- 2. Basic Econometric Models -- 2.1. Cross-sectional Models -- 2.2. Time-series Models -- 2.3. Panel Data Models -- 3. Major Topics in Econometrics -- 3.1. Endogeneity -- 3.2. Multi-equation Modeling -- 3.3. Causal Inference Modeling -- 3.4. Spatial Econometrics -- 4. Major Application Issues -- 4.1. Variable Selection -- 4.2. Non-linear Effect 4.3. Coefficient Interpretation -- 4.4. Estimation of Standard Errors -- 4.5. Sample Selection, Clustering, and Outliers -- 5. Conclusions and Recommendations -- References -- Chapter 5: Tourism Growth, Income Inequality and the Dependence Between Their Quantiles: Evidence from Quantile on Quantile Approach -- 1. Introduction -- 2. Literature Review -- 3. Data -- 4. Methodology -- 5. Empirical Results -- 5.1. QnQ Approach Estimation -- 5.2. Validation of the QQR Technique -- 6. Conclusion and Policy Implications -- References -- Chapter 6: Network Analysis in Tourism and Hospitality: A Comprehensive Review -- 1. Introduction -- 2. SNA: Nuclear Concepts and Definitions -- 3. The Use of SNA in Tourism and Hospitality Studies -- 3.1. The Role of Networks in Tourism and Hospitality -- 3.2. Existing Studies and Approaches -- 4. How to Develop SNA in Tourism and Hospitality Studies: A Practical Application to Tourism Innovation Network of Douro, Portugal -- 4.1. Step 1: Defining the Population, Sampling, and Collecting Data -- 4.2. Step 2: Computing Data -- 4.3. Step 3: Data Analysis -- 4.3.1. The Structure of Douro's Innovation Network -- 4.3.2. Position of Individual Actors: Analysis of Centrality -- 4.3.2.1. Degree Centrality -- 4.3.2.2. Betweenness -- 4.3.2.3. Closeness -- 4.3.2.4. Network Centralization -- 4.3.3. Network Connectivity and Cohesion -- 4.3.3.1. Density -- 4.3.3.2. Distance -- 4.3.3.3. Maximum Flow -- 4.3.3.4. Clustering Coefficient -- 5. Conclusion and Recommendations -- References -- Chapter 7: "Why Not Study What Tourists Actually Do, Instead of Asking Them What They Think They Do?" A Call for More Experiments in Tourism and Hospitality Research -- Introduction -- The Need for a Broader Implementation of Methods: A Literature Review -- Tracking Technologies -- Trip Planning Exercises -- Experiences and Implications from Data Collection Tracking Mobility -- Trip Planning Exercise -- Conclusions and Recommendations -- References -- Chapter 8: Guideline for Application of fuzzy-set Qualitative Comparative Analysis (fsQCA) in Tourism and Hospitality Studies -- 1. Introduction -- 2. Literature Review -- 2.1. Fuzzy-set Qualitative Comparative Analysis -- 2.2. Calibration of Fuzzy Sets -- 2.3. Truth Tables -- 2.4. Sufficient and Necessary Conditions -- 2.5. Logical AND, Logical OR, Logical NOT -- 3. Step-by-step Guideline for fsQCA -- 4. Illustrative Example -- 5. Conclusion and Recommendations -- References -- Appendix 1. Raw Results for Sufficient Configurations for Residents' Perceptions -- Appendix 2. Raw Results for Sufficient Configurations for Residents' Perceptions -- Appendix 3 -- Chapter 9: Application of Necessary Condition Analysis (NCA) in Hospitality and Tourism Research -- 1. Introduction -- 2. The Necessity Logic of Causality -- 3. The Logic of NCA and its Components -- 4. An Illustrative Example of NCA: Health-related Safety Perception and Travel Intention -- 4.1. Formulation of Necessary Condition Hypothesis -- 4.2. Data Collection -- 4.3. Data Analysis -- 4.3.1. Visual Inspection -- 4.3.2. Ceiling Line Techniques -- 4.3.3. Evaluating NCA Parameters -- 4.3.4. Bottleneck Table -- 5. Applying NCA in Hospitality and Tourism Research -- 5.1. (Re)analyze Existing Necessity Statements in Hospitality and Tourism with NCA -- 5.2. Find "Must-Have" Critical Success Factors in Hospitality and Tourism -- 5.3. Where to Apply NCA in Hospitality and Tourism? -- 6. Conclusion -- References -- Chapter 10: Netnography and Its Potential for Studies in Tourism and Hospitality -- Introduction -- Outline of the Netnographic Approach -- Netnographic Method: Distinction of "Online Ethnography" and "Ethnography of the Virtual" -- Methodological Advantages of the Netnographic Approach Application of the Netnographic Approach in Hospitality and Tourism Research -- Illustration Example: A Cross-cultural Netnographic Study on Disappointing Travel Experiences -- Conclusions and Recommendations -- References -- Chapter 11: Conclusions -- References -- Index Cutting Edge Research Methods in Hospitality and Tourism sits at the forefront of fast-paced developments in the tourism and hospitality industry, highlighting the importance of applied and pure research to address the theoretical and practical problems and gaps Tourism Rasoolimanesh, S. Mostafa Sonstige oth Jahani, Shiva Sonstige oth Erscheint auch als Druck-Ausgabe Okumus, Fevzi Cutting Edge Research Methods in Hospitality and Tourism Bingley : Emerald Publishing Limited,c2023 9781804550649 |
spellingShingle | Okumus, Fevzi Cutting Edge Research Methods in Hospitality and Tourism Intro -- Half Title Page -- Title Page -- Copyright Page -- Contents -- List of Figures and Tables -- About the Contributors -- Chapter 1: Introduction -- References -- Chapter 2: Which SEM to Use and What to Report? A Comparison of CB-SEM and PLS-SEM -- 1. Introduction -- 2. Literature Review -- 2.1. Why Use SEM? -- 2.2. The Two Types of SEM -- 2.3. Choosing Between CB-SEM and PLS-SEM -- 2.3.1. Philosophy of Measurement -- 2.3.2. The Aim of the Analysis: To Explain Or to Predict? -- 2.3.3. The Measurement of Constructs: Reflective, Formative, and Composite Measurement -- 2.3.4. Data Distribution -- 2.3.5. Sample Size -- 2.3.6. Secondary or Archival Data -- 2.3.7. Statistical Power -- 2.3.8. Model Complexity -- 2.3.9. Goodness-of-Fit -- 2.3.10. Single-item Constructs -- 2.3.11. Metric Versus Non-metric Data -- 2.3.12. Additional Considerations -- 2.4. Guidelines for Applying CB-SEM -- 2.5. Guidelines for Applying PLS-SEM -- 3. Conclusion -- References -- Chapter 3: Using PLS-SEM to Test for the Moderation Effects of Continuous Variables in Hospitality and Tourism Studies -- Introduction -- Applying the Product Term Method in PLS-SEM and Interpreting Results -- An Example in Hospitality and Tourism Research -- Extending the Product Term Method in PLS-SEM: The Two-step and Orthogonalizing Approaches and their Applications in Hospitality and Tourism -- Conclusion and Recommendations -- References -- Appendix -- Chapter 4: Econometric Analysis in Hospitality and Tourism Management -- 1. Introduction -- 2. Basic Econometric Models -- 2.1. Cross-sectional Models -- 2.2. Time-series Models -- 2.3. Panel Data Models -- 3. Major Topics in Econometrics -- 3.1. Endogeneity -- 3.2. Multi-equation Modeling -- 3.3. Causal Inference Modeling -- 3.4. Spatial Econometrics -- 4. Major Application Issues -- 4.1. Variable Selection -- 4.2. Non-linear Effect 4.3. Coefficient Interpretation -- 4.4. Estimation of Standard Errors -- 4.5. Sample Selection, Clustering, and Outliers -- 5. Conclusions and Recommendations -- References -- Chapter 5: Tourism Growth, Income Inequality and the Dependence Between Their Quantiles: Evidence from Quantile on Quantile Approach -- 1. Introduction -- 2. Literature Review -- 3. Data -- 4. Methodology -- 5. Empirical Results -- 5.1. QnQ Approach Estimation -- 5.2. Validation of the QQR Technique -- 6. Conclusion and Policy Implications -- References -- Chapter 6: Network Analysis in Tourism and Hospitality: A Comprehensive Review -- 1. Introduction -- 2. SNA: Nuclear Concepts and Definitions -- 3. The Use of SNA in Tourism and Hospitality Studies -- 3.1. The Role of Networks in Tourism and Hospitality -- 3.2. Existing Studies and Approaches -- 4. How to Develop SNA in Tourism and Hospitality Studies: A Practical Application to Tourism Innovation Network of Douro, Portugal -- 4.1. Step 1: Defining the Population, Sampling, and Collecting Data -- 4.2. Step 2: Computing Data -- 4.3. Step 3: Data Analysis -- 4.3.1. The Structure of Douro's Innovation Network -- 4.3.2. Position of Individual Actors: Analysis of Centrality -- 4.3.2.1. Degree Centrality -- 4.3.2.2. Betweenness -- 4.3.2.3. Closeness -- 4.3.2.4. Network Centralization -- 4.3.3. Network Connectivity and Cohesion -- 4.3.3.1. Density -- 4.3.3.2. Distance -- 4.3.3.3. Maximum Flow -- 4.3.3.4. Clustering Coefficient -- 5. Conclusion and Recommendations -- References -- Chapter 7: "Why Not Study What Tourists Actually Do, Instead of Asking Them What They Think They Do?" A Call for More Experiments in Tourism and Hospitality Research -- Introduction -- The Need for a Broader Implementation of Methods: A Literature Review -- Tracking Technologies -- Trip Planning Exercises -- Experiences and Implications from Data Collection Tracking Mobility -- Trip Planning Exercise -- Conclusions and Recommendations -- References -- Chapter 8: Guideline for Application of fuzzy-set Qualitative Comparative Analysis (fsQCA) in Tourism and Hospitality Studies -- 1. Introduction -- 2. Literature Review -- 2.1. Fuzzy-set Qualitative Comparative Analysis -- 2.2. Calibration of Fuzzy Sets -- 2.3. Truth Tables -- 2.4. Sufficient and Necessary Conditions -- 2.5. Logical AND, Logical OR, Logical NOT -- 3. Step-by-step Guideline for fsQCA -- 4. Illustrative Example -- 5. Conclusion and Recommendations -- References -- Appendix 1. Raw Results for Sufficient Configurations for Residents' Perceptions -- Appendix 2. Raw Results for Sufficient Configurations for Residents' Perceptions -- Appendix 3 -- Chapter 9: Application of Necessary Condition Analysis (NCA) in Hospitality and Tourism Research -- 1. Introduction -- 2. The Necessity Logic of Causality -- 3. The Logic of NCA and its Components -- 4. An Illustrative Example of NCA: Health-related Safety Perception and Travel Intention -- 4.1. Formulation of Necessary Condition Hypothesis -- 4.2. Data Collection -- 4.3. Data Analysis -- 4.3.1. Visual Inspection -- 4.3.2. Ceiling Line Techniques -- 4.3.3. Evaluating NCA Parameters -- 4.3.4. Bottleneck Table -- 5. Applying NCA in Hospitality and Tourism Research -- 5.1. (Re)analyze Existing Necessity Statements in Hospitality and Tourism with NCA -- 5.2. Find "Must-Have" Critical Success Factors in Hospitality and Tourism -- 5.3. Where to Apply NCA in Hospitality and Tourism? -- 6. Conclusion -- References -- Chapter 10: Netnography and Its Potential for Studies in Tourism and Hospitality -- Introduction -- Outline of the Netnographic Approach -- Netnographic Method: Distinction of "Online Ethnography" and "Ethnography of the Virtual" -- Methodological Advantages of the Netnographic Approach Application of the Netnographic Approach in Hospitality and Tourism Research -- Illustration Example: A Cross-cultural Netnographic Study on Disappointing Travel Experiences -- Conclusions and Recommendations -- References -- Chapter 11: Conclusions -- References -- Index Tourism |
title | Cutting Edge Research Methods in Hospitality and Tourism |
title_auth | Cutting Edge Research Methods in Hospitality and Tourism |
title_exact_search | Cutting Edge Research Methods in Hospitality and Tourism |
title_full | Cutting Edge Research Methods in Hospitality and Tourism |
title_fullStr | Cutting Edge Research Methods in Hospitality and Tourism |
title_full_unstemmed | Cutting Edge Research Methods in Hospitality and Tourism |
title_short | Cutting Edge Research Methods in Hospitality and Tourism |
title_sort | cutting edge research methods in hospitality and tourism |
topic | Tourism |
topic_facet | Tourism |
work_keys_str_mv | AT okumusfevzi cuttingedgeresearchmethodsinhospitalityandtourism AT rasoolimaneshsmostafa cuttingedgeresearchmethodsinhospitalityandtourism AT jahanishiva cuttingedgeresearchmethodsinhospitalityandtourism |