Index
Cutting Edge Research Methods in Hospitality and Tourism
ISBN: 978-1-80455-064-9, eISBN: 978-1-80455-063-2
Publication date: 25 January 2023
This content is currently only available as a PDF
Citation
(2023), "Index", Okumus, F., Rasoolimanesh, S.M. and Jahani, S. (Ed.) Cutting Edge Research Methods in Hospitality and Tourism, Emerald Publishing Limited, Leeds, pp. 201-208. https://doi.org/10.1108/978-1-80455-063-220231013
Publisher
:Emerald Publishing Limited
Copyright © 2023 Fevzi Okumus, S. Mostafa Rasoolimanesh, and Shiva Jahani
INDEX
Absolute fit indices
, 16
Adjusted Goodness of Fit Index (AGFI)
, 16
AEHTD
, 109–110, 112
Akaike information criterion (AIC)
, 62
Analytical netnography
, 175
Association of Tourism Businesses in Douro and Trás-os-Montes (AETUR)
, 110, 112
Attitude
, 7, 123, 189
Augmented Dickey–Fuller unit root test (ADF unit root test)
, 78
Autonetnography
, 175
Autoregressive distributed lag model (ARDL model)
, 57
Average variance extracted (AVE)
, 16, 36
Bayesian information criterion
, 62
Betweenness centrality
, 109–110
Bibliometric analysis
, 96
Bonacich’s Centrality
, 108
Booking process
, 131
Boolean algebra
, 3, 143–144, 160
Bottleneck table
, 166
Calibration of fuzzy sets
, 140–141
Causal combinations
, 3, 139, 141–142, 144–146
Causal inference
, 54, 138
modeling
, 2, 60, 65
Causality
, 3, 54, 138, 150, 158
conventional
, 158
Granger-type
, 65
necessity logic
, 161–162
simultaneous
, 59
Ceiling envelopment (CE)
, 162
Ceiling regression (CR)
, 163
Central actors
, 108–109
Centrality, analysis of
, 108
Chi-square (χ2)
, 16
Citation network
, 100
Clickthrough rates (CTRs)
, 166
Closeness centrality
, 110
Clustering
, 64–65
Clustering coefficient (CC)
, 112–113
main properties and metrics used in SNA
, 116–118
Coefficient interpretation
, 63–64
Cognitive dimension
, 40
Cointegration analysis
, 57
Collaboration
, 100
Community
, 176
Community attachment (CAC)
, 146
Comparative Fit Index (CFI)
, 16
Composite measurement
, 10–11
Composite outer models
, 22
Configurations
, 141
Confirmatory composite analysis (CCA)
, 22
Confirmatory factor analysis
, 13
Consistency
, 145
Continuous variables
, 32
“Continuous” fuzzy set
, 139
Conventional correlational techniques
, 137
Conventional quantile regression
, 78
Conventional validity
, 139
Convergent validity
, 139
Covariance-based structural equation modeling (CB-SEM)
, 1, 6–8, 30, 197
guidelines for applying
, 13–17
PLS-SEM and
, 8–13
Coverage
, 142, 145
Craft shops
, 72
Crisp-set QCA (csQCA)
, 138
Critical ratio (CR)
, 34
Critical success factors (CSFs)
, 167
Cross-cultural differences
, 183, 187
Cross-cultural investigation
, 3
Cross-cultural netnographic study
, 187–191
Cross-cultural similarities
, 190
Cross-cultural studies
, 183
Cross-sectional data
, 54
Cross-sectional econometric models
, 58
Cross-sectional models
, 2, 54–56
Cross-validation approach
, 62
Cultural attitude (CAT)
, 146
Culture
, 176–177
Curio
, 72
Curse of dimensionality
, 78
Cutting-edge research methods
, 1, 200
Data analysis
, 107, 164–166
bottleneck table
, 166
CC
, 112–113
ceiling line techniques
, 164–165
density
, 111
distance
, 111–112
evaluating NCA parameters
, 165–166
maximum flow
, 112
network connectivity and cohesion
, 111
position of individual actors
, 108–109
structure of Douro’s innovation network
, 107–108
visual inspection
, 164
Data collection
, 164, 199
experiences and implications from
, 126
process
, 181
tracking mobility
, 126–130
Decision-making process
, 168, 174
Degree centrality
, 109
actors with highest betweenness
, 109–110
Degrees of freedom (df)
, 16
Density
, 111
Destination choice analysis
, 53
Destination marketing organizations (DMOs)
, 166
Difference-in-differences (DID)
, 60
Digital embodiment
, 176
Digital netnography
, 175
Discriminant validity
, 139
Distance
, 111–112
Douro network
, 109
Douro region
, 113
Douro’s innovation network
main metrics computed for Douro tourism innovation network
, 108
structure of
, 107–108
Ecologic validity
, 125, 131
Econometric analysis in hospitality and tourism management
basic econometric models
, 54–59
causal inference modeling
, 60
coefficient interpretation
, 63–64
endogeneity
, 59
estimation of standard errors
, 64
major application issues
, 61
major topics in econometrics
, 59
multi-equation modeling
, 59–60
non-linear effect
, 62–63
sample selection/clustering/outliers
, 64–65
spatial econometrics
, 60–61
variable selection
, 61–62
Econometric models
, 2, 54, 60, 87
cross-sectional models
, 54–56
panel data models
, 57–59
time-series models
, 56–57
Economic gain (EG)
, 146
Elasticities
, 63
Endogeneity
, 54, 59
Entrepreneurial self-efficacy (ESE)
, 34–35
Environmental attitude (EAT)
, 146
Epistemological approaches
, 122
Ethnographic research online
, 175
Ethnography of virtual
, 177–179
Expectations
, 189
Experiments
, 125
External stakeholders
, 1
External validity
, 125, 128
Facebook
, 186
Fellow tourism researchers
, 122
Field experiments
, 123, 125, 132–133
Fixed-effects estimators (FE estimators)
, 58
Foreign direct investment
, 72
Foreign earnings
, 72
Formative measurement
, 10–11
Formative outer models
, 21–22
Free disposal hull (FDH)
, 163
Freeman’s approach
, 110
Fuzzy package
, 144
Fuzzy set qualitative comparative analysis (fsQCA)
, 160
Fuzzy sets
, 139
calibration of
, 140–141
Fuzzy-set Qualitative Comparative Analysis (fsQCA)
, 1, 3, 138–140, 197
application of
, 138
calibration of fuzzy sets
, 140–141
crisp vs. fuzzy sets
, 140
illustrative example
, 146–148
literature review
, 139–144
Logical AND, Logical OR, Logical NOT
, 143–144
results of necessity analysis for residents’ perceptions
, 148
step-by-step guideline for
, 144–145
sufficient and necessary conditions
, 142–143
sufficient configurations for residents’ perceptions
, 147
sufficient configurations for residents’ perceptions
, 149
truth tables
, 141–142
verbal description of fuzzy-set membership scores
, 141
G* Power
, 13
Gamma exponential
, 17
Generalized method of moments (GMM)
, 59
Geodesic distance
, 111
German tourists
, 130
Global positioning system (GPS)
, 122, 124
devices
, 126, 129
Goodness-of-Fit Index (GFI)
, 16
Goodness-of-fit measures
, 16
absolute fit indices
, 16
incremental fit indices
, 16
parsimony fit indices
, 16
Google Scholar platform
, 183
Group comparison method
, 30
Health-related safety perception
, 163–166
data analysis
, 164–166
data collection
, 164
formulation of necessary condition hypothesis
, 163–164
Heterotrait–monotrait ratio (HTMT ratio)
, 21
Higher-order constructs
, 13, 41
Hospitality
, 34–39
application of netnographic approach in
, 182–187
critical success factors in
, 167–168
develop SNA in hospitality studies
, 104–113
experiences and implications from data collection
, 126–130
NCA in hospitality and tourism research
, 166–169
need for broader implementation of methods
, 122–123
networks role in
, 98–99
outer results for effects and interaction models
, 37–38
reanalyze existing necessity statements in
, 166–167
and tourism researchers
, 198
tracking technologies
, 123–124
trip planning exercise
, 124–126, 130–132
two-step and orthogonalizing approaches and applications in
, 39–42
use of SNA in
, 98–104
Hotel pricing
, 53
Humanistic netnography
, 176
Hybrid method
, 43, 198
Income equality
, 73
Income inequality
, 85
Incremental fit indices
, 16
Independent variable (X)
, 32, 39–40
Indicator reliability
, 139
Individual actors
betweenness
, 109–110
closeness
, 110
degree centrality
, 109
network centralization
, 110–111
position of
, 108
Influencers
, 174–177
Information exchange
, 173
Inner models
, 22
Instagram
, 189
Institutional tourism network of Douro
, 111
Interaction
, 30, 32
effect model
, 35
Interaction/Moderation Tourism Papers
, 49–50
Internal consistency
, 139
Internal stakeholders
, 1
Internal validity
, 125
Internet
, 174–176, 178
Interviews
, 3
Inverse square root methods
, 17
Investigative research on the Internet (IRI)
, 177
Involvement (INV)
, 146
Lasso approach
, 62
Latent variables
, 7
Logarithmic transformations
, 63
Logical AND
, 143–144
Logical NOT
, 143–144
Logical OR
, 143–144
Longitudinal data (see Panel data)
Machine learning algorithms
, 62
Macroeconomic modeling of demand
, 59
Main effects model
, 35–37
Maximum likelihood estimation method (ML estimation method)
, 6
Measurement models
, 10, 13–16
Medical tourism
, 145
Metric data
, 12–13
Mixed frequency models
, 54
Mixed method approach
, 139
Mobile positioning systems
, 124
Mobility data
, 126
Moderation effect
, 30
Moderator variable (M)
, 32, 39–40
Motivation
, 169
Multi-equation modeling
, 54, 57–58
Multigroup analysis (see Group comparison method)
Multimodal social worlds
, 176
Multiple regression analysis
, 138
Multiple-criteria decision making methods
, 137
Naturalness
, 177
Necessary condition analysis (NCA)
, 1–3, 157, 197
applying NCA in hospitality and tourism research
, 166–169
illustrative example of
, 163–166
logic of NCA and components
, 162–163
necessity logic of causality
, 161–162
Necessity logic of causality
, 161–162
Netnography
, 174, 200
application of netnographic approach in hospitality and tourism research
, 182–187
approach
, 174–191
cross-cultural netnographic study on disappointing travel experiences
, 187–191
in hospitality and tourism research, application of
, 182–187
methodological advantages of
, 180–182
netnographic method
, 176–179
outline of
, 175–177
Networks
, 96, 98
centralization
, 110–111
cohesion
, 111–113
concept
, 97
connectivity
, 111–113
role in tourism and hospitality
, 97–99
Non-linear effect
, 62–63
Non-metric data
, 12–13
Nonparametric estimation
, 78–79
Nonparametric quantile regression model
, 78
Normed Chi-Square
, 16
Normed Fit Index (NFI)
, 16
Nuclear concepts
, 96–98
Offline communities
, 176
Online community
, 179, 183, 188–191
Online ethnography
, 177–179
Online interactions
, 174
Ordered logit model
, 56
Ordered probit model
, 56
Ordinary least squares (OLS)
, 54–55, 78
Orthogonalizing approaches and applications in hospitality and tourism
, 39–42
Outliers
, 64–65
Panel data
, 57
cointegration tests
, 58
models
, 2, 57–59
regression
, 58
unit root test
, 58
Parsimony fit indices
, 16
Parsimony Normed Fit Index (PNFI)
, 16
Partial least squares structural equation modeling (PLS-SEM)
, 1–2, 6–8, 29, 197
algorithm
, 39
applying product term method and interpreting results
, 32–34
CB-SEM and
, 8–13
example in hospitality and tourism research
, 34–39
extending product term method in
, 39–42
guidelines for applying
, 17–22
model
, 33
path models
, 32, 40
Perceived destination image
, 7
PLSGraph
, 30
Poisson panel data model
, 58
Polynomial relations
, 62
Polynomial transformations
, 63
Portugal, practical application to tourism innovation network of Douro
, 104–113
Positivistic paradigm
, 123
Poverty
, 73
Principal component analysis (PCA)
, 73
Principal component matrix (PC matrix)
, 75
Product term method
, 40
in CB-SEM
, 31
in PLS-SEM and interpreting results
, 31–34, 39–42
step-by-step guidelines to account for continuous moderator constructs
, 44–45
Propensity score matching (PSM)
, 60
QQR estimates
, 85–86
Qualitative Comparative Analysis (QCA)
, 137–138, 160
Quantile on quantile approach (QQ approach)
, 2, 73, 198
data
, 75–78
descriptive statistics
, 76
empirical results
, 79
estimation
, 79–84
literature review
, 74
methodology
, 78–79
PCA results for tourism activity index
, 75
QnQ estimation
, 77
validation of
, 85–87
Quantile regression
, 55, 78, 85
Random-effects estimators (RE estimators)
, 58
Reachability
, 111
Recipes
, 138
Redundancy analysis
, 21
Reflective measurement
, 10–11
Reflective outer models, assessing
, 21
Regional tourism planning
, 103
Regression
, 56
Regression-based ordinary least squares (Regression-based OLS)
, 6
Reliability metrices
, 139
Residents’ perceptions (RP)
, 146
Risk management
, 168
Root Mean Square Error of Approximation (RMSEA)
, 16
Root mean square residual covariance (RMStheta)
, 12
Safety perception
, 163–165
Sample selection
, 64–65
Scenario-based experiment
, 125
Seemingly unrelated regression equations (SURE)
, 60
Set negation (see Logical NOT)
Set union (see Logical OR)
Simultaneous causality
, 59
Simultaneous equation modeling
, 59
Small Island developing states (SIDS)
, 74
Smartphones
, 129
SmartPLS
, 30
Snowball sampling method
, 105, 130
Social network analysis (SNA)
, 1, 95, 96–98, 197
develop SNA in tourism and hospitality studies
, 104–113
existing studies and approaches
, 99–104
role of networks in tourism and hospitality
, 98–99
use of SNA in tourism and hospitality studies
, 98–99
Social networks
, 105
Social science disciplines
, 3, 138, 199
Sociograms
, 106
Sociometric analysis
, 105
Spatial dependence econometrics
, 60
Spatial Durbin model
, 61
Spatial econometric models
, 54, 60–61
Spatial error model
, 61
Spatial weighting matrix (SWM)
, 61
Standard errors, estimation of
, 64
Standard evaluation criteria for structural models
, 17
Standardized Root Mean Residual (SRMR)
, 12, 16
Stata software
, 144
Stochastic frontier analysis (SFA)
, 56
Structural equation modeling (SEM)
, 1, 5, 160, 197
additional considerations
, 13
advantages of
, 6
aim of analysis
, 10
CB-SEM
, 6
choosing between CB-SEM and PLS-SEM
, 8
data distribution
, 11
goodness-of-fit
, 12
guidelines for applying CB-SEM
, 13–17
guidelines for applying PLS-SEM
, 17–22
guidelines for choosing SEM method
, 9
measurement of constructs
, 10–11
metric vs. non-metric data
, 12–13
model complexity
, 12
moderation/interaction effects in
, 30
philosophy of measurement
, 8–10
PLS-SEM
, 6
sample size
, 11
secondary or archival data
, 11–12
single-item constructs
, 12
statistical power
, 12
two types of
, 7–8
usage
, 6
Structural model
, 16
Sufficiency
, 142
language
, 158
Sufficient configurations
, 145
raw results for sufficient configurations for residents’ perceptions
, 153–154
Surveys
, 3, 180
Sustainability
, 168
Symmetric approach
, 138
Synthetic control method (SCM)
, 60
Tax revenues
, 72
Theoretical econometrics
, 54
Theory confirmation
, 10
Theory development
, 10
Time-invariant variables
, 58
Time-series
data
, 57
models
, 2, 56–57
Top 10 countries
, 76
Topology
, 97
Tourism
, 72, 75
activity index
, 73, 76
communities
, 74
demand modeling
, 53
develop SNA in
, 106–115
expansion
, 72
mobility
, 123
networks role in
, 98–99
sector
, 72
tourism-led growth
, 53
two-step and orthogonalizing approaches and applications in
, 39–42
use of SNA in
, 98–104
Tourism growth
, 72, 85
income inequality on
, 85
Tourism innovation network of Douro, Portugal
, 104
computing data
, 105–106
data analysis
, 107
defining population, sampling, and collecting data
, 105
Tourism research
, 34–39, 122
experiences and implications from data collection
, 126–130
need for broader implementation of methods
, 122–123
tracking technologies
, 123–124
trip planning exercise
, 124–126, 130–132
Tourist behavior
, 123
Tracking experiments
, 123
Tracking mobility
, 3, 126–130
Tracking technologies
, 122–124
Transnational companies (TNCs)
, 72
Travel intention
, 163
data analysis
, 164–166
data collection
, 164
formulation of necessary condition hypothesis
, 163–164
Trip planning exercise
, 124–126, 130–132
booking exercise
, 132
Truth tables
, 141–142
Tucker Lewis Index (TLI)
, 16
Turkey’s international tourism
, 83
Two-stage approach
, 41
Two-stage least squares
, 59
Two-step approach
, 40
and applications in hospitality and tourism
, 39–42
UCINET
, 105
Unit root test
, 57
University of Trás-os-Montes e Alto Douro (UTAD)
, 108
UNU-WIDER
, 75
Validity in tourism research
, 122
Variable selection
, 61–62
Variance inflation factor (VIF)
, 17
Vector autoregressive model (VAR model)
, 60
“Waiting time” management
, 167
Word-of-mouth approach
, 174
World Income Inequality Database (SWIID)
, 75
World Tourism Organization (WTO)
, 72, 75
XL-STAT software
, 30
- Prelims
- Chapter 1: Introduction
- Chapter 2: Which SEM to Use and What to Report? A Comparison of CB-SEM and PLS-SEM
- Chapter 3: Using PLS-SEM to Test for the Moderation Effects of Continuous Variables in Hospitality and Tourism Studies
- Chapter 4: Econometric Analysis in Hospitality and Tourism Management
- Chapter 5: Tourism Growth, Income Inequality and the Dependence Between Their Quantiles: Evidence from Quantile on Quantile Approach
- Chapter 6: Network Analysis in Tourism and Hospitality: A Comprehensive Review
- 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
- Chapter 8: Guideline for Application of fuzzy-set Qualitative Comparative Analysis (fsQCA) in Tourism and Hospitality Studies
- Chapter 9: Application of Necessary Condition Analysis (NCA) in Hospitality and Tourism Research
- Chapter 10: Netnography and Its Potential for Studies in Tourism and Hospitality
- Chapter 11: Conclusions
- Index