Travel Reference
In-Depth Information
Table 14.1 Analytical methods employed in marketing research
Decision domains of
strategic tourism
marketing
Research aim in a
nutshell
Conventional methods
Recent developments
Market response
models
(aggregate and
disaggregate)
Explain and predict
consumer response to
marketing action of
tourism businesses
and DMOs
Linear and nonlinear
regression;
Discrete choice models;
Time series models
Computer simulation
models;
Agent-based modelling
Brand positioning
(BP)
Uncover tourists'
perceptions of and
preferences for
competing choice
alternatives
Exploratory and
confirmatory factor
analysis;
(Non)metric
multidimensional scaling
and unfolding;
Correspondence analysis
Semantic networks;
Item response theory;
for BP and MS : vector
quantization
(self-organizing maps and
topology representing
networks)
Market
segmentation
(MS)
Generate market
segments that react
homogeneously to
tailor-made offerings
and targeting
partitioning and
hierarchical cluster
analysis;
Automatic interaction
detection;
Discriminant analysis;
Latent class analysis;
Covariance-based SEM
and partial least squares
path models
Classification and decision
trees;
Feedforward neural
networks;
Sequence alignment
method;
Nonlinear structural
equation models for MS
and BP :
joint positioning/
segmentation with finite
mixture models
New product
planning and
interactive travel
recommender
systems
Develop and examine
product/service
bundles capable of
building market share
Conjoint analysis;
Expert systems;
Analytical hierarchy
process
fuzzy set theory;
Genetic algorithms;
adaptive (self-learning)
models
multivariate toolkit. Correspondence Analysis and Conjoint Analysis exhibited a disappointing
number of applications (less than 2 per cent each). While Conjoint Analysis was introduced into
marketing research as early as 1971 by Green and Rao in a famous Journal of Marketing Research
article, the fi rst application in tourism marketing research appeared much later (Bojamic and
Calantone 1990). Despite its resourcefulness this study could not trigger off a research tradition
within tourism marketing comparable to the wealth of conjoint applications in core marketing.
(Nonmetric) Multidimensional Scaling ((N)MDS, less than 2 per cent) is not a homogeneous
class of methods but offers a variety of approaches to analyzing direct or attribute-based proxi-
mity and preference data. (N)MDS has been a standard analytical instrument for perceptual
mapping in marketing research from the early 1970s on. In tourism research Fenton and Pearce
(1988) presented a comprehensive overview of MDS techniques. One of the typical applications
related to tourism market segmentation was Yiannakis and Gibson's (1992) attempt of typifying
tourist roles.
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