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hand, factor analysis provides for the parsimonious
structure of observations which will substantially
reproduce the empirical data in a meaningful way.
Factor analysis uses a number of axis rotation
methods including quartimax, quartimin, varimax,
orthomax and oblimax to achieve meaningful
solutions.
Axis rotation can be achieved either subjectively
or objectively and interrelationships among extracted
factors can be either orthogonal �independent)
and oblique �correlated). The most
commonly used rotation method is varimax.
Varimax rotation maintains the orthogonality
among the factors and provides the best fit for a
given factor structure. Data input for factor
analysis is a correlation or proximity matrix.
Although the measurement level of the correlation
data has no specific requirement, the robustness of
estimates and parsimony of a factor model
depend on at least an interval scale and near
multinormal distribution.
There are many ways to conduct factor analysis
depending on how the data is organised �for
example, a three-dimensional cube which includes
entities or cases, characteristics and occasions
define the edges). Applied research commonly uses
factor analysis to explore the interrelationships of
characteristics of entities in a cross-sectional
fashion �R-factor analysis). Other modes of analysis
include Q-, P-, O-, S- and T-factor analysis. Qfactor
analysis, based on the transposing of a data
matrix in the R-factor analysis, examines the
interrelationships among entities from defined
characteristics. O-factor and P-factor analysis look
for the temporal structure of time series data,
whereas S-factor and T-factor analysis focus on the
behavioural variation over various occasions.
See also: multidimensional scaling; motivation;
perceptual mapping; principal component analysis
Further reading
Kim, J.O. and Mueller, C.W. �1978) Introduction to
Factor Analysis:What It is and How To Do It, Sage
University Paper Series on Quantitative Applications
in the Social Sciences, 07±001, Beverly
Hills, CA and London: Sage Publications. �An
introduction book on factor analysis.)
Phillips, P.A. and Moutinho, l. �1998) `The market
planning index: a tool for measuring strategic
marketing effectiveness', Journal of Travel and
Tourism Marketing 7�3): 41±60. �Provides an
example of the application of factor analysis
within the context of tourism marketing.)
Pizam, A. and Sussman, S. �1995) `Does nationality
affect tourist behaviour?', Annals of Tourism
Research 22�4): 901±17. �Provides an example of
the application of factor analysis within the
context of tourism research.)
Rummel, R.J. �1975). Applied Factor Analysis, 2nd
edn, Evanston, IL: Northwestern University
Press. �Provides a discussion on the history,
development and variations of factor analysis.)
factory tourism
JIANN-MIN JENG, USA
DANIEL R. FESENMAIER, USA
Involves organised visits to factories to see things
being manufactured and processes at work.
Breweries and distilleries, together with manufacturers
of clothes, pottery and glass, are amongst the
most popular factory visits. As wet weather
attractions, usually in urban tourism centres,
facilities can include food service, interpretative
displays and shops where first quality goods and
`seconds' are sold.
fairs
MIKE ROBINSON, UK
Fairs are events, usually periodic, held for the
exchange of goods and services. Rooted in the
history of trade, in many cultures fairs have become
more than markets; they encompass education,
amusements, competitions and festive behaviour.
Agricultural fairs or `shows' focus on rural traditions;
trade fairs concentrate on inter-business
dealings. A World's Fair �exposition) brings nations
together for comparison and celebrations, thus
generating more tourist arrivals.
See also: festival
fairs 221
DONALD GETZ, CANADA