Abstract
Chapter 8 builds on previous results published in the first edition of this reader. Section 4.1, Part IV, of the first edition presented ‘A guest mix approach’ to assessing and visualising the competitive relationships among 16 European tourist cities as reflected in the guests’ distribution by nationalities. If two cities A and B exhibit very similar proportions of their guest nationalities it is likely that the CTO managers of A pay the same attention to each of these guest nations as the managers of B. In other words, the analysis rests on the assumption that the CTOs base their marketing effort on a geographical segmentation approach. This does not seem to be a severe restriction as it corresponds to customary strategy guidelines followed by many tourist organisations.
Access provided by Autonomous University of Puebla. Download to read the full chapter text
Chapter PDF
References
Aldenderfer, M. S., Blashfield, R. K. 1984. Cluster Analysis, Series on Quantitative Applications in the Social Sciences, Sage University Paper.
Allison, P. D. 2001. Missing data, Sage, Thousand Oaks, CA.
Borg, I., Groenen, P. 1997. Modern Multidimensional Scaling, Theory and Applications, Springer, New York.
Carroll, J. D. and J. J. Chang 1970. Analysis of Individual Differences in Multidimensional Scaling via an N-way Generalization of “Eckart-Young” Decomposition, Psychometrika, 35, 283–319.
Caudill, M. 1993. “A Little Knowledge is a Dangerous Thing”, AI Expert, 8, 16–22.
Hastie, T., Tibshirani, R., Friedman, J. 2001. The Elements of Statistical Learning, Data Mining, Inference, and Prediction, Springer, New York.
Leisch, F. 2006. A Toolbox for K-Centroids Cluster Analysis, Computational Statistics and Data Analysis, 51 (2), 526–544.
Lemieux, J. and McAlister, L. 2005. Handling Missing Values in Marketing Data: A Comparison of Techniques, MSI Reports 05-107, Marketing Science Institute.
Mazanec, J. A. 1997. A guest mix approach, in: Mazanec, J. A. (ed), International City Tourism, Analysis and Strategy, Pinter, London, pp. 131–146.
Mazanec, J. A. 2001. Neural Market Structure Analysis: Novel Topology-Sensitive Methodology, European Journal of Marketing 35(7–8), 894–916.
Meyer, D. and Buchta, C. 2008. R package proxy — Distance and Similarity Measures, CRAN, http://cran.r-project.org/packages.
Sammon Jr, J.W. 1969. A non-linear mapping for data structure analysis. IEEE Transactions on Computers C-18, 401–409.
Schafer, J. L. 1997. Analysis of incomplete multivariate data, Chapman and Hall, London.
Tan, P. N., Steinbach, M., Kumar, V. 2006. Introduction to Data Mining, Pearson Addison Wesley.
TourMIS, 2008. TourMIS provides free access to Austrian and European tourism statistics, http://tourmis.wu.ac.at, (Site accessed 6 August 2008 and 30 March 2009).
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag/Wien
About this chapter
Cite this chapter
Buchta, C., Mazanec, J.A. (2010). A Guest Mix Approach to Analysing City Tourism Competition. In: Mazanec, J.A., Wöber, K.W. (eds) Analysing International City Tourism. Springer, Vienna. https://doi.org/10.1007/978-3-211-09416-7_9
Download citation
DOI: https://doi.org/10.1007/978-3-211-09416-7_9
Publisher Name: Springer, Vienna
Print ISBN: 978-3-211-09415-0
Online ISBN: 978-3-211-09416-7