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Journal of Vacation Marketing, Vol. 8, No. 3, 247-262 (2002)
DOI: 10.1177/135676670200800304

Positioning the destination product ‘Southern Moravia’

Ulrich R. Orth

Oregon State University, USA, ulrich.orth{at}orst.edu

Jarmila Turecková

Department of Marketing and Trade, Faculty of Economics and Business, Mendel University, Brno, Czech Republic

Decreasing numbers of tourists to the Czech Republic point to a weakening competitive position of Czech destinations. For many regions tourism may be a short-lived economic dream when understanding of tourists’ perceptions and travel motives is lacking. The two objectives pursued in this study are an identification of competing destinations including their positions relative to each other, and an a posteriori segmentation of visitors with psychographic variables. The study was initiated by a regional tourism commission to enable it to derive a favourable positioning strategy based on the segmentation results. Methodologically, the study tries to overcome well-known insufficiencies of single segmentation approaches by exploiting the advantage of the multivariate nature of combined push factors, pull factors and other factors of more restrictive nature. The task employs multivariate data analysis techniques such as factor analysis, cluster analysis and multi-dimensional scaling. The findings indicate that Southern Bohemia is considered the most attractive destination in the Czech Republic, while Southern Moravia is only ranked third. Vacationers perceive both destinations as highly similar, a fact that makes them very close competitors. Among the visitors to Southern Moravia, six homogeneous groups could be identified based on their vacation style orientation: relax-in-safety tourists, demanding pleasure travellers, nature-loving vacationers, cultural interactionists, carefree wellness tourists and sightseeing individuals. The groups were consolidated into a perceptual map and found to differ significantly with respect to preferred destinations and demographic variables.

Key Words: cluster analysis • multi-dimensional scaling • factor analysis • vacation style typology


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