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Optimum market-positioning models for South African arts festival scenarios

The purpose of the study was to develop an optimum market-positioning model for the special interest tourism market to support arts festivals in South Africa (SA). Three subareas were deemed essential for the model, namely determining which attributes contribute to the success of three arts festival scenarios, comparing the different arts festival packages as a tourism attraction and then combining these subareas to develop a model enabling future researchers and marketers to present a successful arts festival in South Africa.

The three main arts festivals in South Africa, at Potchefstroom, Grahamstown and Oudtshoorn, were studied. Screening questions followed by judgmental and quota sampling were used to select only like-minded respondents from festival attendees on a scenario basis. In personal interviews the data were collected and then analysed using conjoint analysis and game theory. Conjoint analysis was used in a linear regression model with individual ratings for each product. The average of the r-squares in this study was 0,83, indicating a good fit between data and model developed. Then these results were used in the game theory, comparing the three arts festival scenarios to identify the most successful tourism attraction. A different combination of attributes gave each of the three festival scenarios an optimum market position in its own niche market.

The study contributes to the existing body of positioning knowledge, specifically in the festivals and events domain. It also adds value as this model can be applied to other festivals in South Africa and also to other business sectors. / Transport Economy, Logistics & Tourism / D. Com. (Tourism Management)

Identiferoai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:unisa/oai:umkn-dsp01.int.unisa.ac.za:10500/1246
Date30 October 2005
CreatorsVan Zyl, Cina
ContributorsBrits, Anton, 1948-, Strydom, J. W. (Johan Wilhelm), 1952-, Botha, C.
Source SetsSouth African National ETD Portal
LanguageEnglish
Detected LanguageEnglish
TypeThesis
Format1 online resource (xv, 418 leaves)

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