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Title: Sub-cluster dynamics of an organizational population ecological analysis of wine making in Tokaj-Hegyalja, 1989-2014
Author: Nagy, Domokos Károly
ISNI:       0000 0004 7230 9904
Awarding Body: Durham University
Current Institution: Durham University
Date of Award: 2018
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This thesis addresses two aspects of contrast dependence theory. Firstly it aimed to test whether it applied to similarity clusters. In other words whether it already takes effect in early stages of the legitimation process. Secondly, the theory was tested at the sub-category level with multiple overlapping clusters that dynamically changed in terms of their defining features. The empirical setting was the wine producer population of Tokaj-Hegyalja, a traditional wine region in Hungary, which went through a major transition in terms of winemaking technology, cultivation method and products between 1989 and 2014. This work argues that the groups of wineries that took different paths in terms of these features were perceived as fuzzy sub-clusters within the main population by the audience. Thus, their yearly vital rates were (also) determined by their contrast level, even though these similarity clusters never became legitimate sub-categories. Besides that, introduction of novel methods and innovations were perceived as the expansion of the relevant feature set, thus the clustering system of the audience was dynamic. In terms of methodology the research significantly differed from existing studies. Instead of gathering membership data directly from the audience, similarity sub-clusters were modelled by using the retrospectively collected relevant features of the main population. As the relevant feature set changed during the studied period, this approach allowed the modelling of a dynamic space of fuzzy similarity clusters at the sub-population level. The steps in the analysis where as follows. First the main population was defined as a crisp set of wineries. Second the yearly sets of relevant features were modelled, which was based on past publications of wine experts. Third, the feature vectors of the wineries were coded according to collected feature value data. Fourth, fuzzy cluster analysis was conducted for each year, which determined the number of similarity clusters, their centres, their contrast levels and grade of memberships of organizations. Finally, a statistically significant correlation was found between the entry rates and the contrasts of the sub-clusters. In addition, the analysis showed that initial membership of new entrants correlated with the cluster contrasts.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available