Literature indicates that events like a wine festival have many role players involved that need each other for them to be successful. The more role players there are, the more complex the event becomes, as in the case of the Wacky Wine Festival which is spread over 48 wine farms. The most important role players are the visitors and wine farmers that represent the demand and supply side of the festival. Local enterprises, wine farmers and the festival organisers put a lot of effort into the event, such as their time, money and skills. It is essential for these role players to know that they will get a return on their investment and for the host community to know that the festival will make a contribution to their local economy. Furthermore, literature indicates that the festival can improve the economic position of the role players by targeting the high spending market through intensive marketing that focuses on this particular segment. Therefore, the purpose of this study was to determine the contribution of the Wacky Wine Festival to the local economy and to compile a profile of the heavy spender. To achieve the latter, a quantitative study was carried out by means of two surveys via questionnaires that were handed out to both the visitor and wine farmer. The data was then captured in Microsoft© Excel©. In Article 1 (Chapter 2) the sales multiplier effect and an analytical framework were used to determine the contribution of the festival to the host community. In Article 2 (Chapter 3) different tests and analyses were used to compile a profile of the heavy spender such as the K–means clustering, Chi–Squared, the Mann–Whitney non–parametric test and an ANOVA analysis. The results from Article 1 (Chapter 2) showed that the Wacky Wine Festival had an positive economic contribution of an estimated R29.9 million to the host community`s economy. From a demand and supply point of view, the visitors contributed R15.4 million and the wine farmers R6 million. From the results, it could be derived that the festival had low leakages in comparison with other festivals. iii The results from Article 2 (Chapter 3) indicated that the heavy and low spenders differ in terms of gender, language, age, occupation, number of people paying for in travelling group, residence and number of days spent at the festival. It was clear from the results that if the festival organisers and wine farmers focus marketing strategies on the high spending segment, this can lead to a R10 million increase in the Wacky Wine Festival’s revenue, thus improving the economic contribution of the event to the local economy of Robertson. / Thesis (M.Com. (Tourism))--North-West University, Potchefstroom Campus, 2012.

Literature indicates that events like a wine festival have many role players involved that need each other for them to be successful. The more role players there are, the more complex the event becomes, as in the case of the Wacky Wine Festival which is spread over 48 wine farms. The most important role players are the visitors and wine farmers that represent the demand and supply side of the festival. Local enterprises, wine farmers and the festival organisers put a lot of effort into the event, such as their time, money and skills. It is essential for these role players to know that they will get a return on their investment and for the host community to know that the festival will make a contribution to their local economy. Furthermore, literature indicates that the festival can improve the economic position of the role players by targeting the high spending market through intensive marketing that focuses on this particular segment. Therefore, the purpose of this study was to determine the contribution of the Wacky Wine Festival to the local economy and to compile a profile of the heavy spender. To achieve the latter, a quantitative study was carried out by means of two surveys via questionnaires that were handed out to both the visitor and wine farmer. The data was then captured in Microsoft© Excel©. In Article 1 (Chapter 2) the sales multiplier effect and an analytical framework were used to determine the contribution of the festival to the host community. In Article 2 (Chapter 3) different tests and analyses were used to compile a profile of the heavy spender such as the K–means clustering, Chi–Squared, the Mann–Whitney non–parametric test and an ANOVA analysis. The results from Article 1 (Chapter 2) showed that the Wacky Wine Festival had an positive economic contribution of an estimated R29.9 million to the host community`s economy. From a demand and supply point of view, the visitors contributed R15.4 million and the wine farmers R6 million. From the results, it could be derived that the festival had low leakages in comparison with other festivals. iii The results from Article 2 (Chapter 3) indicated that the heavy and low spenders differ in terms of gender, language, age, occupation, number of people paying for in travelling group, residence and number of days spent at the festival. It was clear from the results that if the festival organisers and wine farmers focus marketing strategies on the high spending segment, this can lead to a R10 million increase in the Wacky Wine Festival’s revenue, thus improving the economic contribution of the event to the local economy of Robertson. / Thesis (M.Com. (Tourism))--North-West University, Potchefstroom Campus, 2012.

- Ph.D. thesis - Milan Urban, 2017 In some years, the agricultural production of oilseed rape, an important crop in the Czech Republic, is - besides biotic stress - facing the problem of damage caused by frost or drought. Together with special attention paid to proteins revealing responses between crop genotypes with differential abiotic stress tolerance levels we reviewed possible applications of proteomic results in crop breeding programs aimed at an improvement of crop stress tolerance (paper 1). For first original result, cold temperature was imposed upon non-vernalized plants in the stage of leaf rosette. The article (paper 2) shows a significant correlation between frost tolerance (FT), dehydrin (DHN) accumulation, and photosynthetic acclimation in five cultivars (cvs). Newly, the specific DHN D97 was shown to accumulate and other DHNs were shown to have qualitative differences in accumulation. These results imply that proper FT assessment is based on rapid photosynthetic acclimation together with higher accumulation of protective compounds. Drought stress (paper 3) was imposed in the water- demanding stem prolongation phase before flowering, because late-spring drought before and during flowering decreases the yield and seed quality significantly. This paper newly describes two water-uptake...

In this thesis, cluster analysis was applied to data comprising of customer spending habits at a retail chain in order to perform customer segmentation. The method used was a two-step cluster procedure in which the first step consisted of feature engineering, a square root transformation of the data in order to handle big spenders in the data set and finally principal component analysis in order to reduce the dimensionality of the data set. This was done to reduce the effects of high dimensionality. The second step consisted of applying clustering algorithms to the transformed data. The methods used were K-means clustering, Gaussian mixture models in the MCLUST family, t-distributed mixture models in the tEIGEN family and non-negative matrix factorization (NMF). For the NMF clustering a slightly different data pre-processing step was taken, specifically no PCA was performed. Clustering partitions were compared on the basis of the Silhouette index, Davies-Bouldin index and subject matter knowledge, which revealed that K-means clustering with K = 3 produces the most reasonable clusters. This algorithm was able to separate the customer into different segments depending on how many purchases they made overall and in these clusters some minor differences in spending habits are also evident. In other words there is some support for the claim that the customer segments have some variation in their spending habits. / I denna uppsats har klusteranalys tillämpats på data bestående av kunders konsumtionsvanor hos en detaljhandelskedja för att utföra kundsegmentering. Metoden som använts bestod av en två-stegs klusterprocedur där det första steget bestod av att skapa variabler, tillämpa en kvadratrotstransformation av datan för att hantera kunder som spenderar långt mer än genomsnittet och slutligen principalkomponentanalys för att reducera datans dimension. Detta gjordes för att mildra effekterna av att använda en högdimensionell datamängd. Det andra steget bestod av att tillämpa klusteralgoritmer på den transformerade datan. Metoderna som användes var K-means klustring, gaussiska blandningsmodeller i MCLUST-familjen, t-fördelade blandningsmodeller från tEIGEN-familjen och icke-negativ matrisfaktorisering (NMF). För klustring med NMF användes förbehandling av datan, mer specifikt genomfördes ingen PCA. Klusterpartitioner jämfördes baserat på silhuettvärden, Davies-Bouldin-indexet och ämneskunskap, som avslöjade att K-means klustring med K=3 producerar de rimligaste resultaten. Denna algoritm lyckades separera kunderna i olika segment beroende på hur många köp de gjort överlag och i dessa segment finns vissa skillnader i konsumtionsvanor. Med andra ord finns visst stöd för påståendet att kundsegmenten har en del variation i sina konsumtionsvanor.