1990
DOI: 10.1007/978-3-662-08889-0
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Multivariate Analysemethoden

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Cited by 206 publications
(160 citation statements)
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“…Investigating and analysing consumer s' preferences and the extent products avail to them, is crucial for the explanation of consumer behaviour. Conjoint analysis has been introduced to marketing in the early 1970s [16] and is considered as a suitable metho d for product design regarding the needs of a consumer target segment [17] . Combining stimulating factors, consumer s' affective and cognitive components and their preferences towards newly developed food products results in the framework which is shown in Figure 1.…”
Section: Consumer Segmentation and Preference Testing Modelmentioning
confidence: 99%
“…Investigating and analysing consumer s' preferences and the extent products avail to them, is crucial for the explanation of consumer behaviour. Conjoint analysis has been introduced to marketing in the early 1970s [16] and is considered as a suitable metho d for product design regarding the needs of a consumer target segment [17] . Combining stimulating factors, consumer s' affective and cognitive components and their preferences towards newly developed food products results in the framework which is shown in Figure 1.…”
Section: Consumer Segmentation and Preference Testing Modelmentioning
confidence: 99%
“…Hence, they were not appropriate for our research objective (Bortz 2005). The Ward's method has the advantage that it combines objects which increase the within group variation as little as possible and therefore optimises the homogeneity of the clusters (Backhaus et al 2013). As similarity measure, we used the squared Euclidean distance (Hair et al 2010).…”
Section: Methodsmentioning
confidence: 99%
“…The cluster analysis reveals that SMEs are not equally distributed across clusters according to their firm-, product-and industry-specific characteristics (p < 0.01) (see Table 6). 9 Test statistics are provided in form of Pearson's chi-square and Cramer's V. Whereas the Pearson's chisquare test evaluates how likely it is that the observed differences arose by chance or, in other words, whether the distribution across the clusters differs significantly from its distribution in the total sample, Cramer's V measures the strength of association between the passive variable and the cluster affiliation (between 0 and 1) (Backhaus et al, 2013). 10 This result is in line with prior research which found that larger and more mature firms have lower information asymmetries and can therefore access a broader range of financing sources, whereas smaller and younger firms are more likely to use less external capital or-if external capital is required-tend to use more flexible short-term debt (Artola and Genre 2011;Berger and Udell 1998;Holmes and Kent 1991;Hutchinson 1995;.…”
Section: Cluster Analysismentioning
confidence: 99%