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2019
DOI: 10.2478/jec-2019-0011
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The Quality of Brand Products: Expected Attributes vs. Perceived Reality

Abstract: Research purpose. The quality means a core attribute of the product. Based on empirical assessment of the consumer, it is ascertained if the products are of high quality. However, there may be considerable counterarguments against this assessment, because quality is a subjective characteristic. For this reason, a paradoxical situation arises – the same product that we consider to be a quality product someone else may regard as insufficient quality. What is considered standard quality level in some cases may be… Show more

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Cited by 4 publications
(4 citation statements)
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“…Dimension reduction was performed for both Q1 and Q2 data sets using factor analysis -specifically Principal Component Analysis (PCA). In fact, factor analysis is widely used by scholars analysing working in the field of socials sciences and researching a significant amount of data (Durana et al 2019, Lentjusenkova et al 2016.…”
Section: Methodsmentioning
confidence: 99%
“…Dimension reduction was performed for both Q1 and Q2 data sets using factor analysis -specifically Principal Component Analysis (PCA). In fact, factor analysis is widely used by scholars analysing working in the field of socials sciences and researching a significant amount of data (Durana et al 2019, Lentjusenkova et al 2016.…”
Section: Methodsmentioning
confidence: 99%
“…The initial conditions of factor analysis include: a) high correlations of a large number of variables and b) low partial correlations. Whether the correlation and partial correlation matrices satisfy the assumptions is therefore tested by various coefficients and indices, usually KMO and Bartlett's sphericity test [21,22,23], see Table 1. The value of the Kaiser-Meyer-Olkin measure (KMO), i.e.…”
Section: Resultsmentioning
confidence: 99%
“…Table 3 shows the Rotation matrix by Varimax with Kaiser Normalization and contains the structure of the individual components and their loads expressing the degree of correlation of the variable with the given component [21]. In this case, all component loads came out high enough for unambiguous interpretation.…”
Section: Resultsmentioning
confidence: 99%
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