Statistics for Marketing and Consumer Research

Mazzocchi, Mario

doi:10.4135/9780857024657

Cited by 124 publications

(114 citation statements)

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“…To measure the internal reliability of the three dimensions, credibility and usefulness, suspiciousness, and entertainment factor, Cronbach's alpha was provided. 16 Evaluating whether the three dimensions of the original questionnaire were also represented by the shortened instrument, a principal components factor analysis using varimax rotation 17 was applied. The purpose of factor analysis was to confirm that the observed variables could be described by the three dimensions that could not be measured directly.…”

Section: Methodsmentioning

confidence: 99%

Instruments for analysing the influence of advertising on children's food choices

Gwozdz

Reisch

2011

Int J Obes

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Objective: The aim of this report was to present methodological aspects of assessing the effects of advertising on children's food choices and preferences. Methods: Two instruments have been used: first, a choice experiment on children's food knowledge and preferences, and second, a questionnaire on children's knowledge about and attitudes towards advertising. The choice experiment employed 10 matched pairs of food items, each represented in two magazines, one that tested knowledge and the other food preferences. The children's questionnaire contained four dimensions that tested children's credibility and suspiciousness of, as well as entertainment by, advertising. Although based on already developed tools, both instruments were modified to suit the young target group and ensure cross-cultural comparability. The questionnaire was validated via Cronbach's alpha and factor analysis. Subjects: A total of 393 children aged 5-11 years from seven European countries participated in the study. Results: Both instruments proved to be valid and reliable to analyse the food knowledge and preferences of children, as well as knowledge about and attitudes towards advertising. While 92.2% of the children predominantly recognised the healthier food, only 33.2% also preferred the healthier food. The Cronbach's alpha values for the dimensions were 0.470 for credibility, 0.409 for suspiciousness and 0.295 for entertainment factor. The gathered data revealed that children are rather critical and suspicious of advertising and only moderately entertained. Conclusion: Both instruments are applicable for the 5-to 11-year-old age group in different European countries. Descriptive results indicate additional insights into the effects of advertising on children's food knowledge, preferences and food choice.

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Section: Methodsmentioning

confidence: 99%

Instruments for analysing the influence of advertising on children's food choices

Gwozdz

Reisch

2011

Int J Obes

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“…The selected linkage measure will have a direct impact on the clustering procedure and the way in which clusters are merged together (Mazzocchi, 2008). This will subsequently impact the final cluster solution.…”

Section: Linkage Measurementioning

confidence: 99%

“…There exist many different linkage measures that define the distance between pairs of clusters in their own way. Some measures define the distance between two clusters based on the smallest or largest distance that can be found between pairs of cases (single and complete linkage, respectively) in which each case is from a different cluster (Mazzocchi, 2008). Average linkage averages all distance values between pairs of cases from different clusters.…”

Section: Linkage Measurementioning

confidence: 99%

Hierarchical Cluster Analysis: Comparison of Three Linkage Measures and Application to Psychological Data

Yim¹,

Ramdeen²

2015

TQMP

421

254

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Abstract Abstract Cluster analysis refers to a class of data reduction methods used for sorting cases, observations, or variables of a given dataset into homogeneous groups that differ from each other. The present paper focuses on hierarchical agglomerative cluster analysis, a statistical technique where groups are sequentially created by systematically merging similar clusters together, as dictated by the distance and linkage measures chosen by the researcher. Specific distance and linkage measures are reviewed, including a discussion of how these choices can influence the clustering process by comparing three common linkage measures (single linkage, complete linkage, average linkage). The tutorial guides researchers in performing a hierarchical cluster analysis using the SPSS statistical software. Through an example, we demonstrate how cluster analysis can be used to detect meaningful subgroups in a sample of bilinguals by examining various language variables.

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“…Os valores, apresentados por escala (dimensão) e por amostra na Tabela 3, são satisfatórios, todos substancialmente acima do limite mínimo de 0,70, critério usualmente empregado para tratar construtos reflexivos unidimensionais (Churchill, 1979;Mazzocchi, 2008;Costa, 2011). …”

Section: Materialismounclassified