Selected Methods of Categorical Data Analysis and Their Application in Consumer Behaviour Research

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F71226401%3A_____%2F20%3AN0100412" target="_blank" >RIV/71226401:_____/20:N0100412 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/62156489:43110/20:43918277

Výsledek na webu

<a href="https://mme2020.mendelu.cz/wcd/w-rek-mme/mme2020_conference_proceedings_final_final.pdf" target="_blank" >https://mme2020.mendelu.cz/wcd/w-rek-mme/mme2020_conference_proceedings_final_final.pdf</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Selected Methods of Categorical Data Analysis and Their Application in Consumer Behaviour Research

Popis výsledku v původním jazyce

This paper explores the methods of categorical data analysis, with special focus on their pros and cons and their possible application in the research of Czech consumers’ shopping habits. To that end, a large survey mapping shopping preferences of Czech consumers (mainly the shopping behaviours of different genders in relation to their income, education, age, place of residence etc.) has been used as a source of data. The survey results were analyzed using the contingency tables analysis, including the Pearson’s chi-squared test of independence in contingency tables. The dependence intensity was identified via Pearson’s Contingency Coefficient and the impact of individual categories was assessed with the post-hoc residual test. The influence of several combined factors on the payment method was tested through logistic regression; the model parameters were estimated by the Maximum Likelihood Estimation and the ROC curve allowed for the assessment of the model’s quality. Every method proved a statistically significant dependence of the most frequent payment method on the education and age of respondents, number of household members and the size of respondents’ place of residence.

Název v anglickém jazyce

Selected Methods of Categorical Data Analysis and Their Application in Consumer Behaviour Research

Popis výsledku anglicky

This paper explores the methods of categorical data analysis, with special focus on their pros and cons and their possible application in the research of Czech consumers’ shopping habits. To that end, a large survey mapping shopping preferences of Czech consumers (mainly the shopping behaviours of different genders in relation to their income, education, age, place of residence etc.) has been used as a source of data. The survey results were analyzed using the contingency tables analysis, including the Pearson’s chi-squared test of independence in contingency tables. The dependence intensity was identified via Pearson’s Contingency Coefficient and the impact of individual categories was assessed with the post-hoc residual test. The influence of several combined factors on the payment method was tested through logistic regression; the model parameters were estimated by the Maximum Likelihood Estimation and the ROC curve allowed for the assessment of the model’s quality. Every method proved a statistically significant dependence of the most frequent payment method on the education and age of respondents, number of household members and the size of respondents’ place of residence.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

40500 - Other agricultural sciences

Projekt

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Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2020

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

38th International Conference on Mathematical Methods in Economics

ISBN

978-80-7509-734-7

ISSN

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e-ISSN

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Počet stran výsledku

684

Strana od-do

656-661

Název nakladatele

Published by Mendel University Publishing Center

Místo vydání

Brno

Místo konání akce

Brno, Czech Republic

Datum konání akce

9. 9. 2020

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000668460800100