The Use of Cluster Analysis for Development of Categorical Factors in Exploratory Study: Facts and Findings from the Field Research

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F46747885%3A24310%2F16%3A00001014" target="_blank" >RIV/46747885:24310/16:00001014 - isvavai.cz</a>

Výsledek na webu

<a href="http://mme2016.tul.cz/conferenceproceedings/mme2016_conference_proceedings.pdf" target="_blank" >http://mme2016.tul.cz/conferenceproceedings/mme2016_conference_proceedings.pdf</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

The Use of Cluster Analysis for Development of Categorical Factors in Exploratory Study: Facts and Findings from the Field Research

Popis výsledku v původním jazyce

This paper describes the development of categorical latent variables and their use for the typology development. The main idea of this modeling was to investigate the possibility of using the classification methods instead of factor analysis for development of the final latent variable which can cumulatively explain the set of primary indicators. The modeling is based on the empirical findings from the online retail consumers’ behavior study. Selected data allowed confirm the statement that even the small data sets using the classification data analysis methods can display the significant Ecological Validity. The modeling was performed in three steps. First, the number of primary indicators was reduced using the factor analysis. Based on it several latent variables were created. Second, the k-mean cluster analysis instead of secondary factor analysis was used for development of three cluster variables that represent six clusters in total. Third, all three variables were used for development of the final latent variable which is categorical and represents the eight theoretically possible and five empirically confirmed categories.

Název v anglickém jazyce

The Use of Cluster Analysis for Development of Categorical Factors in Exploratory Study: Facts and Findings from the Field Research

Popis výsledku anglicky

This paper describes the development of categorical latent variables and their use for the typology development. The main idea of this modeling was to investigate the possibility of using the classification methods instead of factor analysis for development of the final latent variable which can cumulatively explain the set of primary indicators. The modeling is based on the empirical findings from the online retail consumers’ behavior study. Selected data allowed confirm the statement that even the small data sets using the classification data analysis methods can display the significant Ecological Validity. The modeling was performed in three steps. First, the number of primary indicators was reduced using the factor analysis. Based on it several latent variables were created. Second, the k-mean cluster analysis instead of secondary factor analysis was used for development of three cluster variables that represent six clusters in total. Third, all three variables were used for development of the final latent variable which is categorical and represents the eight theoretically possible and five empirically confirmed categories.

Druh

D - Stať ve sborníku

CEP obor

BB - Aplikovaná statistika, operační výzkum

OECD FORD obor

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Projekt

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Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2016

Kód důvěrnosti údajů

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

Název statě ve sborníku

34th International Conference Mathematical Methods in Economics 2016. Conference Proceedings. September 6th - 9th, 2016, Liberec, Czech Republic

ISBN

978-80-7494-296-9

ISSN

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e-ISSN

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Počet stran výsledku

6

Strana od-do

869-874

Název nakladatele

Technical University of Liberec

Místo vydání

Liberec

Místo konání akce

Liberec

Datum konání akce

1. 1. 2016

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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