Customer Satisfaction Measurement – Clustering Approach

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26510%2F18%3APU127810" target="_blank" >RIV/00216305:26510/18:PU127810 - isvavai.cz</a>

Výsledek na webu

<a href="https://acta.mendelu.cz/66/2/0561/" target="_blank" >https://acta.mendelu.cz/66/2/0561/</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.11118/actaun201866020561" target="_blank" >10.11118/actaun201866020561</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Customer Satisfaction Measurement – Clustering Approach

Popis výsledku v původním jazyce

The paper deals with the issue of customer satisfaction measurement. The aim of this study is to determine the importance of the individual factors and their impact on total customer satisfaction for multiple segments by using linear regression and hierarchical clustering. This study is focused on the market of café establishment. We applied hierarchical clustering with Ward’s criterion to partition customers into segments and then we developed linear regression models for each segment. Linear models for partitioned data showed higher coefficient of determination than the model for the whole market. The results revealed that there are quite significant differences in rankings of customer satisfaction factors among the segments. This is caused by the different preferences of customers. The clustered data allows to achieve a higher homogeneity of data within the segment, which is crucial both for marketing theory and practice. The approach i.e. partitioning the market into smaller more specific segments could become perspective for marketing use in different economic sectors. This attitude can allow marketers to target better on customer segments according to the importance of individual factors.

Název v anglickém jazyce

Customer Satisfaction Measurement – Clustering Approach

Popis výsledku anglicky

The paper deals with the issue of customer satisfaction measurement. The aim of this study is to determine the importance of the individual factors and their impact on total customer satisfaction for multiple segments by using linear regression and hierarchical clustering. This study is focused on the market of café establishment. We applied hierarchical clustering with Ward’s criterion to partition customers into segments and then we developed linear regression models for each segment. Linear models for partitioned data showed higher coefficient of determination than the model for the whole market. The results revealed that there are quite significant differences in rankings of customer satisfaction factors among the segments. This is caused by the different preferences of customers. The clustered data allows to achieve a higher homogeneity of data within the segment, which is crucial both for marketing theory and practice. The approach i.e. partitioning the market into smaller more specific segments could become perspective for marketing use in different economic sectors. This attitude can allow marketers to target better on customer segments according to the importance of individual factors.

Druh

J_SC - Článek v periodiku v databázi SCOPUS

CEP obor

—

OECD FORD obor

50204 - Business and management

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2018

Kód důvěrnosti údajů

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

Název periodika

Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis

ISSN

1211-8516

e-ISSN

2464-8310

Svazek periodika

66

Číslo periodika v rámci svazku

2

Stát vydavatele periodika

CZ - Česká republika

Počet stran výsledku

9

Strana od-do

561-569

Kód UT WoS článku

—

EID výsledku v databázi Scopus

2-s2.0-85047602602