Customer Satisfaction Measurement – Clustering Approach
The result's identifiers
Result code in 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>
Result on the web
<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>
Alternative languages
Result language
angličtina
Original language name
Customer Satisfaction Measurement – Clustering Approach
Original language description
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.
Czech name
—
Czech description
—
Classification
Type
J<sub>SC</sub> - Article in a specialist periodical, which is included in the SCOPUS database
CEP classification
—
OECD FORD branch
50204 - Business and management
Result continuities
Project
—
Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis
ISSN
1211-8516
e-ISSN
2464-8310
Volume of the periodical
66
Issue of the periodical within the volume
2
Country of publishing house
CZ - CZECH REPUBLIC
Number of pages
9
Pages from-to
561-569
UT code for WoS article
—
EID of the result in the Scopus database
2-s2.0-85047602602