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SCHÜLLER, D. PEKÁREK, J. DOSTÁL, P. CHLEBOVSKÝ, V.
Originální název
Profitability of Customer Satisfaction Segments: Genetic Algorithm Method in Multidimensional Clustering
Typ
článek ve sborníku ve WoS nebo Scopus
Jazyk
angličtina
Originální abstrakt
Abstract Due to limited recourses it is difficult for companies to reach a 100% satisfaction level of all customers in all measured factors. Therefore it is argued in this study that the profitability of customer segments is the key driver which companies should take into account in the improvement process of customer satisfaction. The study presents the use of multidimensional genetic algorithm clustering as the efficient method which allows to divide existing customers of a company into relatively homogenous segments according to their satisfaction with the selected factors and on the basis of the profitability of each segment to identify different strategies for the satisfaction improvement process. The suggested procedure is demonstrated on the real data from the field of tea products.
Klíčová slova
Satisfaction, Segmentation, Genetic Algorithm Clustering, Profitability
Autoři
SCHÜLLER, D.; PEKÁREK, J.; DOSTÁL, P.; CHLEBOVSKÝ, V.
Rok RIV
2015
Vydáno
7. 5. 2015
Místo
Amsterdam, Netherlands
ISBN
978-0-9860419-4-5
Kniha
In Innovation Vision 2020: From Regional Development Sustainability to Global Economic Growth
Edice
25
ISSN
NEUVEDENO
Strany od
2561
Strany do
2571
Strany počet
11
URL
https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84947601807&origin=inward
BibTex
@inproceedings{BUT115125, author="David {Schüller} and Jan {Pekárek} and Petr {Dostál} and Vít {Chlebovský}", title="Profitability of Customer Satisfaction Segments: Genetic Algorithm Method in Multidimensional Clustering", booktitle="In Innovation Vision 2020: From Regional Development Sustainability to Global Economic Growth", year="2015", series="25", pages="2561--2571", address="Amsterdam, Netherlands", isbn="978-0-9860419-4-5", url="https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84947601807&origin=inward" }