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Profitability of Customer Satisfaction Segments: Genetic Algorithm Method in Multidimensional Clustering

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26510%2F15%3APU114559" target="_blank" >RIV/00216305:26510/15:PU114559 - isvavai.cz</a>

  • Result on the web

    <a href="https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84947601807&origin=inward" target="_blank" >https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84947601807&origin=inward</a>

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Profitability of Customer Satisfaction Segments: Genetic Algorithm Method in Multidimensional Clustering

  • Original language description

    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.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    50602 - Public administration

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2015

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    In Innovation Vision 2020: From Regional Development Sustainability to Global Economic Growth

  • ISBN

    978-0-9860419-4-5

  • ISSN

  • e-ISSN

  • Number of pages

    11

  • Pages from-to

    2561-2571

  • Publisher name

    Neuveden

  • Place of publication

    Amsterdam, Netherlands

  • Event location

    Amsterdam

  • Event date

    May 7, 2015

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    000360508700250