Using case data to ensure 'real world' input validation within fuzzy set theory models

Sara M. Denize, Sharon Purchase, Doina Olaru

    Research output: Chapter in Book / Conference PaperChapter

    7 Citations (Scopus)

    Abstract

    Fuzzy set theory models have considerable potential to address complex marketing and B2B problems, but for this methodology to be accepted, models require validation. However, there is relatively little detail in the literature dealing with validation of fuzzy simulation in marketing. This limitation is compounded by the difficulty of using case-based and qualitative evidence (data to which fuzzy models are well suited) when applying more general validation. The chapter illustrates a fuzzy model validation process using small-N cased based data and concludes with recommendations to assist researchers in validating their fuzzy models.
    Original languageEnglish
    Title of host publicationFuzzy methods for customer relationship management and marketing : applications and classifications
    EditorsAndreas Meier, Laurent Donzé
    Place of PublicationU.S
    PublisherBusiness Science Reference
    Pages61-89
    Number of pages29
    ISBN (Print)9781466600959
    Publication statusPublished - 2012

    Keywords

    • customer relations
    • fuzzy logic
    • fuzzy sets
    • marketing

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