Using Case Data to Ensure ‘Real World’ Input Validation within Fuzzy Set Theory Models

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Author(s): Sara Denize (University of Western Sydney, Australia), Sharon Purchase (University of Western Australia, Australia)and Doina Olaru (University of Western Australia, Australia)
Copyright: 2012
Pages: 29
Source title: Fuzzy Methods for Customer Relationship Management and Marketing: Applications and Classifications
Source Author(s)/Editor(s): Andreas Meier (University of Fribourg, Switzerland)and Laurent Donzé (University of Fribourg, Switzerland)
DOI: 10.4018/978-1-4666-0095-9.ch004

Keywords: Business & Management / Business Science Reference / Marketing / Marketing and Consumer Behavior

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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.

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