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An Adaptive Questionnaire generation using learning from fuzzy and post clustering of customers responses: an Experience with Communication Products

Abstract

A central problem in marketing is the clear understanding of consumer’s choice or preferences. Designing questionnaires and then analyzing the answers of probable customers can achieve this. The traditional approach in the marketing analysis has been the designing of non-adaptive questionnaires, questionnaires that are predetermined and not at all influenced by respondent’s answers. The aim of this paper is to design a questionnaire that is influenced by respondent’s answer through implementation of soft computing and approximate reasoning methodologies. The learning of particular pattern on respondent’s fuzzy responses has also been envisaged in the post-survey (Post-conjoint) and further better clustering of choices and segregation is accomplished. The module of learning and finer clustering from respondent’s choice pattern could be a major pre-requisite for construction of adaptive questionnaires. Further extensions of the soft computing methods for product recommender system have also been mentioned for the design of adaptive questionnaire.

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Correspondence to Soumya Banerjee.

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Banerjee, S., Al-Qaheri, H., Chiş, M. et al. An Adaptive Questionnaire generation using learning from fuzzy and post clustering of customers responses: an Experience with Communication Products. Telecommun Syst 46, 273–284 (2011). https://doi.org/10.1007/s11235-010-9290-6

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Keywords

  • Adaptive Questionnaire
  • Fuzzy Leaning and Clustering
  • Conjoint Analysis