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Diagnosis of Interactive Conjoint Analysis Based on Social Comparison

Author

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  • Dennis Castel

    (Department of Computer Science and Intelligent System, Osaka Prefecture University, Osaka, Japan)

  • Fei Wei

    (Department of Computer Science and Intelligent System, Osaka Prefecture University, Osaka, Japan)

  • Ryosuke Saga

    (Department of Computer Science and Intelligent System, Osaka Prefecture University, Osaka, Japan)

  • Hiroshi Tsuji

    (Department of Computer Science and Intelligent System, Osaka Prefecture University, Osaka, Japan)

Abstract

To help non-professional background respondents to get awareness from complicated calculations of conjoint analysis, this paper presents overview and functions of preference diagnosis, transforming results of conjoint analysis from tacit knowledge to explicit knowledge. This process also leads to the creation of new knowledge. In addition, this paper also discusses a design of diagnosis model by positioning on individual, groups and clusters. A simple example is also discussed. The proposal includes two types of strategy: by-individual feature, a diagnosis generated in the result of conjoint analysis for individual and by-social feature, a diagnosis based on the comparison with analytical result of other respondents.

Suggested Citation

  • Dennis Castel & Fei Wei & Ryosuke Saga & Hiroshi Tsuji, 2014. "Diagnosis of Interactive Conjoint Analysis Based on Social Comparison," International Journal of Knowledge and Systems Science (IJKSS), IGI Global, vol. 5(2), pages 19-34, April.
    • Handle: RePEc:igg:jkss00:v:5:y:2014:i:2:p:19-34
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