Diagnosis of Interactive Conjoint Analysis Based on Social Comparison

Dennis Castel, Fei Wei, Ryosuke Saga and Hiroshi Tsuji
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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

International Journal of Knowledge and Systems Science (IJKSS), 2014, vol. 5, issue 2, 19-34

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.

Date: 2014
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