Conjoint analysis based on rough approximations by dominance relations using interval regression analysis
Kazutomi Sugihara, Hiroaki Ishii, Hideo Tanaka · 2003
Conjoint analysis is a method for deriving the part worth value of each factor from the total evaluations. This can be also applied to multi-criteria ranking or choice problems. In conjoint analysis, it is generally assumed that the value function is pre-defined as the additive and transitive model. However, there exist many cases in which the pre-defined value function is not appropriate to real situations. We propose conjoint analysis based on rough sets approximated by qualitative data dominance relations. In our formulation, qualitative data often used in the conventional method are transformed into ordered values by dominance relations using interval regression analysis. Our proposed model is suitable for complex situations in which additivity and transitivity do not hold.