Perceptual Choice Experiments: Enhancing CBC to Get from Which to Why (2015)

CBC (Choice-Based Conjoint) choice simulators predict share of choice for product concepts within competitive market scenarios, but they provide no insights into perceptions—the why’s behind the choice.  The author (Orme) introduces Perceptual Choice Experiments as an extension of CBC questionnaires for integrating diagnostic perceptual dimensions into CBC analysis and simulators.  Experimental design, model estimation, and sample size issues are explicated.  Fortunately, perceptual choice experiments leverage the same tools we already employ in CBC studies: orthogonal experiments, MNL estimation, and market simulation via the logit rule (share of preference).  The author demonstrates how perceptual choice data may be analyzed using Sawtooth Software’s MBC system—though any system that can estimate MNL models is suitable for the task.

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