抄録
This paper proposes a goods evaluation model by introducing perceptual encoding. We first distinguish between physical characteristics and attributes by dividing information on goods, acquired by consumers, into information on the physical characteristics and that on the situations in which goods are used. That enables us to define perceptual encoding as that consumers recognize the physical characteristics and evoke the situations to estimate the attributes by the law of cause and effect they have learned through purchase experience.Based on the definition, we build a model of perceptual encoding as estimation of the population parameter of a binominal distribution by Bayseian inference. We got a framework for theoretical analysis of the process from information acquisition to goods evaluation, by which we can analise the influence of goods'character and uncertainty of the law of cause and effect on goods evaluation at information processing level.
