Contingent Valuation of Non-Market Goods Based on Intuitionistic Fuzzy Clustering: Part I

Abstract

In order to value the non-market goods, we consider the uncertain preference of the respondents for non-market goods, individual often have trouble trading off the good or amenity against a monetary measure. Valuation in these situations can best be described as fuzzy in terms of the amenity being valued. We move away from a probabilistic representation of uncertainty and propose the use of intuitionistic fuzzy contingent valuation. That is to say we could apply intuitionistic fuzzy logic to contingent valuation. Since intuitionistic fuzzy sets could provide the information of the membership degree and the nonmembership degree, it has more expression and flexibility better than traditional fuzzy sets in processing uncertain information data. In this paper, we apply intuitionistic fuzzy logic to contingent, developing an intuitionistic fuzzy clustering and interval intuitionistic fuzzy clustering approach for combining preference uncertainty. We develop an intuitionistic fuzzy random utility maximization framework where the perceived utility of each individual is intuitionistic fuzzy in the sense that an individual’s utility belong to each cluster to some degree. Both the willingness to pay (WTP) and willingness not to pay (WNTP) measures we obtain using intuitionistic fuzzy approach are below those using standard probability methods.