Evaluating The Total Costs Of Purchasing Via Probabilistic And Fuzzy Reasoning

Transaction costs analysis is concerned with ways of aligning appropriate governance modes with the attributes of economic transactions. Nowadays transaction costs are universally accep-ted, despite the difficulty in measuring and quantifying them. Starting from the customary definition of transaction costs, this paper proposes a model for the buyer/seller relationship, focusing on the uncertainty characterizing the exchange and the connected costs. In particular, according to a well-known classification, the transaction costs connected to the purchasing phase are divided into ex ante (drafting and negotiating agreements) and ex post (monitoring and enforcing agree-ments) costs. More precisely, we propose to employ appropriate deterministic mo-dels for evaluating ex ante costs and suitable statistical distributions for ex post costs. Obviously, both such costs categories require the quantification of several parameters related to the buyer operating the transaction and to the uncertainty characterizing the buyer/ seller relationship. Hence, in order to correctly evaluate the buyer behavior, a fuzzy logic inference system is design-ned for synthesizing, starting from expert judgments, the required data to the transaction costs model. The repor-ted simulation experiments show the effecttiveness of the proposed model in estimating the transaction costs and total costs associated with a generic transaction.