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EN
The multiple criteria decision making (MCDM) methodology provides decision mak-ers (DM) with a set of universal methods and models that may also be applied for sup-porting negotiation processes. In this paper we discuss the usability of various classic MCDA techniques taking into account decision maker’s subjective preferences for evaluating the negotiation template and building the scoring system for negotiation offers evaluation in the well-structured negotiation problems. This scoring system allows for evaluation of the negotiation offers, ranking and comparing them and therefore makes it easier for negotiators to decide on accepting or rejecting of different contract alternatives proposed by their counterparts. The main goal of the paper is to present a comparative analysis of four multiple crite-ria decision making methods such as: SAW, MAUT, AHP, TOPSIS, the fundamental as-sumptions of which are different, but allow for using them in the negotiation support. All presented procedures make it possible to evaluate the negotiation offers (full packages) and build a ranking of them (and ordering them from the best to the worst one), to deter-mine the alternative offers, to evaluate and compare the extent size of potential conces-sions. Those procedures also allow for conducting postnegotiation analysis in order to find the improvements of the compromise negotiated by the parties themselves by im-plementing some arbitration procedures derived directly from the game theory. We pre-sent the fundamental notions as well as the formal algorithms of each procedure discuss-ing both their advantages and disadvantages. Furthermore, we describe some modifica-tions of these methods that make them more applicable for solving negotiation problems. An example of application in the negotiation context is also presented in the case of problem where the space of feasible alternatives continues. We show in an example how some of the discussed methods are chosen that fit the specific problem, namely the con-struction of a continuous scoring functions allowing for the evaluation of any feasible al-ternative.
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