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This paper examines consensus building in AHP-group decision making from a Bayesian perspective. In accordance with the multicriteria procedural rationality paradigm, the methodology employed in this study permits the automatic identification, in a local context, of “agreement” and “disagreement” zones among the actors involved. This approach is based on the analysis of the pairwise comparison matrices provided by the actors themselves. In addition, the study integrates the attitudes of the actors implicated in the decision-making process and puts forward a number of semiautomatic initiatives for establishing consensus. This information is given to the actors as the first step in the negotiation processes. The knowledge obtained will be incorporated into the system via the learning process developed during the resolution of the problem. The proposed methodology, valid for the analysis of incomplete or imprecise pairwise comparison matrices, is illustrated by an example.

This paper presents a new procedure, to which we have given the name Aggregation of Individual Preference Structures (AIPS), whose objective is to deal with multiactor decision making when using Analytic Hierarchy Process (AHP) as the methodological support. This procedure incorporates ideas similar to Borda count methods and transfers to the case of preference structures the principle of aggregation employed in the two approaches traditionally followed in AHP-group decision making (aggregation of individual judgments and aggregation of individual priorities). The new aggregation method allows us to capture: (i) the richness of uncertainty inherent to human beings; (ii) the vision of each decision maker within the context of the problem; (iii) the interdependencies between the alternatives being compared and (iv) the intensities of the preferences that each decision maker gives to these interdependencies. From the preference structure distribution associated to each decision maker, this new approach (AIPS) provides the holistic importance of each alternative and ranking, as well as the most representative preference structure distribution for the group. The knowledge derived from these could be employed as an initial step in the search for consensus, which characterises the negotiation processes followed by the actors involved in the resolution of decisional problems.

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This paper presents a new tool, the Consistency Consensus Matrix, designed to encourage the search for consensus in group decision making when using the Analytic Hierarchy Process (AHP). The procedure exploits one of the characteristics of AHP: the possibility of measuring consistency in judgement elicitation. Using two other tools, Preference Structures and Stability Intervals, we derive the Consistency Consensus Matrix that corresponds to the actor's core of consistency. The performance analysis of the preference structure obtained from this matrix provides us with valuable information in search for knowledge. The new tool is illustrated by means of a case study adapted from a real-life experiment in edemocracy developed for the City Council of Zaragoza (Spain).