AHP-Group Decision Making: A Bayesian Approach Based on Mixtures for Group Pattern Identification

Pilar Gargallo, José María Moreno-Jiménez () and Manuel Salvador
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Pilar Gargallo: Universidad de Zaragoza
José María Moreno-Jiménez: Universidad de Zaragoza
Manuel Salvador: Universidad de Zaragoza

Group Decision and Negotiation, 2007, vol. 16, issue 6, No 1, 485-506

Abstract: Abstract This paper proposes a Bayesian estimation procedure to determine the priorities of the Analytic Hierarchy Process (AHP) in group decision making when there are a large number of actors and a prior consensus among them is not required. Using a hierarchical Bayesian approach based on mixtures to describe the prior distribution of the priorities in the multiplicative model traditionally used in the stochastic AHP, this methodology allows us to identify homogeneous groups of actors with different patterns of behaviour for the rankings of priorities. The proposed procedure consists of a two-step estimation algorithm: the first step carries out a global exploration of the model space by using birth and death processes, the second concerns a local exploration by means of Gibbs sampling. The methodology has been illustrated by the analysis of a case study adapted from a real experiment on e-democracy developed for the City Council of Zaragoza (Spain).

Keywords: group decision making; AHP; priority; Bayesian analysis; mixtures; MCMC; e-democracy (search for similar items in EconPapers)
Date: 2007
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Citations: View citations in EconPapers (7)

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DOI: 10.1007/s10726-006-9068-0

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