000117240 001__ 117240
000117240 005__ 20240319080955.0
000117240 0247_ $$2doi$$a10.3390/math10030519
000117240 0248_ $$2sideral$$a128646
000117240 037__ $$aART-2022-128646
000117240 041__ $$aeng
000117240 100__ $$0(orcid)0000-0002-0117-7655$$aAltuzarra Casas, A.$$uUniversidad de Zaragoza
000117240 245__ $$aIdentification of Homogeneous Groups of Actors in a Local AHP-Multiactor Context with a High Number of Decision-Makers: A Bayesian Stochastic Search
000117240 260__ $$c2022
000117240 5060_ $$aAccess copy available to the general public$$fUnrestricted
000117240 5203_ $$aThe identification of homogeneous groups of actors in a local AHP-multiactor context based on their preferences is an open problem, particularly when the number of decision-makers is high. To solve this problem in the case of using stochastic AHP, this paper proposes a new Bayesian stochastic search methodology for large-scale problems (number of decision-makers greater than 20). The new methodology, based on Bayesian tools for model comparison and selection, takes advantage of the individual preference structures distributions obtained from stochastic AHP to allow the identification of homogeneous groups of actors with a maximum common incompatibility threshold. The methodology offers a heuristic approach with several near-optimal partitions, calculated by the Occam’s window, that capture the uncertainty that is inherent when considering intangible aspects (AHP). This uncertainty is also reflected in the graphs that show the similarities of the decision-maker’s opinions and that can be used to achieve representative collective positions by constructing agreement paths in negotiation processes. If a small number of actors is considered, the proposed algorithm (AHP Bayesian clustering) significantly reduces the computational time of group identification with respect to an exhaustive search method. The methodology is illustrated by a real case of citizen participation based on e-Cognocracy. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.
000117240 536__ $$9info:eu-repo/grantAgreement/ES/DGA-FEDER/S35-20R
000117240 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttp://creativecommons.org/licenses/by/3.0/es/
000117240 590__ $$a2.4$$b2022
000117240 592__ $$a0.446$$b2022
000117240 591__ $$aMATHEMATICS$$b23 / 329 = 0.07$$c2022$$dQ1$$eT1
000117240 593__ $$aComputer Science (miscellaneous)$$c2022$$dQ2
000117240 593__ $$aMathematics (miscellaneous)$$c2022$$dQ2
000117240 593__ $$aEngineering (miscellaneous)$$c2022$$dQ2
000117240 594__ $$a3.5$$b2022
000117240 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000117240 700__ $$0(orcid)0000-0003-1205-1756$$aGargallo Valero, P.$$uUniversidad de Zaragoza
000117240 700__ $$0(orcid)0000-0002-5037-6976$$aMoreno-Jiménez, J. M.$$uUniversidad de Zaragoza
000117240 700__ $$0(orcid)0000-0002-5788-6661$$aSalvador Figueras, M.$$uUniversidad de Zaragoza
000117240 7102_ $$14014$$2623$$aUniversidad de Zaragoza$$bDpto. Economía Aplicada$$cÁrea Métodos Cuant.Econ.Empres
000117240 773__ $$g10, 3 (2022), 519 [20 pp]$$pMathematics (Basel)$$tMathematics$$x2227-7390
000117240 8564_ $$s6791547$$uhttps://zaguan.unizar.es/record/117240/files/texto_completo.pdf$$yVersión publicada
000117240 8564_ $$s2748760$$uhttps://zaguan.unizar.es/record/117240/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000117240 909CO $$ooai:zaguan.unizar.es:117240$$particulos$$pdriver
000117240 951__ $$a2024-03-18-13:33:30
000117240 980__ $$aARTICLE