Conflict resolution in the era of cognitive multicriteria decision-making: an AHP-retributive approach

Vargas, L.G. ; Moreno-Loscertales, C. (Universidad de Zaragoza) ; Moreno-Jiménez, J.M. (Universidad de Zaragoza)

Resumen: This paper puts forth the foundation for a different type of negotiation that reflects in a more realistic way the behavior of human beings when making complex decisions, aligned with the cognitive process involved. The positive and the negative aspects of decisions reflect two components in the human brain: the nucleus accumbens and the amygdala. The first component deals with behavior related to rewards or potential gains, and the other with behavior related to risk aversion or potential losses. Negotiations require communication, learning, accommodation of positions, and development of alternatives and modification of constraints. Negotiation support systems help and advice negotiators; structure and analyze the problem; elicit preferences to construct a preference function; visualize different aspects of the problem and the process; and facilitate communication and learning. The methodology used is based on the Analytic Hierarchy Process previously employed in a retributive conflict in which each party calculates the incremental benefits it gets and the costs to its opponent. The Israeli–Palestinian conflict is used to show the viability of the approach and the type of inputs we need to study conflicts with this approach. The negotiation platform that we describe here help the actors to start and engage a negotiation from noncooperative parties. It can also be used in human– negotiations to expedite reaching an agreement if one exists. However, we are not seeking automated negotiations. Advantages and risks of Artificial Intelligence contribution in negotiation support systems for cognitive and retributive conflict resolution based on AHP (CRCR-AHP) are also discussed.

Idioma: Inglés

DOI: 10.1111/itor.13088

Año: 2023

Publicado en: INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH 30, 3 (2023), 1453-1478
ISSN: 0969-6016

Factor impacto JCR: 3.1 (2023)

Categ. JCR: MANAGEMENT rank: 171 / 407 = 0.42 (2023) - Q2 - T2
Categ. JCR: OPERATIONS RESEARCH & MANAGEMENT SCIENCE rank: 34 / 106 = 0.321 (2023) - Q2 - T1

Factor impacto CITESCORE: 7.8 - Business and International Management (Q1) - Computer Science Applications (Q1) - Strategy and Management (Q1) - Management of Technology and Innovation (Q1) - Management Science and Operations Research (Q1)

Factor impacto SCIMAGO: 1.027 - Business and International Management (Q1) - Computer Science Applications (Q1) - Strategy and Management (Q1) - Management Science and Operations Research (Q1) - Management of Technology and Innovation (Q2)

Tipo y forma: Article (PostPrint)

Área (Departamento): Area Medicina (Dpto. Medicina, Psiqu. y Derm.)
Área (Departamento): Área Métodos Cuant.Econ.Empres (Dpto. Economía Aplicada)