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How to compromise on the best price? A group tacit knowledge-based multicriteria approach

Arduin, Pierre-Emmanuel; Mayag, Brice; Negre, Elsa; Rosenthal-Sabroux, Camille (2014), How to compromise on the best price? A group tacit knowledge-based multicriteria approach, Journal of Decision Systems, 23, 1, p. 99-112. 10.1080/12460125.2014.863592

Type
Article accepté pour publication ou publié
Date
2014
Journal name
Journal of Decision Systems
Volume
23
Number
1
Publisher
Taylor & Francis
Pages
99-112
Publication identifier
Metadata
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Author(s)
Arduin, Pierre-Emmanuel
Dauphine Recherches en Management [DRM]
Mayag, Brice
Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
Negre, Elsa
Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
Rosenthal-Sabroux, Camille
Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
Abstract (EN)
Tacit knowledge plays an important role in decision-making. That is why, in this paper, we propose a group tacit knowledge-based multicriteria approach for decision processes. This approach is based on a practical case study in the field of second-hand vehicle purchase. This paper proposes ideas and research issues on how to tackle tacit knowledge in group decision processes with cost-benefit and multicriteria decision analysis. Because tacit knowledge cannot always be explained, we use the multicriteria decision analysis to fittingly explain tacit knowledge which can be explained. In order to respect the financial policy of the company that purchases/sells second-hand vehicles, we continue using the cost-benefit analysis already implemented. The goal is to help the buyer and the seller to compromise on the best price.
Subjects / Keywords
Tacit knowledge; Decision process; Cost-benefit analysis; Multi-criteria decision analysis; Group decision
JEL
C44 - Operations Research; Statistical Decision Theory
D70 - General
D83 - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness