Probabilistic Group Decision-Making Using BWT

Majid Mohammadi, Fuqi Liang (), Matteo Brunelli and Jafar Rezaei
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Majid Mohammadi: Vrije Universiteit Amsterdam
Fuqi Liang: Zhejiang University
Matteo Brunelli: University of Trento
Jafar Rezaei: Delft University of Technology

Chapter Chapter 1 in Advances in Best-Worst Method, 2023, pp 1-13 from Springer

Abstract: Abstract In this study, we propose a probabilistic group decision-making method based on the Best-Worst Tradeoff method (BWT) and the Bayesian approach. BWT is a pairwise comparison method that is used to elicit the tradeoffs among a set of attributes (criteria) in a multi-criteria decision-making problem. While BWT is suitable for a single decision-maker situation, Bayesian BWT is suitable for aggregating the tradeoffs among a number of criteria coming from a number of decision-makers or experts. The proposed method aggregates the scaling constants (weights), and assigns a confidence number (between zero and one), to inform about the confidence we have about the ranking order of the criteria. We demonstrate how the method is used in a real-world setting. Data is collected from three experts on ranking a number of European seaports that are performing differently with respect to a number of relevant criteria. We think that the method has great potential in real-world group decision-making problems.

Keywords: Best-Worst method; Best-Worst Tradeoff; Tradeoff procedure; Multi-attribute Value Theory (MAVT); Bayesian; Group decision-making (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:spr:lnopch:978-3-031-40328-6_1

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DOI: 10.1007/978-3-031-40328-6_1

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