3064. Comprehensive review of SMAA descriptive measures
Invited abstract in session WA-8: Decision aiding under uncertainty 1, stream Multiple Criteria Decision Aiding.
Wednesday, 8:30-10:00Room: Clarendon SR 2.08
Authors (first author is the speaker)
| 1. | Sarah Ben Amor
|
| Telfer School of Management, University of Ottawa | |
| 2. | Betania Campello
|
| UNICAMP | |
| 3. | Renata Pelissari
|
| Engineering School, Mackenzie Presbyterian University | |
| 4. | Bianca Santos Serafim
|
| School of Applied Sciences, University of Campinas (UNICAMP) | |
| 5. | Yan Xu
|
| School of Management, Northwestern Polytechnical University |
Abstract
Stochastic Multi-criteria Acceptability Analysis (SMAA) is a family of methods that enables decision analysis under uncertainty without requiring precise framework. The SMAA framework includes various descriptive measures that support decision-making in such contexts. This study provides a comprehensive review of these measures by extending previous literature reviews, which covered studies up to 2018, with an updated analysis of newly published research. Our systematic search identified 74 articles published in international journals. Each paper was reviewed to extract new descriptive measures proposed within SMAA-based methodologies. Through this process, we compiled a set of key measures, including among others the traditional ones rank acceptability indices, confidence factors, central weight vectors, and pairwise winning indices. Based on this set, we conducted a detailed study to examine their theoretical foundations, practical applications, and the challenges involved in their implementation and interpretation. Furthermore, we provide comparative insights into their suitability for different decision-making contexts. By updating the literature and offering a structured classification of SMAA descriptive measures, this work enhances the understanding of SMAA-based methodologies and supports their application in multi-criteria decision-making (MCDM).
Keywords
- Decision Analysis
- Multi-Objective Decision Making
- Decision Support Systems
Status: accepted
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