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How to support the application of multiple criteria decision analysis? Let us start with a comprehensive taxonomy
Citation:
Cinelli, M., M. Kadziński, M. Gonzalez, AND R. Słowiński. How to support the application of multiple criteria decision analysis? Let us start with a comprehensive taxonomy. ACS Omega. American Chemical Society, Washington, DC, 96:102261, (2020). https://doi.org/10.1016/j.omega.2020.102261
Impact/Purpose:
The taxonomy of the Multiple Criteria Decision Analysis (MCDA) process characteristics presented in this product is a first stage of a harmonization phase for MCDA consisting of a structured and comprehensive representation and definition of the components that should be considered when leading multiple criteria-based decision aiding. It has the potentials of shaping the way decision making is conducted and it allows analysts, as well as the DMs/stakeholders, to not be at risk of being overwhelmed by the entity of the task. The proposed taxonomy can be used to support the development of future Decision Support Systems (DSSs) for MCDA method(s) recommendation. Its added value resides in the comprehensiveness as well as modularity of the characteristics. Furthermore, this product also proposes a clustering of DSSs for MCDA method(s) recommendation and it can be a starting point for a traceable and categorizable development of systems that can help analysts during their decision support activities.
Description:
Decision making is a complex task that involves a multitude of perspectives, constraints, and variables. Multiple Criteria Decision Analysis (MCDA) is a process that has been used for several decades to support decision making. It includes a series of steps that systematically help Decision Maker(s) (DM(s)) and stakeholders in structuring a decision making problem, identifying their preferences, and building a decision recommendation consistent with those preferences. Over the last decades, many studies have demonstrated the conduct of the MCDA process and how to select an MCDA method. Until now, there has not been a review of these studies, nor a proposal of a unified and comprehensive high-level representation of the MCDA process characteristics (i.e., features), which is the goal of this paper. We introduce a review of the research that defines how to conduct the MCDA process, compares MCDA methods, and presents Decision Support Systems (DSSs) to recommend a relevant MCDA method or a subset of methods. We then synthesize this research into a taxonomy of characteristics of the MCDA process, grouped into three main phases, (i) problem formulation, (ii) construction of the decision recommendation, and (iii) qualitative features and technical support. Each of these phases includes a subset of the 10 characteristics that helps the analyst implementing the MCDA process, while also being aware of the implication of these choices at each step.
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DOI: How to support the application of multiple criteria decision analysis? Let us start with a comprehensive taxonomy
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