Generalised framework for multi-criteria method selection
This provides a practical tool for decision-makers in various fields to improve recommendation quality, though it is incremental as it builds on existing MCDA methods.
The paper tackles the problem of inconsistent results from improper selection of Multi-Criteria Decision Analysis (MCDA) methods by proposing a framework for selecting suitable methods based on analyzing 56 methods and modeling uncertainty, with practical studies showing consistency with expert recommendations and usability even with data gaps.
Multi-Criteria Decision Analysis (MCDA) methods are widely used in various fields and disciplines. While most of the research has been focused on the development and improvement of new MCDA methods, relatively limited attention has been paid to their appropriate selection for the given decision problem. Their improper application decreases the quality of recommendations, as different MCDA methods deliver inconsistent results. The current paper presents a methodological and practical framework for selecting suitable MCDA methods for a particular decision situation. A set of 56 available MCDA methods was analyzed and, based on that, a hierarchical set of methods characteristics and the rule base were obtained. This analysis, rules and modelling of the uncertainty in the decision problem description allowed to build a framework supporting the selection of a MCDA method for a given decision-making situation. The practical studies indicate consistency between the methods recommended with the proposed approach and those used by the experts in reference cases. The results of the research also showed that the proposed approach can be used as a general framework for selecting an appropriate MCDA method for a given area of decision support, even in cases of data gaps in the decision-making problem description. The proposed framework was implemented within a web platform available for public use at www.mcda.it.