Assessment of Multi-Criteria Preference Measurement Methods for a Dynamic Environment

AbstractMulti-criteria decision analysis is required in various domains where decision making reoccurs as part of a longer-term process. When the decision context changes or the preferences evolve due to process dynamics, one-shot preference measurement is not sufficient to build an adequate basis for decision making. Process dynamics require taking into account the dimension of time. We investigate six interactive preference measurement methods providing the possibility to assess alternatives in terms of utility for an individual decision maker, whether they are suitable for dynamic preference adjustment. We use a mixed-methods approach to analyse them towards 1) requirements for a dynamic method, and 2) their efficiency, validity, and complexity. Our results show that the best method to be further developed for dynamic context is Adaptive Self-Explication slightly preferable over Pre-Sorted Self-Explication. Our assessment implicates that an extension of the Adaptive Self-Explication will enable efficient dynamic decision support.


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