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

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dc.contributor.author Lenz, Annika
dc.contributor.author Schoop, Mareike
dc.date.accessioned 2019-01-02T23:57:05Z
dc.date.available 2019-01-02T23:57:05Z
dc.date.issued 2019-01-08
dc.identifier.isbn 978-0-9981331-2-6
dc.identifier.uri http://hdl.handle.net/10125/59620
dc.description.abstract Multi-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.
dc.format.extent 10 pages
dc.language.iso eng
dc.relation.ispartof Proceedings of the 52nd Hawaii International Conference on System Sciences
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject Multi-criteria Decision Analysis and Support Systems
dc.subject Decision Analytics, Mobile Services, and Service Science
dc.subject dynamic preference adjustment, multi-criteria decision analysis, preference measurement
dc.title Assessment of Multi-Criteria Preference Measurement Methods for a Dynamic Environment
dc.type Conference Paper
dc.type.dcmi Text
dc.identifier.doi 10.24251/HICSS.2019.218
Appears in Collections: Multi-criteria Decision Analysis and Support Systems


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