Comparing Cardinal and Ordinal Ranking in MCDM Methods

Danielson, M. & Ekenberg, L. ORCID: (2022). Comparing Cardinal and Ordinal Ranking in MCDM Methods. In: Multicriteria and Optimization Models for Risk, Reliability, and Maintenance Decision Analysis. Eds. de Almeida, A.T., Ekenberg, L. ORCID:, Scarf, P., Zio, E., & Zuo, M.J., pp. 29-40 Springer. ISBN 978-3-030-89647-8 10.1007/978-3-030-89647-8_2.

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There are several MCDM methods attempting to elicit criteria weights, ranging from direct rating and point allocation methods to more elaborated ones. To facilitate the weight elicitation, some of the approaches utilize elicitation methods whereby prospects are ranked using ordinal importance information, while others use cardinal information. Methods are sometimes assessed in case studies, or more formally by utilizing systematic simulations. Furthermore, the treatment of corresponding methods for the handling of the alternative’s values has sometimes been neglected. There is a wish for methods with as little cognitive demand as possible, lowering the hurdle to employ such methods at all. In this paper, we explore simplified models mixing cardinal and ordinal statements and demonstrate which of them are more efficient than established methods. It turns out that weights are much more insensitive to cardinality than values, which has implications for all ranking methods.

Item Type: Book Section
Uncontrolled Keywords: CAR method; Multi-criteria decision analysis; Simplifying rank order; Surrogate criteria weights
Research Programs: Advancing Systems Analysis (ASA)
Advancing Systems Analysis (ASA) > Cooperation and Transformative Governance (CAT)
Depositing User: Luke Kirwan
Date Deposited: 14 Jul 2022 06:50
Last Modified: 14 Jul 2022 06:50

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