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Lundy, M., Siraj, S., & Greco, S. (2017). The mathematical equivalence of the spanning tree and row geometric mean preference vectors and its implications for preference analysis. European Journal of Operational Research, 257(1), 197–208. Added by: Klaus D. Goepel (06 Jun 2019 06:18:14 Asia/Singapore) Last edited by: Klaus D. Goepel (08 Jun 2019 05:35:41 Asia/Singapore) |
| Resource type: Journal Article DOI: 10.1016/j.ejor.2016.07.042 BibTeX citation key: Lundy2017 Email resource to friend View all bibliographic details  |
Categories: AHP/ANP Keywords: decision analysis, geometric mean method, graph theory, pairwise comparisons, spanning trees Creators: Greco, Lundy, Siraj Collection: European Journal of Operational Research |
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| Abstract |
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Pairwise comparison is a widely used approach to elicit comparative judgements from a decision maker (DM), and there are a number of methods that can be used to then subsequently derive a consistent preference vector from the DM's judgements. While the most widely used method is the eigenvector method, the row geometric mean approach has gained popularity due to its mathematical properties and its ease of implementation. In this paper, we discuss a spanning tree method and prove the mathematical equivalence of its preference vector to that of the row geometric mean approach. This is an important nding due to the fact that it identi es an approach for generating a preference vector which has the mathematical properties of the row geometric mean preference vector, and yet, in its entirety, the spanning tree method has more to offer than the row geometric mean method, in that, it is inherently applicable to incomplete sets of pairwise comparison judgements, and also facilitates the use of statistical and visual techniques to gain insights into inconsistency in the DM's judgements.
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