Use of consistency index, expert prioritization and direct numerical inputs for generic fuzzy-AHP modeling: A process model for shipping asset management

► In the recent literature, many studies do not present or check consistency of applied fuzzy-AHP surveys. ► The proposed method improves the conventional fuzzy-AHP method by Centric Consistency Index (CCI) control. ► This paper provides a standard procedure for direct numerical inputs without exper...

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Bibliographic Details
Published in:Expert systems with applications 2012-02, Vol.39 (2), p.1911-1923
Main Authors: Bulut, Emrah, Duru, Okan, Keçeci, Tuba, Yoshida, Shigeru
Format: Article
Language:English
Subjects:
Algorithms
Asset management
Consistency
Consistency index
Consultation
Criteria
Decision support systems
Generic fuzzy-AHP
Markets
Mathematical models
Ship investment
Shipping
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Summary:► In the recent literature, many studies do not present or check consistency of applied fuzzy-AHP surveys. ► The proposed method improves the conventional fuzzy-AHP method by Centric Consistency Index (CCI) control. ► This paper provides a standard procedure for direct numerical inputs without expert consultation. ► When the numerical results are comparable, ranking procedure is useful, time saving and capable of comparing priority. ► This expert prioritization framework is combined with fuzzy-AHP method for ranking the level of experience. The aim of this paper is to develop a generic version of the conventional fuzzy-analytic hierarchy process (FAHP) method and investigate the shipping asset management (SAM) problem in the dry bulk shipping market. The recent literature has various applications of the FAHP, but these studies lack consistency control, use identical decision support rather than weighted expert choices, and lack measurable criteria. The proposed model, generic fuzzy-AHP (here after GF-AHP), provides a standard control of consistency on the decision matrix for the expert group. GF-AHP also improves the capabilities of the FAHP by executing direct numerical inputs without expert consultation. In practical business, some of the criteria can be easily calculated and expert consultation is a redundant process. Therefore, GF-AHP presents how to transform such numerical inputs to a priority scale. Finally, expertise differences on the decision group are reflected in the GF-AHP process by an expert weighting algorithm.
ISSN:0957-4174
1873-6793
DOI:10.1016/j.eswa.2011.08.056