A Fuzzy Multi-Attribute Decision Making Model for Strategic Risk Assessment


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Arikan R., Dagdeviren M., KURT M.

INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS, vol.6, no.3, pp.487-502, 2013 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 6 Issue: 3
  • Publication Date: 2013
  • Doi Number: 10.1080/18756891.2013.781334
  • Journal Name: INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.487-502
  • Keywords: Risk assessment, multi attribute decision making, fuzzy analytic hierarchy process, fuzzy logarithmic least squares method, LOGARITHMIC LEAST-SQUARES, EXTENT ANALYSIS METHOD, SIMILARITY MEASURES, HIERARCHICAL ANALYSIS, RANKING, AHP, UNCERTAINTY, MANAGEMENT, SELECTION, INTERVAL
  • Gazi University Affiliated: Yes

Abstract

Risk assessment is a very important issue for an effective institution, since the lack of accurate risk assessment method or the improper risk management might cause problems to achieve institutions' strategic objectives. There are a finite number of risks which have to be ranked considering many different and conflicting criteria. In this respect, assessing risks by relating to strategic objectives is a multi-attribute decision making problem. In this study, an integrated approach which employs analytic hierarchy process (AHP) and fuzzy logarithmic least squares method (LLSM) together is proposed for the strategic risk assessment problem. The AHP is used to analyze the structure of the risk assessment problem and to determine weights of the criteria, and fuzzy LLSM method is used to obtain final ranking. Proposed approach is applied to a problem of prioritizing risks in a public institution.