By David L. Olson, Desheng Wu

ISBN-10: 3662537842

ISBN-13: 9783662537848

ISBN-10: 3662537850

ISBN-13: 9783662537855

This booklet is a entire consultant to numerous features of hazard, together with info structures, catastrophe administration, offer chain and catastrophe administration views. an important component of this ebook is dedicated to featuring a few operations learn versions which have been (or may be) utilized to company provide threat administration, in particular from the provision chain point of view. each one bankruptcy of this publication can be utilized as a special module on a distinct themes with committed examples, definitions and dialogue notes.

This publication comes at a time while the realm is more and more challenged by means of various varieties of possibility and the way to control them. occasions of the twenty first Century have made firm possibility administration much more severe. dangers corresponding to suspicions surrounding top-management constructions, monetary and know-how bubbles (especially on account that 2008), in addition to the validated threat from terrorism, resembling the 11th of September assault within the U.S. in addition to newer occasions in France, Belgium, and different destinations in Europe, have an important influence on many elements of industrial. companies, in reality, exist to deal with hazard of their zone of specialization.

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Comparison of weights in TOPSIS models. Mathematical and Computer Modelling 40(7–8), 721–727. 54 4 Examples of Supply Chain Decisions Trading Off Criteria 3. , Jain, V. S. (2013). Quantifying risks in a supply chain through integration of fuzzy AHP and fuzzy TOPSIS, International Journal of Production Research 51 (8), 2433–2442. 4. , Kucukvar, M. and Tatari, O. (2016). Application of the TOPSIS and intuitionistic fuzzy set approaches for ranking the life cycle sustainability performance of alternative vehicle technologies.

With twelve criteria, it will be rare that one alternative (of the final set of filtered choices) will dominate another, meaning that it is at least as good or better on all criteria measures, and strictly better on at least one criterion. Each measure can now be assigned a value score on a 0–1 scale, with 0 being the worst performance imaginable, and 1 being the best performance imaginable. This reflects the decision maker’s perception, a subjective value. 3), a possible set of values could be: The SMART method now needs to identify relative weights for the importance of each criterion in the opinion of the decision maker or decision making group.

Jain, V. S. (2013). Quantifying risks in a supply chain through integration of fuzzy AHP and fuzzy TOPSIS, International Journal of Production Research 51 (8), 2433–2442. 4. , Kucukvar, M. and Tatari, O. (2016). Application of the TOPSIS and intuitionistic fuzzy set approaches for ranking the life cycle sustainability performance of alternative vehicle technologies. Sustainable Production and Consumption 6, 12–25. 5. D. M. and Valle, R. (2013). Triple bottom line analysis of oil and gas industry with multicriteria decision making.

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Enterprise Risk Management Models by David L. Olson, Desheng Wu


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