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	AHP-BOCR	Processo Gerarchico Analitico	Metodo Best-Worst	Teoria dell'Utilità Multi-Attributo
Campo	Processo decisionale	Processo decisionale	Processo decisionale	Processo decisionale
Famiglia	MCDM	MCDM	MCDM	MCDM
Anno di origine	2008	1980	2015	1976
Ideatore	Thomas L. Saaty (AHP); BOCR framework development extended AHP	Saaty, T. L.	Rezaei, J.	Keeney, R. L., Raiffa, H.
Tipo	Hierarchical pairwise comparison with strategic perspective	Pairwise comparison (eigenvalue)	Pairwise comparison (best-to-others + others-to-worst vectors), LP	Additive multi-attribute utility function
Fonte seminale	Saaty, T. L. (2008). Decision making with the analytic hierarchy process. International Journal of Services Sciences, 1(1), 83-98.	Saaty, T. L. (1980). The Analytic Hierarchy Process: Planning, Priority Setting, Resource Allocation. McGraw-Hill, New York ISBN: 978-0070543713	Rezaei, J. (2015). Best-worst multi-criteria decision-making method. Omega	Keeney, R. L., Raiffa, H. (1976). Decisions with Multiple Objectives: Preferences and Value Trade-offs. Wiley ISBN: 978-0-521-43883-4
Alias	AHP-BOCR, Strategic Criteria AHP	—	—	—
Correlati	5	8	8	8
Sintesi	AHP-BOCR is an extension of the Analytic Hierarchy Process that incorporates strategic perspectives through the BOCR framework: Benefits, Opportunities, Costs, and Risks. Instead of optimizing a single objective, AHP-BOCR decomposes decisions into four strategic dimensions and uses a formula (Benefits × Opportunities) / (Costs × Risks) to synthesize a strategic priority. This approach is particularly suited to long-term, complex decisions with multiple stakeholder perspectives.	AHP (Analytic Hierarchy Process) is a weight subjective multi-criteria decision-making (MCDM) method introduced by Saaty, T. L. in 1980. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.	BWM (Best-Worst Method) is a weight subjective multi-criteria decision-making (MCDM) method introduced by Rezaei, J. in 2015. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.	MAUT (Multi-Attribute Utility Theory) is a ranking multi-criteria decision-making (MCDM) method introduced by Keeney, R. L., Raiffa, H. in 1976. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.