The Analytic Hierarchy and the Network Process in Multicriteria Decision Making: Performance Evaluation and Selecting Key Performance Indicators Based on ANP Model

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Abstract

AHP is a method for ranking decision alternatives and selecting the best one when the decision maker has multiple criteria In evaluation n competing alternatives A 1 , A 2 ,,A n under a given criterion, it is natural to use the framework of pair-wise comparison by n n square matrix from which a set of preference values for the alternatives is derived. Many methods for estimating the preference values from the pair-wise comparison matrix have been proposed and the effectiveness comparatively evaluated. Most of the estimating methods proposed and studied are with the paradigm of the analytic hierarchy process that presumes ratio-scaled preference values. AHP is one of the ways for deciding among the complex criteria structure in different levels. Fuzzy AHP is a synthetic extension of classical AHP method when the fuzziness of the decision maker is considered. ANP is a new theory that extends the Analytic Hierarchy Process (AHP) to case of dependence and feedbacks introduced by Saaty (1980), with book in 1996 revised and extended in 2001. The ANP makes it possible to deal systematically with all kinds of dependence and feedback in decision system ANP allows for complex interrelationships among decision levels and attributes. The ANP feedback approach replaces hierarchies with networks in which the relationship between levels are not easily represented as higher or lower, dominated or being dominated, directly or indirectly (Meade & Sarkis, 1999). For instance, not only does the importance of the criteria determine the importance of the alternatives, as in hierarchy, but the importance of the alternatives may also have an impact on importance of the criteria Therefore, a hierarchical representation with a linear top-to-bottom structure is not suitable for complex system In literature, there exists numerous studies conduct with the aim of performing indicators within the boundaries of objective criteria. Sardana (2009) presents a business performance measurement framework, for organizational design, process management, quality management and recipient satisfaction, and defines an appropriate set of performance

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