Improvement in Weighting Assignment Process in Analytic Hierarchy Process by Introducing Suggestion Matrix and Likert Scale

Abstract

Analytic Hierarchy Process (AHP) has been widely used in varieties of decision making processes among several alternatives, where data on pair-wise comparisons are aggregated and the degree of importance of each alternative is quantified. The process of assigning importance or priorities against the alternatives has inherent limitations, which lead to higher possibility of inconsistency. This paper focuses on two basic limitations of the AHP, first one is its inconsistency generated from huge comparisons in judgment matrix and the second one is the use of ‘ranking weightages’ given by AHP. To eliminate these limitations, this research paper recommends to calculate relative importance among alternatives from the ratings assigned from “Likert scale” to form a “suggestion matrix” with zero percent CR before judgment matrix which gives privilege to decision makers to change relative importance within the range of CR.  This process intensifies the effectiveness of AHP by reducing time consumption through optimizing inconsistency.