An intelligent approach to ERP software selection through fuzzy ANP
Özdemir, Rifat Gürcan
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During the implementations of enterprise resource planning (ERP) systems, most companies have experienced some problems, one of which is how to determine the best ERP software satisfying their needs and expectations. Because improperly selected ERP software may have an impact on the time required, and the costs and market share of a company, selecting the best desirable ERP software has been the most critical problem for a long time. On the other hand, selecting ERP software is a multiple-criteria decision-making (MCDM) problem, and in the literature, many methods have been introduced to evaluate this kind of problem, one of which is the analytic hierarchy process (AHP), which has been widely used in MCDM selection problems. However, in this paper, we use a fuzzy extension of an analytic network process (ANP), a more general form of AHP, which uses uncertain human preferences as input information in the decision-making process, because the AHP cannot accommodate the variety of interactions, dependencies, and feedback between higher- and lower-level elements. Instead of using the classical eigenvector prioritization method in the AHP, only employed in the prioritization stage of ANP, a fuzzy-logic method providing more accuracy on judgements is applied. The resulting fuzzy ANP enhances the potential of the conventional ANP for dealing with imprecise and uncertain human comparison judgements. In short, in this paper, an intelligent approach to ERP software selection through a fuzzy ANP is proposed by taking into consideration quantitative and qualitative elements to evaluate ERP software alternatives.