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Publication Metadata only A Fuzzy Risk Assessment Model for Hospital Information System Implementation(Pergamon-Elsevier Science Ltd, The Boulevard, Langford Lane, Kidlington, Oxford Ox5 1Gb, England, 2012-01) Özok, Ahmet Fahri; Yücel, Gülçin; Hoege, B.; Çebi, Selçuk; 207507; 202323; 24803There is research which reveals negative effects of IT applications in the healthcare sector on both patients and staff. Therefore, methods are necessary to predict the risk of new healthcare information technology in order to reduce the unintended results of new applications. A new predictive risk assessment model for a hospital information system (HIS) has been developed in this paper to estimate risk before the implementation of new HIS. The methodology consists of analytic network process (ANP), reality-design gap evaluation and fuzzy inference system. An application of the proposed algorithm has been applied for a research and education hospital in Istanbul, Turkey. Risk magnitude of a new HIS implementation for the hospital is found as major with a belief of 100%. The relative importances of risk factors for HIS implementation success are obtained. The most effective factors on the HIS implementation are found as technological factors; usefulness, compatibility, user involvement and ease of use. These factors are followed by organizational factors; training and organizational commitment. The most important individual factor is also found as user's previous HIS experience. A risk assessment model has been proposed in this paper. The model processes experts' evaluations defined in linguistic forms when there is no sufficient data and it integrates possible risk factors into the decision-making process of risk assessment. In the model, a reality-design gap analysis is used to determine risk likelihood instead of directly risk evaluation. (C) 2011 Elsevier Ltd. All rights reserved.Publication Metadata only A Hybrid Approach To Concept Selection Through Fuzzy Analytic Network Process(Pergamon-Elsevier Science Ltd, The Boulevard, Langford Lane, Kidlington, Oxford Ox5 1Gb, England, 2009-02) Ayağ, Zeki; Özdemir, Rifat Gürcan; TR8785; TR141173Evaluating conceptual design alternatives in a new product development (NPD) environment has been one of the most critical issues for many companies which try to survive in the fast-growing world markets. Therefore, most companies have used various methods to successfully carry out this difficult and time-consuming evaluation process. Of these methods, analytic hierarchy process (AHP) has been widely used in multiple-criteria decision-making (MCDM) problems. But, in this study, we used analytical network process (ANP), a more general form of AHP, instead of AHP due to the fact that AHP cannot accommodate the variety of interactions, dependencies and feedback between higher and lower level elements. Furthermore, in some cases, due to the vagueness and uncertainty on the judgments of a decision-maker, the crisp pairwise comparison in the conventional ANP is insufficient and imprecise to capture the right judgments of the decision-maker. Therefore, a fuzzy logic is introduced in the pairwise comparison of ANP to make up for this deficiency in the conventional ANP, and is called as fuzzy ANP. In short, in this paper, a fuzzy ANP-based approach is proposed to evaluate a set of conceptual design alternatives developed in a NPD environment in order to reach to the best one satisfying both the needs and expectations of customers, and the engineering specifications of company. In addition, a numerical example is presented to illustrate the proposed approach. (C) 2008 Elsevier Ltd. All rights reserved.Publication Metadata only An analytic network process-based approach to concept evaluation in a new product development environment(TAYLOR & FRANCIS LTD, 4 PARK SQUARE, MILTON PARK, ABINGDON OX14 4RN, OXON, ENGLAND, 2007-06) Özdemir, Rifat Gürcan; Ayağ, Zeki; TR141173; TR8785Selecting the best product concept is one of the most critical tasks in a new product development (NPD) environment. Making decisions at this stage becomes very difficult due to imprecise and uncertain product requirements. So, the evaluation process of determining the most satisfying conceptual design has been a very vital issue for companies to survive in fast-growing markets for a long time. Therefore, most companies have used various methods to successfully carry out this difficult and time-consuming process. Of these methods, an analytic hierarchy process (AHP) has been widely used in multiple-criteria decision-making problems (i.e. concept selection, equipment evaluation). In this study, however, we use an analytic network process (ANP), a more general form of AHP, due to the fact that AHP cannot accommodate the variety of interactions, dependencies and feedback between higher and lower level elements. Briefly, in this paper, an ANP-based approach is presented to evaluate a set of conceptual design alternatives in order to reach to the best concept satisfying the needs and expectations of both customers and company. In addition, a numerical example is presented to illustrate the proposed approach.Publication Metadata only Evaluating Machine Tool Alternatives Through Modified TOPSIS And Alpha-Cut Based Fuzzy ANP(Elsevier Science Bv, Po Box 211, 1000 Ae Amsterdam, Netherlands, 2012-12) Ayağ, Zeki; Özdemir, Rifat Gürcan; TR8785; TR141173The problem of machine tool selection among available alternatives has been critical issue for most companies in fast-growing markets for a long time. In the presence of many alternatives and selection criteria, the problem becomes a multiple-criteria decision making (MCDM) machine tool selection problem. Therefore, most companies have utilized various methods to successfully carry out this difficult and time-consuming process. In this work, both of the most used MCDM methods, the modified TOPSIS and the Analytical Network Process (ANP) are introduced to present a performance analysis on machine tool selection problem. The ANP method is used to determine the relative weights of a set of the evaluation criteria, as the modified TOPSIS method is utilized to rank competing machine tool alternatives in terms of their overall performance. Furthermore, in this paper, we use a fuzzy extension of ANP, a more general form of AHP, which uses uncertain human preferences as input information in the decision-making process, because 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 AHP, only employed in the prioritization stage of ANP, a fuzzy logic method providing more accuracy on judgments is applied. The resulting fuzzy ANP enhances the potential of the conventional ANP for dealing with imprecise and uncertain human comparison judgments. The proposed approach is also applied for a real-life case in a company. (C) 2012 Elsevier B.V. All rights reserved.