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Language: enSubject: Data envelopment analysis (DEA)

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    Article
    Citation - WoS: 76
    Citation - Scopus: 73
    Measuring the Efficiency of Hospitals: a Fully-Ranking Dea-Fahp Approach
    (Springer, 2019) Rouyendegh, Babak Daneshvar; Oztekin, Asil; Ekong, Joseph; Dag, Ali
    The goal of this study is to present a DEA-based fuzzy multi-criteria decision making model for firms in the health care industry in order to enhance their business performance. The study demonstrates a real-life use of the proposed model, mainly designed for hospitals. Data envelopment analysis enhanced with fuzzy analytic hierarchy process are collectively utilized to quantify the data and structure the model in decision-making. The juxtaposition of the two methods is used to compile a ranked list of multiple proxies containing diverse input and output variables which occur in two stages. This hybrid model provides several benefits, one of which is the ability to make the most appropriate decision considering the value of the weights determined by the data from the hybrid model.
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    Article
    Citation - Scopus: 9
    Selecting the High - Performing Departments Within Universities Applying the Fuzzy Madm Methods
    (2011) Rouyendegh,B.D.
    In this study, the process of efficiency measurement is tackled using multi-attribute decision-making (MADM) processes where a sequential algorithm is proposed. The framework of the study is based on two main stages; first, the data envelopment analysis (DEA), separately formulating each pair of units, formulates the department evaluation problem. DEA is a nonparametric multiple criteria method; no production, cost, or profit function is estimated from the data. In the second stage, the pair-wise evaluation matrix generated in the first stage is utilized to fully rank-scale the units via the fuzzy analytical hierarchical process (FAHP). The FAHP method adopted here uses triangular fuzzy numbers (TFN). Inability of AHP to deal with the impression and subjectiveness in the pair-wise comparison process has been improved in Fuzzy AHP. Instead of a crisp value, Fuzzy AHP a range of value to incorporate the decision maker's uncertainly. ©2011 Academic Journals.