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DEA. In this study, we provide a taxonomy and review of the fuzzy DEA methods. We present a classification scheme with … possibility approach. We discuss each classification scheme and group the fuzzy DEA papers published in the literature over the …
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An important property of production functions is the concept return to scale (RTS) as found in the literature. There are two common variations RTS in data envelopment analysis (DEA) used, constant return to scale (CRS) and variation return to scale (VRS). The envelopment surface in BCC model is...
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Analysis of strengths, weaknesses, opportunities and threats (SWOT) is a method to formulate the strategy. Although the SWOT analysis successfully provides the key factors of the problem, it has some drawbacks in selecting appropriate strategy for the evaluation and final decision steps. During...
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Performance evaluation in conventional data envelopment analysis (DEA) requires crisp numerical values. However, the observed values of the input and output data in real-world problems are often imprecise or vague. These imprecise and vague data can be represented by linguistic terms...
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Many real-world decision problems involve conflicting systems of criteria, uncertainty and imprecise information. Some also involve a group of decision makers (DMs) where a reduction of different individual preferences on a given set to a single collective preference is required. Multi-criteria...
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Data envelopment analysis (DEA) is a methodology for measuring the relative efficiencies of a set of decision making units (DMUs) that use multiple inputs to produce multiple outputs. The standard DEA models assume that all inputs and outputs are crisp and can be changed at the discretion of...
Persistent link: https://www.econbiz.de/10013114996