نتایج جستجو برای: discretionary inputs and undesirable outputs
تعداد نتایج: 16831608 فیلتر نتایج به سال:
data envelopment analysis (dea) is a non-parametric approach for performance analysis of decision making units (dmus) which uses a set of inputs to produce a set of outputs without the need to consider internal operations of each unit. in recent years, there have been various studies dealt with two-stage production systems, i.e. systems which consume some inputs in their first stage to produce ...
data envelopment analysis (dea) is a method for measuring the efficiency of peer decision making units (dmus) which uses a set of inputs to produce a set of outputs. in some cases, dmus have a two-stage structure, in which the first stage utilizes inputs to produce outputs used as the inputs of the second stage to produce final outputs. one important issue in two-stage dea is the sensitivity of...
In the real world applications, there are some situations where inputs and outputs are time-dependent and are affected during the production periods. Capital stock can be seen as an effective instance in such occasions. In order to handling long-time planning, dynamic structure was proposed in efficiency evaluation. In this framework, there are some of the inputs and outputs change proportiona...
Traditional DEA models do not deal with imprecise data and assume that the data for all inputs and outputs are known exactly. Inverse DEA models can be used to estimate inputs for a DMU when some or all outputs and efficiency level of this DMU are increased or preserved. this paper studies the inverse DEA for fuzzy data. This paper proposes generalized inverse DEA in fuzzy data envelopment anal...
Different from traditional efficiency research and previous studies considering undesirable outputs, this paper proposes models which distinguish weak and strong disposability features among various undesirable outputs based on the technical nature of the undesirable outputs. The paper illustrates the approach using a research sample covering 582 base-load Chinese coal-fired power plants in 200...
Data envelopment analysis (DEA) is a method to measure relative efficiency of a set of decision-making units (DMUs) which uses multiple inputs and produces multiple outputs. In the conventional DEA, crisp inputs and outputs are fundamentally necessary. But the observed values of inputs and outputs in real-world problems are sometimes imprecise. Thus, performance measurement often needs to be do...
F€are and Grosskopf (2004) address the approach of Seiford and Zhu (2002) where undesirable input and output measures are treated in data envelopment analysis (DEA). One key feature of Seiford and Zhu s (2002) approach is that the bad outputs are treated as outputs in DEA model but are reduced when DEA efficiency is evaluated. F€are and Grosskopf (2004) suggest an alternative approach in treati...
Traditional data envelopment analysis (DEA) models deal with measurement of relative efficiency of decision making units (DMUs) in which multiple-inputs consumed to produce multiple-outputs. One of the drawbacks of these models is neglecting internal processes of each system, which may have intermediate products and/or independent inputs and/or outputs. In this paper some methods which are usab...
نمودار تعداد نتایج جستجو در هر سال
با کلیک روی نمودار نتایج را به سال انتشار فیلتر کنید