in this paper it has been tried to present a model by usingsome changes in the classical dea models and combining these modelswith fuzzy models to eliminate these weaknesses. inputs and outputs arerecognized by using mcdm and ahp techniques and experts views. inthe next step, the gathered data is compounded by fuzzy techniques andentered in the special dea model after changing to the crisp amou...

This article analyzes the interactions through which primary-care nurses and patients accomplish patient weighing. The analysis is based on videotaped nurse-adult patient interactions in clinics in the area of Southern California. Detailed examination of co-participants' naturally situated weighing conduct shows that parties recurrently deliver utterances that go beyond that required to accompl...

‎‎in the data envelopment analysis (dea) the efficiency of the units‎ ‎can be obtained by identifying the degree of the importance of the‎ ‎criteria (inputs-outputs).in dea basic models‎, ‎challenges are zero‎ ‎and unequal weights of the criteria when decision‎- ‎making units are‎ ‎evaluated‎. ‎one of the strategies applied to deal with these problems‎ ‎is using common weights of the each input...

The highest efficiency score 1 (100% efficiency) is regarded as a common benchmark for Decision Making Units (DMUs). This brings about the existence of more than one DMU with the highest score. Such a case normally occurs in all Data Envelopment Analysis (DEA) models and also in all the Common Set of Weights (CSWs) methods and it may lead to the lack of thorough ranking of DMUs. And ideal DMU b...

Conventional data envelopment analysis (DEA) assists decision makers in distinguishing between efficient and inefficient decisionmaking units (DMUs) in a homogeneous group. However, DEA does not provide more information about the efficient DMUs. This research proposes a methodology to determine one common set of weights for the performance indices of only DEA efficient DMUs. Then, these DMUs ar...

One may employ Data Envelopment Analysis (DEA) to discriminate decision-making units (DMUs) into efficient and inefficient ones base upon the multiple inputs and output performance indices. In this paper we consider that there is a centralized decision maker (DM) who ‘owns’ or ‘supervises’ all the DMUs. In such intraorganizational scenario the DM has an interest in discriminating the efficient ...