Marketing has a tradition in conducting scientific research with cutting-edge techniques developed in management science, such as data envelopment analysis (DEA) (Charnes et al. 1985). Two decades ago, Kamakura, Ratchford, and Agrawal (1988) applied DEA to examine market efficiency and consumer welfare loss. In this review of three new books, my purpose is (1) to provide a background of DEA for...

The data envelopment analysis (DEA) is an optimization based technique that has been proposed by Charnes, Cooper and Rhodes (1978) to measure the relative efficiency of public sector activities and no profit organizations, such as for example educational institutions and health services. The DEA efficiency measure is computed by solving a fractional linear programming model that can be converte...

Risk early-warning of natural disasters is a very intricate non-deterministic prediction, and it was difficult to resolve the conflicts and incompatibility of the risk structure. Risk early-warning factors of natural disasters were differentiated into essential attributes and external characters, and its workflow mode was established on risk early-warning structure with integrated Entropy and D...

Data Envelopment Analysis (DEA) is a linear programming methodology for measuring the efficiency of Decision Making Units (DMUs) to improve organizational performance in private and public sectors. However, if new DMU needs be known its score, DEA analysis would have re-conducted, especially nowadays, datasets from many fields been growing rapidly real world, which will need huge amount computa...

Benchmarking of container terminals is an important issue facing port management. Data envelopment analysis (DEA), which is a multi-factor productivity measurement tool is generally used in assessing the relative efficiency of homogenous units and setting benchmark for inefficient units. Evaluation of container terminals by DEA produces limited set of efficient units which are reference to inef...

Data Envelopment Analysis (DEA) is a widely used mathematical programming technique for comparing the inputs and outputs of a set of homogenous Decision Making Units (DMUs) by evaluating their relative efficiency. The conventional DEA methods assume deterministic and precise values for the input and output observations. However, the observed values of the input and output data in real-world pro...

Abstract Data Envelopment Analysis (DEA) is a method for measuring efficiencies of Decision Making Units (DMUs). While it has been widely used in many industrial and economic applications, for large DMUs with many inputs and outputs, DEA would require huge computer resources in terms of memory and CPU time. Several studies have attempted to overcome this problem for large datasets. However, the...

Thermo-responsive polymer "nanogels" (crosslinked hydrogel particles with sub-100 nm diameters) are intriguing for many potential applications in biotechnology and medicine. There have been relatively few reports of electrostatically neutral, thermosensitive nanogels comprising a high fraction of hydrophilic co-monomer. Here we demonstrate the syntheses and characterization of novel, non-ionic ...

There is a growing body of evidence on the role of nitric oxide (NO) in retinal physiology. Recently, interest has developed in the functional role of an alternative redox form of NO, namely nitroxyl (HNO/NO(-)), because it is formed by a number of diverse biochemical reactions. The aim of the present report was to comparatively analyze the effect of HNO and NO on the retinal nitridergic pathwa...

Bladder cancer (BC) is a common malignancy of the urinary tract that has a higher frequency in men than in women. Cytostatic resistance and metastasis formation are significant risk factors in BC therapy; therefore, there is great interest in overcoming drug resistance and in initiating research for novel chemotherapeutic approaches. Here, we suggest that desethylamiodarone (DEA)-a metabolite o...