Titlebook: Quantitative Models for Performance Evaluation and Benchmarking; Data Envelopment Ana Joe Zhu Book 2014Latest edition Springer Internationa

inhumane

Antarctic

Schlemms-Canal

Congestion,n be found in underground mining and agriculture. For example, too much fertilizer applied to a given plot could reduce the overall output. We here adopt the following definition of congestion from Cooper et al. (. 3–45, 1996).

遭遇

Identifying Critical Measures in DEA,the management to know the critical measures. The current chapter introduces the approach of Chen and Zhu (.. (1–4), 225–244, 2003) for identifying the critical measures to DMUs’ performance. Note that once the DEA evaluation is done, the management needs to either (i) maintain the best practice for

簡略

Interval and Ordinal Data in DEA,interval data. For example, some outputs and inputs may be only known as in forms of bounded or interval data, ordinal data, and ratio bounded data. Cook et al. (. 133–140, 1993; . 945–953, 1996) were the first who developed a modified DEA structure where the inputs and outputs are represented as ra

向宇宙

craven

Returns-to-Scale, has been widely studied within the framework of DEA. RTS have typically been defined only for single output situations. DEA generalizes the notion of RTS to the multiple-output case. This, in turn, further extended the applicability of DEA.

Amplify

Models for Evaluating Supply Chains and Network Structures,le, if the process is to make a car, then important subprocesses include assembling and painting. If we evaluate the efficiency of a supply chain system, then we need to measure the performance of each individual supply chain components, including suppliers, manufacturers, retailers, and customers.

無關緊要

Interval and Ordinal Data in DEA,ook et al. (. 133–140, 1993; . 945–953, 1996) were the first who developed a modified DEA structure where the inputs and outputs are represented as rank positions in an ordinal, rather than numerical sense.

領先

0884-8289 version of DEA Frontier software in Springer Extras.Includes.The author is one of the prominent researchers in the field of Data Envelopment Analysis (DEA), a powerful data analysis tool that can be used in performance evaluation and benchmarking. This book is based upon the author’s years of resear