[讨论]Data Envelopment Analysis

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Could you tell me which procedure in SAS 9.1 can conduct DEA?

[此贴子已经被作者于2006-4-18 21:40:29编辑过]

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关键词：Envelopment Analysis Analysi alysis Analys Analysis 讨论 Data Envelopment

以下是引用hanszhu在2006-4-18 12:30:00的发言：
Could you tell me which procedure in SAS 9.1 can conduct DEA?

ABSTRACT

This paper explores the use of the optimisation procedures in SAS/ OR software with application to the decision system support using Data Envelopment Analysis ( DEA) techniques. Data Envelopment Analysis is a linear programming method for assessing the efficiency and productivity of Decision Making Units. Over the last decade DEA has gained considerable attention as a managerial tool for measuring performance of organisations and it has been used widely for assessing the efficiency of public and private sectors such as banks, airlines, hospitals, universities and manufactures. As a result, new applications with more variables and more complicated models are being introduced. On the other hand, the SAS ? System has numerous optimisation routines that handle the standard optimisation problems such as linear programming with all types of constraints. To facilitate the use of DEA by SAS users, a SAS/ DEA code was implemented in the SAS programming language. The SAS macro developed in this paper selects the chosen variables from a SAS data file and constructs a Linearprogramming model based on the selected DEA. An example is given to illustrate how could one use the code to measure the efficiency of organisations.

48918.pdf (188.61 KB)

2006-4-18 12:33:00 上传

[讨论]DEA in SAS

[此贴子已经被作者于2006-4-18 12:42:16编辑过]

DEA SOFTWARE TOOLS AND TECHNOLOGY

A State- of- the- Art Survey

Richard S. Barr

Department of Engineering Management, Information, and Systems; Southern Methodist University, Dallas, TX 75275 USA

Abstract:

Today’s DEA practitioners and researchers have a wide range of solution technology choices. Clearly, software is no longer an impediment to the incorporation of DEA into decision- support systems and benchmarking processes. This is evidenced by the availability of interoperable tools with a variety of user interfaces, advanced modeling options, and the power to evaluate large- scale data sets on inexpensive computing platforms. This survey describes and critiques prominent DEA software packages, both commercial and non- commercial, and summarizes the current state of the art.

48919.pdf (1.08 MB)

2006-4-18 12:40:00 上传

[此贴子已经被作者于2006-4-18 12:41:30编辑过]

Data Envelopment Analysis (DEA). A nonparametric method in operations research and econometrics for multivariate frontier estimation and ranking.

With the intention of being consistent with microeconomic production theory and when being conscious of the existence of inefficiencies in the production processes, frontier techniques have been developed during the last 30 years.

Among the different solutions, we can find a nonparametric method called Data Envelopment Analysis (DEA), which is a linear programming methodology to measure the efficiency of multiple Decision Maker Units (DMUs) when the production process presents a structure of multiple inputs and outputs.

Then, some of the benefits of it are: (1) there is no need to explicitly specify a mathematical form for the production function, (2) it has proven to be useful in uncovering relationships that remain hidden for other methodologies, (3) is capable of handling multiple inputs and outputs, (4) it can be used with any input-output measurement, (5) the sources of inefficiency can be analysed and quantified for every evaluated unit.

In the DEA methodology, formerly developed by Charnes, Cooper and Rhodes (1978), efficiency is defined as a weighted sum of outputs to a weighted sum of inputs, where the weights structure is calculated by means of mathematical programming and constant returns to scale are assumed. In 1984, Banker, Charnes and Cooper developed a model with variable returns to scale.

[此贴子已经被作者于2006-4-18 12:53:10编辑过]

Reference

• "Measuring the efficiency of decision-making units," European Journal of Operational Research by A. Charnes, W. Cooper, and E. Rhodes (1978).
• "An Extensive Bibliography of Data Envelopment Analysis (DEA), Volume I: Working Papers.", [[1]]

[此贴子已经被作者于2006-4-18 12:55:18编辑过]

A Data Envelopment Analysis (DEA) Home Page

http://www.emp.pdx.edu/dea/homedea.html

Contents

About this Document

Introduction to DEA

• Simple Numerical Example
• Graphical Example
• Returns to Scale
• Applications
• Strengths of DEA
• Limitations of DEA
• Other Topics

DEA Software

References

[此贴子已经被作者于2006-4-18 12:59:04编辑过]

Data Envelopment Analysis for Consultants

Michael Trick

Data Envelopment Analysis (DEA) is an increasingly popular management tool. This write-up is an introduction to Data Envelopment Analysis (DEA) for people unfamiliar with the technique. For a more in-depth discussion of DEA, the interested reader is referred to Seiford and Thrall [1990] or the seminal work by Charnes, Cooper, and Rhodes [1978].

DEA is commonly used to evaluate the efficiency of a number of producers. A typical statistical approach is characterized as a central tendency approach and it evaluates producers relative to an average producer In contrast, DEA compares each producer with only the "best" producers. By the way, in the DEA literature, a producer is usually referred to as a decision making unit or DMU. DEA is not always the right tool for a problem but is appropriate in certain cases. (See Strengths and Limitations of DEA.)

In DEA, there are a number of producers. The production process for each producer is to take a set of inputs and produce a set of outputs. Each producer has a varying level of inputs and gives a varying level of outputs. For instance, consider a set of banks. Each bank has a certain number of tellers, a certain square footage of space, and a certain number of managers (the inputs). There are a number of measures of the output of a bank, including number of checks cashed, number of loan applications processed, and so on (the outputs). DEA attempts to determine which of the banks are most efficient, and to point out specific inefficiencies of the other banks.

A fundamental assumption behind this method is that if a given producer, A, is capable of producing Y(A) units of output with X(A) inputs, then other producers should also be able to do the same if they were to operate efficiently. Similarly, if producer B is capable of producing Y(B) units of output with X(B) inputs, then other producers should also be capable of the same production schedule. Producers A, B, and others can then be combined to form a composite producer with composite inputs and composite outputs. Since this composite producer does not necessarily exist, it is typically called a virtual producer.

The heart of the analysis lies in finding the "best" virtual producer for each real producer. If the virtual producer is better than the original producer by either making more output with the same input or making the same output with less input then the original producer is inefficient. The subtleties of DEA are introduced in the various ways that producers A and B can be scaled up or down and combined.

• Numerical Example
• Graphical Example
• Using Linear Programming
  • Example
• Applications
• Strengths and Limitations of DEA
• References
• About this document ...

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http://web.cenet.org.cn/web/Occidental/

[此贴子已经被作者于2006-4-18 13:02:23编辑过]

Data Envelopment Analysis Links:

Portland State University, Engineering management program: - Lectures - Bibliography - DEA Dataset repository	University of Warwick, Warwick Business School: - DEA homepages (Ali/Laura) - Lecture - DEA-software (demo available) - Bibliography	University of Dortmund, Faculty for economics and social sciences: - DEA homepage (Holger) - DEA data collection - EMS-software (free!)
University of Mannheim, School of Business Administration, Chair of Business Adminstration and Operations Research: - WWW-based DEA interface		University on New England, School of Economics, Centre for Efficiency and Productivity Analysis: - DEAP-software (free!)
Banxia Software: - Frontier Analyst-Software (demo available) - Bibliography	Imperial College of Science, Technology and Medicine: - Lecture - DEA data collection	Instituto Politécnico da Guarda: - DEA homepage (Gabriel) - Bibliography / search engine

48921.pdf (1.92 MB)

2006-4-18 13:13:00 上传

[讨论]DEA in SAS

An Introduction to Data Envelopment Analysis
A Tool for Performance Measurement

R Ramanathan:Sultan Qaboos University, Oman

Description:
From the Foreword:

'This book is an excellent tool for practitioners who are interested in the merits and pitfalls of the technique…. (The author's) research is an example of inventiveness, diligence and accuracy' - Freerk A. Lootsma, Delft Institute of Technology

Data envelopment Analysis is a Mathematical Programme for measuring performance efficiency of organizational units. The organizational units, termed as decision-making units (DMU) can be of any kind: manufacturing units, a set of schools, banks, hospitals, power plants, police stations, prisons, a set of firms etc.

DEA has been unsuccessfully applied to measure the performance efficiency of these different kinds of DMUs which share a common characteristic - that they are non-profit organization where measurement of performance efficiency is difficult.

DEA has been employed for assessing the relative performance of a set of firms that use a variety of identical inputs-say in the case of a school: quality of students, teachers, grants etc.,-to produce a variety of identical outputs-number of students who pass the final year, average grades obtained by the students in the final year etc.

DEA assumes the performance of the DMUs by using the concepts of efficiency or productivity which is measured as the ratio of total outputs to total inputs. Also, the efficiencies estimated are relative to the best performing DMU or DMUs. The best performing DMU is given a score of 100% and the performance of other DMUs vary between 0 -100%.

[此贴子已经被作者于2006-4-18 13:16:56编辑过]