Modeling Data Irregularities and Structural Complexities in Data Envelopment Analysis

Modeling Data Irregularities and Structural Complexities in Data Envelopment Analysis edited by Joe Zhu, Wade D. Cook.

In a relatively short period of time, Data Envelopment Analysis (DEA) has grown into a powerful quantitative, analytical tool for measuring and evaluating performance. It has been successfully applied to a whole variety of problems in many different contexts worldwide. The analysis of an array of th...

Full description

Saved in:
Bibliographic Details
Corporate Author: SpringerLink (Online service)
Other Authors: Zhu, Joe (Editor), Cook, Wade D. (Editor)
Format: eBook
Language:English
Published: New York, NY : Springer US : Imprint: Springer, 2007.
Edition:1st ed. 2007.
Series:Springer eBook Collection.
Subjects:
Operations research.
Decision making.
Mathematical optimization.
Public finance.
Econometrics.
Business.
Management science.
Electronic resources (E-books)
Online Access:Click to view e-book
Holy Cross Note:Loaded electronically.
Electronic access restricted to members of the Holy Cross Community.
Table of Contents:
  • Data Irregularities And Structural Complexities In Dea
  • Rank Order Data In Dea
  • Interval And Ordinal Data
  • Variables With Negative Values In Dea
  • Non-Discretionary Inputs
  • DEA with Undesirable Factors
  • European Nitrate Pollution Regulation and French Pig Farms’ Performance
  • PCA-DEA
  • Mining Nonparametric Frontiers
  • DEA Presented Graphically Using Multi-Dimensional Scaling
  • DEA Models For Supply Chain or Multi-Stage Structure
  • Network DEA
  • Context-Dependent Data Envelopment Analysis and its Use
  • Flexible Measures–Classifying Inputs and Outputs
  • Integer Dea Models
  • Data Envelopment Analysis With Missing Data
  • Preparing Your Data for DEA.

Similar Items