Modeling Data Irregularities and Structural Complexities in Data Envelopment Analysis

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...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor Corporativo: SpringerLink (Online service)
Otros Autores: Zhu, Joe (Editor ), Cook, Wade D. (Editor )
Formato: Electrónico eBook
Idioma:Inglés
Publicado: New York, NY : Springer US : Imprint: Springer, 2007.
Edición:1st ed. 2007.
Temas:
Operations research.
Mathematical optimization.
Finance, Public.
Econometrics.
Business.
Management science.
Operations Research and Decision Theory.
Optimization.
Public Economics.
Business and Management.
Operations Research, Management Science .
Acceso en línea:Texto Completo
Tabla de Contenidos:
  • 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.

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