Measuring the Efficiency of Decision Making Units with Some New Production Functions and Estimation Methods.

Abstract

A series of linear programming models are used to clarify and extend a measure of efficiency. The duals to these models are shown to yield estimates of production coefficients from the same empirical data and computations that yield the measures of efficiency. The nature of the resulting production functions and ways in which they differ from more customary ones are discussed en route to synthesizing the associated cost functions and other such (economic) relations. Methods for adjusting observations are suggested for economic inferences and policy applications. Multiple output-multiple input extensions are effected via a new definition of efficiency which involves a nonlinear model for determining the optimal input and output weights from observational data. The theory of fractional programming is used to secure ordinary linear programming models from which the weights and efficiency measures may also be obtained.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 1977
Accession Number
ADA049149

Entities

People

  • Abraham Charnes
  • E. Rhodes
  • William W. Cooper

Organizations

  • University of Texas at Austin

Tags

Communities of Interest

  • Energy and Power Technologies
  • Human Systems

DTIC Thesaurus Topics

  • Algorithms
  • Business Administration
  • Computations
  • Convex Sets
  • Data Analysis
  • Economics
  • Evolutionary Algorithms
  • Inequalities
  • Linear Programming
  • Mathematical Programming
  • Mathematics
  • New York
  • Operations Research
  • Optimization
  • Simplex Method
  • Systems Engineering
  • Two Dimensional

Fields of Study

  • Mathematics

Readers

  • Operations Research
  • Regression Analysis.
  • Theoretical Analysis.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Machine Learning Algorithms