Management Science Relations for Evaluation and Management Accountability

Abstract

Management accountability as an added dimension for management science research is examined from the standpoint of possible uses in some of the newer comprehensive auditing approaches to propriety, effectiveness and efficiency evaluations of management and organization behavior. Attention is centered on non-market activities and not-for-profit organizations. Goal focusing is examined, for example, as a relatively recent extension of goal programming for use in effectiveness evaluation and as an alternative to utility theoretic approaches in national goals accounting systems designed to deal with programs or objectives involving numerous kinds of off-market activities. The bulk of the paper, however, is devoted to a new mathematical programming model for deriving analytic representations of extremal frontiers or envelopes from empirical data and for measuring the efficiency of not-for-profit entities. An illustrative application to a recently completed large-scale social experiment in educating disadvantaged children in the U.S. public schools is used to show how distinctions may also be drawn between program efficiency and management efficiency. The appendix develops a canonical form for the types of statistical distributions involved. It also provides a beginning for dealing with statistical properties of the extremal relations obtained by applying these kinds of mathematical programming models to observational data.

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Document Details

Document Type
Technical Report
Publication Date
May 01, 1979
Accession Number
ADA080452

Entities

People

  • Abraham Charnes
  • William W. Cooper

Organizations

  • University of Texas at Austin

Tags

Communities of Interest

  • Biomedical
  • Energy and Power Technologies
  • Human Systems

DTIC Thesaurus Topics

  • Accountability
  • Accounting
  • Auditing
  • Business Administration
  • Computer Programming
  • Contracts
  • Economics
  • Education
  • Goal Programming
  • Mathematical Programming
  • New York
  • Operations Research
  • Social Sciences
  • Statistical Distributions
  • Statistics
  • Students
  • United States

Readers

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  • Economics
  • Theoretical Analysis.