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A framework for optimizing managerial decision

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  • Littauer, S. B.
  • Yegulalp, T. M.
  • Zahariev, G. K.

Abstract

There have been numerous attempts to analyze and formulate management problems within the general framework of Management Science and Operations Research, so as to help managers in their decision making problems. This paper focuses on the fundamental aspects of management decision making and introduces a conceptual framework in which problems of management and its different levels of functioning are systematically identified. Management problems are considered within two major categories: Enterprise and Operations problems. In spite of the difficulties in defining a clear-cut boundary between Enterprise and Operations problems, such a broad classification leads to three basic levels of management functioning, namely: Policy making, coordinating and implementation. The universal relationship among these three basic levels of functioning provides a basic functional element called the Management Triad. In contrast to classical higherarchial structure, triad structure provides a methodology to analyze relationships among different levels of management functions in terms of a given decision problem. It is demonstrated that for different decision making problems individuals can shift from one end of the triad to another and perform a different management function. A quantitative approach has been introduced for operations management decision making by adapting Shewhart's control chart philosophy which in turn provides for quasi-automated decisions for corrective action and also for filtering significant signals of change to appropriate management functioning levels.

Suggested Citation

  • Littauer, S. B. & Yegulalp, T. M. & Zahariev, G. K., 1976. "A framework for optimizing managerial decision," Omega, Elsevier, vol. 4(1), pages 35-48.
  • Handle: RePEc:eee:jomega:v:4:y:1976:i:1:p:35-48
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    References listed on IDEAS

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    1. Richard Ehrhardt, 1979. "The Power Approximation for Computing (s, S) Inventory Policies," Management Science, INFORMS, vol. 25(8), pages 777-786, August.
    2. Richard Ehrhardt & Charles Mosier, 1984. "A Revision of the Power Approximation for Computing (s, S) Policies," Management Science, INFORMS, vol. 30(5), pages 618-622, May.
    3. Arthur F. Veinott, Jr. & Harvey M. Wagner, 1965. "Computing Optimal (s, S) Inventory Policies," Management Science, INFORMS, vol. 11(5), pages 525-552, March.
    4. Eliezer Naddor, 1975. "Optimal and Heuristic Decisions in Single-and Multi-Item Inventory Systems," Management Science, INFORMS, vol. 21(11), pages 1234-1249, July.
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