Management science

Management science (or managerial science) is a wide and interdisciplinary study of solving complex problems and making strategic decisions as it pertains to institutions, corporations, governments and other types of organizational entities. It is closely related to management, economics, business, engineering, management consulting, and other fields. It uses various scientific research-based principles, strategies, and analytical methods including mathematical modeling, statistics and numerical algorithms and aims to improve an organization's ability to enact rational and accurate management decisions by arriving at optimal or near optimal solutions to complex decision problems.[1]:113

Management science looks to help businesses achieve goals using a number of scientific methods. The field was initially an outgrowth of applied mathematics, where early challenges were problems relating to the optimization of systems which could be modeled linearly, i.e., determining the optima (maximum value of profit, assembly line performance, crop yield, bandwidth, etc. or minimum of loss, risk, costs, etc.) of some objective function. Today, the discipline of management science may encompass a diverse range of managerial and organizational activity as it regards to a problem which is structured in mathematical or other quantitative form in order to derive managerially relevant insights and solutions.[2][3]

Overview

Management science is concerned with a number of areas of study:

  • Developing and applying models and concepts that may prove useful in helping to illuminate management issues and solve managerial problems. The models used can often be represented mathematically, but sometimes computer-based, visual or verbal representations are used as well or instead.[4]
  • Designing and developing new and better models of organizational excellence.
  • Helping to improve, stabilize or otherwise manage profit margins in enterprises.

Management science research can be done on three levels:[5]

  • The fundamental level lies in three mathematical disciplines: probability, optimization, and dynamical systems theory.
  • The modeling level is about building models, analyzing them mathematically, gathering and analyzing data, implementing models on computers, solving them, experimenting with themall this is part of management science research on the modeling level. This level is mainly instrumental, and driven mainly by statistics and econometrics.
  • The application level, just as in any other engineering and economics disciplines, strives to make a practical impact and be a driver for change in the real world.

The management scientist's mandate is to use rational, systematic and science-based techniques to inform and improve decisions of all kinds. The techniques of management science are not restricted to business applications but may be applied to military, medical, public administration, charitable groups, political groups or community groups. The norm for scholars in management science is to focus their work in a certain area or subfield of management like public administration, finance, calculus, information and so forth.[6]

History

The origins of management science can be traced to operations research, which became influential during World War II when the Allied forces recruited scientists of various disciplines to assist with military operations. In these early applications, the scientists used simple mathematical models to make efficient use of limited technologies and resources. The application of these models to the corporate sector became known as management science.[7]

In 1967 Stafford Beer characterized the field of management science as "the business use of operations research".[8]

Theory

Some of the fields that management science involves include:

Applications

Applications of management science are abundant in industries such as airlines, manufacturing companies, service organizations, military branches, and in government. Management science has contributed insights and solutions to a vast range of problems and issues, including:[4]

  • scheduling airlines, both planes and crew
  • deciding the appropriate place to site new facilities such as a warehouse or factory
  • managing the flow of water from reservoirs
  • identifying possible future development paths for parts of the telecommunications industry
  • establishing the information needs of health services and appropriate systems to supply them
  • identifying and understanding the strategies adopted by companies for their information systems

Management science is also concerned with so-called soft-operational analysis, which concerns methods for strategic planning, strategic decision support, and problem structuring methods (PSM). At this level of abstraction, mathematical modeling and simulation will not suffice. Therefore, since the late 20th century, new non-quantified modelling methods have been developed, including morphological analysis and various forms of influence diagrams.[1]:545

See also

References

  1. An Introduction to Management Science: Quantitative Approaches to Decision Making (15 ed.). Boston: Cengage Learning, Inc. 2019. ISBN 978-1-337-40652-9. Retrieved 14 October 2022.
  2. "Tools for Thinking — Modelling in Management Science". Taylor & Francis Online. Retrieved 30 March 2023.
  3. "Management Models and Industrial Applications of Linear Programming". Management Science. 4 (1): 38–91. 1957. doi:10.1287/mnsc.4.1.38. Retrieved 30 March 2023.
  4. What is Management Science? Archived 2009-07-25 at the Wayback Machine Lancaster University, 2008. Retrieved 5 June 2008.
  5. What is Management Science Research? Archived 2008-11-04 at the Wayback Machine University of Cambridge 2008. Retrieved 5 June 2008.
  6. "Sub-disciplines in Management Sciences: Review of Classifications in Polish and Worldwide Research Practice". International Journal of Contemporary Management. 17 (1): 137–156. 2018. doi:10.4467/24498939IJCM.18.008.8387. Retrieved 30 March 2023.
  7. What is Management Science? Archived 2008-12-07 at the Wayback Machine The University of Tennessee, 2006. Retrieved 5 June 2008.
  8. Stafford Beer (1967). Management Science: The Business Use of Operations Research

Further reading

  • Kenneth R. Baker, Dean H. Kropp (1985). Management Science: An Introduction to the Use of Decision Models
  • David Charles Heinze (1982). Management Science: Introductory Concepts and Applications
  • Lee J. Krajewski, Howard E. Thompson (1981). "Management Science: Quantitative Methods in Context"
  • Thomas W. Knowles (1989). Management science: Building and Using Models
  • Kamlesh Mathur, Daniel Solow (1994). Management Science: The Art of Decision Making
  • Laurence J. Moore, Sang M. Lee, Bernard W. Taylor (1993). Management Science
  • William Thomas Morris (1968). Management Science: A Bayesian Introduction.
  • William E. Pinney, Donald B. McWilliams (1987). Management Science: An Introduction to Quantitative Analysis for Management
  • Gerald E. Thompson (1982). Management Science: An Introduction to Modern Quantitative Analysis and Decision Making. New York : McGraw-Hill Publishing Co.
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