MANAGEMENT SCIENCE
This is concerned with developing
and applying models and concepts that may prove useful in helping to illuminate
management issues and solve managerial problems, as well as designing and
developing new and better models of organizational excellence. The application
of these models within the corporate sector became known as management science.
The models used can often be represented mathematically, but sometimes
computer-based, visual or verbal representations are used.
The range of problems
and issues to which management science has contributed insights and solutions
is vast. It includes 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 and appropriate systems to supply them within the health
serviced and identifying and understanding the strategies adopted by them within the health service, and identifying and
understanding the strategies adopted by companies for their information systems.
Management science is the
application of statistical or mathematical methods and principles to business
decision-making and problem-solving processes. Applying scientific-style
methods to common management situations can help companies develop a deeper
understanding of business scenarios and how to approach these issues from a
managerial standpoint. Management science may also take a more theoretical
approach to making business decisions or solving problems rather than relying
on a managers personal judgment or perception of business situations.
Management science may use the principles of managerial economics when
approaching various business situations. Managerial economics relies on
statistical tools, such as risk analysis, pricing analysis, capital budgeting,
regression analysis or correlation, to determine the best opportunity companies
should choose when making business decisions.
Management Science is also a branch of
traditional operations research used
in business management. Operations research applies
mathematical or quantitative techniques to the decision-making process. This management process typically
uses computer analysis models that allow managers to input various pieces of
data and use a mathematical formula to compute best case scenarios based on the
data. Using computer analysis techniques may also allow companies to enter
several variations to the original data; these variations allow the computer
program to quickly change the outcome based on the new information.
ln1967 Tafford Beer characterized
the field of management science as "the business use of operations research".
However, in modern times the term management science may also be used to
refer to the separate fields of organizational
studies or corporate strategy.
Like operational research itself,
management science (MS) is an interdisciplinary branch of applied mathematics devoted to
optimal decision planning, with strong links with economics, business, engineering, and other sciences. It uses various scientific
research-based principles, strategies, and analytical
methods including mathematical modeling, statistics and numerical algorithms to
improve an organization's ability to enact
rational and meaningful-management decisions by' arriving at optimal or near optimal solutions to complex decision
problems.
In short, management sciences help
businesses to achieve their goals using the scientific methods of operational research.
The management scientist's mandate
is to use rational, systematic, science-based techniques to inform and improve
decisions of all kinds. Of course, 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.
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Truesdell,
Clifford (1984). An Idiot’s Fugitive Essays on Sciences. Springer pp. 121 -7 ISBN 3-540-90703-3
Billings
S. A “Nonlinear System Identification: NARMAX Methods in the Time, Frequency, and Spatio-Temproal Domains”
Wiley, 2013
Mackay, D.
J. Information Theory, Inference, and Learning Algorithms, Cambridge, (2003-2004). ISBN
0-521-64298-1
Pyke, G.
H. (1984). “Optimal Foraging Theory: A Critical Review”. Annual Review of Ecology and Systematic
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(1990). The Organizational of Learning. Cambridge: The MIT Press ISBN 0-262-07113-4.
Whishaw,
I. Q,; Hines, D. J.Wallace, D. C. (2001). Behaviroual Brain Research 127 (1-2): 49-69. doi:10.1016/S0166-4328(01)00359-X.
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