To systems scientists, the world can be understood as a system of systems.[4] The field aims to develop transdisciplinary foundations that are applicable in a variety of areas, such as psychology, biology, medicine, communication, business management, technology, computer science, engineering, and social sciences.[5]
Themes commonly stressed in system science are (a) holistic view, (b) interaction between a system and its embedding environment, and (c) complex (often subtle) trajectories of dynamic behavior that sometimes are stable (and thus reinforcing), while at various 'boundary conditions' can become wildly unstable (and thus destructive). Concerns about Earth-scale biosphere/geosphere dynamics is an example of the nature of problems to which systems science seeks to contribute meaningful insights.
The systems sciences are a broad array of fields. One way of conceiving of these is in three groups: fields that have developed systems ideas primarily through theory; those that have done so primarily through practical engagements with problem situations; and those that have applied systems ideas in the context of other disciplines.[6]
The soft systems methodology was developed in England by academics at the University of Lancaster Systems Department through a ten-year action research programme. The main contributor is Peter Checkland (born 18 December 1930, in Birmingham, UK), a British management scientist and emeritus professor of systems at Lancaster University.
Systems analysis branch of systems science that analyzes systems, the interactions within those systems, or interaction with its environment,[7] often prior to their automation as computer models. Systems analysis is closely associated with the RAND corporation.
System dynamics is an approach to understanding the behavior of complex systems over time. It offers "simulation technique for modeling business and social systems",[8] which deals with internal feedback loops and time delays that affect the behavior of the entire system. What makes using system dynamics different from other approaches to studying complex systems is the use of feedback loops and stocks and flows.
Systems engineering (SE) is an interdisciplinary field of engineering, that focuses on the development and organization of complex systems. It is the "art and science of creating whole solutions to complex problems",[9] for example: signal processing systems, control systems and communication system, or other forms of high-level modelling and design in specific fields of engineering.
^ G. E. Mobus & M. C. Kalton, Principles of Systems Science, 2015, New York:Springer.
^Philip M'Pherson (1974, p. 229); as cited by: Hieronymi, Andreas (2013). "Understanding Systems Science: A Visual and Integrative Approach"(PDF). Systems Research and Behavioral Science. 30 (5): 580–595. doi:10.1002/sres.2215.. He defined systems science as "the ordered arrangement of knowledge acquired from the study of systems in the observable world, together with the application of this knowledge to the design of man-made systems".
^Peter Checkland. 1981. Systems Thinking, Systems Practice. Chichester: Wiley.
^Anthony Debons. "Command and Control: Technology and Social Impact" in: Advances in computers, Vol. 11. Franz L. Alt & Morris Rubinoff eds. (1971). p. 362
^Center for Complex Adaptive Agent Systems Simulation Argonne National Laboratory (2007) Managing Business Complexity : Discovering Strategic Solutions with Agent-Based Modeling and Simulation: Discovering Strategic Solutions with Agent-Based Modeling and Simulation. Oxford University Press. p. 55
^Derek K. Hitchins (2008) Systems Engineering: A 21st Century Systems Methodology. p. 100
Further reading
B. A. Bayraktar, Education in Systems Science, 1979, 369 pp.
Kenneth D. Bailey, "Fifty Years of Systems Science:Further Reflections", Systems Research and Behavioral Science, 22, 2005, pp. 355–361. doi:10.1002/sres.711
Ervin László, Systems Science and World Order: Selected Studies, 1983.
G. E. Mobus & M. C. Kalton, Principles of Systems Science, 2015, New York:Springer.
Anatol Rapoport (ed.), General Systems: Yearbook of the Society for the Advancement of General Systems Theory, Society for General Systems Research, Vol 1., 1956.
Li D. Xu, "The contributions of Systems Science to Information Systems Research", Systems Research and Behavioral Science, 17, 2000, pp. 105–116.
Graeme Donald Snooks, "A general theory of complex living systems: Exploring the demand side of dynamics", Complexity, vol. 13, no. 6, July/August 2008.
