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Towards an Approach for a Conceptual System Design

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  • Austin Amaechi
  • Steve Counsell

Abstract

Complex adaptive systems are usually difficult to design and control. The design of complex adaptive systems often, if not always, occurs in a context that is uncertain. In addition to the complexity of the system, the systems both affect and are influenced by a social environment containing a large variety of actors. Methods and processes that study the design of such types of systems can help scholars and practitioners to better understand, design and manage complex adaptive systems. The aim in this paper is to provide a methodology useful for designing and controlling systems developed to solve complex adaptive problems. In this paper, the complex systems life cycle understanding and design framework are introduced as an approach for satisficing of systems at conceptual design. To illustrate the methodology, a financial systemic risks infrastructure systems architecture development case study is presented. Copyright © 2013 John Wiley & Sons, Ltd.

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  • Austin Amaechi & Steve Counsell, 2013. "Towards an Approach for a Conceptual System Design," Systems Research and Behavioral Science, Wiley Blackwell, vol. 30(6), pages 780-793, November.
    • Handle: RePEc:bla:srbeha:v:30:y:2013:i:6:p:780-793
    DOI: 10.1002/sres.2244
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    References listed on IDEAS

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    1. Steven H. Strogatz, 2001. "Exploring complex networks," Nature, Nature, vol. 410(6825), pages 268-276, March.
    2. William B. Rouse, 2007. "Complex engineered, organizational and natural systems," Systems Engineering, John Wiley & Sons, vol. 10(3), pages 260-271, September.
    3. J. M. Ottino, 2004. "Engineering complex systems," Nature, Nature, vol. 427(6973), pages 399-399, January.
    4. Herbert A. Simon, 1996. "The Sciences of the Artificial, 3rd Edition," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262691914, December.
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    Cited by:

    1. Kennedy, Deanna M. & Sommer, S. Amy & Nguyen, Phuong Anh, 2017. "Optimizing multi-team system behaviors: Insights from modeling team communication," European Journal of Operational Research, Elsevier, vol. 258(1), pages 264-278.

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