Level of complexity: Difference between revisions
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[[File:levels_of_complexity.png|400px|right|thumb|Fig.1. Levels of complexity]] | |||
There is no such '''control system''' that would be universal for use in all circumstances. From what circumstances the [[organization]] faces, it is possible to apply a given control system. An accidental [[project]] that is likely to be important for control is related to conventional control [[documentation]]. For the research on the design of management control one of the dominant paradigms has become the contingency theory. A [[method]] for categorizing research has been introduced, which offers great opportunities for future research. | There is no such '''control system''' that would be universal for use in all circumstances. From what circumstances the [[organization]] faces, it is possible to apply a given control system. An accidental [[project]] that is likely to be important for control is related to conventional control [[documentation]]. For the research on the design of management control one of the dominant paradigms has become the contingency theory. A [[method]] for categorizing research has been introduced, which offers great opportunities for future research. | ||
Revision as of 15:26, 2 September 2020
| Level of complexity |
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| See also |
Level of complexity is a measure, which describes characteristics of organizational or social system. In management we can distinguish following levels of system complexity:
- complicated system (e.g. machine, computer)
- random system (market, customer behaviour, chaotic changes in financial markets)
- organized complexity (organizational structure, processes, principles, algorithms)
- self-organized complexity (adaptive systems, organizational flexibility, innovation)
Categorization
There is no such control system that would be universal for use in all circumstances. From what circumstances the organization faces, it is possible to apply a given control system. An accidental project that is likely to be important for control is related to conventional control documentation. For the research on the design of management control one of the dominant paradigms has become the contingency theory. A method for categorizing research has been introduced, which offers great opportunities for future research.
The level of complexity of the analysis classifies scientific articles on control. Research on internal control is carried out in a fragmented way. This is one of the main weaknesses of this study. At the same time, one conditional factor and one control attribute examine a lot of research. In order to determine the effectiveness of the control system design, it may be crucial to understand the interaction between multiple condition and control.
The simplest emergency analysis attempts to correlate the factor with the control system attribute. However, a more complex analysis can analyze many conditional and coercive factors simultaneously. The development and testing of a comprehensive model that includes multiple control systems, many conditional and resultant variables should be the ultimate goal of conditional testing.
The appropriate controls, cases and tests are described in the first place according to the level of their complexity. Next, the definition of the formal control system is discussed. The third step is to analyze the characteristics of the conditional model and list the conditional variables that were included in the control studies. Discussing previous works on conditional control and introducing the classification framework for these studies is a fourth step.The final stage is to assess some of the weaknesses of current conditional control studies and discuss the possibilities for future research[1].
References
- Fisher J. (1995). Contingency-based research on management control systems: Categorization by level of complexity. Journal of Accounting Literature, 24-53.
- Li, H., & Williams, T. J. (2002). Management of complexity in enterprise integration projects by the PERA methodology. Journal of Intelligent Manufacturing, 13(6), 417-427.
- Plsek, P. E., & Wilson, T. (2001). Complexity science: complexity, leadership, and management in healthcare organisations. BMJ: British Medical Journal, 323(7315), 746.
- Pich, M. T., Loch, C. H., & Meyer, A. D. (2002). On uncertainty, ambiguity, and complexity in project management. Management science, 48(8), 1008-1023.
Footnotes
- ↑ Fisher J. 1995
Author: Anna Zuwała
