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Systems thinking in technical change: An analogical modelling approach

Dimond, A.J. (1990). Systems thinking in technical change: An analogical modelling approach. (Unpublished Doctoral thesis, City, University of London)


This research argues that the subject of technical change has, rather surprisingly, continued to utilise old-fashioned ideas to illustrate its causes and effects. A review of technical change models indicates a continuing reliance on the production function and equilibrium structures to explain various aspects of technical change. The need to determine a new comprehensive interpretation for the structure of technical change is advocated by using a systems based investigation. This is examined by illustrating the utility of Stafford Beer’s (1984) methodology of topological maps in developing a system scientific model of technical change. The methodological application of the adaptive whole system and viable system in the analogical context to technical change, presents a basis for developing the systems model. This provides a unique approach which produces a systems modelling reinterpretation for the structure and functions of technical change. An evaluatory analysis of the model, using both theoretical evidence and practical field research in a U.K based microelectronics company, finds that a basic structural complementarity exists between known characteristics of technical change and the viable systems model. In addition, it is also shown that this new structural and functional model provides an alternative direction for illustrating the necessary managerial control preparations for viable technical changes, and an explanation of its causes and effects. Based on these findings, recommendations are made for continued systems research in technical change.

Publication Type: Thesis (Doctoral)
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
T Technology > T Technology (General)
Departments: Doctoral Theses
School of Science & Technology > School of Science & Technology Doctoral Theses
School of Science & Technology > Engineering > Electrical & Electronic Engineering
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