Item Details

The Dimensions of Systems Thinking - an Approach for a Standard Language of Systems Thinking

Whitehead, N. Peter
Thesis/Dissertation; Online
Whitehead, N. Peter
Scherer, William
The concept of systems thinking (and its embodiment in the systems approach, systems science and systems engineering) dates from the historical origins of engineering, policy and philosophy. However, unlike mathematics, physics, biology and other fields with similar histories, systems thinking lacks a common, foundational language that facilitates transparent communication. If language is the manifestation of thought per Chomsky, then systems thinking can be succinctly expressed via its underlying language. Examples from the author’s research and the literature show that the practice of and research in systems approaches would benefit from a common language and foundation of systems thinking. This thesis proposes a common, foundational language to express any systems approach. The author derives this foundation through building a definition of systems thinking from the respective definitions of systems and critical thinking. This definition is then expanded into a foundational working lexicon of systems thinking - the Dimensions of Systems Thinking (DST). To reduce ambiguity and fill gaps, key concepts are introduced including the observer effect of systems thinking, the difference between the scope of the analysis and the boundaries of the system and the distinction between metrics and indices of performance of a system. Case studies demonstrate the development and application of the foundational elements in practical analysis. Liquid biofuel, healthcare and science policy are each considered and system improvements recommended through the application of the Dimensions of Systems Thinking. The thesis then develops a method of analytically identifying the level of systems thinking in a document. In doing so, it considers the statistical semantic characteristics of term frequency and inverse document frequency, cosine similarity and Naïve Bayes classifiers with supervised learning such as Rocchio classifiers and quadratic discriminant analysis. A proof-of-concept study then tests the proposed approach. The study successfully demonstrates the analytical assessment of the systems thinking quality of each document in a learning/training corpus and a corpus of unread research studies on life cycle assessment. It also shows that an analytical relation between the specific components of the Dimensions of Systems Thinking and a document can be established - a capability that will be useful for improving the quality of systems approaches. The way forward will be to discuss and debate the elements of the language of systems thinking with the goal of codifying the concept, to continue refining and testing the analytical capability and further testing of this new methodology on case studies.
Date Received
University of Virginia, Department of Systems Engineering, PHD (Doctor of Philosophy), 2014
Published Date
PHD (Doctor of Philosophy)
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