Many industries, such as healthcare, transportation, education, and other fields that involve large corporations and institutions, are complex systems composed of many diverse interacting components. Frequently, to improve performance within these industries, to move into new markets, or to expand capability or capacity, decision-makers face opportunities or mandates to implement innovations (new technology, processes, and services). Successful implementation of these innovations involves seamless integration with the policy, economic, social, and technological dynamics associated with the complex system. These dynamics are frequently difficult for decision-makers to observe and understand. Consequently, they take on risk from lack of insight into how best to implement the innovation and how their system-of-interest will ultimately perform. This research defines a framework for an integrated, multi-scale modeling and simulation systems approach that provides decision-makers with prospective insight into the likely performance to expect once an innovation of change is implemented in a complex system. The need for such a framework when modeling complex systems is described, and suitable simulation paradigms and the challenges related to implementing these simulations are discussed. A healthcare case study is used to demonstrate the framework’s application and utility in understanding how an innovation, once fielded, will actually affect the larger complex system to which it belongs.
|Advisor:||Mazzuchi, Thomas A., Sarkani, Shahram|
|Commitee:||Blackburn, Timothy, Murphree, E. Lile, Stuban, Steven|
|School:||The George Washington University|
|Department:||Engineering Management and Systems Engineering|
|School Location:||United States -- District of Columbia|
|Source:||DAI-B 77/12(E), Dissertation Abstracts International|
|Keywords:||Complex systems, Multi-scale modeling, Systems approach, Systems engineering|
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