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Abstract
Enterprise transformation involves fundamental change and often involves a sequence of innovation, disruption, uncertainty, risk and opportunity. Under volatile economic situations, intense market competition, unpredictable company strategy, and frequently changed product technology, a successful transformation requires deeper and well-informed decision making practices that can have profound influences on society.
In this thesis, we addressed various enterprise transformations in the U.S. automobile market to consider the issues from a broader perspective. A series of research studies of transformation case histories and specific technology adoption cases are reported. We believe that various changes in different levels of an enterprise are key phenomena.
To investigate the transformation in the auto industry, we started from a historical standpoint to get familiar with the industry and cover more perspectives without the limitations of mathematical narratives. The first study addressed high-level disruptions from the economic level on a long period of time. A case-based approach was used to qualitatively discuss in rich detail the demise of twelve American automobile brands over the past century.
Based on this initial research, we decided to evaluate enterprise transformation using a quantitative analysis of on-going transformation. Considering fundamental transformation can start from bottom up (Rouse, 2006), technology adoption was picked as a perspective from which to detect top-down economic level disruptions and also bottom-up technology disruptions with higher level implications. Considering the potential environmental and economic impacts of alternative powertrain systems, the adoptions of various battery electric related and hydrogen fuel cell technologies were taken as subjects of multi-level systems dynamic simulation.
To explore the power to anticipate potential scenarios before they unfold, we decided to pursue an analysis on an even more promising and wider impact technology, autonomous driving technology. The last part of the thesis focuses on understanding how autonomous driving technology will be adopted and how it will impact the transportation and other industries, specifically the auto insurance industry. The systems dynamic simulation was constructed and evaluated based on expert opinion and available data in and out of the automobile industry.
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