Applying Complexity Theory to Chinese Overseas Investment in Oil: Continuous Adaptation
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This dissertation applied complexity theory as a conceptual framework for understanding Chinese National Oil Companies’ (NOCs) continuously changing investment strategies. Complexity theory offers an alternative way of looking at Chinese NOCs, that is, as agents or components of a complex, dynamic, adaptive and nonlinear system. The conceptualization of Chinese NOCs as agents of a complex adaptive system (CAS) in turn makes possible new ways of understanding their behavior. According to complexity theory, agents’ evolving patterns of behavior are shaped by individual experience and driven by the nonlinear, dynamic interactions and feedback processes that are constantly taking place both among agents and between agents and the external environment. When applied to the empirical data collected on Chinese NOCs’ actions between 1993 and 2012, the complexity theory framework helps identify and trace the interactions and feedback processes behind Chinese NOCs’ behavior. As a result of this effort, this dissertation produces some important insights into the “why” and “how” of Chinese NOCs’ behavior. In essence, the dissertation shows that Chinese NOCs’ investment decisions—the “why”—are heavily influenced by the degree of positive or negative feedback they experience, which in turn depends on their degree of interaction and/or activity. “How” these investment decisions are expressed is determined in large part by the companies’ confidence level, attributes, willingness to take risks and positive/negative feedback. Finally, the dissertation finds that there are the significant differences in Chinese NOCs’ behavior over time and across regions, which are tied to their diverse backgrounds and resource-bases. Additionally, the study shows that the impact of Chinese NOCs on the international oil system has been growing and evolving from being purely positive to mixed.