Applications include: work motivation, personnel selection and turnover, creative thinking by individuals and groups, the development of social networks, coordination in work groups, the emergence of leaders, work performance in organizational hierarchies, economic problems that are relevant to organizations, techniques for predicting the future, and emergency management.Įach application begins with a tight summary of standard thinking on a subject, followed by the new insights that are afforded by nonlinear dynamics and the empirical data supporting those ideas. The dynamics concepts are then explained along with the most recent research methods for analyzing real data.
Managing Emergent Phenomena begins by describing how the concept of an organization has changed from a bureaucracy, to a humanistic and organic system, to a complex adaptive system. Discuss examples of emergent phenomena and explain why they are classified as emergent.Chaos, catastrophe, self-organization, and complexity theories (nonlinear dynamics) now have practical and measurable roles in the functioning of work organizations.
Explain why the search for general principles that explain emergent phenomena make them an active locus of scientific investigation.ĥ. Describe how the length scale used to examine a phenomenon can contribute to how you analyze and understand it.Ĥ. Explain why the reductivist approach is understood by many to be inadequate as a means of describing and predicting complex systems.ģ. Explain the difference in assumptions between an emergent versus reductive approach to science.Ģ. Upon completing this course, you will be able to:ġ.
#Managing emergent phenomena with ketamine software#
Note: The fractal image (Sierpinkski Triangle) depicted on the course home page was generated by a software application called XaoS 3.4, which is distributed by the Free Software Foundation under a GNU General Public License. This course lets you explore the concept of emergence using examples from materials science, mathematics, biology, physics, and neuroscience to illustrate how ordinary components when brought together can collectively yield unexpected, surprising behaviors. We can study these components individually without ever imagining how combining them in just the right way can lead to something as complex and wonderful as a living organism! Thus, we can consider life to be an emergent property of what is essentially an accumulation of constituent parts that are somehow organized in a very precise way. Consider a living cell, which consists mostly of carbon, hydrogen, and oxygen along with other trace elements. However, there are some systems that defy this notion. For instance, if one could write down the equations of motion for every atom in a system, it should be possible to solve those equations (with the aid of a sufficiently large computing device) and make accurate predictions about that system’s future. Before the advent of quantum mechanics in the early 20th century, most scientists believed that it should be possible to predict the behavior of any object in the universe simply by understanding the behavior of its constituent parts.
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