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Myong-Hun Chang studied Operations Research & Industrial Engineering as an undergraduate at Cornell University.  Upon graduating with a B.S. in 1984, he entered the graduate program in Economics at The Johns Hopkins University, earning a Ph.D. in 1988.  Since 1988, he has been teaching at Cleveland State University, where he is currently Professor and Chair of the Economics Department.  He has also held visiting positions at The Johns Hopkins University and the Owen Graduate School of Management at Vanderbilt University.

His fields of research and teaching interest include Industrial Organization, Applied Game Theory, Computational Organization Theory, and Competitive Strategy.  In the fall of 2008, he is teaching  Game Theory and the Social Sciences in the University Honors Program.

He is currently pursuing three separate lines of research:

1. Industry Dynamics: The objective of this project is to build a computational model of industry evolution which has the capacity to generate a large number of empirical regularities, and is rich enough to allow extensive comparative dynamics analyses involving various industry-specific factors. The current model entails an evolving population of myopic but adaptive firms engaged in knowledge-based competition with entry and exit.
2. Organizational Structure: The central focus of this research is on how the design of coordination and communication structures influences the dynamics of individual and social learning in complex organizational systems.  A recent project, joint with Professor Joseph E. Harrington, Jr. at The Johns Hopkins University, explored the impact of centralization and decentralization on the performance of co-evolving multi-unit business firms in a competitive environment.  The outcomes of this project have been published in a number of refereed journals, including Management Science, Computational and Mathematical Organization Theory, and Journal of Economic Dynamics and Control. This project has evolved into an on-going project which explores the role of communication and information processing in endogenous hierarchies.
3. Endogenous Social Networks: This project investigates the dynamic structure and performance of social networks that emerge endogenously in a population of adaptive agents, when they are engaged in the process of discovery through innovation and imitation.  Some of the results from this line of research have been reported in a special issue of American Journal of Sociology and a recent issue of Organization Science.

All of these research efforts employ game-theoretic and/or agent-based computational modeling techniques.  His recent research on organizations and the related literature are surveyed in a co-authored chapter in Handbook of Computational Economics II: Agent-Based Computational Economics (edited by Leigh Tesfatsion and Ken Judd).