Computational Organization Theory

Dear Colleagues,

Computational Organization Theory is an emerging interdisciplinary area of research that applies the computational modeling and analysis technique to the questions that lie at the intersection of fields such as sociology, economics, political science, organizational science, and many others. The perspective that is common among all approaches within this area is that an organization is a system of many autonomous agents interacting with one another through a set of rules that are specific to the organization. The “organization” can be as small as a team or a group of a few individuals or as large as the entire social system that contains smaller organizations of varying sizes.
The agents are typically assumed to be purposive – i.e., have well-defined objectives that they try to meet, albeit imperfectly – but are less than fully rational in the sense of having limited foresight and imperfect computational capability. While autonomous in decision making, the agents are nevertheless social and engage in interactive relationships with each other, through either formal organizational mechanism that are imposed on them from top down or an informal system of beliefs and understandings that arise endogenously from the bottom up. Computational Organization Theory offers an approach that allows us to rigorously study the evolving nature of these formal and informal organizational relationships through a series of computational experiments.
This special issue seeks contributions using computational models to address a broad set of issues that arise in the conceptual framework described above. These issues include, but are not limited to the following:

• Organizational learning when the organization consists of autonomous agents capable of learning individually
• Exploration vs. exploitation (or innovation vs. imitation) at the level of agents within an organization and their impact on the organization’s performance over time
• Impact of an improvement in information technology on the optimal structure of an organization (both formal and informal)
• Simplicity and complexity of an organizational problem and their impact on the structure of the organizational hierarchy dedicated to problem-solving
• Endogenous structure of a learning network within a social and/or an organizational system
• Endogenous division of cognitive labor within a social and/or an organizational system
• Organizational structure and the organization’s capability to adapt in a turbulent environment
• Strategy-and-structure nexus

Prof. Dr. Myong-Hun Chang
Guest Editor

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• computational model
• organizational learning
• organizational search
• organizational structure
• complexity
• exploration
• exploitation
• social network
• adaptive organization