Special Issue "Computational Organization Theory"
A special issue of Administrative Sciences (ISSN 2076-3387).
Deadline for manuscript submissions: closed (1 September 2014)
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
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a double-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Administrative Sciences is an international peer-reviewed open access quarterly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
- computational model
- organizational learning
- organizational search
- organizational structure
- social network
- adaptive organization