Computational Organization Theory

A special issue of Administrative Sciences (ISSN 2076-3387).

Deadline for manuscript submissions: closed (1 September 2014) | Viewed by 25852

Special Issue Editor

Department of Economics, Cleveland State University, Cleveland, OH 44115, USA
Interests: computational economics; computational organization theory; industrial organization; social networks; game theory

Special Issue Information

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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Keywords

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

Published Papers (4 papers)

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Research

1097 KiB  
Article
Vaccination Games with Peer Effects in a Heterogeneous Hospital Worker Population
by Troy Tassier, Philip Polgreen and Alberto Segre
Adm. Sci. 2015, 5(1), 2-26; https://doi.org/10.3390/admsci5010002 - 14 Jan 2015
Cited by 48 | Viewed by 5163
Abstract
We develop a game theoretic model to analyze the Nash equilibrium of vaccine decisions in a hospital population with heterogeneous contacts. We use the model in conjunction with person-to-person contact data within a large university hospital. We simulate, using agent-based models, the probability [...] Read more.
We develop a game theoretic model to analyze the Nash equilibrium of vaccine decisions in a hospital population with heterogeneous contacts. We use the model in conjunction with person-to-person contact data within a large university hospital. We simulate, using agent-based models, the probability of infection for various worker types in the data and use these probabilities to identify the Nash equilibrium vaccine choices of hospital workers. The analysis suggests that there may be large differences in vaccination rates among hospital worker groups. We extend the model to include peer effects within the game. The peer effects may create additional equilibria or may further cement existing equilibria depending on parameter values. Further, depending on the magnitude of the peer effects and the costs of infection and vaccination, peer effects may increase or decrease differences in worker group vaccination rates within the hospital. Full article
(This article belongs to the Special Issue Computational Organization Theory)
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1191 KiB  
Article
Competition in a New Industrial Economy: Toward an Agent-Based Economic Model of Modularity
by Bin-Tzong Chie and Shu-Heng Chen
Adm. Sci. 2014, 4(3), 192-218; https://doi.org/10.3390/admsci4030192 - 04 Jul 2014
Cited by 23 | Viewed by 5570
Abstract
When firms (conglomerates) are competing, not only for the present, with a given population of customers and a fixed set of commodities or service, but also for the future, in which products are constantly evolving, what will be their competitive strategies and what [...] Read more.
When firms (conglomerates) are competing, not only for the present, with a given population of customers and a fixed set of commodities or service, but also for the future, in which products are constantly evolving, what will be their competitive strategies and what will be the emerging ecology of the market? In this paper, we use the agent-based modeling of a modular economy to study the markup rate dynamics in a duopolistic setting. We find that there are multiple equilibria in the market, characterized by either a fixed point or a limit cycle. In the former case, both firms compete with the same markup rate, which is a situation similar to the familiar classic Bertrand model, except that the rate is not necessarily zero. In the latter case, both firms survive by maintaining different markup rates and different market shares. Full article
(This article belongs to the Special Issue Computational Organization Theory)
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1686 KiB  
Article
Individual Learning and Social Learning: Endogenous Division of Cognitive Labor in a Population of Co-evolving Problem-Solvers
by Myong-Hun Chang and Joseph E. Harrington, Jr.
Adm. Sci. 2013, 3(3), 53-75; https://doi.org/10.3390/admsci3030053 - 12 Jul 2013
Cited by 31 | Viewed by 5416
Abstract
The dynamic choice between individual and social learning is explored for a population of autonomous agents whose objective is to find solutions to a stream of related problems. The probability that an agent is in the individual learning mode, as opposed to the [...] Read more.
The dynamic choice between individual and social learning is explored for a population of autonomous agents whose objective is to find solutions to a stream of related problems. The probability that an agent is in the individual learning mode, as opposed to the social learning mode, evolves over time through reinforcement learning. Furthermore, the communication network of an agent is also endogenous. Our main finding is that when agents are sufficiently effective at social learning, structure emerges in the form of specialization. Some agents focus on coming up with new ideas while the remainder of the population focuses on imitating worthwhile ideas. Full article
(This article belongs to the Special Issue Computational Organization Theory)
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6426 KiB  
Article
Autonomy, Conformity and Organizational Learning
by Nobuyuki Hanaki and Hideo Owan
Adm. Sci. 2013, 3(3), 32-52; https://doi.org/10.3390/admsci3030032 - 05 Jul 2013
Cited by 8 | Viewed by 9179
Abstract
There is often said to be a tension between the two types of organizational learning activities, exploration and exploitation. The argument goes that the two activities are substitutes, competing for scarce resources when firms need different capabilities and management policies. We present another [...] Read more.
There is often said to be a tension between the two types of organizational learning activities, exploration and exploitation. The argument goes that the two activities are substitutes, competing for scarce resources when firms need different capabilities and management policies. We present another explanation, attributing the tension to the dynamic interactions among search, knowledge sharing, evaluation and alignment within organizations. Our results show that successful organizations tend to bifurcate into two types: those that always promote individual initiatives and build organizational strengths on individual learning and those good at assimilating the individual knowledge base and exploiting shared knowledge. Straddling the two types often fails. The intuition is that an equal mixture of individual search and assimilation slows down individual learning, while at the same time making it difficult to update organizational knowledge because individuals’ knowledge base is not sufficiently homogenized. Straddling is especially inefficient when the operation is sufficiently complex or when the business environment is sufficiently turbulent. Full article
(This article belongs to the Special Issue Computational Organization Theory)
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