IDEAS home Printed from https://ideas.repec.org/a/jas/jasssj/2014-107-3.html
   My bibliography  Save this article

Multi-Agent Based Simulation of Organizational Routines on Complex Networks

Author

Listed:
  • Dehua Gao
  • Xiuquan Deng
  • Qiuhong Zhao
  • Hong Zhou
  • Bing Bai

Abstract

Organizational routines are collective phenomena involving multiple individual actors. They are crucial in helping to understand how organizations behave and change in a certain period. In this paper, by regarding the individual habits of multiple actors involved as fundamental building blocks, we consider organizational routines from an ‘emergence-based’ perspective. We emphasise the impacts of connections or network topologies among individual actors in the formation of organizational routines, and carry out a multi-agent based simulation analysis of organizational routines on complex networks. We consider some important factors such as inertia resulted from individual memories, component complexity of organizational tasks, turnover of individual actors, the impacts of both heterogeneity and improvisation of individual actors involved, and the dynamical properties of the network topologies within which individual actors are located. The results of our research show that network topologies among individual actors do determine the dynamic characteristics of organizational routines. Although the fact is that the mechanisms beneath this are also influenced by some main factors like the memory capacity of individual actors and the component complexity of organizational tasks that these individual actors should deal with repetitively, and that the total costs for the organization to bear during their implementation of organizational tasks are variant, the routine system on scale-free networks can always have a better performance, and obtain a much higher coherency and routinization level of collective behaviours, even in the case of turnover of individual actors. In addition, when individual actors involved are heterogeneous, the routine system on scale-free networks would also exhibit a strong anti-disturbance ability, no matter whether there are minor improvisations from these individual actors or not. Nevertheless, a large number of improvisations enable individual actors to act in some more individualistic manners, and destroy the routine system as a result.

Suggested Citation

  • Dehua Gao & Xiuquan Deng & Qiuhong Zhao & Hong Zhou & Bing Bai, 2015. "Multi-Agent Based Simulation of Organizational Routines on Complex Networks," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 18(3), pages 1-17.
  • Handle: RePEc:jas:jasssj:2014-107-3
    as

    Download full text from publisher

    File URL: https://www.jasss.org/18/3/17/17.pdf
    Download Restriction: no
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Dehua Gao & Flaminio Squazzoni & Xiuquan Deng, 2018. "The role of cognitive artifacts in organizational routine dynamics: an agent-based model," Computational and Mathematical Organization Theory, Springer, vol. 24(4), pages 473-499, December.
    2. Dehua Gao & Aliakbar Akbaritabar, 2022. "Using agent-based modeling in routine dynamics research: a quantitative and content analysis of literature," Review of Managerial Science, Springer, vol. 16(2), pages 521-550, February.
    3. Bing Bai & Byungjoon Yoo & Xiuquan Deng & Iljoo Kim & Dehua Gao, 2016. "Linking routines to the evolution of IT capability on agent-based modeling and simulation: a dynamic perspective," Computational and Mathematical Organization Theory, Springer, vol. 22(2), pages 184-211, June.
    4. Dehua Gao & Flaminio Squazzoni & Xiuquan Deng, 2018. "The Intertwining Impact of Intraorganizational and Routine Networks on Routine Replication Dynamics: An Agent-Based Model," Complexity, Hindawi, vol. 2018, pages 1-23, November.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:jas:jasssj:2014-107-3. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Francesco Renzini (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.