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Knowledge sharing in a dynamic, multi-level organization: an agent-based modeling approach

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Abstract

Organizations are complex systems comprised of many dynamic and evolving interaction patterns among individuals and groups. Understanding these interactions and how patterns, such as informal structures and knowledge sharing behavior, emerge are crucial to creating effective and efficient organizations. Studying organizations as complex systems is a challenge as we must account for hierarchically nested structures, multi-level processes, and changes over time. Informal structures interact with individual attitudes to influence organizational processes such as knowledge sharing, a process vital to organizational performance and innovation. To explore such organizational dynamics, we integrate dynamic social networks, a cognitive model of attitude formation and change, and a physical environment into an agent-based model, the combination of which represents a novel way to study organizations. We use a hospital in southwest Virginia as our case study. The agents in the model are the healthcare workers within the hospital and agent movement occurs over the physical environment of the hospital. Results show that the simulated hospital is resilient to impacts from employee attrition but that communication approaches must be thought through strategically so as not to hinder knowledge sharing. For managers, this type of modeling approach can provide resource and planning guidance in regards to attrition-based strategies and communication approaches.

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Notes

  1. Sitters are healthcare workers that monitor and interact with patients (particularly high-need patients).

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Acknowledgements

This research was supported by an Early Career Award through the Army Research Institute (W119NF-16-10574). The authors would like to thank Gizem Korkmaz and Daniel Chen for their technical guidance, Bryan Lewis for his help in acquiring the data and early discussions of its implementation in our model, and Sallie Keller for her review of the paper. The author’s affiliation with The MITRE Corporation is provided for identification purposes only and is not intended to convey or imply MITRE’s concurrence with, or support for, the positions, opinions, or viewpoints expressed by the author. The research in this paper was undertaken prior to Emily Molfino’s employment at the U.S. Census Bureau. Any opinions and conclusions expressed herein are those of the authors and do not necessarily represent those of the U.S. Census Bureau. The research in this paper does not use any confidential Census Bureau information.

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Authors and Affiliations

  1. The MITRE Corporation, McLean, VA, 22102, USA

    Bianica Pires

  2. Biocomplexity Institute and Initiative, University of Virginia, Arlington, TX, 22209, USA

    Joshua Goldstein

  3. U.S. Census Bureau, Suitland, MD, 20746, USA

    Emily Molfino

  4. Old Town Psychology, Alexandria, 22314, VA, USA

    Kathryn Ziemer

  5. Biocomplexity Institute and Initiative, University of Virginia, Charlottesville, VA, 22904, USA

    Mark Orr

  6. Graduate Program in Health and Business Administration, Army-Baylor University, Fort Sam Houston, TX, 78234, USA

    José Jiménez

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  1. Bianica Pires
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Pires, B., Goldstein, J., Molfino, E. et al. Knowledge sharing in a dynamic, multi-level organization: an agent-based modeling approach. Comput Math Organ Theory 30, 75–100 (2024). https://doi.org/10.1007/s10588-023-09373-8

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