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    An Integrated Approach to Testing Dynamic, Multilevel Theory: Using Computational Models to Connect Theory, Model, and Data

    78509.pdf (575.0Kb)
    Access Status
    Open access
    Authors
    Ballard, T.
    Palada, H.
    Griffin, Mark
    Neal, A.
    Date
    2019
    Type
    Journal Article
    
    Metadata
    Show full item record
    Citation
    Ballard, T. and Palada, H. and Griffin, M. and Neal, A. 2019. An Integrated Approach to Testing Dynamic, Multilevel Theory: Using Computational Models to Connect Theory, Model, and Data. Organizational Research Methods.
    Source Title
    Organizational Research Methods
    DOI
    10.1177/1094428119881209
    ISSN
    1094-4281
    Faculty
    Faculty of Business and Law
    School
    Future of Work Institute
    URI
    http://hdl.handle.net/20.500.11937/78407
    Collection
    • Curtin Research Publications
    Abstract

    Some of the most influential theories in organizational sciences explicitly describe a dynamic, multilevel process. Yet the inherent complexity of such theories makes them difficult to test. These theories often describe multiple subprocesses that interact reciprocally over time at different levels of analysis and over different time scales. Computational (i.e., mathematical) modeling is increasingly advocated as a method for developing and testing theories of this type. In organizational sciences, however, efforts that have been made to test models empirically are often indirect. We argue that the full potential of computational modeling as a tool for testing dynamic, multilevel theory is yet to be realized. In this article, we demonstrate an approach to testing dynamic, multilevel theory using computational modeling. The approach uses simulations to generate model predictions and Bayesian parameter estimation to fit models to empirical data and facilitate model comparisons. This approach enables a direct integration between theory, model, and data that we believe enables a more rigorous test of theory.

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