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Organizationally-relevant configurations: the value of modeling local dependence

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Abstract

Configurations are important across all levels of organizations. Despite the interest in and importance of configurations in research for organizations, the empirical methods for assessing and classifying configurations has not kept pace with the theoretical advancements. Theory suggests that configurations must include aligned elements that have local dependence. Local dependence is defined as the interrelationships among variables necessary to form an internally consistent configuration. We explain how latent class cluster analysis (LCCA) enables modeling for local dependence and provides theoretical and methodological value for configurations researchers. Using primary data from two samples, we demonstrate that LCCA with local dependence outperforms traditional cluster analysis-based approaches. Our method can be used for detecting configurations at a variety of organizational levels (e.g. nation, industry, firm, and group).

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  1. Department of Marketing and Management, Miller College of Business, Ball State University, 2000 W. University Ave., Muncie, IN, 47306, USA

    Pankaj C. Patel

  2. College of Business, University of Louisville, Louisville, KY, 40292, USA

    Sherry M. B. Thatcher

  3. Psychology Department, Santa Clara University, 500 El Camino Real, Santa Clara, CA, 95050, USA

    Katerina Bezrukova

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  1. Pankaj C. Patel
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  2. Sherry M. B. Thatcher
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Patel, P.C., Thatcher, S.M.B. & Bezrukova, K. Organizationally-relevant configurations: the value of modeling local dependence. Qual Quant 47, 287–311 (2013). https://doi.org/10.1007/s11135-011-9520-3

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