Latent Class Markov Modeling for Studying Dynamic Organizational Configurations

Le résumé fourni par la source

Interest in configurational approaches has seen a resurgence in organizational studies. Techniques such as QCA and fsQCA, commonly used to analyze organizational configurations, are static in nature and temporal extensions are limited. However, organizational researchers are often concerned with changes in organizational configurations over time, especially those interested in organization fit under conditions of dynamic external environments, or the development of organizational configurations during organizational emergence or evolution. The authors present latent class Markov modelling (LCMM) as a research method for organizational theory development, through dynamic analysis of organizational configurations. LCMM allows scholars to study certain forms of path dependency of configurational change, as well as antecedents or boundary conditions of such change. An empirical application, based on commonly available software, analyzing the trajectories of resource-based competitiveness configurations for a large longitudinal sample of new ventures demonstrates the utility of the method to abductively contribute to theory development.

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