Capturing non-linear temporally embedded processes in organizations using recurrence quantification analysis

Abstract

ABSTRACT Despite the growing consensus that the majority of psychological phenomena at work are temporally embedded and highly dynamic, existing research is often based on simplified theoretical and methodological models, which take limited account of process dynamics and especially non-linear growth trajectories. In this paper, we highlight the potentials of using recurrence quantifications analysis (RQA) and an extension of RQA – cross-recurrence quantification analysis (CRQA) – for researching process dynamics in organizations. (C)RQA is a powerful technique that can be used to both visualize and quantify time-series data such as repeated measurements of psychological states or sequentially coded dyadic and team interactions. To illustrate the manifold opportunities of (C)RQA, we present three application examples focusing on individuals as systems, dyads as systems, and teams as systems. Specifically, we highlight how (C)RQA can be applied to individual diary data, to leader-follower communication dynamics observed during annual appraisal interviews, and to high-density coded team interactions observed during organizational meetings. We discuss the strengths and limitations of (C)RQA and provide recommendations for researchers interested in using the method.