Dynamic patterns of flow in the workplace: Characterizing within-individual variability using a complexity science approach

By L. Ceja, J. Navarro. 2011

97 citations recorded by the source corpus.

Summary As a result of the growing interest in studying employee well-being as a complex process that portrays high levels of within-individual variability and evolves over time, this present study considers the experience of flow in the workplace from a nonlinear dynamical systems approach. Our goal is to offer new ways to move the study of employee well-being beyond linear approaches. With nonlinear dynamical systems theory as the backdrop, we conducted a longitudinal study using the experience sampling method and qualitative semistructured interviews for data collection; 6981 registers of data were collected from a sample of 60 employees. The obtained time series were analyzed using various techniques derived from the nonlinear dynamical systems theory (i.e., recurrence analysis and surrogate data) and multiple correspondence analyses. The results revealed the following: 1) flow in the workplace presents a high degree of withinindividual variability; this variability is characterized as chaotic for most of the cases (75%); 2) high levels of flow are associated with chaos; and 3) different dimensions of the flow experience (e.g., merging of action and awareness) as well as individual (e.g., age) and job characteristics (e.g., job tenure) are associated with the emergence of different dynamic patterns (chaotic, linear and random). Copyright # 2011 John Wiley & Sons, Ltd.

Subfields: Cognitive Neuroscience, Developmental and Educational Psychology, Experimental and Cognitive Psychology

View Paper: https://www.semanticscholar.org/paper/2bf1ad5ee6f324cbef48b437af260a4f8f01443b

How researchers see this paper

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In Cognitive Neuroscience

  1. David T. Wagner
  2. R. Ilies

In Developmental and Educational Psychology

  1. Michael D. Johnson
  2. R. Ilies
  3. L. Ceja

In Experimental and Cognitive Psychology

  1. Kelly Schwind Wilson
  2. David T. Wagner
  3. Michael D. Johnson
  4. Daniel R. Ilgen
  5. R. Ilies
  6. L. Ceja
  7. T. Judge
  8. Brent A. Scott

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