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Summary
This summary is machine-generated.

This study models team coordination using a modified Kuramoto model, finding a critical team size where synchronization is lost. Results suggest larger optimal team sizes than previously proposed in management science.

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Area of Science:

  • Complex systems
  • Organizational dynamics
  • Network science

Background:

  • Understanding the limits of team coordination is crucial for organizational efficiency.
  • Existing models often simplify the complex interactions within teams.
  • The Kuramoto model provides a framework for analyzing synchronization in coupled systems.

Purpose of the Study:

  • To develop and calibrate a Kuramoto-model-inspired representation of peer-to-peer collaboration.
  • To identify the critical point at which team coordination breaks down.
  • To compare model predictions with established concepts like the span of control.

Main Methods:

  • Modified the Kuramoto model to account for cognitive resource dispersion (input/output node degrees).
  • Used data on maximum team sizes where coordination fails for calibration.
  • Analytically determined the critical point of synchronization loss.
  • Validated the model against the 'span of control' in hierarchical organizations.

Main Results:

  • Identified a critical point indicating a loss of synchronization as team size increases.
  • Calibrated the model's coupling parameter using empirical data on maximum team sizes.
  • The model suggests larger maximum team sizes than early management theories.
  • Findings align with studies focusing on direct supervisor-subordinate relationships.

Conclusions:

  • The modified Kuramoto model offers insights into the scalability of peer-to-peer collaboration.
  • Coordination breakdown in teams can be understood as a loss of synchronization.
  • Results challenge traditional views on optimal team size, emphasizing dyadic interactions.