Grouping Interdependent Tasks: Using Spectral Graph Partitioning to Study Complex Systems

Abstract

This article uses spectral graph partitioning to advance strategic management research, and focuses on the study of complex systems that contain strongly connected components with component interactions that are weighted and directed. The spectral graph partitioning method complements existing methods, especially, when external architectural artifacts do not exist or are less than certain. We illustrate this methodology using a U.S. airline’s production system. We highlight some useful metrics and show how researchers can apply this method to generate additional architectural insights.

Keywords: system architecture; complex systems; modularity; graph partitioning; interdependence; complexity; sequential tasks; reciprocal tasks