List of Boxes
List of Figures
List of Tables
Acknowledgements
Abbreviations
Introduction
Chapter One: Methodology: towards a representation of complex system dynamics
Introduction
Complexity Science
The classical reductionist method
Beyond reductionist science
Sensitivity to initial conditions
Emergence
Autopoiesis
Feedback
Networks
Summarising the influences of complexity theory
Understanding system change as patterns
Complexity in economic systems
Time and Space
Critical Realism
Case similarity and difference
Convergence and divergence
Complex causation
Methodological conclusions
Mixed methods
Conclusions
Chapter Two: the Method - introducing Dynamic Pattern Synthesis (DPS)
Introduction
Cluster Analysis (CA)
Cluster Analysis: specific approaches
Distance measures
Hierarchical and non-hierarchical cluster analysis
Clustering algorithms
Dendrogram charts
Icicle chart
Using SPSS to calculate and compare cluster methods
Further considerations of the effects of clustering algorithms
Understanding variable relationships within cluster formulation
Repeating Cluster Analysis over time
Qualitative Comparative Analysis (QCA)
Crisp set QCA
Accounting for time in case based methods <lc+