Self-organization of industrial clustering in a transition economy: A proposed framework and case study evidence from China

The evolution of the industrial cluster has long been a comparatively difficult problem due to its complexity and the differing particularities of individual clusters. Based on a study of two clusters, this paper draws some logic and ideas from complexity theory and develops a generic framework to explain cluster self-organization. We present the cluster as a complex adaptive system (CAS) that experiences self-organization through four critical features: landscape design, positive feedback, boundary constraints, and novel outcomes. We then use this framework to analyze two clusters from the ICT sector within China's transitional economy. Finally, the paper draws out a few implications for our understanding of cluster development processes. In particular, we stress the importance of both path-dependence (due to initial conditions) and the unpredictability of developmental paths (due to the uniqueness of each cluster).

► We examine the industrial cluster as a complex adaptive system. ► We then use self-organization concepts to explain the evolution of clusters using case studies. ► From this we develop a generic framework of cluster self-organization. ► Our generic framework comprises: landscape design, positive feedback, boundary constraints, novel outcomes. ► We draw out new policy implications for understanding cluster development processes.