Self-organization of industrial clustering in a transition economy: A proposed framework and case study evidence from China
Zheng He,
Lez Rayman-Bacchus and
Yiming Wu
Research Policy, 2011, vol. 40, issue 9, 1280-1294
Abstract:
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).
Keywords: Cluster evolution; Complexity theory; Self-organization (search for similar items in EconPapers)
Date: 2011
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0048733311001582
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:respol:v:40:y:2011:i:9:p:1280-1294
DOI: 10.1016/j.respol.2011.07.008
Access Statistics for this article
Research Policy is currently edited by M. Bell, B. Martin, W.E. Steinmueller, A. Arora, M. Callon, M. Kenney, S. Kuhlmann, Keun Lee and F. Murray
More articles in Research Policy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().