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

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  • He, Zheng
  • Rayman-Bacchus, Lez
  • Wu, Yiming

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).

Suggested Citation

  • He, Zheng & Rayman-Bacchus, Lez & Wu, Yiming, 2011. "Self-organization of industrial clustering in a transition economy: A proposed framework and case study evidence from China," Research Policy, Elsevier, vol. 40(9), pages 1280-1294.
    • Handle: RePEc:eee:respol:v:40:y:2011:i:9:p:1280-1294
    DOI: 10.1016/j.respol.2011.07.008
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    Cited by:

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    2. Qingling Shi & Xiangzheng Deng & Chenchen Shi & Shiyi Chen, 2015. "Exploration of the Intersectoral Relations Based on Input-Output Tables in the Inland River Basin of China," Sustainability, MDPI, vol. 7(4), pages 1-18, April.
    3. Fang Wei & Xiao Limin, 2018. "Simulation of Knowledge Transfer Process Model Between Universities: A Perspective of Cluster Innovation Network," Complexity, Hindawi, vol. 2018, pages 1-13, December.
    4. Kristina Grumadaitė & Giedrius Jucevičius, 2022. "Strategic Approaches to the Development of Complex Organisational Ecosystems: The Case of Lithuanian Clusters," Sustainability, MDPI, vol. 14(23), pages 1-13, November.
    5. Corral de Zubielqui Graciela & Jones Janice & Statsenko Larissa, 2016. "Managing Innovation Networks for Knowledge Mobility and Appropriability: A Complexity Perspective," Entrepreneurship Research Journal, De Gruyter, vol. 6(1), pages 75-109, January.
    6. Vlaisavljevic, Vesna & Medina, Carmen Cabello & Van Looy, Bart, 2020. "The role of policies and the contribution of cluster agency in the development of biotech open innovation ecosystem," Technological Forecasting and Social Change, Elsevier, vol. 155(C).
    7. Grumadaitė Kristina & Jucevičius Giedrius, 2017. "Preconditions for Emergence of Lithuanian Clusters: from Informal Cooperation to Its Legitimation," Management of Organizations: Systematic Research, Sciendo, vol. 77(1), pages 37-56, June.
    8. Cha, Hongryol, 2020. "A paradigm shift in the global strategy of MNEs towards business ecosystems: A research agenda for new theory development," Journal of International Management, Elsevier, vol. 26(3).

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