The risk of cascading breakdown in industrial cluster innovation networks: A complex networks perspective

It is of significantly concern that an industrial cluster would be broken down due to the bankruptcy of a very few enterprises through the cascading failure process. Based on the complex network theory, the evolution mechanism of cluster innovation networks is analyzed, and a model of cascading failure in the cluster innovation networks is developed. This study shows that: (1) there is a close relation between the evolution mechanism of cluster innovation networks and the risk-resistant capability of the networks, and the process of evolving based on the principle of “preferential attachment” brings about the scale-free character of the cluster innovation networks; (2) the uniform distribution of enterprises strength contributes to improve the invulnerability of the innovation networks; (3)there is a threshold of inter-firm connection density that intensive inter-firm relationship contributes to the risk-resistant ability of innovation networks up to a threshold and beyond which more intensive inter-firm relationship can lead to a decrease in risk-resistant ability of innovation networks. Finally, it is found that the key factors causing the cascading breakdown of cluster innovation networks can be summarized into three areas: the distribution of inter-firm connections, the distribution of firms' risk-resistant capabilities, and the innovation capabilities of the enterprises within the cluster. Some recommendations regarding to improving the robustness of cluster innovation networks are proposed in order to avoid the occurrence of cascading breakdown in industrial cluster.

[1]  Cai Ning.  THE STRUCTURE AND FUNCTION OF INDUSTRIAL CLUSTERS' COMPLEX NETWORKS , 2006 .

[2]  Fred Steward,et al.  Social Interaction and Organisational Change: Aston Perspectives on Innovation Networks , 2001 .

[3]  N. Economides.  The Economics of Networks , 1995 .

[4]  X. Luo,et al.  Do Birds of a Feather Flock Higher? The Effects of Partner Similarity on Innovation in Strategic Alliances in Knowledge-Intensive Industries , 2009 .

[5]  Y. Moreno,et al.  Instability of scale-free networks under node-breaking avalanches , 2001 .

[6]  N. Economides.  The economics of networks , 1996 .

[7]  Nicholas Economides,et al.  Special issue on network economics: Business conduct and market structure , 1996 .

[8]  Adilson E Motter.  Cascade control and defense in complex networks. , 2004, Physical review letters.

[9]  Morten T. Hansen,et al.  Knowledge Transfer in Intraorganizational Networks : Effects of Network Position and Absorptive Capacity on Business Unit Innovation and Performance , 2007 .

[10]  Roy Rothwell,et al.  External networking and innovation in small and medium-sized manufacturing firms in Europe , 1991 .

[11]  Ying-Cheng Lai,et al.  Attack vulnerability of scale-free networks due to cascading breakdown. , 2004, Physical review. E, Statistical, nonlinear, and soft matter physics.

[12]  Hui-jun Sun,et al.  Cascade and breakdown in scale-free networks with community structure. , 2006, Physical review. E, Statistical, nonlinear, and soft matter physics.

[13]  Y. Baba,et al.  Systemic innovation and cross-border networks : transcending markets and hierarchies to create a new techno-economic system , 1989 .

[14]  R. Boschma.  Proximity and Innovation: A Critical Assessment , 2005 .

[15]  A. Markusen.  Sticky Places in Slippery Space: A Typology of Industrial Districts* , 1996 .

[16]  R. Martin,et al.  Path dependence and regional economic evolution , 2006 .

[17]  Duncan J. Watts,et al.  Collective dynamics of ‘small-world’ networks , 1998, Nature.

[18]  Zhang Zhuo.  Flexible Weighted Complex Network Evolving Model and Simulation , 2009 .

[19]  Albert,et al.  Emergence of scaling in random networks , 1999, Science.

[20]  Roberto Camagni,et al.  Innovation Networks , 1991 .

[21]  Gernot Grabher.  The embedded firm : on the socioeconomics of industrial networks , 1995 .

[22]  Guanrong Chen,et al.  Understanding and preventing cascading breakdown in complex clustered networks. , 2008, Physical review. E, Statistical, nonlinear, and soft matter physics.

[23]  Andaç T. Arıkan,et al.  Interfirm Knowledge Exchanges and the Knowledge Creation Capability of Clusters , 2009 .

[24]  J. Christensen.  Proximity and Innovation: A Critical Assessment , 2008 .

[25]  Daniel A. Levinthal,et al.  ABSORPTIVE CAPACITY: A NEW PERSPECTIVE ON LEARNING AND INNOVATION , 1990 .

[26]  R. Rothwell.  Successful industrial innovation: critical factors for the 1990s , 1992 .

[27]  Liang Zhang,et al.  Attack vulnerability of scale-free networks due to cascading failures , 2008 .

[28]  Gianni Lorenzoni,et al.  Creating a Strategic Center to Manage a Web of Partners , 1995 .

[29]  Wenpin Tsai.  Knowledge Transfer in Intraorganizational Networks: Effects of Network Position and Absorptive Capacity on Business Unit Innovation and Performance , 2001 .

[30]  C. Freeman.  Networks of innovators: A synthesis of research issues , 1991 .

[31]  Adilson E Motter,et al.  Cascade-based attacks on complex networks. , 2002, Physical review. E, Statistical, nonlinear, and soft matter physics.

[32]  Antonio Messeni Petruzzelli,et al.  Proximity and knowledge gatekeepers: the case of the Polytechnic University of Turin , 2008, J. Knowl. Manag..