Simulating the Evolution Process of Industrial Clusters Innovation Networks

2008 ◽  
Author(s):  
Gang Tian ◽  
Yong-An Zhang
Keyword(s):  
Industrial Clusters ◽  
Evolution Process ◽  
Innovation Networks

New Stage in Formation of Innovative Economy: Experience of France

2012 ◽  
pp. 61-71
Author(s):  
N. Lapina
Keyword(s):  
Higher Education ◽  
Scientific Research ◽  
Industrial Clusters ◽  
High Tech ◽  
Innovation Networks ◽  
Regional Innovation ◽  
The World ◽  
The Creation ◽  
Innovative Economy ◽  
Nicolas Sarkozy

The author eexamines the policy initiated by French President Nicolas Sarkozy and aimed at the development of innovation. This policy is reflected by the support of high-tech industries, by the creation of scientific-industrial clusters, by the development of regional innovation networks, by upgrading of higher education and scientific research. Altogether it is to raise the France’s competitive force and to turn it into one of the leading powers of the world.

THE CONSTRUCTION OF INNOVATION NETWORKS AND THE DEVELOPMENT OF TECHNOLOGICAL CAPABILITIES OF INDUSTRIAL CLUSTERS IN CHINA

2008 ◽  
Vol 05 (02) ◽  
pp. 179-199 ◽  
Author(s):  
XIAOBO WU ◽  
ZHIGANG GU ◽  
WEI ZHANG
Keyword(s):  
Industrial Clusters ◽  
Collective Learning ◽  
Innovation Networks ◽  
Technological Capabilities ◽  
Technology Acquisition ◽  
Need Support ◽  
Important Means ◽  
Effective Development ◽  
Technology Resources

Innovation network has been viewed as one of the most important means in improving technological capabilities for decades. Based on literature review, this paper presents a conceptual model on the relationships between the construction of innovation networks and the development of technological capabilities of industrial clusters in China. Applying this model we conduct a case study on reviewing history path of Zhejiang Haining leather industrial cluster. Conclusions can be drawn as follows: firstly, industrial clusters in China take on specific paradigm for technology acquisition by constructing external innovation networks; secondly, assimilation of acquired external technology resources and their translation into technological capabilities of clustered firms need support from internal innovation networks of industrial clusters; thirdly, quasi-external network, as a nexus between external and internal innovation networks of industrial clusters supported by collective learning, helps promote the effective development of technological capabilities of industrial clusters in China.

Policy-Driven University – Industry Linkages and Regional Innovation Networks in Korea

2009 ◽  
Vol 27 (4) ◽  
pp. 647-664 ◽  
Author(s):  
Dong-Won Sohn ◽  
Hyungjoo Kim ◽  
Jeong Hyop Lee
Keyword(s):  
Industrial Clusters ◽  
Innovation Networks ◽  
Regional Innovation ◽  
Main Determinant ◽  
Capital Region ◽  
Innovation Activities ◽  
Networks Analysis ◽  
University Industry ◽  
University Industry Linkages

In this paper we examine the role of the Korean government in creating university – industry linkages and in promoting the role of universities as knowledge providers in regional innovation systems. We investigate the different types of universities' roles in the capital region of Seoul and in the noncapital regions. We argue that government policy is the main determinant that drives Korean universities to play the role of knowledge provider for industrial innovation. This policy has also brought about regional differences in the way universities participate in innovation activities in the capital region and outside the capital region. In the Korean context, universities in noncapital regions act as a backbone for creating and managing regional innovation networks as well as a close and easily accessible knowledge provider to local industry. However, universities in the capital region play the role of a close knowledge provider only to local industry, while corporate research and development centres are the key players in developing and managing innovation networks in the capital region. To arrive at our conclusions we use social networks analysis and government document analysis to demonstrate the structure of innovation networks and to analyze two types of universities' roles in the regional innovation networks of four Korean industrial clusters.

scholarly journals Evolution process, dynamic factors, and agglomeration models of intelligent industrial clusters in the Zhongguancun Science Park

2020 ◽  
Vol 39 (9) ◽  
pp. 1485-1497
Author(s):  
Wensong SU ◽  
Yuchen GUO ◽  
Dingbo YUAN ◽  
Fan YANG ◽  
Shuang LIU ◽  
...  
Keyword(s):  
Industrial Clusters ◽  
Evolution Process ◽  
Science Park ◽  
Process Dynamic ◽  
Dynamic Factors

Industrial Clusters: a New Idea or an Old One?

1999 ◽  
Vol 29 (First Serie (1) ◽  
pp. 73-77 ◽  
Author(s):  
Gavin McCrone
Keyword(s):  
Industrial Clusters

Industrial Clusters: Scotland's Route to Economic Success

1999 ◽  
Vol 29 (First Serie (1) ◽  
pp. 43-58 ◽  
Author(s):  
Ron Botham ◽  
Bob Downes
Keyword(s):  
Industrial Clusters ◽  
Economic Success

Stochastic optimization of economic, financial, information, and logistics inter-cluster cooperation

2020 ◽  
Vol 26 (9) ◽  
pp. 1928-1950
Author(s):  
S.N. Yashin ◽  
Yu.V. Trifonov ◽  
E.V. Koshelev
Keyword(s):  
Public Policy ◽  
Population Growth ◽  
Stochastic Optimization ◽  
Optimization Model ◽  
Federal District ◽  
Industrial Clusters ◽  
Financial Information ◽  
Policy Management ◽  
Federal Districts ◽  
Further Development

Subject. This article deals with the simulation technologies based on the principles of stochastic optimization. They can bring a significant financial effect in the planning of investment development of both individual innovation and industrial clusters and federal districts of the country. Objectives. The article aims to investigate the mechanisms of inter-cluster cooperation within a single district. Methods. For the analysis, we used a stochastic optimization model in view of economic, financial, information, and logistics inter-cluster cooperation within a single federal district. Results. The considered stochastic optimization model of economic, financial, information, and logistics inter-cluster cooperation shows that the increase in fixed investment does not always cause population growth in the federal district regions. Conclusions. The use of a digital twin mechanism of inter-cluster cooperation can help avoid premature unreasonable public policy management decisions regarding the further development of innovation and industrial clusters.

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