scholarly journals The Impact of Innovative Industrial Cluster Policy on Regional Innovation: Evidence from a Quasi-Natural Experiment in China

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Huan Wang ◽  
Jinhua Guo

As important carriers of local innovation activities, innovative industrial clusters are attracting increasing attention. Therefore, several countries have started promotion policies for innovative industrial clusters. However, there are few empirical studies on relevant policies. This paper investigates the impact of China’s “innovative industrial cluster pilot” (IICP) policy on regional innovation. Taking the implementation of IICP policy as a quasi-natural experiment and using the panel data of 266 prefecture-level cities in China in 2008-2019, this paper provides strong evidence that IICP policy promotes regional innovation. The conclusion still holds after a battery of robustness checks. The heterogeneity test shows that the promoting effect of IICP policy on innovation is more significant in central and western region than in eastern region. Moreover, the lower the city administrative level and the lower the dependence on natural resource, the more prominent the innovation effect of IICP policy. Further, the mechanism test shows that the IICP policy can promote regional innovation indirectly by strengthening government support for innovation and attracting the agglomeration of science and technological talents, but the mediation effect of industrial structure has not been verified.

2016 ◽  
Vol 2016 ◽  
pp. 1-19 ◽  
Author(s):  
Xiaohui Jia ◽  
Minghui Jiang ◽  
Lei Shi

From the perspective of the interactive cooperation among subjects, this paper portrays the process of cooperative innovation in industrial cluster, in order to capture the correlated equilibrium relationship among them. Through the utilization of two key tools, evolutionary stable strategy and replicator dynamics equations, this paper considers the cost and gains of cooperative innovation and the amount of government support as well as other factors to build and analyze a classic evolutionary game model. On this basis, the subject’s own adaptability is introduced, which is regarded as the system noise in the stochastic evolutionary game model so as to analyze the impact of adaptability on the game strategy selection. The results show that, in the first place, without considering subjects’ adaptability, their cooperation in industrial clusters depends on the cost and gains of innovative cooperation, the amount of government support, and some conditions that can promote cooperation, namely, game steady state. In the second place after the introduction of subjects’ adaptability, it will affect both game theory selection process and time, which means that the process becomes more complex, presents the nonlinear characteristics, and helps them to make faster decisions in their favor, but the final steady state remains unchanged.


2020 ◽  
pp. 102452942094949 ◽  
Author(s):  
Sergey Sosnovskikh ◽  
Bruce Cronin

Culture, attitudes and perceptions have an underappreciated effect on industrial cluster policies particularly in transition economies, where long-established local social norms are confronted with hard-pressed external imperatives. This paper examines the impact of cultural and governmental peculiarities in the Russian context on the development of special economic zones and industrial parks. Based on some stylized facts about the Russian context, in-depth interviews and surveys of the managing companies and tenants of all industrial clusters in Russia, we find cultural and governmental characteristics emerge as major influences on the effective development of industrial cluster policies. We develop an adapted industrial cluster model that accommodates these factors and suggests a policy pathway for mitigation.


2016 ◽  
Vol 14 (2) ◽  
pp. 74-83 ◽  
Author(s):  
Sri Hartono ◽  
Agus Sobari

Many studies show that industrial clusters have been successfully promoting the progress of small and medium enterprises (SMEs). Therefore, many governments around the world, including Indonesia, enthusiastically perform comparative studies of cluster policy. Thus, it is important to understand the characteristics of the business of small and medium industries as input in formulating the policy of industrial clusters. Research objectives are focused on the early stages of analysis as to whether the cluster of wood and rattan furniture industry which has existed long enough in Jepara, Central Java, Indonesia, has formed a pattern of awareness among employers in considering the benefits proportionally between cooperation and competition. In various scientific literature reviews, this issue was named by the term coopetition. Thus, the benefits of this research are useful in formulating policy toward strengthening the industrial cluster furniture and rattan towards a more integrative of industrial clusters, and supporting industries involve complex, well integrated backward (backward linkage) and integrated into the front (forward linkage). In the end, it is expected that increasingly mature industrial clusters of wooden furniture and rattan will be transformed into a form of industrial agglomeration and positively impact on strengthening the competitiveness of the furniture industry widely influential in regional and national economy. The test results show that nearly all of the dimensions of a differentiator (discriminant factor) are significant by influence on differentiating into three patterns of interaction between companies in the cluster of wooden furniture and rattan, while there is only one dimension that is not significant, i.e., the horizontal dimension of cooperation. These results indicate that the industrial cluster of wooden furniture and rattan in Jepara have long formed, where the cycles and patterns of cooperation are factors that could indicate variations in differences concerning perceptions of entrepreneurs in the wood and rattan furniture cluster. Results of the analysis with the approach of the discriminant also show the forming awareness of employers about balancing the important role of competition. It is, as well as cooperation in the industrial cluster wood and rattan furniture from Jepara being already cycle of clusters, characterized by maturity. The cooperation is characterized by bilateral, multilateral, and vertical indicating that the cluster is ready to metamorphose into a form more complicated than an agglomeration. This condition needs to be examined further to see the impact of the maturity cycle of an industrial cluster and more complex patterns of cooperation towards the formation prerequisite agglomeration, and its impact on industrial performance and competitiveness clusters in the aggregate, as well as the economic development of the region


2019 ◽  
pp. 36-47
Author(s):  
M.B. Trachenko ◽  
O.D. Gaisha

The article is solving an actual problem — development of a system of indicators to evaluate the effectiveness of financing industrial clusters in Russia. The article analyzes the cluster models of Russian and foreign authors, identifies their strengths and weaknesses. A universal information model of the cluster was developed, reflecting the interaction of the participants among themselves and with external stakeholders of the cluster development. The developed model has three control loops: internal cluster stakeholders, cluster, cluster's region. Each has the specificity of the movement of inventory and cash flows, information interaction in the implementation of cluster policy, and reflects the interests of various stakeholders of industrial clusters. The model lays the groundwork to justify a three-tier system of indicators to evaluate the effectiveness of financing industrial clusters. The subsystems of the indicators of the impact of the industrial cluster on the regional economy, of the indicators of the industrial cluster development and the subsystem of the indicators of the financial condition of enterprises participating in the industrial cluster are highlighted in the proposed system. The study used the methods of bibliographic and logical analysis, synthesis and systems approach, mathematical methods of statistical data processing. The developed system of indicators for assessing the effectiveness of financing industrial clusters can be used to conduct current and subsequent monitoring of financing the implementation of cluster programs, to prepare decisions on the allocation of budgetary funds by state and municipal authorities, and to potential investors to determine the most promising investment instruments.


2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
You-Qun Wu ◽  
Huai-Xin Lu ◽  
Xin-Lin Liao ◽  
Jia-Bao Liu ◽  
Jia-Ming Zhu

Based on the theoretical mechanism analysis of FDI, regional innovation, and green economic efficiency, this article uses China’s provincial panel data to calculate the provincial green economic efficiency level based on the three-stage DEA method and uses the system GMM model, intermediary effect model, and threshold model to empirically test the specific effects and transmission paths of FDI on the efficiency of the green economy. Research shows that FDI is one of the important factors that promote the improvement of green economic efficiency. Subregional tests have found that FDI has a significant regional heterogeneity in promoting the efficiency of the green economy. The mediation effect test found that the mediation effect of regional innovation is significant, and FDI can significantly promote the growth of green economic efficiency through regional innovation. The threshold effect analysis found that there are significant and effective double thresholds for regional economic levels, and the impact of FDI on green economic efficiency is heterogeneous within different threshold intervals. The research conclusions provide new inspiration for China to allocate FDI more rationally and efficiently under the new development pattern.


2012 ◽  
Vol 3 (3) ◽  
pp. 21-36 ◽  
Author(s):  
Neil Reid ◽  
Bruce W. Smith

Industrial clusters have received considerable attention as a regional development strategy. While their efficacy has been debated by academics, clusters have become popular among practitioners. Despite clusters’ acceptance, there have been few attempts to measure their success or their impact on constituent firms. This paper outlines and discusses the metrics developed to evaluate the success of the northwest Ohio greenhouse cluster. The cluster was launched in 2004 to help the industry become more competitive though collaborative problem solving. In identifying success metrics, the authors were cognizant of the fact that they had to reflect the cluster’s objectives and goals. Thus metrics that measured the impact of branding and marketing efforts, reducing energy costs, and increasing collaboration among cluster stakeholders were developed. The work reported in this paper is only the beginning phases of a longer-term, on-going effort to track the progress and success of the northwest Ohio greenhouse cluster.


2014 ◽  
Vol 9 (2) ◽  
pp. 141-159 ◽  
Author(s):  
Maw-Shin Hsu ◽  
Yung-Lung Lai ◽  
Feng-Jhy Lin

Purpose – The purpose of this study was to explore the impact of the formation of industrial clusters on the obtainment of professional human resources, to verify the impact of human resources on clustering relationships and firm’s performance and to understand whether the formation of clusters can contribute to the obtainment of professional human resources and the improvement of competitiveness of enterprises. It was expected that solutions could be found to make new contributions through the verification of special economic zones (SEZs). Design/methodology/approach – Using manufacturers in Taiwan’s SEZs as the subjects, this study explored the impact on the obtainment of professional human resources after the formation of industrial clusters in SEZs, through conducting and empirical study with a questionnaire survey. Findings – The professional human resources are the essential factor for the formation of industrial clusters and the improvement of competitiveness. This study also confirmed that industries can have professional human resources by industrial clustering and that this will produce a positive impact on the enterprise clustering relationships, which can also have a positive impact on firm’s performance and can enhance the enterprise’s competitive advantage. Practical implications – Industrial clustering is the key factor to attract professional human resources; industrial clusters can enhance firm’s performance; and professional human resources affect firm’s performance of enterprises. Originality/value – No study has discussed the topic of clusters from the perspective of SEZs also including six export processing zone (EPZ) parks in Taiwan. This study discussed the topic using theories relating to clustering and human resources. The formation of industrial clusters can result in higher competitiveness in the face of the global market. The EPZ industrial cluster provides an excellent investment environment. Coupled with one-stop express services and geographic advantage, the land-use rate is up to 97 per cent and the per hectare output value amounts to NTD 3.2 billion, setting a successful example of an industrial cluster.


2021 ◽  
Vol 2021 (3) ◽  
Author(s):  
I. Maksymenko ◽  
O. Shkulipa ◽  
O. Pavlenko ◽  
O. Dreval

The article analyzes the impact of territorial and innovative aspects on the formation of an industrial cluster. Improving the efficiency of territorial development is one of the biggest problems of the modern economy and management. The system of consideration of territorial and innovative aspects of industrial cluster formation is considered in the article. It is determined that an important component is the institutional changes, the use of appropriate methods and tools of state influence, aimed at the process of clustering in the study areas. Particular importance is attached to the study of the implementation of the phased process of cluster formation. The need for effective functioning of the state mechanism is revealed. Statistical indicators of Ukraine's development are presented, on the basis of which the components for assessing the development potential of the territory are analyzed. In particular, a model of dependence of the territory's potential on a number of indicators is proposed. The influence of the development of the innovation aspect on the formation of the attractiveness of the region is studied. It is proved that the assessment of the region's potential correlates with the costs of innovation in this region. The results of the study showed that the cluster approach allows to consider and describe the industries applied to a particular area and its features. Most often, clusters of enterprises are classified according to such parameters as geographical location, availability of capital, proximity of suppliers, competitiveness, access to specialized services, development of labor potential, availability of specialized educational institutions and research organizations, industry affiliation. The application of integrated assessment in this study made it possible to identify highly promising, medium-promising and low-promising areas, ie to determine the stages of formation of industrial clusters. The article also analyzed statistical indicators such as innovation activity of industrial enterprises, labor force, research and development costs. In particular, the coincidence of the dynamics of changes in these indicators was determined. This is the basis for taking into account territorial and innovative aspects in the formation of industrial clusters.


2021 ◽  
Vol 251 ◽  
pp. 01025
Author(s):  
Pan Zhang

The development of innovative industrial clusters is an important way to promote the development of innovative enterprises in China. At the same time, it also has definite practical significance to encourage regional innovation. This paper uses the CNKI database as the research platform, and selects the literature in the field of innovative industrial clusters from 2002 to March 1, 2021 as the research object, using bibliometrics method and CiteSpace software tools to analyze the number of publications, cooperative institutions, research hotspots, and trends. Perform visual analysis and systematically comb the progress status of innovative industrial clusters and predict future research trends in China. The research results show that the research on the basic theories of innovation industry clusters is not solid enough in China, and the cooperation between scientific research institutions needs to be strengthened; in addition, in this paper, the research process is divided into the embryonic exploration period and the development period for analysis, and then found it Related research hotspots mainly focus on innovative industrial clusters and industrial cluster theory, innovative industrial cluster development areas, innovative enterprises and government policies.


2021 ◽  
Vol 13 (19) ◽  
pp. 11089
Author(s):  
Zhen Xu ◽  
Xiang Zhu ◽  
Guoen Wei ◽  
Xiao Ouyang

Improving regional innovation efficiency is the key to developing an innovative country. Exploring the spatio-temporal evolution characteristics of regional innovation efficiency is crucial in the formulation of regional policies and the choice of innovation models. This study used the superdata envelopment analysis method with undesirable outputs in evaluating the innovation efficiency of Chinese provinces. To assess the spatial spillover effects of innovation factors, the spatial autocorrelation and spatial Durbin model were adopted to characterize the spatio-temporal evolution, spatial correlation, and mechanisms of innovation efficiency. The highlights of the results are as follows: (1) The time-series changes in innovation efficiency showed a general trend from declining to increasing. (2) There were pronounced regional differences in innovation efficiency. The innovation efficiencies at the provincial level evolved from being decentralized to concentrated. The innovation efficiency was relatively stable in the eastern region and increased significantly in the central and western regions. The east–center–west evolution pattern gradually weakened. (3) The innovative efficiency exhibited spatial dependence, and the spatial agglomeration continued to increase. The extent of hot spots expanded, while cold spots shrunk slightly. (4) The scientific research environment, entrepreneurial environment, labor quality, and market environment were the essential elements that improved innovation efficiency. The impact of the different factors on innovation efficiency at different periods exhibited significant spatial heterogeneity.


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