Evaluation of the Effectiveness of Financing Industrial Clusters

2019 ◽  
pp. 36-47
Author(s):  
M.B. Trachenko ◽  
O.D. Gaisha
Keyword(s):  
Systems Approach ◽  
Industrial Cluster ◽  
Cash Flows ◽  
Industrial Clusters ◽  
Cluster Policy ◽  
Mathematical Methods ◽  
Actual Problem ◽  
Cluster Development ◽  
Tier System ◽  
The Impact

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.

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
Keyword(s):  
Natural Experiment ◽  
Industrial Cluster ◽  
Industrial Clusters ◽  
Government Support ◽  
Mediation Effect ◽  
Eastern Region ◽  
Cluster Policy ◽  
Regional Innovation ◽  
Promoting Effect ◽  
The Impact

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.

scholarly journals The effects of culture, attitudes and perceptions on industrial cluster policy: The case of Russia

2020 ◽  
pp. 102452942094949 ◽  
Author(s):  
Sergey Sosnovskikh ◽  
Bruce Cronin
Keyword(s):  
Cluster Model ◽  
Industrial Cluster ◽  
Industrial Clusters ◽  
Cluster Policy ◽  
Industrial Parks ◽  
Attitudes And Perceptions ◽  
Effective Development ◽  
Economic Zones ◽  
The Impact ◽  
Depth Interviews

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.

scholarly journals The role of cluster cycle and pattern of interaction to competition strategy

2016 ◽  
Vol 14 (2) ◽  
pp. 74-83 ◽  
Author(s):  
Sri Hartono ◽  
Agus Sobari
Keyword(s):  
Small And Medium Enterprises ◽  
Industrial Cluster ◽  
Industrial Clusters ◽  
Furniture Industry ◽  
Cluster Policy ◽  
Central Java ◽  
Medium Enterprises ◽  
Wooden Furniture ◽  
The Impact

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

scholarly journals Research on Cooperative Innovation Behavior of Industrial Cluster Based on Subject Adaptability

2016 ◽  
Vol 2016 ◽  
pp. 1-19 ◽  
Author(s):  
Xiaohui Jia ◽  
Minghui Jiang ◽  
Lei Shi
Keyword(s):  
Steady State ◽  
Evolutionary Game ◽  
Industrial Cluster ◽  
Industrial Clusters ◽  
Government Support ◽  
Correlated Equilibrium ◽  
Game Model ◽  
Cooperative Innovation ◽  
The Cost ◽  
The Impact

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.

CONCEPT AND PROBLEMS OF PRODUCTION COOPERATION

2020 ◽  
pp. 16-18
Author(s):  
L.S. Markov ◽  
◽  
V.S. Plotnikov ◽  
Keyword(s):  
Industrial Cluster ◽  
The State ◽  
Cluster Policy ◽  
Cluster Development ◽  
Industrial Cooperation ◽  
Regional Cluster ◽  
Direct Support ◽  
Labor Resources ◽  
Cooperation Support

One of the modern forms of cooperation between enterprises is industrial and territorial clusters. Researchers in the development of industrial cooperation processes and cluster projects highlight a number of problems, among which there are problems associated with the development of international cooperation, support for industrial cooperation at the state and regions of the state levels, the formation and implementation of joint projects, as well as the quality of labor resources. Today, an actual rejection of the systemic cluster policy in all directions is demonstrated, which is confirmed by the curtailment of direct support for industrial cluster projects, as well as the refusal to support regional cluster development centers. The main reason for this reversal seems to be the insufficiency of the cooperative component of domestic clusters.

A research on the cluster competitiveness evaluation of the Chinese automobile industry based on cuckoo-AHP

2016 ◽  
Vol 10 (4) ◽  
pp. 746-769 ◽  
Author(s):  
Xiujie Wang ◽  
Jian Liu ◽  
Can Ma
Keyword(s):  
Automobile Industry ◽  
Evaluation Method ◽  
Industrial Cluster ◽  
Cuckoo Search ◽  
Evaluation Methods ◽  
Industrial Clusters ◽  
Evaluation Index System ◽  
Evaluation Index ◽  
Content Type ◽  
Cluster Development

Purpose The purpose of this study is that on the basis of the competitive edge theory, source mechanism and evaluation approaches of industrial cluster competitiveness, combined with international trends in the automobile industry and the features of Chinese automobile industrial cluster development, an evaluation index system about cluster competitiveness of auto industry is built with comprehensive consideration of factors such as cluster development environment, external scale effect and internal competitiveness from the perspective of value chain of automobile industry. Design/methodology/approach An evaluation index system for automobile industrial cluster competitiveness was realized by integrating current strengths and future growth capacities with multidimensional, dynamic and comprehensive characteristics, which included 3 second-level, 10 third-level and 16 fourth-level indices. In the light of evaluation methods, a group intelligence optimization algorithm – (cuckoo search) – and traditional methods of complex decision-making system – analytic hierarchy process (AHP) – were combined to propose the cuckoo-AHP evaluation method. It was applied for the calculation and optimization of weight values in an automobile industrial cluster competitiveness evaluation index for the purpose of obtaining better scientific and more reliable results. Findings The research might further enrich the evaluation theory of automobile industrial cluster competitiveness and also can be useful for showing how traditional evaluation methods can be combined with intelligent algorithms to carry out better automobile industrial cluster competitiveness evaluations. In addition, studies of channels for kick-starting Chinese auto industrial cluster competitiveness are expected to provide references for how to enhance the cluster competitiveness of the Chinese automobile industry. Practical implications Changsha and Liuzhou, the Guangxi automobile industrial clusters as the two empirical analysis objects selected for this paper, are geographically adjacent to each other. The automobile industries of the two cities are local pillar industries with the strong support of the local government. Both clusters have their own advantages and weak points with different characteristics of cluster development, and they enjoy a representative significance amongst China’s numerous auto industrial clusters that are taking shape. Comparative analysis of both clusters serves as a good reference for the objective evaluation of the competitiveness of Chinese automobile clusters in terms of their real and practical developments and in respect of the success of reasonable scientific and industrial cluster policies. Originality/value Multidimensional, dynamic, integrated evaluation index systems are constructed around automobile industrial cluster competitiveness, which has taken into account developments in current strengths and future growth capacity. The cuckoo-AHP evaluation method has been formed by combining the traditional decision-making method known as AHP with a new meta-heuristic optimization algorithm called “cuckoo search”. Both have been used in evaluations of automobile industrial cluster competitiveness in Liuzhou and Changsha, which will be beneficial for enriching automobile industrial cluster competitiveness evaluation theory and new evaluation methods that will enable better evaluations of automobile industrial cluster competitiveness.

scholarly journals TOOLS OF CLUSTER POLICY IMPLEMENTATION

2021 ◽  
Author(s):  
Anna Prisyazhnyuk ◽  
Natalia Shulpina
Keyword(s):  
Development Strategy ◽  
National Level ◽  
Industrial Clusters ◽  
Cluster Policy ◽  
Cluster Development ◽  
Goods And Services ◽  
Research And Innovation ◽  
Use Of Resources ◽  
Smart Specialization ◽  
Different Levels

The article considers the current tools for the implementation of cluster policy in Ukraine, taking into account the practice and experience of European countries. The relationship between cluster policies and tools for their implementation at the national, regional and local levels has been studied. It is substantiated that modern attempts to develop and implement cluster policy at different levels in Ukraine are dissonant, fragmentary and have a more declarative than applied content. This is evidenced by the lack of appropriate legislation at the national level and distortions in defining “reasonable specialization” of regions, lack of effective communication, financial donations, mechanisms and tools for promoting and implementing cluster policies in both regions and the state as a whole. Given the above, we will focus the plane of the problem field on the main vectors of integrated cluster policy in Ukraine: tools and programs at the cluster level; tools and programs at the regional level; national policies and strategies that define sectoral priorities and directions of development and are directly related to cluster development (industrial policy, innovation, export, digital), as well as national regional development policy). Mechanisms that determine the general economic course and conditions, primarily tax, financial and organizational instruments. The study of tools for the implementation of cluster policies at different levels has convincingly demonstrated the need for their comprehensive interaction within a single national cluster development strategy. It is thanks to the purposeful policy of promoting the development of clusters in Ukraine that it is possible to develop supply chains of goods and services with their further integration into European value chains; to implement research and innovation strategies of smart specialization in the regions; to solve problems of ecology and efficient use of resources by introduction of ecological innovations, eco-industrial clusters and parks; to equalize socio-economic distortions in the development of sectors of the economic system.

Assessing the Success of an Industrial Cluster

2012 ◽  
Vol 3 (3) ◽  
pp. 21-36 ◽  
Author(s):  
Neil Reid ◽  
Bruce W. Smith
Keyword(s):  
Problem Solving ◽  
Development Strategy ◽  
Industrial Cluster ◽  
Industrial Clusters ◽  
Collaborative Problem Solving ◽  
Energy Costs ◽  
Collaborative Problem ◽  
Regional Development Strategy ◽  
The Impact ◽  
Reducing Energy

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.

The impact of industrial clusters on human resource and firms performance

2014 ◽  
Vol 9 (2) ◽  
pp. 141-159 ◽  
Author(s):  
Maw-Shin Hsu ◽  
Yung-Lung Lai ◽  
Feng-Jhy Lin
Keyword(s):  
Human Resources ◽  
Positive Impact ◽  
Industrial Cluster ◽  
Industrial Clusters ◽  
Global Market ◽  
Content Type ◽  
Key Factor ◽  
The Face ◽  
Processing Zone ◽  
The Impact

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.

Internet Industry Cluster Design Based on PDE Mathematical Model

2014 ◽  
Vol 539 ◽  
pp. 959-963
Author(s):  
He Huang ◽  
Hui Xiao
Keyword(s):  
Cluster Analysis ◽  
Distribution Channel ◽  
Industrial Cluster ◽  
Industrial Clusters ◽  
Validity And Reliability ◽  
Cluster Development ◽  
Cluster Environment ◽  
And Performance ◽  
Virtual Platform ◽  
Analysis System

The industrial cluster is formed by the common competitiveness elements of enterprise group. Under the cluster environment, common technology and common customer as well as distribution channel are composition of cluster development performance mode. On the basis of the parabolic PDE cluster development model, and combined with Internet industrial cluster analysis of virtual platform, the Internet structure industrial cluster analysis system is designed. In order to verify the validity and reliability of the model and system, this paper takes the cluster development of machining as an example to carry on the research for the system performance, which can get the virtual grid node and stress distribution of cluster processing center, finally we can obtain the industrial cluster investment and performance relationship table, to provide the theoretical guidance for the development of industrial clusters.

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