Partnerships and industrial clusters: the case of the fashion cluster development in Montreal

2015 ◽  
pp. 203-215
Author(s):  
Diane-Gabrielle Tremblay
Keyword(s):  
Industrial Clusters ◽  
Cluster Development

scholarly journals Industrial clusters in St. Petersburg as a basis for development of Arctic territories

2018 ◽  
Vol 170 ◽  
pp. 02006
Author(s):  
Elena Khutieva ◽  
Alexander Maizel ◽  
Marina Vlasova
Keyword(s):  
Industrial Clusters ◽  
The State ◽  
State Support ◽  
Strategic Development ◽  
Cluster Development ◽  
Effective Implementation ◽  
Coordination Center ◽  
Cluster Environment ◽  
The Given ◽  
Essential Prerequisite

The exploitation of Arctic resources is becoming now one of the most important directions of Russia’s strategic development. The coordination center for this project is St. Petersburg. The article assesses the potential of this region which forms an essential prerequisite for the effective implementation of the given work from the standpoint of the state and prospects of industrial clusters formed in its territory. The subjects of the cluster environment of St. Petersburg relevant programs of state support are divided into three categories: 2 innovative territorial clusters, 3 territorial clusters, 9 territorial clusters administered by the Center for cluster development. Specific recommendations for them are proposed on the basis of analysis of their strengths and weaknesses, as well as assessment of opportunities and threats to their development.

Identifying and Modelling Trustworthiness Competencies of Cluster Development Agents (CDAs)

2019 ◽  
Vol 27 (01) ◽  
pp. 61-91
Author(s):  
Hadi Notash ◽  
Morteza Rezaei-Zadeh ◽  
Ghanbar Mohammadi Elyasi ◽  
Kambiz Talebi
Keyword(s):  
Industrial Clusters ◽  
Practical Implementation ◽  
Structural Modelling ◽  
Structured Interviews ◽  
Cluster Development ◽  
Interpretive Structural Modelling ◽  
Interactive Management ◽  
Development Agents ◽  
Coherent Curriculum

While trustworthiness is seen as an important factor in success of cluster development agents (CDAs), its antecedent competencies were not identified. Against this gap, the current study seeks to explore the scope and sequence of CDAs’ trustworthiness competencies, highlighting the importance of paying attention to cultivating those competencies. Conducting a number of semi-structured interviews as well as one Interactive Management (IM) session which was empowered by using Interpretive Structural Modelling (ISM) software, 6 trustworthiness competencies seem to be important for CDAs were identified, including: Proficiency, Altruism, Acceptability, Ability to alert stakeholders, Expectation identification ability, and Ability to make cooperation. More importantly, the interdependencies amongst those 6 competencies were identified and modelled, shedding light on the priority and weight of each of those competencies as antecedents of CDAs’ trustworthiness. As the theoretical implementation, this study expressed the importance of trustworthiness for CDAs and modelled the antecedent competencies which need to be obtained by CDAs if they are to be trusted by their clients. If a cluster clients do now trust their agent, they should not be blamed. The trustee need to cultivate those pre-requirement competencies if s/he wants to be trustworthy. As the practical implementation, the findings of this study provide a coherent curriculum for enhancing CDAs’ trustworthiness competencies. This curriculum should be implemented by the economic and development organisations who are dealing with training and preparing agents to take role in activating and extending industrial clusters in different countries.

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 THEORETICAL-METHODOLOGICAL BASES AND RESULTS OF ESTIMATION OF THE EFFECTIVENESS OF CLUSTER SPATIAL DEVELOPMENT OF THE RUSSIAN FEDERATION REGIONS

2018 ◽  
pp. 101-111 ◽  
Author(s):  
Tatyana Yurievna Kovaleva
Keyword(s):  
Russian Federation ◽  
Regional Economy ◽  
Spatial Development ◽  
Industrial Clusters ◽  
Evaluation Methodology ◽  
Model Description ◽  
High Tech ◽  
Cluster Development ◽  
Regional Cluster ◽  
The Russian Federation

In modern conditions clusters are considered as an effective tool for achieving sustainable economic growth in the regional economy. Their successful development is a decisive condition for creating a new management model based on the priority of innovative production renewal. In this regard, the creation of high-tech and efficient clusters should become the main direction of strategic management of territorial development by the state authorities of the Russian Federation subjects. However, the solution of this task is impossible without the development of an appropriate methodology and techniques for assessing the effectiveness of the regional economy clustering, which could be used in the development of cluster initiatives and preparation of state programs for regional cluster development. The article highlights the main results of the research carried out under the RFBR grant «Effectiveness of cluster spatial development of the region in conditions of transition to an innovative economy» No 16-12-59011 in 2016-2017. Theoretical and methodological grounds for developing a multi-criterial approach to assessing the cluster effectiveness of the regional economic space have been formulated. Interpretation and distinctive features of the cluster as a self-developing system are given. Configuration of the effectiveness criteria for cluster spatial development of the economy is proposed, which is a primary visualization of the cluster criterial efficiency model. Description of the criterial and indicative approach to the analysis of the effectiveness of regional economy cluster development is given and an integral indicator is proposed for its evaluation. Methodology for assessing the Regional cluster index was tested in nine regions of the Russian Federation, which territorial clusters were officially registered in the Register of industrial clusters 2016 of the Ministry of Industry and Trade of the Russian Federation. Results of the survey can be of interest to representatives of the government bodies at various levels, heads of specialized cluster structures, enterprises and organizations that are members of clusters.

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.

scholarly journals SASARAN STRATEGIS PENGEMBANGAN MODEL KLUSTER INDUSTRI PERIKANAN TANGKAP (Strategic objectives for Cluster Development Model of Capture Fisheries Industry)

2016 ◽  
Vol 5 (2) ◽  
pp. 109
Author(s):  
Tri Wiji Nurani ◽  
. Ardani ◽  
Ernani Lubis
Keyword(s):  
Balanced Scorecard ◽  
Swot Analysis ◽  
Production Quality ◽  
Industrial Clusters ◽  
Development Model ◽  
Industry Cluster ◽  
Institutional Perspective ◽  
Strategic Objectives ◽  
Cluster Development ◽  
Strategic Objective

<p>ABSTRACT<br />Cluster model in fisheries industry base on leading commodity is a policies initiated by the Ministry of Fisheries and Marine Affairs to promote the accelerated development of marine and fisheries sector. Palabuhanratu is one of the areas designated as fisheries industry cluster development. The successful development of the program needs to be evaluated by measurable indicators. This study aims to formulate strategic goals as a measure of the success of the development model of capture fisheries industrial clusters in Palabuhanratu. SWOT analysis and balanced scorecard are used to formulate a strategy and a benchmark for the success of the program. The study states that the strategic objectives of capture fisheries industry cluster development in Palabuhanratu should be able to synergize the interests of actors and interests among sectors in order to create industries competitiveness and productiveness. Factors of successinclude8 strategic targets with 17 benchmarks are covered in 4 perspectives: customer and stakeholder perspective, financial, internal business and institutional perspective. Strategic objectives include balancing utilization and conservation, continuity of production, quality, customer satisfaction, supply chain integration, partnerships, and commitment among the actors in the development of the program.</p><p><br />Keywords: cluster industry model, Palabuhanratu, capture fisheries, strategic objective, benchmark</p><p>-------</p><p><br />ABSTRAK</p><p>Model kluster industri perikanan berbasis komoditas unggulan merupakan kebijakan yang digulirkan oleh Kementerian Kelautan dan Perikanan untuk mendorong percepatan pembangunan sektor kelautan dan perikanan. Palabuhanratu merupakan salah satu lokasi yang ditetapkan sebagai kawasan pengembangan kluster industri perikanan tangkap. Keberhasilan pengembangan program perlu dievaluasi melalui indikator yang terukur. Penelitian ini bertujuan untuk memformulasikan sasaran strategis sebagai tolok ukur keberhasilan pengembangan model kluster industri perikanan tangkap di Palabuhanratu. Analisis SWOT dan balanced scorecard digunakan untuk merumuskan strategi dan tolok ukur keberhasilan program. Hasil penelitian menyatakan bahwa sasaran strategis pengembangan kluster industri perikanan tangkap di Palabuhanratu harus dapat mensinergikan kepentingan para pelaku dan kepentingan antar sektor untuk dapat menciptakan industri yang memiliki daya saing dan produktif. Faktor keberhasilan mencakup 8 sasaran strategis, dengan 17 tolok ukur keberhasilan yang tercakup dalam 4 perspektif yaitu perpektif pelanggan dan stakeholder, keuangan, bisnis internal dan perspektif kelembagaan. Sasaran strategis meliputi keseimbangan pemanfaatan dan konservasi, kontinuitas produksi, mutu, kepuasan pelanggan, integrasi rantai pasok, kemitraan, dan komitmen diantara para pelaku dalam pengembangan program.</p><p><br />Kata kunci: model kluster industri, Palabuhanratu, perikanan tangkap, sasaran strategis, tolok ukur</p>

Countermeasures for Tobacco Industrial Cluster Development

2021 ◽  
Vol 7 (4) ◽  
pp. 326-338
Author(s):  
Liu Mingjuan
Keyword(s):  
World Economy ◽  
Economies Of Scale ◽  
Tobacco Industry ◽  
Industrial Clusters ◽  
World Health ◽  
Industry Clusters ◽  
Cluster Development ◽  
Leading Role ◽  
The World ◽  
Health Organization

Nowadays, the deepening globalization of the world economy promotes the economic development to present more and more obvious regionalization characteristics, and industrial clusters are increasingly becoming an important source for a country or region to achieve competitive advantages. China is the largest tobacco country in the world, and the tobacco industry is the largest source of tax revenue in China, which has made outstanding contributions to the national financial accumulation. After joining the World Trade Organization (WTO) and signing the Framework Convention on Tobacco Con trol (FCTC) o f the World Health Organization (WHO), the competition in the domestic and foreign tobacco markets has become increasingly fierce, and more attention to health issues has put forward higher requirements for the development of China's tobacco industry. Therefore, the Chinese tobacco industry urgently needs to use industrial clusters to form economies of scale and enhance market competitiveness. Overall, the development level of China's tobacco industry is not high. Due to some existing problems that restrict the development of tobacco industry clusters, some measures must be taken to enhance the competitiveness of China's tobacco industry clusters in the world economy, such as strengthening o verall coordination and planning guidance , guiding industries from agglomeration to cluster development, actively supporting related industries, and vigorously enhancing innovation ability. Therefore, it is necessary to find out the breakthrough point of the development of tobacco industry clusters, select the appropriate industrial clusters to focus on cultivating, strengthening the leading role, supplementing the chain and clustering, and guide and promote the healthy growth of tobacco industry clusters, so as to stimulate the growth of the national economy.

Clustering, growth and inequality in China

2020 ◽  
Vol 20 (5) ◽  
pp. 1207-1239
Author(s):  
Di Guo ◽  
Kun Jiang ◽  
Chenggang Xu ◽  
Xiyi Yang
Keyword(s):  
Economic Growth ◽  
Panel Data ◽  
Income Inequality ◽  
Instrumental Variables ◽  
Industrial Clusters ◽  
Regional Economic Growth ◽  
County Level ◽  
Cluster Development ◽  
Rural Income ◽  
Urban Rural

Abstract This study examines the effects of China’s industrial clusters on regional economic growth and urban–rural income inequality within a region. A density-based index (DBI) is developed to capture the unique features of cluster development in China. From a county-level DBI panel data constructed based on firm- and county-level datasets, we find that clusters enhance local economic growth substantially. Moreover, the existence of entrepreneurial clusters (clusters mainly consist of nonstate-owned firms) helps to reduce local urban–rural income inequality by increasing the income of local rural residents. We also find that the clustering effects on growth and reduction of inequality are less significant in more urbanized regions or megacities. Identification issues are carefully addressed by deploying two-stage estimations with instrumental variables and Granger test.

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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