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Article
Publication date: 27 April 2022

Ekaterina Turkina and Boris Oreshkin

This paper aims to investigate the evolution of the phenomenon of industrial districts and explores the broader regional innovation systems that consist of multiple…

Abstract

Purpose

This paper aims to investigate the evolution of the phenomenon of industrial districts and explores the broader regional innovation systems that consist of multiple industrial districts.

Design/methodology/approach

This paper uses a combination of network analysis and patent analysis techniques to analyze the social structure of Montreal tech agglomeration and its innovation.

Findings

The findings indicate that the cores of modern regional innovation systems are composed of densely collaborating organizations belonging to different industrial clusters, and these organizations are responsible for the most radical innovations. The analysis also reveals the importance of brokers and international ties in generating radical innovations.

Research limitations/implications

The findings of our paper extend the initial concept of industrial district and call for the need to no longer focus exclusively on individual clusters, but to take into consideration broader competitive regional innovation systems that are composed of multiple clusters. The current trend of the core of such systems to be composed of organizations from multiple clusters indicates that the traditional understanding of industrial district confined to the borders of specific industry is no longer relevant and there is a need to revise the conceptualization of clusters and further analyze the social fabric of broader regional innovation systems. In future, such intense collaboration within the core of the regional innovation system network may give rise to new industrial and technological configurations. It is important to further investigate these structures, because they have important implications for innovation and are responsible for new innovation patterns.

Practical implications

To boost innovation in specific localities, policymakers could encourage collaboration between different clusters and support interdisciplinary projects and programs. Those would help the local community generate radical innovations.

Social implications

Using this research, local policymakers could help local companies understand and explore international markets, as well as focus on attracting multinational firms that are leaders in their respective fields. Finally, local policymakers could further support important cluster intermediaries

Originality/value

This paper offers original contributions to the studies of industrial districts as it explores a competitive ecosystem composed of multiple industrial districts and analyzes how these industrial districts interact and where the most innovative solutions lie in the social fabric of this big ecosystem.

Details

Competitiveness Review: An International Business Journal , vol. 32 no. 5
Type: Research Article
ISSN: 1059-5422

Keywords

Article
Publication date: 22 April 2022

Yongcong Luo, Jianzhuang Zheng and Jing Ma

The focus of industrial cluster innovation lies in the cooperation between enterprises and universities/scientific research institutes to make a theoretical breakthrough…

Abstract

Purpose

The focus of industrial cluster innovation lies in the cooperation between enterprises and universities/scientific research institutes to make a theoretical breakthrough in the system and mechanism of industrial cluster network. Under the theoretical framework of cluster network, industrial structure can be optimized and upgraded, and enterprise benefit can be improved. Facing the increasing proliferation and multi-structured enterprise data, how to obtain potential and high-quality innovation features will determine the ability of industrial cluster network innovation, as well as the paper aims to discuss these issues.

Design/methodology/approach

Based on complex network theory and machine learning method, this paper constructs the structure of “three-layer coupling network” (TLCN), predicts the innovation features of industrial clusters and focuses on the theoretical basis of industrial cluster network innovation model. This paper comprehensively uses intelligent information processing technologies such as network parameters and neural network to predict and analyze the industrial cluster data.

Findings

From the analysis of the experimental results, the authors obtain five innovative features (policy strength, cooperation, research and development investment, centrality and geographical position) that help to improve the ability of industrial clusters, and give corresponding optimization strategy suggestions according to the result analysis.

Originality/value

Building a TLCN structure of industrial clusters. Exploring the innovation features of industrial clusters. Establishing the analysis paradigm of machine learning method to predict the innovation features of industrial clusters.

Details

Kybernetes, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0368-492X

Keywords

Article
Publication date: 5 October 2010

Keui‐Hsien Niu

The research of industrial cluster and organizational adaptation can be traced back to early strategic management and organization theory. This paper initiates an attempt…

1840

Abstract

Purpose

The research of industrial cluster and organizational adaptation can be traced back to early strategic management and organization theory. This paper initiates an attempt to empirically examine the relationship between a firm's involvement in an industrial cluster and its adaptive outcomes.

Design/methodology/approach

Field survey research method was used and data were collected from four international industrial clusters which consist of 188 company responses. Regression analysis and path analysis were used to analyze the data.

Findings

The paper found that the degree of a firm's involvement in an industrial cluster affects its adaptation outcomes. But the nature of the adaptation benefits depends, to a large degree, on the type of cluster involvement.

Research limitations/implications

Using self‐reported data could be a potential limitation of this paper. It would be preferable to have other forms of data for a study.

Practical implications

Industrial clusters are widely considered a network‐based industrial system with the aim of adapting to fast‐changing markets and technologies as an organized whole. Firms within a cluster can work together to co‐evolve for the purpose of enhancing competitiveness and adapting to the environmental change. As the sum of the benefit of a cluster is of greater value than each individual company or institution, whether to involve in an industrial cluster to have effective adaptation is worthy of managers' consideration.

Originality/value

The major contribution of this work is the first attempt to operationalize the construct “industrial cluster” and to create a coherent model that logically links industrial clusters and organizational adaptation to tests that have not been covered sufficiently in the literature.

Details

Competitiveness Review: An International Business Journal, vol. 20 no. 5
Type: Research Article
ISSN: 1059-5422

Keywords

Article
Publication date: 12 January 2022

Yawen Wang and Weixian Xue

The purpose is to analyze and discuss the sustainable development (SD) and financing risk assessment (FRA) of resource-based industrial clusters under the Internet of…

Abstract

Purpose

The purpose is to analyze and discuss the sustainable development (SD) and financing risk assessment (FRA) of resource-based industrial clusters under the Internet of Things (IoT) economy and promote the application of Machine Learning methods and intelligent optimization algorithms in FRA.

Design/methodology/approach

This study used the Support Vector Machine (SVM) algorithm that is analyzed together with the Genetic Algorithm (GA) and Ant Colony Optimization (ACO) algorithm. First, Yulin City in Shaanxi Province is selected for case analysis. Then, resource-based industrial clusters are studied, and an SD early-warning model is implemented. Then, the financing Risk Assessment Index System is established from the perspective of construction-operation-transfer. Finally, the risk assessment results of Support Vector Regression (SVR) and ACO-based SVR (ACO-SVR) are analyzed.

Findings

The results show that the overall sustainability of resource-based industrial clusters and IoT industrial clusters is good in the Yulin City of Shaanxi Province, and the early warning model of GA-based SVR (GA-SVR) has been achieved good results. Yulin City shows an excellent SD momentum in the resource-based industrial cluster, but there are still some risks. Therefore, it is necessary to promote the industrial structure of SD and improve the stability of the resource-based industrial cluster for Yulin City.

Originality/value

The results can provide a direction for the research on the early warning and evaluation of the SD-oriented resource-based industrial clusters and the IoT industrial clusters, promoting the application of SVM technology in the engineering field.

Details

Journal of Enterprise Information Management, vol. 35 no. 4/5
Type: Research Article
ISSN: 1741-0398

Keywords

Article
Publication date: 2 October 2017

Gabriel Marcuzzo do Canto Cavalheiro and Mariana Brandao

By examining the intellectual property (IP) portfolio of the largest Brazilian footwear firms, the purpose of this paper is to improve the understanding of how…

Abstract

Purpose

By examining the intellectual property (IP) portfolio of the largest Brazilian footwear firms, the purpose of this paper is to improve the understanding of how manufacturing firms in the footwear industry in a developing country are using the IP system.

Design/methodology/approach

Intellectual property rights (IPRs) are widely acknowledged to be of central importance to manufacturing processes and systems. As such, manufacturing firms located in developing countries also need to use the international IP system in order to increase their competitiveness. This study examines how the Brazilian footwear industry is protecting their IPRs by assessing IP filings in recent years from this particular industry.

Findings

Here, the authors provide empirical evidence indicating a recent growth in IP filings that was accomplished by manufacturing firms in the Brazilian footwear industry. Additionally, the authors also found that the use of the IP system is highly concentrated in the two Brazilian footwear industrial clusters, which are located in the States of São Paulo (SP) and Rio Grande do Sul (RS).

Research limitations/implications

The analysis can be considered a solid reference for future studies that assess the use of IP of manufacturing organizations as a developing country context. The authors believe it is worthwhile to conduct qualitative interviews with the senior managers of the IP department of Brazilian footwear manufacturers located in the SP and RS industrial clusters, as a means of deepening our understanding on their motivations to file IP applications.

Practical implications

The results presented in this study demonstrate a recent growth in IP filings accomplished by firms in the Brazilian footwear industry, which is an industry subject to serious threats posed by counterfeit and pirated goods. More specifically, the authors provide empirical evidence that the use of the IP system is more intense in two industrial clusters, which are located in the states of SP and RS. In this way, the authors believe that similar patterns will appear in other technical areas, in which industrial clusters can be identified.

Social implications

According to OECD/EUIPO (2016), the footwear industry has been leading the rank of the most severely affected by counterfeit and pirated goods worldwide. Highly copied goods also include clothing, electrical machinery and equipment, articles of leather, and watches. However, footwear products are more frequently illegally copied as compared to any other type of product.

Originality/value

Given the increased importance of IP assets in the current knowledge-based society, firms located in developing countries ought to use IP more intensively. In fact, even with growing correlation between IP and competitiveness, IP data from firms in developing countries have received limited treatment in the extant literature. In summary, the evidence base is not strong and it urgently needs strengthening. As such, to the authors’ knowledge, this study is the first contribution addressing the use of IP by footwear manufacturing firms in a developing country.

Details

Journal of Manufacturing Technology Management, vol. 28 no. 8
Type: Research Article
ISSN: 1741-038X

Keywords

Article
Publication date: 22 October 2010

Yan Zhao, Wen Zhou, Stefan Hüsig and Wim Vanhaverbeke

The purpose of this paper is to categorize industrial clusters, and then compare three industrial clusters of three countries from the perspectives of hard environment…

Abstract

Purpose

The purpose of this paper is to categorize industrial clusters, and then compare three industrial clusters of three countries from the perspectives of hard environment, soft environment, factors from supply and demand sides, and the network mechanism.

Design/methodology/approach

Data were collected through interview with cluster coordinators. Qualitative case studies were conducted.

Findings

The center of excellence behaves well in nearly all aspects, while the spatially narrowly distributed specific center of innovation mainly exploits benefits from its concentrated sector. For the Chinese comprehensive technology incubator, relatively limited geographical space and broad sectorial distribution endow it with unclear strengths, implying the inadequacy of interconnectedness and industry relatedness mentioned by Porter.

Research limitations/implications

Data were collected mainly from cluster coordinators, implying further data collecting and more comprehensive analysis.

Practical implications

It only makes sense to compare industrial clusters that are comparable with each other. Elements must be matched to facilitate the network interactions, and hence the innovation performance of clusters.

Originality/value

This paper contributes to the theoretical basis through it analyzing and clarifying the scales to measure industrial clusters, and answers the question: what is the situation of industrial clusters behaving in several aspects including hard environment, soft environment, supply, demand, network interactions and innovation performance?

Details

Journal of Science and Technology Policy in China, vol. 1 no. 3
Type: Research Article
ISSN: 1758-552X

Keywords

Article
Publication date: 7 November 2016

Xiujie Wang, Jian Liu and Can Ma

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…

1557

Abstract

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.

Details

Chinese Management Studies, vol. 10 no. 4
Type: Research Article
ISSN: 1750-614X

Keywords

Article
Publication date: 7 June 2013

Rongzhi Liu, Qingxiong Weng, Guanfeng Mao and Tianwei Huang

The purpose of the paper is to explore why the entrepreneurial activities are agglomerative in a cluster and to investigate the government agencies' functions in the…

Abstract

Purpose

The purpose of the paper is to explore why the entrepreneurial activities are agglomerative in a cluster and to investigate the government agencies' functions in the industry cluster that can construct favourable environment for entrepreneurial development.

Design/methodology/approach

The case study method is chosen to collect in‐depth data to investigate the research domain, and the detailed case of the industrial cluster in Wenzhou, China is selected. The empirical data for the analysis are derived from in‐depth interviews with entrepreneurs in private and public organizations. Statistical data and historical documents are also collected to increase the understanding of the regional conditions, as well as for comparison with and triangulation of the research theme.

Findings

It was found that in Wenzhou, four major groups of government agencies which perform the functions of investment, research & innovation, industrial information and supporting service, were generated along with the development of the industrial clusters; and it was found that initial capital, technology support and human capital are the critical resources those institutes had tried to provide to facilitate the entrepreneurial activities in the local clusters.

Originality/value

The paper enriches our understanding about how entrepreneurship is promoted and cultivated in industrial clusters under the social‐economic environment in China and sheds light on the Chinese entrepreneurial process in the local industrial clusters.

Details

Chinese Management Studies, vol. 7 no. 2
Type: Research Article
ISSN: 1750-614X

Keywords

Article
Publication date: 15 July 2014

Maw-Shin Hsu, Yung-Lung Lai and Feng-Jhy Lin

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…

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Abstract

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.

Article
Publication date: 23 March 2012

Kuei‐Hsien Niu, Grant Miles, Seung Bach and Kenichiro Chinen

The research of industrial clusters, trust, and learning can be traced back to early strategic management and organization theory. The purpose of this paper is to review…

2014

Abstract

Purpose

The research of industrial clusters, trust, and learning can be traced back to early strategic management and organization theory. The purpose of this paper is to review past literature and offer a conceptual framework that is related to industrial clusters, trust and learning.

Design/methodology/approach

This study incorporates a literature review to filter key factors of industrial clusters, trust and learning by using a deductive approach to conclude a conceptual framework.

Findings

This study provides a conceptual framework which includes a firm's industrial cluster involvement, trust and learning. Based on the literature, inter‐organizational trust may be strengthened due to reduced proximity and better information flow within a cluster. Further, industrial clusters encourage co‐evolution and co‐adaptation that stimulates effective learning practices for clustering firms.

Research limitations/implications

This study uses a literature review and offers a conceptual framework to examine a firm's involvement in industrial clusters with the possible influences of trust and organizational learning. There is a need for empirical as well as statistical analysis to validate the framework and to obtain more insight.

Practical implications

Industrial clusters are widely considered a network‐based industrial system, with the aim of adapting to fast‐changing markets and technologies as an organized whole. Firms within a cluster can work together to co‐evolve for the purpose of enhancing competitiveness and entering the world market through effective learning and inter‐firm trust. As the sum of the benefit of a cluster is of greater value than each individual company or institution, whether to be involved in an industrial cluster to sustain competitiveness and enhance learning is worthy of managers' consideration.

Originality/value

The major contribution of this work is that it is the first attempt to produce the measures for a firm's involvement in industrial clusters for empirical tests, which are generally considered insufficient in this area of research. Further, this study offers a conceptual framework which brings cluster, trust and learning together for future empirical study.

Details

Competitiveness Review: An International Business Journal, vol. 22 no. 2
Type: Research Article
ISSN: 1059-5422

Keywords

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