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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 in the…

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. 52 no. 10
Type: Research Article
ISSN: 0368-492X

Keywords

Article
Publication date: 17 October 2016

Stephen Brosnan, Eleanor Doyle and Sean O’Connor

The purpose of this paper is to offer clarity on a central concept introduced in Porter’s The Competitive Advantage of Nations, i.e. the cluster. The authors situate the concept…

1310

Abstract

Purpose

The purpose of this paper is to offer clarity on a central concept introduced in Porter’s The Competitive Advantage of Nations, i.e. the cluster. The authors situate the concept introduced by Porter (1990) relative to two of its antecedents, the industrial district and industrial complex. Placing the cluster in a historical context permits consideration of the extent to which it, as a concept for analysis, may be differentiated from other geography-based approaches to economic phenomena. In this way, this paper examines the added value of the cluster concept derived from economic factors.

Design/methodology/approach

The paper provides a detailed literature review tracing the evolution of theories of location and agglomeration into which Porter’s cluster fits. The evolution of Porter’s own conceptualisation of the cluster and how this relates to theoretical clarity surrounding the concept is explored. Comparative analysis of theories of location, agglomeration and clustering is provided to identify similarities and differences across the approaches and identify the added value of the cluster concept in relation to other approaches.

Findings

Clustering represents a process associated with spatial organisational form which may offer advantages in efficiency, effectiveness and flexibility. Cluster benefits can be appreciated through the lens of Young’s (1928) identified sources of increasing returns. A key aspect in clustering is revealed in terms of its role in enabling four sources of increasing returns. The authors outline how these sources of increasing returns are related to “soft” processes of networking, interaction and individual and collective learning. Porter’s Diamond is a self-reinforcing system which can permit increasing returns and reinforce such tendencies of economic activity within agglomerations.

Originality/value

Added value from Porter’s cluster concept is identified in the context of both its locational anchoring and in terms of its potential for understanding the role of exploitation of increasing returns for development. This points to the importance of focusing on clustering as a process rather than on cluster within typologies of organisational form. This implies that the nature of relationships (and how they change) within and across markets, institutions and actors lies at the heart of clustering because of their roles in knowledge-generation, including innovation, knowledge sharing and upgrading.

Details

Competitiveness Review, vol. 26 no. 5
Type: Research Article
ISSN: 1059-5422

Keywords

Article
Publication date: 17 July 2017

Alfonso Mendoza-Velazquez

This study investigates the existence of Marshall, Jacob and Porter’s type of externalities in Mexico. We measure the impact of industrial specialization, competition and…

Abstract

Purpose

This study investigates the existence of Marshall, Jacob and Porter’s type of externalities in Mexico. We measure the impact of industrial specialization, competition and diversity on employment growth for the period 2004 to 2008.

Design/methodology/approach

The analysis is based on data from 41 highly dynamic industrial clusters originally obtained by applying Porter’s (1998) methodology. We use a cross-section specification estimated via instrumental variables and two-stage least square estimation (2SLS) to control for endogeneity.

Findings

On average, we find that industrial specialization exerts a negative impact on employment growth within states and within clusters, indicating that traded industries in Mexico carry very little innovation, operate in early stages of the life cycle, face high costs of employment reassignation or exhibit low adaptability. A negative impact of specialization on employment conforms with Jacobs (1969) type of externalities and confirms what other studies have found in France (Combes, 2000), Korea (Lee et al., 2005) and the USA (Delgado et al., 2014). The authors also find that competition generates more employment.

Research limitations/implications

Industrial data at the sub-branch level were obtained from the Economic Census (EC) of the National Institute of Geography and Statistics (INEGI). The EC information for 2004 was still not fully compatible with the North America Industry Classification System (NAICS), with 262 of the 309 data at the fourth-digit level aligned to the USA. In addition, industrial information from the EC is recorded every four years, which prevents this study to use panel data techniques and it makes it impossible to use time series methods.

Practical implications

Policymakers can clearly identify competition forces having a significant impact on employment growth. This can orient policymakers to implement measures to encourage the development of some of these clusters, as well as to identify some of the sources that drive specialization, competition and diversity.

Originality/value

This paper contributes to the debate on the existence of Marshallian (MAR), Jacobian and Porter externalities. This is the first study using the definition of traded clusters in Mexico, which allows the authors to identify how specialization, competition and diversity forces drive the dynamics of regional employment growth.

Details

Competitiveness Review: An International Business Journal, vol. 27 no. 4
Type: Research Article
ISSN: 1059-5422

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, soft…

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: 11 October 2021

Cláudia Fabiana Gohr, Maryana Scoralick de Almeida Tavares and Sandra Naomi Morioka

This paper aims to propose an assessment framework to evaluate companies' innovation capability in the context of industrial clusters.

Abstract

Purpose

This paper aims to propose an assessment framework to evaluate companies' innovation capability in the context of industrial clusters.

Design/methodology/approach

The assessment framework was built based on the Graph-Theoretic Approach (GTA) to measure the influence of the factors and sub-factors of innovation capabilities. To quantify the level of interdependence between factors and sub-factors of innovation capability Delphi method was adopted. The authors developed five case studies in firms from an Information and Communications Technology and Creative Economy cluster in Northeastern Brazil to test the framework's applicability.

Findings

The results showed that identifying and evaluating the factors of innovation capability allows a larger understanding of what affects these capabilities to a greater or lesser extent and contributes to strategic decision-making.

Research limitations/implications

The framework evaluates the innovation capability of each firm, not providing an index for the whole industrial cluster. Besides, the framework does not consider the innovations developed by the companies through the innovation's capabilities. As the Delphi technique was adopted to analyze the levels of influence or interdependence between factors and sub-factors of innovation capability, different experts may lead to different results.

Practical implications

Among the managerial implications, the authors can highlight the innovation capability index as a practical performance measure to stimulate improvement initiatives regarding innovations in industrial clusters. Besides, as the proposed framework is generic, research organizations, public institutions and regional governments can adopt it to analyze innovation capabilities in cluster-based companies.

Originality/value

Previous industrial cluster studies have concentrated on knowledge transfer as the main attribute influencing innovation capabilities. The literature also presents assessment frameworks focusing on qualitative analyses or innovation capabilities outcomes (patents and products). Differently, the authors proposed a quantitative assessment framework considering specific factors (and sub-factors) of innovation capabilities in industrial clusters.

Details

Journal of Business & Industrial Marketing, vol. 37 no. 7
Type: Research Article
ISSN: 0885-8624

Keywords

Article
Publication date: 19 July 2013

Amrendra Kumar Singh and Rakesh L. Shrivastava

A geographically proximate group of rice mills, supporting companies, suppliers, and associated institutions in a particular field is emerging as a concept to make rice mills more…

Abstract

Purpose

A geographically proximate group of rice mills, supporting companies, suppliers, and associated institutions in a particular field is emerging as a concept to make rice mills more competitive. The factors, which emerged due to cluster formation, appear to have the potential to contribute to the performance of rice mills. The purpose of this paper is to investigate the effect of a rice mill cluster initiative. The primary objective is to identify the critical factors of a successful rice mill cluster initiative. To meet this objective, a questionnaire is developed for the assessment of effects of cluster elements.

Design/methodology/approach

The methodology used for this paper is an exploratory cross‐sectional and literature review of published materials.

Findings

There is strong evidence to suggest that a cluster policy brings additional positive effect to existing small enterprises such as rice mills located in a cluster.

Originality/value

This study offers initial empirical evidence and a number of important insights to assist managers and policy makers in enhancing performance of rice mills located in a cluster. The findings from this research will assist strategy makers in making more informed decisions regarding the adoption of a cluster approach and entering into cluster‐based relations, as well as assisting policy makers in designing more efficient cluster policies. The academic value will be added in the context of expanding knowledge in relation to the impact of clusters on economic development in developing countries and as such contribute in filling gaps within the existing literature.

Details

International Journal of Productivity and Performance Management, vol. 62 no. 6
Type: Research Article
ISSN: 1741-0401

Keywords

Article
Publication date: 23 November 2010

Zheng He and Lez Rayman‐Bacchus

Firms in the same industry often display a striking propensity to agglomerate. These geographic concentrations significantly affect innovative behavior of individual firms and…

1281

Abstract

Purpose

Firms in the same industry often display a striking propensity to agglomerate. These geographic concentrations significantly affect innovative behavior of individual firms and therefore have important strategic implications. The purpose of this paper is to report on how networks within the cluster influence firms' commitment to innovation.

Design/methodology/approach

Employing a longitudinal case study approach data were collected for 2004 and 2007 about the Shaxi garment cluster in Zhongshan, China. A novel method of measuring innovative behavior was developed and tested at the level of individual small and medium sized enterprises, where R&D expenditure is not recorded, by measuring managerial perception of developments in three areas: product, process, and market development.

Findings

The extent to which related firms, various associations, and government policies affected the individual firm's propensity to innovate was examined. The main findings of this paper show firm‐level commitment to innovation is significantly stimulated by three groups of factors: competitor action and cooperation in the supply chain, membership of various government and industry associations and government stimulus policies in the cluster. The relative significance and nature of these influences do change over time.

Originality/value

Disincentives to firm innovation were also found, such as knowledge spillover between competitors, leading to free rider problem, weak intellectual property right protection leading to imitation, and underground economy in the cluster resulting from weak implementation of regulation compounded by the difficulties of effectively policing regulation. These factors appear to be particularly strong in a developing economy.

Details

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

Keywords

Abstract

Details

The Russian Urban Sustainability Puzzle
Type: Book
ISBN: 978-1-83982-631-3

Article
Publication date: 17 October 2017

Xiling Yao, Seung Ki Moon and Guijun Bi

This paper aims to present a hybrid machine learning algorithm for additive manufacturing (AM) design feature recommendation during the conceptual design phase.

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Abstract

Purpose

This paper aims to present a hybrid machine learning algorithm for additive manufacturing (AM) design feature recommendation during the conceptual design phase.

Design/methodology/approach

In the proposed hybrid machine learning algorithm, hierarchical clustering is performed on coded AM design features and target components, resulting in a dendrogram. Existing industrial application examples are used to train a supervised classifier that determines the final sub-cluster within the dendrogram containing the recommended AM design features.

Findings

Through a case study of designing additive manufactured R/C car components, the proposed hybrid machine learning method was proven useful in providing feasible conceptual design solutions for inexperienced designers by recommending appropriate AM design features.

Originality/value

The proposed method helps inexperienced designers who are newly exposed to AM capabilities explore and utilize AM design knowledge computationally.

Details

Rapid Prototyping Journal, vol. 23 no. 6
Type: Research Article
ISSN: 1355-2546

Keywords

Open Access
Article
Publication date: 30 June 2011

Hyung-Geun Kim

China is currently developing and promoting an industrial cluster policy at the government level. By enacting the ‘Opinion on promoting industrial cluster development’, China is…

Abstract

China is currently developing and promoting an industrial cluster policy at the government level. By enacting the ‘Opinion on promoting industrial cluster development’, China is supporting the development of industrial clusters. Building an industrial cluster is done by using a single factor but requires many additional factors like regional characteristics, competitiveness factors are also diversified. To evaluate the competitiveness of the Chinese automobile industry cluster, a competitiveness element index should be developed and a competitiveness evaluation method is needed to evaluate the importance of each element. To accomplish this objective, this research applied the analytic hierarchy process (AHP) and focused on the importance of the competitiveness elements.

This research investigated the character is tics regarding cases of clusters and also analyzed the competitiveness of the Changchun automobile cluster located in northeastern China. The purpose of this research is to help Korean enterprises who enter China in the hopes that Korea will emerge as a top automobile production country.

Details

Journal of International Logistics and Trade, vol. 9 no. 1
Type: Research Article
ISSN: 1738-2122

Keywords

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