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This paper aims to examine whether in old industrial regions, the trajectory of clusters follows that of their corresponding industry or deviates from it and which are the factors that account for cluster evolution. This paper deals with the issue of how established clusters either renew or transform themselves in such regions and how they adapt to changes in their corresponding international industries.

This research paper draws from in-depth case studies on six industrial clusters, takes a longitudinal perspective and uses a multi-level and qualitative analysis. Based on existing literature, the paper suggests and exploratory analytical framework with four alternative scenarios for cluster evolution and three broad factors: cluster knowledge base, social capital at cluster and region-level and public policies.

Clusters do not always follow the life cycle of its dominant industry. The paper clearly shows a diversity of cluster evolution across clusters and even within clusters (at subcluster level). This study suggests that cluster knowledge diversity and heterogeneity allow to broaden the scope of evolutionary trajectories available; the same goes for social capital at cluster and region levels.

The main limitation of this paper lies in its qualitative approach that makes its conclusions more suggestive than conclusive. In any case, further research on other Basque clusters may corroborate or question its findings.

The paper offers an empirical and longitudinal study on cluster evolution, very much needed to the ongoing theoretical discussion on this issue. So far, there are very few empirical studies on cluster evolution with this perspective. At the same time, it presents a theoretical framework to analyse diversity of cluster evolution in old industrial regions that builds on Menzel and Fornah’s (2010) model.

ISO 9001 certification is nowadays considered to be one of the most effective tools that can be adopted for guiding the management of Quality Systems. The stunning growth observed by these standards all over the world confirms a strong polarization of enterprises' interest in this practice. Owing to the wide incidence of this phenomenon, a deep investigation of ISO 9001 diffusion over time is of mandatory importance. The research here reported covers the development of statistical models in order to characterize the ISO 9001 certification evolution on a country basis, as well as worldwide.

Based on the pioneering results obtained by Saraiva and Duarte, an attempt is now made to: identify clusters of countries, according to their ISO 9001 evolution patterns; characterize the worldwide ISO 9001 certification evolution; identify which are the main evolution perspectives for ISO 9001 diffusion; identify significant variables that may influence ISO 9001 quality management systems diffusion; develop mathematical models in order to characterize the ISO 9001 certification evolution on a country‐by‐country basis.

The research carried out allowed one to analyze the worldwide evolution of ISO 9001 certification and suggest new prediction models for the diffusion of quality management systems certification at different geographical realities.

This paper covers the development of statistical models in order to characterize the ISO 9001 certification evolution on a country basis, as well as worldwide.

This paper aims to analyze the impact of the capabilities and strategies of the actors (micro-dynamics), learning process and networks (meso-dynamics) and institutions (macro-dynamics) in the evolution of the Brazilian ceramic clusters. Based on these experiences, managerial and policy implications are suggested.

Main data were gathered through 22 in-depth face-to-face interviews with managers and industry experts. The data were complemented by documentary analysis, including brand documents, descriptions of internal processes and Brazilian and international ceramics magazines and journals. In addition, the authors also use information from the previous experience of the authors who have been studying the sector for more than 15 years.

The paper provides empirical insights about the main characteristics of the evolution of two main Brazilian ceramic tiles clusters, as well as how there are different patterns of evolution among them. The results of this paper show that Brazilian ceramic tile clusters do not necessarily follow the life cycle model of their dominant industry, by proving evidence that different clusters in the same industry can follow different evolutionary paths.

This paper shed light on a multi-level approach (micro, meso and macro) of dynamics of the clusters and how it impacts the cluster’s life cycle. The micro-dynamics dimension was analyzed by the capabilities and strategies of local ceramic tile manufacturers. The meso-dynamics are being considered the localized learning processes, especially from those that arise from interactions, collaboration and networks carried by local and foreign suppliers. The macro-dynamics were considered by the role of local demand, factors conditions, institutions, historical legacy in the clusters’ emergence along with path dependence mechanisms.

The paper includes implications for both clusters to promote innovation, particularly to keep and create market and technological leadership through the establishment of partnership between firms and clients, regulators and research centers and universities are crucial for innovation.

This paper fulfils an identified lack of attention regarding the under-appreciation of the context-specific issues such as the capabilities of the actors, networks and institutions that may influence the long-term development of clusters.

This study aims to systematise the links between firms’ strategies (corporate and business) and the cluster dynamics (through the cluster life cycle [CLC] perspective) and propose an integrative framework bridging firms’ strategic behaviour and cluster dynamics (CLC).

The methodology used is an integrative literature review, which provides a distinctive form of research.

The study identifies several links between firms’ strategies (corporate and business) and the cluster dynamics (CLC), namely: (1) firms’ strategies as a triggering factor of cluster evolution; (2) firms’ strategies and path's decline; (3) firms’ strategies and cluster’s renewal; (4) resilience strategies and the cluster life cycle; and (5) cluster’s features and firms’ strategies.

This study contributes to developing strategic management theory and cluster theory by bridging firms' strategies and cluster dynamics (CLC). It proposes a new conceptualisation of the impact of cluster dynamics on firms' strategic choices – firstly, it proposes a specific approach to identify the CLC; and secondly, it develops an integrative framework model that relates firms' strategies and each stage of the CLC. These are theoretical tools relevant for further advancements in this area of research, as they can be applied in studies of different clusters for validation, something that was not done.

The integrative framework is expected to be helpful to company managers, allowing them to design better strategies that account for dynamic cluster environments.

This study aims to fill this gap in the literature by systematising the links between firms' strategies (corporate and business) and the cluster dynamics (CLC).

This study aims to propose a visualized model of hot technology evolution to describe its development.

The basic concept is to divide a technological field into a timeline consisting of several patent clusters. Hot technology trajectories are then explored using their continuity, as well as the point in time at which they occur.

Patents in orthopaedics between 1999 and 2014 have been chosen as the research subjects and the field is divided into several hot technology trajectories. A further step is taken by interpreting high-frequency key terms. Three categories – spine-related materials, bone repairing materials and bone plates – have been identified.

The trajectories presented by evolving diagrams allow readers to understand the evolution of hot technology and help analysts to plan layout and strategies to remain competitive.

Patent clusters reflect the knowledge context of technology development. Previous studies have focused on only new technology evolution and have rarely explored the knowledge context of hot patents that have been frequently cited in recent years. Such patents often guide the development of technology.

This paper aims to analyse the evolution of Chinese industrial ethnic clusters in Italy, by focusing on the role of social networks and the processes behind the phenomenon of Chinese worker exploitation and entrepreneur “self-exploitation”.

The case study is a sub-cluster of micro and small enterprises owned by Chinese entrepreneurs within the leather industrial district of Florence, Italy. This research adopts the following mixed methods: a small-scale survey to capture the characteristics of the sub-cluster and a social network analysis to describe cluster evolution, complemented by life-course interviews conducted with key informants and entrepreneurs.

Migrant social capital and social networks play a central role in the evolution of the case study sub-cluster. Social networks play a supportive role in migration, job creation, entrepreneurship formation and the creation of business opportunities. Simultaneously, they enhance the phenomenon of worker exploitation and entrepreneur self-exploitation. Furthermore, the more the business community grows, the more the economic performance of ethnic enterprises depends on agglomeration forces produced by the cluster.

The findings suggest a series of potential policies to upgrade the ethnic enterprises' capacities, to increase their formality and inclusion in the Italian social and economic systems and sub-cluster.

To the authors’ knowledge, this paper is the first attempt to examine the evolution of social networks in relation to the phenomenon of Chinese worker exploitation and entrepreneur self-exploitation in an ethnic industrial sub-cluster.

This paper aims to review the literature on carbon trading from the perspective of evolution, finds out the evolution path of these literatures and gives out the future research hotspots in this field.

Uses visualization tools (CiteSpace and HistCite) to systematically categorize the literature on carbon-trading schemes in the Web of Science core collection from 1998 to 2018, comprehensively analyzes carbon-trading schemes from four dimensions, namely, discipline evolution, keyword evolution, citation cluster evolution and citation path evolution.

Research on carbon-trading schemes has a specific development and evolution path along four dimensions, namely, in the discipline dimension, the largest change lies in the mathematics pointed to by at least four different disciplines; the keyword evolution dimension shows a gradual deepening emphasis on coordinated development; citation clusters identify three major clusters – carbon prices, China’s carbon trading, carbon market and supply chain; and citation paths identify three major evolutionary paths, the most important of which shows that “What affects carbon price?” has changed to “What is the impact of carbon prices?”

Reveals the evolution path of carbon trading research studies and proposes four possible development directions for carbon-trading scheme research, which is helpful for future carbon trading-related research and serves as a reference for the promotion of and improvements in carbon-trading schemes.

The purpose of this paper is to attempt to calculate the trust degree between two enterprises in an industrial network using grey correlation degree algorithm for exploring characteristics of community structure and evolution rules of cluster cooperation networks in axle‐type and satellite‐type clusters.

Starting from analysis of trust formation mechanism of inter‐enterprise in industrial networks, adjacency of inter‐enterprise relationship, their information acquisition ability, their influence power in network and their past interaction experience are chosen as influencing factors of the trust between two enterprises. Grey correlation degree algorithm was chosen to calculate the trust degree between two enterprises in an industrial network. According to the rules of dynamic adjustment of trust degree originated from thoughts of the prisoners' dilemma model, computer simulation is applied to explore characteristics of community structure and evolution rules of cluster cooperation network in axle‐type and satellite‐type clusters.

With the dynamic adjustment of enterprises' trust degree, the network density of axle‐type and satellite‐type cluster networks was decreasing as the cluster scale was enlarging, and eventually tended to be stable; community structure was emerged in axle‐type and satellite‐type industrial clusters as the cluster scale was enlarging; community characteristics were obviously stronger in axle‐type cluster networks than in satellite‐type; communities were overlapped in axle‐type cluster networks, that is, bridge nodes emerged between communities.

This paper is the first to apply the grey correlation degree algorithm to calculate the trust degree between two enterprises in cluster networks for designing the rules of dynamic adjustment of trust degree.

This paper presents an empirical contribution to the literature on cluster evolution, highlighting the decline phase. The analysis focuses on the footwear sector in Rio Grande do Sul (RS) state, in southern Brazil, where an important footwear cluster is located, which was once considered one of the world's largest footwear clusters. The purpose of this study is to analyse the transformation of this footwear industrial sector since the beginning of the 2000s using several sectoral statistics.

This paper presents an empirical and longitudinal study that comprises the sourcing of 20 years of secondary data, based on official sources. The main data analysed were production, price, industrial structure, labour market and foreign market.

The main results indicated a significant reduction in production, export and employment. In addition, a precarization of the labour market was observed, with lower wage levels, even with an increase in the formal qualification of labour over time. The finding is that the RS footwear sector underwent a huge structural change and lost the status of a worldwide supercluster. This decline occurred due to two central factors: an external shock related to China's entry into the international and Brazilian domestic markets, accompanied by a slowdown in the Brazilian economy since 2015; and the difficulty of local firms responding to the new challenges.

Synthesizing the findings, it is understood that this paper contributes to registering the trajectory of decline over time of the footwear sector in RS. In this sector, the Sinos Valley cluster is located, historically known as a footwear producing and exporting supercluster. This cluster loses the characteristic of a “supercluster”, but it still remains an important footwear cluster in Brazil. Therefore, this study reinforces the existence of fragilities already pointed out by the literature in Schimtz (1999) and, more recently, in Schmidt (2020). The need to address a set of fragilities remains current, both at the micro- and meso-levels. This is key to reversing the decline trajectory of the cluster and the sector. Moreover, as recent studies on clusters point out, one still must think about the impact of another ongoing paradigmatic transformation concerning the use and development of Industry 4.0 technologies. Thus, the central challenge is to think about and implement new public and private policies. The historical, economic and social relevance of the sector and the cluster demand efforts to reverse the decline.

This study focuses to contribute to the discussion about the decline of the footwear production in the region by analysing secondary data regarding the industrial sector. This is an analysis at the meso-level (industry). The authors understand that the originality of the research lies in the longitudinal analysis for a recent period (past 20 years) that captures the greatest current crisis experienced by the region.

This research paper examines how hub firm transformation and restructuring of network partnerships shape the development of industrial clusters in China.

Questionnaire data were collected from 210 managers (response rate 70.9 percent) from the manufacturing industrial clusters in Eastern China.

The results inform that a cluster’s hub firm transformation influences the evolution of the cluster. Though the hub firm may possess transformation capabilities, the cluster is likely to be weakened if network partnerships and resource synergy are not formed amongst the cluster members.

This paper, in examining the individual- and firm-level attributes of orchestration capability and their interactions, sheds light on the firm level and inter-firm level relationships between resources and innovation in an industrial cluster.

To facilitate learning and the upgrading of firms within an industry cluster and promote a cluster’s innovation network, policymakers can initiate preferential policy measures to cultivate support to strategically transform a cluster’s hub firm, thus fostering cluster network growth.

The paper studies the evolution of clusters by investigating the hub firm transformation and member firm interaction. Focusing on the inter-firm network interactions lends a richer understanding of the nuances of the evolution of industrial clusters in Asia.