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This article aims to explore how cluster affiliation moderates the relationship between family involvement and speed of internationalization in family firms. The speed of internationalization is examined in terms of earliness and post-internationalization speed.

The research is based on a sample of 639 Portuguese family businesses (FBs) created and internationalized between 2010 and 2018 that was retrieved from the Iberian Balance Analysis System – SABI database. The partial least squares structural equation modeling (PLS-SEM) was used to assess the measurement and construct the model.

The results suggest that higher levels of family involvement in ownership and management make family firms enter on international markets in later stages of their development but, after the first international market entry, the firms are able to exhibit a higher post-internationalization speed. When considering the effect of cluster affiliation, the authors found that clustered FBs are more likely to engage in early internationalization and to accelerate the post-internationalization process than non-clustered FBs.

The study's findings are explained by the existence of socially proximate relationships with other cluster members, based on similarity, trust, knowledge exchange and sense of belonging, which push family firms to internationalize and increase their level of international commitment over time. The empirical evidence, therefore, highlights the primary role of industrial clusters in moderating the relationship between family involvement, earliness of internationalization and post-internationalization speed.

This study is exploratory in nature and designed to address poorly documented issues in the literature. The dimensions of regional distribution or spatial organisation of Industry 4.0 (I4.0), including the potential role of clusters, have only recently been addressed, with most available studies focusing on advanced, mainly Western European countries. Although developing fast, the literature on I4.0 in other countries, such as the Central and Eastern European or post-transition economies like Poland, needs to pay more attention to the spatial distribution or geographical and organisational aspects. In response to the identified knowledge gap, this paper aims to identify the role of clusters in the transformation towards I4.0. This explains why clusters may matter for advancing the fourth digital transformation, how advanced in implementing I4.0 solutions are the residents of Polish clusters and how they perceive the advantages of cluster membership for such implementation. Finally, it seeks to formulate policy recommendations based on the evidence gathered.

The methodology used in this study combines quantitative analysis of secondary data from a cluster benchmarking survey with a case study approach. The benchmarking survey, conducted by the polish agency for enterprise development in 2021, gathered responses from 435 cluster members and 41 cluster managers, representing an estimated 57% of the current clusters in Poland. In addition to quantitative analysis, a case study approach was used, incorporating primary sources such as interview with cluster managers and surveys of cluster members, as well as secondary sources like company documents and information from cluster organisation websites. Statistical analysis involved assessing the relationship between technology implementation and the adoption of management systems, as well as exploring potential correlations between technology use and company characteristics such as revenue, export revenue share and number of employees using Pearson correlation coefficient.

In Poland, implementing I4.0 technologies by cluster companies is still modest. The cluster has influenced the use of I4.0 technologies in 23% of surveyed companies. Every second surveyed company declared a positive impact of a cluster on technological advancement. The use of I4.0 technologies is not correlated with the revenue of clustered companies. A rather bleak picture emerges from the results, revealing a need for more interest among cluster members in advancing I4.0 technologies. This may be due to a comfortable situation in which firms still enjoy alternative competitive advantages that do not force them to seek new advanced advantages brought about by I4.0. It also reflects the sober approach and awareness of associated high costs and necessary investments, which are paramount and prevent successful I4.0 implementation.

The limitations inherent in this study reflect the scarcity of the available data. This paper draws on the elementary survey administered centrally and is confined by the type of questions asked. The empirical section focuses on an important, though only one selected sector of the economy – the automotive industry. Nevertheless, the diagnosis of the Polish cluster’s role in advancing I4.0 should complement the existing literature.

The exploratory study concludes with policy recommendations and sets the stage for more detailed studies. Amidst the research’s limitations, this study pioneers a path for future comprehensive investigations, enabling a deeper understanding of Polish clusters’ maturity in I4.0 adoption. By comparing the authors’ analysis of the Polish Automotive Group (PGM) cluster with existing literature, the authors uncover a distinct disparity between the theoretical prominence of cluster catalysis and the current Polish reality. Future detailed dedicated enquiries will address these constraints and provide a more comprehensive map of Polish clusters’ I4.0 maturity.

This study identifies patterns of I4.0 implementation and diagnoses the role of clusters in the transformation towards I4.0. It investigates how advanced is the adoption of I4.0 solutions among the residents of Polish clusters and how they perceive the advantages of cluster membership for such transformation. Special attention was paid to the analysis of the automotive sector. Comparing the conclusions drawn from the analysis of the Polish PGM cluster in this case study to those from the literature on the subject, it becomes clear that the catalytic role of clusters in the implementation of I4.0 technologies by enterprises, as emphasised in the literature, is not yet fully reflected in the Polish reality.

This study aims to further develop the CLC stage/path’s identification model that distinguishes between path’s emergence (emergence stage), path’s development (growth stage), path’s sustainment (maturity stage), path’s decline (decline stage) and path’s transformation (renewal stage), and by applying it, define the current stage/path of the Demarcated Douro Region (DDR) cluster. The Port wine industry, which is the dominant industry of the DDR cluster, is at the maturity/decline stage – is the same for the cluster itself?

It is a case study with a longitudinal perspective based on the analysis of the dynamics of the parameters of cluster evolution using available secondary sources (cluster identity/brand; number of firms; number of employees; network; innovation; policies and regulations; and external markets – exports), especially addressing the past decade, that represent the stage of maturity/decline of the cluster’s dominant Port wine industry.

The conclusion is that since the 1990s the Demarcated Douro Region has gone through a “path transformation” where during the following 20 years new “anchors” for the cluster were gradually introduced, such as Doc Douro Wines, new forms of consumption of Port wine, tourism and olive oil. Since 2010 the cluster has entered a growth stage/(new) path’s development, where these “anchors” are in steady growth. The Douro brand is becoming more internationally recognized and established, the number of firms and employees is increasing, the network is restructuring with the creation of cluster-specific official institutions, innovation is especially reflected with increasing heterogeneity through diversification of the clusters into new activities and regulations and policies are supportive for expansion – all these parameters are indicating the rise of the new cycle for the cluster. Thus, the DDR cluster represents an attractive business environment and requires attention from regional policymakers to support the cluster’s development. Especially institutions have been highlighted as internal factors driving clusters growth, European integration as an external factor and firms’ strategies of diversification and internationalization as an appropriate de-locking mechanism for new path’s development.

This research contributes to the CLC theory by further developing and applying a CLC stage/path identification model. It provides a better understanding of the dynamics of the DDR cluster that diverge from its dominant industry life cycle, which is relevant for regional policies and firms’ strategies. This study has its limitations. It provides an exploratory application of the theoretical framework proposed, and consequently, no general conclusions are possible yet. More empirical studies with different clusters in different stages are necessary to test the framework.

These findings are useful to policymakers when designing their policies for cluster development but also for clusters’ entities and actors when making their strategic decisions as it allows based on the verification of the established parameter of CLC to identify its current stage/path of development.

The paper presents a theoretically grounded model for CLC identification and for the first time to the best of the authors’ knowledge applies it to a cluster case – the DDR cluster. This case applies the proposed model and illustrates its usefulness. The model provides the tools for a better understanding of cluster dynamics.

The purpose of this study is to shed light on the twin transition in China in the organization of innovation processes in artificial intelligence (AI) and green technology (GT) development and to understand the role of foreign multinationals in Chinese innovation systems.

A qualitative research approach is used by interviewing executives from German multinationals with expertise in AI and GT development and organization of innovation processes in China. In total, 11 semi-structured interviews were conducted with companies, and the data were analysed with a thematic qualitative text analysis.

The findings show that AI applications for GT are primarily developed in cross-company projects that are led by local and regional authorities through the organization of industrial districts and clusters. German multinationals are either being integrated, remaining autonomous or being excluded from these twin transition innovation processes.

This paper aims to fill the gap in the literature by providing one of the first qualitative approach towards twin transition innovation processes in China and exploring the integration of multinational enterprises in cluster organizations. To the best of the author’s knowledge, this is one of the first twin transition studies from this perspective in emerging economies.

This paper aims to analyse how local agri-food systems (LAFS), compared to other production models, can offer innovative responses to the important environmental challenges facing food production under the twin transition. These responses are more conducive to community inclusion and local development.

The paper combines territorial development, clusters and industrial districts literature with studies on agri-food industry environmental problems and twin transition technologies to develop an agri-food systems typology. This typology is based on a territorial approach to environmental challenges of food production and serves to illustrate the ways in which LAFS can provide innovative responses to these challenges.

The study allows to visualise the differences between LAFS and other agri-food production models, showing how the operationalisation and implementation of digitisation occur at territorial level and how rural communities are involved in the process. The theoretical proposal emphasises not assuming that technology is inherently beneficial but ensuring that its implementation is inclusive and generates social value for the communities.

The paper aims to enrich future research by adopting a territorial perspective to study the twin transition challenges associated with food production systems.

This article examines the strategic actions of multinational corporations (MNCs) in creating social value at the base of the pyramid (BoP), providing insights into novel business models (BMs) and tactics employed for poverty alleviation.

This conceptual article links three relevant pieces of literature – creating shared value (CSV), the three-value creation logic and the three core values of social development – to analyze the current research and real-world examples of MNCs implementing the BoP BMs.

The article identifies four strategies and 11 tactics used by MNCs to adapt BMs elements (value proposition, value constellation and value capture) and generate social value at the different levels (coverture of basic needs, self-esteem and freedom from servitude) by following the distinct value creation logics (chain, shop and network).

This article provides a conceptual framework that links relevant literature and sheds light on the strategic actions that MNCs apply in their BMs to tackle the multidimensionality of poverty in the BoP markets.

In developing countries like Tanzania, gems and jewellery industry mainly consists of disintegrated and unstable micro and small workshops which operate in a way that misalign value addition processes. This study is aimed to bridge gap by focussing on exploitation of industrial clusters in social normalisation and economic resilience to developing countries. The world economic shocks has been not only individually experienced but also globally shared while disrupted lives across all countries and communities and negatively affected global socio-economic growth.

Furthermore, the explorative design was adopted in this study in order to explore needs of respondents, and with the aim to direct the study towards a descriptive design. The sample frame consists of participants in gems and jewellery activities in Tanzania whereby sample was drawn from Dar es Salaam and Arusha. Semi-structured interview was used to collect quantitative data to establish evidence of Tanzanians’ SSJs linked to global value chains (GVCs).

Results revealed the benefits of exploitation of artisanal industrial clusters to Tanzanians’ SSJs when linked to global value chains (GVCs). Findings of the study demonstrate the importance of artisanal industrial clusters in facilitating Tanzanians’ SSJs to access GVCs. Further, insufficient education, trust and social protection directly affects inclusive GVCs, inferring that the impact of artisanal industrial clusters on inclusive GVCs in social normalisation and economic resilience.

Study findings reveals shortcomings in existing regulatory framework of linking Tanzanians’ SSJs to artisanal industrial clusters, for improvements to better support the inclusiveness in GVCs. Findings of this research invite interventions on institutional capabilities and entrepreneurial competencies to enhance the capabilities of small-scale jewellers (SSJs). Like other studies, this study involved cross-sectional data, limit targeted study population as representative of SSJs in industrial clusters and GVCs in economic crises at limited time.

The study findings makes important practical contributions to the Tanzania’s SSJs by examining mediating role of artisanal industrial clusters hence informing policymakers of mining sector how to improve accessibility on GVCs by focus on offering great institutional capabilities and entrepreneurial competencies. These findings will help SSJs and policy makers to get better understanding of the relationships in exploitation of artisanal industrial clusters when accessing GVCs. Therefore, they can make better decisions on implementing artisanal industrial clusters as well as management accessing GVCs, so that SSJs will attain the best possible performance.

This emphasises the importance of community empowerment in the GVCs process through artisanal industrial clusters. Study findings indicate the influence of industrial relations to social dynamics which are previously inadequately addressed and scantly researched. In actual fact study propose initiatives that ensure local communities benefit socially from the integration of SSJs into GVCs through artisanal industrial clusters. Findings suggest local communities that take into account inter-sectionality of artisanal industrial clusters and inclusive GVCs, by considering how factors like education, trust and social protection status intersect to influence the social inclusiveness of SSJs.

There is limited evidence of linking Tanzanians’ SSJs to GVCs in social normalisation and economic resilience and few researchers have explored this topic. This article leverages exploitation of industrial clusters in normalisation and economic resilience to developing countries such as Tanzania as way of improving shared prosperity, sustainability, inclusive growth, cohesion, value chain upgrading and financial inclusion to SSJs.

This study theoretically investigates the extant literature published about circular economy and sustainable development to identify significant research themes, the most relevant authors, countries and journals.

Bibliometric analysis is used, followed by cluster formation using co-citation analysis. The clusters are discussed in-depth to identify emerging themes and future research areas.

By systematically reviewing 596 research articles, significant themes of research in this field were found. These include frameworks and indicators to define and assess the circular economy, circular business models and use cases, global and industrial contexts of application of circular economy and different dimensions of the circular economy.

Publications from only one database have been used. Only articles published in relevant academic journals have been used for the bibliometric analysis. For co-citation analysis and cluster formation, only articles with a high number of citations were selected.

The analysis of the various clusters revealed research areas that can be explored in future research to understand the circular economy better and implement its practices to attain sustainability.

This paper aims to explore the interplay between industrial diversity and sustainable economic development in US counties.

Among other popularly used measures, this study uses an underused measure, Hachman index, to gauge the degree of industrial diversity in the models. To capture the impact of industrial diversity on the local community, this study estimates the relationship of two diversity measures to four traditional socioeconomic indicators: per capita personal income growth, gross domestic product per worker, income inequality ratio and poverty rate.

Statistical results suggest that industrial diversity, which is measured by Hachman index, is significantly related to the four socio-economic indicators. Industrial diversity can positively contribute to regional per capita personal income growth and mitigate income inequality and poverty stress; however, it is negatively related to the gross domestic product (GDP) per worker, which means industrial specialization may contribute to GDP per worker growth.

The findings of this study show that there is a nonlinear relationship between industrial diversity and all socioeconomic indicators. Most of the control variables, human capital variables and business and industry profile variables also display significant and positive impacts on economic development.