Clustering in Ireland: development cycle considerations

O’Connor, Sean M.; Doyle, Eleanor; Brosnan, Stephen

doi:10.1080/21681376.2017.1402361

Cited by 7 publications

(4 citation statements)

References 40 publications

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“…In terms of the specific policy context of the cluster examined, the Irish Government devoted limited resources to cluster policies since the 1990s (Culliton, 1992; Cooke, 1996; NESC, 1997, 1998). Interest has been recently revived with programmes announced (Enterprise Ireland, 2012, 2016), however, its focus and investments are removed from what is internationally classified as “national cluster policy” (Van Egeraat and Doyle, 2018; O’Connor et al , 2017). Various cluster initiatives have been supported at the regional level in an ad hoc fashion.…”

Section: Discussionmentioning

confidence: 99%

Network diversity, distance and economic impact in a cluster: visualising linkages and assessing network capital

Byrne

Doyle

Hobbs

2021

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Purpose Effective policy to support business ecosystems should build on evidence-based analyses of firm-level activities and outcomes. This paper aims to contribute to this requirement and makes three contributions. The first contribution is to extend the application of the network capital concept to a variety of eight distinct linkage categories (e.g. suppliers, customers and business support agencies) that support networking and clustering, in both activity and impact terms. The second contribution is outlining a novel method of network visualisation (V-LINC) based on the collection of primary and qualitative data. The third contribution is in applying the method to one cluster, information and communications technologies. Design/methodology/approach Qualitative research on the nature and extent of organisational network linkages was undertaken. Structured interviews with a set of focal firms followed a tailored design approach. The concept of network capital was extended and applied to the cluster context by measuring network inputs and output (i.e. investments and impact). The approach was operationalised via a novel impact measurement approach, denoted as V-LINC, an acronym for visualising linkages in networks and clusters. Findings The authors develop a business impact framework exploiting novel linkage visualisations and qualitative data from firms in a cluster in one city region across eight linkage types to capture distinct network capital elements. Organisational inputs into network development, measured as investment and involvement indicators and organisational outcomes from those networks, measured as importance and intensity indicators, are used to assess network performance. A comprehensive, systematic and robust analysis of network elements and performance is possible. Distance is found to interact differently across linkage types. Targeted recommendations may be made from the analysis of local or regional business ecosystems in light of measured business impacts of linkages. Research limitations/implications Due to the resource-intensive nature of data collection, the current study engages a limited sample of firms and interviewees. Applications of this approach in other contexts will permit further research into its usefulness in evaluating business impacts generated through networking activities. Originality/value The method introduced here (V-LINC) offers a novel means to include both geography network theory into an understanding of knowledge relationships and networks within clusters. Accounting for both distance and linkage type reveals which categories of intra-regional and extra-regional linkages generate the greatest impact, given their frequency. The approach adds to available cluster visualisation and analysis approaches through identifying patterns of disaggregated knowledge flows and their impacts, with application to evaluation demands of policy.

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Section: Discussionmentioning

confidence: 99%

Network diversity, distance and economic impact in a cluster: visualising linkages and assessing network capital

Byrne

Doyle

Hobbs

2021

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“…But despite the wide range of research on cluster evolution, there is still no consensus on how to identify the stage of CLC the cluster is in. One of the most used identification models of CLC is the model proposed by Menzel and Fornahl (2010) based on the analysis of the dynamic of the number of firms and employees and qualitative dimension (heterogenity of knowledge), that was deployed by many CLC researchers (Branco and Lopes, 2018; Dyba et al , 2020; Elola et al , 2017, 2012; Mahroum and Al-Saleh, 2015; O’Connor et al , 2017; Shin and Hassink, 2011; Tavassoli and Tsagdis, 2014; Viederytė, 2018). Menzel and Fornahl (2010) admit that in their development, clusters do not jump from one stage to another but slowly turn to the next stage:…”

Section: Theoretical Frameworkmentioning

confidence: 99%

New growth of the Douro wine cluster

Ostapenko,

Africano,

Meneses

2024

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Purpose 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? Design/methodology/approach 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. Findings 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. Research limitations/implications 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. Practical implications 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. Originality/value 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.

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“…Key objectives include promoting export-led growth (Breathnach et al, 2015), generating industry-university R&D partnerships (Barry, 2014b), and developing better linkages between industries (Barry, 2014a;O'Leary and van Egeraat, 2018). One of the key strategies developed to foster linkages and knowledge spillovers between domestic and MNE activities includes the development of collaborative R&D infrastructure and clusters (Department of Jobs, Enterprise and Innovation, 2014), which have been linked to the emergence of industrial clusters (O'Connor et al, 2017). Our study of the impact and persistence of MNE-domestic linkages on export activity contributes to our understanding of these policy efforts.…”

Section: Mnes As Agents Of Structural Changementioning

confidence: 99%

The role of relatedness and strategic linkages between domestic and MNE sectors in regional branching and resilience

Landman¹,

Ojanperä²,

Kinsella³

et al. 2021

Preprint

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Despite the key role of multinational enterprises (MNEs) in both international markets and domestic economies, there is no consensus on whether or how they positively impact their host economy. In particular, do MNEs foster the creation of new domestic firms through knowledge spillovers? In this study, we look at the impact of the presence of related MNE industries on the entry and exit of domestic export industries in Irish regions before, during, and after the 2008 financial crisis. Specifically, we are interested in whether the presence of MNEs in a region results in knowledge spillovers and the creation of new domestic export activities in related sectors. To quantify how related an industry is to a region's current export basket we deploy an existing cohesion variable, closeness, that measures the relatedness of a new industry to existing industries within a region. We also introduce a new variable, strategic closeness, which captures not only the relatedness of industries within a region but their own connectivity or embeddedness. We use a dataset containing all government-supported export firms in Ireland between 2006-2018. We find that the presence of related MNE industries is associated with the entry of new domestic activity, suggesting that Irish regions benefited from domestic-MNE linkages. However this relationship was temporarily lost after the financial crisis and only recently re-established, with domestic entry dependent on the presence of highly embedded MNE sectors. Furthermore, we find that related MNEs help protect domestic industries against exit after the crisis and thereby play a role in enhancing regional resilience.

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Clustering in Ireland: development cycle considerations

Cited by 7 publications

References 40 publications

Network diversity, distance and economic impact in a cluster: visualising linkages and assessing network capital

Network diversity, distance and economic impact in a cluster: visualising linkages and assessing network capital

New growth of the Douro wine cluster

The role of relatedness and strategic linkages between domestic and MNE sectors in regional branching and resilience

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