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Measuring relatedness in a multisectoral cluster: an input--output approach

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  • Karyn Morrissey
  • Valerie Cummins

Abstract

Studies in evolutionary economic geography have found that knowledge spillovers, crucial for the development and maintenance of clusters, tend to flow between sectors that are related via similar inputs and/or outputs. Thus, there is a growing body of literature stating that industrial variety within clusters is beneficial for economic growth, whereby local industrial diversity sparks creativity, new ideas and innovations. Within this context, the Irish Maritime and Energy Resource Cluster (IMERC) is a diverse, multisectoral cluster. Using an Input--Output table this paper examines the intra-cluster linkages, as well as the relatedness in terms of inputs and outputs across the four IMERC pillars: Marine Energy; Shipping, Logistics and Transport; Maritime Safety and Security; and Yachting Products and Services. This analysis found that although IMERC has weak intra-cluster linkages, the four pillars share a high number of related inputs and outputs. Based on this analysis, IMERC has the potential to develop into a strong maritime cluster.

Suggested Citation

  • Karyn Morrissey & Valerie Cummins, 2016. "Measuring relatedness in a multisectoral cluster: an input--output approach," European Planning Studies, Taylor & Francis Journals, vol. 24(4), pages 629-644, April.
    • Handle: RePEc:taf:eurpls:v:24:y:2016:i:4:p:629-644
    DOI: 10.1080/09654313.2015.1127898
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    References listed on IDEAS

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    1. Duffy, David & Timoney, Kevin, 2013. "Quarterly Economic Commentary, Spring 2013," Forecasting Report, Economic and Social Research Institute (ESRI), number QEC20131, march.
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    Cited by:

    1. Yang, Dong & Li, Chengkun & Li, Lu & Lai, Kee-hung & Lun, Venus Y.H., 2022. "Maritime cluster relatedness and policy implications," Transport Policy, Elsevier, vol. 128(C), pages 76-88.
    2. Munday, Max & Reynolds, Laura & Roberts, Annette, 2023. "Re-appraising ‘in-process’ benefits of strategic infrastructure improvements: Capturing the unexpected socio-economic impacts for lagging regions," Transport Policy, Elsevier, vol. 134(C), pages 119-127.
    3. Koliousis, Ioannis G. & Papadimitriou, Stratos & Riza, Elena & Stavroulakis, Peter J. & Tsioumas, Vangelis, 2019. "Strategic correlations for maritime clusters," Transportation Research Part A: Policy and Practice, Elsevier, vol. 120(C), pages 43-57.
    4. Belmartino, Andrea, 2022. "Green & non-green relatedness: challenges and diversification opportunities for regional economies in Argentina," Nülan. Deposited Documents 3697, Universidad Nacional de Mar del Plata, Facultad de Ciencias Económicas y Sociales, Centro de Documentación.
    5. Shi, Xin & Jiang, Haizhou & Li, Huan & Xu, Dong, 2020. "Maritime cluster research: Evolutionary classification and future development," Transportation Research Part A: Policy and Practice, Elsevier, vol. 133(C), pages 237-254.
    6. Wang, Dan & Zhao, Xu & Shen, Lixin & Yang, Zhongzhen, 2020. "Industry choice for an airport economic zone by multi-objective optimization," Journal of Air Transport Management, Elsevier, vol. 88(C).

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