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A new approach to the identification of regional clusters: hierarchical clustering on principal components

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  • M. Argüelles
  • C. Benavides
  • I. Fernᮤez

Abstract

This study focuses on the identification of regional business clusters as a primary step in the design and implementation of cluster-based development strategies. A methodology that has not been used previously to identify clusters is applied to data on inter-industry linkages from the input-output table of a region in northern Spain. The first advantage of this approach, hierarchical clustering on principal components (HCPC), over the use of factorial analysis alone, is that it involves the application of objective clustering techniques to the principal components analysis results, which leads to a better cluster solution. A second advantage is derived from using a mixed algorithm for the clustering process - a combination of the Ward's classification method with the K-means algorithm - which improves the robustness of the final results.

Suggested Citation

  • M. Argüelles & C. Benavides & I. Fernᮤez, 2014. "A new approach to the identification of regional clusters: hierarchical clustering on principal components," Applied Economics, Taylor & Francis Journals, vol. 46(21), pages 2511-2519, July.
    • Handle: RePEc:taf:applec:v:46:y:2014:i:21:p:2511-2519
    DOI: 10.1080/00036846.2014.904491
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    Cited by:

    1. Juárez-Torres Miriam & Puigvert Jonathan & Zazueta-Borboa Francisco, 2022. "The Role of Clusters in the Performance of the Mexican Economy," Working Papers 2022-06, Banco de México.
    2. Song, Bingjie & Robinson, Guy M. & Bardsley, Douglas K. & Xue, Yanlong & Wang, Bing, 2023. "Multifunctional agriculture in a peri-urban fringe: Chinese farmers’ responses to shifts in policy and changing socio-economic conditions," Land Use Policy, Elsevier, vol. 133(C).
    3. Gökhan Önder & Cemil Ulukan, 2020. "Innovation and the network position of firms: the case of the Eskişehir–Bilecik–Kütahya ceramic cluster in Turkey," Economia e Politica Industriale: Journal of Industrial and Business Economics, Springer;Associazione Amici di Economia e Politica Industriale, vol. 47(4), pages 589-612, December.
    4. Adem Sakarya, 2023. "Clustering potential of organized industrial zones in Türkiye," Asia-Pacific Journal of Regional Science, Springer, vol. 7(1), pages 255-276, March.
    5. Zhenshan Yang & Michael Dunford, 2017. "Cluster evolution and urban industrial dynamics in the transition from a planned to a socialist market economy: the case of Beijing," Spatial Economic Analysis, Taylor & Francis Journals, vol. 12(1), pages 50-71, January.
    6. Waßenhoven, Anna & Rennings, Michael & Laibach, Natalie & Bröring, Stefanie, 2023. "What constitutes a “Key Enabling Technology” for transition processes: Insights from the bioeconomy's technological landscape," Technological Forecasting and Social Change, Elsevier, vol. 197(C).
    7. Gulbis Ivo & Geipele Sanda, 2016. "Social Partner Involvement in Latvia Special Economic Zones," Baltic Journal of Real Estate Economics and Construction Management, Sciendo, vol. 4(1), pages 145-152, November.
    8. Andrés Niembro & Jésica Sarmiento, 2021. "Regional development gaps in Argentina: A multidimensional approach to identify the location of policy priorities," Regional Science Policy & Practice, Wiley Blackwell, vol. 13(4), pages 1297-1327, August.
    9. Chiambaretto, Paul & Combe, Emmanuel, 2023. "Business model hybridization but heterogeneous economic performance: Insights from low-cost and legacy carriers in Europe," Transport Policy, Elsevier, vol. 136(C), pages 83-97.
    10. Maria Jose Murcia & Pilar Acosta, 2023. "Accounting for Plural Cognitive Framings of Growth and Sustainability: Rethinking Management Education in Latin America," Journal of Business Ethics, Springer, vol. 185(2), pages 299-313, June.

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