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Spatializing Social Networking Analysis to Capture Local Innovation Flows towards Inclusive Transition

Author

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  • Carmelina Bevilacqua

    (CLUDsLab, PAU Department, Università degli Studi Mediterranea of Reggio Calabria, 89124 Reggio Calabria, RC, Italy)

  • Poya Sohrabi

    (CLUDsLab, PAU Department, Università degli Studi Mediterranea of Reggio Calabria, 89124 Reggio Calabria, RC, Italy)

  • Nourhan Hamdy

    (CLUDsLab, PAU Department, Università degli Studi Mediterranea of Reggio Calabria, 89124 Reggio Calabria, RC, Italy)

Abstract

The location of the local network of firms impacts, positively or negatively, their economic performance. The interactions between different sectors in a territory are still not easily observable. We test the complexity of the economic structure at a local level, given the availability of data at a very granular scale. This could greatly assist in observing sectors or/and locations that play a dominant role in the regional economy. Thus, in order to interpret the economic structure of a territory, we used cluster-based analysis. The analysis helps in evaluating the interconnections among sectors that constitute a cluster. A novel method of describing the territorial economic structure is presented by applying Social Network Analysis (SNA) within cluster-based analysis to characterize the importance of both location and economic interconnections. In this study, we focus on the industrial agglomerations in Calabria, Italy, to underpin the potential of the region’s industries by using social networking analysis metrics. This research put forward new interpretations of SNA metrics that describe regional economic compositions. Our findings reveal that territorial social networks are a potential instrument for understanding interactions in regional systems and economic clusters and might help in highlighting local industrial potentials. We believe that this study’s results could be considered as the initial steps for a pioneer data-driven place-based structural analysis model.

Suggested Citation

  • Carmelina Bevilacqua & Poya Sohrabi & Nourhan Hamdy, 2022. "Spatializing Social Networking Analysis to Capture Local Innovation Flows towards Inclusive Transition," Sustainability, MDPI, vol. 14(5), pages 1-19, March.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:5:p:3000-:d:763996
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    References listed on IDEAS

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    2. Carmelina Bevilacqua & Poya Sohrabi & Nourhan Hamdy & Federica Mangiulli, 2023. "Mapping Connections between Neighborhoods in Response to Community-Based Social Needs," Sustainability, MDPI, vol. 15(6), pages 1-22, March.
    3. Xiaoyi Xie & Peiji Shi, 2023. "Dynamic Evolution and Collaborative Development Model of Urban Agglomeration in Hexi Corridor from the Perspective of Economic Flow," Land, MDPI, vol. 12(2), pages 1-20, January.

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