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Through the magnifying glass: an analysis of regional innovation models based on co-word and meta-synthesis methods

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Abstract

This paper performs a fine-grained analysis of regional innovation models discussed in the literature, using a combination of quantitative (co-word analysis) and qualitative (meta-synthesis) methods applied to 300 papers from the Scopus and Sage databases covering the period 1990–2013. The co-word analysis produced knowledge maps that identify the most frequently occurring regional innovation models and group them into three clusters: Cluster 1 (industrial districts, local production systems), Cluster 2 (industrial clusters and regional clusters), and Cluster 3 (innovative milieus, regional innovation systems, innovation networks and learning regions). The meta-synthesis analysis used for exploring the content of these models identified three main themes, each with several sub-themes, as well as distinct features of the regions implementing them. Based on these distinctions, a typology of regions was derived, distinguishing between Early Innovators, Transitional Innovators and Advanced Innovators, which can serve as a useful instrument for academic researchers, policy-makers and practitioners involved in regional innovation.

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Notes

  1. The software tool was developed by the Centre for Science and Technology Studies (CWTS) at Leiden University in the Netherlands.

  2. See details at http://cor.europa.eu/.

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Authors and Affiliations

  1. Department of Information Technology Management, School of Management and Economy, Tarbiat Modares University, Tehran, Iran

    Reza Naghizadeh, Shaban Elahi & Sepehr Ghazinoory

  2. Department of Industrial Engineering, College of Engineering, Tehran University, Tehran, Iran

    Manoochehr Manteghi

  3. H-STAR Institute, Stanford University, 210 Panama Str., Cordura Hall, Stanford, CA, 94304, USA

    Marina Ranga

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  1. Reza Naghizadeh
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Naghizadeh, R., Elahi, S., Manteghi, M. et al. Through the magnifying glass: an analysis of regional innovation models based on co-word and meta-synthesis methods. Qual Quant 49, 2481–2505 (2015). https://doi.org/10.1007/s11135-014-0123-7

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