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Territorial innovation models: to be or not to be, that’s the question

David Doloreux, Jose Gaviria de la Puerta, Iker Pastor-López, Igone Porto Gómez (), Borja Sanz and Jon Mikel Zabala-Iturriagagoitia
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David Doloreux: HEC Montréal
Jose Gaviria de la Puerta: University of Deusto
Iker Pastor-López: University of Deusto
Igone Porto Gómez: University of Deusto
Borja Sanz: University of Deusto
Jon Mikel Zabala-Iturriagagoitia: University of Deusto

Authors registered in the RePEc Author Service: Jon Mikel Zabala Iturriagagoitia ()

Scientometrics, 2019, vol. 120, issue 3, No 10, 1163-1191

Abstract: Abstract Industrial agglomerations are key in explaining the development paths followed by territories, particularly at sub-national levels. This field of research has received increasing attention in the last decades, what has led to the emergence of a variety of models intended to characterize innovation at the regional level. Moulaert and Sekia (Reg Stud 37:289–302, 2003) introduced the concept of ‘Territorial Innovation Models’ (TIMs) as a generic name that embraced these conceptual models of regional innovation in the literature. However, the literature does not help to assess the extent to which convergence or divergence is found across TIMs. In this paper we aim to clarify if there are clear boundaries across TIMs, so each TIM has particular characteristics that make it conceptually different from others, and hence, justify its introduction in the literature. Based on natural language processing methodologies, we extract the key terms of a large volume of academic papers published in peer review journals indexed in the Web of Science for the following TIMS: industrial districts, innovative milieu, learning regions, clusters, regional innovation systems, local production systems and new industrial spaces. We resort to Rapid Automatic Keyword Extraction to identify the associations between the topics extracted from the previous corpus. Finally, a configuration to visualise the results of the methodology followed is also proposed. Our results evidence that the previous models do not have a unique flavour but are rather similar in their taste. We evidence that there is quite little that is truly new in the different TIMs in terms of theory-building and the concepts being used in each model.

Keywords: Territorial innovation models; Bibliometric analysis; Natural language processing; Regional development (search for similar items in EconPapers)
Date: 2019
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DOI: 10.1007/s11192-019-03181-1

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