2012
DOI: 10.1111/j.1944-8287.2012.01170.x
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The Emergence of New Industries at the Regional Level in Spain: A Proximity Approach Based on Product Relatedness

Abstract: Key words: regional branching diversification new industries capabilities Spain proximity index abstract How do regions diversify over time? Inspired by recent studies, we argue that regions diversify into industries that make use of capabilities in which regions are specialized. Since the spread of capabilities occurs through mechanisms that have a strong regional bias, we expect that capabilities that are available at the regional level play a larger role than do capabilities that are available at the countr… Show more

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Cited by 314 publications
(256 citation statements)
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References 42 publications
(92 reference statements)
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“…In terms of relatedness, the greater the regional variety across related sectors, the more learning opportunities will become available and inter-sectoral knowledge spillovers, and economic performance will also improve [108]. This is relevant to RV between tourism sectors (and between tourism sectors and other sectors) with balanced cognitive proximity.…”
Section: Prioritisation Of Tourismmentioning
confidence: 99%
“…In terms of relatedness, the greater the regional variety across related sectors, the more learning opportunities will become available and inter-sectoral knowledge spillovers, and economic performance will also improve [108]. This is relevant to RV between tourism sectors (and between tourism sectors and other sectors) with balanced cognitive proximity.…”
Section: Prioritisation Of Tourismmentioning
confidence: 99%
“…By comparing the cluster classification introduced by Porter (2003) and the proximity index proposed by Hidalgo et al (2007), they show that Spanish provinces with a wide range of related industries tend to enjoy higher economic growth rates. Focussing on regional competitiveness, Boschma et al (2013) instead explore the role of regional-and country-level density measures around a product on a region's probability to develop a revealed comparative advantage in that product. By using export data on 50 Spanish regions at the NUTS 3 level in the period 1988-2008, they show that proximity to the regional industrial structure plays a much larger role in the emergence of new comparative advantage industries in regions than does relatedness to the national industrial structure.…”
Section: Geography Technological Relatedness and The Relative Contrmentioning
confidence: 99%
“…A recent body of literature has highlighted the role of technological relatedness for starting a new sector in a country (Hausmann and Hidalgo, 2009;Hidalgo, 2009), a region (Boschma and Iammarino, 2009;Neffke et al, 2011;Boschma et al, 2012Boschma et al, , 2013 or a firm (Breschi et al, 2003;Poncet and de Waldemar, 2012;Neffke and Henning, 2013). In particular, empirical work in economic geography has shown that knowledge spillovers can spur innovation and growth across economic units located in space, as long as the right-not too little, not too much (Nooteboom, 2000;Boschma, 2005)-extent of cognitive proximity exists among the relevant economic actors.…”
Section: Introductionmentioning
confidence: 99%
“…Conclusive remarks are incorporated in the final section of the study. Different authors agree that geographic proximity is worth the attention that it gets for it enables collaboration, innovation (Letaifa and Rabeau 2013;Boschma et al 2013;Castellani et al 2013;D'Este et al 2013;Maskell 2014) and knowledge sharing (Crespo et al 2014;D'Angelo et al 2013). In addition, social networks are analyzed to understand their relationship with innovations (Casanueva 2013;Letaifa and Rabeau 2013), production (Carswell 2013) and knowledge sharing (Lorenzen and Mudambi 2013).…”
Section: Introductionmentioning
confidence: 99%
“…Different methods are applied in order to analyze qualitative and quantitative data, such as correlation and regression analysis (Casanueva et al 2013;Lai et al 2014;Tavassoli, Carbonara 2014;Crespo et al 2014;D'Angelo et al 2013), gravitation model (Castellani et al 2013), case analysis (Ben Lafeita and Rabeu 2013;Boschma et al 2013;Bouncken and Kraus 2013;Carswell 2013;Lorenzen, Mudambi 2013;Tokatli 2013;Dobusch and Schussler 2013;Morrison et al 2013) or literature analysis (Crane et al 2014;D'Agostino et al 2013;Maskell 2014;Feldman 2014;D'Este et al 2013;Ketels 2013). The problem of providing the most effective way to evaluate the data of different phenomena, which are mentioned in clusters' studies, could be by performing a quantitative evaluation of clusters' performance ).…”
Section: Introductionmentioning
confidence: 99%