Geographical clustering and firm growth: Differential growth performance among clustered firms
By: C.-Y. Lee. Research Policy, Vol. 47, Iss. 6, pp. 1173-1184, 2018.
Abstract: “This paper investigates the effect of being located in a cluster on firm growth. In particular, it focuses on the differential growth effect of being located in a cluster, or a growth divide among clustered firms, based on the idea that, contrary to the conventional wisdom, advantages of geographical clustering are not randomly or equally available to clustered firms. Due to the intense competition among clustered firms for resources such as creative talent, firms who are more attractive to the resources are more likely to entice better resources and hence achieve higher growth. Our empirical analysis of firms in nine industries across six countries shows that being located in a cluster per se does not have a positive effect on firm growth and that domestic technological leaders with a sufficient technological distance to the global technological frontier show differentially higher growth due both to the attractiveness to promising resources and to the opportunity for incoming knowledge spillovers from global technological leaders.” [ABSTRACT FROM AUTHOR]
Innovation Networks and Clusters Dynamics
By: B. Desmarchelier, L. Zhang. Research Institute for Economic Integration Working Papers Series, Working Paper No. 2018-04, 2018.
Abstract: “Contributions in terms of clusters life cycle indicate that intense interactions between a variety of agents within the cluster are essential to its success. Despite being accepted by the literature, this view has not yet been confirmed by analyses of large temporal networks of interactions within industrial clusters. This paper proposes to fill this gap by building and studying the innovation networks of three clusters over a 10 years period. We find that clusters’ growth is all but smooth and that low assortativity and preferential attachment among agents can constitute safeguards against clusters decline. Also, we bring evidence that clusters’ innovation networks are resilient to decline. This observation supports contributions advocating for non-deterministic life- cycles in which clusters can still grow, even after a period of pronounced decline.” [ABSTRACT FROM AUTHORS]
Growth and the Geography of Knowledge
By: M. Aloi, J. Poyago-Theotoky, F. Tournemaine. CESifo Working Paper No. 6951, ISSN: 2364‐1428, 2018.
Abstract: “We analyse how spatial disparities in innovation activities, coupled with migration costs, affect economic geography, growth and regional inequality. We provide conditions for existence and uniqueness of a spatial equilibrium, and for the endogenous emergence of industry clusters. Spatial variations in knowledge spillovers lead to spatial concentration of more innovative firms. Migration costs, however, limit the concentration of economic activities in the most productive region. Narrowing the gap in knowledge spillovers across regions raises growth, and reduces regional inequality by making firms more sensitive to wage differentials. The associated change in the spatial concentration of industries has positive welfare effects.” [ABSTRACT FROM AUTHORS]
Relatedness and growth: The impact of creative industries to the wider economy
By: N. Innocenti, L. Lazzeretti. Urban & Regional research center Utrecht, Papers in Evolutionary Economic Geography No. 18.19, 2018.
Abstract: “The role of the cultural and creative industries (CCIs) in fostering both innovation and growth in the wider economy has been much debated, beginning with Bakhshi et al.’s (2008) seminal contribution. Such studies of creative environments tend to assign a strategic role to territories, but they provide little empirical evidence. In this paper, the issues of the creative economy are combined with evolutionary economic geography (EEG) topics in an attempt to understand whether the CCIs are able to foster innovation and growth in the wider economy. Using an indicator of the relatedness density between the creative and other sectors for the Italian provinces, we analyse employment growth and innovation over a period of ten years (2006–2015) by drawing from the AMADEUS database. A panel data analysis is then applied to investigate the role of relatedness and the clustering of the creative industries in wider economic growth, which shows that, at a local level, the creative industries require the presence of other sectors with a high degree of cognitive proximity/relatedness, while the capacity for development and innovation does not merely depend on their presence, but also on their relations and interdependencies with other economic sectors.” [ABSTRACT FROM AUTHORS]
Local and trans-local dynamics of innovation practices in the Taipei design industry: an evolutionary perspective
By: C.-Y. Lin. European Planning Studies, DOI: 10.1080/09654313.2018.1465895, 2018.
Abstract: “Spatial-organizational proximities are crucial elements underpinning the innovation practices of creative industries. However, few studies have systematically explored how creative industries integrate the heterogeneous synergies of local and trans-local innovation practices as the diversity driving the evolution of a creative cluster within an Asian city. This paper contributes to unpacking the spatiality of local and trans-local innovation practices in the design industry from an evolutionary perspective. Based on 55 semi-structured interviews with Taipei product designers from 2011 to 2015, this paper presents a multi- dimensional framework for the spatiality of innovation practices, which exhibit two evolutionary dynamics in Taipei’s design industry cluster. First, the political-economic context enables the design industry to recombine heterogeneous knowledge by illustrating different proximities and diversities in various spatial- temporal environments. Second, the design industry increasingly depends on local and trans-local innovation practices, leading to a dynamic spatial strategy of design product differentiation. Studying the spatiality of innovation practices in the design industry reveals that the role of strategic agency, not spatial conditions, is crucial to understanding the transformation of the design economy.” [ABSTRACT FROM AUTHOR]
Collaboration Networks and Innovation: How to Define Network Boundaries
By: P. Galaso, J. Kovářík. Universidad del Pa ́ıs Vasco, Instituto de Econom ́ıa, Universidad de la Repu ́blica, Dpto. Fundamentos del An ́alisis Econo ́mico, MPRA Paper No. 85108, 2018.
Abstract: “Numerous studies in management, sociology, and economics have documented that the architecture of collaboration networks affects the innovation performance of individuals, firms, and regions. Little is known though about whether the association between collaboration patterns and innovation outcomes depends on the network geographical boundaries chosen by the researcher. This issue is crucial for both policy-makers and firms that rely on innovation. This article compares the association between collaboration networks and future patenting between regional and country-level collaboration networks. If we relate future innovation to the global, country-wide network our statistical analysis reproduces the findings of the previous literature. However, we find systematically less important effects of regional innovation patterns on subsequent patenting of innovators. Hence, managers and policy makers should choose the boundaries of the innovation networks that they look at carefully, aiming for integration into larger-scale collaboration communities.” [ABSTRACT FROM AUTHORS]
Firm Sorting and Agglomeration
By: C. Gaubert. National Bureau of Economic Research, Working Paper No. 24478, 2018.
Abstract: “The distribution of firms in space is far from uniform. Some locations host the most productive large firms, while others barely attract any. In this paper, I study the sorting of heterogeneous firms across locations and analyze policies designed to attract firms to particular regions (place- based policies). I first propose a theory of the distribution of heterogeneous firms in a variety of sectors across cities. Aggregate TFP and welfare depend on the extent of agglomeration externalities produced in cities and on how heterogeneous firms sort across them. The distribution of city sizes and the sorting patterns of firms are uniquely determined in equilibrium. This allows me to structurally estimate the model, using French firm-level data. I find that nearly half of the observed productivity advantage of large cities is due to firm sorting. I use the estimated model to quantify the general equilibrium effects of place-based policies. I find that policies that decrease local congestion lead to a new spatial equilibrium with higher aggregate TFP and welfare. In contrast, policies that subsidize under-developed areas have negative aggregate effects.” [ABSTRACT FROM AUTHOR]
Where New Creative Industries Locate? Evidence from French Departments
By: J. M. Arauzo-Carod, E. Coll-Martinez, C. Turcu. Universitat Rovira i Virgili, Centre de Recerca en Economia Industrial I Economia Publica, ISSN: 1988 – 0820, 2018.
Abstract: “This paper focuses on the creative industries and the role played by the existing spatial distribution and agglomeration economies of these activities in relation to their entry decisions. Our main statistical source is the Répertoire des entreprises et des établissements (REE) provided by INSEE, which has plant-level microdata on the location of new establishments between 2006 and 2013. We use Count Data Models to show that location determinants are quite similar in creative and non-creative industries and that specialisation in creative industries positively.” [ABSTRACT FROM AUTHORS]
Academic Inventors and the Antecedents of Green Technologies. A Regional Analysis of Italian Patent Data
By: F. Quatraro, A. Scandura. Universita Degli Studi Di Torino, Department of Economics and Statistics “Cognetti de Martiis”, Working Paper No. 06/18, ISSN: 2039-4004, 2018.
Abstract: “This work investigates the generation of green technologies (GTs) in Italian NUTS 3 regions across time, by focusing on the knowledge generation mechanisms underlying the creation of green patents. Firstly, we hypothesize that inventions in non-green technological domains positively influence the generation of GTs, because the latter occur as the outcome of a recombination process among a wide array of technological domains. Secondly, we hypothesise that the involvement of academic inventors in patenting activity bears positive effects on the generation of GTs, because they are able to manage the recombination across different technological domains. Thirdly, we explore the interaction effect between academic inventors’ involvement and non-green technologies to investigate whether the former are especially relevant in presence of higher or lower levels of the latter. We estimate zero-inflated negative binomial, spatial durbin and logistic regressions on a dataset of 103 Italian NUTS 3 regions for which we collected patent and regional data for the time span 1998-2009. The results suggest that both academic inventors and spillovers from polluting technologies bear positive direct effects on the generation of GTs; moreover, we find that academic inventors compensate for low levels of spillovers.” [ABSTRACT FROM AUTHORS]
Innovation-based regional structural change: Theoretical reflections, empirical findings and political implications
By: K. Koschatzky. Fraunhofer ISI, Working Papers Firms and Regions No. R1/2018, ISSN 1438-9843, 2018.
Abstract: “The objective of this paper is to broaden the knowledge base on the topic of innovation-based regional structural change and to discuss the possibilities of raising structurally weak regions to a dynamic growth path by means of innovation-promoting measures. The background to this objective are political developments in Germany with regard to the development of a comprehensive German support system for structurally weak regions from 2020 onwards. While regional structural support (ERDF and German regional support) is so far essentially concentrated on regions in the eastern federal states, it should focus in future on structurally weak regions in all federal states and eliminate the differentiation between eastern and western Germany (Deutscher Bundestag 2016, 4). The experience gained in the eastern German states with the focus on innovation as a driver of structural change is intended to provide a starting point here, but taking into account the fact that some structural factors differ markedly between East German and West German regions. Against this background, this paper focuses on the innovation policy component of a system for promoting structural change in structurally weak regions.” [ABSTRACT FROM AUTHOR]
Evolution of knowledge bases in European regions: searching for spatial regularities and links with innovation performance
By: V. Květoň, V. Kadlec. European Planning Studies, DOI: 10.1080/09654313.2018.1464128, 2018.
Abstract: “This paper aims at a greater comprehension of the distribution of differentiated knowledge bases and their association with innovation performance. Drawing on evolutionary economic geography, we applied a combinatorial and dynamic view on knowledge bases. The main contribution is the examination of changes and transformations of knowledge bases over time in particular group of regions in Europe and links with innovation performance. Our study revealed systematic regularities between regions with different innovation performance and their knowledge bases. With decreasing regional innovation performance the volatility of knowledge bases over time increases. Innovation leaders evinced stability over time and the most balanced composition of knowledge bases (compared with Central and Eastern Europe regions). Western European countries and regions exhibit the most balanced structure of knowledge bases. An important complementarity and synergy has been identified in the close relatedness of the symbolic knowledge base to the analytical knowledge base. The highest intensity of SME cooperation takes place in regions with a strong analytical base and in regions with the most balanced mix among all three bases (particularly in the UK, the Netherlands and Belgium. Underperforming in innovation show a balanced mix of synthetic and symbolic knowledge bases.” [ABSTRACT FROM AUTHORS]
Innovation and network multiplexity: R&D and the concurrent effects of two collaboration networks in an emerging economy
By: M. G. Andrade Rojasa, E. R. Ramirez Solisb, J. J. Zhu. Research Policy, Vol. 47, Iss. 6, pp. 1111-1124, 2018.
Abstract: “This study focuses on the multiplexity of firm R&D networks, and it investigates two types of boundary-spanning networks: the bipartite network between firms and government-sponsored institutions (GSIs), and the traditional firm–firm network. We apply a social network perspective to examine the effects that these kinds of networks have on firm innovativeness, in relation to the effects of the firm’s internal R&D efforts. We define the firm-GSI network as bipartite, and we investigate how the structural characteristics of this network (cohesion and centrality) affect innovativeness. We then decompose the innovational effects of firm–firm networks into two categories (intra- and inter-sector) to distinguish the effects of these collaboration networks. Furthermore, we investigate how these various external collaborative networks interact with a firm’s internal R&D efforts for driving innovativeness. Our empirical study of 420 manufacturing firms in Mexico evaluates evidence from surveys and secondary data. The findings indicate that the structural properties of both firm–GSI and firm–firm networks have positive effects on innovativeness, but firm–GSI network cohesion has a stronger negative interaction with R&D in influencing firm innovativeness. Moreover, intra-sector centrality in a firm–firm network has a stronger negative interaction with R&D than inter-sector centrality does in driving firm innovativeness. We contribute to the literature by integrating insights from the perspectives of network multiplexity, social embeddedness, and resource complementarity in regard to inter-organizational behavior. Our study also provides meaningful guidelines for both managers and policy makers. The study’s findings are robust to concerns of common method bias and alternative model specifications.” [ABSTRACT FROM AUTHORS]