Firm clustering and innovation: Determinants and effects

In this article we ask why innovator firms engage in innovation networks, and which factors explain the spatial dispersion of these networks. Benefits of the use of internal and external knowledge resources for innovative performance of firms were partially confirmed. Especially the utilisation of external competences drawn from buyers and suppliers had stronger effects on innovative performance if complexity of innovation projects was high. Spatial concentration of innovation networks of buyers and suppliers turned out to have a reciprocal, positive relation with interaction intensity between firms. Interaction enhances spatial concentration of relations and vice versa, although the strength of effects differs for ties with buyers and suppliers. Finally we found that higher regional economic embeddedness increases spatial concentration of innovation networks, whereas R& D effort had no effect at all. Received: 11 October 2000 / Accepted: 18 April 2001     

Embeddedness of regions in European knowledge networks: a comparative analysis of inter-regional R&D collaborations,co-patents and co-publications

This paper investigates the embeddedness of European regions in different types of inter-regional knowledge networks, namely project-based R&D collaborations within the European framework programmes (FPs), co-patent networks and co-publication networks. Embeddedness refers to the network positioning of regions captured in terms of social network analytic (SNA) centrality measures. The objective is to estimate how region-internal and region-external factors influence network embeddedness in the distinct network types, in order to identify differences in their driving factors at the regional level. In our modelling approach, we apply advanced spatial econometric techniques by means of a mixed effects panel version of the spatial Durbin model (SDM) and introduce a set of variables accounting for a capacity specific, a relational as well as a spatial dimension in regional knowledge production activities. The results reveal conspicuous differences between the knowledge networks. Internal capacity- and technology-related aspects but also spatial spillover impacts from surrounding regions prove to be particularly important for centrality in the co-patent network. We also find significant—region-internal and region-external—impacts of general economic conditions on a region’s centrality in the FP network. However, we cannot observe substantial spillover effects of region-external factors on centrality in the co-publication network. Thus, the distinctive knowledge creation foci in each network seem to find expression in the network structure as well as its regional determinants.     

R&D networks and regional knowledge production in Europe: Evidence from a space‐time model

In this study we estimate space‐time impacts of the embeddedness in R&D networks on regional knowledge production using a dynamic spatial panel data model with non‐linear effects for 229 European NUTS 2 regions in the period 1998–2010. Embeddedness refers to the positioning in networks where nodes represent regions that are linked by joint R&D projects funded by EU Framework Programmes. We find evidence that increasing embeddedness in EU funded R&D networks leads to positive immediate impacts on regional knowledge production, and that regions with lower levels of own knowledge endowments more likely exploit the positive effects. However, the long‐term impacts of a region's embeddedness in these R&D networks are comparatively small.     

Institutions vs. ‘first‐nature’ geography: What drives economic growth in Europe's regions?

The debate on whether institutions or geography prevail in driving economic growth has been rife (e.g., Sachs 2003 vs. Rodrik et al. 2004). Most of the empirical analyses delving into this debate have focused on world countries, whose geographical and institutional conditions differ widely. Subnational analyses considering groups of countries with, in principle, more similar institutional and geographical conditions have been limited and tended to highlight that geography is more important than institutions at subnational level. This paper aims to address whether this is the case by investigating how differences in institutional and ‘first‐nature’ geographical conditions have affected economic growth in Europe's regions in the period 1995–2009. In the analysis we use a newly developed dataset including regional quality of government indicators and geographical characteristics and employ two‐stage least squares (2SLS) and instrumental variables‐generalized method of moments (IV‐GMM) estimation techniques with a number of regional historical variables as instruments. Our results indicate that at a regional level in Europe institutions rule. Regional institutional conditions – and, particularly, government effectiveness and the fight against corruption – play an important role in shaping regional economic growth prospects. This does not imply, however, that geography is irrelevant. There is evidence of geographical factors affecting regional growth, although their impact is dwarfed by the overriding influence of institutions.     

Modeling knowledge networks in economic geography: a discussion of four methods

The importance of network structures for the transmission of knowledge and the diffusion of technological change has been recently emphasized in economic geography. Since network structures drive the innovative and economic performance of actors in regional contexts, it is crucial to explain how networks form and evolve over time and how they facilitate inter-organizational learning and knowledge transfer. The analysis of relational dependent variables, however, requires specific statistical procedures. In this paper, we discuss four different models that have been used in economic geography to explain the spatial context of network structures and their dynamics. First, we review gravity models and their recent extensions and modifications to deal with the specific characteristics of networked (individual level) relations. Second, we discuss the quadratic assignment procedure that has been developed in mathematical sociology for diminishing the bias induced by network dependencies. Third, we present exponential random graph models that not only allow dependence between observations, but also model such network dependencies explicitly. Finally, we deal with dynamic networks, by introducing stochastic actor-oriented models. Strengths and weaknesses of the different approach are discussed together with domains of applicability the geography of innovation studies.     

Innovation, knowledge spillovers and local labour markets

Abstract.  This article investigates the role played by geography in the promotion of innovation. In order to examine these issues we employ empirical data from Finland in order to test the extent to which the variety and nature of face-to-face contacts affects the innovation performance of the firm. In addition, we then also control for the geographical mobility of the labour employed by the firm. This allows us to identify the different roles that the geography of knowledge spillovers and exchanges and the geography of labour markets play in the innovation process.     

Scalable shift-share analysis: Novel framework and application to France

The shift-share analysis (SSA) of regional employment growth disparities aims at disentangling the effects of regional differences in industry mix and industrial competitiveness. Yet, the spatial concentration of industry is a blindspot of this approach. We generalize the SSA to encompass this salient feature of the economic geography. Besides, industry emergence and catastrophic growth events—booming or collapsing industries—are integrated in our framework. This novel method is applied to study regional disparities in manufacturing employment growth in France in a dynamic way over a 22-year period at a fine geographical level.     

Applying social network analysis in economic geography: framing some key analytic issues

Social network analysis attracts increasing attention in economic geography. We claim social network analysis is a promising tool for empirically investigating the structure and evolution of inter-organizational interaction and knowledge flows within and across regions. However, the potential of the application of network methodology to regional issues is far from exhausted. The aim of our paper is twofold. The first objective is to shed light on the untapped potential of social network analysis techniques in economic geography: we set out some theoretical challenges concerning the static and dynamic analysis of networks in geography. Basically, we claim that network analysis has a huge potential to enrich the literature on clusters, regional innovation systems and knowledge spillovers. The second objective is to describe how these challenges can be met through the application of network analysis techniques, using primary (survey) and secondary (patent) data. We argue that the choice between these two types of data has strong implications for the type of research questions that can be dealt with in economic geography, such as the feasibility of dynamic network analysis.     

Geography, institutions and urban development: Italian cities, 1300–1861

Recent studies have highlighted the role of geography and institutions as key determinants of urban development. In this paper, we test this hypothesis by considering the case of Italian cities over a very long time period, i.e., from 1300 to 1861. Our measure of development is the urban population, and we relate it to geographical and institutional variables at both city and regional level. We find that the quality of institutions as measured by the experience of free city-state and the presence of a university has a positive effect on urban development, whereas we could not find a robust impact of the quality of regional government. However, we also find that cities located in mountain areas grew less than cities located in lowlands, possibly with access to the sea. We interpret these results as evidence of the importance of urban institutions and geography in shaping urban development.     

Research productivity and the quality of interregional knowledge networks

This paper estimates the impact of interregional knowledge flows on the productivity of research at the regional level. We develop the novel index of ‘ego network quality’ in order to measure the contribution of knowledge accessed from the interregional network to the production of new knowledge inside the region. Quality of interregional knowledge networks is related to the level of knowledge accumulated by the partners (‘knowledge potential’), the extent of collaboration among partners (‘local connectivity’) and the position of partners in the entire knowledge network (‘global embeddedness’). Ego network quality impact on the productivity of research in scientific publications and patenting at the regional level is tested with co-patenting and EU Framework Program collaboration data for 189 European NUTS 2 regions.     

Regional and structural analysis of the manufacturing industry in Turkey

The geography of the manufacturing industry has been changing due to technological development, flexible production and reducing transportation costs regarding the new specialization and distribution process in the world. While manufacturing production has been moving from developed countries to the relatively less developed ones, which have become the emerging economies over the last two decades, the concentration of these activities within the countries has always received the attention of researchers. On the other hand, not only the geographical shift but also structural shifts have increasingly been an important phenomenon of the twenty-first century. It is known that the level of technology and innovation makes a significant contribution to regional economic development. Determinants of manufacturing agglomerations have created a wide literature based on different empirical studies. Moreover the structural changes of industry need to be investigated regarding the spatial agglomerations. The aim of this paper is to explore how the factors of manufacturing agglomerations have differentiated due to the technological level across the country. Furthermore, we assume that the agglomeration mechanism is likely to vary across the space. Therefore, we have run both global and local regression models based on the employment data of the 81 NUTS III level regions (provinces) of Turkey in 2012. The results point out that the factors of agglomerations are different in the east and west provinces, while GWR has significantly improved global results.     

Geography and the costs of local telephone networks

This paper expands past research on the cost structure of local telephone networks by considering the cost effects of geographical factors, such as service territory size, land uses, street patterns, population density, soil types, slopes, and the spatial partitioning of a company into local exchanges. A translog cost function is estimated using data on 41 telephone companies operating within the New York State, together with GIS-derived geographical data. The results confirm the importance of geography as a determinant of local telephone costs, and suggest that earlier estimates of size thresholds between economies and diseconomies of scale may be too low. The trade-offs between geographical factors in shaping the frontier between economies and diseconomies of scale are assessed. The implication for public policy on competition at the local level is that natural monopoly may be more prevalent than previously assumed. An earlier version of this paper was presented at the 50th Annual North American Meeting of the Regional Science Association International, 20–22 November 2003, Philadelphia, PA.     

Distinct spatial characteristics of industrial and public research collaborations: evidence from the fifth EU Framework Programme

This study compares the spatial characteristics of industrial R&D networks to those of public research R&D networks (i.e. universities and research organisations). The objective is to measure the impact of geographical separation effects on the constitution of cross-region R&D collaborations for both types of collaboration. We use data on joint research projects funded by the fifth European Framework Programme (FP) to proxy cross-region collaborative activities. The study area is composed of 255 NUTS-2 regions that cover the EU-25 member states (excluding Malta and Cyprus) as well as Norway and Switzerland. We adopt spatial interaction models to analyse how the variation of cross-region industry and public research networks is affected by geography. The results of the spatial analysis provide evidence that geographical factors significantly affect patterns of industrial R&D collaboration, while in the public research sector effects of geography are much smaller. However, the results show that technological distance is the most important factor for both industry and public research cooperative activities.     

The geography of innovation in a small metropolitan region: An intra‐regional approach in Luxembourg

The objective of the paper is to analyse the local determinants of innovation in a small European metropolitan region. First, we examine the extent to which geographic space is a determinant of innovation for five intra‐regional units. Second, we investigate whether innovation is dependent on accessibility to the mean centre. In both cases we examine innovation propensity and innovation output using microdata from the Community Innovation Survey carried out in Luxembourg. The paper provides evidence of a link between the effects on innovation at the intra‐regional level of firms' profiles and agglomeration externalities.     

Industry and location effects on UK plants' innovation propensity

This paper uses UK plant-level survey data to examine the relative importance of industry concentration, technological opportunity and locational factors in determining innovation propensity.  The results suggest no evidence that industry concentration has any significant positive effect on innovation. Industries' technological characteristics are important, however, with the potential for industry-specific spill-over effects. Plants' own technological activities in terms of undertaking R&D and having an R&D department were also important determinants of innovation propensity as were plants' participation in technology transfer and inter-firm networks. Strong locational effects were identified relating to industrial composition, the level of R&D activity, external ownership, the preponderance of small firms and the general level of regional prosperity. In addition, strong interactions were evident between plants' R&D activity and their regional environment. Undertaking R&D enabled plants to take advantage of any environmental benefits for innovation and insulated them from potential negative effects. Received: February 1998/Accepted: August 1999     

Skilled labour mobility, networks and knowledge creation in regions: a panel data approach

The aim of this paper is to investigate the relative contribution of different features of the local labour market for inventors on regional patenting. By means of a knowledge production function and a sample of 276 European regions, we assess whether local labour mobility of inventors, as well as the scale and extent of their collaborative research networks, correlates with innovation outcomes. In the second part of the paper, we extend the analysis to the role of spatial mobility of knowledge workers and cross-regional research networks as predictors of regional patenting.     

浙江历史地理对传统聚落发生发展的影响分析

浙江传统聚落作为浙江极具特色的历史建筑文化的一部分,拥有丰富的类型和悠久的历史,在浙江特定的地域环境中孕育发展。聚落与其赖以生存的地域之间历经了几千年的相互作用,历经了朝代的更替、环境的变迁、生活方式的转变,从最初的人类聚居点发展成具有区域特色的传统聚落文化。该文通过对近百个浙江传统聚落进行研究,探讨聚落与历史地理环境的相互关系,历史地理环境对聚落的分布、规模、形态、发展过程与职能的影响,从中得出对传统聚落保护的启示。     

Knowledge networks and industrial structure for regional innovation: An analysis of patents collaborations in Italy

The aim of the research is to investigate whether the structure of knowledge networks and the variety of the local industrial structure are important for regional innovation and if the interplay between these two forces has an additional effect on local innovativeness. The research analyses co-patenting collaborations at firm level in the Italian provinces in three five-year intervals in the period 2001–2016. Results show that the structure of knowledge networks and agglomeration economies of inventors boost local inventive capacity. It also highlights how these forces have an increasing impact on innovation as the variety of the area increases.     

Agglomeration economies, inventors and entrepreneurs as engines of European regional economic development

In economic agglomeration studies, the distinction of various externalities circumstances related to knowledge spillovers remains largely unclear. This paper introduces human capital, innovation and several types of entrepreneurship as potential drivers of regional economic performance with an impact of agglomeration economies. We use measures of specific types of entrepreneurship, discerned at the individual level, as well as human capital and invention through patenting activity for the period 2001–2006. The empirical application on 111 regions across 14 European countries investigates their relation with observed regional productivity rates in 2006. Our main findings indicate that (i) human capital, patenting activity and entrepreneurship are all linked to regional performance, more so in regions containing large as well as medium-sized cities; (ii) they act as complements rather than substitutes, facilitating productivity differently; and (iii) accounting for patenting activity and entrepreneurship captures agglomeration externalities effects previously subscribed only to the density of resources of regional performance. The particular role of regions with medium-sized cities next to regions with large cities complies with observed growth trends as well as recently proposed place-based development approaches that assume that interactions between institutions and geography are critical for regional economic performance.     

Predicting innovative growth and demand with proximate human capital: A case study of the Helsinki metropolitan area

Human capital is an essential driver for the growth of national and regional innovation systems. In this study, we can show that also intra-metropolitan innovation clusters locate in, or in proximity to, neighbourhoods with a high level of human capital. Our interpretation of human capital involves an educated, talented, creative and tolerant workforce. Indicators from earlier literature are complemented by identified new propositions. In addition, by using both relative and absolute measures, we conclude that innovations emerge the best in dense and mixed urban structure. After identifying the geography of human capital and innovativeness, we predict also potential growth areas, which could help urban planning of the HMA. The modelling methods used in this study can be implemented and applied in urban studies of other city regions.