Mario A. Maggioni

Space Vs. Networks in the Geography of Innovation: A European Analysis

In the last fifteen years, income differences among European Member States have been strongly narrowing while the process has been matched with a widening of the inter-regional variance within single countries. Traditionally, regional economic disparities in Europe have been ascribed to peripherality and/or to a high level of dependence on declining sectors. Nowadays regional disparities can be no longer defined only in terms of statistical differences in the values of standard macroeconomic indicators, but also according to innovative capacities and knowledge endowment. This paper provides an original framework for the interpretation of the existing relationships between innovation process and research activity in Europe and the structural and geographical features shaping the European scientific and technological map. In order to do so, we focus on two knowledge-based relational phenomena: participation in the same research networks (funded by the EU Fifth Framework Programme) and EPO co-patent applications. Using two complementary econometric techniques we try to assess those factors that determine patenting activity, distinguishing structural features, geographical and relational spillovers. Through these variables we measure the intrinsic relational structure of knowledge flows which directly connects people, institutions and, indirectly, regions, across European countries in order to test whether hierarchical relationships based on a-spatial networks between geographically distant excellence centres prevail over diffusive patterns based on spatial contiguity.

Intersectoral innovation flows and national technological systems: network analysis for comparing Italy and Germany

Abstract The paper compares the innovative structure and performance of Italy and Germany by using the concept of the technological system which is defined as the result of the interaction of four different components: the industrial, the innovative, the commercial (domestic and foreign markets) and the institutional sub-systems. The analysis of the intersectoral innovation flows within the two national technological systems is based on an input-output database rearranged in vertically integrated sectors. Specific hypotheses have been formulated and valid proxies for the variables studied have been used. The final results have been obtained by using network analysis methodology and indicators. This called for a dicotornisation of the original matrices. These results take into account separately the existing differences between Italy and Germany in both absolute terms ( dimension effect ) and relative terms ( proportion effect ). The paper shows that Germany is characterised by a higher level of systemic connection both in absolute and (generally) in relative terms. The Italian technological system seems to be segmented in a dualistic structure where few high-tech sectors co-exist along with a pool of traditional ones, rather peripheral in the innovation flow network. The German system, on the contrary, appears to be homogeneous with a more evenly distributed structure of intersectoral innovation flows. The paper concludes by considering the effects of the introduction of other sub-systems: namely foreign market and public intervention. While the former introduces further elements of differentiation between Italy and Germany, the latter seems to perform a similar role in both systems.

Inter-regional Knowledge Flows in Europe: An Econometric Analysis

Applied Evolutionary Economics and Economic Geography aims to further advance empirical methodologies in evolutionary economics, with a special emphasis on geography and firm location. It does so by bringing together a select group of leading scholars including economists, geographers and sociologists, all of whom share an interest in explaining the uneven distribution of economic activities in space and the historical processes that have produced these patterns.

Mapping the Evolution of "Clusters": A Meta-analysis

This paper presents a meta-analysis of the “cluster literature” contained in scientific journals from 1969 to 2007. Thanks to an original database we study the evolution of a stream of literature which focuses on a research object which is both a theoretical puzzle and an empirical widespread evidence. We identify different growth stages, from take-off to development and maturity. We test the existence of a life-cycle within the authorships and we discover the existence of a substitutability relation between different collaborative behaviours. We study the relationships between a “spatial” and an “industrial” approach within the textual corpus of cluster literature and we show the existence of a “predatory” interaction. We detect the relevance of clustering behaviours in the location of authors working on clusters and in measuring the influence of geographical distance in co-authorship. We measure the extent of a convergence process of the vocabulary of scientists working on clusters.

Treating Patents as Relational Data: Knowledge Transfers and Spillovers across Italian Provinces

The paper applies a relational perspective to patent data in order to investigate the characteristics of innovation flows within and across 103 Italian NUTS3 regions (province). In this way it is possible to use the CRENoS database on regional patenting—built on EPO data spanning from 1978 to 2003—to investigate the scientific and technological “relations” among “invention-creating ” and “invention-adopting ” territories. In particular, patents are used as relational data connecting inventors and applicants along a dual interpretation of a “knowledge production” and a “knowledge utilization” function. In addition a gravity model is used to identify frictions and attractions of the Italian innovation system. Analytical tools, such as social network analysis, spatial econometrics and negative binomial estimation procedures, are used to map and measure the structure and the evolution of a series of innovation sub-systems, both at territorial level (i.e. province) and at the industry level (i.e. five specific industries, chosen according to the Pavitts taxonomy, Footwear, Textiles, Machinery, Personal Computers and Chemicals).

The strength of strong ties: How co-authorship affect productivity of academic economists?

Abstract Increased specialization and extensive collaboration are common behaviours in the scientific community, as well as the evaluation of scientific research based on bibliometric indicators. This paper aims to analyse the effect of collaboration (co-authorship) on the scientific output of Italian economists. We use social network analysis to investigate the structure of co-authorship, and econometric analysis to explain the productivity of individual Italian economists, in terms of ‘attributional’ variables (such as age, gender, academic position, tenure, scientific sub-discipline, geographical location), ‘relational’ variables (such as propensity to cooperate and the stability of cooperation patterns) and ‘positional’ variables (such as betweenness and closeness centrality indexes and clustering coefficients).

HIGH-TECH FIRMS AND THE DYNAMICS OF INNOVATIVE INDUSTRIAL CLUSTERS

Industrial clusters have been defined as “a spatial and sectoral concentrations of firms” (Bresnahan et al. 2002). Innovative industrial clusters have been defined either as those clusters which, in a given period of time, have displayed a high level of innovative outputs or, more generally, as those cluster whose sectoral specialisation is in “high-tech industries” defined on the basis of innovative inputs.Aim of this chapter is to discuss the empirical identification and measurement of innovative industrial clusters; to present a theoretical framework for the analysis of clusters development; to analyse the dynamics of a restricted sample of high-tech industries across the US (over the period 19882003).)

Multiplexity, Growth Mechanisms and Structural Variety in Scientific Collaboration Networks

A substantial body of literature has recently been concerned with the structure and dynamics of the collaboration networks that underlie the production and dissemination of scientific knowledge. Despite the growing interest in these networks, relatively little emphasis has been placed on two broad areas of investigation: on the one hand, the interplay of the growth mechanisms underpinning the evolution of collaborative arrangements; on the other, the implications that the structure and multiplexity of these arrangements have on knowledge creation and diffusion. The articles in this Special Issue aim to bridge these gaps in the literature and, by embracing a variety of perspectives, contribute towards a better understanding of how collaboration networks originate, function, and evolve. This Introduction offers a theoretical and methodological framework for the articles here included. It begins by discussing problems of measurement of scientific collaboration, and goes on to examine the role that growth mechanisms, structural variety and multiplexity play in shaping the genesis and functioning of collaboration networks. In reviewing current and emerging research themes, the discussion will also identify promising research directions that will stimulate future work on collaboration networks in science and technology.

Regional Growth and the Co-Evolution of Clusters: The Role of Labour Flows

Regional performances are traditionally explained in terms of factor endowments, like physical capital accumulation (exogenous growth models), openness to international trade (export-led growth models) or education and innovation dynamics (endogenousgrowthmodels). These approaches neglect productive interdependence within or between regions and industries as possible sources of growth. Interdependence may occur in several ways; we have decided to focus on labour flows as the way regions and industries interact. Clusters are defined as the intersection of territorial and industrial units; sectors and territories are the two central dimensions for the evolution of clusters. More precisely, cluster growth depends on two kinds of interactions: those which are industry-specific (intra-industry interactions) and those which are region-specific (inter-industry interactions). Inter-regional dependence ranges frommutualism (in which each region’s growth is positively related to the size of the other region) to competition, in which the growth of one region is obtained at the expenses of the other. In these models, the size of a region is measured by the number of firms and the employment level, but the mechanisms lying beyond these interactions (apart from a generic reference to the existence of spatial spillovers, inter-industry linkages and agglomeration economies), are often left unexplained. One way to make interand intra-regional interactions explicit is to take the role played by the mobility of labour into account. Labour flows act as the channel for these inter-industry and inter-regional interdependencies and determine the growth performance of a region. Variation in the growth performance of a group of regions may determine the existence of divergence or convergence dynamics which may be due to the different level of skills embedded in the migrating workers. An important methodological background to the chapter is the Ecological Approach. Ecological models (Dendrinos and Mullally 1985; Maggioni 2002a) define

Intersectoral Innovation Flows Within and Between Nations and Regions: Network Analysis and Systems of Innovation

This paper analyses the innovative systems of different territorial entities: two European countries (Italy and Germany) and two Italian regions (Lombardy and Piedmont). The analysis of the intersectoral innovation flows within the systems is based on an input-output database rearranged in vertically integrated sectors and studied through network analysis methodology and indicators.