Clustering dynamics and the location of high-tech firms

The location of productive activities and the emergence of clustering dynamics has been an important research topic since the early works of Weber (1929) and Marshall (1920 and 1921). This thesis aims at relating the processes of firms' location decision and the development of high-tech clusters within an encompassing theoretical and empirical framework. The thesis shows the empirical relevance of the clustering of high-tech sectors and highlights the importance of the issue through the construction and use of an original database on the location of high-tech establishments and employment (at two different geographical levels) in four major industrialised countries. It also contains a critical review of a number of different streams of theoretical and empirical literature which are directly connected, or which have been explicitly put in connection by the author, with the topic of study. In the thesis we develop a composite modelling framework for analysing firms' location decisions and the growth of high-tech clusters, and we empirically test a number of crucial hypotheses in order to draw some guidelines for economic policy. The models presented in the theoretical chapter derive from two different streams of literature. The first derives from the analysis of population ecology, the second from the theory of innovation diffusion. These modelling frameworks have stressed the existence of a critical mass and a maximum dimension of the cluster and their effects on the early and late phases of development within the "life cycle" of a cluster. They also highlighted the role of rank, stock, order and epidemics effects in the location decision of an individual firm which has to decide whether to locate into a developing cluster. The empirical evidence presented in the thesis has focused on the crucial elements of the location process by verifying the empirical relevance of different locational factors, has stressed the relative importance of agglomeration versus scale economies in determining the industrial specialisation of an area, and has measured the competitive effects which arise between the development of different clusters and the synergistic effects which are generated within the cluster. Finally the thesis presents empirical evidence which shows that local competition and industrial specialisation are the key elements for the success of an industrial cluster. A final chapter extracts some crucial policy conclusions on the role of entry versus growth policies, on the different development path that an industrial cluster may follow depending on the excludability condition, presents an original taxonomy of specific policies, applies some of these findings to a brief survey of the phenomenon of science parks and finally produces a series of guidelines for policy makers. The conclusion summarises the results obtained in the thesis and present a brief agenda for future research

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.Cluster, Life-Cycle, Cluster Literature, Textual Analysis, Agglomeration, Co-Authorship

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

Does intentional mean hierarchical? Knowledge flows and innovative performance of European regions

The production of scientific and technical knowledge is mostly concentrated in specific locations (high-tech clusters, innovative industry agglomerations, centres of excellence, and technologically advanced regions). Knowledge flows very easily within regions; however, scientific and technical knowledge also flow between regions. The aim of this paper was to analyse how knowledge flows between regions, and the effect of these flows on the innovative performance, measured by patent applications. We estimate a regional knowledge production function, and, using appropriate spatial econometric estimation techniques, we test the effect of both geographical and relational autocorrelation (measured by participation in EU funded research networks as part of Fifth Framework Programme). We model unobservable structure and link value of knowledge flows in these joint research networks. We find that knowledge flows within inter-regional research networks, along non-symmetrical and hierarchical structures in which the knowledge produced by network participants tends to be exploited by the network coordinator

International networks of knowledge flows: an econometric analysis

In this paper we address the manifold nature of knowledge through the analysis of four distinct but complementary phenomena (Internet hyperlinks, European research networks, EPO co-patent applications, Erasmus students mobility) that characterize knowledge as an intrinsic relational structure (directly) connecting people, institutions and (indirectly) regions across five European countries. We study the structure (in terms of density, clustering and centralisation) of these networks through network analysis techniques and test the influence of geographical distance as opposed to sectoral (based on the industrial distribution of the innovative activity) and functional (based on the value of the RSII European technological leadership index) distances in shaping the strength of knowledge relations though a gravitational model. The empirical analysis shows the existence of a polarized centre-periphery hierarchy of European regions that is reflected in the structure of knowledge flows. By using a gravitational model we demonstrate that, far from the claim of the death of distance, geographic distance is still relevant for determining the structure of inter-regional knowledge flows. Functional and sectoral distances play also a crucial role suggesting that knowledge flows easily between similar (according to their scientific, technological and sectoral characteristics) regions. If the EU intends to build a truly European Research Area in which the networking of centres of excellence acts as catalysts for backward areas this target may still be far away

The rise and fall of industrial clusters: Technology and the life cycle of region

When a major technological innovation spreads out in both high-tech and middle/low-tech industries, new clusters appear, develop and grow at the expenses of “older” historical industrial sites. The literature has, under various labels, recognized three main stages of cluster development: an initial stage sparked by an initial exogenous, shock; a second stage driven by Marshall’s (1920) agglomeration economies (labor market pooling, supply of intermediate goods and services and knowledge spillovers); a third stage in which the cluster either achieves a sectoral leadership or declines. The paper shows how different clusters ’evolution (often told as separated stories) are part of a wider picture in which technological and spatial interactions between emerging and declining clusters play a decisive role. A final section draws some policy suggestions for public authorities and regional planners dealing with the development of an innovative cluster

Trust behind bars: Measuring change in inmates' prosocial preferences

The paper presents the results of a Longitudinal Lab-in-the-Field Experiment implemented between September 2015 and July 2016 performed in two State Prisons in California (USA) to measure change in prosocial preferences. A subset of eligible inmates willing to undertake GRIP (Guiding Rage Into Power) program, were randomly assigned to it. The paper tests whether the participation to this program (used as a treatment in the experiments) affects prosocial preferences of participants, with specific reference to trust. The results of a Difference-in-Differences (DID) estimation procedure show that trust significantly increased in GRIP participants compared to the control group. This result is robust to alternative estimation techniques and to the inclusion of an endogenous behavioral measure of altruism

Robots Are Not All the Same: Young Adults' Expectations, Attitudes, and Mental Attribution to Two Humanoid Social Robots

The human physical resemblance of humanoid social robots (HRSs) has proven to be particularly effective in interactions with humans in different contexts. In particular, two main factors affect the quality of human-robot interaction, the physical appearance and the behaviors performed by the robot. In this study, we examined the psychological effect of two HRSs, NAO and Pepper. Although some studies have shown that these two robots are very similar in terms of the human likeness, other evidence has shown some differences in their design affecting different psychological elements of the human partner. The present study aims to analyze the variability of the attributions of mental states (AMS), expectations of robotic development and negative attitudes as a function of the physical appearance of two HRSs after observing a real interaction with a human (an experimenter). For this purpose, two groups of young adults were recruited, one for the NAO

Does democracy cause growth? A meta-analysis (of 2000 regressions)

The relationship between democracy and economic growth has been widely debated in the social sciences with contrasting results. We apply a meta-analytical framework surveying 188 studies (2047 models) covering 36 years of research in the field. We also compare the effect of democracy on growth with the effect of human capital on growth in a sub-sample of 111 studies (875 models). Our findings suggest that democracy has a positive and direct effect on economic growth beyond the reach of publication bias, albeit weaker (about one third) of that of human capital. Further, the growth effect of democracy appears to be stronger in more recent papers not surveyed in Doucouliagos and Uluba\u15fo\u11flu (2008). Finally, we show that the heterogeneity in the reported results is mainly driven by spatial and temporal differences in the samples, indicating that the democracy and growth nexus is not homogeneous across world regions and decades

Expert consensus document: A 'diamond' approach to personalized treatment of angina.

In clinical guidelines, drugs for symptomatic angina are classified as being first choice (β-blockers, calcium-channel blockers, short-acting nitrates) or second choice (ivabradine, nicorandil, ranolazine, trimetazidine), with the recommendation to reserve second-choice medications for patients who have contraindications to first-choice agents, do not tolerate them, or remain symptomatic. No direct comparisons between first-choice and second-choice treatments have demonstrated the superiority of one group of drugs over the other. Meta-analyses show that all antianginal drugs have similar efficacy in reducing symptoms, but provide no evidence for improvement in survival. The newer, second-choice drugs have more evidence-based clinical data that are more contemporary than is available for traditional first-choice drugs. Considering some drugs, but not others, to be first choice is, therefore, difficult. Moreover, double or triple therapy is often needed to control angina. Patients with angina can have several comorbidities, and symptoms can result from various underlying pathophysiologies. Some agents, in addition to having antianginal effects, have properties that could be useful depending on the comorbidities present and the mechanisms of angina, but the guidelines do not provide recommendations on the optimal combinations of drugs. In this Consensus Statement, we propose an individualized approach to angina treatment, which takes into consideration the patient, their comorbidities, and the underlying mechanism of disease