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MNCs often engage in international research collaborations with foreign universities through one of their central RD laboratories (at headquarters or elsewhere) even though they operate a local RD unit close to that university, and hence forego the benefits of geographic proximity and local collaboration. Drawing on the knowledge-based theory of the firm, we hypothesize that the choice between distant and local collaboration systematically relates to the knowledge capabilities of the firms' RD units, the characteristics of the focal knowledge, and local knowledge leakage risks. Analysis of close to 13,000 research collaborations with foreign universities by the world's major biopharmaceutical firms (1995-2015) confirms that collaboration at distance occurs if this allows the firm to benefit from scale and knowledge diversity advantages, if the central unit has strong basic research capabilities, and if collaboration is in a core research domain of the MNC while rival firms are locally present. Maturity of the focal research domain is associated with local collaboration. Our findings qualify the common arguments in favor of collaboration in proximity and suggest that (distant) central RD units are important orchestrators of research collaboration with universities around the globe.Les entreprises multinationales s'engagent souvent dans des collaborations de recherche internationales avec des universités étrangères par le biais de l'un de leurs laboratoires centraux de RD (au siège ou ailleurs) même si elles exploitent une unité de RD locale, proche de cette université. Elles renoncent ainsi aux avantages de la proximité géographique et de la collaboration locale. Nous appuyant sur la théorie de la firme fondée sur la connaissance, nous développons l’hypothèse que le choix entre les collaborations distantes et locales soit systématiquement lié aux capacités en matière de connaissances des unités de RD des entreprises, aux caractéristiques des connaissances focales et aux risques de fuites de connaissances locales. L'analyse de près de 13000 collaborations de recherche des principales entreprises biopharmaceutiques (1995-2015) avec des universités étrangères confirme que la collaboration à distance se produira si cela permet à l'entreprise de bénéficier des avantages d'échelle et de diversité des connaissances, si l'unité centrale dispose de solides capacités de recherche fondamentale, et si la collaboration s’inscrit dans un domaine de recherche stratégique des multinationales alors que des entreprises concurrentes sont localement présentes. La maturité du domaine de recherche focal est associée à la collaboration locale. Nos résultats nuancent l'argumentation courante en faveur de la collaboration à proximité, et suggèrent que les unités centrales (et distantes) de RD soient d'importants orchestrateurs de la collaboration de recherche avec les universités du monde entier.Las empresas multinacionales con frecuencia participan en colaboraciones de investigación internacionales con universidad extranjeras mediante uno de sus laboratorios de I+D centrales (en la casa matriz o en otra parte) aún cuando operan una unidad de I+D local cerca a esa universidad, y de ahí que proceden los beneficios de la proximidad geográfica y la colaboración local. Basándonos en la teoría de la empresa basada en el conocimiento, planteamos la hipótesis de que la elección entre la colaboración a distancia y la local está sistemáticamente relacionada con las capacidades de conocimiento de las unidades de I+D de las empresas, las características del conocimiento focal y los riesgos de fuga de conocimiento local. Una análisis de cerca de 13.000 colaboraciones de investigación con universidades extranjeras por las empresas biofarmacéuticas más importantes del mundo (1995-2015) confirma que la colaboración a distancia se produce si esto permite a la empresa beneficiarse de las ventajas de escala y de la diversidad de conocimientos, si la unidad central tiene fuertes capacidades de investigación básica, y si la colaboración se produce en un dominio de investigación central de la empresa multinacional mientras que las empresas rivales están presentes a nivel local. La madurez del ámbito de investigación central está asociada a la colaboración local. Nuestros hallazgos habilitan la argumentación común a favor de la colaboración en proximidad y sugieren que las unidades centrales de I+D (distantes) son importantes orquestadoras de la colaboración en investigación con las universidades de todo el mundo.MNCs frequentemente se envolvem em colaborações de pesquisa internacionais com universidades estrangeiras por meio de um de seus laboratórios centrais de RD (na sede ou em outro lugar), embora operem uma unidade local de RD perto dessa universidade e, portanto, renunciam aos benefícios da proximidade geográfica e colaboração local. Com base na teoria baseada no conhecimento da firma, formulamos a hipótese de que a escolha entre colaboração distante e local se relaciona sistematicamente com as capacidades de conhecimento das unidades de RD das empresas, as características do conhecimento focal e os riscos locais de vazamento de conhecimento. Análise de cerca de 13.000 colaborações de pesquisa com universidades estrangeiras pelas principais empresas biofarmacêuticas do mundo (1995-2015) confirma que a colaboração à distância ocorre se isso permite que a firma se beneficie de vantagens de escala e diversidade de conhecimento, se a unidade central tiver fortes capacidades básicas de pesquisa , e se a colaboração está em um domínio de pesquisa central da MNC enquanto empresas rivais estão localmente presentes. A maturidade do domínio de pesquisa focal está associada à colaboração local. Nossas descobertas qualificam a argumentação comum em favor da colaboração na proximidade e sugerem que as unidades centrais (distantes) de RD são importantes orquestradoras da colaboração em pesquisa com universidades ao redor do mundo.跨国公司(MNC)经常通过其中央研发实验室中的一个 (在总部或其它地方) 来与外国大学开展国际研究合作, 即使它们在该大学附近设有本地研发机构, 也会放弃地理位置接近和本地合作的益处。借鉴企业知识基础观, 我们假设在远程合作与本地合作之间进行的选择与企业研发机构的知识能力、焦点知识的特征以及本地知识泄漏风险有关。对世界主要生物制药公司与国外大学的近13,000项研究合作进行的分析 (1995-2015年) 证实, 远程合作在如下情况下发生: 如果这可以使公司从规模和知识多样化的优势中受益、如果中央机构具有强大的基础研究能力, 以及如果进行的合作是该MNC的核心研究领域而竞争公司在本地存在。焦点研究领域的成熟度与本地合作有关。我们的发现证实了支持近距离合作的普遍论点, 并表明 (远程) 中央研发机构是与全球大学开展研究合作的重要协调者。.

This paper investigates the key driving features of the evolving long-term division of innovative labor in biotechnology and pharmaceuticals from 1981 to 2012. Our main goal is to find if technological trajectories and mechanisms discovered by Orsenigo et al. (Res Policy 30(3): 485–508, 2001) as the main drivers of the structural configuration of the network of collaborative alliances have been at work in the long-term evolution of the industry. We extensively analyze the evolving dynamics of the degree distribution and the higher order properties of the R&D network. As in Orsenigo et al. (Res Policy 30(3): 485–508, 2001), we find that polarization through preferential attachment driven by large pharmaceutical companies as Developers and by the entry of new specialized biotechnology companies acting as Originators of new R&D opportunities dominated the early stages of the biotechnology revolution. Later on the evolution of the collaborative network has been shaped by roles’ transitions between Originators and Developers of innovative ideas. Against this background, we introduce parsimonious model of network formation and evolution is introduced, to account for some essential features of the data generating processes underlying the evolution of the network.

Corporate groups or networks, which are defined as collections of two or more legally independent firms connected through ownership ties, are prevalent in both developed and developing countries. The separate effects of firm centrality and corporate group size on firm performance have been largely discussed in the literature. However, the effect of their interaction remains underexplored. This paper attempts to fill the gap by introducing a new normalized measure of firm centrality independent of corporate group size. Our empirical analysis is based on a set of global corporate networks encompassing 17.8 million firms and the ownership ties between them extracted from the ORBIS database in 2014. We further investigate the firm performance in the corporate networks above by gathering financial information on 483,835 Italian firms from the AIDA database from 2014 to 2016. We find a positive relationship between firm centrality and firm performance, but the significance of the relationship decreases as corporate group size increases.

This paper investigates the relations between festivals and their institutional settings, and how these relations shape festival management. We analyze institutional logics and work practices in a complex project, Lucca Comics & Games, which is the biggest festival dedicated to fantasy culture in Italy. Our results, based on archival research, media coverage and interview data, reveal the recursive interplay between institutional logics and work practices for institutional maintenance. We argue that the study of festivals is essential to understanding key aspects of project-based organizing more generally. In this regard, the maintaining of institutions must be distinguished from stability or the absence of change and consideration of historical and contextual analysis, and multiple tensions that occur due to competing institutional logics can open up new ways of thinking for prospective research. We also demonstrate that future research can use institutional work practices for understanding institutional maintenance in recurring temporary organizations.

Proponents describe stem Cell Replacement Therapy and related technologies to be a significant step forward for medicine. However, due to the inherent ethical problems in human Embryonic Stem Cell Research (hESC), it is strictly regulated around the world. The US has passed at the federal and state level, both supportive and restrictive laws over the years. The changing legislative environment at the state and federal levels has created a situation whereby researchers have to choose whether and where to carry out this research. By exploiting the temporal and spatial heterogeneity and legislative shocks, we assess if the affected scientists have voted with their feet, leaving the state or country imposing restrictive rules and whether hESC research has clustered geographically. We find that most of the hESC research is carried out in supportive states, and significant legislative changes have had a minor but noticeable effect on relocation choices. Most importantly, the research has moved to supportive states. This result suggests that several state-level interventions (supportive), which were opposed to federal laws (restrictive), have counteracted each other.

Thanks to the increasing availability of granular, yet high-dimensional, firm level data, machine learning (ML) algorithms have been successfully applied to address multiple research questions related to firm dynamics. Especially supervised learning (SL), the branch of ML dealing with the prediction of labelled outcomes, has been used to better predict firms’ performance. In this chapter, we will illustrate a series of SL approaches to be used for prediction tasks, relevant at different stages of the company life cycle. The stages we will focus on are (1) startup and innovation, (2) growth and performance of companies, and (3) firms’ exit from the market. First, we review SL implementations to predict successful startups and R&D projects. Next, we describe how SL tools can be used to analyze company growth and performance. Finally, we review SL applications to better forecast financial distress and company failure. In the concluding section, we extend the discussion of SL methods in the light of targeted policies, result interpretability, and causality.

Global cities boast higher rates of innovation as measured through patent and scientific production. However, the source of the location advantage of innovation hubs is still debated in the literature, with arguments ranging from localized knowledge spillovers to network effects. Thanks to an extensive data set of individual scientist career paths, we shed new light on the role of scientist location choices in determining the superior innovative performance of global cities. We analyze the career paths of around two million researchers over a decade across more than two thousand cities around the globe. First, we show that scientists active in global cities are more productive in terms of citation weighted publications. We then show that this superior performance is in part driven by highly prolific scientists moving and remaining preferentially in global cities, i.e., central cities in the international scientist mobility network. The overall picture that emerges is that global cities are better positioned to attract and retain prolific scientists than more peripheral cities., Research Policy, 50 (1), ISSN:0048-7333, ISSN:1873-7625

This paper investigates the relationship between international trade and migration with the specific aim of estimating direct and indirect effect of the latter on cross-border flows of both homogeneous and differentiated goods. Adopting a spatial econometric approach along with a gravity model set-up, we account for the role of ethnic communities in neighbouring countries on trade, and we propose a new way to define neighbours based on the intensity of links in the migration network. Our approach is particularly well suited to measure the indirect effect stemming from the presence of significant ethnic communities on trade through a “market familiarization” effect. Using data covering all countries between 1970 and 2000, we find a significant indirect effect of migration on trade, that depends on the chosen weight matrix.

The proper characterization of the size distribution of business firms represents an important issue in economic literature, with the most common reference distribu- tions being the lognormal and the Pareto varieties. This analysis is related to some methodological issues that are rarely properly addressed in applied work, and may significantly affect the results: the major difficulties arise from low power of the tests caused by limited sample size and the common practice of binning the data. In this paper we contribute to this body of literature by analyzing the size distribu- tion of all French companies, strongly rejecting the hypothesis that it is a Pareto distribution. Moreover, we argue that the lognormal distribution is a more reason- able first-cut benchmark for the entire population of firms. This is especially true for single-product firms, while we show the emergence of a Zipf tail for the class of multi-product companies. Our findings are in strong agreement with some recent theoretical contributions, which predict that the size distribution depends on a set of industry specific determinants.

The relationship between international trade and foreign direct investment (FDI) is one of the main features of globalisation. In this paper, we investigate the effects of FDI on trade from a network perspective, since FDI takes not only direct but also indirect channels from origin to destination countries because of firms’ incentive to reduce tax burden, to minimise coordination costs and to break barriers to market entry. We use a unique data set of international corporate control as a measure of stock FDI to construct a corporate control network (CCN), where the nodes are the countries and the edges are the corporate control relationships. Network measures, as the shortest path length and the communicability, are then computed on the CCN to capture the indirect channel of FDI. Empirically, we find that corporate control has a positive effect on trade both directly and indirectly. The result is robust with different specifications and estimation strategies. Hence, our paper provides strong empirical evidence of the indirect effects of FDI on trade. Moreover, we identify a number of interplaying factors such as regional trade agreements and the region of Asia. We also find that the indirect effects are more pronounced for the manufacturing sector than for primary sectors such as oil extraction and agriculture.

Networks of portfolio holdings exemplify how interdependence both between the agents and their assets can be a source of systemic vulnerability. We study a real-world holdings network and compare it with various alternative scenarios from randomization and rebalancing of the original investments. Scenarios generation relies on algorithms that satisfy the global constraints imposed by the numbers of outstanding shares in the market. We consider fixed-diversification models and diversification-maximizing replicas too. We extensively analyze the interplay between portfolio diversification and differentiation, and how the outreach of exogenous shocks depends on these factors as well as on the type of shock and the size of the network with respect to the market. We find that real portfolios are poorly diversified but highly similar, that portfolio similarity correlates with systemic fragility and that rebalancing can come with an increased similarity depending on the initial network configuration. We show that a large diversification gain is achieved through rebalancing but, noteworthy, that makes the network vulnerable in front of unselective shocks. Also, while the network is riskier in the presence of targeted shocks, it is safer than its random counterparts when it is stressed by widespread price downturns.

In the current paper, we discuss the need for regulation at EU level of Connected and Automated Driving solutions (henceforth CAD) based on multiple considerations, namely (i) the need for uniformity of criteria across European Member States, and (ii) the impact that regulation—or the absence of it—has on the proliferation of specific technological solutions. The analysis is grounded on legal and economic considerations of possible interactions between vehicles with different levels of automation, and shows how the existing framework delays innovation. A Risk-Management Approach, identifying one sole responsible party ex ante (one-stop-shop), liable under all circumstances—pursuant to a strict, if not absolute liability rule—is to be preferred. We analyse the solution adopted by some Member States in light of those considerations and conclude that none truly corresponds to a RMA approach, and differences will also cause market fragmentation. We conclude that because legal rules determine what kind of technological application is favoured over others—and thence they are not technology-neutral—uniformity across MSs is of essential relevance, and discuss possible policy approaches to be adopted at European level.

We present a new network model accounting for multidimensional assortativity. Each node is characterized by a number of features and the probability of a link between two nodes depends on common features. We do not fix a priori the total number of possible features. The bipartite network of the nodes and the features evolves according to a stochastic dynamics that depends on three parameters that respectively regulate the preferential attachment in the transmission of the features to the nodes, the number of new features per node, and the power-law behavior of the total number of observed features. Our model also takes into account a mechanism of triadic closure. We provide theoretical results and statistical estimators for the parameters of the model. We validate our approach by means of simulations and an empirical analysis of a network of scientific collaborations.

International trade has been increasingly organized in the form of global value chains (GVCs) where different stages of production are located in different countries. This recent phenomenon has substantial consequences for both trade policy design at the national or regional level and business decision making at the firm level. In this paper, we provide a new method for comparing GVCs across countries and over time. First, we use the World Input-Output Database (WIOD) to construct both the upstream and downstream global value networks, where the nodes are individual sectors in different countries and the links are the value-added contribution relationships. Second, we introduce a network-based measure of node similarity to compare the GVCs between any pair of countries for each sector and each year available in the WIOD. Our network-based similarity is a better measure for node comparison than the existing ones because it takes into account all the direct and indirect relationships between country-sector pairs, is applicable to both directed and weighted networks with self-loops, and takes into account externally defined node attributes. As a result, our measure of similarity reveals the most intensive interactions among the GVCs across countries and over time. From 1995 to 2011, the average similarity between sectors and countries have clear increasing trends, which are temporarily interrupted by the recent economic crisis. This measure of the similarity of GVCs provides quantitative answers to important questions about dependency, sustainability, risk, and competition in the global production system., Comment: 30 pages, 14 figures

This paper investigates the role of real options reasoning in R&D project portfolio management and investment decisions of pharmaceutical firms. We analyse a unique dataset that integrates information on initiation and termination of clinical trials at the level of specific medical indications. Consistent with existing literature, we find a positive relationship between market size and firm entry in clinical trials. We also show that the option value of R&D investments, as proxied by the scope of R&D projects, affects the selection of target markets. Moreover, high-risk research areas attract more entry, in line with the predictions of real options theory. However, we also find that more flexibility in project duration and delayed project discontinuation attract higher rates of entry. Departures from pure real options reasoning are motivated by the presence of incremental learning in pharmaceutical R&D.

When studying patent data as a way to understand innovation and technological change, the conventional indicators might fall short, and categorizing technologies based on the existing classification systems used by patent authorities could cause inaccuracy and misclassification, as shown in literature. Gao et al. (International Workshop on Complex Networks and their Applications, 2017) have established a method to analyze patent classes of similar technologies as network communities. In this paper, we adopt the stabilized Louvain method for network community detection to improve consistency and stability. Incorporating the overlapping community mapping algorithm, we also develop a new method to identify the central nodes based on the temporal evolution of the network structure and track the changes of communities over time. A case study of Germany’s patent data is used to demonstrate and verify the application of the method and the results. Compared to the non-network metrics and conventional network measures, we offer a heuristic approach with a dynamic view and more stable results. Electronic supplementary material The online version of this article (10.1007/s41109-018-0090-3) contains supplementary material, which is available to authorized users.

Network theory proved recently to be useful in the quantification of many properties of financial systems. The analysis of the structure of investment portfolios is a major application since their eventual correlation and overlap impact the actual risk by individual investors. We investigate the bipartite network of US mutual fund portfolios and their assets. We follow its evolution during the Global Financial Crisis and study the diversification, as understood in modern portfolio theory, and the similarity of the investments of different funds. We show that, on average, portfolios have become more diversified and less similar during the crisis. However, we also find that large overlap is far more likely than expected from benchmark models of random allocation of investments. This indicates the existence of strong correlations between fund investment strategies. We exploit a deliberately simplified model of shock propagation to identify a systemic risk component stemming from the similarity of portfolios. The network is still partially vulnerable after the crisis because of this effect, despite the increase in the diversification of multi asset portfolios. Diversification and similarity should be taken into account jointly to properly assess systemic risk.

Patent data represent a significant source of information on innovation and the evolution of technology through networks of citations, co-invention and co-assignment of new patents. A major obstacle to extracting useful information from this data is the problem of name disambiguation: linking alternate spellings of individuals or institutions to a single identifier to uniquely determine the parties involved in the creation of a technology. In this paper, we describe a new algorithm that uses high-resolution geolocation to disambiguate both inventor and assignees on more than 3.6 million patents found in the European Patent Office (EPO), under the Patent Cooperation treaty (PCT), and in the US Patent and Trademark Office (USPTO). We show that our algorithm has both high precision and recall in comparison to a manual disambiguation of EPO assignee names in Boston and Paris, and show it performs well for a benchmark of USPTO inventor names that can be linked to a high-resolution address (but poorly for inventors that never provided a high quality address). The most significant benefit of this work is the high quality assignee disambiguation with worldwide coverage coupled with an inventor disambiguation that is competitive with other state of the art approaches. To our knowledge this is the broadest and most accurate simultaneous disambiguation and cross-linking of the inventor and assignee names for a significant fraction of patents in these three major patent collections., Comment: 25 pages, 3 figures

Complex economic systems can often be described by a network, with nodes representing economic entities and edges their interdependencies, while network centrality is often a good indicator of importance. Recent publications have implemented a nonlinear iterative Fitness-Complexity (FC) algorithm to measure centrality in a bipartite trade network, which aims to represent the ‘Fitness’ of national economies as well as the ‘Complexity’ of the products being traded. In this paper, we discuss this methodological approach and conclude that further work is needed to identify stable and reliable measures of fitness and complexity. We provide theoretical and numerical evidence for the intrinsic instability in the nonlinear definition of the FC algorithm. We perform an in-depth evaluation of the algorithm’s rankings in two real world networks at the country level: the global trade network, and the patent network in different technological domains. In both networks, we find evidence of the instabilities predicted theoretically, and show that ‘complex’ products or patents tend often to be those that countries rarely produce, rather than those that are intrinsically more difficult to produce. ispartof: Scientific Reports vol:7 issue:1 ispartof: location:England status: published

In this paper, we build a cumulative innovation model to understand the role of both success and failure in the learning dynamics that characterize pharmaceutical R&D. We test the prediction of our model by means of a unique dataset that combines patent information with R&D projects, thus distinguishing patents related to successfully marketed products from those covering candidate drugs that failed in clinical trials. Results confirm model predictions showing that patents associated with successfully completed projects receive more citations than those associated with failed projects. However, we also show that failed projects can be in turn cited more often than patents lacking clinical or preclinical information. We further explore the ‘black box’ of innovation, providing evidence that both successes and failures contribute to R&D investment decisions and knowledge dynamics in science-driven sectors.

The fragmentation of production across countries has become an important feature of the globalization in recent decades and is often conceptualized by the term, global value chains (GVCs). When empirically investigating the GVCs, previous studies are mainly interested in knowing how global the GVCs are rather than how the GVCs look like. From a complex networks perspective, we use the World Input-Output Database (WIOD) to study the global production system. We find that the industry-level GVCs are indeed not chain-like but are better characterized by the tree topology. Hence, we compute the global value trees (GVTs) for all the industries available in the WIOD. Moreover, we compute an industry importance measure based on the GVTs and compare it with other network centrality measures. Finally, we discuss some future applications of the GVTs., Comment: 26 pages, 6 figures. arXiv admin note: text overlap with arXiv:1407.0225

We draw on diverse data sets to compare the institutional organization of upstream life science research across the United States and Europe. Understanding cross-national differences in the organization of innovative labor in the life sciences requires attention to the structure and evolution of biomedical networks involving public research organizations (universities, government laboratories, nonprofit research institutes, and research hospitals), science-based biotechnology firms, and multinational pharmaceutical corporations. We use network visualization methods and correspondence analyses to demonstrate that innovative research in biomedicine has its origins in regional clusters in the United States and in European nations. But the scientific and organizational composition of these regions varies in consequential ways. In the United States, public research organizations and small firms conduct R&D across multiple therapeutic areas and stages of the development process. Ties within and across these regions link small firms and diverse public institutions, contributing to the development of a robust national network. In contrast, the European story is one of regional specialization with a less diverse group of public research organizations working in a smaller number of therapeutic areas. European institutes develop local connections to small firms working on similar scientific problems, while cross-national linkages of European regional clusters typically involve large pharmaceutical corporations. We show that the roles of large and small firms differ in the United States and Europe, arguing that the greater heterogeneity of the U.S. system is based on much closer integration of basic science and clinical development.

Theory of complex networks proved successful in the description of a variety of static networks ranging from biology to computer and social sciences and to economics and finance. Here we use network models to describe the evolution of a particular economic system, namely the International Trade Network (ITN). Previous studies often assume that globalization and regionalization in international trade are contradictory to each other. We re-examine the relationship between globalization and regionalization by viewing the international trade system as an interdependent complex network. We use the modularity optimization method to detect communities and community cores in the ITN during the years 1995-2011. We find rich dynamics over time both inter- and intra-communities. Most importantly, we have a multilevel description of the evolution where the global dynamics (i.e., communities disappear or reemerge) tend to be correlated with the regional dynamics (i.e., community core changes between community members). In particular, the Asia-Oceania community disappeared and reemerged over time along with a switch in leadership from Japan to China. Moreover, simulation results show that the global dynamics can be generated by a preferential attachment mechanism both inter- and intra-communities., 8 pages, 4 figures

An integrated European Research Area (ERA) is a critical component for a more competitive and open European R&D system. However, the impact of EU-specific integration policies aimed at overcoming innovation barriers associated with national borders is not well understood. Here we analyze 2.4 x 10^6 patent applications filed with the European Patent Office (EPO) over the 25-year period 1986-2010 along with a sample of 2.6 x 10^5 records from the ISI Web of Science to quantitatively measure the role of borders in international R&D collaboration and mobility. From these data we construct five different networks for each year analyzed: (i) the patent co-inventor network, (ii) the publication co-author network, (iii) the co-applicant patent network, (iv) the patent citation network, and (v) the patent mobility network. We use methods from network science and econometrics to perform a comparative analysis across time and between EU and non-EU countries to determine the "treatment effect" resulting from EU integration policies. Using non-EU countries as a control set, we provide quantitative evidence that, despite decades of efforts to build a European Research Area, there has been little integration above global trends in patenting and publication. This analysis provides concrete evidence that Europe remains a collection of national innovation systems., 24 pages, 4 figures, 2 tables

The Statistical Physics of Complex Networks has recently provided new theoretical tools for policy makers. Here we extend the notion of network controllability to detect the financial institutions, i.e. the drivers, that are most crucial to the functioning of an interbank market. The system we investigate is a paradigmatic case study for complex networks since it undergoes dramatic structural changes over time and links among nodes can be observed at several time scales. We find a scale-free decay of the fraction of drivers with increasing time resolution, implying that policies have to be adjusted to the time scales in order to be effective. Moreover, drivers are often not the most highly connected “hub” institutions, nor the largest lenders, contrary to the results of other studies. Our findings contribute quantitative indicators which can support regulators in developing more effective supervision and intervention policies., Scientific Reports, 3, ISSN:2045-2322

Economic systems, traditionally analyzed as almost independent national systems, are increasingly connected on a global scale. Only recently becoming available, the World Input-Output Database (WIOD) is one of the first efforts to construct the multi-regional input-output (MRIO) tables at the global level. By viewing the world input-output system as an interdependent network where the nodes are the individual industries in different economies and the edges are the monetary goods flows between industries, we study the network properties of the so-called world input-output network (WION) and document its evolution over time. We are able to quantify not only some global network properties such as assortativity, clustering coefficient, and degree and strength distributions, but also its subgraph structure and dynamics by using community detection techniques. Over time, we detect a marked increase in cross-country connectivity of the production system, only temporarily interrupted by the 2008-2009 crisis. Moreover, we find a growing input-output regional community in Europe led by Germany and the rise of China in the global production system. Finally, we use the network-based PageRank centrality and community coreness measure to identify the key industries and economies in the WION and the results are different from the one obtained by the traditional final-demand-weighted backward linkage measure., Comment: 24 pages, 16 figures

Recent studies on the geography of knowledge networks have documented a negative impact of physical distance and institutional borders upon research and development (R&D) collaborations. Though it is widely recognized that geographic constraints and national borders impede the diffusion of knowledge, less attention has been devoted to the temporal evolution of these constraints. In this study we use data on patents filed with the European Patent Office (EPO) for OECD countries to analyze the impact of physical distance and country borders on inter-regional links in four different networks over the period 1988–2009: (1) co-inventorship, (2) patent citations, (3) inventor mobility and (4) the location of R&D laboratories. We find the constraint imposed by country borders and distance decreased until mid-1990s then started to grow, particularly for distance. The intensity of European cross-country inventor collaborations increased at a higher pace than their non-European counterparts until 2004, with no significant relative progress thereafter. For geographical networks of mobility, R&D activities and patent citations we cannot detect any substantial progress in European research integration above and beyond the common global trend. publisher: Elsevier articletitle: The evolution of networks of innovators within and across borders: Evidence from patent data journaltitle: Research Policy articlelink: http://dx.doi.org/10.1016/j.respol.2014.10.015 content_type: article copyright: Copyright © 2014 Elsevier B.V. ispartof: Research Policy vol:44 issue:3 pages:651-668 status: published