944 research outputs found

    Phenomenological Models of Socio-Economic Network Dynamics

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    We study a general set of models of social network evolution and dynamics. The models consist of both a dynamics on the network and evolution of the network. Links are formed preferentially between 'similar' nodes, where the similarity is defined by the particular process taking place on the network. The interplay between the two processes produces phase transitions and hysteresis, as seen using numerical simulations for three specific processes. We obtain analytic results using mean field approximations, and for a particular case we derive an exact solution for the network. In common with real-world social networks, we find coexistence of high and low connectivity phases and history dependence.Comment: 11 pages, 8 figure

    Exploring the role of professional associations in collective learning in London and New York's advertising and law professional service firm clusters.

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    The value of regional economies for collective learning has been reported by numerous scholars. However often work has been criticised for lacking analytical clarity and failing to explore the architectures of collective learning and the role of the knowledge produced in making firms in a cluster economy successful. This paper engages with these problematics and investigates how collective learning is facilitated in the advertising and law professional service firm clusters in London and New York. It explores the role of professional associations and investigates how they mediate a collective learning process in each city. It argues that professional associations seed urban communities of practice that emerge outside of the formal activities of professional associations. In these communities individual with shared interests in advertising and law learn from one-another and are therefore able to adapt and evolve one-another approaches to common industry challenges. The paper suggests this is another form of the variation Marshall highlighted in relation to cluster-based collective learning. The paper also shows how the collective learning process is affected by the presence, absence and strength of an institutional thickness. It is therefore argued that a richer understanding of institutional affects is needed in relation to CL

    Migration, communities-on-the-move and international innovation networks: An empirical analysis of Spanish regions

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    This paper investigates the impact of migration on innovation networks between regions and foreign countries. We posit that immigrants (emigrants) act as a transnational knowledge bridge between the host (home) regions and their origin (destination) countries, thus facilitating their co-inventorship networks. We also argue that the social capital of both the hosting and the moving communities reinforces such a bridging role, along with language commonality and migrants’ human capital. Focusing on Spain, as a country that hosted an intense process of migration over the past two decades, we combine patent data with national data on residents and electors abroad and we apply a gravity model to the co-inventorship between Spanish provinces (NUTS3 regions) and a number of foreign countries. Both immigrants and emigrants affect the kind of innovation networking at stake. The social capital of both the moving and the hosting communities actually moderate this impact in a positive way. The effect of migration is stronger for more skilled migrants and with respect to non-Spanish speaking countries, pointing to a language-bridging role of migrants. Policy implications are drawn accordingly

    Industrial clusters in the developing economies: insights from the Iranian carpet industry

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    Industrial clusters are perceived as potential drivers of SMEs development and efficient policy instruments to lead national and regional innovation and growth. However, these clusters in developing economies are typically placed in complex environments that impose a mix of serious challenges which adversely affect their overall performance. Therefore, this study aims to analyze the nature of these challenges and understand their dynamics using a case study of a carpet industry cluster in Iran. Using multiple sources of evidence, the study reveals two distinct, yet interrelated, levels of challenges: micro and macro. Under each level, a number of key dimensions were identified and theoretically linked which helped to conceptualize the structure of these challenges and model their dynamics

    Agglomerations and firm performance: who benefits and how much?

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    [EN] Agglomerations and firm performance: who benefits and how much? Regional Studies. Agglomeration can generate gains. If it does, how does it work and how are those gains distributed across agglomerated firms? The paper examines the effect of localization externalities on innovation. Localization externalities are measured as industry specialization or a firm s colocation in a relatively high own-industry employment region. By analyzing a large dataset of 6697 firms integrated with another regional agglomeration-related dataset, results show that (1) co-location in an agglomeration has a positive influence on a firm s innovative performance; and (2) firms benefit heterogeneously from agglomerations, with benefits being distributed asymmetrically. Agglomeration gains exist but not all firms benefit equally.Financial support was provided by the Spanish Ministry of Economics, Industry and Competitiveness [research grant ECO:2015-63645-R] (Mineco/Feder), Open Innovation in Clusters.HervĂĄs Oliver, JL.; Sempere-Ripoll, F.; Rojas Alvarado, RJ.; Estelles Miguel, S. (2018). Agglomerations and firm performance: who benefits and how much?. Regional Studies. 52(3):338-349. https://doi.org/10.1080/00343404.2017.1297895S33834952

    Cluster Performance reconsidered: Structure, Linkages and Paths in the German Biotechnology Industry, 1996-2003

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    This paper addresses the evolution of biotechnology clusters in Germany between 1996 and 2003, paying particular attention to their respective composition in terms of venture capital, basic science institutions and biotechnology firms. Drawing upon the significance of co-location of "money and ideas", the literature stressing the importance of a cluster's openness and external linkages, and the path dependency debate, the paper aims to analyse how certain cluster characteristics correspond with its overall performance. After identifying different cluster types, we investigate their internal and external interconnectivity in comparative manner and draw on changes in cluster composition. Our results indicate that the structure, i.e. to which group the cluster belongs, and the openness towards external knowledge flows deliver merely unsystematic indications with regard to a cluster's overall success. Its ability to change composition towards a more balanced ratio of science and capital over time, on the other hand, turns out as a key explanatory factor. Hence, the dynamic perspective proves effective illuminating cluster growth and performance, where our explorative findings provide a promising avenue for further evolutionary research

    Scientists as Midwives to Cluster Emergence: An Institutional Work Framework

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    The question of how embedded actors can create institutions that support cluster emergence remains unsolved in the cluster and national innovation systems literature. The present paper extends the recent literature on institutional entrepreneurship and institutional work to solve this paradox of embedded agency in the context of science-based clusters. Building on a longitudinal single case study of a functional foods cluster in Finland, we present an institutional work framework for cluster formation. We argue that, in addition to ideational, material and bridging work, authentic leadership work is critical for cluster emergence. The results of the study highlight the opportunities that scientists have to act as midwives to cluster formation, but they also show that well-functioning clusters need a broader support base.Peer reviewe

    A new approach to migration: communities on the move as assets

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    The aim of this article (opening the special issue) is to examine the impact of migration on a specific set of issues at the regional level: innovation, entrepreneurship and economic performance. In particular, we look at migration through a new lens of analysis, which we have termed the “Communities-on-the-Move (CoM)” approach. In a nutshell, this approach focuses on migrant communities, emerging from the capacity of specific national/regional groups to carry the heritage of their social capital when moving from one place to another. More precisely, the CoM approach focuses on the social capital migrants can rely on to “bond” their in-group relations and to “bridge” with extra-group ones during the migration process. The CoM approach represents a different, though complementary approach to the analysis of diasporas in the migration literature. Indeed, CoM relates to diasporas similarly to how “clustering effects” relate to “networking activities” in the regional economics of innovation literature. CoM approach takes account of the local effects such communities generate in the localities they are embedded in (“clustering effect”), while the related ‘diaspora communities concept’ captures the non-local “networking activities” that connect ethnic communities across the world. As we will also maintain in the following, through this specificity the CoM approach is likely to capture a significant impact on innovation, entrepreneurship and economic performance, which would remain otherwise hidden by using more standard approaches to migration
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