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Proximity and the Evolution of Collaboration Networks: Evidence from Research and Development Projects within the Global Navigation Satellite System (GNSS) Industry

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  • Pierre-Alexandre Balland

Abstract

B alland P.-A. Proximity and the evolution of collaboration networks: evidence from research and development projects within the global navigation satellite system (GNSS) industry, Regional Studies . This paper analyses the influence of proximity on the evolution of collaboration networks. It determines empirically how organizations choose their partners according to their geographical, cognitive, organizational, institutional and social proximity. Relational databases are constructed from research and development collaborative projects, funded under the European Union 6th Framework Programme within the global navigation satellite system (GNSS) industry from 2004 to 2007. The stochastic actor-based model SIENA is used to model the network dynamic as a realization of a continuous-time Markov chain and to estimate parameters for underlying mechanisms of its evolution. Empirical results show that geographical, organizational and institutional proximity favour collaborations, while cognitive and social proximity do not play a significant role. B alland P.-A. 相似性以及协作网络&# x7684;演进:来自全球导 22A;卫星系统产业研究Լ A;发展项目的相关证据 ,区域研究。本文分&# x6790;了相似性在协作网 EDC;演进过程中的作用̀ 2;这一研究从经验层面 上考察了不同的组织&# x662F;如何根据地理的、 BA4;知的、组织学的、ԣ 6;度的以及社会的相似 性来选择合作伙伴的&# x3002;2004-2007 年间欧盟全球导航卫&# x661F;系统产业的第六次 846;架计划资助了一系ԡ 7;研究及发展项目,基 于上述研究及项目我&# x4EEC;构建了相关的数据 E93;。我们利用随机的ࢄ C;为者模型 SIENA 来模型化了网络活力&# xFF0C;以实现连续的 Markov 链同时估测了影响其&# x6F14;进机制的相关变量 002;经验结果表明,地݀ 6;的、组织的以及制度 的相似性会促进协作&# x7684;产生,而认知与空 5F4;的相似性作用并不٣ E;著。 协作网络 相似性 &# x7ECF;济地理学 活力网 EDC;模型 全球导航卫١ F;系统 (GNSS) B alland P.-A. La proximité et l’évolution des réseaux de collaboration: des preuves provenant des projets de R et D au sein de l’industrie du système global de navigation par satellite (GNSS), Regional Studies . Ce papier analyse l’influence de la proximité sur l’évolution des réseaux de collaboration. Il détermine empiriquement la façon dont les organisations choisissent leurs partenaires en fonction de leur proximité géographique, cognitive, organisationnelle, institutionnelle et sociale. Les bases de données relationnelles sont construites à partir des projets collaboratifs de R&D financés par le 6-super-ème Programme Cadre de Recherche et de Développement de l’Union Européenne, dans la navigation par satellite (GNSS) de 2004 à 2007. Le modèle stochastique orienté par l’acteur SIENA est utilisé pour modéliser la dynamique du réseau par une chaîne de Markov en temps continu et pour estimer les paramètres liés aux mécanismes de son évolution. Les résultats empiriques montrent que les dimensions de proximité géographique, organisationnelle et institutionnelle favorisent les collaborations, tandis que les formes de proximité cognitive et sociale ne jouent pas un rôle significatif. Réseaux de collaboration Proximité Économie géographique Modèles de réseaux dynamiques Système global de navigation par satellite (GNSS) B alland P.-A. Nähe und Entstehen von kooperativen Netzwerken: Belege aus Forschungs- und Entwicklungsprojekten innerhalb der Branche des globalen Navigationssatellitensystems (GNSS), Regional Studies . In diesem Beitrag wird der Einfluss der Nähe auf das Entstehen von kooperativen Netzwerken untersucht. Auf empirische Weise wird ermittelt, wie sich Firmen ihre Partner je nach ihrer geografischen, kognitiven, organisationellen, institutionellen und sozialen Nähe aussuchen. Auf der Grundlage von kooperativen Forschungs- und Entwicklungsprojekten innerhalb der Branche des globalen Navigationssatellitensystems (GNSS) im Zeitraum von 2004 bis 2007, die unter dem 6. Rahmenprogramm der Europäischen Union finanziert wurden, werden relationale Datenbanken aufgebaut. Zur Modellierung der Netzwerkdynamik als Realisierung einer zeitlich kontinuierlichen Markow-Kette und zur Schätzung der Parameter für die zugrundeliegenden Mechanismen ihrer Entstehung kommt das stochastische, akteurbasierte SIENA-Modell zum Einsatz. Aus den empirischen Ergebnissen geht hervor, dass eine geografische, organisationelle und institutionelle Nähe die Zusammenarbeit fördert, während die kognitive und soziale Nähe keine signifikante Rolle spielt. Kooperative Netzwerke Nähe Wirtschaftsgeografie Dynamische Netzwerkmodelle Globales Navigationssatellitensystem (GNSS) B alland P.-A. Proximidad y la evolución de las redes de colaboración: evidencias de proyectos de investigación y desarrollo en la industria del sistema global de navegación por satélite (GNSS), Regional Studies . En este artículo se analiza la influencia de la proximidad en la evolución de las redes de colaboración. Se determina empíricamente cómo las organizaciones eligen sus socios en función de su proximidad geográfica, cognitiva, organizativa, institucional y social. Se construyen bases de datos relacionados a partir de proyectos colaboradores de investigación y desarrollo financiados bajo el sexto programa marco de la Unión Europea en la industria del sistema global de navegación por satélite (GNSS) de 2004 a 2007. Se utiliza el enfoque estocástico SIENA basado en actores para modelar la dinámica de redes como realización de una cadena Markov de tiempo continuo y calcular los parámetros de los mecanismos subyacentes de su evolución. Los resultados empíricos muestran que la proximidad geográfica, organizativa e institucional favorece las colaboraciones mientras que la proximidad cognitiva y social no desempeña un papel significativo. Redes de colaboración Proximidad Geografía económica Modelos de redes dinámicas Sistema global de navegación por satélite (GNSS)

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Article provided by Taylor & Francis Journals in its journal Regional Studies.

Volume (Year): 46 (2012)
Issue (Month): 6 (September)
Pages: 741-756

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Handle: RePEc:taf:regstd:v:46:y:2012:i:6:p:741-756

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Cited by:
  1. Negin Salimi & Rudi Bekkers & Koen Frenken, 2013. "Governance Mode Choice in Collaborative PhD Projects," Working Papers 13-09, Eindhoven Center for Innovation Studies, revised Oct 2013.
  2. Muhamed Kudic & Andreas Pyka & Marco Sunder, 2013. "Network Formation: R&D Cooperation Propensity and Timing Among German Laser Source Manufacturers," IWH Discussion Papers 9, Halle Institute for Economic Research.
  3. Pierre-Alexandre Balland & Ron Boschma & Koen Frenken, 2013. "Proximity and Innovation: From Statics to Dynamics," Papers in Evolutionary Economic Geography (PEEG) 1314, Utrecht University, Section of Economic Geography, revised Aug 2013.
  4. T. Buchmann & D. Hain & Muhamed Kudic & M. Müller, 2014. "Exploring the Evolution of Innovation Networks in Science-driven and Scale-intensive Industries: New Evidence from a Stochastic Actor-based Approach," IWH Discussion Papers 1, Halle Institute for Economic Research.
  5. Ron Boschma, 2014. "Towards an evolutionary perspective on regional resilience," Papers in Evolutionary Economic Geography (PEEG) 1409, Utrecht University, Section of Economic Geography, revised Mar 2014.

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