Pierre-Alexandre Balland

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

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 R&D collaborative projects, funded under the European Union 6th Framework Programme within the navigation by satellite industry (GNSS) from 2004 to 2007. The stochastic actor-based model SIENA is used to model the network dynamic as a realisation 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.Balland 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. Balland P.-A. 相似性以及协作网络的演进：来自全球导航卫星系统产业研究及发展项目的相关证据，区域研究。本文分析了相似性在协作网络演进过程中的作用。这一研究从经验层面上考察了不同的组织是如何根据地理的、认知的、组织学的、制度的以及社会的相似性来选择合作伙伴的。2004－2007 年间欧盟全球导航卫星系统产业的第六次框架计划资助了一系列研究及发展项目，基于上述研究及项目我们构建了相关的数据库。我们利用随机的行为者模型 SIENA 来模型化了网络活力，以实现连续的 Markov 链同时估测了影响其演进机制的相关变量。经验结果表明，地理的、组织的以及制度的相似性会促进协作的产生，而认知与空间的相似性作用并不显著。 协作网络 相似性 经济地理学 活力网络模型 全球导航卫星系统 （GNSS） Balland 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 6ème 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) Balland 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) Balland 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)

Proximity and Innovation: From Statics to Dynamics

Balland P.-A., Boschma R. and Frenken K. Proximity and innovation: from statics to dynamics, Regional Studies. Despite theoretical and empirical advances, the proximity framework has remained essentially static. A dynamic extension of the proximity framework is proposed that accounts for co-evolutionary dynamics between knowledge networking and proximity. For each proximity dimension, how proximities might increase over time as a result of past knowledge ties is described. These dynamics are captured through the processes of learning (cognitive proximity), integration (organizational proximity), decoupling (social proximity), institutionalization (institutional proximity), and agglomeration (geographical proximity). The paper ends with a discussion of several avenues for future research on the dynamics of knowledge networking and proximity.

Structural and geographical patterns of knowledge networks in emerging technological standards: evidence from the European GNSS industry

The concentration and dispersion of innovative activities in space have been largely explained and evidenced by the nature of knowledge and the geographical extent of knowledge spillovers. One of the empirical challenges is to go beyond this by understanding how the geography of innovation is shaped by particular structural properties of knowledge networks. This paper contributes to this challenge, focusing on the particular case of global navigation satellite systems at the European level. We exploit a database of R&D collaborative projects based on the fifth and sixth European Union Framework Programs, and apply social network analysis in economic geography. We study the properties both of the network of organizations and the network of collaborative projects. We show that the nature of the knowledge involved in relationships influences the geographical and structural organizations of the technological field. The observed coexistence of a relational core/periphery structure with a geographical cluster/pipeline one is discussed in the light of the industrial and geographical dynamics of technological standards.

The Dynamics of Technical and Business Knowledge Networks in Industrial Clusters: Embeddedness, Status, or Proximity?

Abstract Although informal knowledge networks have often been regarded as a key ingredient behind the success of industrial clusters, the forces that shape their structure and dynamics remain largely unknown. Drawing on recent network dynamic models, we analyze the evolution of business and technical knowledge networks within a toy cluster in Spain. Empirical results suggest that the dynamics of the two networks differ to a large extent. We find that status drives the formation of business knowledge networks, proximity is more crucial for technical knowledge networks, while embeddedness plays an equally important role in the dynamics of both networks.

The Geography of Complex Knowledge

abstract There is consensus among scholars and policy makers that knowledge is one of the key drivers of long-run economic growth. It is also clear from the literature that not all knowledge has the same value. However, too often in economic geography and cognate fields we have been obsessed with counting knowledge inputs and outputs rather than assessing the quality of knowledge produced. In this article we measure the complexity of knowledge, we map the distribution and the evolution of knowledge complexity in US cities, and we explore how the spatial diffusion of knowledge is linked to complexity. Our knowledge complexity index rests on the bimodal network models of Hidalgo and Hausmann. Analysis is based on more than two million patent records from the US Patent and Trademark Office that identify the technological structure of US metropolitan areas in terms of the patent classes in which they are most active between 1975 and 2010. We find that knowledge complexity is unevenly distributed across the United States and that cities with the most complex technological structures are not necessarily those with the highest rates of patenting. Citation data indicate that more complex patents are less likely to be cited than less complex patents when citing and cited patents are located in different metropolitan areas.

The formation of economic networks: a proximity approach

The notion of proximity is increasing in popularity in economic and geographic literature, and is now commonly used by scholars in regional science and spatial economics. Few academic works, however, have explored the link between regional development and proximity relations. This comprehensive book redresses the balance with its assessment of the role of, and obstacles caused by, proximity relations in regional development processes.

Smart specialization policy in the European Union: relatedness, knowledge complexity and regional diversification

ABSTRACT The operationalization of smart specialization policy has been rather limited because a coherent set of analytical tools to guide the policy directives remains elusive. We propose a policy framework around the concepts of relatedness and knowledge complexity. We show that diversifying into more complex technologies is attractive but difficult for European Union regions to accomplish. Regions can overcome this diversification dilemma by developing new complex technologies that build on local related capabilities. We use these findings to construct a policy framework for smart specialization that highlights the potential risks and rewards for regions of adopting competing diversification strategies.

Unveiling the geography of historical patents in the United States from 1836 to 1975

It is clear that technology is a key driver of economic growth. Much less clear is where new technologies are produced and how the geography of U.S. invention has changed over the last two hundred years. Patent data report the geography, history, and technological characteristics of invention. However, those data have only recently become available in digital form and at the present time there exists no comprehensive dataset on the geography of knowledge production in the United States prior to 1975. The database presented in this paper unveils the geography of historical patents granted by the United States Patent and Trademark Office (USPTO) from 1836 to 1975. This historical dataset, HistPat, is constructed using digitalized records of original patent documents that are publicly available. We describe a methodological procedure that allows recovery of geographical information on patents from the digital records. HistPat can be used in different disciplines ranging from geography, economics, history, network science, and science and technology studies. Additionally, it is easily merged with post-1975 USPTO digital patent data to extend it until today.

The Principle of Relatedness

The idea that skills, technology, and knowledge, are spatially concentrated, has a long academic tradition. Yet, only recently this hypothesis has been empirically formalized and corroborated at multiple spatial scales, for different economic activities, and for a diversity of institutional regimes. The new synthesis is an empirical principle describing the probability that a region enters - or exits - an economic activity as a function of the number of related activities pre- sent in that location. In this paper we summarize some of the recent empirical evidence that has generalized the principle of relatedness to a fact describing the entry and exit of products, industries, occupations, and technologies, at the national, regional, and metropolitan scales. We conclude by describing some of the policy implications and future avenues of research implied by this robust empirical principle.

Relatedness and the geography of innovation

Scholars and policy makers consider knowledge accumulation a major driver of growth and regional development. During the past two decades, the geography of innovation literature has provided a rich and detailed account of the underlying processes of regional knowledge production. More recently, a growing body of empirical literature has analysed the specific knowledge bases of regions and their evolution over time. The aim of these studies is not to explain why some regions produce more knowledge outputs than others, but why some regions produce a specific type of knowledge. The author refers to this body of literature as the relatedness literature. In the chapter the author discusses the theoretical foundations of this literature, its methodological framework and recent empirical findings. Based on evolutionary thinking, the spatial dynamics of knowledge are understood as a cumulative, path-dependent and interactive process. As a result, a main driving force is relatedness, as new knowledge is expected to branch out from related, pre-existing knowledge. Empirically, relatedness has mainly been formalized as a network, the knowledge space. In this network, nodes are knowledge categories, such as technological classes or scientific fields, and the links between these knowledge types indicate their degree of relatedness. The empirical analysis of relatedness and the knowledge space allows the mapping of regions’ knowledge bases, explaining scientific and technological change and identifying further opportunities for recombination and innovation. After having reviewed the empirics on knowledge space, the author discusses implications for research and innovation policy and suggests some avenues for future research.