Networks & Proximities

The relationship of policy induced R&D networks and inter-regional knowledge diffusion

Bednarz, M. & Broekel, T. (2019), The relationship of policy induced R&D networks and inter-regional knowledge diffusion, Journal of Evolutionary Economics, https://doi.org/10.1007/s00191-019-00621-2 (pdf).

 

Knowledge diffusion is argued to be strongly influenced by knowledge networks and spatial structures. However, empirical studies primarily apply an indirect approach in measuring their impact. Moreover, little is known about how policy can influence the spatial diffusion of knowledge. This paper seeks to fill this gap by testing empirically the effects of policy induced knowledge networks on the propensity of inter-regional patent citations. We use patent citation data for 141 labor market regions in Germany between 2000 to 2009, which is merged with information on subsidized joint R&D projects. Based on the latter, we construct a network of subsidized R&D collaboration. Its impact on inter-regional patent citations is evaluated with binomial and negative binomial regression models. Our findings do not indicate that inter-regional network links created by public R&D subsidies facilitate patent citations and, hence, inter-regional knowledge diffusion.

Disentangling link formation and dissolution in spatial networks: An application of a two-mode STERGM to a project-based R&D network in the German biotechnology industry

Broekel, T. & Bednarz, M. (2019), Disentangling link formation and dissolution in spatial networks: An application of a two-mode STERGM to a project-based R&D network in the German biotechnology industry, Networks and Spatial Economics, https://doi.org/10.1007/s11067-018-9430-1 (pdf).

 

The analysis of spatial networks’ evolution has predominantly concentrated on the formation process of links. However, the evolution of networks is similarly shaped by the dissolution of links, which has thus far received considerably less attention. The paper presents separable temporal exponential random graph models (STERGMs) as a promising method in this context, which allows for the disentangling of both processes. Moreover, the applicability of the method to two-mode network data is demonstrated. We illustrate the use of these models for the R&D collaboration network of the German biotechnology industry as well as for testing for the relevance of different forms of proximities for its evolution. The results reveal proximities varying in their relative importance for link formation and link dissolution.

Critical links in knowledge networks – What about proximities and gatekeeper organisations?

Broekel, T. and Mueller, W. (2018), Critical links in knowledge networks – What about proximities and gatekeeper organisations? Industry & Innovation, 25(10):919-939 (pdf).

 

The paper analyses links in knowledge networks that are essential for the integration and knowledge diffusion properties of the entire network. By focusing on critical links, as defined in network science, we evaluate these links’ properties from the perspective of the proximity and regional gatekeeper literature. We thereby gain insights into likely conditions of their emergence and functions. Moreover, we extend the dyadic perspective on regional gatekeeper organisations and link it more strongly to the network science and proximity framework literature. An empirical study applies these arguments and investigates the proximity characteristics of critical links in 132 technology-specific subsidised knowledge networks in Germany. The results show that critical links tend be formed between regional gatekeepers that offer related knowledge resources. The links bridge institutional distances by utilising the benefits of geographic and social proximity.

The role of universities in a network of subsidized R&D collaboration: The case of the biotechnology-industry in Germany

Roesler, C. and Broekel, T. (2017), The role of universities in a network of subsidized R&D collaboration: The case of the biotechnology-industry in Germany, Review of Regional Research, 37(2):135-160 (pdf).

 

This paper contributes to the growing literature on knowledge network evolution. It provides an analysis of the role universities play in a network emerging from the joint participation of organizations in R&D projects subsidized by pub- lic authorities. In addition to theorizing universities’ effect on network formation processes, the paper includes an empirical study identifying the main drivers be- hind the formation of the subsidized network of R&D collaboration in the German biotechnology industry. We find that universities strongly shape the evolution of the network in the period 2007–2010. They are clearly central knowledge sources and dominate the network as partners in many R&D projects. While knowledge links among universities are an essential part of the network, universities are also able to connect local firms to inter-regional knowledge networks. Accordingly, subsidies for joint R&D support universities in acting as regional gatekeepers and thereby facilitate local and inter- regional knowledge diffusion.

Institutional Change and Network Evolution: Explorative and Exploitative Tie Formations of Co-Inventors During the Dot-com Bubble in the Research Triangle Region

Menzel, M-P and Feldman and Broekel, T. (2017), Institutional Change and Network Evolution: Explorative and Exploitative Tie Formations of Co-Inventors During the Dot-com Bubble in the Research Triangle Region, Regional Studies, 51(8):1179-1191 (pdf).

 

We investigate how institutions impact tie formation. In doing so, we describe Venture Capital as institution that can direct firm strategies towards exploration or exploitation. These strategies are translated into tie formations: explorative tie formation produces structural holes as a source of “good ideas”, exploitative tie formation closes structural holes to facilitate the mobilization of resources to put ideas into products. Using the example of co-inventors in ICT in the Research Triangle Park during the dot-com bubble, we expected explorative tie formation during the bubble and exploitative tie formations after its burst. Stochastic Actor Oriented Models did not clearly support our assumptions. We found that the emergence of venture capital lead to a large variance in connection patterns during the bubble, probably resulting from overlapping institutional effects. After the burst of the bubble, these incoherencies disappeared.

Network structures in Regional Innovation Systems

Stuck, J., Broekel, T., Revilla Diez, J. (2016), Network structures in Regional Innovation Systems, European Planning Studies, 24(3): 423-442 (pdf).

 

While interactive learning and inter-organizational relations are the fundamental building blocks in regional innovation system (RIS) theory, the framework is rarely related to investigations of regional knowledge network structures, because in RIS literature relational structures and interaction networks are discussed in a rather fuzzy and generic manner, with the “network term” often being used rather metaphorically. This paper contributes to the literature by discussing theoretical arguments about interactions and knowledge exchange relations in the RIS literature from the perspective of social network analysis. More precise, it links network- theoretical concepts and insights to the well-known classification of RIS types by Cooke (2004). We thereby exemplarily show how the RIS literature and the literature on regional knowledge networks can benefit from considering insights of the respective other.

The co-evolution of proximities – a network level study

Broekel, T. (2015), The co-evolution of proximities – a network level study. Regional Studies, 49(6):921-935 (pdf).

 

Little is known about how network structures and proximity relations between linked actors evolve over time. This paper argues that a number of networks’ internal proximity structures are interrelated, which may give rise to specific types of co-evolution dynamics. An empirical investigation tests these arguments using information on the evolution of 280 networks of subsidized research and development (R&D) collaboration in Germany. The empirical findings clearly confirm the existence of systematic and dynamic interrelatedness between proximities. In this way, the paper underlines the need to consider such relations when investigating the evolution of knowledge networks.

Modeling knowledge networks in economic geography: A discussion of four empirical strategies

Broekel, T. and Balland, P.-A. and Burger, M. and van Oort, F. (2014), Modeling knowledge networks in economic geography: A discussion of four empirical strategies. Annals of Regional Science, 53(2): 423-452, DOI:10.1007/s00168-014-0616-2 (pdf).

 

The importance of network structures for the transmission of knowledge and the diffusion of technological change has been recently emphasized in economic geography. Since network structures drive the innovative and economic performance of actors in regional contexts, it is crucial to explain how networks form and evolve over time and how they facilitate inter-organizational learning and knowledge transfer. The analysis of relational dependent variables, however, requires specific statistical proce- dures. In this paper, we discuss four different models that have been used in economic geography to explain the spatial context of network structures and their dynamics. First, we review gravity models and their recent extensions and modifications to deal with the specific characteristics of networked (individual level) relations. Second, we discuss the quadratic assignment procedure that has been developed in mathemati- cal sociology for diminishing the bias induced by network dependencies. Third, we present exponential random graph models that not only allow dependence between observations, but also model such network dependencies explicitly. Finally, we deal with dynamic networks, by introducing stochastic actor-oriented models. Strengths and weaknesses of the different approach are discussed together with domains of applicability the geography of innovation studies.

Explaining the structure of inter-organizational networks using exponential random graph models

Broekel, T. and Hartog, M. (2013), Explaining the structure of inter-organizational networks using exponential random graph models Industry and Innovation, 20(3):277-295 (pdf).

 

A key question raised in recent years is what factors determine the structure of inter- organizational networks. Most research so far has focused on different forms of proximity between organizations, namely geographical, cognitive, social, institutional and organizational proximity, which are all factors at the dyad level. However, recently, factors at the node and structural network levels have been highlighted as well. To identify the relative importance of factors at these three different levels for the structure of inter-organizational networks that are observable at only one point in time, we propose the use of exponential random graph models. Their usefulness is exemplified by an analysis of the structure of the knowledge network in the Dutch aviation industry in 2008, for which we find factors at all different levels to matter. Out of different forms of proximity, only institutional and geographical proximity remains significant once we account for factors at the node and structural levels.

What drives patent performance of German biotech firms? The impact of R&D subsidies, knowledge networks and their location.

Fornahl, D. and Broekel, T. and Boschma, R. (2011), What drives patent performance of German biotech firms? The impact of R&D subsidies, knowledge networks and their location. Papers in Regional Science, 90(2): 395-418 (pdf).

 

This paper aims at explaining whether R&D subsidies, the engagement in collabo- ration networks and the location influence the patent activities of biotech firms in Germany! We demonstrate that R&D subsidies focusing on single firms do not increase patent intensity, while subsidies which are granted to joint R&D projects do so to a certain extent. The number of knowledge links firms have is not influencing performance, but the type of network partners has an effect. We found strong evidence that some but not too much cognitive distance between collaboration partners and being located in a cluster have a positive effect.

Knowledge Networks in the Dutch Aviation Industry – The Proximity Paradox

Broekel, T. and Boschma, R. (2012), Knowledge Networks in the Dutch Aviation Industry – The Proximity Paradox. Journal of Economic Geography, 12 (2): 409-433 (pdf).

 

The importance of geographical proximity for interaction and knowledge sharing has been discussed extensively in recent years. There is increasing consensus that geographical proximity is just one out of many types of proximities that might be relevant. We argue that proximity may be a crucial driver for agents to connect and exchange knowledge, but too much proximity between agents on any of the dimensions might harm their innovative performance at the same time. In a study on knowledge networks in the Dutch aviation industry, we test this so-called proximity paradox empirically. We found evidence that the proximity paradox holds to a considerable degree. Our study clearly showed that cognitive, social, organizational and geographical proximity were crucial for explaining the knowledge network of the Dutch aviation industry. However, we found strong evidence that too much cognitive proximity lowered firms’ innovative performance, and organizational proximity did not have an effect.

Aviation, Space or Aerospace? Exploring the knowledge networks of two industries in the Netherlands

Broekel, T. and Boschma, R. (2011), Aviation, Space or Aerospace? Exploring the knowledge networks of two industries in the Netherlands. European Planning Studies, 19(7): 1205-1227 (pdf).

 

Little is known about the extent to which the structure of knowledge networks differs between industries and to what degree knowledge relations occur between actors in different industries. This paper presents a network study on the Dutch aviation and space industry. Both industries are often treated as similar and categorized as aerospace accordingly, although they show variations in their knowledge bases. Our study shows that the structure of the knowledge networks differs between the two industries, and few knowledge linkages have been established between the two. Our findings suggest that the gap between the two industries’ knowledge networks is more pronounced for market knowledge than for technological knowledge. Non-profit organizations do seem to bridge the knowledge networks of the two industries.