Previous research indicates that firm innovativeness can either be determined by a firm’s position within the network dimension or by its position within the geographical dimension. Integrative studies addressing both distinct and combined proximity effects remains rare (cf. Whittington et al. 2009). Thus, we address in this Chapter the following research question: Are firm-level innovation outcomes positively or negatively related to network positioning effects, geographical co-location effects or combined proximity effects; and if the latter case is true, are the combined effects substitutional or complementary in nature? Panel data count models with fixed and random effects were used to analyze a firm’s innovative performance as measured by patent application counts. This last empirical analysis is organized as follows: We start with a short introduction in Sect. 12.1. Next, we provide a brief discussion of theoretical background in Sect. 12.2. In Sect. 12.3 we introduce our conceptual framework and derive our hypotheses. In Sect. 12.4 we introduce the data and methods used. Next, we outline the estimation strategy and report our empirical results in Sect. 12.5. Finally, we discuss our findings and conclude with a number of critical remarks in Sect. 12.6.

This paper contributes to the discussion on the importance of physical distance in the emergence of cross-region collaborative Research and Development (R&D) interactions. The proximity theory, and its extensions, is used as a theoretical framework. A spatial interaction model for count data was implemented for the empirical analysis of German data from the period from 2005 to 2010. The results show that all tested proximity measurements (geographical, cognitive, social and institutional proximity) have a significant positive influence on collaboration intensity. The proximity paradox, however, cannot be confirmed for geographical, social and institutional proximity, but for cognitive proximity.

Academic startups are thought to locate in their parent university’s home region because geographic proximity to a university facilitates access to academic knowledge and resources. In this paper we analyze the importance of a different channel, namely social ties between academic entrepreneurs and university researchers, for the access to academic knowledge and resources, and therefore for the location of the startups. We employ unique data on academic startups from regions with more than one university and find that only the parent university influences academic entrepreneurs’ decisions to stay in the region while other universities in the same region play no role. Our findings suggest that geographic proximity to a university may not per se guarantee access to knowledge and resources; social contacts are additionally required. The importance of social ties implies that academic knowledge and resources are not necessarily local public goods. This holds implications for universities’ role in stimulating regional development.

Our primary goal is to analyse the drivers of evolutionary network change processes by using a stochastic actor-based simulation approach. We contribute to the literature by combining two unique datasets, concerning the German laser and automotive industry, between 2002 and 2006 to explore whether geographical, network-related, and techno-logical determinants affect the evolution of networks, and if so, as to what extent these determinants systematically differ for science-driven industries compared to scale-intensive industries. Our results provide empirical evidence for the explanatory power of network-related determinants in both industries. The ‘experience effect’ as well as the ‘transitivity effects’ are significant for both industries but more pronounced for laser manufacturing firms. When it comes to ‘geographical effects’ and ‘technological ef-fects’ the picture changes considerably. While geographical proximity plays an important role in the automotive industry, firms in the laser industry seem to be less dependent on geographical closeness to cooperation partners; instead they rather search out for cooperation opportunities in distance. This might reflect the strong dependence of firms in science-driven industries to access diverse external knowledge, which cannot necessarily be found in the close geographical surrounding. Technological proximity negatively influences cooperation decisions for laser source manufacturers, yet has no impact for automotive firms. In other words, technological heterogeneity seems to ex-plain, at least in science-driven industries, the attractiveness of potential cooperation partners.

Nähe und Übertragung von akademischem Wissen: Belege aus dem räumlichen Muster der Kooperation zwischen ostdeutschen Professoren und der Industrie, Regional Studies. Universitäten können die ökonomische Entwicklung von Regionen stimulieren, insbesondere durch Kooperation mit der lokalen Industrie. Die vorliegende Studie analysiert, wann solche Kooperationen lokal stattfinden. Die existierende Literatur deutet daraufhin, dass aufgrund von tacidem Wissen und der Bedeutung geographischer Nähe Kooperationen überwiegend lokal stattfinden. Die vorliegende Studie findet Evidenz, dass das räumliche Muster von Kooperationen zwischen Universitäten und der Industrie als Resultat eines komplexen Matching-Prozesses zwischen Partnern mit geeigneten Charakteristika betrachtet werden kann. Die Ergebnisse deuten darauf hin, dass individuelle, relationale sowie institutionelle Charakteristika der Akteure eine wichtige Rolle für die Partnerwahl spielen. Demnach sind lokale Kooperationen nicht zwingend.

The paper accounts for the determinants of inward foreign direct investment in business services across the EU-27 regions. Together with the traditional variables considered in the literature (market size, market quality, agglomeration economies, labour cost, technology, human capital), we focus on the role of forward linkages with manufacturing sectors and other service sectors as

attractors of business services FDI at the regional level. This hypothesis is based on the evidence that the growth of business services is mostly due to increasing intermediate demand by other services industries and by manufacturing industries and on the importance of geographical proximity for forward linkages in services.

To our knowledge, there are no studies investigating the role of forward linkages for the location of FDI. This paper aims therefore to fill this gap and add to the FDI literature by providing a picture of the specificities of the determinants of FDI in business services at the regional level. The empirical analysis draws upon the database fDi Markets, from which we selected projects having as a destination NUTS 2 European regions in the sectors of Business services over the period 2003-2008. Data on FDI have been matched with data drawn from the Eurostat Regio

database. Forward linkages have been constructed using the OECD Input/Output database. By estimating a negative binomial model, we find that regions specialised in those (manufacturing) sectors that are high potential users of business services attract more FDI than other regions. This confirms the role of forward linkages for the localisation of business service FDI, particularly in the case of manufacturing.

Using a large dataset of 406 subsidized R&D cooperation projects, we provide detailed insights into the relationship between project characteristics and innovation output. Patent applications and publications are used as measures for the innovation output of an R&D project. We find that large-firm involvement is strongly positively related with the number of patent applications, but not with the number of publications. Conversely, university involvement has positive effects on projects’ innovation output in terms of the number of publications but not in terms of patent applications. In general, projects’ funding as measure of projects’ size is an important predictor of the innovation output of R&D cooperation projects. No significant effects are found for the number of partners as (an alternative) measure of projects’ size, for spatial proximity between cooperation partners, for the involvement of a public institute for applied research, and for prior cooperation experiences. We derive conclusions for the design of R&D cooperation support schemes.

This article analyses how regional employment growth in Germany is affected by related variety, unrelated variety and the functions a region performs in the production process. Following the related variety literature, we argue that regions benefit from the existence of related activities that facilitate economic development. However, we argue that the sole reliance of related variety on standard industrial classifications remains debatable. Hence, we offer estimations for establishing that conceptual progress can indeed be made when a focus for analysis goes beyond solely considering industries. We develop an industry-function based approach of related and unrelated variety. Our findings suggest that related variety only in combination with a high functional specialization of the region facilitates regional growth in Germany. Additionally, also unrelated variety per se fails to wield influences affecting development of regions. It is rather unrelated, but functionally proximate variety in the groups “White Collar” and “Blue Collar Workers” positively affects regional employment growth.

The focus of this article is the empirical identification of factors influencing Foreign Direct Investment (FDI) in transition economies on a regional level (NUTS 2). The analysis is designed as benchmark between three neighboring post-communist regions, i.e. East Germany, the Czech Republic and Poland. Their different transition paths have not only resulted in economic differences. We can also observe today that the importance of pull factors for FDI varies significantly across the regions. This analysis shows that in comparison with Poland and the Czech Republic, East Germany’s major benefit is its purchasing power, its geographical proximity to West European markets, and its modern infrastructure. Furthermore, the analysis suggests that intra-industry linkages such as specialization and agglomeration economies are relevant factors for the location decision of foreign investors. This result can help to explain the regional divergence of FDI streams in transition economies.

Most finance–growth studies approximate the size of financial systems rather than the quality of intermediation to explain economic growth differentials. Furthermore, the neglect of systematic differences in cross-country studies could drive the result that finance matters. We suggest a measure of bank’s intermediation quality using bank-specific efficiency estimates and focus on the regions of one economy only: Germany. This quality measure has a significantly positive effect on growth. This result is robust to the exclusion of banks operating in multiple regions, controlling for the proximity of financial markets, when distinguishing different banking sectors active in Germany, and when excluding the structurally weaker East from the sample.