Identifying Cooperation for Innovation – A Comparison of Data Sources
Michael Fritsch, Matthias Piontek, Mirko Titze
Abstract
The value of social network analysis is critically dependent on the comprehensive and reliable identification of actors and their relationships. We compare regional knowledge networks based on different types of data sources, namely, co-patents, co-publications, and publicly subsidised collaborative Research and Development projects. Moreover, by combining these three data sources, we construct a multilayer network that provides a comprehensive picture of intraregional interactions. By comparing the networks based on the data sources, we address the problems of coverage and selection bias. We observe that using only one data source leads to a severe underestimation of regional knowledge interactions, especially those of private sector firms and independent researchers. The key role of universities that connect many regional actors is identified in all three types of data.
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Differences Make a Difference: Diversity in Social Learning and Value Creation
Yiwei Fang, Bill Francis, Iftekhar Hasan
Journal of Corporate Finance,
Vol. 48,
2018
Abstract
Prior research has demonstrated that CEOs learn privileged information from their social connections. Going beyond the importance of the number of social ties in a CEO's social network, this paper studies the value generated from a diverse social environment. We construct an index of social-network heterogeneity (SNH) that captures the extent to which CEOs are connected to people of different demographic attributes and skill sets. We find that higher CEO SNH leads to greater firm value through the channels of better corporate innovation and diversified M&As. Overall, the evidence suggests that CEOs' exposure to human diversity enhances social learning and creates greater growth opportunities for firms.
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Criminal Network Formation and Optimal Detection Policy: The Role of Cascade of Detection
Liuchun Deng, Yufeng Sun
Journal of Economic Behavior and Organization,
Vol. 141 (September),
2017
Abstract
This paper investigates the effect of cascade of detection, how detection of a criminal triggers detection of his network neighbors, on criminal network formation. We develop a model in which criminals choose both links and actions. We show that the degree of cascade of detection plays an important role in shaping equilibrium criminal networks. Surprisingly, greater cascade of detection could reduce ex ante social welfare. In particular, we prove that full cascade of detection yields a weakly denser criminal network than that under partial cascade of detection. We further characterize the optimal allocation of the detection resource and demonstrate that it should be highly asymmetric among ex ante identical agents.
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Does Social Capital Matter in Corporate Decisions? Evidence from Corporate Tax Avoidance
Iftekhar Hasan, Chun-Keung (Stan) Hoi, Qiang Wu, Hao Zhang
Journal of Accounting Research,
Vol. 55 (3),
2017
Abstract
We investigate whether the levels of social capital in U.S. counties, as captured by strength of civic norms and density of social networks in the counties, are systematically related to tax avoidance activities of corporations with headquarters located in the counties. We find strong negative associations between social capital and corporate tax avoidance, as captured by effective tax rates and book-tax differences. These results are incremental to the effects of local religiosity and firm culture toward socially irresponsible activities. They are robust to using organ donation as an alternative social capital proxy and fixed effect regressions. They extend to aggressive tax avoidance practices. Additionally, we provide corroborating evidence using firms with headquarters relocation that changes the exposure to social capital. We conclude that social capital surrounding corporate headquarters provides environmental influences constraining corporate tax avoidance.
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Transferability of Skills across Sectors and Heterogeneous Displacement Costs
Moises Yi, Steffen Müller, Jens Stegmaier
American Economic Review: Papers and Proceedings,
Vol. 107 (5),
2017
Abstract
We use rich German administrative data to estimate new measures of skill transferability between manufacturing and other sectors. These measures capture the value of workers' human capital when applied in different sectors and are directly related to workers' displacement costs. We estimate these transferability measures using a selection correction model, which addresses workers' endogenous mobility, and a novel selection instrument based on the social network of workers. Our results indicate substantial heterogeneity in how workers can transfer their skills when they move across sectors, which implies heterogeneous displacement costs that depend on the sector to which workers reallocate.
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The Structure and Evolution of Inter-sectoral Technological Complementarity in R&D in Germany from 1990 to 2011
T. Broekel, Matthias Brachert
Journal of Evolutionary Economics,
Vol. 25 (4),
2015
Abstract
Technological complementarity is argued to be a crucial element for effective R&D collaboration. The real structure is, however, still largely unknown. Based on the argument that organizations’ knowledge resources must fit for enabling collective learning and innovation, we use the co-occurrence of firms in collaborative R&D projects in Germany to assess inter-sectoral technological complementarity between 129 sectors. The results are mapped as complementarity space for the Germany economy. The space and its dynamics from 1990 to 2011 are analyzed by means of social network analysis. The results illustrate sectors being complements both from a dyadic and portfolio/network perspective. This latter is important, as complementarities may only become fully effective when integrated in a complete set of different knowledge resources from multiple sectors. The dynamic perspective moreover reveals the shifting demand for knowledge resources among sectors at different time periods.
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The Role of Multinational Enterprises in the Transition Process of Central and Eastern European Economies
Philipp Marek
PhD Thesis, University of Groningen,
2015
Abstract
The collapse of the communist system has initiated the transformation of Central and Eastern European (CEE) countries from a social-planned towards a market economy. The institutional transition, structural change and privatization process evolved at a different extent across CEE countries. The former satellite states implemented a rapid transformation of the economic system and joined the European Union (EU), whereas the countries of the Commonwealth of Independent States (CIS) faced severe difficulties in adapting their system to the new environment. Due to the lack of capital and knowledge, foreign direct investment (FDI) has played a crucial role in the process of technological renewal and economic development. This thesis consists of two research objectives; the location decision of multinational enterprises (MNE) in CEE regions and the impact of FDI in host economies. This thesis is based on firm level information and takes three theoretical frameworks on FDI into account: International Economics, Regional Economics and International Business. Taking the different transition paths of CEE countries into account, the findings suggest that the regional distribution of FDI differs across sectors and is affected by agglomeration economies and by the access to locally bounded inputs. Therefore, FDI amplifies the concentration of economic activities. The investigation of FDI spillovers provides evidence that FDI contributes to the competitiveness of domestic firms in CEE economies. Notwithstanding, the results show that local firms only benefit from FDI if foreign affiliates are sufficiently embedded in the host economy and global production networks.
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The Structure and Evolution of Intersectoral Technological Complementarity in R&D in Germany from 1990 to 2011
Matthias Brachert, T. Broekel
Abstract
Technological complementarity is argued to be a crucial element for effective Research and Development (R&D) collaboration. The real structure is, however, still largely unknown. Based on the argument that organizations’ knowledge resources must fit for enabling collective learning and innovation, we use the co-occurrence of firms in collaborative R&D projects in Germany to assess inter-sectoral technological complementarity between 129 sectors. The results are mapped as complementarity space for the Germany economy. The space and its dynamics from 1990 to 2011 are analyzed by means of social network analysis.
The results illustrate sectors being complements both from a dyadic and portfolio/ network perspective. This latter is important, as complementarities may only become fully effective when integrated in a complete set of different knowledge resources from multiple sectors. The dynamic perspective moreover reveals the shifting demand for knowledge resources among sectors at different time periods.
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Social Capital and Migration Preferences - An Empirical Analysis for the Case of the Reunified Germany
Peter Bönisch, Lutz Schneider, Walter Hyll
Grincoh Working Papers July 2013,
2013
Abstract
We focus on the relevance of different types of social capital on migration intentions in the context of shrinking regions. On the one hand, formal social capital characterised by weak ties without local roots is supposed to drive selectivity and outmigration. On the other hand, informal social capital stressing strong ties to friends, relatives or neighbours might hinder migration. In our regression results we do not find an effect of shrinking regions on mobility intentions. Thus, living in a shrinking area is by itself not a reason to move away or to invest less in social capital. However, if an individual considers to move away she reduces her participation in informal and formal networks. Individuals characterised by strong informal ties, i.e. strong relationships to friends, relatives or neighbours show a significantly lower probability of moving away. And, more qualified types of social capital as participation in local politics or initiatives seem to encourage spatial mobility.
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Analyzing Innovation Drivers in the German Laser Industry: the Role of Positioning in the Social and Geographical Space
Muhamed Kudic, Peter Bönisch, Iciar Dominguez Lacasa
Abstract
Empirical and theoretical contributions provide strong evidence that firm-level performance outcomes in terms of innovativeness can either be determined by the firm’s position in the social space (network effects) or by the firm’s position in the geographical space (co-location effects). Even though we can observe quite recently first attempts in bringing together these traditionally distinct research streams (Whittington et al. 2009), research on interdependent network and geographical co-location effects is still rare. Consequently, we seek to answer the following research question: considering that the effects of social and geographic proximity on firm’s innovativeness can be interdependent, what are the distinct and combined effects of firm’s network and geographic position on firm-level innovation output? We analyze the innovative performance of German laser source manufacturers between 1995 and 2007. We use an official database on publicly funded R&D collaboration projects in order to construct yearly networks and analyze firm’s network positions. Based on information on population entries and exits we calculate various types of geographical proximity measures between private sector and public research organizations (PRO). We use patent grants as dependent variable in order to measure firm-level innovation output. Empirical results provide evidence for distinct effect of network degree centrality. Distinct effect of firm’s geographical co-location to laser-related public research organization promotes patenting activity. Results on combined network and co-location effects confirms partially the existence of in-terdependent proximity effects, even though a closer look at these effects reveals some ambiguous but quite interesting findings.
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