The evolution of innovation networks : the case of a German automotive network

In this paper we outline a conceptual framework for depicting network development patterns of interfirm innovation networks and for analyzing the dynamic evolution of an R&D network in the German automotive industry. We test the drivers of evolutionary change processes of a network which is based on subsidised R&D projects in the 10 year period between 1998 and 2007. For this purpose a stochastic actor-based model is applied to estimate the impact of various drivers of network change. We test hypotheses in the innovation and evolutionary economics framework and show that structural positions of firms as well as actor covariates and dyadic covariates are influential determinants of network evolution

The evolution of innovation networks : an automotive case study

Competitive pressure forces firms to continuously develop new ideas, invent new technologies and bring new products to the market in order to survive the destructive part of Schumpeterian innovation competition. This holds particularly for the automotive industry in Germany, challenged by firms from emerging markets which are able to offer their products for lower prices. In the competition for new technological solutions, competences and cutting-edge knowledge are success factors. New knowledge stimulates the emergence of new ideas that can be transformed into innovation. Such knowledge can partly be generated internally in the companies R&D laboratories. However, relying on internal knowledge generation is no longer sufficient. Participation in innovation networks which allow for access to external knowledge, and applying innovation cooperation as a strategic tool to acquire necessary knowledge which cannot be developed in-house opens up rich opportunities to complement and recombine the own knowledge-base. Thus, knowledge becomes the most important source of competitive advantage. In this dissertation, I analyze the drivers of innovation networks evolution among a sample of German automotive firms.Innovationsnetzwerke dienen im innovationsökonomischen Kontext dazu, komplexe Innovationsprozesse durchzuführen, besser mit technologischer Unsicherheit umzugehen und Gelegenheiten zu gegenseitigem Lernen und Austausch von Wissen zu schaffen (Pyka, 2002). Im Rahmen meines Dissertationsprojektes untersuche ich die zeitliche strukturelle Entwicklung eines Innovationsnetzwerks in der deutschen Automobilindustrie. Im Mittelpunkt stehen dabei die treibenden Faktoren der Netzwerkstrukturveränderung. Das untersuchte Netzwerk basiert auf der Teilnahme von Unternehmen an kollaborativen Forschungsprojekten (Verbundforschung), welche aus Bundesmitteln gefördert werden. Dabei untersuche ich die Relevanz der Akteurseigenschaften (auf individueller und dyadischer Ebene), wie auch eines endogenen Faktors als Determinanten für die Wahrscheinlichkeit eine Kooperation einzugehen. Die in diesem Zusammenhang aus theoretischen Überlegungen abgeleiteten Hypothesen werden mit Hilfe des sogenannten stochastic actor-based model for network dynamics (Snijders, 1996; Snijders, 2001) getestet. Die empirischen Ergebnisse deutschen darauf hin, dass wissensbezogene Faktoren (Absorptionsfähigkeit, technologische Distanz und Modularität der Wissensbasis) wichtige Determinanten der Netzwerkentwicklung sind. Darüber hinaus zeigt sich, dass Transitivität ein endogener hoch signifikanter Faktor ist. Zudem spielt die Kooperationserfahrung wie auch die geographische Distanz eine Rolle. Dagegen haben die Firmengröße wie auch die Industrieerfahrung keinen signifikanten Einfluss auf der Wahrscheinlichkeit einer Teilnahme an einem Verbundforschungsprojekt

Simulating knowledge diffusion in four structurally distinct networks : an agent-based simulation model

In our work we adopt a structural perspective and apply an agent-based simulation approach to analyse knowledge diffusion processes in four structurally distinct networks. The aim of this paper is to gain an in-depth understanding of how network characteristics, such as path length, cliquishness and the distribution and asymmetry of degree centrality affect the knowledge distribution properties of the system. Our results show in line with the results of Cowan and Jonard (2007) that an asymmetric or skewed degree distribution actually can have a negative impact on a networks knowledge diffusion performance in case of a barter trade knowledge diffusion process. Their key argument is that stars rapidly acquire so much knowledge that they interrupt the trading process at an early stage, which finally disconnects the network. However, our findings reveal that stars cannot be the sole explanation for negative effects on the diffusion properties of a network. In contrast, interestingly and quite surprisingly, our simulation results led to the conclusion that in particular very small, inadequately embedded agents can be a bottleneck for the efficient diffusion of knowledge throughout the networks

The co-evolution of innovation networks : collaboration between West and East Germany from 1972 to 2014

This paper describes the co-evolution of East and West German innovation networks after the German reunification in 1990 by analyzing publication data from 1972 to 2014. This study uses the following four benchmark models to interpret and classify German innovation networks: the random graph model, the small-world model, the BarabásiAlbert model, and the evolutionary model. By comparing the network characteristics of empirical networks with the characteristics of these four benchmark models, we can increase our understanding of the particularities of German innovation networks, such as development over time as well as structural changes (i.e., new nodes or increasing/decreasing network density). We first confirm that a structural change in EastWest networks occurred in the early 2000s in terms of the number of link between the two. Second, we show that regions with few collaborators dominated the properties of German innovation networks. Lastly, the change in network cliquishness, which reflects the tendency to build cohesive subgroups, and path length, which is a strong indicator of the speed of knowledge transfer in a network, compared with the four benchmark models show that East and West German regions tended to connect to new regions located in their surroundings, instead of entering distant regions. Our findings support the German federal governments continuous efforts to build networks between East and West German regions

Proposal for Quantum Simulation via All-Optically Generated Tensor Network States

We devise an all-optical scheme for the generation of entangled multimode photonic states encoded in temporal modes of light. The scheme employs a nonlinear down-conversion process in an optical loop to generate one- and higher-dimensional tensor network states of light. We illustrate the principle with the generation of two different classes of entangled tensor network states and report on a variational algorithm to simulate the ground-state physics of many-body systems. We demonstrate that state-of-the-art optical devices are capable of determining the ground-state properties of the spin-1/2 Heisenberg model. Finally, implementations of the scheme are demonstrated to be robust against realistic losses and mode mismatch.Comment: 6 pages main text plus 6 pages Supplementary Material and many figures. Updated to published version. Comments welcom

Technikinnovationen für die Energiewende verantwortungsvoll gestalten: Ein Leitfaden zur Anwendung des Konzepts der Responsible Research and Innovation

Der Leitfaden stellt heraus, wie bereits in Forschung, Technologieentwicklung und Innovation (FTI) der Versuch unternommen werden kann, einen Beitrag zu günstigen Voraussetzungen für gesellschaftliche Wünschbarkeit und Akzeptanzfähigkeit von Technologien für die Energiewende zu leisten. Er präsentiert ein Indikatoriksystem, das auf dem Leitbild einer verantwortungsvollen Gestaltung von FTI aufbaut, auf Energiewendetechnologien (und andere FTI-Bereiche) angewendet werden kann und als Webapplikation für eine verantwortungsvolle FTI-Gestaltung zur Verfügung steht. Er richtet sich an Akteure, die mit der Durchführung oder Förderung von FTI im Bereich Energiewendetechnologien befasst sind

Towards Intense Ultra-Broadband High Repetition Rate Terahertz Sources Based on Organic Crystals [Invited]

Increasing the average power of broadband, few-cycle terahertz (THz) sources is currently a topic of intense investigation, fueled by recent immense progress in high average power femtosecond laser driving sources at 1030 nm. However, many crucial applications would benefit not only from an increase in average power, but also from ultra-broad bandwidth, while maintaining high dynamic range at these frequencies. This calls for the challenging combination of high repetition rates and high average power simultaneously. Here, we discuss the recent progress in the promising approach enabled by organic crystals for THz-generation. Specifically, this review article discusses advances with the most commonly used organic crystals BNA, DAST, DSTMS, OH1 and HMQ-TMS. We place special emphasis on nonlinear and thermal properties and discuss future directions for this field