Browsing by Subject "Innovation network"

Now showing 1 - 8 of 8
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    Avoiding evolutionary inefficiencies in innovation networks
    (2011) Pyka, Andreas
    Innovation policy is in need for a rational which allows the design and evaluation of policy instruments. In economic policy traditionally the focus is on market failures and efficiency measures are used to decide whether policy should intervene and which instrument should be applied. In innovation policy this rational cannot meaningfully be applied because of the uncertain and open character of innovation processes. Uncertainty is not a market failure and cannot be repaired. Inevitably policy makers are subject to failure and their goals are to be considered as much more modest compared to the achievement of a social optimum. Instead of optimal innovation, the avoidance of evolutionary inefficiencies becomes the centrepiece of innovation policy making. Superimposed to the several sources of evolutionary inefficiencies are socalled network inefficiencies. Because of the widespread organisation of innovation in innovation networks, the network structures and dynamics give useful hints for innovation policy, where and when to intervene.
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    Distal embedding as a technology innovation network formation strategy
    (2012) Pyka, Andreas; Paredes-Frigolett, Harold
    Although the area of innovation economics dates back to the early twentieth century with the seminal contributions of Schumpeter (1911), it is only recently that governments have understood the role of a comprehensive approach towards public sector economics that puts innovation systems in the eye of public policy decision makers. Although well researched in academia in recent years, the role that innovation networks play in driving successful processes of innovation and entrepreneurship has been less understood by policy makers. Indeed, so far public policy makers have been concerned with the macro level of public policy in a way that has been rather ?disconnected? from the meso level of innovation networks. Not surprisingly, overall strategies for innovation network formation have not been on the radar screen of public policy. The academic community, on the other hand, has been devoting more attention to the study of innovation networks in an attempt to understand the role they play as a catalyst of innovation and entrepreneurship. By and large in the research community, the process of innovation network formation has been left rather unattended. Indeed, the question of how these networks are formed and what strategies can be developed to ignite processes of innovation network formation has been largely absent from the academic debate. In this article, we make a contribution in this area and present ?distal embedding" as one of three generic innovation network formation strategies. We also show why ?distal embedding'' is particularly well suited for emerging regions of innovation and entrepreneurship. Our contributions lie at the macro-meso interface and can shed light on public policy at the macro level aiming to have a direct impact at the meso level of innovation network formation.
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    Privatization of agricultural advisory services and innovation systems : the case of Brandenburg, Germany
    (2021) Knuth, Ulrike; Knierim, Andrea
    The European regulations on Rural Development of the last two decades brought Agricultural Advisory Systems back onto the political agenda. Along with the introduction of Cross Compliance (CC), Member states were obliged to review their Farm Advisory System or to build up new infrastructure. The importance of innovation generation, knowledge dissemination and on-going learning in rural areas has been emphasized, and Agricultural Advisory Systems are regarded one important partner. A further development over the last 30 years has been a wave of privatization of Agricultural Advisory Systems (AAS) in Europe due to the pressure of decreasing public budgets. This cumulative dissertation examines the dialectic of increased and changing demands on Farm Advisory Systems on the one hand and the effects of privatization on the other hand. Privatization of agricultural advisory services in European Member States has been a process for decades. Both within Europe and Germany, the German federal state of Brandenburg has an Agricultural Advisory System with a comparatively high level of privatization and commercialization. It was therefore selected as an excellent case to address the development and the impacts of privatization. The goal of this dissertation is to answer the following leading research questions i) What were the consequences of privatization specifically for the situation of advisors, their capacities and competences?, ii) What are the responsibilities of public authorities to steer a (privatized) advisory system and innovation networks within pluralistic Agricultural Knowledge and Innovations Systems (AKIS)?, iii) How was the EU’s obligation to establish Farm Advisory Systems (FAS) implemented and thus, how is advice on Cross Compliance with Farm Management Systems (FMS) as a policy-induced innovation implemented and adopted in Brandenburg and Germany?, iv) How successful are innovation networks as an instrument to fill the interaction gap of the AAS in Brandenburg?. This dissertation contributes to the empirical evidence on the functioning of AKIS and Advisory Systems and provides public authorities in Brandenburg with longitudinal information to be used for future farm advice- and innovation-related policies. The cumulative thesis builds on 4 articles published from 2013 till 2018. The articles analyze qualitatively and discuss the view of agricultural advisors and farmers through a series of semi-structured interviews, analyze applied Farm Management Tools and assess new cooperation forms like innovation networks. Chapter 2 describes the development of the situation of private farm advisors in Brandenburg over a longer period of more than 15 years, from before until complete commercialization of the service in 2000. It shows which topics advisors (can) address and which they cannot, which clients they work with and which they do not, and it provides data on their basic work situation. It also gives insights on their networking activities. The following chapter 3 provides recommendations for public authorities regarding their responsibilities in pluralistic AKIS in Europe, which can also be applied to Brandenburg. Chapter 4 provides an analysis of Cross Compliance advice to farmers with Farm Management Systems (FMS) as one public responsibility in AKIS. A special focus is pointed to farmers’ usage of FMS in Brandenburg and qualitative comparison of FMS in Germany. In chapter 5 the cooperation of various actors from science and practice in Brandenburg is examined using the example of the innovation network for climate change adaptation. Innovation networks can be considered as one important instrument to cope with the challenges of AKIS privatization in Brandenburg by filling the interaction gap. This chapter presents an analysis of collaboration success factors and shows how crucial repeated participation, appropriate information management, and inclusive as well as responsive network practices are. Chapter 6 discusses the results regarding the development of Brandenburg’s AKIS and its Agricultural Advisory System (AAS) during the period of complete privatization (2002 until 2017), in which the research of chapter 2 thru 5 was conducted. Chapter 7 gives an update of Brandenburg’s AKIS and advisory system development from 2017 on, when AKIS and advisory services returned on the political agenda, and new policies emerged, which support innovation networks and advisory services. Chapter 8 concludes policy and research recommendations.
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    Simulating knowledge diffusion in four structurally distinct networks : an agent-based simulation model
    (2015) Kudic, Muhamed; Mueller, Matthias; Bogner, Kristina; Buchmann, Tobias
    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 network’s 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.
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    The co-evolution of innovation networks : collaboration between West and East Germany from 1972 to 2014
    (2016) Mueller, Matthias; Buchmann, Tobias; Yi, Seung-Kyu; Jun, Bogang
    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 Barabási–Albert 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 East–West 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 government’s continuous efforts to build networks between East and West German regions.
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    The evolution of innovation networks : an automotive case study
    (2014) Buchmann, Tobias; Pyka, Andreas
    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.
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    Turkish-German innovation networks in the European research landscape
    (2013) Heller-Schuh, Barbara; Pyka, Andreas; Prostolupow, Irene
    Research networks are regarded as channels for knowledge creation and diffusion and are thus essential for the development and integration of economies. In this paper we have a look at the long Turkish-German-migration history which should offer opportunities for both countries to benefit from brain circulation, transnational entrepreneurs and research networks. The present paper examines the structure of research networks of the European Framework Programmes (FP) that are established by joint participation of organizations in research projects, in particular German research organizations with Turkish participants in FP5 to FP7 in the knowledge-intensive technology fields ICT, Biotechnology and Nanoscience. A better understanding of these networks allows for improving the design of research policies at national levels as well as at the EU level. The empirical examination of network properties reveals that the diverse networks show a range of similarities in the three technology fields in each FP such as the small-world properties. Moreover, our findings show that German actors play a specific role in most examined research networks with Turkish participation.
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    United we stand, divided we fall : essays on knowledge and its diffusion in innovation networks
    (2019) Bogner, Kristina; Pyka, Andreas
    Knowledge is a key resource, allowing firms to innovate and keep pace with national and international competitors. Therefore, the management of this resource within firms and innovation networks is of utmost importance. As the collection and generation of (new) knowledge gives such competitive advantage, there is a strong interest of firms and policy makers on how to foster the creation and diffusion of new knowledge. Within four studies, this doctoral thesis aims at extending the literature on knowledge diffusion performance by focussing on the effect of different network structures on diffusion performance as well as on knowledge types besides mere techno-economic knowledge. Study 1 analyses the effect of different structural disparities on knowledge diffusion by using an agent-based simulation model. It focuses on how different network structures influence knowledge diffusion performance. This study especially emphasizes the effect of an asymmetric degree distribution on knowledge diffusion performance. Study 1 complements previous research on knowledge diffusion by showing that (i) besides or even instead of the average path length and the average clustering coefficient, the (symmetry of) degree distribution influences knowledge diffusion. In addition, (ii) especially small, inadequately embedded agents seem to be a bottleneck for knowledge diffusion in this setting, and iii) the identified rather negative network structures on the macro level seem to result from the myopic linking strategies of the actors at the micro level, indicating a trade-off between ‘optimal’ structures at the network and at the actor level. Study 2 uses an agent-based simulation model to analyse the effect of different network properties on knowledge diffusion performance. In contrast to study 1, this study analyses this relationship in a setting in which knowledge is diffusing freely throughout an empirical formal R&D network as well as through four benchmark networks. In addition, the concept of cognitive distance and differences in learning between agents in the network are taken into account. Study 2 complements study 1 and further previous research on knowledge diffusion by showing that (i) the (asymmetry of) degree distribution and the distribution of links between actors in the network indeed influence knowledge diffusion performance to a large extend. In addition, (ii) the extent to which a skewed degree distribution dominates other network characteristics varies depending on the respective cognitive distance between agents. Study 3 analyses how so called dedicated knowledge can contribute to the transformation towards a sustainable, knowledge-based Bioeconomy. In this study, the concept of dedicated knowledge, i.e. besides mere-techno economic knowledge also systems knowledge, normative knowledge and transformative knowledge, is first introduced. Moreover, the characteristics of dedicated knowledge which are influencing knowledge diffusion performance are analysed and evaluated according to their importance and potential role for knowledge diffusion. In addition, it is analysed if and how current Bioeconomy innovation policies actually account for dedicated knowledge. This study complements previous research by taking a strong focus on different types of knowledge besides techno-economic knowledge (often overemphasized in policy approaches). It shows, that i) different types of knowledge necessarily need to be taken into account when creating policies for knowledge creation and diffusion, and ii) that especially systems knowledge so far has been insufficiently considered by current Bioeconomy policy approaches. Study 4 analyses the effect of different structural disparities on knowledge diffusion by deducing from theoretical considerations on network structures and diffusion performance. The study tries to answer whether the artificially generated network structures seem favourable for the diffusion of both mere techno-economic knowledge as well as dedicated knowledge. Study 4 especially complements previous research on knowledge diffusion by (i) analysing an empirical network over a long period of time, and (ii) by indicating a potential trade-off between structures favourable for the diffusion of mere techno-economic knowledge and those for the diffusion of other types of dedicated knowledge. Summing up, it is impossible to make general statements that allow for valid policy recommendations on network structures ‘optimal’ for knowledge diffusion. Without knowing the exact structures and context, politicians will hardly be able to influence network structures. Especially if we call for knowledge enabling transformations as the transformation towards a sustainable knowledge-based Bioeconomy, creating structures for the creation and diffusion of this knowledge is quite challenging and needs for the inclusion and close cooperation of many different actors on multiple levels.