712,340 research outputs found

    Networked by design: can policy constraints support the development of capabilities for collaborative innovation?

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    While there has been some recent interest in the behavioural effects of policies in support of innovation networks, this research field is still relatively new. In particular, an important but under-researched question for policy design is “what kind of networks” should be supported, if the objective of the policy is not just to fund successful innovation projects, but also to stimulate behavioural changes in the participants, such as increasing their ability to engage in collaborative innovation. By studying the case of the innovation policy programmes implemented by the regional government of Tuscany, in Italy, between 2002 and 2008, we assess whether the imposition of constraints on the design of innovation networks has enhanced the participants’ collaborative innovation capabilities, and we draw some general implications for policy

    Mapping London's Innovation Networks

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    A wide range of authors have highlighted the potential benefits for entrepreneurial companies that engage in effective networking along and across the supply-chain. As many organisations have downsized or outsourcedbasic research activities Universities have an increasingly important role within such networks. A number of UK initiatives have been established to encourage greater 'entanglement' between academia and commerce; the London Technology Network is one example which is intended to encourage interactions between London's leading research institutes and innovative businesses.Using the detailed data acquired by this network this paper is intended to presents an exploratory analysis of such activities with the aim of establishing the extent to which company size, sector and/or location play a significant role in participation in the network's activities. A wide range of authors have highlighted the potential benefits for entrepreneurial companies that engage in effective networking along and across the supply-chain. As many organisations have downsized or outsourced basic research activities Universities have an increasingly important role within such networks. A number of UK initiatives have been established to encourage greater 'entanglement' between academia and commerce; the London Technology Network is one example which is intended to encourage interactions between London's leading research institutes and innovative businesses.Using the detailed data acquired by this network this paper is intended to presents an exploratory analysis of such activities with the aim of establishing the extent to which company size, sector and/or location play a significant role in participation in the network's activities

    Network connections and innovation capacity in traditional agrifood chains

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    In the New Economy, the network is considered as more important than the firm itself. In this paper the focus is on chain networks which include vertical networks among chain members, horizontal networks with peers, and networking with third parties. Networks have an important role in the diffusion and adoption of innovations, thus they are the locus of innovation. While previous research focused on the firm, we contribute to the understanding of innovations in chain networks, i.e. we investigate the innovation capacity in vertical networks and how networking with peers and third parties is influencing the innovation capacity of the vertical network. We propose that there is a positive relationship between the network connections the direct chain partners have with peers and third parties and the innovation capacity of the vertical network. Data were collected from 90 direct agrifood chains in the traditional food sector. Cluster analysis suggested three clusters of chains corresponding to three distinct levels of innovation capacity: low, medium and high. Via descriptive analysis and binary logistic regression the influence of networking with peers and third parties on the innovation capacity of the vertical network was investigated. Our results confirm our proposition. However, we found that the chain partners are either horizontally or vertically networking for innovation. Nevertheless, more networking within the chain and with peers and third parties is linked to higher levels of innovation capacity. Consequently, our study adds to the research in the field of the New Economy by deepening the understanding of how innovation capacity is developed in vertical networks. We can confirm that the network is very important for the development and implementation of innovations and that the innovation capacity of one firm is linked to the innovation capacity of its chain partners. For future research we propose to investigate the link between networking for innovation and types of innovation which can be achieved. Further, future research should explore further inter-organizational links in the chain network and explore wider networks than the direct chain.SMEs, chain networks, traditional food products, Agribusiness, Agricultural and Food Policy, Community/Rural/Urban Development, Food Consumption/Nutrition/Food Safety, Labor and Human Capital,

    Analysis and measurement of interactions in European Innovation

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    Innovation Systems constitute an analysis framework, which allows comprehending the socio-economic structure of a territory. It consists of analyzing the existence of actors such as government institutions, clusters, universities, industries… their main competences, and the interactions into Innovation Networks among them. Thus, authorities (regional, national, local…) are endowed of a tool that allows the creation and development of competitive and efficient Innovation Systems. In this context, and due to the importance of interactions inside Innovation Systems, the present research intends to contribute a methodology which helps us to analyze and measure these interactions produced within Innovation Networks. The methodology developed will be tested in a sector which is present in several European Territories. This way, not only the measures defined but also the differences among the Networks analyzed will be observed and tested.Innovation Systems, Interactions, Innovation Networks, Measures.

    Horizontal and vertical networks for innovation in the traditional food sector

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    The locus of innovation is not the individual firm anymore but increasingly the network in which the firm is embedded. Hence, in this paper innovation is investigated in the broader context of networks and applied to the traditional food sector. Networking refers to a process of identifying and acting on complementary interests with or without formal means of cooperation and plays an important role for the diffusion and adoption of innovations, because they increase the flow of information. Two main types of networks exist. Vertical networks relate to cooperation of partners belonging to the same chain. Meanwhile, horizontal networks refer to coopereation among firms which are primarily competitors. Data were collected during focus groups and in-depths interviews in three European contries: Belgium, Hungary, and Italy. In each country, data are collected from retailers/wholesalers, food manufacturers and suppliers in the beer, hard and half hard cheese, ham, sausage, or white paprika chain. In the investigated countries both vertical and horizontal networks exist. However, the intensity of using the network differs. On the one hand vertical networks are well developed based on quality assurance schemes and traceability, though these networks often face difficulties due to high lack of trust. On the other hand, horizontal networks are well developed when a producer consortium is involved. However, these networks can be inhibited through strong competition. The partners in traditional food networks focus mainly on innovation related to product characteristics such as new size, form and packaging without changing the traditional character of the product. The main barriers for innovation in the traditional food networks are the lack of understanding the benefits of networking activities for innovation, the lack of trust, the lack of knowledge of appropriate methods and skills, and the lack of financial and physical resources. Our study points out that successful SMEs use their networks to overcome lacks of knowledge and information and to create possibilities of joint use of resources

    The Spatial Evolution of Innovation Networks: A Proximity Perspective

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    We propose an evolutionary perspective on the geography of network formation that is grounded in a dynamic proximity framework. In doing so, we root the proximity concept in an evolutionary approach to the geography of innovation networks. We discuss three topics. The first topic focuses on explaining the structure of networks. The second topic concentrates on explaining the effects of networks on the performance of actors. The third topic deals with the changing role of proximity dimensions in the formation and performance of innovation networks in the longer run.evolutionary economic geography, knowledge networks, innovation networks, dynamic proximity

    Chain networks as a leverage for innovation capacity : the case of food SMEs

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    &nbsp;Nowadays, innovation is no longer limited to the individual firm but involves increasingly the chain network in which the firm is embedded. The chain network is considered as the place where the internal and external resources of a firm are combined and transformed, leading to innovation capacity. In the increasingly globalizing market, innovation is an important strategic tool for small and medium sized enterprises (SMEs) to achieve competitive advantage. However, SMEs are often confronted with barriers for developing and introducing innovations, such as the lack of economies of scale. Our paper investigates how the chain network is contributing to the enhancement of the innovation capacity and which chain network characteristics are crucial in this process. In contrast to previous studies at chain network level, in our research specific chain networks are investigated and compared to each other. Hence, data collection took place at different chain network levels, being the supplier, the food manufacturer and the customer, working together and consequently belonging to one specific and unique chain network.The analysis of innovation capacity at the chain network level is realized by means of cluster analysis. This results in a three-cluster solution dividing the sample into Non-innovator chain networks, Customer-driven innovator chain networks and food manufacturer-supplier-driven innovator chain networks. Next, the influence of the chain network on the innovation capacity is examined. Thereby, the three achieved clusters differ significantly related to certain chain network characteristics. The following characteristics form an important leverage for the innovation capacity: firm size, profitability and business growth of the chain network members, as well as higher dependency, and lower levels of integration, rewarding power, social satisfaction and collaboration. The distinction of Customer-driven and food manufacturer-supplier-driven innovator chain networks reveals that the involvement of the chain network partners for the enhancement of the innovation capacity is a very important aspect. In future research, the degree of complexity of the studied system should gradually be increased, namely from a chain network of three members to more complex chain networks.</p

    The innovation process and network activities of manufacturing firms: Conceptual considerations and empirical evidence from the metropolitan region of Vienna

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    Innovation networks of manufacturers are currently receiving much attention as a competitive strategy. The contribution represents a response to the growing recognition that there are very important reasons why we need a better understanding of the relationship between innovation and networking. This response is conceptual in form, but enriched with some empirical evidence from the metropolitan region of Vienna. The paper demonstrates unambiguously the importance of external network activities during the innovation process that are organized around five types of networks: customer networks, manufacturing supplier networks, producer service supplier networks, producer networks and co-operation with research institutions and departments of universities. The data clearly indicate that networking is not only and primarily a metropolitan phenomenon. Spatial proximity is just one, but evidently not the decisive criterion for innovation-oriented relationships. The geography of networking largely extends to national and international levels.
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