888,153 research outputs found

    The Process of Innovation

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    The paper argues that innovation processes can be cognitive, organisational and/or economic. They happen in conditions of uncertainty and (in the capitalist system) of competition. Three broad, overlapping sub-processes of innovation are identified: the production of knowledge; the transformation of knowledge into products, systems, processes and services; and the continuous matching of the latter to market needs and demands. The paper identifies key trends in each of these areas: (1) increasing specialisation in knowledge production; (2) increasing complexity in physical artefacts, and in the knowledge bases underpinning them; and (3) the difficulties of matching technological opportunities with market needs and organisational practices. Despite advances in scientific theory and information and communication technologies (ICTs), innovation processes remain unpredictable and difficult to manage. They also vary widely according to the firm's sector and size. Only two innovation processes remain generic: co-ordinating and integrating specialised knowledge, and learning in conditions of uncertainty. The paper also touches on the key challenges now facing 'innovation managers' within modern industrial corporations, bearing in mind the highly contingent nature of innovation.innovation processes, specialised knowledge production, knowledge transformation, modern industrial corporations

    Validation of a set of design principles to promote knowledge productivity and innovation

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    This study explores the learning processes that contribute to knowledge productivity: gradual improvement and radical innovation of an organisation’s procedure and products and services, based on the development and application of new knowledge. The research is based on the assumption that innovation is the result of a series of powerful social learning processes. Based on previous case study research we formulated a set of twelve design principles. Those principles reflect key factors relevant to the innovation processes. The study at hand presents the validation of this set of design principles. The method used is a set of circular scales with which people involved in innovation practices analysed their innovation process. From the data it reveals that the design principles do not miss elements that are essential for innovation practices. The two design principles that seem to be ambiguous and need further elaboration are principles 11 and 12. Furthermore it became clear that reflecting upon an innovation practice works best when doing it together instead of doing this individually

    Design Principles For Knowledge Productivity

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    This study explores the learning processes that contribute to knowledge productivity: the improvement and innovation of an organisation’s procedures, products and services, based on the development and application of new knowledge. Based on reconstruction and parallel case studies in more than 20 innovation practices, we formulated eleven design principles. Those principles help key players to turn the work environment into a learning environment that supports knowledge productivity

    Innovation, generative relationships and scaffolding structures: implications of a complexity perspective to innovation for public and private interventions

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    The linear model of innovation has been superseded by a variety of theoretical models that view the innovation process as systemic, complex, multi-level, multi-temporal, involving a plurality of heterogeneous economic agents. Accordingly, the emphasis of the policy discourse has changed over time. The focus has shifted from the direct public funding of basic research as an engine of innovation, to the creation of markets for knowledge goods, to, eventually, the acknowledgement that knowledge transfer very often requires direct interactions among innovating actors. In most cases, policy interventions attempt to facilitate the match between “demand” and “supply” of the knowledge needed to innovate. A complexity perspective calls for a different framing, one focused on the fostering of processes characterized by multiple agency levels, multiple temporal scales, ontological uncertainty and emergent outcomes. This contribution explores what it means to design interventions in support of innovation processes inspired by a complex systems perspective. It does so by analyzing two examples of coordinated interventions: a public policy funding innovating networks (with SMEs, research centers and university), and a private initiative, promoted by a network of medium-sized mechanical engineering firms, that supports innovation by means of technology brokerage. Relying on two unique datasets recording the interactions of the organizations involved in these interventions, social network analysis and qualitative research are combined in order to investigate network dynamics and the roles of specific actors in fostering innovation processes. Then, some general implications for the design of coordinated interventions supporting innovation in a complexity perspective are drawn

    Reinforcing Innovation Effectiveness – A New Methodological Approach for Policy Evaluation

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    ‘Innovation is the ability to take new ideas and translate them into commercial outcomes by using new processes, products or services in a way that is better and faster than the competition’ (Nedis & Byler, 2009). Innovation is considered as an important competitiveness factor for companies and a source of wealth for economies. Therefore it is an important subject of policy intervention and regional development. The understanding of what innovation is has evolved in the past decades away from a purely technological definition – of new products and processes introduced on the market, to a wider one including organisational and marketing aspects or incremental innovation in low tech production companies and more recently, innovation in services (European Commission, 2008). The main purpose of this paper is to propose a new methodology for territorial analysis and planning focused on innovation and knowledge transfer and in its governance mechanisms. A new methodology which is intended that can contribute to strengthen the present analytical tools applied to the processes of regional innovation and technology transfer. A new methodology that seeks, for each specific territorial context, contribute to the following results: 1) Evaluate the socio-economic and territorial impacts of knowledge transfer and technology diffusion; 2) Mapping territorial innovation effects and pathways – reinforcing innovation mapping and strategic planning; 3) Monitor innovation productivity, competitiveness and its systemic effects; 4) Monitor the innovation implementing processes and public policies, and support the multidimensional and multiscale evaluation of its results; 5) Better understand the knowledge transfer and technology diffusion in a specific territorial bases; 6) Increase the understanding of local and regional contexts of innovation governance.

    Business services as actors of knowledge transformation and diffusion: some empirical findings on the role of KIBS in regional and national innovation systems

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    Over the last years, there has been a significant increase in the attention paid to the activities of knowledge-intensive business services (KIBS). KIBS produce and duffus knowledge, which is crucial for innovation processes. The paper gives an overview of the role and function of KIBS in innovation systems and their knowledge production, transformation and diffusion activities. Focusing on innovation interactions between manufacturing small- and medium-sized enterprises (SMEs) and KIBS; the empirical analyses gasps KIBS in position in five contexts. The analysis leads to the conclusion that innovation activities links SMEs and KIBS through the process of knowledge and diffiusion. --

    The prescriptive quality of 11 design principles for knowledge productivity

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    This study explores the learning processes that contribute to knowledge productivity: gradual improvement and radical innovation of an organisation’s operating procedures, products, and services, based on the development and application of new knowledge. The research is based on the assumption that innovation is the result of a series of powerful social learning processes. Previous research revealed a set of eleven design principles that reflect factors that really matter in an innovation process. The study at hand presents how these design principles facilitate the design of an innovation practice. Review workshops and design workshops were used to answer the main research question: How do the design principles facilitate the design of an innovation practice? The data reveals that the design principles do not work as prescriptive rules that in a specific combination, applied to a predefined situation, will result in certain effects. Every design principle offers a new perspective on the innovation practice. This new perspective helps to get new ideas for interventions in the innovation practice. After the design of these interventions it is mainly the facilitator who has an important role in making it a success. If he sees opportunities and is capable, then he can use the interventions to create breakthroughs in the innovation practice

    KIBS and industrial development of cities.Labour mobility, innovation and client interaction

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    The paper departs from a seemingly disagreement between theoretical propositions stressing the importance of the KIBS sector as an innovation agent, and empirical results from quantitative innovation surveys. KIBS are increasingly seen to have a strategic role in stimulating innovation processes, particularly in large cities. However, the alleged importance of KIBS does not show up in empirical surveys. The surveys generally regard KIBS (or consultancy firms) to be of less importance as information sources and innovation partners. The paper somewhat supports the conclusions from the empirical surveys, pointing to the fact that parts of the literature attach larger importance to the role of KIBS in innovation processes than can be confirmed by empirical results. However, the low importance attached to KIBS in quantitative surveys may rely on the fact that surveys only seize some of the roles played by KIBS in innovation processes. Surveys do not map, for example, knowledge spillovers occurring through the mobility of workers. The paper demonstrates that many workers left the KIBS sector in Norway to start working in other sectors during parts of the 1990s, signifying a flow of knowledge following the workers out of the KIBS sector. However, the paper also demonstrates that the flow of knowledge via labour mobility first of all benefits the most central parts of Norway. Less knowledge is seen to flow from the KIBS sector in Oslo and the other large cities to other industries and other parts of the country.

    Simulating Knowledge-Generation and -Distribution Processes in Innovation Collaborations and Networks

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    An agent-based simulation model representing a theory of the dynamic processes involved in innovation in modern knowledge-based industries is described. The agent-based approach al-lows the representation of heterogeneous agents that have individual and varying stocks of knowledge. The simulation is able to model uncertainty, historical change, effect of failure on the agent population, and agent learning from experience, from individual research and from partners and collaborators. The aim of the simulation exercises is to show that the artificial innovation networks show certain characteristics they share with innovation networks in knowledge intensive industries and which are difficult to be integrated in traditional models of industrial economics.innovation networks, agent-based modelling, scale free networks
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