Open AccessPosted Content
An Overview of Innovation
TLDR
The process of innovation must be viewed as a series of changes in a complete system not only of hardware, but also of market environment, production facilities and knowledge, and the social contexts of the innovation organization as discussed by the authors.Abstract:
Models that depict innovation as a smooth, well-behaved linear process badly misspecify the nature and direction of the causal factors at work. Innovation is complex, uncertain, somewhat disorderly, and subject to changes of many sorts. Innovation is also difficult to measure and demands close coordination of adequate technical knowledge and excellent market judgment in order to satisfy economic, technological, and other types of constraints—all simultaneously. The process of innovation must be viewed as a series of changes in a complete system not only of hardware, but also of market environment, production facilities and knowledge, and the social contexts of the innovation organization.read more
Citations
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Forms of knowledge and modes of innovation
TL;DR: In this article, the authors compared two modes of innovation, Science, Technology and Innovation (STI) and Doing, Using and Interacting (DUI), and found that firms combining the two modes are more likely to innovate new products or services than those relying primarily on one mode or the other.
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National Innovation Systems: Analytical Concept and Development Tool
TL;DR: In this article, a core of the innovation system is defined and it is illustrated that it is necessary both to understand micro-behaviour in the core and understand the wider setting within which the core operates.
Posted Content
Leveraging External Sources of Innovation: A Review of Research on Open Innovation
TL;DR: In this paper, an analysis of prior research on how firms leverage external sources of innovation is presented, which suggests a four-phase model in which a linear process of obtaining, integrating, integrating and commercializing external innovations is combined with interaction between the firm and its collaborators.
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University–industry relationships and open innovation: Towards a research agenda
Markus Perkmann,Kathryn Walsh +1 more
TL;DR: In this paper, the diffusion and characteristics of collaborative relationships between universities and industry are explored, and a research agenda informed by an open innovation perspective is developed. But the authors focus on the effects of university-industry links on innovation-specific variables, such as patents or firm innovativeness, and the dynamics of these relationships remain under-researched.
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'Mode 3' and 'Quadruple Helix': toward a 21st century fractal innovation ecosystem
TL;DR: The 'Quadruple Helix' emphasises the importance of also integrating the perspective of the media-based and culture-based public, and results is an emerging fractal knowledge and innovation ecosystem, well-configured for the knowledge economy and society.
References
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Journal ArticleDOI
Firm's objective function and product and process R&D
TL;DR: In this article, the authors study the effect of a firm having a general objective function (that takes into consideration both profits and consumer surplus) on its product and process R&D choices and corresponding implications.
Dissertation
Engineering value, engineering risk : what derivatives quants know and what their models do
TL;DR: In this paper, the authors examined the evaluation culture of derivatives quants working in the over-the-counter markets for interest rate derivatives tied to Libor, using data from interviews with quants, financial mathematicians, and economists conducted primarily in the United Kingdom and the United States, combined with fieldwork at derivatives "quant" conferences and an extensive set of technical sources.
Journal ArticleDOI
Modeling study of knowledge diffusion in scientific collaboration networks based on differential dynamics: A case study in graphene field
TL;DR: The results show that the state evolution of research entities in the knowledge diffusion process of science collaboration networks is affected not only by the evolution states of adjacent research entities with whom they have certain collaboration relationships, but also by the structural attributes and degree distributions of scientific collaboration networks.
Proceedings Article
Innovation in virtual worlds: social structure and diffusion
TL;DR: This research-in-progress paper investigates the impact of social structures in virtual worlds (VWs) on the diffusion of innovations within them and proposes the use of social network analysis to investigate these propositions.
Posted Content
Process innovation objectives and management complementarities: patterns, drivers, co-adoption and performance effects
TL;DR: In this paper, the authors examined process innovation as more than a mere dependent variable for predicting innovators and provided insights into the poor attention that process innovation variable has received as an indicator of a firm's performance.