149,766 research outputs found

    The underlying social dynamics of paradigm shifts

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    We develop here a multi-agent model of the creation of knowledge (scientific progress or technological evolution) within a community of researchers devoted to such endeavors. In the proposed model, agents learn in a physical-technological landscape, and weight is attached to both individual search and social influence. We find that the combination of these two forces together with random experimentation can account for both i) marginal change, that is, periods of normal science or refinements on the performance of a given technology (and in which the community stays in the neighborhood of the current paradigm); and ii) radical change, which takes the form of scientific paradigm shifts (or discontinuities in the structure of performance of a technology) that is observed as a swift migration of the knowledge community towards the new and superior paradigm. The efficiency of the search process is heavily dependent on the weight that agents posit on social influence. The occurrence of a paradigm shift becomes more likely when each member of the community attaches a small but positive weight to the experience of his/her peers. For this parameter region, nevertheless, a conservative force is exerted by the representatives of the current paradigm. However, social influence is not strong enough to seriously hamper individual discovery, and can act so as to empower successful individual pioneers who have conquered the new and superior paradigm.Fil: Rodriguez Sickert, Carlos. Universidad del Desarrollo; ChileFil: Cosmelli, Diego. Pontificia Universidad Católica de Chile; ChileFil: Claro, Francisco. Pontificia Universidad Católica de Chile; ChileFil: Fuentes, Miguel Angel. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad San Sebastián; Chil

    Economic growth, innovation systems, and institutional change: a trilogy in five parts

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    Development and growth are products of the interplay and interaction among heterogeneous actors operating in specific institutional settings. There is a much alluded-to, but under-investigated, link between economic growth, innovation systems, and institutions. There is widespread agreement among most economists on the positive reinforcing link between innovation and growth. However, the importance of institutions as catalysts in this link has not been adequately examined. The concept of innovation systems has the potential to fill this gap. But these studies have not conducted in-depth institutional analyses or focussed on institutional transformation processes, thereby failing to link growth theory to the substantive institutional tradition in economics. In this paper we draw attention to the main shortcomings of orthodox and heterodox growth theories, some of which have been addressed by the more descriptive literature on innovation systems. Critical overviews of the literatures on growth and innovation systems are used as a foundation to propose a new perspective on the role of institutions and a framework for conducting institutional analysis using a multi-dimensional typology of institutions. The framework is then applied to cases of Taiwan and South Korea to highlight the instrumental role played by institutions in facilitating and curtailing economic development and growth

    Knowledge about knowledge since Nelson & Winter: a mixed record

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    Progress in our understanding of the role of knowledge in the economy, based on Nelson and Winter's book published in 1982, has been mixed. It has been greatest when their concepts have been enriched by empirical evidence, often coming from outside evolutionary economics. It has been least when discussions have been mainly theoretical, and constrained within evolutionary economics.knowledge, innovation, technical change

    Agents intentionality, capabilities and the performance of Systems of Innovation

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    We are interested on why and how an economic system evolves and, in particular, on the causes of the differences across systems of innovation (SI). SI’s performance differs substantially because there are specific causes at work, apart from the differences in the underlying technologies, institutions, etc. In particular, we refer to the intentionality of the agents interacting within a system for innovation to find out the relationship between agents’ goals, SI’s performance and its policy implications. The underlying thesis in this paper is that agent intentionality is a necessary condition for a substantive explanation of the dynamism of any socio-economic system. The paper departs from an abstract definition of a system as a set of constitutive elements and the connections among them serving a common purpose. And explores how intentionality shapes the structure, evolution and performance of an SI. In this context an evolutionary efficiency criterion is proposed.systems of innovation; intentionality; evolving capabilities; evolutionary efficiency.

    Small Worlds in Networks of Inventors and the Role of Science: An Analysis of France.

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    · Using data on patent applications at European Patent Office, we examine the structural properties of networks of inventors in France in different technologies, and how they depend from the inventive activity of scientists from universities and public research organizations (PROs). We revisit earlier findings on small world properties of social networks of inventors, and propose more rigorous tests of such hypothesis. We find that academic and PRO inventors contribute significantly to patenting in science‐based fields. Such contribution is decisive for the emergence of small world properties.networks, inventors, academic patenting, small world.

    The Effect of the Dynamics of Knowledge Base Complexity on Schumpeterian patterns of Innovation: the upstream petroleum industry

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    This paper addresses important changes in innovation patterns in the upstream petroleum industry over the period from the 1970s to 2005. It argues that the shifts in patterns of innovation over that period can be explained by the dynamics of knowledge base complexity (KBC). We develop a quantitative method to explore KBC and show that increasing KBC has shifted innovation patterns, from a broadly Schumpeter Mark I to a 'modified' form of Schumpeter Mark II, led less by the established oil majors, but by a new class of integrated service providers
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