Evolutionary Model of an Innovative and Differentiated Industry (original) (raw)
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Editorial: Evolutionary Economic Geography – Theoretical and Empirical Progress
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Evolutionary economic geography and its implications for regional innovation policy
2009
Related variety is important to regional growth because it induces knowledge transfer between complementary sectors at the regional level. This is accomplished through three mechanisms: spinoff dynamics, labor mobility and network formation. They transfer knowledge across related sectors, which contributes to industrial renewal and economic branching in regions. Since these mechanisms of knowledge transfer are basically taking place at the regional level, and because they make regions move into new growth paths while building on their existing assets, regional innovation policy should encourage spinoff activity, labor mobility and network formation. Doing so, policy builds on region-specific assets that provides opportunities but also sets limits to what can be achieved by policy. Public intervention should neither apply 'one-size-fits-all' approaches nor adopt 'picking-thewinner' strategies, but should aim to connect complementary sectors and exploit related variety as a source of regional diversification.
Evolutionary economics and economic geography
Journal of Evolutionary Economics, 1999
This article attempts to explore how key notions from Evolutionary Economics, such as selection, path-dependency, chance and increasing returns, may be applied to two key topics in Economic Geography. The ®rst issue is the problem of how to specify the (potential) impact of the spatial environment on new variety in terms of technological change. Evolutionary thinking may be useful to describe and explain: (1) the process of localized`collective' learning in a regional context, (2) the adjustment problems that regions may be confronted with in a world of increasing variation, and (3) the spatial formation of newly emerging industries as an evolutionary process, in which the spatial connotation of increasing returns (that is, agglomeration economies) may result in a spatial lock-in. The second issue is the problem of how new variety may aect the long-term evolution of the spatial system. We distinguish three approaches that, each in a different way, apply evolutionary notions to the nature of spatial evolution. This is strongly related to the issue whether mechanisms of chance and increasing returns, rather than selection and path-dependency, lay at the root of the spatial evolution of new technology.
Innovation, diffusion and agglomeration
Economics of Innovation and New Technology, 2009
Traditional accounts of innovation have tended to neglect the need for change to take place at particular times and in particular places. This paper considers how to move towards a description of innovative processes which take time and place into account.
Industry dynamics with product innovation: An evolutionary model
2009
We present an evolutionary simulation model of industry dynamics with product innovation and diff:erentiated demand. The major goal of the paper is to unite two strands of the evolutionary literature on innovation that tend to be analysed in isolation. The paper calls for considering jointly the role of market competition and of technology complexity in shaping innovation patterns of an industry. Most of the earlier works on innovation study the eff:ects of innovation on competition, but do not consider the complexity aspect of exploring a complex landscapes. Conversely, complexity studies focus on the nature and limits of innovation patterns by bounded rational agents, irrespective of the eff:ects of economic competition in directing innovative eff:orts, such as funding R&D investments and shaping the type of innovation required to generate profi:ts. This work calls for uniting the two strands of the literature, considering explicitly: 1) the role of complex landscapes 2) the incentives of competitive firms. The paper proposes a model where fi:rms are represented as innovating agents in technological spaces of varying complexity. Such model is used to replicate some of the results already JEL -codes: L, D, -
An evolutionary approach to regional systems of innovation
2011
Abstract This article examines how the birth and the development of regional systems of innovation are connected with economic selection and points to implications for regional-level policies. The research questions are explored using an evolutionary model, which emphasizes geographical spaces and production of intermediate goods.
Innovation, Dynamic Regions and Regional Dynamics
Advances in Spatial Science, 2009
This paper analyses the aspects of spatial economics that deals with innovation, regional specialization and dynamic systems of functional regions and in particular the contributions made by the economist Börje Johansson. The innovation aspect consists of innovation networks, knowledge sources and knowledge sinks, cost and innovation of product characteristics and innovation at the industry and sector level. In the regional specialization part the infrastructure, regional economic milieus, the specialization of regions and specific the specialization in small and large regions, spatial transaction costs, and endogenous specialization are subjects that are being treated. Regional dynamics consists of location dynamics in a system of functional urban regions where different theories are being discussed as the spatial product life cycle theory and filtering-down theory. The last part does also take up lead-lag models.
Industrial Dynamics and Economic Geography
Regional Studies, 2012
ABSTRACT We review the literature on clusters and their effects on industrial dynamics as well on various lifecycle dynamics underlying the process of cluster formation and cluster dynamics. The review shows that there is little evidence that clusters enhance firm growth and survival. In the absence of localization economies, the emergence of clusters is best understood as an evolutionary process of capability transmission between parents firms and their spinoffs. We discuss various future research avenues and call for theorising based on firm heterogeneity as well as empirical research based on common methodological standards.