Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/95277 
Autor:innen: 
Erscheinungsjahr: 
2012
Schriftenreihe/Nr.: 
Quaderni di Dipartimento No. 176
Verlag: 
Università degli Studi di Pavia, Dipartimento di Economia Politica e Metodi Quantitativi (EPMQ), Pavia
Zusammenfassung: 
The paper presents an Agent-Based extension of Nelson-Winter model of schumpeterian competition. The original version did not provide any insight about the direction of firms’ innovative activities and of technological change as a whole. As a result, it lacked an explicit structure governing firms interaction and the shape of externalities. We address these criticisms by taking explicitly into account the structure of technology in use in the industry, that we shape as a directed network of nodes and links: nodes represent technological skills to be learnt by firms looking for ’new combinations’ and links represent their reciprocal interdependencies. The network is created in order to reflect the defining properties of Technological Paradigms and Technological Trajectories, as they emerge by evolutive-neoschumpeterian literature. Firms’ ability to learn technological skills through imitation of competitors generates spillover effects related to the process of diffusion of innovation. The basic model presented here focuses on a particular aspect of schumpeterian competition: the relationship between industry initial concentration and its overall innovative performance and, vice-versa, between innovation process and the evolution of industry structure over time. In this same perspective we also analyze how firms’ interactions and the structure of technology concur in determining the success or failure of an innovative strategy. Finally we argue that the model presented here might constitute a flexible framework worthy of further applications in the study of innovation process and technological progress.
Dokumentart: 
Working Paper

Datei(en):
Datei
Größe
3.35 MB





Publikationen in EconStor sind urheberrechtlich geschützt.