Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

Enterprise clusters triggered by radical innovation: a modelistic approach

Enterprise clusters triggered by radical innovation: a modelistic approach Purpose – This papers aims to deal with enterprise networks and clusters dynamics, as well as inter‐firm joint efforts and collaborations, in order to study their evolution and possible effects when radical innovation occurs inside them. Design/methodology/approach – In order to study these dynamics, with the optimal balancing among different strategies and the importance of exogenous parameters in cluster creation, a model is presented. It follows the agent‐based paradigm, particularly suited for describing complex social systems in which many parts interact among them. This allows one to create simulations of the studied system, and to test different hypotheses. Besides, it is the only paradigm in which the emergent features of complex systems can arise spontaneously, thanks to the bottom‐up design. A model is introduced and described in detail. Findings – Qualitative results are described, reflecting current state‐of‐the art theories. The results show how clusters emerge and evolve among enterprises, and how radical innovation can trigger this phenomenon. Different managerial behaviour (externally or internally focused) is discussed as well. Originality/value – The most important feature of a model based on agent is the possibility of repeating the experiment several times, by changing one or few variables at a time, by leaving the others unchanged. It constitutes for social sciences the equivalent of lab experiments for such disciplines as physics or chemistry. The presented model allows the study of different clustering scenarios, by changing the initial conditions. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png EuroMed Journal of Business Emerald Publishing

Enterprise clusters triggered by radical innovation: a modelistic approach

Loading next page...
 
/lp/emerald-publishing/enterprise-clusters-triggered-by-radical-innovation-a-modelistic-pvZuXLWvUf
Publisher
Emerald Publishing
Copyright
Copyright © 2010 Emerald Group Publishing Limited. All rights reserved.
ISSN
1450-2194
DOI
10.1108/14502191011065527
Publisher site
See Article on Publisher Site

Abstract

Purpose – This papers aims to deal with enterprise networks and clusters dynamics, as well as inter‐firm joint efforts and collaborations, in order to study their evolution and possible effects when radical innovation occurs inside them. Design/methodology/approach – In order to study these dynamics, with the optimal balancing among different strategies and the importance of exogenous parameters in cluster creation, a model is presented. It follows the agent‐based paradigm, particularly suited for describing complex social systems in which many parts interact among them. This allows one to create simulations of the studied system, and to test different hypotheses. Besides, it is the only paradigm in which the emergent features of complex systems can arise spontaneously, thanks to the bottom‐up design. A model is introduced and described in detail. Findings – Qualitative results are described, reflecting current state‐of‐the art theories. The results show how clusters emerge and evolve among enterprises, and how radical innovation can trigger this phenomenon. Different managerial behaviour (externally or internally focused) is discussed as well. Originality/value – The most important feature of a model based on agent is the possibility of repeating the experiment several times, by changing one or few variables at a time, by leaving the others unchanged. It constitutes for social sciences the equivalent of lab experiments for such disciplines as physics or chemistry. The presented model allows the study of different clustering scenarios, by changing the initial conditions.

Journal

EuroMed Journal of BusinessEmerald Publishing

Published: Jul 20, 2010

Keywords: Enterprise zones; Innovation; Diffusion; Management strategy

References