DocumentCode :
1540688
Title :
To innovate or not to innovate?
Author :
Dawid, Herbert ; Reimann, Marc ; Bullnheimer, Bernd
Author_Institution :
Dept. of Econ., Univ. of Southern California, Los Angeles, CA, USA
Volume :
5
Issue :
5
fYear :
2001
fDate :
10/1/2001 12:00:00 AM
Firstpage :
471
Lastpage :
481
Abstract :
In this paper, we analyze the evolution of output decisions of adaptive firms in an environment of oligopolistic competition. The firm might either choose to produce one of several existing product variants or try to establish a new product variant on the market. The demand for each individual product variant is subject to a life cycle, but aggregate demand for product variants is constant over time. Every period each firm has to decide whether to produce the product again, introduce a new product variant itself (which generates an initial advantage on that market), or follow another firm and change to the production of an already established product. Different firms have heterogeneous abilities to develop products and imitate existing designs; therefore, the effects of the decision whether to imitate existing designs or to innovate differ between firms. We examine the evolution of behavior in this market using an agent-based simulation model. The firms are endowed with simple rules to estimate market potentials and market founding potentials of all firms, including themselves, and make their decisions using a stochastic learning rule. Furthermore, the characteristics of the firms change dynamically due to “learning by doing” effects. The main questions discussed are how the success and the optimal strategy of a firm depend on the interplay between characteristics of the industry and properties of the firm
Keywords :
adaptive systems; digital simulation; economic cybernetics; learning (artificial intelligence); optimisation; software agents; stochastic processes; adaptive firms; agent-based simulation model; design imitation; heterogeneous abilities; innovation; life cycle; market founding potentials; oligopolistic competition; optimal strategy; output decision evolution; product development; stochastic learning rule; Aggregates; Business communication; Economic forecasting; Environmental economics; Government; Production; Stochastic processes; Technological innovation; Timing; Uncertainty;
fLanguage :
English
Journal_Title :
Evolutionary Computation, IEEE Transactions on
Publisher :
ieee
ISSN :
1089-778X
Type :
jour
DOI :
10.1109/4235.956711
Filename :
956711
Link To Document :
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