Compound Learning, Neural Nets And The Competitive Process

Mario Calderini () and John Metcalfe

Economics of Innovation and New Technology, 1998, vol. 7, issue 4, 271-302

Abstract: In this paper we try to assess the potential application of neural networks as a modelling tool for complex evolutionary processes. The concept that we wish to investigate is the one of compound learning, that is the fact that, in a complex environment, what and how much economic entities learn depends upon what has been learnt in other entities in an interactive fashion. Our application consists of a stylised environment in which two firms learn how to innovate their product and to sell it on a market which learns how to evaluate the product which is being supplied. We seek to demonstrate that what matters for competitive advantage is not the absolute value of learning capability but the differential learning capability between the competing firms and between the firms and the market. Another appealing way to see it is that the chance for one of the two firms to gain competitive advantage is not unlimited but is constrained by own learning capability and the learning capability of the market.

Keywords: Learning; Competition; Neural networks; JEL Classification: L20; O30 (search for similar items in EconPapers)
Date: 1998
References: View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://www.tandfonline.com/doi/abs/10.1080/10438599800000037 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:ecinnt:v:7:y:1998:i:4:p:271-302

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/GEIN20

DOI: 10.1080/10438599800000037

Access Statistics for this article

Economics of Innovation and New Technology is currently edited by Professor Cristiano Antonelli

More articles in Economics of Innovation and New Technology from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().