Abstract

This paper explores the dynamics of allocation under increasing returns in a context where increasing returns arise naturally: agents choosing between technologies competing for adoption. Modern, complex technologies often display increasing returns to adoption in that the more they are adopted, the more experience is gained with them, and the more they are improved.1 When two or more increasing-return technologies 'compete' then, for a 'market' of potential adopters, insignificant events may by chance give one of them an initial advantage in adoptions. This technology may then improve more than the others, so it may appeal to a wider proportion of potential adopters. It may therefore become further adopted and further improved. Thus a technology that by chance gains an early lead in adoption may eventually 'corner the market' of potential adopters, with the other technologies becoming locked out. Of course, under different 'insignificant events' - unexpected successes in the performance of prototypes, whims of early developers, political circumstances - a different technology might achieve sufficient adoption and improvement to come to dominate. Competitions between technologies may have, multiple potential outcomes. It is well known that allocation problems with increasing returns tend to exhibit multiple equilibria, and so it is not surprising that multiple outcomes should appear here. Static analysis can typically locate these multiple equilibria, but usually it cannot tell us which one will be 'selected'. A dynamic approach might be able to say more. By allowing the possibility of 'random events' occurring during adoption, it might examine how these influence ' selection' of the outcome - how some sets of random 'historical events' might cumulate to drive the process towards one market-share outcome, others to drive it towards another. It might also reveal how the two familiar increasingreturns properties of non-predictability and potential inefficiency come about: how increasing returns act to magnify chance events as adoptions take place, so that

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