ABSTRACT
“Returns to scale”, as a methodology, goes
back to Adam Smith (1776). Economists after Marshall (1842-1924), with certain
exceptions, confined their interests exclusively to “Constant returns to scale”. As a return they secured for their analysis a single equilibrium point with convenient convex curves. Early economists were
sure that “resource-based” economic sectors like “Agriculture”, “Bulk goods
production” and “Mining” exhibited “diminishing returns to scale”, a belief
valid till this day. However, at least 9 important “knowledge-based” sectors
exhibited increasing returns. More important is that increasing returns
provides also no obstacle to growth of a firm, and of an industry…till it
becomes a monopoly... We presented arguments against and in favor of this last
theory drawn from Shipping and Marketing. Moreover, we examined the existence
of increasing returns in relation to shipping industry and especially with 2
case-studies dealing with: 1) the exceptional economies of scale concerning
“Vale S.A.” and its giant ships “Valemax” of 400,000 dwt, double in size of
existing ships (i.e. the Capes of
about 200,000 dwt) and 2) the case of shipowners locked-in within the extremely
high chartering markets during 2003-2008. The first was also examined in
relation to the impact of “chance or small historical events”. Traditional
economists indeed did not have the mathematical tools to deal with “increasing
returns” and “path dependence” till 1983, when “Arthur et al.” discovered the “Urn schemes of the Polya kind”. This method
succeeded in combining probabilities or random facts with deterministic or
chaos motions! This had a great impact on methodology, which, prior to that,
dealt with either random or deterministic models in a water-proof separate
manner. The aim of this paper was to mark out the importance of increasing
returns, which has important implications in economic
development policies, and comes from Complexity Theory and Chaos theory. With
the first case study we showed, in addition, that market does not know best and
small chance (historical) events, or mistakes, determine prevalence of a good
or of a technical innovation. Moreover, we showed that in case of a lock-in,
firms cannot do the best provided they have also the ability to foresee future.
This analysis deals with a slice of Complexity theory.