From: John Conover <john@email.johncon.com>
Subject: Re: When are SD models appropriate?
Date: Sat, 17 Dec 94 23:58 PST
Stephen Robbins writes:
>
> Having just completed MIT's course in system dynamics, my impression
> is that system dynamic models are appropriate whenever you have
> multiple feedback loops in a system, and/or long delays between cause
> and effect. What the models helped me understand most in the course
> of the semester was the overall behavior patterns of systems. For
> example, we built a model of a particular marketplace, and discovered
> that, given the model's assumption, there were certain policies a
> company could follow to guarantee a profit in that marketplace under
> a wide variety of circumstances. [It also showed us that the market
> had a prisoner's dilemma characteristic--we could win BIG if we
^^^^^^^^^^^^^^^^^^
Hi Stever. What is a prisoner's dilemma characteristic in the market
place? How do you run a defection strategy in the market place. Don't
all competitors in a market place run a defection strategy? Isn't that
the essence of capitalism? Isn't a cooperation strategy illegal, and a
violation of SEC rules and regulations? (BTW, it is not clear to me
that markets are zero sum, although a lot of folks pay lip service to
the buz words.) Note that the classical prisoner's dilemma (as per
Luce, et al) is a SINGLE iterated "game," between only two players,
which probably does not model the market dynamics adequately. When
there are multiple iterated "games" available concurrently in the
marketplace, the situation is much different (as per Axelrod and
Forrest,) since you can choose who your opponent is, and perhaps find
an opponent that will run a cooperation strategy, eg, form a coalition
(at least for a while.) Thus, emergent phenomena are an expected
outcome of the market dynamics. IMHO, that emergent phenomena is how
markets develop.
Wana good PHD thesis? Most markets, empirically, exhibit a 1/f squared
time series power spectrum distribution (sometimes cubed, etc.) Prove
that a market with an alternative of multiple iterated prisoner's
dilemma games will exhibit a 1/f type of time series power
spectrum. (If, indeed, a prisoner's dilemma type of scenario is the
"engine" of a competitive market place-which may be counter intuitive
to classical and neo-classical economics and its equilibrium
paradigm.)
How does all of this relate to learning organizations? If you get the
program fractal dimension program, FD3 (available via anonymous ftp
from lyapunov.ucsd.edu:/pub/cal-state-stan [132.239.86.10],) and run
it on the monthly statistics for the electronic components market (I
work in the semiconductor industry, and it is available on electronic
media from the Department of Commerce,) you will find that it has a
fractal dimension of 0.9, or so (which is a 1/f power spectrum
distribution.) What this means is that the market environment is only
forcastable to 53% accuracy, or so, 6 months out-eg., the organization
has about 6 months to adapt and learn a new market paradigm, or the
organization will not be competitive in the market place. (If this is
true, then annual MBO may not be suitable in such situations-and a
rolling management methodology may have more specific application.)
Note that, if this is true, then we would have a kind of formal basis
for the learning organization concept.
For what it is worth, just some thoughts,
John
BTW, while we are on the subject of game-theoretic solutions to
management issues, a closely related works by Kenneth Arrow states
that there is no logical methodology to determine priorities in a
group of people, (the so called Impossibility Theorem.) Since
executive management (a personal observation) is chartered with such
things, and usually the priority determination process breaks down
into a set of defection strategies (eg., parochial issues,) is there a
formal relationship between the determination of priorities in a group
and the iterated prisoner's dilemma? Just a curious thought ...
--
John Conover, john@email.johncon.com, http://www.johncon.com/