I have found the comments below from Dr Mukherjee most interesting. They
move
the discussion further down to the deepest issues of what SD is supposed
to be (as initially proposed by proposed by Forrester), what it has
evolved to become, and what we want it to be in the future: a theory to
describe systems? a method to simulate systems as continuous processes
regulated by information feedback? or a simulation-based computer tool
that helps conceptualizing and solving complex differential equations?
Other views are, of course, possible.
As defined by Forrester in Industrial Dynamics, SD consists of
investigating the *feedback* character of complex (industrial) systems,
through the use of *computer-based simulation models*, with the aim of
helping to re-design and improve *organisational form* and *managerial
control policies*. This identifies the principles of SD:
(1) the behaviour of social systems can be explained, in great part, by
the information-feedback phenomenon, which occurs and results from the
many reciprocal internal interactions;
(2) models can be developed to *describe* these feedback mechanisms that
partially *explain* how the system behaves;
(3) these *explanatory* models can and are better implemented using
computer simulation. Feedback necessarily implies reciprocal
interactions *over time*. Simulation is the obvious candidate to
(re)create these interactions; digital computers appear to do the job
well;
(4) as a model eventually describes the feedback mechanisms embodied in
a real system, and further expains how these drive its behaviour, the
knowledge embodied in the model can be used as the basis to exercise
reasoning on how, if the system were different, its behaviour would
change. In this sense, a model works as an explanatory theory (as
discussed for example by Barlas and Carpenter 1990).
But is SD in itself a theory? SD certainly builds upon other theories,
but that does not prevent it to be a theory on its own. A theory can be
seen as an object of structured abstract knowledge which explains how
human-kind perceives how something works (including human abstract
creations). As described by Roberts (1978), and by many other authors,
there is no doubt that SD sought inspiration in the control theory and
principles of feedback, in the emergent studies of the human
decision-making processes, and in computer simulation (see also
Richardson 1991). It is also true that the Engineering field also sought
inspiration in the Control Theory (and helped to develop it) and found
critical support in digital computers. It did and continues to do so.
The term "System Dynamics" is often used in the engineering field (e.g.
see Shearer 1967, Seborg 1989, and Ogata 1993). The four points above
apply to any kind of system driven by feedback, and Engineers found that
too. Forrester made it clear that Engineering models provided the
appropriate precedent for the social systems.
Now, where do the mathematics of ODE come from? Mathematics seem to be
ultimate level of formality to where knowledge can be structured. In a
sense, it can be seen as the ultimate level of understanding. Although
this is debatable, one tends to push knowledge towards mathematical
structuring as one understands it better. Of course, mathematics is made
of relative conventions which over the years have proven to fit well in
the human framework of abstract reasoning; yet this requires thorough
education. The description of feedback mechanisms, if taken to this
level of formality, does lead to the mathematics of differential
equations.
SD has been criticised since the early days as representing no more than
a system of ordinary differential equations, often not properly
validated, and which aim at describing reality (see Berlinsky 1976, "On
Systems Analysis"). But I have serious doubts that Forresters initial
thoughts were: "The behaviour of social systems can clearly be described
by ordinary differential equations, but as these are so complex that
they are difficult to conceptualize and to solve analytically, let us
develop computer tools to do the job." Of course, after one has learnt
the mathematics of DE, one can anticipate when it can be applicable to
certain situations. But the process of developing a feedback-based
representation of a system, to decide what to include and what no
neglect, to identify and recognize the importance of the feedback
forces, to relate these forces to observed behaviour, to quantify the
individual interactions within the system, to continuously debate and
revise all this by analysing and simulating this representation, to
validate all this while moving towards the perceived reality, and
ultimately to learn more about the real system, and eventually identify
alternative structures which provide improved behaviour, all this looks
to me as going far beyond the theory of ODE. Differential equations
emerge as the ultimate level of formality to *define* (but a difficult
to read representation) our beliefs on how a feedback system works, and
the consequences of such beliefs. Yet, neither they are the objective
purpose of an SD study, nor they are the appropriate means to represent
and learn about the system, and find better solutions.
In my opinion, and while building upon other theories, SD provides a
rather novel way of studying social systems. A new way of structuring
knowledge about these systems, of explicating the feedback nature of
their behaviour, of helping to identify solutions for real problems in
the real world. Is it a theory on its own? The answer is debatable. It
is certainly much more than a computer application that helps developing
and solving ODEs about social systems. It raises critical philosophical
issues about our understanding of social systems; it raises critical
methodological issues about modelling in the wide field of OR/MS, like
"validation". To understand whether there is a theory of SD, and what
this theory is about, one needs to study the other uderlying theories
and find the steps given further by SD. This takes scientific
discipline, time, and effort. Of course, the same is not true about
developing models as an art. These "artistic" models may well prove
useful sometimes. But as Forrester argued, the way ahead from art to
science is to distill and structure knowledge gained from empirical
experience.
All theories take time to emerge, to prove themselves, and to be
recognised as such.
Apologies for such a long message, and thanks to JM for raising so
imporant questions and ideas.
Best regards,
Alexandre Rodrigues
alex@mansci.strath.ac.uk