FORRESTER himself made one of the most lapidary critical evaluation of his method: "A computer simulation model is a theory of the behavior it creates" (Quoted by K.B.DE GREENE)
He could have added that it is based on the specific representation of the behavior of the concrete system by the observer-modelizer.
Among the difficult and yet unresolved problems for the construction of S.D. models, we can list:
- the possibility of misunderstandings between the "owner of the problem" and the modelizer about the nature of the problem at hand;
- the sometimes doubtful value of the data that can be effectively gathered from the concrete situation;
- the sometimes dubious criteria leading to the introduction or rejection of some elements within the structure of the model;
- the possible neglect of some significant interactions between the elements, or on the contrary the introduction of spurious ones;
- the impossibility to modelize simultaneity of events taking place at the same moment in different places in the modelized concrete system;
- the necessity to reduce the whole structure of the model to binary logics, adapted to the sequentiality of computers;
- the difficulty to retranslate the obtained results in terms adapted to practical intervention on the concrete system.
R.L. FLOOD and M.C. JACKSON made an extended critical survey of S.D. (1991, p.78-83), from four different viewpoints:
"a)…" Putting in place the feedback loops which constitute system structure and explain system behavior is held to be more important than exact representation achieved through precise reductionist methods. Obviously this leave S.D. open to charges that it lacks scientific rigour and is imprecise"… Of course, from the S.D. point of view, adhering strictly to the scientific method would exclude it from adressing most of the problem types for which it was originally intended"…
"b) Soft systems thinkers question the underlying assumption of S.D. that there is an external world made up of systems the structure of which can be grasped using models built upon feedback processes. To soft systems thinkers social systems are much more complex than this. They are the creative construction of human beings whose intentions, motivations and actions play a significant part in shaping "system" behavior".
"c) It follows that the attempt of S.D. thinkers to model external reality is misguided. Social systems are not only too complex for this but the subjective intentions of human beings cannot be captured in such "objective" models".
"d) Since it is held that social reality is too complex to model, soft systems thinkers argue that S.D. models must be distorted, one-sided reflections of reality. They are models from one, often unstated, point of view. In each model there is embedded a taken-for-granted purpose which can often be associated with the transformation that is being undertaken but ultimately relates back to the particular prejudices of the modellers.
"a) The hard systems critique of SD methodology is … aimed at the modelling process"… In its concern to be of practical use S.D is not content to wait upon all the necessary data becoming available. It seeks to built its systems models based upon judgements about interdependencies even when data are uncertain or missing".
"b) Soft systems thinkers similarly derive their critique of S.D. methodology from what they see as the theoretical shortcomings of the approach". Social systems are held not to be amenable to quantitative investigation. S.D. attempts to use mathematics in a loose fashion on variables (rates) and states (levels) that are often far from being clearly identifiable.
"a) Rather worrying from the ideological point of view is the manner in which SD analysts act somewhat like elite technicians. They see themselves serving decision makers, and managers, as experts providing objective and neutral guidance. There is no involvement of other "stakeholders"…
"b) S.D. modellers using feedforward control appear to believe that there are optimal future states that we should steer systems towards. However, these states are not made explicit. This is particularly worrying in the case of social systems which will contain different groups espousing alternative aims and intentions. S.D. modellers are likely implicitly to privilege the aims of some groups over others"…
"a) Hard systems thinkers believe that S.D. models are sometimes based upon poor data, sometimes ignore extant theories and often do not undergo a rigorous enough validation regime…
"b) Soft systems thinkers could forgive S.D. its lack of precision in areas where precision is difficult to obtain – scientific exactitude must sometimes be sacrificed for ready practical usefulness. What they cannot forgive is its attempt to present itself as an objective and neutral approach in the domain of social systems where "objectivity" (at last in the usual sense of that word) and "neutrality" are impossible to obtain ".
"c) A final point of soft systems criticism against S.D. concerns the relationship S.D. presupposes as existing between analysts and decision makers. The S.D. approach sees these functions as separate, the analyst simply presenting expert recommendations to the decision maker". According to soft systems thinkers"…the analyst needs to be much more closely involved with the decision maker"
D. MEADOWS et al., recognize that the problem of representing possible abrupt changes in a Systems Dynamics model is still unsolved: "No existing global model has been able to simulate these changes successfully, and the models that generate changes in the structure of the model do it in a mechanistic way. BARILOCHE model, with the transition from its "projective" to its "normative" face, is a good example of this" (1982, p.165)
This is of course because data used are only quantitative and the models themselves practically exclude qualitative change, notwithstanding the existence of feedbacks, meant to be corrective in order to maintain the system steady.
The BARILOCHE model, elaborated in Argentina, had pre-defined goals, i.e. was qualitative a priori, once and for all, but altogether deterministic and prescriptive.
The abrupt changes problem is obviously insolvable in linear terms, because complex systems are normally chaotic. It may remain definitively so, as chaotic systems forecast is necessarily probabilistic. The only satisfactory model of the system would then be the system itself.
- 1) General information
- 2) Methodology or model
- 3) Epistemology, ontology and semantics
- 4) Human sciences
- 5) Discipline oriented
To cite this page, please use the following information:
Bertalanffy Center for the Study of Systems Science (2020). Title of the entry. In Charles François (Ed.), International Encyclopedia of Systems and Cybernetics (2). Retrieved from www.systemspedia.org/[full/url]
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