System Dynamics Methods Papers

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[edit] Three contributions of Peirce's pragmatist philosophy to SD modelling practice

Author: John Barton Contact: jabarton@ozemail.com.au

Title: Rethinking the methodology of System Dynamics- An Exercise in Deconstruction and Reconstruction.

Abstract:

Forrester’s ‘Growth Model’ is arguably the seminal demonstration of the application of System Dynamics (SD) methodology. This model, together with a number of Forrester’s wider discussions of SD emphasizing SD as the application of feedback thought to socio-economic thinking, define SD methodology.

This paper summarises the methodology described by Forrester and identifies a number of key components. It then considers these components from the perspective of how they might be enhanced by contemporary thinking in artificial intelligence (the role of abductive inference) and in causality, particularly the role of counterfactuals in simulation modeling.

This approach reveals a number of possible ways of improving SD methodology, particularly that aspect that relates to the continuing debate about the validation of SD models.

Title: Developing Knowledge Maps using System Dynamics Stock Flow Diagrams.

Abstract:

Identifying what is meant by “knowledge” and how knowledge is differentiated from “data” and “information” presents a central dilemma to those that want to undertake organizational knowledge audits. In general terms, knowledge maps have been proposed as a way forward in addressing such issues. But there is a dearth of published accounts of soundly based, coherent approaches to knowledge mapping. This paper proposes such an approach.

Although of the terms- knowledge, information, and data- are used almost interchangeably in common language, each has quite distinct technical meanings arising out of the respective fields of philosophy, information theory, and statistics, for example.

This paper argues that these usages can be suitably integrated using Peirce’s theory of semiotics to provide a result where knowledge is the interpreter of data to provide information upon which we take action.

System Dynamics diagramming conventions allow us to identify data and information flows as well as decision points where data is transformed into information that drives rates in the stock flow structure. It is then a matter of cataloguing the knowledge in content and form (eg tacit and explicit) for each decision point.

An example relating to a professional service firm is provided.

Title: Modelling Intangibles in System Dynamics

Abstract:

This paper argues that modeling intangibles such as “reputation” and “morale” as stock variables stretches the credibility of SD models in the eyes of clients (and some SD practitioners), and is both unnecessary and possibly technically incorrect.

An alternative approach is described based on the application of Peirce’s theory of categories and its application in semiotics. This approach argues that intangibles result as a reaction to things that are ultimately tangible (and can be sensibly expressed in stock-flow terms), and can only be known through actions that may result (Peirce’s pragmatic principle), ie, by their affect on rate variables. Within this framework, intangibles are expressed as indexes and modeled using auxiliary variables and graph functions.