Why we iterate: scientific modeling in theory and practice

Abstract

An approach to system dynamics modeling is advocated that adheres to the scientific method, and that may be applied regardless of model scope or size. Scientific modeling is distinguished from other approaches largely by the quality of evaluation and revision performed and by an insistence upon empirical evidence to support hypotheses and formulations. Three case studies drawn from the author's experience are presented. Practical lessons for scientific modeling are given to help guide expectations and maximize effectiveness of the approach. Modelers and clients should clearly understand the level of rigor they wish to pursue and what this means for the degree of confidence that may be placed in model results and insights.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 167 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.