The Effectiveness of Force Directed Graphs vs. Causal Loop Diagrams: An experimental study

摘要

When it comes to making tough decisions in dynamic environments, decision makers usually do not make the optimal choices (Moxnes, 2004). In order to help decision makers understand the consequences of their decisions modelers usually reveal the structure of their models through Causal Loop Diagrams (CLD). Here I have run a small pilot experiment comparing an alternative method of model structure, model behavior visualization called Force Directed Graphs (FDG) in an attempt to determine which is the more effective aid to decision makers. Participants in this study were asked to make decisions in a dynamic system, and were given either a CLD of the underlying model, or a FDG as an aid. The results of this study were inconclusive as to which was more effective, but it appeared that FDG users had better strategy, but were on the whole unable to translate that into optimal decision making. This paper also discusses changes to be applied to its experimental design before this study can be run in full.