Information flow and analysis: Theory, simulation, and experiments. II. Simulation, examples, and results

This series of articles describes research which has been underway at The Ohio State University in an effort to develop a fundamental and general theory of information flow and analysis. More specifically, the research attempts to (1) identify and quantify important variables and parameters in the information flow process; (2) establish relationships among these variables; (3) apply the theory to practical situations and to examine the resulting implications; and (4) develop models, both simulation and experimental, to utilize and validate the theory. The basis for our work treats information as data of value in decision‐making. This, in turn, leads to a powerful model of a Generalized Information System. We have now made considerable progress and have developed the basic elements comprising a generalized theory. In particular, we have been able to establish quantitative definitions for and relationships among quantity of information, value of information, effectiveness of information, decision‐maker effectiveness, decision‐maker performance, and other terms. By dealing with “average” decision‐makers, we establish unique relationships for specific decision situations. Typical relationships and curves are presented in the articles. We describe a flexible, sophisticated simulation model which permits the examination of the interrelationship between information and decision‐making for a wide variety of different situations. We present detailed simulation results for two specific examples‐a typical farmer and a mathematical example. We describe prototype experiments which place human decision‐makers in an interactive decision‐making situation. We are able to obtain data on their decision‐making behavior in the light of our conceptual model. Preliminary analysis of the data is described.