Introduction

The preceding chapter offered a theoretical framework for understanding how people decide which decision strategy to use in solving a particular judgment or choice problem. We hypothesized that the use of multiple strategies by a decision maker was an adaptive response to decision problems, given that the decision maker had goals for both the accuracy of the decision and for the effort required.

A major distinction between our framework and that of several other researchers is the emphasis we place on understanding contingent decision behavior at a detailed information-processing level of explanation. This emphasis on understanding process requires an integrated methodology with two features: the capability to derive specific process level predictions regarding adaptivity in decision processes; and tests of those predictions on detailed, process-tracing data from individuals facing decision problems. We propose and illustrate such an approach in this chapter. Our approach combines the use of simulation of decision processes to make detailed predictions with the use of a computerized system for collecting process-tracing data on information acquisition behavior, which can then be used to test those predictions. This integrated methodology is unique to our work and is at a more detailed level than is typical in most research on decision making.

In the next sections we present the components of our methodology. First, we examine how to simulate decision strategies using production systems, discuss some computer simulation results, and consider the predictions for process data that these results imply.