The Adaptive Decision-Maker: Effort and Accuracy in Choice

Abstract

Research has shown that the strategies people use to evaluate and choose among a set of multiattribute alternatives are highly sensitive to a variety of task and context variables. This chapter reviews a program of research concerned with better understanding how decision making behavior is contingent upon properties of the decision task. The perspective adopted is that strategy selection is a function of both costs, primarily the effort required to use a decision Rule, and benefits, primarily the ability of a strategy to select the best alternative. A series of experiments involving both Monte-Carlo simulation and process-tracing techniques is reported that support the effort- accuracy framework. Unresolved issues of learning, bottom-up as well as top-down processing, and the role of incentives in strategy selection are then discussed. Finally, an implication of adaptive decision behavior for improving decisions by designing information displays which make effective processing easier is outlined.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1989
Accession Number
ADA205750

Entities

People

  • Eric J. Johnson
  • James R. Bettman
  • John W. Payne

Organizations

  • Duke University

Tags

Communities of Interest

  • Biomedical
  • C4I
  • Human Systems

DTIC Thesaurus Topics

  • Acquisition
  • Cognition
  • Cognitive Systems Engineering
  • Commerce
  • Computer Science
  • Databases
  • Human-Computer Interaction
  • Information Processing
  • Information Science
  • Judgment
  • Mathematical Models
  • Military Research
  • Monte Carlo Method
  • New York
  • Psychology
  • Schools
  • Universities

Readers

  • Systems Analysis and Design
  • Team-Based Human-Centered Cognitive Task Decision Making and Information Performance.