Understanding Preferences in Experience-Based Choice

Abstract

The objective of this article is to improve our understanding of preferences in experienced-based choice. Positioned within the framework of naturalistic decision making, this article responds to the recent call to complement the examination of experience-based choice with studies of cognition in the “wild.” We document an exploratory field study that uses applied cognitive task analysis (ACTA) to examine financial day traders’ preferences. Providing real-world examples, our study illustrates how day traders construct their understanding of gains relative to losses and emphasizes the relevance of prospect theory for understanding the asymmetry of human choice. The fourfold pattern of preferences as studied in the wild is risk seeking for medium- and high-probability gains, risk averse for small-probability gains, risk averse for small-probability losses, and risk averse for medium- and high-probability losses. Our results differ from the fourfold pattern of preferences exhibited by experience-based choice when studied in the laboratory. The implications of this work for prospect theory and the distinction between “experience through learning” and “experience through professional training” are discussed alongside the merits of the ACTA technique for professional expert domain-based knowledge elicitation.