Peak-End rule versus average utility: how utility aggregation affects evaluations of experiences

Irina Cojuharenco*, Dmitry Ryvkin

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

28 Citations (Scopus)

Abstract

The "Peak-End rule" which averages only the most extreme (Peak) and the final (End) impressions, is often a better predictor of overall evaluations of experiences than average impressions. We investigate the similarity between the evaluations of experiences based on Peak-End and average impressions. We show that the use of the Peak-End rule in cross-experience comparisons can be compatible with preferences for experiences that are better on average. Two conditions are shown to make rankings of experiences similar regardless of the aggregation rule: (i) the individual heterogeneity in the perception of stimuli, and (ii) the persistence in impressions. We describe their effects theoretically, and obtain empirical estimates using data from previous research. Higher estimates are shown to increase correlational measures of association between the Peak-End and average impressions. The high association per se is shown to be not only a theoretical possibility, but an empirical fact.
Original languageEnglish
Pages (from-to)326-335
Number of pages10
JournalJournal of Mathematical Psychology
Volume52
Issue number5
DOIs
Publication statusPublished - Oct 2008

Keywords

  • Average utility
  • Peak-end rule
  • Total utility
  • Utility dynamics

Fingerprint

Dive into the research topics of 'Peak-End rule versus average utility: how utility aggregation affects evaluations of experiences'. Together they form a unique fingerprint.

Cite this