# Contrasting holistic-compensatory with probabilistic heuristic strategies in multi-attribute decisions

## TL;DR

The study compares how people make decisions when given multiple options, finding that most use a compensatory strategy rather than a simplified one.

## Contribution

A new probabilistic extension of the Take the Best heuristic is proposed and tested against compensatory models using decision times.

## Key findings

- The SPA model mimics compensatory choices but is outperformed by the WAV model when analyzing decision times.
- Most participants (70%) used compensatory strategies, contradicting earlier assumptions about simplified heuristics.
- Individual differences in decision strategies were observed, with 30% using a TTB-like approach.

## Abstract

Recent research on multi-attribute decision-making has challenged the view that in open-view conditions, under time pressure, humans mostly rely on simplified strategies that only examine part of the choice information, as in Take the Best (TTB) or the priority heuristics. Here we examine and test a probabilistic extension of TTB which preserves the central heuristic idea that each decision is made based on a single attribute but selects this attribute probabilistically (rather than deterministically as in TTB) and maintains choice accuracy at levels found in human data. We show that this single probabilistic attribute (SPA) model produces choice patterns similar to the compensatory (normative) weighted-average (WAV) model, and we computationally compare the SPA model with a similar model called gTTB (Bergert & Nosofsky, Journal of Experimental Psychology: Learning, Memory, and Cognition, 33:107, 2007), showing that SPA provides better fit for 3 attributes to choice data (and about equal fit for 4 and 5 attributes). We then show that the heuristic (SPA/gTTB) and compensatory (WAV) models can be distinguished based on decision times, by contrasting high vs. low choice-polarization trials. To arbitrate between the SPA and the normative model, we collected data on a speeded multi-attribute decision task with 3, 4 and 5 numerical attributes, in a main and a replication experiment (total N = 117 participants). Our data shows significant individual differences in decision strategy. While about 30% of the participants appear to deploy a TTB strategy, the majority (70%) show choices that are consistent with either the SPA or the WAV models. Contrary to Bergert and Nosofsky (Bergert & Nosofsky, Journal of Experimental Psychology: Learning, Memory, and Cognition, 33:107, 2007), we found that the examination of decision-time provided strong evidence against the SPA model and supported instead the normative weighted-average account: when presented with choice information in free view most participants were able to carry out fast (mean-RT < 1.5 s) and compensatory decisions that attend to (and weight) all choice attributes.

The online version contains supplementary material available at 10.3758/s13423-025-02795-2.