Seeing the trade-offs: Evaluating visualizations for multi-criteria comparison of set alternatives-test

Comparisons are central in multi-criteria decision-making, where alternatives must be evaluated across multiple, often conflicting goals. This process becomes especially complex when alternatives are grouped into sets. Based on formative research with domain experts, we first characterize set comparisons in trade-off analysis. In two design workshops, we identify potential visualization solutions to support them. Finally, we conduct a user study with lay participants and collect expert feedback to evaluate the two most promising visualizations that encode trade-offs, alongside a baseline that conveys this information numerically. Our findings show that visual encodings are preferred. The decoupled visual encoding, which separates different trade-off metrics, is favored by the domain expert. For non-experts, this decoupled visualization leads to higher perceived mental load and lower confidence although it may support more varied decision strategies. In contrast, the coupled visualization that integrates these metrics, results in higher confidence but may promote strategies that min-max only the top priorities. Supplementary material are available at https://osf.io/xnbm2/overview?view_only=4b5b940dce0f4ced8b933d9eaceaf3f5 .

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Publication Details

Journal
Information Visualization
Published
2026-06-30
DOI
https://doi.org/10.1177/14738716261457001
Primary Topic
Data Visualization and Analytics
Type
article
Field-Weighted Citation Impact
0.00

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article

Seeing the trade-offs: Evaluating visualizations for multi-criteria comparison of set alternatives-test

Mehdi Chakhchoukh, Nadia Boukhelifa, Anastasia Bezerianos
Information Visualization
Data Visualization and Analytics
article

Seeing the trade-offs: Evaluating visualizations for multi-criteria comparison of set alternatives-test

Mehdi Chakhchoukh, Nadia Boukhelifa, Anastasia Bezerianos
article en

Abstract

Comparisons are central in multi-criteria decision-making, where alternatives must be evaluated across multiple, often conflicting goals. This process becomes especially complex when alternatives are grouped into sets. Based on formative research with domain experts, we first characterize set comparisons in trade-off analysis. In two design workshops, we identify potential visualization solutions to support them. Finally, we conduct a user study with lay participants and collect expert feedback to evaluate the two most promising visualizations that encode trade-offs, alongside a baseline that conveys this information numerically. Our findings show that visual encodings are preferred. The decoupled visual encoding, which separates different trade-off metrics, is favored by the domain expert. For non-experts, this decoupled visualization leads to higher perceived mental load and lower confidence although it may support more varied decision strategies. In contrast, the coupled visualization that integrates these metrics, results in higher confidence but may promote strategies that min-max only the top priorities. Supplementary material are available at https://osf.io/xnbm2/overview?view_only=4b5b940dce0f4ced8b933d9eaceaf3f5 .

Information Visualization
Centre National de la Recherche Scientifique (FR), Université Paris-Saclay (FR), Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement (FR), Centre Inria de Saclay (FR), Laboratoire Matière et Systèmes Complexes (FR)
Agence Nationale de la Recherche, Ecoles doctorales, Université Paris-Saclay
Peace, Justice and strong institutions
Openalex Percentile: Top 8%
Data Visualization and Analytics
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