A distance-based aggregation method for finding consensus in preference-approvals

This paper proposes a distance-based aggregation and consensus method for preference-approvals with potential applications in group decision-making, recommendation systems, and social choice theory. Preference-approvals are a type of preference data where individuals provide a list of approved alternatives in addition to a strict ranking. The proposed method aims to synthesise individual preference-approvals into a unified consensus representing the group’s collective view. The consensus is the preference-approval, which minimises the average distance within the whole set of voters. The performance of the proposed method is investigated through a sensitivity analysis on the weighting parameter, two simulation studies, and two real-data applications.

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Publication Details

Journal
Advances in Data Analysis and Classification
Published
2026-01-06
DOI
https://doi.org/10.1007/s11634-025-00663-4
Primary Topic
Game Theory and Voting Systems
Type
article
Field-Weighted Citation Impact
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article

A distance-based aggregation method for finding consensus in preference-approvals

Alessandro Albano, Maurizio Romano
Advances in Data Analysis and Classification
Game Theory and Voting Systems
article

A distance-based aggregation method for finding consensus in preference-approvals

Alessandro Albano, Maurizio Romano
article en

Abstract

This paper proposes a distance-based aggregation and consensus method for preference-approvals with potential applications in group decision-making, recommendation systems, and social choice theory. Preference-approvals are a type of preference data where individuals provide a list of approved alternatives in addition to a strict ranking. The proposed method aims to synthesise individual preference-approvals into a unified consensus representing the group’s collective view. The consensus is the preference-approval, which minimises the average distance within the whole set of voters. The performance of the proposed method is investigated through a sensitivity analysis on the weighting parameter, two simulation studies, and two real-data applications.

Advances in Data Analysis and Classification
University of Cagliari (IT), University of Palermo (IT)
Peace, Justice and strong institutions, Reduced inequalities
Openalex Percentile: Top 96%
Game Theory and Voting Systems
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