Privacy-Preserving Data Fusion

Marketing Science 2026

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Authors: Longxiu Tian, Dana Turjeman, Samuel Levy
DOI: 10.1287/mksc.2023.0068
Cited by: 1
References: 51

Abstract

This paper proposes a generative methodology enabling companies to combine data sets with strong privacy guarantees and near-optimal performance in customer analytics.

Fields of Study & Subjects

Privacy-Preserving Technologies in Data Privacy Security and Data Protection Data Quality and Management

Publication details

Journal / source
Marketing Science
Publisher
Institute for Operations Research and the Management Sciences (INFORMS)
Volume
45
Issue
5
Pages
930–953
Publication date
1 April 2026
Language
EN