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Massachusetts Institute of Technology

Optimal Targeting under Gender Fairness

Abstract

dc:description.abstract

While targeted marketing campaigns can offer high potential for increased firms’ profit, they often lack due consideration for fairness among different protected demographic groups. We investigate methods to mitigate gender disparities for both firm’s actions and benefit outcomes in the setting of offer allocations for targeted marketing campaigns. We develop and compare four optimization models to identify the optimal policies that maximize the firm’s financial return while concurrently satisfying relevant gender fairness conditions. Our results reveal that only regulating the gender disparity in the firm’s actions is not sufficient to guarantee that the responding customers of either gender receive similar level of discount benefit. Hence, we recommend firms to design policies by directly solving for the same level of benefit outcomes instead of firms’ actions across gender. Among the four models developed in this thesis, the optimal transport model is the only model that simultaneously meet both the group fairness condition in aggregate and the conditional demographic parity condition within each socioeconomic segment. Our results in the empirical setting show that the optimal policies from the optimal transport model achieve the lowest gender disparity in overall benefit outcomes. These policies also demonstrate the minimum level of firm manipulation across the four models, and provide the most discounts to the most female-concentrated neighborhoods.

Degree

thesis:*
Name thesis:degree_name
Master
Department dc:contributor.department
Massachusetts Institute of Technology. Operations Research Center
Grantor dc:publisher
Massachusetts Institute of Technology
Year dc:date.issued
2022

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Niu, Yumeng
Advisors dc:contributor.advisor
  • Freund, Robert
  • Simester, Duncan

Rights

dc:rights
Statement dc:rights
  • In Copyright - Educational Use Permitted
  • Copyright MIT

Identifiers

dc:identifier.*
Handle dc:identifier.uri
https://hdl.handle.net/1721.1/144995
OAI identifier oai:identifier
oai:dspace.mit.edu:1721.1/144995

Chain of custody

source
Harvested from
MIT
Base URL
dspace.mit.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
related terms
citation

Niu, Yumeng. Optimal Targeting under Gender Fairness. Massachusetts Institute of Technology, 2022. https://hdl.handle.net/1721.1/144995