TY - JOUR
T1 - Segmentation, incentives, and privacy
AU - Nissim, Kobbi
AU - Smorodinsky, Rann
AU - Tennenholtz, Moshe
N1 - Funding Information:
This work was supported by the National Science Foundation (NSF) [Grant CNS-1237235] and grants from the Sloan Foundation. The research of R. Smorodinsky is supported by the Israel Science Foundation [Grant 276/12], the United States-Israel Binational Science Foundation, and NSF [Grant 2016734]; by the German-Israel Foundation [Grant I-1419-118.4/2017]; by the Ministry of Science and Technology [Grant 19400214]; and by Technion VPR grants and the Bernard M. Gordon Center for Systems Engineering at the Technion. M. Tennenholtz gratefully acknowledges the support of the European Union [Project 740435] (Mechanism Design for Data Science).
Publisher Copyright:
Copyright: © 2018 INFORMS.
PY - 2018/1/1
Y1 - 2018/1/1
N2 - Data-driven segmentation is the powerhouse behind the success of online advertising. Various underlying challenges for successful segmentation have been studied by the academic community, with one notable exception-consumers' incentives have been typically ignored. This lacuna is troubling, as consumers have much control over the data being collected. Missing or manipulated data could lead to inferior segmentation. The current work proposes a model of prior-free segmentation, inspired by models of facility location and, to the best of our knowledge, provides the first segmentation mechanism that addresses incentive compatibility, efficient market segmentation, and privacy in the absence of a common prior.
AB - Data-driven segmentation is the powerhouse behind the success of online advertising. Various underlying challenges for successful segmentation have been studied by the academic community, with one notable exception-consumers' incentives have been typically ignored. This lacuna is troubling, as consumers have much control over the data being collected. Missing or manipulated data could lead to inferior segmentation. The current work proposes a model of prior-free segmentation, inspired by models of facility location and, to the best of our knowledge, provides the first segmentation mechanism that addresses incentive compatibility, efficient market segmentation, and privacy in the absence of a common prior.
KW - Facility location
KW - Marketing segmentation
KW - Noncooperative games
UR - http://www.scopus.com/inward/record.url?scp=85059961248&partnerID=8YFLogxK
U2 - 10.1287/moor.2017.0903
DO - 10.1287/moor.2017.0903
M3 - Article
AN - SCOPUS:85059961248
SN - 0364-765X
VL - 43
SP - 1252
EP - 1268
JO - Mathematics of Operations Research
JF - Mathematics of Operations Research
IS - 4
ER -