Journal article
Protecting survey data on a consumer level
Journal of marketing analytics, v 8(1)
01 Mar 2020
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
This paper offers an easy-to-implement approach to protect multivariate survey data common in marketing, such as attitudes and demographics. Our approach preserves multivariate distributions by releasing a protected data set with privacy protections. The data represent a highly detailed multivariate survey with severe privacy issues that enables us to demonstrate the tradeoff between data utility and data privacy. We create a data privacy metric that quantifies the ability of a data intruder successfully identify survey respondents and their sensitive responses. We provide data privacy measurements for a variety of competitor methods such as sampling and random noise addition and we show that by comparison, our approach can prevent a data intruder from targeting individuals while maintaining a very high level of data utility.
Metrics
Details
- Title
- Protecting survey data on a consumer level
- Creators
- Matthew J. Schneider - Drexel UniversityDawn Iacobucci - Vanderbilt University
- Publication Details
- Journal of marketing analytics, v 8(1)
- Publisher
- Springer Nature
- Number of pages
- 15
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Decision Sciences (and Management Information Systems)
- Web of Science ID
- WOS:000538569100002
- Scopus ID
- 2-s2.0-85082306729
- Other Identifier
- 991019169652704721
UN Sustainable Development Goals (SDGs)
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InCites Highlights
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- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Business