The DOI matches its Crossref record; 107 of the 107 references it cites were found in a registry or an index.
The role of data privacy in marketing
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“the collection and utilization of consumer data by AI and analytical algorithms via social media give rise to serious issues regarding invasion of consumers' privacy, fraud, offensive or harmful marketing appeals, lack of transparency, information leakage and identity theft (Martin & Murphy, 2017).”
From Setting the future of digital and social media marketing research: Perspectives and research propositions (2021) · cites this paper as Martin & Murphy, 2017
In the citing paper
“Consumer concerns regarding data privacy, and their ability to trust brands and platforms are not new (for a review on data privacy see Martin and Murphy 2017).”
From The future of social media in marketing (2020) · cites this paper as Martin and Murphy 2017
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Metadata
- Authors
- Martin, K. D., & Murphy, P. E.
- Affiliations
- Colorado State University (US)
- University of Notre Dame (US)
- Corresponding author
- Martin, Kelly D.
- ORCID
- Martin, Kelly D.
- Venue
- Journal of the Academy of Marketing Science
- Published
- 2016-09-22
- Volume
- 45
- Issue
- 2
- Pages
- 135-155
- ISSN
- 0092-0703 (ISSN-L)
- 1552-7824
- OpenAlex
- W2521701804
- Semantic Scholar
- 0c0d9a7f8061ce76a83d14a7c78387569847d56b
- Cited by
- 902
- References
- 105
- Citations by year
- 2026: 196 · 2025: 162 · 2024: 116 · 2023: 90 · 2022: 89 · 2021: 83 · 2020: 79 · 2019: 46 · 2018: 25 · 2017: 13 · 2016: 3
- FWCI
- 82.92
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of the Academy of Marketing Science (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Topics
- Social Sciences › Sociology and Political Science › Privacy, Security, and Data Protection
- Social Sciences › Business, Management and Accounting › Marketing › Consumer Market Behavior and Pricing
- Physical Sciences › Computer Science › Artificial Intelligence › Privacy-Preserving Technologies in Data
- Keywords
- data privacy, marketing, economics of privacy, consumer privacy, privacy ethics, privacy law, stakeholder impact
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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