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Privacy in the Digital Age: a Review of Information Privacy Research in Information Systems1
Open accessAbstract
Information privacy refers to the desire of individuals to control or have some influence over data about themselves. Advances in information technology have raised concerns about information privacy and its impacts, and have motivated Information Systems researchers to explore information privacy issues, including technical solutions to address these concerns. In this paper, we inform researchers about the current state of information privacy research in IS through a critical analysis of the IS literature that considers information privacy as a key construct. The review of the literature reveals that information privacy is a multilevel concept, but rarely studied as such. We also find that information privacy research has been heavily reliant on student-based and USA-centric samples, which results in findings of limited generalizability. Information privacy research focuses on explaining and predicting theoretical contributions, with few studies in journal articles focusing on design and action contributions. We recommend that future research should consider different levels of analysis as well as multilevel effects of information privacy. We illustrate this with a multilevel framework for information privacy concerns. We call for research on information privacy to use a broader diversity of sampling populations, and for more design and action information privacy research to be published in journal articles that can result in IT artifacts for protection or control of information privacy.
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“Consumer trust in online platforms is contingent upon transparent and ethical data management practices (Bélanger & Crossler, 2011).”
From Feeling Watched: A Phenomenological Exploration of Consumer Discomfort and Data Privacy Concerns in E-Commerce Personalized Email Marketing (2025) · cites this paper as Bélanger & Crossler, 2011
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“Moreover, supported research highlighted that clear communication about data use policies builds consumer trust in digital environments (Bélanger & Crossler, 2011).”
From Feeling Watched: A Phenomenological Exploration of Consumer Discomfort and Data Privacy Concerns in E-Commerce Personalized Email Marketing (2025) · cites this paper as Bélanger & Crossler, 2011
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Metadata
- Authors
- Bélanger, F., & Crossler, R. E.
- Affiliations
- Pamplin College of Business, Virginia Tech, 3007 Pamplin Hall, Blacksburg, VA 24061-0101 U.S.A.
- Mississippi State University (US)
- ORCID
- Crossler, Robert E.
- Venue
- MIS Quarterly
- Publisher
- MIS Quarterly
- Published
- 2011-12-01
- Volume
- 35
- Issue
- 4
- Pages
- 1017-A36
- ISSN
- 0276-7783 (ISSN-L)
- 2162-9730
- OpenAlex
- W1870146437
- Cited by
- 1,339
- References
- 501
- Citations by year
- 2026: 108 · 2025: 94 · 2024: 110 · 2023: 112 · 2022: 114 · 2021: 111 · 2020: 112 · 2019: 88 · 2018: 107 · 2017: 74 · 2016: 83 · 2015: 89 · 2014: 70 · 2013: 40 · 2012: 23
- FWCI
- 145.71
- Type
- journal article
- Language
- en
- Open access
- green
- hdl.handle.net
- Locations
- MIS Quarterly (publishedVersion)
- VTechWorks (Virginia Tech) (submittedVersion)
- Topics
- Social Sciences › Sociology and Political Science › Privacy, Security, and Data Protection
- Physical Sciences › Computer Science › Artificial Intelligence › Privacy-Preserving Technologies in Data
- Physical Sciences › Computer Science › Information Systems › Information and Cyber Security
- Keywords
- data privacy, multilevel analysis, multi-level framework, privacy concerns, privacy preservation, data control, digital era
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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