The DOI matches its Crossref record; 62 of the 63 references it cites were found in a registry or an index.
Content for Free? Drivers of Past Payment, Paying Intent and Willingness to Pay for Digital Journalism – A Systematic Literature Review
Abstract
The advertising-based revenue model for journalism is severely challenged due to the effects of digitization. Providers of journalistic content have therefore put increasing emphasis on paid content strategies in recent years. This article provides a literature review of factors that contribute to consumers’ past payment (PP), paying intent (PI) and willingness to pay (WTP) for digital journalistic content. We identify 17 variables based on 37 articles that influence PP, PI and WTP. While those factors are linked to either consumer(s), the product or its economics, little research examines the psychological needs and motives associated with demand for digital journalism. Due to inconsistent measurements in the literature, however, the results remain ambiguous.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“As a result, information consumption becomes more fragmented and less balanced.(O'Brien et al., 2020).”
From CHANGES IN PUBLIC INFORMATION CONSUMPTION PATTERNS IN THE DIGITAL ERA: A LITERATURE STUDY ON DIGITAL JOURNALISM (2025) · cites this paper as O'Brien et al., 2020
In the citing paper
“While this can increase the relevance of information, it can also narrow the spectrum of information consumed, creating a 'filter bubble' where users are not exposed to different perspectives.”
From CHANGES IN PUBLIC INFORMATION CONSUMPTION PATTERNS IN THE DIGITAL ERA: A LITERATURE STUDY ON DIGITAL JOURNALISM (2025) · cites this paper as O'Brien et al., 2020
In the citing paper
“Many digital platforms use algorithms to tailor the news and information that appears to users based on their browsing habits and preferences.”
From CHANGES IN PUBLIC INFORMATION CONSUMPTION PATTERNS IN THE DIGITAL ERA: A LITERATURE STUDY ON DIGITAL JOURNALISM (2025) · cites this paper as O'Brien et al., 2020
Citations
Cites
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“However, studies on trust in e-commerce suggest that trust and perceived risk of a product have a strong impact on PI (Kim, Ferrin, and Rao 2008).”
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Cited by
Items 101–102 of 102
A Bibliometric and Visualized Analysis of Digital Payment 2019-2021
Susanti, M., & Reza, H. K. (2023) · International Journal of Intelligent Systems and Applications in Engineering
Goyanes, M., Urbániková, M., & Jordá, B. (2026) · Journalism · doi:10.1177/14648849261496571
Metadata
- Authors
- O’Brien, D., Wellbrock, C.-M., & Kleer, N.
- Affiliations
- University of Cologne (DE)
- Corresponding author
- O’Brien, Daniel
- Venue
- Digital Journalism
- Publisher
- Informa UK Limited
- Published
- 2020-05-27
- Volume
- 8
- Issue
- 5
- Pages
- 643-672
- ISSN
- 2167-0811 (ISSN-L)
- 2167-082X
- OpenAlex
- W3033217106
- Cited by
- 90
- References
- 63
- Citations by year
- 2026: 11 · 2025: 16 · 2024: 13 · 2023: 23 · 2022: 14 · 2021: 12 · 2020: 1
- FWCI
- 4.37
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Digital Journalism (publishedVersion)
- Kölner Universitäts PublikationsServer (Universität zu Köln) (publishedVersion)
- Topics
- Social Sciences › Communication › Journalism and Media Studies
- Social Sciences › Communication › News Media Framing and Political Communication
- Social Sciences › Library and Information Sciences › Publishing and Scholarly Communication
- Keywords
- paid content, willingness to pay, consumer behavior, advertising revenue model, content pricing, psychological motives
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.
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
