The DOI matches its Crossref record; 53 of the 53 references it cites were found in a registry or an index.
Artificial Intelligence Creates Art? An Experimental Investigation of Value and Creativity Perceptions
Open accessAbstract
ABSTRACT This paper presents a study analyzing the perception of artistic products created by or with the support of artificial intelligence (AI). The research builds on previous studies revealing that the output of artificial creativity processes can indeed rival human‐made products, satisfy consumer expectations, and derive enjoyment. However, in contrast to earlier works, the study focuses on the awareness of how AI is used during production processes (full automation, human‐AI co‐creation, and solely human) and product types (levels of involvement and product tangibility). A laboratory experiment was conducted to compare the value and creativity perceptions of 199 participants. Results revealed that, overall, the use of AI enhanced perceptions of process novelty. Additionally, the use of AI led to more positive evaluations of intangible and high involvement products such as songs compared to tangible and high involvement products such as paintings. This shows a decrease in perceived quality as more AI is involved in the production process. Furthermore, the level of product involvement level indicated no causal relationship to the degree of AI used in the production process.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
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?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Equipped with a vast knowledge base and divergent thinking, AI can generate unexpected ideas and thus evoke a stronger sense of novelty (Doshi and Hauser, 2024; Tigre Moura et al., 2023)”
From From humans to AI: understanding why AI is perceived as the preferred co-creation partner (2025) · cites this paper as Tigre Moura et al., 2023
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
SERVQUAL: A multiple-Item Scale for measuring consumer perceptions of service quality
Parasuraman, A., Berry, L. L., & Zeithaml, V. A. (1988) · Zenodo · doi:10.5281/zenodo.14579729 · Cited by 21,118
(2017) · Cited by 16,319
Proceedings of the 24th international conference on Machine learning
(2007) · doi:10.1145/1273496 · Cited by 11,869
A Style-Based Generator Architecture for Generative Adversarial Networks
Karras, T., Laine, S., & Aila, T. (2019) · 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2019.00453 · Cited by 11,714
Consumer Perceived Value: The Development of a Multiple Item Scale
Sweeney, J. C., & Soutar, G. N. (2001) · Journal of Retailing · doi:10.1016/s0022-4359(01)00041-0 · Cited by 6,643
Research Methods for Business Students
(2000) · Qualitative Market Research An International Journal · doi:10.1108/qmr.2000.3.4.215.2 · Cited by 5,631
Hedonic Consumption: Emerging Concepts, Methods and Propositions
Hirschman, E. C., & Holbrook, M. B. (1982) · Journal of Marketing · doi:10.1177/002224298204600314 · Cited by 5,616
Generative Adversarial Networks
Goodfellow, I. J., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A., & Bengio, Y. (2014) · arXiv · doi:10.48550/arxiv.1406.2661 · Cited by 4,477
Creative industries: contracts between art and commerce
(2000) · Choice Reviews Online · doi:10.5860/choice.38-1661 · Cited by 1,957
Attitude Structure and Function.
Schuman, H., Pratkanis, A. R., Breckler, S., & Greenwald, A. G. (1990) · Contemporary Sociology A Journal of Reviews · doi:10.2307/2072868 · Cited by 1,301
Research works printed but not linked: 7
- Blythe J., 2013, Consumer behavior
- Epstein S., 2003, Handbook of psychology. Personality and social psychology, 159
- Ferrell O.C., 2008, Marketing strategy
- Jacob B., 1995, Composing with genetic algorithms, in International Computer Music Conference (ICMC)
- Liang Y., 2018, International Textile and Apparel Association Annual Conference Proceedings, 4401
- Machado P., 2021, Artificial intelligence and the arts‐computational creativity, artistic behavior, and tools for creatives
- Solomon M., 2016, Consumer behaviour
Cited by
Sorted by citations
Liu, Y.-L. E., & Huang, Y.-M. (2025) · International Journal of Human–Computer Interaction · doi:10.1080/10447318.2024.2311975 · Cited by 47
Perception of AI creativity: dimensional exploration and scale development
Yang, Y., & Xu, H. (2025) · The Journal of Creative Behavior · doi:10.1002/jocb.70028 · Cited by 15
From humans to AI: understanding why AI is perceived as the preferred co-creation partner
Liu, Y., Yang, Y., & Xu, H. (2025) · Frontiers in Psychology · doi:10.3389/fpsyg.2025.1695532 · Cited by 10
AI-generated versus human-created advertising: Effects on consumer trust and purchase intent
Israfilzade, K. (2025) · Equilibrium. Quarterly Journal of Economics and Economic Policy · doi:10.24136/eq.4038 · Cited by 21
Metadata
- Authors
- Tigre Moura, F., Castrucci, C., & Hindley, C.
- Affiliations
- IU University of Applied Sciences
- IU International University of Applied Sciences (DE)
- Venue
- The Journal of Creative Behavior
- Publisher
- Wiley
- Published
- 2023-06-27
- Volume
- 57
- Issue
- 4
- Pages
- 534-549
- ISSN
- 0022-0175 (ISSN-L)
- 2162-6057
- OpenAlex
- W4382458172
- Cited by
- 79
- References
- 53
- Citations by year
- 2026: 29 · 2025: 33 · 2024: 14 · 2023: 1
- FWCI
- 11.50
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- The Journal of Creative Behavior (publishedVersion, cc-by)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Aesthetic Perception and Analysis
- Social Sciences › Business, Management and Accounting › Marketing › Consumer Behavior in Brand Consumption and Identification
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Creativity in Education and Neuroscience
- Keywords
- artificial intelligence, AI-generated art, creativity perception, perceived value, human-AI co-creation, full automation, product involvement, perceived quality, painting
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 ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Artificial Intelligence Creates Art? An Experimental Investigation of Value and Creativity Perceptions. https://app.cochat.ai/papers/10.1002/jocb.600
- The paper
- Tigre Moura, F., Castrucci, C., & Hindley, C. (2023). Artificial Intelligence Creates Art? An Experimental Investigation of Value and Creativity Perceptions. The Journal of Creative Behavior. https://doi.org/10.1002/jocb.600
