The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
The Inference of Perceived Usability From Beauty
Abstract
A review of 15 papers reporting 25 independent correlations of perceived beauty with perceived usability showed a remarkably high variability in the reported coefficients. This may be due to methodological inconsistencies. For example, products are often not selected systematically, and statistical tests are rarely performed to test the generality of findings across products. In addition, studies often restrict themselves to simply reporting correlations without further specification of underlying judgmental processes. The present study's main objective is to re-examine the relation between beauty and usability, that is, the implication that “what is beautiful is usable.” To rectify previous methodological shortcomings, both products and participants were sampled in the same way and the data aggregated both by averaging over participants to assess the covariance across ratings of products and by averaging over products to assess the covariance across participants. In addition, we adopted an inference perspective to qualify underlying processes to examine the possibility that, under the circumstances pertaining in most studies of this kind where participants have limited experience of using a website or product, the relationship between beauty and usability is mediated by goodness. A mediator analysis of the relationship between beauty, the overall evaluation (i.e., “goodness”) and pragmatic quality (as operationalization of usability) suggests that the relationship between beauty and usability has been overplayed as the correlation between pragmatic quality and beauty is wholly mediated by goodness. This pattern of relationships was consistent across four different data sets and different ways of data aggregation. Finally, suggestions are made regarding methodologies that could be used in future studies that build on these results.
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.
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
SPSS and SAS procedures for estimating indirect effects in simple mediation models
Preacher, K. J., & Hayes, A. F. (2004) · Behavior Research Methods, Instruments, & Computers · doi:10.3758/bf03206553 · Cited by 17,383
Asymptotic Confidence Intervals for Indirect Effects in Structural Equation Models
Sobel, M. E. (1982) · Sociological Methodology · doi:10.2307/270723 · Cited by 12,810
Dion, K., Berscheid, E., & Walster, E. (1972) · Journal of Personality and Social Psychology · doi:10.1037/h0033731 · Cited by 3,865
Tractinsky, N., Katz, A. S., & Ikar, D. (2000) · Interacting with Computers · doi:10.1016/s0953-5438(00)00031-x · Cited by 1,376
The Thing and I: Understanding the Relationship Between User and Product
Hassenzahl, M. (2003) · Human-Computer Interaction Series · doi:10.1007/1-4020-2967-5_4 · Cited by 1,097
Self-citationRetrieval selectivity in memory-based impression judgments.
Lingle, J. H., & Ostrom, T. M. (1979) · Journal of Personality and Social Psychology · doi:10.1037/0022-3514.37.2.180 · Cited by 256
(2003) · Berichte des German Chapter of the ACM · doi:10.1007/978-3-322-80058-9 · Cited by 62
Cited by
Boyle, E. A., Hainey, T., Connolly, T. M., Gray, G., Earp, J., Ott, M., Lim, T., Ninaus, M., Ribeiro, C., & Pereira, J. (2016) · Computers & Education · doi:10.1016/j.compedu.2015.11.003 · Cited by 1,133
Needs, affect, and interactive products – Facets of user experience
Hassenzahl, M., Diefenbach, S., & Göritz, A. (2010) · Interacting with Computers · doi:10.1016/j.intcom.2010.04.002 · Cited by 867
Self-citationBargas-Avila, J. A., & Hornbæk, K. (2011) · Proceedings of the SIGCHI Conference on Human Factors in Computing Systems · doi:10.1145/1978942.1979336 · Cited by 660
Hertzum (2017) · doi:10.1145/3127358 · Cited by 307
Draxler, F., Werner, A., Lehmann, F., Hoppe, M., Schmidt, A., Buschek, D., & Welsch, R. (2024) · ACM Transactions on Computer-Human Interaction · doi:10.1145/3637875 · Cited by 186
“…antonymous adjective pairs: (1) the pragmatic quality or usability of a product, its hedonic quality or pleasantness in terms of (2) stimulation , i.e., being inspiring and facilitating personal development, (3) identity , i.e., communicating a desired identity, and (4) its overall appeal [48, 49].”
BackgroundMethodJuicy Game Design: Understanding the Impact of Visual Embellishments on Player Experience
Hicks, K., Gerling, K., Dickinson, P., & Vanden Abeele, V. (2019) · Proceedings of the Annual Symposium on Computer-Human Interaction in Play · doi:10.1145/3311350.3347171 · Cited by 71
Understanding and Measuring User Experience in Conversational Interfaces
Kocaballi, A. B., Laranjo, L., & Coiera, E. (2019) · Interacting with Computers · doi:10.1093/iwc/iwz015 · Cited by 68
Vollenwyder, B., Petralito, S., Iten, G. H., Brühlmann, F., Opwis, K., & Mekler, E. D. (2023) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2022.102956 · Cited by 62
Significant Productivity Gains through Programming with Large Language Models
Weber, T., Brandmaier, M., Schmidt, A., & Mayer, S. (2024) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3661145 · Cited by 64
“Participants completed the short AttrakDiff [16, 18, 19] after each test condition to quantify satisfaction.”
Good Game Feel: An Empirically Grounded Framework for Juicy Design
Hicks, K., Dickinson, P., Holopainen, J., & Gerling, K. (2018) · DiGRA Digital Library · doi:10.26503/dl.v2018i1.936 · Cited by 30
Bellet, T., Banet, A., Petiot, M., Richard, B., & Quick, J. (2020) · Information · doi:10.3390/info12010013 · Cited by 12
(2018) · NCSU Libraries Repository (North Carolina State University Libraries) · Cited by 5
Metadata
- Authors
- Hassenzahl, M., & Monk, A.
- Venue
- Human-Computer Interaction
- Publisher
- Informa UK Limited
- Published
- 2010-07
- Volume
- 25
- Issue
- 3
- Pages
- 235-260
- ISSN
- 0737-0024 (ISSN-L)
- OpenAlex
- W2071575120
- Cited by
- 330
- References
- 7
- FWCI
- 33.16
- Type
- journal article
- Language
- en
- Open access
- closed
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
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.