The DOI matches its Crossref record; 55 of the 55 references it cites were found in a registry or an index.
The effect of online restaurant menus on consumers’ purchase intentions during the COVID-19 pandemic
Open accessAbstract
As COVID-19 escalated globally in 2020, mandated suspension of dine-in services was instilled to control virus transmission. Restaurants lost billions of dollars, millions experienced severe employment changes, and numerous small restaurants closed. For those remaining in business, converting to online food ordering was essential. Unique to the food ordering setting, this study extended the Stimulus-Organism-Response model to predict the purchase intentions of participants in an online food ordering context. Using structural equation modeling, this study discovered the indirect effects of the menu’s visual appeal and informativeness, and the perception of COVID-19 risks on consumer purchase intentions. This causal relationship was significantly mediated by consumers’ desire for food and their perceived convenience of online food ordering. Through providing theoretical and managerial implications for how to identify appropriate products, utilize content marketing effectively, and attract new customers, this study could assist restaurants in adapting to remaining competitive, even post COVID-19.
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
Evaluating structural equation models with unobservable variables and measurement error
Fornell, C., & Larcker, D. F. (1981) · Journal of Marketing Research · doi:10.1177/002224378101800104 · Cited by 109,190
Tabachnick, B. G., & Fidell, L. S. (1983) · Cited by 79,866
(1974) · Medical Entomology and Zoology · Cited by 7,295
Introduction to Statistical Mediation Analysis
MacKinnon, D. P. (2012) · doi:10.4324/9780203809556 · Cited by 5,618
The Fear of COVID-19 Scale: Development and Initial Validation
Ahorsu, D. K., Lin, C.-Y., Imani, V., Saffari, M., Griffiths, M. D., & Pakpour, A. H. (2022) · International Journal of Mental Health and Addiction · doi:10.1007/s11469-020-00270-8 · Cited by 4,332
Understanding Service Convenience
Berry, L. L., Seiders, K., & Grewal, D. (2002) · Journal of Marketing · doi:10.1509/jmkg.66.3.1.18505 · Cited by 1,602
The Components of Perceived Risk
Jacoby, J., & Kaplan, L. B. (1972) · ACR Special Volumes · Cited by 1,248
Saper, C. B., Chou, T. C., & Elmquist, J. K. (2002) · Neuron · doi:10.1016/s0896-6273(02)00969-8 · Cited by 1,120
Hassanein, K., & Head, M. (2007) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2006.11.018 · Cited by 986
Consumer experiences, attitude and behavioral intention toward online food delivery (OFD) services
Yeo, V. C. S., Goh, S.-K., & Rezaei, S. (2017) · Journal of Retailing and Consumer Services · doi:10.1016/j.jretconser.2016.12.013 · Cited by 956
Cited by
Uzir, M. U. H., Al Halbusi, H., Thurasamy, R., Thiam Hock, R. L., Aljaberi, M. A., Hasan, N., & Hamid, M. (2021) · Journal of Retailing and Consumer Services · doi:10.1016/j.jretconser.2021.102721 · Cited by 478
Metadata
- Authors
- Brewer, P., & Sebby, A. G.
- Venue
- International Journal of Hospitality Management
- Publisher
- Elsevier BV
- Published
- 2021-04
- Volume
- 94
- Pages
- 102777
- ISSN
- 0278-4319 (ISSN-L)
- OpenAlex
- W3119546009
- Cited by
- 268
- References
- 55
- FWCI
- 51.23
- Type
- journal article
- Language
- en
- Open access
- green
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: The effect of online restaurant menus on consumers’ purchase intentions during the COVID-19 pandemic. https://app.cochat.ai/papers/10.1016/j.ijhm.2020.102777
- The paper
- Brewer, P., & Sebby, A. G. (2021). The effect of online restaurant menus on consumers’ purchase intentions during the COVID-19 pandemic. International Journal of Hospitality Management. https://doi.org/10.1016/j.ijhm.2020.102777
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.
