The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
The Influence of Avatars on Online Consumer Shopping Behavior
Abstract
An impediment to Web-based retail sales is the impersonal nature of Web-based shopping. A solution to this problem is to use an avatar to deliver product information. An avatar is a graphic representation that can be animated by means of computer technology. Study 1 shows that using an avatar sales agent leads to more satisfaction with the retailer, a more positive attitude toward the product, and a greater purchase intention. Study 2 shows that an attractive avatar is a more effective sales agent at moderate levels of product involvement, but an expert avatar is a more effective sales agent at high levels of product involvement.
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
Baron, R. M., & Kenny, D. A. (1986) · Journal of Personality and Social Psychology · doi:10.1037/0022-3514.51.6.1173 · Cited by 91,532
Mass Communication and Para-Social Interaction
Horton, D., & Richard Wohl, R. (1956) · Psychiatry · doi:10.1080/00332747.1956.11023049 · Cited by 4,380
Dion, K., Berscheid, E., & Walster, E. (1972) · Journal of Personality and Social Psychology · doi:10.1037/h0033731 · Cited by 3,865
On the practice of dichotomization of quantitative variables.
MacCallum, R. C., Zhang, S., Preacher, K. J., & Rucker, D. D. (2002) · Psychological Methods · doi:10.1037/1082-989x.7.1.19 · Cited by 3,538
Intimate Exchanges: Using Computers to Elicit Self-Disclosure from Consumers
Moon, Y. (2000) · Journal of Consumer Research · doi:10.1086/209566 · Cited by 842
Effects of rhetorical questions on persuasion: A cognitive response analysis.
Petty, R. E., Cacioppo, J. T., & Heesacker, M. (1981) · Journal of Personality and Social Psychology · doi:10.1037/0022-3514.40.3.432 · Cited by 272
Cited by
AI-based chatbots in customer service and their effects on user compliance
Adam, M., Wessel, M., & Benlian, A. (2021) · Electronic Markets · doi:10.1007/s12525-020-00414-7 · Cited by 1,195
“…and Benbasat 2009) and particularly important for service encounters and online sales, for example on company websites (e.g., Etemad-Sajadi 2016; Holzwarth et al. 2006), in virtual worlds (e.g., Jin 2009; Jin and Sung 2010), and even in physical interactions with robots in stores (Bertacchini…”
BackgroundAraujo, T. (2018) · Computers in Human Behavior · doi:10.1016/j.chb.2018.03.051 · Cited by 1,156
Pelau, C., Dabija, D.-C., & Ene, I. (2021) · Computers in Human Behavior · doi:10.1016/j.chb.2021.106855 · Cited by 889
Qiu, L., & Benbasat, I. (2009) · Journal of Management Information Systems · doi:10.2753/mis0742-1222250405 · Cited by 737
An Emerging Theory of Avatar Marketing
Miao, F., Kozlenkova, I. V., Wang, H., Xie, T., & Palmatier, R. W. (2022) · Journal of Marketing · doi:10.1177/0022242921996646 · Cited by 688
Metadata
- Authors
- Holzwarth, M., Janiszewski, C., & Neumann, M. M.
- Venue
- Journal of Marketing
- Publisher
- SAGE Publications
- Published
- 2006-10
- Volume
- 70
- Issue
- 4
- Pages
- 19-36
- ISSN
- 0022-2429 (ISSN-L)
- 1547-7185
- OpenAlex
- W2163846111
- Cited by
- 810
- References
- 6
- FWCI
- 21.05
- 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.
