Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 508

The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.

The Effects of Virtual Reality on Consumer Learning: An Empirical Investigation1

Suh, Kil-Soo, Lee, Young Eun·2005·MIS Quarterly

Abstract

As competition in business-to-consumer e-commerce becomes fiercer, Web-based stores are attempting to attract consumers’ attention by exploiting state-of-the-art technologies. Virtual reality (VR) on the Internet has been gaining prominence recently because it enables consumers to experience products realistically over the Internet, there by mitigating the problems associated with consumers’ lack of physical contact with products. However, while the employment of VR has increased in B2C e-commerce, its impact has not been explored extensively by research in the IS field. This study investigates whether and under what circumstances VR enhances consumer learning about products. In general, VR enables consumers to learn about products thoroughly by providing high-quality three-dimensional images of products, interactivity with the products, and increased telepresence. In addition, congruent with the theory of cognitive fit, the effects of VR are more pronounced when it exhibits products whose salient attributes are completely apparent through visual and auditory cues (because most VR on desktop computers uses only those two sensory modalities to deliver information). Based on these attributes, we distinguish between two types of products—namely, virtually high experiential (VHE) and virtually low experiential (VLE) products—in terms of the sensory modalities that are used and required for product inspection. Hypotheses arising from the distinctions expressed by these terms were tested via a laboratory experiment. The results support the predictions that VR interfaces increase overall consumer learning about products and that these effects extend to VHE products more significantly than to VLE products.

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.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.2307/25148705

Cites

6 of 6 references verified0 citation errors · 0 not checkable

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.

A few free checks a day · papers already verified open instantly · results are public

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

Show all 6 references

Cited by

See all 508

Metadata

Authors
Suh, K.-S., & Lee, Y. E.
Venue
MIS Quarterly
Publisher
MIS Quarterly
Published
2005-12-01
Volume
29
Issue
4
Pages
673-698
ISSN
  • 0276-7783 (ISSN-L)
  • 2162-9730
OpenAlex
W1733635077
Cited by
508
References
6
FWCI
16.72
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

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 Effects of Virtual Reality on Consumer Learning: An Empirical Investigation1. https://app.cochat.ai/papers/10.2307/25148705
The paper
Suh, K.-S., & Lee, Y. E. (2005). The Effects of Virtual Reality on Consumer Learning: An Empirical Investigation1. MIS Quarterly. https://doi.org/10.2307/25148705

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.