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
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.
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Citations
Cites
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Cognitive Fit: A Theory‐Based Analysis of the Graphs Versus Tables Literature*
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The Effects of Personalization and Familiarity on Trust and Adoption of Recommendation Agents1
Komiak, S. Y. X., & Benbasat, I. (2006) · MIS Quarterly · doi:10.2307/25148760 · Cited by 1,374
E-Commerce Product Recommendation Agents: Use, Characteristics, and Impact1
Xiao, B., & Benbasat, I. (2007) · MIS Quarterly · doi:10.2307/25148784 · Cited by 1,081
Syam, N., & Sharma, A. (2018) · Industrial Marketing Management · doi:10.1016/j.indmarman.2017.12.019 · Cited by 852
On Product Uncertainty in Online Markets: Theory and Evidence1
Dimoka, A., Hong, Y., & Pavlou, P. A. (2012) · MIS Quarterly · doi:10.2307/41703461 · Cited by 682
Virtual reality as a patient education tool in healthcare: A scoping review
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Sun, C., Fang, Y., Kong, M., Chen, X., & Liu, Y. (2022) · Journal of Retailing and Consumer Services · doi:10.1016/j.jretconser.2021.102828 · Cited by 148
Curbing shopping cart abandonment in C2C markets — an uncertainty reduction approach
Tang, H., & Lin, X. (2019) · Electronic Markets · doi:10.1007/s12525-018-0313-6 · Cited by 56
Using authentic 3D product visualisation for an electrical online retailer
Algharabat, R., & Dennis, C. (2010) · Journal of Customer Behaviour · doi:10.1362/147539210x511326 · Cited by 49
Seeing the Bigger Picture? Ramping up Production with the Use of Augmented Reality
Wuttke, D., Upadhyay, A., Siemsen, E., & Wuttke-Linnemann, A. (2022) · Manufacturing & Service Operations Management · doi:10.1287/msom.2021.1070 · Cited by 36
Health Website Success: User Engagement in Health-Related Websites
Imlawi, J. (2017) · International Journal of Interactive Mobile Technologies (iJIM) · doi:10.3991/ijim.v11i6.6959 · Cited by 14
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
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