The DOI matches its Crossref record; 14 of the 14 references it cites were found in a registry or an index.
Metaverse marketing: How the metaverse will shape the future of consumer research and practice
Open accessAbstract
The initial hype and fanfare from the Meta Platforms view of how the metaverse could be brought to life has evolved into an ongoing discussion of not only the metaverse's impact on users and organizations but also the societal and cultural implications of widespread usage. The potential of consumer interaction with brands within the metaverse has engendered significant debate within the marketing‐focused discourse on the key challenges and transformative opportunities for marketers. Drawing on insights from expert contributors, this study examines the marketing implications of the hypothetical widespread adoption of the metaverse. We identify new research directions and propose a new framework offering valuable contributions for academia, practice, and policy makers. Our future research agenda culminates in a checklist for researchers which clarifies how the metaverse can be beneficial to digital marketing and advertising, branding, services, value creation, and consumer wellbeing.
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
Dwivedi, Y. K., Hughes, L., Ismagilova, E., Aarts, G., Coombs, C., Crick, T., Duan, Y., Dwivedi, R., Edwards, J., Eirug, A., et al. (2021) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2019.08.002 · Cited by 4,611 · cited 3×
“In alignment with an approach initially set out in Foerster (2003) and subsequent expert contributor ‐ focused studies (Dwivedi et al., 2020, 2015; Dwivedi, Hughes, et al., 2021; Dwivedi, Ismagilova, et al., 2021; Dwivedi, Hughes, Baabdullah, et al., 2022; Dwivedi, Hughes, Cheung, et al., 2022;…”
Self-citationDwivedi, Y. K., Ismagilova, E., Hughes, D. L., Carlson, J., Filieri, R., Jacobson, J., Jain, V., Karjaluoto, H., Kefi, H., Krishen, A. S., et al. (2021) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2020.102168 · Cited by 4,608
Self-citationDwivedi, Y. K., Hughes, L., Baabdullah, A. M., Ribeiro-Navarrete, S., Giannakis, M., Al-Debei, M. M., Dennehy, D., Metri, B., Buhalis, D., Cheung, C. M. K., et al. (2022) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2022.102542 · Cited by 2,753
Self-citationBrave new world: service robots in the frontline
Wirtz, J., Patterson, P. G., Kunz, W. H., Gruber, T., Lu, V. N., Paluch, S., & Martins, A. (2018) · Journal of Service Management · doi:10.1108/josm-04-2018-0119 · Cited by 2,315
Self-citationA strategic framework for artificial intelligence in marketing
Huang, M.-H., & Rust, R. T. (2021) · Journal of the Academy of Marketing Science · doi:10.1007/s11747-020-00749-9 · Cited by 2,059 · cited 1×
“For example, understanding how AI (Huang & Rust, 2021) and machine learning (Volkmar et al., 2022) impact marketing can be extended to envision metaverse implications for the marketing domain.”
Dwivedi, Y. K., Hughes, D. L., Coombs, C., Constantiou, I., Duan, Y., Edwards, J. S., Gupta, B., Lal, B., Misra, S., Prashant, P., et al. (2020) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2020.102211 · Cited by 1,232 · cited 1×
“In alignment with an approach initially set out in Foerster (2003) and subsequent expert contributor ‐ focused studies (Dwivedi et al., 2020, 2015; Dwivedi, Hughes, et al., 2021; Dwivedi, Ismagilova, et al., 2021; Dwivedi, Hughes, Baabdullah, et al., 2022; Dwivedi, Hughes, Cheung, et al., 2022;…”
Self-citationFlow online: lessons learned and future prospects.
Hoffman, D. L., & Novak, T. P. (2009) · Journal of Interactive Marketing · doi:10.1016/j.intmar.2008.10.003 · Cited by 954
Dwivedi, Y. K., Hughes, L., Kar, A. K., Baabdullah, A. M., Grover, P., Abbas, R., Andreini, D., Abumoghli, I., Barlette, Y., Bunker, D., et al. (2022) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2021.102456 · Cited by 761
Self-citationSocial media engagement behaviour: a uses and gratifications perspective
Dolan, R., Conduit, J., Fahy, J., & Goodman, S. (2016) · Journal of Strategic Marketing · doi:10.1080/0965254x.2015.1095222 · Cited by 720
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 · cited 1×
“Furthermore, events and competitions in the metaverse can be organized like real life, providing more options for brands to engage with their customers (Jin & Sung, 2010; Miao et al., 2022).”
Advertising in the metaverse: Research agenda
Kim, J. (2021) · Journal of Interactive Advertising · doi:10.1080/15252019.2021.2001273 · Cited by 645 · cited 8×
“Currently defined as “ an interoperated persistent network of shared virtual environments where people can interact synchronously through their avatars with other agents and objects ” (Kim, 2021, p. 142), the metaverse will enable people to embody avatars and interact through them.”
InfluentialSelf-citationMakransky, G., & Mayer, R. E. (2022) · Educational Psychology Review · doi:10.1007/s10648-022-09675-4 · Cited by 386
Antecedents to the adoption of augmented reality smart glasses: A closer look at privacy risks
Rauschnabel, P. A., He, J., & Ro, Y. K. (2018) · Journal of Business Research · doi:10.1016/j.jbusres.2018.08.008 · Cited by 344
Self-citationBarrett, M., Oborn, E., & Orlikowski, W. (2016) · Information Systems Research · doi:10.1287/isre.2016.0648 · Cited by 269
Cited by
Dwivedi, Y. K., Kshetri, N., Hughes, L., Slade, E. L., Jeyaraj, A., Kar, A. K., Baabdullah, A. M., Koohang, A., Raghavan, V., Ahuja, M., et al. (2023) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2023.102642 · Cited by 4,584
Self-citationOoi, K.-B., Tan, G. W.-H., Al-Emran, M., Al-Sharafi, M. A., Capatina, A., Chakraborty, A., Dwivedi, Y. K., Huang, T.-L., Kar, A. K., Lee, V.-H., et al. (2025) · Journal of Computer Information Systems · doi:10.1080/08874417.2023.2261010 · Cited by 746
Self-citationThe merchants of meta: A research agenda to understand the future of retailing in the metaverse
Yoo, K., Welden, R., Hewett, K., & Haenlein, M. (2023) · Journal of Retailing · doi:10.1016/j.jretai.2023.02.002 · Cited by 353
Kim, D. Y., Lee, H. K., & Chung, K. (2023) · Journal of Retailing and Consumer Services · doi:10.1016/j.jretconser.2023.103382 · Cited by 283
Is it the end of the technology acceptance model in the era of generative artificial intelligence?
Mogaji, E., Viglia, G., Srivastava, P., & Dwivedi, Y. K. (2024) · International Journal of Contemporary Hospitality Management · doi:10.1108/ijchm-08-2023-1271 · Cited by 187
Self-citation
Metadata
- Authors
- Dwivedi, Y. K., Hughes, L., Wang, Y., Alalwan, A. A., Ahn, S. J. (., Balakrishnan, J., Barta, S., Belk, R., Buhalis, D., Dutot, V., Felix, R., Filieri, R., Flavián, C., Gustafsson, A., Hinsch, C., Hollensen, S., Jain, V., Kim, J., Krishen, A. S., Lartey, J. O., Pandey, N., Ribeiro‐Navarrete, S., Raman, R., Rauschnabel, P. A., Sharma, A., Sigala, M., Veloutsou, C., & Wirtz, J.
- Venue
- Psychology & Marketing
- Publisher
- Wiley
- Published
- 2022-12-16
- Volume
- 40
- Issue
- 4
- Pages
- 750-776
- ISSN
- 0742-6046 (ISSN-L)
- 1520-6793
- OpenAlex
- W4313310852
- Cited by
- 899
- References
- 14
- FWCI
- 267.06
- Type
- journal article
- Language
- en
- Open access
- hybrid
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.
