The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
Modeling innovative points of sales through virtual and immersive technologies
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Citations
Cites
Perceived usefulness, perceived ease of use, and user acceptance of information technology
Davis, F. D. (1989) · MIS Quarterly · doi:10.2307/249008 · Cited by 68,483
Venkatesh, V. (2000) · Information Systems Research · doi:10.1287/isre.11.4.342.11872 · Cited by 6,664
The use of lisrel in validating marketing constructs
Steenkamp, J.-B. E. M., & van Trijp, H. C. M. (1991) · International Journal of Research in Marketing · doi:10.1016/0167-8116(91)90027-5 · Cited by 1,848
Consumer e-shopping acceptance: Antecedents in a technology acceptance model
Ha, S., & Stoel, L. (2009) · Journal of Business Research · doi:10.1016/j.jbusres.2008.06.016 · Cited by 1,353
The effect of web interface features on consumer online purchase intentions
Hausman, A. V., & Siekpe, J. S. (2009) · Journal of Business Research · doi:10.1016/j.jbusres.2008.01.018 · Cited by 981
Technology Adaptation in E-commerce:
Chen, L.-D., & Tan, J. (2004) · European Management Journal · doi:10.1016/j.emj.2003.11.014 · Cited by 306
Antecedents of trust in online auctions
Chiu, C.-M., Huang, H.-Y., & Yen, C.-H. (2010) · Electronic Commerce Research and Applications · doi:10.1016/j.elerap.2009.04.003 · Cited by 236
Cited by
Yim, M. Y.-C., Chu, S.-C., & Sauer, P. L. (2017) · Journal of Interactive Marketing · doi:10.1016/j.intmar.2017.04.001 · Cited by 1,142
Enabling smart retail settings via mobile augmented reality shopping apps
Dacko, S. G. (2017) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2016.09.032 · Cited by 543
Rese, A., Baier, D., Geyer-Schulz, A., & Schreiber, S. (2017) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2016.10.010 · Cited by 470
Nikhashemi, S. R., Knight, H. H., Nusair, K., & Liat, C. B. (2021) · Journal of Retailing and Consumer Services · doi:10.1016/j.jretconser.2021.102464 · Cited by 366
Constituents and consequences of smart customer experience in retailing
Roy, S. K., Balaji, M. S., Sadeque, S., Nguyen, B., & Melewar, T. C. (2017) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2016.09.022 · Cited by 348
Metadata
- Authors
- Pantano, E., & Servidio, R.
- Venue
- Journal of Retailing and Consumer Services
- Publisher
- Elsevier BV
- Published
- 2012-05
- Volume
- 19
- Issue
- 3
- Pages
- 279-286
- ISSN
- 0969-6989 (ISSN-L)
- OpenAlex
- W2086377092
- Cited by
- 237
- References
- 7
- FWCI
- 20.11
- Type
- journal article
- Language
- en
- Open access
- closed
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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.
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How to cite
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- This page
- CoChat. (2026). Citation check: Modeling innovative points of sales through virtual and immersive technologies. https://app.cochat.ai/papers/10.1016/j.jretconser.2012.02.002
- The paper
- Pantano, E., & Servidio, R. (2012). Modeling innovative points of sales through virtual and immersive technologies. Journal of Retailing and Consumer Services. https://doi.org/10.1016/j.jretconser.2012.02.002
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.
