The DOI matches its Crossref record; 18 of the 18 references it cites were found in a registry or an index.
Okay, Google!: An empirical study on voice assistants on consumer engagement and loyalty
Abstract
E‐commerce shopping has gradually become a norm in consumers’ choice of shopping channel and part of this shopping process is aided by advance technologies including voice assistants (VA). There is a variety of artificial intelligence that is being developed in the market currently, and one of which has gradually gained its presence or information acquisition is the VA. In this paper, we propose a model that investigates the technology acceptance model constructs (perceived ease of use and perceived usefulness) and its effect on the engagement and loyalty between VA and consumers. Our model also investigates the moderating role of localizing VA between transactional and nontransactional based online activities. This study highlights the implication of technology integration in an e‐commerce environment.
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
The theory of planned behavior
Ajzen, I. (1991) · Organizational Behavior and Human Decision Processes · doi:10.1016/0749-5978(91)90020-t · Cited by 90,587
Podsakoff, P. M., MacKenzie, S. B., Lee, J.-Y., & Podsakoff, N. P. (2003) · Journal of Applied Psychology · doi:10.1037/0021-9010.88.5.879 · Cited by 82,194
On the Evaluation of Structural Equation Models
Bagozzi, R. P., & Yi, Y. (1988) · Journal of the Academy of Marketing Science · doi:10.1007/bf02723327 · Cited by 26,163
An Index of Factorial Simplicity
Kaiser, H. F. (1974) · Psychometrika · doi:10.1007/bf02291575 · Cited by 14,898
Structural equation models with unobservable variables and measurement error: Algebra and statistics
Fornell, C., & Larcker, D. F. (1981) · Journal of Marketing Research · doi:10.1177/002224378101800313 · Cited by 13,287
Efficacy of the Theory of Planned Behaviour: A meta‐analytic review
Armitage, C. J., & Conner, M. (2001) · British Journal of Social Psychology · doi:10.1348/014466601164939 · Cited by 9,970
(2003) · International Journal of Electronic Commerce · doi:10.1080/10864415.2003.11044275 · Cited by 5,715
Harter, J. K., Schmidt, F. L., & Hayes, T. L. (2002) · Journal of Applied Psychology · doi:10.1037/0021-9010.87.2.268 · Cited by 4,623
Chase, W. G., & Simon, H. A. (1973) · Cognitive Psychology · doi:10.1016/0010-0285(73)90004-2 · Cited by 4,479
Machines and Mindlessness: Social Responses to Computers
Nass, C., & Moon, Y. (2000) · Journal of Social Issues · doi:10.1111/0022-4537.00153 · Cited by 4,022
Cited by
Kim, J., Giroux, M., & Lee, J. C. (2021) · Psychology & Marketing · doi:10.1002/mar.21498 · Cited by 353
Conversational commerce: entering the next stage of AI-powered digital assistants
Balakrishnan, J., & Dwivedi, Y. K. (2024) · Annals of Operations Research · doi:10.1007/s10479-021-04049-5 · Cited by 301
Alexa, what do we know about conversational commerce? Insights from a systematic literature review.
Lim, W. M., Kumar, S., Verma, S., & Chaturvedi, R. (2022) · Psychology & Marketing · doi:10.1002/mar.21654 · Cited by 293
Creepiness: Its antecedents and impact on loyalty when interacting with a chatbot
Rajaobelina, L., Prom Tep, S., Arcand, M., & Ricard, L. (2021) · Psychology & Marketing · doi:10.1002/mar.21548 · Cited by 252
Bawack, R. E., Wamba, S. F., & Carillo, K. D. A. (2021) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2021.102309 · Cited by 240
Metadata
- Authors
- Moriuchi, E.
- Venue
- Psychology & Marketing
- Publisher
- Wiley
- Published
- 2019-01-15
- Volume
- 36
- Issue
- 5
- Pages
- 489-501
- ISSN
- 0742-6046 (ISSN-L)
- 1520-6793
- OpenAlex
- W2911095486
- Cited by
- 297
- References
- 18
- FWCI
- 12.66
- 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: Okay, Google!: An empirical study on voice assistants on consumer engagement and loyalty. https://app.cochat.ai/papers/10.1002/mar.21192
- The paper
- Moriuchi, E. (2019). Okay, Google!: An empirical study on voice assistants on consumer engagement and loyalty. Psychology & Marketing. https://doi.org/10.1002/mar.21192
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.
