Signalling Effects of Vlogger Popularity on Online Consumers
Abstract
This article investigates the effect of video loggers (vloggers) popularity on consumer credibility perception and purchase intention. It employs a two (high versus low vlogger popularity) by two (search versus experience product types) between-subject experimental design to uncover the signalling effect of vlogger popularity. While vlogger popularity influences the consumers’ credibility perception and purchase intention for all products, a high popularity vlogger is likely to be more effective in influencing the online consumers for experience products. We confirm the usefulness of the popularity construct in explaining purchase behavior in social media settings. In doing so, we provide an empirical evidence concerning the specific conditions under which credibility is more (or less) effective in influencing behavior. This study is the first to examine vlogger popularity effects in social media. Our findings provide important insights to both academics and practitioners.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Consumers' purchase behaviour in endorsed products is positively related to video bloggers' popularity.
“Ladhari et al. [98] and Hill et al. [134] also demonstrated that consumers’ purchase behaviour in endorsed products is positively related to video bloggers’ popularity.”
From Consumers purchase intention in live-streaming e-commerce: A consumption value perspective and the role of streamer popularity (2024) · cites this paper as [134]
Cites
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 · see citing works
Statistical power analyses using G∗Power 3.1: tests for correlation and regression analyses
Faul, F., Erdfelder, E., Buchner, A., & Lang, A.-G. (2009) · Behavior Research Methods · doi:10.3758/brm.41.4.1149 · Cited by 37,615 · see citing works
GPOWER: A general power analysis program
Erdfelder, E., Faul, F., & Buchner, A. (1996) · Behavior Research Methods, Instruments, & Computers · doi:10.3758/bf03203630 · Cited by 4,864 · see citing works
Ohanian, R. (1990) · Journal of Advertising · doi:10.1080/00913367.1990.10673191 · Cited by 4,043 · see citing works
Social and Heuristic Approaches to Credibility Evaluation Online
Metzger, M. J., Flanagin, A. J., & Medders, R. B. (2010) · Journal of Communication · doi:10.1111/j.1460-2466.2010.01488.x · Cited by 1,394 · see citing works
Mitra, K., Reiss, M. C., & Capella, L. M. (1999) · Journal of Services Marketing · doi:10.1108/08876049910273763 · Cited by 507 · see citing works
Consumer's decision to shop online: The moderating role of positive informational social influence
Lee, M. K. O., Shi, N., Cheung, C. M. K., Lim, K. H., & Sia, C. L. (2011) · Information & Management · doi:10.1016/j.im.2010.08.005 · Cited by 315 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
The effect of characteristics of source credibility on consumer behaviour: A meta-analysis
Ismagilova, E., Slade, E., Rana, N. P., & Dwivedi, Y. K. (2020) · Journal of Retailing and Consumer Services · doi:10.1016/j.jretconser.2019.01.005 · Cited by 504 · see citing works
Zhang, Q., Wang, Y., & Ariffin, S. K. (2024) · PLoS ONE · doi:10.1371/journal.pone.0296339 · Cited by 50 · see citing works
Wear in or wear out: how consumers respond to repetitive influencer marketing
Geng, R., Chen, X., & Wang, S. (2024) · Internet Research · doi:10.1108/intr-01-2022-0075 · Cited by 34 · see citing works
- Authors
- Hill, S. R., Troshani, I., & Chandrasekar, D.
- Affiliations
- The University of Adelaide (AU)
- Corresponding author
- Troshani, Indrit
- Venue
- Journal of Computer Information Systems
- Publisher
- Informa UK Limited
- Published
- 2017-12-08
- Volume
- 60
- Issue
- 1
- Pages
- 76-84
- ISSN
- 0887-4417 (ISSN-L)
- 2380-2057
- OpenAlex
- W2774592337
- Cited by
- 127
- References
- 7
- Citations by year
- 2026: 9 · 2025: 19 · 2024: 19 · 2023: 23 · 2022: 25 · 2021: 21 · 2020: 4 · 2019: 7
- FWCI
- 7.70
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Computer Information Systems (publishedVersion)
- Adelaide Research & Scholarship (AR&S) (University of Adelaide) (submittedVersion)
- Topics
- Social Sciences › Sociology and Political Science › Digital Marketing and Social Media
- Social Sciences › Business, Management and Accounting › Marketing › Consumer Behavior and Marketing Influence
- Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
- Keywords
- vloggers, signaling theory, purchase intention, social media influence, experience goods, search products, online consumer behavior, influencer marketing
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
