The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
What is Interactivity and is it Always Such a Good Thing? Implications of Definition, Person, and Situation for the Influence of Interactivity on Advertising Effectiveness
Abstract
Most perceptions of interactivity are that it is an inherently good thing, that it will change marketing and advertising as we know it. However, though there are obvious and intuitive advantages to interactivity, it may pose a disadvantage for marketing and advertising in some conditions. In this article, we explore the nature of interactivity and its underlying processes to determine the conditions in which interactivity may be both useful and detrimental in an advertising context. We first discuss the multidimensional nature of the interactivity construct as it has appeared in the literature. We then provide a concrete conceptualization and definition of interactivity that encompasses these various dimensions. We argue that inconsistencies between the definitions and operationalizations found in previous studies make it difficult to draw firm conclusions about the role of interactivity but that these inconsistencies can be at least partly explained by a focus on the different dimensions of interactivity. Finally, drawing on theory and research in cognitive, social, and personality psychology, we suggest that the influence of interactivity on advertising effectiveness may be a function of both the person and the situation. We offer a program of research, in the form of testable propositions, to explore these boundary conditions and discuss implications for Internet advertising strategy.
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
Defining virtual reality: Dimensions determining telepresence
Steuer, J. (1992) · Journal of Communication · doi:10.1111/j.1460-2466.1992.tb00812.x · Cited by 5,459
Conceptualizing consumer experiences in cyberspace
Shih, C. (. (1998) · European Journal of Marketing · doi:10.1108/03090569810224056 · Cited by 256
Cited by
de Vries, L., Gensler, S., & Leeflang, P. S. H. (2012) · Journal of Interactive Marketing · doi:10.1016/j.intmar.2012.01.003 · Cited by 2,060
Labrecque, L. I. (2014) · Journal of Interactive Marketing · doi:10.1016/j.intmar.2013.12.003 · Cited by 971
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
Can a Retail Web Site Be Social?
Wang, L. C., Baker, J., Wagner, J. A., & Wakefield, K. (2007) · Journal of Marketing · doi:10.1509/jmkg.71.3.143 · Cited by 672
Developing a scale to measure the interactivity of websites
Liu, Y. (2003) · Journal of Advertising Research · doi:10.2501/jar-43-2-207-216 · Cited by 659
Self-citationLike, comment, and share on Facebook: How each behavior differs from the other
Kim, C., & Yang, S.-U. (2017) · Public Relations Review · doi:10.1016/j.pubrev.2017.02.006 · Cited by 550
Toward Meaningful Engagement: A Framework for Design and Research of Gamified Information Systems1
Liu, D., Santhanam, R., & Webster, J. (2017) · MIS Quarterly · doi:10.25300/misq/2017/41.4.01 · Cited by 521
Factors affecting YouTube influencer marketing credibility: a heuristic-systematic model
Xiao, M., Wang, R., & Chan-Olmsted, S. (2018) · Journal of Media Business Studies · doi:10.1080/16522354.2018.1501146 · Cited by 497
Chi, H.-H. (2011) · Journal of Interactive Advertising · doi:10.1080/15252019.2011.10722190 · Cited by 294
Examining the antecedents and consequences of mobile app engagement
Kim, S., & Baek, T. H. (2018) · Telematics and Informatics · doi:10.1016/j.tele.2017.10.008 · Cited by 203
Schultz, C. D. (2017) · Electronic Commerce Research and Applications · doi:10.1016/j.elerap.2017.09.005 · Cited by 191
Advertising benefits from ethical Artificial Intelligence algorithmic purchase decision pathways
Rodgers, W., & Nguyen, T. (2022) · Journal of Business Ethics · doi:10.1007/s10551-022-05048-7 · Cited by 137
Chatbot ads with a human touch: A test of anthropomorphism, interactivity, and narrativity
Sun, Y., Chen, J., & Sundar, S. S. (2024) · Journal of Business Research · doi:10.1016/j.jbusres.2023.114403 · Cited by 115
A Tale of Two Houses: The House of Commons, the Big Brother House and the People at Home
Coleman, S. (2003) · Parliamentary Affairs · doi:10.1093/pa/gsg113 · Cited by 104
Crutzen, R., Cyr, D., & de Vries, N. K. (2012) · Journal of Medical Internet Research · doi:10.2196/jmir.1922 · Cited by 91
Lew, Z., Walther, J. B., Pang, A., & Shin, W. (2018) · Journal of Computer-Mediated Communication · doi:10.1093/jcmc/zmy009 · Cited by 86
Aydin, G., Uray, N., & Silahtaroglu, G. (2021) · Journal of Theoretical and Applied Electronic Commerce Research · doi:10.3390/jtaer16040044 · Cited by 70
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
van Velsen, L., van der Geest, T., van de Wijngaert, L., van den Berg, S., & Steehouder, M. (2015) · Journal of Organizational Computing and Electronic Commerce · doi:10.1080/10919392.2015.990782 · Cited by 32
An Experimental Analysis of the Effectiveness of Multi-Screen Advertising
Hoeck, L., & Spann, M. (2020) · Journal of Interactive Marketing · doi:10.1016/j.intmar.2020.01.002 · Cited by 26
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
Damaj, A., & Nofal, R. (2026) · Journal of Theoretical and Applied Electronic Commerce Research · doi:10.3390/jtaer21040112 · Cited by 8
Metadata
- Authors
- Liu, Y., & Shrum, L. J.
- Venue
- Journal of Advertising
- Publisher
- Informa UK Limited
- Published
- 2002-12
- Volume
- 31
- Issue
- 4
- Pages
- 53-64
- ISSN
- 0091-3367 (ISSN-L)
- 1557-7805
- OpenAlex
- W2004400415
- Cited by
- 1,134
- References
- 2
- FWCI
- 35.15
- 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
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.
