The DOI matches its Crossref record; 15 of the 15 references it cites were found in a registry or an index.
Social media marketing: Who is watching the watchers?
Open accessAbstract
The ready access to and availability of social media has opened up a wealth of data that marketers are leveraging for strategic insight and digital marketing. Yet there is a lack of professional norms regarding the use of social media in marketing and a gap in understanding consumers’ comfort with marketers’ use of their social media data. This study analyzes a census-balanced sample of online adults (n = 751) to identify consumers’ perceptions of using social media data for marketing purposes. The research finds that consumers’ perceived risks and benefits of using social media have a relationship with their comfort with marketers using their publicly available social media data. The research extends the applicability of communication privacy management theory to social media and introduces marketing comfort —a new construct of high importance for future marketing research. Marketing comfort refers to an individual's comfort with the use of information posted publicly on social media for targeted advertising, customer relations, and opinion mining. In the context of the construct development, we find that targeted advertising is the strongest contributing component to marketing comfort, relative to the other two dimensions: opinion mining and customer relations. By understanding what drives consumer comfort with this emerging marketing practice, the research proposes strategies for marketers that can support and mitigate consumers’ concerns so that consumers can maintain trust in marketers’ digital practices.
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Cites
A new criterion for assessing discriminant validity in variance-based structural equation modeling
Henseler, J., Ringle, C. M., & Sarstedt, M. (2015) · Journal of the Academy of Marketing Science · doi:10.1007/s11747-014-0403-8 · Cited by 38,459
Social media? Get serious! Understanding the functional building blocks of social media
Kietzmann, J. H., Hermkens, K., McCarthy, I. P., & Silvestre, B. S. (2011) · Business Horizons · doi:10.1016/j.bushor.2011.01.005 · Cited by 4,970
Big other: Surveillance Capitalism and the Prospects of an Information Civilization
Zuboff, S. (2015) · Journal of Information Technology · doi:10.1057/jit.2015.5 · Cited by 3,205 · cited 2×
“In particular, the study shows that while users still value using social media platforms as a source of entertainment and information—where they can express and present themselves in favorable ways—they are becoming more aware of the use of these platforms as major data warehousing and advertising platforms, as well a…”
BackgroundImagined Communities: Awareness, Information Sharing, and Privacy on the Facebook
Acquisti, A., & Gross, R. (2006) · Lecture Notes in Computer Science · doi:10.1007/11957454_3 · Cited by 1,895
Information Privacy Concerns, Procedural Fairness, and Impersonal Trust: An Empirical Investigation
Culnan, M. J., & Armstrong, P. K. (1999) · Organization Science · doi:10.1287/orsc.10.1.104 · Cited by 1,870
Uses and gratifications of social media: A comparison of Facebook and instant messaging
Quan-Haase, A., & Young, A. L. (2010) · Bulletin of Science, Technology & Society · doi:10.1177/0270467610380009 · Cited by 1,205
Uses and Grats 2.0: New Gratifications for New Media
Sundar, S. S., & Limperos, A. M. (2013) · Journal of Broadcasting & Electronic Media · doi:10.1080/08838151.2013.845827 · Cited by 1,070
Social Networks, Personalized Advertising, and Privacy Controls
Tucker, C. E. (2014) · Journal of Marketing Research · doi:10.1509/jmr.10.0355 · Cited by 829
Fox, J., & Moreland, J. J. (2015) · Computers in Human Behavior · doi:10.1016/j.chb.2014.11.083 · Cited by 763
An Empirical Examination of the Concern for Information Privacy Instrument
Stewart, K. A., & Segars, A. H. (2002) · Information Systems Research · doi:10.1287/isre.13.1.36.97 · Cited by 734
Cited by
Dwivedi, 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
“Future research should endeavor to understand what influences individuals’ “marketing comfort” (Jacobson et al., 2020).”
BackgroundSelf-citation‘Instagram made Me buy it’: Generation Z impulse purchases in fashion industry
Djafarova, E., & Bowes, T. (2021) · Journal of Retailing and Consumer Services · doi:10.1016/j.jretconser.2020.102345 · Cited by 650
Tafesse, W., & Wood, B. P. (2021) · Journal of Retailing and Consumer Services · doi:10.1016/j.jretconser.2020.102303 · Cited by 438
Zhang, Y., & Wang, S. (2023) · Journal of Retailing and Consumer Services · doi:10.1016/j.jretconser.2023.103432 · Cited by 102
Ahmed, S., & Aziz, N. A. (2025) · International Journal of Human–Computer Interaction · doi:10.1080/10447318.2024.2400395 · Cited by 67
Metadata
- Authors
- Jacobson, J., Gruzd, A., & Hernández-García, Á.
- Venue
- Journal of Retailing and Consumer Services
- Publisher
- Elsevier BV
- Published
- 2020-03
- Volume
- 53
- Pages
- 101774
- ISSN
- 0969-6989 (ISSN-L)
- OpenAlex
- W2924095995
- Cited by
- 285
- References
- 15
- FWCI
- 68.16
- Type
- journal article
- Language
- en
- Open access
- hybrid
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- Jacobson, J., Gruzd, A., & Hernández-García, Á. (2020). Social media marketing: Who is watching the watchers? Journal of Retailing and Consumer Services. https://doi.org/10.1016/j.jretconser.2019.03.001
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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.