The DOI matches its Crossref record; 21 of the 21 references it cites were found in a registry or an index.
Determinants of consumer engagement in electronic word-of-mouth (eWOM) in social networking sites
Abstract
As more and more marketers incorporate social media as an integral part of the promotional mix, rigorous investigation of the determinants that impact consumers’ engagement in eWOM via social networks is becoming critical. Given the social and communal characteristics of social networking sites (SNSs) such as Facebook, MySpace and Friendster, this study examines how social relationship factors relate to eWOM transmitted via online social websites. Specifically, a conceptual model that identifies tie strength, homophily, trust, normative and informational interpersonal influence as an important antecedent to eWOM behaviour in SNSs was developed and tested. The results confirm that tie strength, trust, normative and informational influence are positively associated with users’ overall eWOM behaviour, whereas a negative relationship was found with regard to homophily. This study suggests that product-focused eWOM in SNSs is a unique phenomenon with important social implications. The implications for researchers, practitioners and policy makers of social media regulation are discussed.
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Cites
Structural equation modeling in practice: A review and recommended two-step approach
Anderson, J. C., & Gerbing, D. W. (1988) · Psychological Bulletin · doi:10.1037/0033-2909.103.3.411 · Cited by 41,941
A Theory of Cognitive Dissonance
Festinger, L. (1957) · doi:10.1515/9781503620766 · Cited by 24,241
Users of the world, unite! The challenges and opportunities of Social Media
Kaplan, A. M., & Haenlein, M. (2010) · Business Horizons · doi:10.1016/j.bushor.2009.09.003 · Cited by 17,875
Social network sites: definition, history, and scholarship
boyd, D. M., & Ellison, N. B. (2007) · Journal of Computer-Mediated Communication · doi:10.1111/j.1083-6101.2007.00393.x · Cited by 16,251
Ellison, N. B., Steinfield, C., & Lampe, C. (2007) · Journal of Computer-Mediated Communication · doi:10.1111/j.1083-6101.2007.00367.x · Cited by 9,939
Social Capital: Prospects for a New Concept
Adler, P. S., & Kwon, S.-W. (2002) · The Academy of Management Review · doi:10.2307/4134367 · Cited by 9,665
The Effect of Word of Mouth on Sales: Online Book Reviews
Chevalier, J. A., & Mayzlin, D. (2006) · Journal of Marketing Research · doi:10.1509/jmkr.43.3.345 · Cited by 6,003
Hennig-Thurau, T., Gwinner, K. P., Walsh, G., & Gremler, D. D. (2004) · Journal of Interactive Marketing · doi:10.1002/dir.10073 · Cited by 5,916
A study of normative and informational social influences upon individual judgment.
Deutsch, M., & Gerard, H. B. (1955) · The Journal of Abnormal and Social Psychology · doi:10.1037/h0046408 · Cited by 4,819
Internet paradox: A social technology that reduces social involvement and psychological well-being?
Kraut, R., Patterson, M., Lundmark, V., Kiesler, S., Mukophadhyay, T., & Scherlis, W. (1998) · American Psychologist · doi:10.1037/0003-066x.53.9.1017 · Cited by 4,793
Cited by
Erkan, I., & Evans, C. (2016) · Computers in Human Behavior · doi:10.1016/j.chb.2016.03.003 · Cited by 1,188
Social media in marketing: A review and analysis of the existing literature
Alalwan, A. A., Rana, N. P., Dwivedi, Y. K., & Algharabat, R. (2017) · Telematics and Informatics · doi:10.1016/j.tele.2017.05.008 · Cited by 1,123
Evans, N. J., Phua, J., Lim, J., & Jun, H. (2017) · Journal of Interactive Advertising · doi:10.1080/15252019.2017.1366885 · Cited by 921
Trust me, trust me not: A nuanced view of influencer marketing on social media
Kim, D. Y., & Kim, H.-Y. (2021) · Journal of Business Research · doi:10.1016/j.jbusres.2021.05.024 · Cited by 804
Ki, C. ‘., & Kim, Y. (2019) · Psychology & Marketing · doi:10.1002/mar.21244 · Cited by 749
Self-citation
Metadata
- Authors
- Chu, S.-C., & Kim, Y.
- Venue
- International Journal of Advertising
- Publisher
- Informa UK Limited
- Published
- 2011-01
- Volume
- 30
- Issue
- 1
- Pages
- 47-75
- ISSN
- 0265-0487 (ISSN-L)
- 1759-3948
- OpenAlex
- W2041563290
- Cited by
- 2,053
- References
- 21
- FWCI
- 210.03
- Type
- journal article
- Language
- en
- Open access
- closed
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- Chu, S.-C., & Kim, Y. (2011). Determinants of consumer engagement in electronic word-of-mouth (eWOM) in social networking sites. International Journal of Advertising. https://doi.org/10.2501/ija-30-1-047-075
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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.
