The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.
Advertising on Social Network Sites: A Structural Equation Modelling Approach
Abstract
Social networking sites (SNSs) emerged as one of the most powerful media for advertising across the globe. Globally, companies are shifting a larger pie of their advertising budgets towards social networking sites for better reach and interactive platform. The companies are also looking at it as a low-cost model, which could reap results in minimum time possible for the targeted ‘Facebook generation’. These very facts motivate researchers to study the value of advertisements on social networking sites like Facebook, LinkedIn, Twitter and others. The article is an empirical study to understand the implications of different variables in advertisements on the delivery of advertising value to the respondents. Confirmatory factor analysis (CFA) has been conducted to test the reliability of instrument being used for data collection. Further, a model has been proposed for measuring advertising value through structural equation modelling. The predicted results confirm the roles of different variables, namely, information, entertainment and irritation, in accessing value of advertisements displayed on social networking sites.
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Cites
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
Specification, evaluation, and interpretation of structural equation models
Bagozzi, R. P., & Yi, Y. (2012) · Journal of the Academy of Marketing Science · doi:10.1007/s11747-011-0278-x · Cited by 3,735
A Review of Scale Development Practices in the Study of Organizations
Hinkin, T. R. (1995) · Journal of Management · doi:10.1177/014920639502100509 · Cited by 3,193
College students' social networking experiences on Facebook
Pempek, T. A., Yermolayeva, Y. A., & Calvert, S. L. (2009) · Journal of Applied Developmental Psychology · doi:10.1016/j.appdev.2008.12.010 · Cited by 2,081
Online and offline social networks: Use of social networking sites by emerging adults
Subrahmanyam, K., Reich, S. M., Waechter, N., & Espinoza, G. (2008) · Journal of Applied Developmental Psychology · doi:10.1016/j.appdev.2008.07.003 · Cited by 1,284 · cited 1×
“Second, a number of studies have reported that students are the main users of social networking websites (Dwyer et al., 2007; Pempek et al., 2009; Subrahmanyam et al., 2008).”
BackgroundPeterson, R. A. (2001) · Journal of Consumer Research · doi:10.1086/323732 · Cited by 1,258
Effect of the number of variables on measures of fit in structural equation modeling
Kenny, D. A., & McCoach, D. B. (2003) · Structural Equation Modeling: A Multidisciplinary Journal · doi:10.1207/s15328007sem1003_1 · Cited by 1,231
How consumers assess the value of advertising
Ducoffe, R. H. (1995) · Journal of Current Issues & Research in Advertising · doi:10.1080/10641734.1995.10505022 · Cited by 774
Muenjohn, D. N., & Armstrong, P. A. (2008) · Contemporary Management Research · doi:10.7903/cmr.704 · Cited by 224
Cited by
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
Advertising in social media: a review of empirical evidence
Knoll, J. (2016) · International Journal of Advertising · doi:10.1080/02650487.2015.1021898 · Cited by 362
Transforming Digital Marketing with Generative AI
Islam, T., Miron, A., Nandy, M., Choudrie, J., Liu, X., & Li, Y. (2024) · Computers · doi:10.3390/computers13070168 · Cited by 68
Aggarwal, V., Dash, S., Yadav, P. D., & Gupta, A. K. (2022) · 2022 2nd International Conference on Innovative Practices in Technology and Management (ICIPTM) · doi:10.1109/iciptm54933.2022.9754158 · Cited by 18
Metadata
- Authors
- Saxena, A., & Khanna, U.
- Venue
- Vision: The Journal of Business Perspective
- Publisher
- SAGE Publications
- Published
- 2013-03
- Volume
- 17
- Issue
- 1
- Pages
- 17-25
- ISSN
- 0972-2629 (ISSN-L)
- 2249-5304
- OpenAlex
- W2022459436
- Cited by
- 220
- References
- 9
- FWCI
- 28.85
- Type
- journal article
- Language
- en
- Open access
- closed
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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.
