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Advertising on Social Network Sites: A Structural Equation Modelling Approach

Author

Listed:
  • Anant Saxena
  • Uday Khanna

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.

Suggested Citation

  • Anant Saxena & Uday Khanna, 2013. "Advertising on Social Network Sites: A Structural Equation Modelling Approach," Vision, , vol. 17(1), pages 17-25, March.
  • Handle: RePEc:sae:vision:v:17:y:2013:i:1:p:17-25
    DOI: 10.1177/0972262912469560
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    References listed on IDEAS

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    1. Phillips, Megan & McFadden, Dawn Thilmany & Sullins, Martha, 2010. "How Effective is Social Networking for Direct Marketers?," Journal of Food Distribution Research, Food Distribution Research Society, vol. 41(1), pages 1-5, March.
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    3. Peterson, Robert A, 2001. "On the Use of College Students in Social Science Research: Insights from a Second-Order Meta-analysis," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 28(3), pages 450-461, December.
    4. Wynne W. Chin & Abhijit Gopal & W. David Salisbury, 1997. "Advancing the Theory of Adaptive Structuration: The Development of a Scale to Measure Faithfulness of Appropriation," Information Systems Research, INFORMS, vol. 8(4), pages 342-367, December.
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    Cited by:

    1. Petra Marešová & Oluwaseun Fadeyi & Kamil Kuča, 2020. "Are Social Networks Sufficiently Used in Companies? Case Study in the Czech Republic," Sustainability, MDPI, vol. 12(3), pages 1-14, February.
    2. Hossam Deraz, 2018. "Users’ Assessment of the Value of Advertisements on Social Networking Sites: A conceptual Study," International Review of Management and Marketing, Econjournals, vol. 8(6), pages 32-40.
    3. Naveed Ul Hassan & Bilal Aziz & Maryam Mushtaq, 2017. "Do Macro-Economic and Technical Indicators Matter?- a Principal Component Analysis Approach for Equity Risk Premium Prediction," European Journal of Economics and Business Studies Articles, Revistia Research and Publishing, vol. 3, September.
    4. Yash Chawla & Anna Kowalska-Pyzalska & Paulo Duarte Silveira, 2019. "Marketing and communications channels for diffusion of smart meters in Portugal," HSC Research Reports HSC/19/05, Hugo Steinhaus Center, Wroclaw University of Technology.
    5. Alina Daniela Mihalcea & Rodica Maria Savulescu, 2013. "Social Networking Sites: Guidelines For Creating New Business Opportunities Through Facebook, Twitter And LinkedIn," Management Dynamics in the Knowledge Economy, College of Management, National University of Political Studies and Public Administration, vol. 1(1), pages 39-53, May.
    6. Hossam Deraz, 2019. "Factors Contributing to Consumers’ Assessment of Advertisement Value on Social Networking Sites: A Cross-Cultural Focus Group Study," International Review of Management and Marketing, Econjournals, vol. 9(1), pages 13-25.

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