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A framework for enhancing the influence of Facebook advertising: the key role of personalisation and interactivity

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  • Taanika Arora

Abstract

Given the increasing popularity in the usage of Facebook across Indian consumers and the heavy allocation of advertising budget by companies on Facebook advertisements, the effectiveness of Facebook ads in attracting consumers remains limited. Therefore, this research emerges as a pioneering effort in proposing a comprehensive framework by integrating the Ducoffe' web advertising model, flow theory, personalisation and interactivity in determining their role in forming purchase intention towards Facebook advertisements. A systematic approach using non-probability sampling was used to collect data through a self-administered questionnaire (using Google Forums) from 702 active Indian Facebook users. The model deployed the structural equation modelling (SEM) technique for determining model fitness, establishing the validity, reliability of the adapted scales, and testing the proposed hypothesis. The results indicate that the proposed framework is a robust tool for measuring advertising effectiveness on Facebook. This study theoretically contributes to the application of the Facebook advertising model and practically contributes influential factors for effective advertising to marketers and advertisers.

Suggested Citation

  • Taanika Arora, 2022. "A framework for enhancing the influence of Facebook advertising: the key role of personalisation and interactivity," International Journal of Economics and Business Research, Inderscience Enterprises Ltd, vol. 24(3), pages 305-343.
    • Handle: RePEc:ids:ijecbr:v:24:y:2022:i:3:p:305-343
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    Cited by:

    1. Ghadah Alarifi & Mst Farjana Rahman & Md Shamim Hossain, 2023. "Prediction and Analysis of Customer Complaints Using Machine Learning Techniques," International Journal of E-Business Research (IJEBR), IGI Global, vol. 19(1), pages 1-25, January.

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