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Beyond likes and shares: the secret to building stronger brands on social media from a privacy calculus perspective

Sohail Ahmad et al.

International Journal of Internet Marketing and Advertising2025https://doi.org/10.1504/ijima.2025.144205article
AJG 1ABDC C
Weight
0.37

What the paper says

Nowadays, social media platforms are becoming an integral part of marketing strategies. Social media success is measured by consumer engagement. This new technology gives organisations new ways to communicate with consumers. To engage with consumers, the organisation created online communities. Despite their significance, there is still a lack of understanding of what keeps users actively engaged in online communities. The study investigates the influence of social media marketing activity in building brand loyalty through community engagement. Moreover, to understand community information disclosure concerns, this study determines the influence of privacy calculus on community engagement. We developed a conceptual framework using SOR, S-D logic, and privacy calculus theories. Using purposive sampling, online surveys were conducted from 465 global cosmetic brand followers on social network sites. This study found that SMMa has a massive potential to build brand loyalty and community engagement is the crucial mediator between SMMa and brand loyalty.

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https://doi.org/https://doi.org/10.1504/ijima.2025.144205

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@article{sohail2025,
  title        = {{Beyond likes and shares: the secret to building stronger brands on social media from a privacy calculus perspective}},
  author       = {Sohail Ahmad et al.},
  journal      = {International Journal of Internet Marketing and Advertising},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1504/ijima.2025.144205},
}

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Beyond likes and shares: the secret to building stronger brands on social media from a privacy calculus perspective

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Evidence weight

0.37

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.16 × 0.4 = 0.06
M · momentum0.53 × 0.15 = 0.08
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.