Structural model for the adoption of online advertising on social network in Vietnam

Nguyen, The-Vinh; Cao, Thi Hao; Tran, Nghia D.

doi:10.1109/icacci.2014.6968653

Cited by 4 publications

(2 citation statements)

References 25 publications

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“…The model explains the potential user's behavioral intention to use technological innovation (Arli, 2017;Luna-Nevareza and Torres, 2015;Nguyen et al, 2014)…”

Section: Appendixmentioning

confidence: 99%

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Social media advertising reactance model: a theoretical review

Huo

2020

INTR

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PurposeResearch on social media advertising reactance (SMAR) is in the early stages. This paper intends to present a full picture of SMAR studies, introduce a comprehensive theoretical model (the social media advertising reactance model, SMARM) and provide insights into research and practice.Design/methodology/approachThis review adopts the concept-driven systematic review approach, identifying 92 articles from four primary academic databases – EBSCO, Elsevier, Web of Science and Google Scholar.FindingsFirst, this review offers overviews of five topics: publication trends, the journals publishing research, research methodology, targeted platform and the main theories. Second, based on the framework of psychological reactance, this study proposes the SMARM, identifying and elaborating on four components of the nomological relationship to SMAR: related concepts, antecedents, moderators and consequences.Practical implicationsThis research has implications for advertisers, social media platform operators and policymakers by providing a whole picture of SMAR. Moreover, the SMARM could guide the stakeholders to adopt a user-friendly advertising design for the sustainable development of social media advertising (SMA).Originality/valueBy presenting an up-to-date review of SMAR-related research, this paper contributes to the literature of social media, advertising and marketing. Through a comparison with traditional advertising, this paper makes the characteristics of SMA clear. Meanwhile, the SMARM is developed to systematically elaborate on all related elements of SMAR and explain their underlying causal relationships. Future research directions are proposed.

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“…The model explains the potential user's behavioral intention to use technological innovation (Arli, 2017;Luna-Nevareza and Torres, 2015;Nguyen et al, 2014)…”

Section: Appendixmentioning

confidence: 99%

“…Explains the relationship between attitudes and behaviors in human actions (Ahmed and Raziq, 2017;Arli, 2017;Nguyen et al, 2014;Yang et al, 2017)…”

Section: Appendixmentioning

confidence: 99%