Grounded on the cognition–affect–conation (C–A–C) framework, this study aims to explore how perceived information overload affects the information avoidance intention of social media users through fatigue, frustration and dissatisfaction.
A quantitative research design is adopted. The data collected from 254 respondents in China are analyzed via structural equation modeling (SEM).
Perceived information overload directly affects fatigue, frustration and dissatisfaction among social media users, thereby affecting their information avoidance intention. In addition, frustration significantly affects social media fatigue and dissatisfaction. Consequently, social media fatigue influences dissatisfaction among users.
The literature review indicates that social media overload and fatigue yield negative behavioral outcomes, including discontinuance. However, rather than completely abstaining or escaping, social media users adopt moderate strategies, including information avoidance, to cope with overload and fatigue owing to their high dependence on social media. Unfortunately, merely few studies are available on the information avoidance behavior of social media users. Focusing on this line of research, the current study develops a model to investigate the antecedents of information avoidance in social media.
Funding information: Humanities and Social Sciences Fund for Young Scientists of the Ministry of Education of China 17YJC630017 and National Natural Science Foundation of China 71871083.
Dai, B., Ali, A. and Wang, H. (2020), "Exploring information avoidance intention of social media users: a cognition–affect–conation perspective", Internet Research, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/INTR-06-2019-0225Download as .RIS
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