To read this content please select one of the options below:

Understanding social media users' information avoidance intention: a C-A-C perspective

Tao Zhou (School of Management, Hangzhou Dianzi University, Hangzhou, China)
Yingying Xie (School of Management, Hangzhou Dianzi University, Hangzhou, China)

Aslib Journal of Information Management

ISSN: 2050-3806

Article publication date: 30 March 2023

704

Abstract

Purpose

Based on the C-A-C framework, this article examined users' information avoidance intention in social media platforms.

Design/methodology/approach

The authors conducted data analysis using a mixed method of the SEM and fsQCA.

Findings

The results indicated that information overload, functional overload and social overload influence fatigue and dissatisfaction, both of which further determine users' information avoidance intention. The results of the fsQCA identified two paths that trigger users' information avoidance intention.

Originality/value

Extant studies have examined the information avoidance in the contexts of healthcare, academics and e-commerce, but have seldom explored the mechanism underlying users' information avoidance in social media. To fill this gap, this article will empirically investigate users' information avoidance in social media platforms based on the C-A-C framework.

Keywords

Citation

Zhou, T. and Xie, Y. (2023), "Understanding social media users' information avoidance intention: a C-A-C perspective", Aslib Journal of Information Management, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/AJIM-10-2022-0471

Publisher

:

Emerald Publishing Limited

Copyright © 2023, Emerald Publishing Limited

Related articles