Promoting users’ smartphone avoidance intention: the role of health beliefs

6Citations
Citations of this article
46Readers
Mendeley users who have this article in their library.
Get full text

Abstract

Purpose: Drawing on the Health Belief Model (HBM), this study aims to investigate the roles of health beliefs (i.e. perceived susceptibility, perceived severity, perceived benefits, perceived barriers, health self-efficacy and cues to action) in promoting college students’ smartphone avoidance intention. Design/methodology/approach: Empirical data were collected through a cross-sectional survey questionnaire administered to 4,670 student smartphone users at a large university located in Central China. Further, a two-step Structural Equation Modeling was conducted using AMOS 22.0 software to test the hypothesized relationships in the research model. Findings: Analytical results indicate that (1) perceived susceptibility, perceived severity, perceived benefits and health self-efficacy positively influence users’ smartphone avoidance intention; (2) perceived barriers negatively influence smartphone avoidance intention, while (3) cues to action reinforce the relationships between perceived susceptibility/perceived benefits and smartphone avoidance intention, but attenuate the relationships between perceived barriers/health self-efficacy and smartphone avoidance intention. Research limitations/implications: This study demonstrates that HBM is invaluable in explaining and promoting users’ smartphone avoidance intention, thereby extending extant literature on both HBM and smartphone avoidance. Originality/value: Research on smartphone avoidance is still in a nascent stage. This study contributes to the field by offering a fresh theoretical lens for pursuing this line of inquiry together with robust empirical evidence.

Cite

CITATION STYLE

APA

Zhao, H., Deng, S., Liu, Y., Xia, S., Lim, E. T. K., & Tan, C. W. (2022). Promoting users’ smartphone avoidance intention: the role of health beliefs. Industrial Management and Data Systems, 122(4), 963–982. https://doi.org/10.1108/IMDS-07-2020-0420

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free