Exploring the adoption decisions of mobile health service users: a behavioral reasoning theory perspective
Industrial Management & Data Systems
ISSN: 0263-5577
Article publication date: 25 July 2023
Issue publication date: 4 August 2023
Abstract
Purpose
To improve the frequency of adoption of mobile health services (MHSs) by users (consumers), it is critical to understand users' MHS adoption behaviors. However, the literature primarily focuses on MHS adoption-related factors and lacks consideration of the joint impacts of reasons for (RF) and reasons against (RA) on users' attitudes and adoption behaviors regarding MHSs. To fill this gap, this study integrates behavioral reasoning theory (BRT) and protective motivation theory (PMT) to develop a research model by uncovering the reasoning process of personal values, RF and RA, adoption attitudes and behavior toward MHSs. In particular, health consciousness (HC) is selected as the value. Comparative advantage, compatibility and perceived threat severity are considered the RF subconstructs; value barriers, risk barriers and tradition and norm barriers are deemed the RA subconstructs.
Design/methodology/approach
A total of 281 responses were collected to examine the model with the partial least squares structural equation modeling (PLS-SEM) method.
Findings
The results show that HC positively affects attitude through RA and RF. Additionally, RF partially mediates the relationship between HC and adoption behavior. This study contributes to a deeper understanding of user adoption behavior in MHS and provides practical guidance for the health services industry.
Originality/value
This study contributes to the existing MHS literature by understanding the joint influences of personal values, RF and RA on user attitude, which eventually determines users' adoption decisions regarding MHSs.
Keywords
Citation
Lee, J.-C., Chen, L. and Zhang, H. (2023), "Exploring the adoption decisions of mobile health service users: a behavioral reasoning theory perspective", Industrial Management & Data Systems, Vol. 123 No. 8, pp. 2241-2266. https://doi.org/10.1108/IMDS-11-2022-0682
Publisher
:Emerald Publishing Limited
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