PurposeThe purpose of this paper is to understand the effect of platform characteristics (i.e. media richness and interactivity) on individual perception (i.e. outcome expectations) and consequent behavioral response (i.e. user participation in online health communities (OHCs)) based on the stimulus-organism-response (S-O-R) model.Design/methodology/approachThis study developed a research model to test the proposed hypotheses, and the proposed model was tested using partial least squares structural equation modeling (PLS-SEM) for which data were collected from 321 users with OHC experience using an online survey.FindingsThe empirical results show the following: (1) the three dimensions of media richness significantly affect the three outcome expectations, except that richness of expression has no significant effect on the outcome expectation of health self-management competence. (2) Human-to-human interaction significantly affects the three outcome expectations. Moreover, compared with human-to-human interaction, human-to-system interaction has a stronger impact on the outcome expectation of health self-management competence. (3) The three outcome expectations have a significant influence on user participation in OHCs.Originality/valueThis study extends the understanding about how platform characteristics (i.e. media richness and interactivity) motivate user participation in the context of OHCs. Drawing on the S-O-R model, this study reveals the underlying mechanisms by which media richness and interactivity are associated with outcome expectations and by which outcome expectations is associated with user participation in OHCs. This study enriches the literature on media richness, interactivity, outcome expectations and user participation in OHCs, providing insights for developers and administrators of OHCs.
Aim
The purpose of this study is to investigate how the use of artificial intelligence is associated with the retention of elderly caregivers.
Background
The turnover of elderly caregivers is high and increasing. Elderly care institutions are beginning to use artificial intelligence to support caregivers in their work, and the use of technology is critical to staff retention. Empowerment of elderly caregivers has been neglected by managers and researchers.
Methods
This cross‐sectional study involved 511 elderly caregivers in 25 elderly institutions. Six validated standardized scales were used for data collection, and the software SPSS and SmartPLS were used for data analysis.
Results
The quality of artificial intelligence has a significant positive effect on empowerment. Artificial intelligence psychological empowerment (β = .355, p < .001) and artificial intelligence structural empowerment (β = .375, p < .001) both had positive effects on retention intention, and the jointly explained variance (R2) was 42.6%.
Conclusions
The results show that a significant relationship exists between artificial intelligence empowerment and retention intention. Elderly caregivers with more structural empowerment have higher retention intention.
Implications for Nursing Management
Artificial intelligence suppliers need to pay attention to the role of product quality in elderly care services, continuously improve artificial intelligence quality, and strengthen the application and routine maintenance of artificial intelligence technologies. Elderly care institution managers should pay special attention to artificial intelligence structural empowerment (such as artificial intelligence‐related education and training, learning and development opportunities, and resource support).
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