A two-stage sem—artificial neural network analysis of the rewards effects on self perceived performance in healthcare

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Abstract

Healthcare managers consider the rewards and performances of employees as central elements of their activities due to the challenges caused by the phenomenon of healthcare employees’ emigrating to higher-income countries, which has reduced patient satisfaction and led to a negative image of hospitals. In this context, this paper analyzes how employee rewards influence the employees’ self-perceived performances in the hospital units of the emergency medical system in Romania. Using structural equation modeling, we analyzed the relationships between the investigated variables, showing that financial motivation and the recognition of employees’ merits are central to employees’ self-perceived performances. Ensuring equity also has a positive impact on how the reward package is established and managed. While financial rewards are the most important incentives to increase efforts to exhibit higher performances, recognition has a long-term motivational effect.

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APA

Bocean, C. G., Rotea, C. C., Vărzaru, A. A., Ploscaru, A. N., & Rotea, C. Ștefan. (2021). A two-stage sem—artificial neural network analysis of the rewards effects on self perceived performance in healthcare. International Journal of Environmental Research and Public Health, 18(23). https://doi.org/10.3390/ijerph182312387

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