Assessing the risk of turnover intention among hospital workers

Artikel

Solving the shortage of hospital workers has become an increasingly urgent priority in recent decades. Understanding the turnover problem remains a major scientific challenge. The objective of this study was to assess the risk intention for hospital workers based on the probabilistic risk assessment concept. A cross-sectional study was conducted. The survey samples included nursing staff and hospital workers from one regional teaching hospital in Taiwan. Participants completed a questionnaire with measures of emotional labor, job stress (JS), internal marketing (IM), organizational citizenship behavior, and the perception of turnover intention (TI) in order to assess a risk-based model of the perception of TI based on a doseresponse relationship. The results showed that employees' perceptions of JS influenced their perception of TI, and organizational commitment was a mediator between IM and the perception of TI. To represent the current knowledge of the predictive model, the present study was the first to incorporate the probabilistic and risk assessment concepts to assess the perception of TI. The proposed dose-response scheme may enable the early identification of the perception of TI among individuals, and help to maintain workflow stability in hospital environments.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Journal: International Journal of Management, Economics and Social Sciences (IJMESS) ; ISSN: 2304-1366 ; Volume: 6 ; Year: 2017 ; Issue: Special Issue ; Pages: 244-258 ; Jersey City, NJ: IJMESS International Publishers

Classification and Topics

• Classification: Wirtschaft
• Subject: Turnover intention ; hospital workers ; risk ; job stress ; healthcare management

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Tsai, Yafang ; Wu, Shih-Wang ; Chen, Szu-Chieh
• Event: Veröffentlichung
• (who): IJMESS International Publishers
• (where): Jersey City, NJ
• (when): 2017

Further information

• Handle: http://hdl.handle.net/10419/173240
• Last update: 10.03.2025, 11:44 AM CET