Structural Equation Modeling of the Relationship between the Intention to Quit and Ethical Climate, Job Satisfaction, and Organizational Commitment among the Staff of Shiraz Private Hospitals

Introduction: Ethical climate is a part of organizational culture. Organizational values deal with ethical issues and determine what is considered ethically correct. The ethical climate of an organization can predict unethical and ethical behaviors. This study aimed to investigate and model the structural equations between the intention to quit and ethical climate, job satisfaction, and organizational commitment among the staff of Shiraz private hospitals. Methods: This was an applied, descriptive correlational research conducted in spring, 2010. The study population consisted of 299 employees of private hospital departments who were selected by cluster random sampling. Data was collected by 4 standard questionnaires whose validity and reliability have been confirmed. Collected data were analyzed through descriptive and inferential statistics using SPSS16. Structural model equation analysis was performed by Lisrel8.5. Results: The findings revealed that there was a significant positive correlation between ethical climate and job satisfaction (r = 0.235), organizational commitment (r = 0.334). A negative correlation was found between intention to quit and ethical climate (r = -0.114). Moreover, there was a significant positive correlation between job satisfaction and organizational commitment (r = 0.625). Negative correlations were observed between intention to quit and job satisfaction (r = -0.359) and organizational commitment (r = -0.292). In addition, structural model equations demonstrated that job satisfaction and organizational commitment had direct effects on intention to quit. Conclusion: Structural equations modeling provided a framework of variables to improve satisfaction and commitment in private hospitals of Shiraz by promoting ethical climate for keeping staff. Keywords: Job Satisfaction; Organizational Commitment; Personnel, Hospitals.