A Study on the Factors Influencing Turnover Intention among Faculty in Chinese Private Higher Education Institutions
Keywords:
Faculty turnover intention; Private higher education; Job Demands–Resources model; Social Exchange Theory; Career development; ChinaAbstract
Abstract
This study investigates the factors influencing turnover intention among faculty members in private higher education institutions in China, with a focus on Fujian Province. Guided by the Job Demands–Resources (JD-R) model and Social Exchange Theory (SET), the research explores how demographic characteristics, job demands, and job resources shape faculty members’ intention to leave their institutions. A quantitative survey was administered to 400 full-time faculty members from 24 private universities, employing stratified random sampling to ensure representativeness. Descriptive statistics, ANOVA, and multiple regression analyses were conducted using SPSS 27.0. The results reveal three key findings: (1) demographic characteristics, such as age, academic rank, and income, significantly influence turnover intention; (2) high job demands—including research pressure, role conflict, and technological adaptation—exert a positive effect on turnover intention; and (3) sufficient job resources—especially collegial support, leadership support, and institutional fairness—play a protective role by reducing turnover intention, although career development support was identified as a major shortcoming. Theoretically, this study enriches the application of the JD-R model and SET within the context of Chinese private higher education, addressing a gap in the literature that has predominantly focused on public universities or Western contexts. Practically, the findings highlight the need for private institutions to reduce excessive job demands, enhance professional development pathways, and strengthen leadership and collegial support in order to improve faculty retention. Limitations of this study include its regional scope and cross-sectional design, suggesting avenues for future research involving longitudinal studies and comparative analyses across provinces.
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