Journal of Applied Data Sciences
Vol 6, No 4: December 2025

Understanding Teacher Retention through the Lens of Job Satisfaction: An Empirical Study of Organizational and Human Resource Management in Chinese Universities

Hui, Xie Xiao (Unknown)
Tresirichod, Teetut (Unknown)



Article Info

Publish Date
22 Oct 2025

Abstract

This study investigates the determinants of teacher retention in public universities in Sichuan Province, China, emphasizing the mediating role of job satisfaction between organizational management (OM) and human resource management (HRM) on job retention (JR). The research aims to (1) identify the key factors influencing the retention of non-established teachers and (2) propose effective strategies to enhance their job stability. A quantitative approach was applied using a questionnaire survey administered to 1,400 teachers from 27 public universities, yielding 1,335 valid responses (95% response rate). Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results demonstrate that both OM (β = 0.031, p 0.001) and HRM (β = 0.029, p 0.001) significantly and positively affect JR, while job satisfaction fully mediates these relationships (β = 0.030, p 0.001). The explanatory power of the model was moderate, with R² = 0.630 for job satisfaction and R² = 0.545 for job retention, indicating that the proposed model accounts for over 50% of the variance in both variables. Descriptive statistics further revealed that 50.3% of respondents were non-established teachers, and 61.5% were female, highlighting a balanced and diverse sample. The findings indicate that well-structured OM and HRM practices, such as transparent promotion systems, career development opportunities, and inclusive institutional participation, substantially enhance teacher satisfaction and retention. This study’s novelty lies in its integrated model combining OM, HRM, and job satisfaction to explain teacher retention, a topic rarely explored in the context of Chinese public universities. The research contributes to the literature by offering empirical evidence and actionable recommendations for policymakers and administrators to strengthen human resource strategies and ensure the long-term stability of university faculty.

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Journal Info

Abbrev

JADS

Publisher

Subject

Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management

Description

One of the current hot topics in science is data: how can datasets be used in scientific and scholarly research in a more reliable, citable and accountable way? Data is of paramount importance to scientific progress, yet most research data remains private. Enhancing the transparency of the processes ...