A study on the turnover intention of teachers in Chinese regional universities: A predictive power analysis based on five management dimensions of high-performance human resource practices.

In this study, the direct influences of five management dimensions of high-performance human resource practices (HPHRP), i.e., talent selection and cultivation (TSC), career and job security (CJS), performance appraisal and compensation incentives (PACI), participative management (PM), and affective...

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Main Authors: Jun Li, Lingjie Wang, Xiaoli Xu, Junyan Liu, Lei Peng
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2025-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0324487
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author Jun Li
Lingjie Wang
Xiaoli Xu
Junyan Liu
Lei Peng
author_facet Jun Li
Lingjie Wang
Xiaoli Xu
Junyan Liu
Lei Peng
author_sort Jun Li
collection DOAJ
description In this study, the direct influences of five management dimensions of high-performance human resource practices (HPHRP), i.e., talent selection and cultivation (TSC), career and job security (CJS), performance appraisal and compensation incentives (PACI), participative management (PM), and affective incentives (AI), on Chinese local university teachers' turnover intentions (TI) were investigated. Additionally, the mediating role of organizational commitment (OC) in these relationships was examined. According to the results of a questionnaire survey among 740 teachers from five regional colleges and universities in China, the five management dimensions of HPHRP significantly and negatively impact college teachers' TI, with TSC being the most influential predictor (B = -0.359, t = -10.597***, R² = 0.132), followed by AI ( = -0.277, t = -7.829***, R² = 0.077), PACI ( = -0.262, t = -7.390***, R² = 0.069), CJS ( = -0.262, t = -7.390***, R² = 0.069), and PM ( = -0.231, t = -6.456***, R² = 0.053). Furthermore, OC was found to partially mediate the relationship between TSC (B = -0.243, t = -5.987***, R² = 0.164), CJS (B = -0.105, t = -2.621**, R² = 0.131), PACI (B = -0.127, t = -3.290**, R² = 0.136), and AI (B = -0.126, t = -3.125**, R² = 0.135) on college teachers' TI and completely mediated the influence of PM (B = -0.053, t = -1.288, R² = 0.125) on college teachers' TI. The findings suggest that TSC, OC, and PM play more significant roles in affecting Chinese regional university teachers' TI. In order to reduce teachers' TI, local university administrators should focus on talent, encourage teachers to take part in school management, and strengthen their commitment to the university.
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spelling doaj-art-441b8ee6e64d4c99a1de50dcab016eb92025-08-20T03:44:40ZengPublic Library of Science (PLoS)PLoS ONE1932-62032025-01-01205e032448710.1371/journal.pone.0324487A study on the turnover intention of teachers in Chinese regional universities: A predictive power analysis based on five management dimensions of high-performance human resource practices.Jun LiLingjie WangXiaoli XuJunyan LiuLei PengIn this study, the direct influences of five management dimensions of high-performance human resource practices (HPHRP), i.e., talent selection and cultivation (TSC), career and job security (CJS), performance appraisal and compensation incentives (PACI), participative management (PM), and affective incentives (AI), on Chinese local university teachers' turnover intentions (TI) were investigated. Additionally, the mediating role of organizational commitment (OC) in these relationships was examined. According to the results of a questionnaire survey among 740 teachers from five regional colleges and universities in China, the five management dimensions of HPHRP significantly and negatively impact college teachers' TI, with TSC being the most influential predictor (B = -0.359, t = -10.597***, R² = 0.132), followed by AI ( = -0.277, t = -7.829***, R² = 0.077), PACI ( = -0.262, t = -7.390***, R² = 0.069), CJS ( = -0.262, t = -7.390***, R² = 0.069), and PM ( = -0.231, t = -6.456***, R² = 0.053). Furthermore, OC was found to partially mediate the relationship between TSC (B = -0.243, t = -5.987***, R² = 0.164), CJS (B = -0.105, t = -2.621**, R² = 0.131), PACI (B = -0.127, t = -3.290**, R² = 0.136), and AI (B = -0.126, t = -3.125**, R² = 0.135) on college teachers' TI and completely mediated the influence of PM (B = -0.053, t = -1.288, R² = 0.125) on college teachers' TI. The findings suggest that TSC, OC, and PM play more significant roles in affecting Chinese regional university teachers' TI. In order to reduce teachers' TI, local university administrators should focus on talent, encourage teachers to take part in school management, and strengthen their commitment to the university.https://doi.org/10.1371/journal.pone.0324487
spellingShingle Jun Li
Lingjie Wang
Xiaoli Xu
Junyan Liu
Lei Peng
A study on the turnover intention of teachers in Chinese regional universities: A predictive power analysis based on five management dimensions of high-performance human resource practices.
PLoS ONE
title A study on the turnover intention of teachers in Chinese regional universities: A predictive power analysis based on five management dimensions of high-performance human resource practices.
title_full A study on the turnover intention of teachers in Chinese regional universities: A predictive power analysis based on five management dimensions of high-performance human resource practices.
title_fullStr A study on the turnover intention of teachers in Chinese regional universities: A predictive power analysis based on five management dimensions of high-performance human resource practices.
title_full_unstemmed A study on the turnover intention of teachers in Chinese regional universities: A predictive power analysis based on five management dimensions of high-performance human resource practices.
title_short A study on the turnover intention of teachers in Chinese regional universities: A predictive power analysis based on five management dimensions of high-performance human resource practices.
title_sort study on the turnover intention of teachers in chinese regional universities a predictive power analysis based on five management dimensions of high performance human resource practices
url https://doi.org/10.1371/journal.pone.0324487
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