Exploring intrinsic factors that affect quality job and turnover intention in the Chinese educational services industry

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Organizations must attain a sustainable competitive advantage via the workforce. Active employee engagement can foster motivation and provide intrinsic job satisfaction. This study aims to analyze the impact of prospective intrinsic factors on the turnover intention of academic staff in the educational service industry in Anhui, China. A quantitative study method was devised using the Daniel Pink’s theory with a survey questionnaire consisting of 51 items. The study used a 5-point Likert scale. Nonprobability sampling with the snowball method was exercised for 403 fully completed responses for data analysis using the SPSS program version 23. The Pearson correlation analysis revealed a significant and robust inverse relationship between employee turnover intention and all of the independent variables examined (r² = 55.06 for managerial behavior empowerment, r² = 54.76 for psychological empowerment, r² = 54.46 for career growth opportunity, r² = 63.84 for organizational commitment, and r² = 27.46 for compensation). The multiple regression analysis was subsequently implemented. The model evaluation yields an adjusted R² value of 0.685, signifying that the independent variables collectively account for approximately 69% of the variance in the dependent variable, except for compensation, which exhibits a significant positive correlation with turnover intention. However, it is impossible to disregard the impact of compensation as the silence factor. Appropriate delivery of this baseline reward is necessary to ensure that it satisfies the fundamental requirements of the employee and fosters intrinsic motivation.

Acknowledgment
This study received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

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    • Table 1. Correlations
    • Table 2. Model summary
    • Table 3. ANOVA
    • Table 4. Coefficients
    • Conceptualization
      Ganesh Ramasamy, Wu Mengling
    • Data curation
      Ganesh Ramasamy, Wu Mengling
    • Formal Analysis
      Ganesh Ramasamy
    • Methodology
      Ganesh Ramasamy, Wu Mengling
    • Resources
      Ganesh Ramasamy, Wu Mengling
    • Software
      Ganesh Ramasamy
    • Validation
      Ganesh Ramasamy
    • Writing – original draft
      Ganesh Ramasamy, Wu Mengling
    • Writing – review & editing
      Ganesh Ramasamy, Wu Mengling
    • Investigation
      Wu Mengling