Human capital and sustainable university: Mediating role of sustainable human resource management in Indonesia

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Sustainable universities play a role in evaluating and reporting on sustainable practices in developing countries. The study aims to identify human capital’s impact on sustainable university performance by implementing sustainable human resource management (sustainable HRM) as a mediating variable. The paper uses a quantitative approach, with a sample of 140 employees consisting of lecturers and educational staff at Esa Unggul University, Jakarta, Indonesia. Data were collected using a Likert scale questionnaire and analyzed using structural equation modeling-partial least squares with SmartPLS 4.0 software. The results showed a positive and significant impact that was statistically proven by a direct impact of human capital and sustainable HRM on sustainable universities as well as an indirect impact of human capital on sustainable universities mediated by sustainable HRM. Furthermore, the results showed that the level of direct influence of human capital on sustainable universities has an influence value of 0.371, where the influence is categorized as weak. The level of indirect influence with sustainable HRM as a mediator between human capital and sustainable universities has an influence of 0.662 with a fairly strong/moderate influence. This proves that the role of sustainable HRM practices is an essential component in realizing a sustainable university. Empirical findings recommend increasing the capacity and quality of lecturers and education staff as the main component of university human capital to achieve sustainable higher education performance. Sustainable HRM practices need to be implemented thoughtfully by universities to improve performance from economic, environmental, and social aspects.

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    • Figure 1. Conceptual model
    • Figure 2. Outer model results
    • Figure 3. Hypothesis testing results
    • Table 1. Definitions of operational variables
    • Table 2. Loading factor values
    • Table 3. AVE results
    • Table 4. Cronbach’s alpha results
    • Table 5. R-square (R2) value of the research model
    • Table 6. Hypothesis testing
    • Conceptualization
      Yunata Kandhias Akbar, Sunda Ariana, Suharno Pawirosumarto
    • Data curation
      Yunata Kandhias Akbar, Sunda Ariana, Antonius Setyadi
    • Formal Analysis
      Yunata Kandhias Akbar, Suharno Pawirosumarto, Endri Endri
    • Investigation
      Yunata Kandhias Akbar, Suharno Pawirosumarto, Endri Endri
    • Methodology
      Yunata Kandhias Akbar, Sunda Ariana, Suharno Pawirosumarto, Endri Endri
    • Resources
      Yunata Kandhias Akbar, Antonius Setyadi
    • Validation
      Yunata Kandhias Akbar, Sunda Ariana, Endri Endri
    • Visualization
      Yunata Kandhias Akbar, Sunda Ariana, Antonius Setyadi
    • Writing – original draft
      Yunata Kandhias Akbar, Sunda Ariana, Antonius Setyadi
    • Funding acquisition
      Sunda Ariana, Antonius Setyadi, Endri Endri
    • Project administration
      Sunda Ariana, Antonius Setyadi
    • Software
      Sunda Ariana, Suharno Pawirosumarto
    • Supervision
      Antonius Setyadi, Suharno Pawirosumarto, Endri Endri
    • Writing – review & editing
      Endri Endri