The nexus between boundary-spanning leadership, proactive behavior, corporate governance, and employee performance through work engagement

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Type of the article: Research Article

Abstract
Employee performance is a key factor determining a company’s sustainability and competitiveness. Therefore, this study aims to explore the role of work engagement in mediating the influence of boundary-spanning leadership, proactive behavior, and corporate governance on employee performance. The study used a survey method via a Likert-scale questionnaire, involving 485 participants from companies in Indonesia engaged in trade, services, finance, and investment in 2025. Data analysis used structural equation modeling supported by descriptive and correlational analysis. The results showed that boundary-spanning leadership, proactive behavior, corporate governance, and work engagement were associated with employee performance (β = 0.242, 0.160, 0.186, 0.276; p < 0.05). Then, boundary-spanning leadership, proactive behavior, and corporate governance also correlated with employee work engagement (β = 0.227, 0.414, 0.160; p < 0.05). In addition, boundary-spanning leadership, proactive behavior, and corporate governance are linked to employee performance through work engagement (β = 0.063, 0.114, 0.044; p < 0.05). With these findings, this study offers a new empirical model of the relationship between boundary-spanning leadership, proactive behavior, corporate governance, and employee performance, mediated by work engagement. This model contributes to organizational behavior and human resource management research and provides practitioners with insights into how boundary-spanning leadership, proactive behavior, and corporate governance can improve employee performance, with work engagement as the crucial mediating factor.

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    • Table 1. Participant profile
    • Table 2. Descriptive, skewness, kurtosis, and correlation analysis
    • Table 3. Result of the measurement model
    • Table 4. Results of HTMT, Fornell–Larcker, and VIF
    • Table 5. Hypothesis testing results
    • Table A1. Variables, indicators, and items
    • Conceptualization
      Ririn Handayani, Widodo Widodo
    • Data curation
      Ririn Handayani, Widodo Widodo, Fahmi Oemar, Suhardiman Amby, Suwandi Suwandi
    • Formal Analysis
      Ririn Handayani, Widodo Widodo
    • Funding acquisition
      Ririn Handayani, Suhardiman Amby, Suwandi Suwandi
    • Investigation
      Ririn Handayani, Widodo Widodo, Fahmi Oemar, Suhardiman Amby, Suwandi Suwandi
    • Project administration
      Ririn Handayani, Suhardiman Amby, Suwandi Suwandi
    • Resources
      Ririn Handayani, Widodo Widodo, Fahmi Oemar, Suhardiman Amby, Suwandi Suwandi
    • Writing – original draft
      Ririn Handayani
    • Writing – review & editing
      Ririn Handayani, Widodo Widodo, Fahmi Oemar, Suhardiman Amby, Suwandi Suwandi
    • Methodology
      Widodo Widodo
    • Software
      Widodo Widodo
    • Validation
      Widodo Widodo, Fahmi Oemar
    • Visualization
      Widodo Widodo, Fahmi Oemar