Examining the moderating role of institutional leadership in the relationship between institutional pressures and the use of performance measurement systems: Evidence from local government in Yogyakarta, Indonesia

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Type of the article: Research Article

Abstract
Institutional leadership represents an important internal capacity for institutionalizing performance measurement systems within local government, particularly in contexts where external forces such as institutional isomorphism shape organizational behavior. This study examines the moderating role of institutional leadership in the relationship between institutional pressures (coercive, mimetic, and normative) and the use of performance measurement systems. Survey data were collected from 77 senior officials responsible for implementing and using performance measurement systems across all government agencies in the Special Region of Yogyakarta, Indonesia, in 2022. The data were analyzed using partial least squares structural equation modeling (PLS-SEM). The results indicate that institutional leadership significantly moderates the relationship between coercive pressure and performance measurement systems use (path coefficient = −0.194, p = 0.037), suggesting a negative moderating effect that weakens coercive influence. However, no significant moderating effects were found for mimetic pressure (−0.121, p = 0.138) or normative pressure (0.008, p = 0.138). Institutional leadership also does not exert a direct effect on the use of performance measurement systems (0.019, p = 0.433). Regarding direct effects, coercive and mimetic pressures positively influence performance measurement systems use (0.394 and 0.310, respectively; p < 0.05), while normative pressure is not significant (0.017, p = 0.440). These findings suggest that institutional leadership functions more effectively as a contingent moderating mechanism than as an independent driver in shaping organizational responses to institutional pressures.

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    • Figure 1. Research model
    • Figure 2. Output model
    • Table 1. Demographics of respondents
    • Table 2. Validity and reliability
    • Table 3. Fornell–Larcker criterion
    • Table 4. Fit summary
    • Table 5. Hypothesis test results
    • Table 6. Endogeneity and additional analysis
    • Table A1. Measurements
    • Conceptualization
      Anthonius H. Citra Wijaya, Rusdi Akbar
    • Data curation
      Anthonius H. Citra Wijaya
    • Formal Analysis
      Anthonius H. Citra Wijaya
    • Funding acquisition
      Anthonius H. Citra Wijaya
    • Investigation
      Anthonius H. Citra Wijaya, Rusdi Akbar
    • Methodology
      Anthonius H. Citra Wijaya, Rusdi Akbar
    • Project administration
      Anthonius H. Citra Wijaya
    • Resources
      Anthonius H. Citra Wijaya
    • Software
      Anthonius H. Citra Wijaya
    • Supervision
      Anthonius H. Citra Wijaya, Rusdi Akbar
    • Visualization
      Anthonius H. Citra Wijaya
    • Writing – original draft
      Anthonius H. Citra Wijaya
    • Writing – review & editing
      Anthonius H. Citra Wijaya, Rusdi Akbar
    • Validation
      Rusdi Akbar