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Performance Measurement in Local Government: Institutional Factors

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  • Rabina Laila
  • Ermawati

Abstract

The purpose of this research is to give empirical evidence of the impact of management commitment, resources, legislative mandate, management innovation, and reward/incentive on performance measurement. This research data was collected through a Google Form, in which 64 questionnaires were sent to the Head of the Planning Subdivision and their staff in each of the Regional Apparatus Organizations in the South Tangerang City Government. With the technique used, census sampling, this study took a quantitative approach employing non-probability sampling. Structural Equation Modeling (SEM) using PLS version 3.0 was used to evaluate the data. Management commitment and legislative mandate have a considerable impact on performance measurement. Meanwhile, resources, management innovation, and reward/incentive do not. This study has implications for local governments in terms of describing how performance measurement is carried out based on institutional factors, as well as making recommendations for improving local government performance measurements in the future to make them more reliable, effective, and efficient.

Suggested Citation

  • Rabina Laila & Ermawati, 2021. "Performance Measurement in Local Government: Institutional Factors," Journal of Social and Development Sciences, AMH International, vol. 12(2), pages 35-44.
    • Handle: RePEc:rnd:arjsds:v:12:y:2021:i:2:p:35-44
    DOI: 10.22610/jsds.v12i2(S).3208
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    References listed on IDEAS

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    1. Cavalluzzo, Ken S. & Ittner, Christopher D., 2004. "Implementing performance measurement innovations: evidence from government," Accounting, Organizations and Society, Elsevier, vol. 29(3-4), pages 243-267.
    2. Khoirul Aswar & Lovina Eka Putri & Ermawati, 2020. "The Effect of Organizational Factors on Performance Measurement in Indonesia Local Governments," International Journal of Economics & Business Administration (IJEBA), International Journal of Economics & Business Administration (IJEBA), vol. 0(4), pages 122-131.
    3. Sarstedt, Marko & Ringle, Christian M. & Smith, Donna & Reams, Russell & Hair, Joseph F., 2014. "Partial least squares structural equation modeling (PLS-SEM): A useful tool for family business researchers," Journal of Family Business Strategy, Elsevier, vol. 5(1), pages 105-115.
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