Title: Human Resources Information System (HRIS) to Enhance Civil Servants' Innovation Outcomes: Compulsory or Complimentary? A Critical review
Authors: Azhar Naima M.
Volume: 10
Issue: 8
Pages: 60-64
Publication Date: 2026/08/28
Abstract:
This critical and analytical review focuses on the study " Role of Digital Human Resource Systems to Improve Innovation for Civil Servant Government Office of Innovation" conducted in Indonesia by Sat Ipsievi, Ismi Rajiani, Mamun Murod and Andriansyah. The study aimed to answer the burning question: " Mandatory or Complementary? " when assessing a move to new digital human resource systems in Government. Based on the survey of 500 respondents, statistical analysis based on Structural Equation Modelling found that not only was the new digital system successfully adopted, but paradoxically there was no significant impact of moving to a new system on innovation, leading the authors to conclude it only plays a complementary role in government bureaucracy. In this review I praise the researchers for their open-mindedness, publishing negative findings and analyzing thoroughly the reasons why the innovation was not successfully introduced through the filter of cultural and bureaucratic context of Indonesia (seniority system and week incentives), using The AMO model. At the same time I focus on limitations relating to the methodology used from cross-sectional sample, not tackling time factor, limited geographical scope on capital Jakarta and measuring innovation on the basis of self-assessment of the respondents vs. objective indicators, to old-fashioned model of mediation based on Bardon and Kenny. On theoretical level the comparison of the research findings (lack of real motivation of employees having sure job, " cosmetic compliance" ) confirms and explains observations from other, international studies. I close the research with a set of developmental recommendations concentrating on cross-sectional analysis over time and measuring innovation through objective indicators, using new, digital statistical analysis, e.g. SmartPLS and increasing the geographical scope of sample to embrace remote areas outside capital cities.