UNVEILING IMPLEMENTATION AND IMPACT OF NEO-WEBERIAN STATE MODEL IN THE INTERNATIONAL BUREAUCRATIC REVOLUTION
DOI:
https://doi.org/10.30997/jgs.v10i2.14351Keywords:
Global Bureaucratic Reform, Neo Weberian State (NWS), Public Service PerformanceAbstract
This research uses a literature review (SLR) study to investigate the application of the Neo-Weberian State (NWS) model in global bureaucratic reform, with an emphasis on economic, social and health issues. This research aims to provide a comprehensive understanding of the implementation of NWS, critically evaluate its success and provide recommendations for developing government governance and community services. This research applies a five-stage approach by Transfield to review the literature on the implementation of the Neo-Weberian State (NWS) over the past few decades. This review combines results from qualitative and quantitative research that has been published between 2021-2024 in various European countries. The results show that the Neo Weberian State (NWS) can increase efficiency in public services and overcome global challenges, despite facing internal obstacles, limited resources, complex regulations, and shortcomings in accountability and transparency. This research emphasizes the importance of adaptation according to context, capacity building, simpler deregulation, and strict supervision to ensure the effectiveness of the Neo Weberian State (NWS). The participation of government, civil society and the private sector is considered very important in creating new and creative public service solutions. This research outlines how the Neo-Weberian State (NWS) model faces broad challenges in carrying out bureaucratic reform. The NWS improves the quality of public services, addresses internal constraints, and emphasizes contextual adaptation, capacity building, modest deregulation, and strict supervision, which are critical to governance and public services. Although it provides a solution for solving problems in the current era of revolution, additional research is still needed to fully understand its impact and design more effective implementation models.
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