This study assesses Vietnam’s state-level implementation of artificial intelligence (AI) technology and analyses the government’s efforts to encourage AI implementation by focusing on the National Strategy on AI Development Program. This study emphasizes the possibility of implementing AI at the state level in Vietnam and the importance of conducting continuous reviews and enhancements to achieve sustainable and inclusive AI growth. Impact evaluations were conducted in public organizations alone, and implication evaluations were considered optional. AI impact assessments were constrained by societal norms that necessitated establishing relationships among findings. There is a lack of official information regarding the positive impact of Vietnam’s AI policy on the development of AI infrastructure, research, and talent pools. The study’s findings highlight the necessity of facilitating extensive AI legislation, and strengthening international cooperation. The study concludes with the following recommendations for improving Vietnam’s AI policy: implementing a strong AI governance structure and supporting AI education and awareness.

The study has formulated the objective of synthesizing the extent to which technological barriers intervene in the transparency and effectiveness of public management (PM). Methodologically, the study was of a fundamental or basic nature, with a systematic review design, the databases of Scopus (369), SciELO (2), Web of Science (184) were explored, after the review process a set of 22 articles was available. The registration was made in an Excel table where the main data of the articles were included. 32% of the articles selected for the analysis of the evidence are from the period 2020, 27% were from 2022 and 18% from the year 2023; as far as origin is concerned, 14% of the articles come from Peru and 9% from Australia, Brazil, South Korea, Spain and Indonesia. In summary, the study points out that government institutions are making progress in digitizing and improving the citizen experience through electronic services, but they face challenges in areas such as resource management, the low adoption of advanced technologies such as blockchain and artificial intelligence, as well as the lack of transparency in PM. Despite this, it is highlighted that e-government improves citizen satisfaction, and the need to invest in digital innovation, training and overcoming technological barriers to achieve an effective transformation in state administration and promote a more inclusive and advanced society is emphasized.

This research aims to determine the factors driving the success of four large cities in Indonesia in implementing Transit-Oriented Development (TOD) infrastructure policies beyond the eight TOD 3.0 Principles. Only a few studies like this have been conducted. The research uses qualitative methods and is supported by in-depth interviews with stakeholders, community leaders, community groups, and service users. The research findings reveal six themes: policy dialogue, organizational structure and coordination, changes in community habits, resources, dissemination and communication, and transportation and connectivity services. The characteristics of the community in the study area that prioritize deliberation are important determinants in policy dialogue and are involved in determining policy formulation. The city government has established a comprehensive organizational and coordination structure for the village and sub-district levels. The Government controls infrastructure development activities, establishes a chain of command and coordination, and encourages people to change their private car usage habits. The city government combines all this with the principle of deliberation and conveys important information to the public. The research highlights the differences in TOD implementation in Indonesia compared to other countries. Specifically, the existence of policy dialogue and the direct involvement of community members influence the level of program policy formulation and are crucial in controlling urban infrastructure development.

This article aims to examine the impact of fiscal decentralization on the performance of local government expenditure in Vietnam. By using a dataset including 63 provinces from 2012 to 2021, the research shows the more expenditure-based fiscal decentralization occurs, the better is the performance of local expenditure. Moreover, the level of provincial literacy and the size of the private sector have positive impacts on the local expenditure index, while the opposite effect can be seen in the case of the ratios of local citizens to total citizens of the country. Besides this, the study also provides some recommendations which are strictly related to the mechanism of fiscal decentralization to improve local expenditure performance of Vietnamese provinces, such as more effective decentralization of budget expenditures to local government, improving the vertical budget imbalance at local budget level, increasing local government budget autonomy, and establishing stronger mechanisms to control public spending.

This study investigates the influence of government expenditure on the economic growth of the ASEAN-5 countries from 2000 to 2021. The study employs the Pooled Mean Group (PMG) ARDL model and robust least squares method. The importance of the current study lies in its analysis of the short and long-run impact of government expenditure on economic growth in ASEAN-5. The empirical findings demonstrate a positive relationship between government expenditure and economic growth in the long run. These results align with the Keynesian perspective, asserting that government expenditure stimulates economic growth. The study also confirms one-way causality from government expenditure to economic growth, supporting the Keynesian hypothesis. These insights hold significance for policymakers in the ASEAN-5, highlighting the necessity for policies promoting the effective allocation of productive government expenditure. Moreover, it is important to enhance systems that promote economic growth and efficiently allocated economic resources toward productive expenditures while also maintaining effective governance over such expenditures.

Named Entity Recognition (NER), a core task in Information Extraction (IE) alongside Relation Extraction (RE), identifies and extracts entities like place and person names in various domains. NER has improved business processes in both public and private sectors but remains underutilized in government institutions, especially in developing countries like Indonesia. This study examines which government fields have utilized NER over the past five years, evaluates system performance, identifies common methods, highlights countries with significant adoption, and outlines current challenges. Over 64 international studies from 15 countries were selected using PRISMA 2020 guidelines. The findings are synthesized into a preliminary ontology design for Government NER.