Given the large amount of railway maintenance work in China, whereas the maintenance time window is continuously compressed, this paper proposes a novel network model-based maintenance planning and optimization method, transforming maintenance planning and optimization into an integer linear programming problem. Based on the dynamic inspection data of track geometry, the evaluation index of maintenance benefit and the model of the decay and recovery of the track geometry are constructed. The optimization objective is to maximize the railway network’s overall performance index, considering budget constraint, maximum length constraint, maximum number of maintenance activities within one single period constraint, and continuity constraint. Using this method, the track units are divided into several maintenance activities at one time. The combination of surrounding track units can be considered for each maintenance activity, and the specific location, measure, time, cost, and benefit can be determined. Finally, a 100 km high-speed railway network case study is conducted to verify the model’s effectiveness in complex optimization scenarios. The results show that this method can output an objective maintenance plan; the combination of unit track sections can be considered to expand the scope of maintenance, share the maintenance cost and improve efficiency; the spatial-temporal integrated maintenance planning and optimization can be achieved to obtain the optimal global solution.

The allocation of funds in the local budget is a matter of concern for the governments and economic scholars. The study examines the influence of local budget expenditures on the GRDP per capita of 63 provinces and municipalities in Vietnam from 2018 to 2022. Regression analysis of panel data reveals that capital expenditure has a positive correlation with local GRDP per capita, whereas current expenditure has a negative correlation with GRDP per capita. Furthermore, the analysis indicates that the percentage of individuals aged 15 and above who are employed and the percentage of urban citizens have an equivalent influence as the GRDP per capita. Conversely, the average age and local Gini coefficient have contrasting effects on GRDP per capita. The author suggests several policy alternatives to assist localities in boosting their GRDP per capita based on the findings of the study model.

In this paper, we explore the static and dynamic effects of oil rent on competitiveness in Saudi Arabia’s economy during the period 1970–2022. In addition, we examined the short-run, strong and long-run relationships between exports and industry, inflation, energy use (oil rents) and agriculture using the Autoregressive Distributed Lag (ARDL) approach developed. The analysis showed that government spending will contribute to enhancing the competitive environment with a difference of one year. Moreover, the industry will contribute to increasing competitiveness for a positive relationship in the long term. The results stated that there is an insignificant relationship between competitiveness, inflation, and oil rents. The analysis also shows that inflation has a negative impact with statistical significance in the short term. In addition, the error correction model (ECM) coefficient is negative and has statistical significance at 0.76 at a 1% significant level, which indicates the existence of an error correction mechanism and thus the existence of a long-term relationship between the variables.