The study evaluates to what extent logistics performance and its components impact Vietnam’s bilateral export value. The augmented Gravity model is applied on panel data in the period from 2010 to 2018. Logistics efficiency is measured by Logistic performance index (LPI) and its sub-indices developed by the World Bank. A variety of diagnostic tests and estimation methods are employed to ensure the stability of the results. The main findings confirm that all explanatory variables demonstrate the expected signs, and aggregate logistics performance and its sub-indices have positive impacts on Vietnam’s export flows, with the magnitude of logistics impacts is greater than other factors in the research model. Among LPI components of Vietnam, Ease of arranging shipments index is the most influential factor on exports, followed by Infrastructure, Timeliness, and Quality of logistics services. These export’s effects are also identified by partners’ LPI indicators namely Quality of logistics services, Customs, Infrastructure, and Tracking and tracing.

This research examines three data mining approaches employing cost management datasets from 391 Thai contractor companies to investigate the predictive modeling of construction project failure with nine parameters. Artificial neural networks, naive bayes, and decision trees with attribute selection are some of the algorithms that were explored. In comparison to artificial neural network’s (91.33%) and naive bays’ (70.01%) accuracy rates, the decision trees with attribute selection demonstrated greater classification efficiency, registering an accuracy of 98.14%. Finally, the nine parameters include: 1) planning according to the current situation; 2) the company’s cost management strategy; 3) control and coordination from employees at different levels of the organization to survive on the basis of various uncertainties; 4) the importance of labor management factors; 5) the general status of the company, which has a significant effect on the project success; 6) the cost of procurement of the field office location; 7) the operational constraints and long-term safe work procedures; 8) the implementation of the construction system system piece by piece, using prefabricated parts; 9) dealing with the COVID-19 crisis, which is crucial for preventing project failure. The results show how advanced data mining approaches can improve cost estimation and prevent project failure, as well as how computational methods can enhance sustainability in the building industry. Although the results are encouraging, they also highlight issues including data asymmetry and the potential for overfitting in the decision tree model, necessitating careful consideration.

While infrastructure provides necessary public services and is vital for the socio-economic development of a nation, public funds alone cannot finance all infrastructure needs in society, especially after the COVID-19 pandemic, where many countries are facing budget deficits. Although private financing schemes, such as public-private partnerships (PPPs) and land value capture, have been considered intensively, they have yet to produce adequate private capital flows to infrastructure projects due to a lack of incentives for private investors. Against the background, this paper proposes a new financing mechanism in which governments might divert some of the increased tax revenue from the spillover effects of newly constructed infrastructures to fund the private sector through grants or subsidies. The empirical work in Vietnam shows a significant increase in tax revenues after completing two expressways, supporting our idea about spillover effects, which includes small- and medium-sized enterprise (SME) development. This study’s results suggest that spillover effects can bring new opportunities for governments and multilateral development banks (MDBs) to implement infrastructure projects with greater private sector involvement in the region. It also proposes some financial schemes, such as land capture and financing for business startups, including SMEs, to enhance the spillover effects of infrastructure.