International logistics supply chain is an important guarantee to support the country to build a new development pattern, this paper aims to propose a new strategy to promote the development of international logistics supply chain through the case study of Ningbo City. On the basis of supply chain theory and international logistics theory, this paper constructs SWOT model to study the case of Ningbo City, and draws the following conclusions: The international logistics supply chain of Ningbo city has the advantages of superior geographical location, perfect logistics infrastructure and strong port resources, and the disadvantages of low logistics informatization level and logistics management mode to be optimized. At the same time, it faces the opportunities of “One Belt and One Road” initiative and the competitive threat of other logistics centers. Adopting strategies such as policy support, strengthening logistics informatization construction and optimizing logistics management mode can ensure the stable development of foreign trade, which is conducive to accelerating the construction of a new development pattern and modern economic system in which domestic and foreign cycles promote each other.

In rural areas, land use activities around primary arterial roads influence the road section’s traffic characteristics. Regulations dictate the design of primary arterial roads to accommodate high speeds. Hence, there is a mix of traffic between high-speed vehicles and vulnerable road users (pedestrians, bicycles, and motorcycles) around the land. As a result, researchers have identified several arterial roads in Indonesia as accident-prone areas. Therefore, to improve the road user’s safety on primary arterial roads, it is necessary to develop models of the influence of various factors on road traffic accidents. This research uses binary logistic regression analysis. The independent variables are carelessness, disorderliness, high speed, horizontal alignment, road width, clear zone, road shoulder width, signs, markings, and land use. Meanwhile, the dependent variable is the frequency of accidents, where the frequency of accidents consists of multi-accident vehicles (MAV) and single-accident vehicles (SAV). This study collects data for a traffic accident prediction model based on collision frequency in accident-prone areas. The results, road shoulder width, and road sign factor all have an impact on the frequency of traffic accidents. According to a realistic risk analysis, MAV and SAV have no risk difference. After validation, this model shows a confidence level of 92%. This demonstrates that the model generates estimations that accurately reflect reality and are applicable to a wider population. This research has the potential to assist engineers in improving road safety on primary arterial roads. In addition, the model can help the government measure the impact of implemented policies and engage the public in traffic accident prevention efforts.

This study examines the bottleneck effect of logistics performance on Vietnam’s imports, utilizing bilateral trade data from 2007 to 2022. We evaluate the impact of logistics performance on imports of Vietnam using the augmented gravity model and a random effects estimator. Our findings reveal that the minimum logistics performance between Vietnam and its trading partners has a significantly positive impact on the Vietnamese imports. The magnitude of its bottleneck effects is much larger than the influence of Vietnam’s individual logistics performance or deviations in performance with its trading partners. Recognizing the impact of logistics bottlenecks on international trade enables policymakers to develop more effective and efficient logistics-related policies for enhancing bilateral trade with trading partners.

Outsourcing logistics operations is a common trend as businesses prioritize core activities. Establishing a sustainable partnership between businesses and logistics service providers requires a systematic approach. This study is needed to develop a more effective and adaptive framework for logistics service provider selection by integrating diverse criteria and decision-making methodologies, ultimately enhancing the precision and sustainability of procurement processes. This study advocate for leveraging industry-based knowledge in procurement, emphasizing the need to define decision-making elements. The research analyzes nearly 300 logistics procurement projects, using a neural network-based methodology to propose a model that aids businesses in identifying optimal criteria for evaluating logistics service providers based on extensive industry knowledge. The goal of this study is to develop and test a practical model that would support businesses in choosing most suitable criteria for selection of logistics service providers based on cumulative market patterns. The results of this study are as follows. It introduces novel elements by gathering and systematizing unique market data using developed data processing methodology. It innovatively classifies decision-making elements, allocating them into distinct groups for use as features in a neural network. The study further contributes by developing and training a predictive model based on a prepared dataset, addressing pre-defined goals, expectations related to green logistics, and specific requirements in the tendering process for selecting logistics service providers. Study is concluded by summarizing suggestions for future research in area of adopting neural networks for selection of logistics service providers.

Vietnamese e-commerce has recently experienced a robust growth, especially e-commerce platforms such as Shopee, Lazada, Tiki. Reverse logistics has been pointed out as having a significant impact on the performance of an e-commerce platform. To capture the actual impact of some reverse logistics factors, i.e, Return Processing Time (RPT), Return Policy (RP), Return Cost (RC), Customer Service (CSR), and Post-Return Product (PRP), on Customer Satisfaction (CS), an OLS model was conducted. The results indicated significant correlation between all independent variables and dependent variables, which CSR shows the greatest correlation and PRP shows the weakest correlation.  The study then made some suggestions for e-commerce platforms in Vietnam to enhance their reverse logistics process to get higher customer satisfaction.