The lack of sufficient charging infrastructure for long-haul transportation is a significant barrier preventing the widespread adoption of electric vehicles (EVs). Planning EV charging facilities in this context requires considerations distinct from those in urban environments, accounting for factors such as traffic patterns and charging behaviors. This research paper presents a multi-agent simulation model designed to assess travel and charging activities, specifically on highways. By utilizing this model, the effectiveness of EV charging facility planning is evaluated. Empirical data from a real highway section in China are employed for analysis purposes. The findings reveal that the concentration of charging facilities significantly impacts both travel time and queue time for vehicles, demonstrating the potential for optimization through the proposed model. These established models hold practical value for both greenfield development and the expansion of existing charging networks, with the goal of minimizing total social costs.

With the maturity of the online food delivery (OFD) industry in China, the growth of the market in recent years is mainly driven by the increase of the usage frequency of existing users rather than the number of new users. The usage frequency of users is affected by various factors, with the delivery charge as one of the most significant ones. The purpose of this study is to examine the impact of delivery charge and other factors on the probability of consumers choosing to use OFD service. In this study, 391 questionnaire records from China were collected, based on which a logistic regression model was established. The results of the model show that age, occupation, monthly income, city tier of residence, location and time period of usage, and delivery charges all play a role on the probability of consumers using the service, and the delivery charge has the greatest impact. For every one yuan increase in the delivery charge, consumers will be less likely to choose “certainly” of using OFD (OR: 0.435; 95% CI: 0.415, 0.455). Sensitivity analysis shows that when the delivery charge changes between 2~5 yuan, it has the greatest impact on the probability of consumers using the service. The analysis further shows that delivery charge has different impacts under different scenarios composed of three key factors, i.e., the city tier of residence, locations of usage, and time period of usage. From a management perspective, these findings help to understand the behavior of OFD consumers and provide insights for the OFD operators to establish best pricing strategies for long-term economic sustainability.

Overcapacity of seaport infrastructure has been a common issue in many countries in recent years. Cautious investment decisions shall be made on the basis of realistic capacity evaluation and productivity improvement of existing ports. However, operational analysis and evaluation of a seaport is not always easy, especially for multipurpose terminals which are commonly seen in developing countries. These small-scaled multipurpose seaports handle different cargo types with multiple interrelated processes and varying handling methods and process times. This paper studies a single-berth multipurpose seaport with wharf space restriction in Indonesia and shows how the simulation model can be essential and significantly helpful in the evaluation of the port’s productivity and realistic capacity. Furthermore, a new handling method is proposed and evaluated by the simulation model. The simulation approach and related results help the port operator in making decisions regarding port improvement and future expansion investments.

While most countries implemented measures to reduce people activities and gathering to contain the coronavirus, the outcome may vary significantly depending on how and to what extent people behaviors have been changed. We conducted a survey of 1,048 people in five major cities in China to track and quantify the behavior changes in different periods since the outbreak. It is found that there was nearly 80% reduction of out-of-home activities (working, eating, shopping, taking public transportation, and travelling) during the peak period. Such activities are gradually increasing after the easing of containment measures but still significantly below pre-outbreak level. The significant behavior changes have contributed to the rapid control of virus transmission in China. While countries are reopening the economies before the virus disappears, the system and capacity of testing and contact tracing should be carefully designed with the tracking of people behavior changes in the future.