Typhoons are a severe form of natural disaster that can impose huge economic losses and casualties on society. High school students are more vulnerable compared with adults during typhoons. Improving risk perceptions of typhoons can help high school students to effectively respond to typhoons and reduce related losses. Environmental values play an important role in human perceptions and actions. Although typhoons are caused by environmental factors, few studies have investigated the influence of environmental factors on typhoon risk perceptions of high school students. This study investigates the typhoon risk perceptions of high school students in Ningbo, China, and further analyzes the influence of environmental values on these perceptions with the structural equations model. The results reveal that environmental values have significantly positive impacts on typhoon risk perceptions. The findings also demonstrate that disaster threats and the disaster management ability of the government have significant positive impacts on typhoon risk perceptions. This study proposes suggestions and measures to improve typhoon risk perceptions among high school students and provides a reference for typhoon prevention and reduction education in China.

Purpose: This paper investigates the complexities of a multimodal dry port transportation network, operating under the challenging conditions posed by the availability of transportation modes. Design/methodology/approach: Our study focuses on a network structure that includes multiple foreign seaports, local seaports, dry ports and manufacturers. We identify a significant research gap in the existing literature on dry port–based multimodal transportation networks. We first develop a mixed-integer non-linear programming (MINLP) model that adeptly integrates freight departure and demand scheduling, inventory management and backlog, while considering the availability of transportation modes in every node. To account for disruptions from uncertain events like extreme weather, we extend this deterministic foundation to a two-stage stochastic programming model. This stochastic model explicitly incorporates uncertainty in transportation mode availability, allowing proactive and adaptive strategies. Findings: The computational study, conducted across two distinct setups, demonstrates our models effectively avoiding substantial backlog penalties as well as delivering robust, cost-balanced solutions to handle uncertainty and complexity. In conclusion, the paper presents a comprehensive analysis including sensitivity analysis, dynamic planning evaluation and cross-regional validation, providing insightful guidance for strategic decision-making and demonstrating the model’s adaptability across different operational contexts. Originality/value: The insights gained from this analysis not only underline the practicality and strategic significance of our framework but also suggest key strategies for businesses.