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With the global increase in air transport demand, the shortage of ground handling personnel to support ground operations at airports has become a major challenge, impacting airport services and causing considerable flight delays. This study presents a novel method to generate trip data that specify the origin and destination locations as the purpose of travel for each ground support equipment (GSE) vehicle. The proposed method uses data obtained from comprehensive observations of 2234 GSE vehicles over a 24 h × 7 d time interval at Tokyo International Airport. From these observations and trip data, the characteristics of the driving conditions for each GSE vehicle type, the locations where GSE traffic volume increases in the airport, and changes in the time interval are identified. The primary results show that the GSE traffic volume is the highest mainly around passenger terminals and in the vehicle corridors connecting these terminals, which aligns with the airport's operational status. Investigating GSE driving conditions, such as the traffic flow throughout an airport, can provide valuable data to improve the efficiency of GSE scheduling and facilitate the introduction of automated driving technology. [ABSTRACT FROM AUTHOR]

There is a limited understanding on the information-seeking behavior of international tourists during disaster response scenarios due to the lack of empirical studies on crisis communication in Japan. This study clarifies the topics generated from both international tourists and official Twitter accounts by applying the embedding Bidirectional Encoder Representations from Transformers (BERT) topic model and examines the temporal sentiment changes toward transportation and tourism using the sentiment scores obtained from topic-based Valence Aware Dictionary and sEntiment Reasoner (VADER) sentiment analysis during disasters. A case study was conducted using Twitter data on Typhoons Faxai and Hagibis, which struck Japan in 2019. This study found differences in the topics generated among international tourists and officials in response and a continuous negative sentiment toward specific transportation services. The managerial implications of these findings regarding the use of social media in crisis communication in tourism are also discussed. [ABSTRACT FROM AUTHOR]

Developing cooperative relationships between neighboring ports has emerged as an effective strategy for enhancing overall productivity. Two key factors to consider in such collaborations are: cooperative motivation (which drives the decision to cooperate between ports) and cooperation type (which defines the business scope of collaborative activities). Cooperative motivation can be categorized into regional welfare and competition, while cooperation type encompasses activities related to hinterland access and terminal management. This study aims to determine the most optimal types of cooperation based on different motivations. To achieve this, a bi-level optimization model was developed to analyze the relationship between shippers and ports, specifically focusing on the cooperation between the Kobe and Osaka ports. Competition with the Busan port was examined as a case study to provide a comprehensive understanding of the dynamics involved. The findings revealed that cooperation plays a crucial role in enhancing regional welfare for both North American and Southeast Asian cargo, particularly when cooperation levels are relatively low. Furthermore, it was observed that an effective cooperative strategy for competition in the Kobe and Osaka ports is contingent upon specific conditions. Hence, for successful competition-based cooperation, careful consideration of market dynamics and prevailing circumstances is essential. [ABSTRACT FROM AUTHOR]