Objective: This paper aims to provide a comprehensive overview of the current state of agent-based models, focusing specifically on their application in urban transportation research. It identifies research gaps and challenges while outlining the key potential directions for future research. Methodology: To conduct this study, a bibliometric analysis has been performed on 309 documents obtained from the Scopus database. The resulting clustering analysis has been further supplemented with content analysis. Findings: The analysis reveals the existence of nine distinct clusters representing a wide range of research methods and problem interpretations in the field. In-depth examination of selected publications within each cluster has helped to identify key challenges faced by agent-based modelling approaches. These challenges include enhancing computing efficiency, developing unified calibration and validation methods, ensuring reproducibility of work, and incorporating various modules or frameworks into models to accurately replicate the complexities of the transport system and travel behaviour within specific application contexts.

With the advent of activity-based modelling, transport planners’ focus has shifted from isolated trips to tours. Tours are series of interconnected trips that start and finish at home. There are different types of tours; we focus on two: hwh (start at home; go to work; and then go back home) and hw+wh (where + represents a non-work activity). Tour types introduce a new dimension to the traditional problem of travel mode choice, as the mode choice might be influenced by the type of tour. This study attempts to measure and compare the relationship between tour type and mode choice using three different modelling approaches: Multinomial Logit (MNL); Nested Logit (NL) and Cross-Nested Logit (CNL). We compare each approach using secondary data from a larger survey: 24-h daily activity patterns of 420 commuters between Bekasi and Jakarta; one of the busiest commuting routes in Indonesia. Among other results, we found that gender and income significantly influence commuter’s choice of mode and that reducing travel time and cost can increase the ridership of public transport. Furthermore, the NL and CNL models showed significant improvement over the simpler MNL when grouping the alternatives based on tour types. This points to a significant influence of the tour type on the mode choice. Policy recommendations to increase traveler’s wellbeing are also formulated.

Despite the establishment of the Trans Jogja Bus (TJB) service in 2008 as a solution for the problems with conventional bus services in numerous Indonesian cities, public transport ridership in Yogyakarta has remained somewhat stagnant. On TJB, adolescents comprise the dominant demographic group. This study investigated the factors influencing the frequency of TJB use, including sociodemographic and household characteristics, the built environment, perception of TJB performance, pro-environmental attitudes, and health behaviors among adolescents aged 13 to 15 years old. A face-to-face interview survey was conducted to collect data on 774 adolescents. This study used both an ordered logit model in which the perception variables were set as the independent variables and an ordered hybrid choice model, which incorporated the latent variables on adolescents’ perception of TJB use. The model results reveal that age, the number of adults in a household, car ownership, and the distance to school correlate with the use of TJB. We found that positive perceptions of TJB such as safety, security, comfort, and low cost substantially influence the use of TJB compared with negative perceptions such as infrequent buses, scarce bus stops, and slow meandering bus routes. With this in mind, perceived benefits such as reduced congestion, improved health, and environmental advantages have no significant influence on the frequency of TJB use. The model results emphasize the need to improve route efficiency, enhance existing performance, and promote TJB as a healthy, green, and sustainable travel mode.

Nowadays, airports are expected to be operated as a self-service organisation that provides efficient and high-quality services. Since the satisfaction of passengers is essential for airport’s operators, the efforts to provide better services for passengers become a concern for airport’s operators by increasing the quality of service to passengers. It is crucial to identify which kind of services that would be the top priority service for the passengers. Thus, this study aims to improve the quality of service to passengers that are conducted by combining the Servqual method and Kano model. Servqual method is used to capture consumer perceptions and expectations of service along with the multi-dimensional research instrument, while the Kano model is a theory to observe costumer’s satisfaction preferences. The combination of the methods aims to determine the type of service that becomes the top priority for immediate improvement so that it can improve the service quality effectively. The selection of the priority services is based on the magnitude of the gap between expectations and perceptions of passengers on a particular service, and the assessment of passengers on the type of service that significantly influences passengers’ satisfaction with the service performance at the airport. The results of this research showed that there were three types of services as the top priority for improving their performance, namely the type of services related to the personal attention to passengers, the attractive waiting room conditions, and the understanding of each passenger’s needs individually. The airport management is expected to immediately improve the performance of the services so that the quality of service can immediately increase.