Public transport is a known hotspot for sexual violence and harassment. Through 41 interviews with women and gender-diverse people who have experienced sexual violence and harassment on public transport, we found that women and gender-diverse people engage in extensive \"safety work,\" such as changing their behavior, strategizing, and planning. Safety work takes considerable time and effort, often leaving participants feeling stressed. However, participants advocated for changes to public transport to reduce the work they do to stay safe. We argue that significant changes, including primary prevention of gender-based violence, are needed to reduce their safety work.

BACKGROUND: Most evidence on transport use and mortality has focused on the commute to work. This study aims to fill a gap by assessing relationships between public transport use and mortality among older adults.
METHODS: Data come from a cohort of 10,186 individuals aged 50 or older who participated in the English Longitudinal Study of Ageing (ELSA), with survey data linked to mortality records over 16 years (2002-2018). We assessed a binary measure of public transport use and frequency of use from \'every day or nearly every day\' to \'never\'. Cox proportional-hazards regression models were used to estimate hazard ratios (HRs) with 95% confidence intervals (CIs) for associations between public transport use and mortality. Analyses were adjusted for a range of covariates including socio-demographic factors, chronic disease, and self-reported problems with daily living activities.
RESULTS: Overall, 3371 participants (33.1%) died within the study period. Mortality was lower among public transport users (21.3%) compared with non-users (64.2%). Adjusted analyses found that users had 34% lower mortality than non-users (HR 0.66 (95% CI 0.61;0.71)). Adjusted analyses showed similar association sizes across frequencies of public transport use, with those using public transport every day or nearly every day having 41% lower mortality than never users (HR 0.59 (0.49;0.71)). Associations were similar among those with and without a longstanding illness.
CONCLUSIONS: The use of public transport among older adults is linked to lower levels of mortality. Reductions in provision of public transport services could be detrimental to both transportation and population health.

Service failure is bound to happen, but dissatisfaction has always been undermined by scholars previously. The present study investigates dissatisfaction factors in travel decision-making leading towards re-travel intention with the help of the expectancy disconfirmation theory (EDT) model. Moreover, complaint behavior mediates the relationship between dissatisfaction and re-travel intention concerning the factors involved in it. For the findings, 434 real-time responses were collected through an offline survey following the lifetime value (LTV) approach. Kaiser-Meyer-Olkin (KMO) and Bartlett\'s tests were conducted to test the sphericity of the variables one by one. Furthermore, structural equation modeling (SEM) was implied to test the measurement and structural models. All the hypotheses supported and accepted the proposed research questions. The findings reveal that the dissatisfaction factors, with their interaction terms (transaction-based and experience-based), help study the variable dissatisfaction and its multifaceted concept in travel and tourism literature. Moreover, complaint behavior is identified as a key mediating factor in the relationship between dissatisfaction and re-travel intention, suggesting that commuters\' response to dissatisfaction, including complaints, shapes their future re-travel intentions. The theoretical implications of the study are substantial, as it advances our understanding of commuter behavior in the context of public transport travel and tourism. Practically, the findings offer actionable insights for public transport authorities and service providers. Understanding the specific dissatisfaction factors influencing re-travel intention allows for targeted interventions to improve service quality and customer experience. Recognizing the importance of effective complaint management systems can help organizations better address customer grievances and mitigate the negative effects of dissatisfaction on re-travel intention.

OBJECTIVE: The health benefits of active commuting have been reported. However, few studies have assessed commuting modes using objective methods. This study clarified the association between changes in objectively measured commuting modes and body weight among Japanese workers.
METHODS: This longitudinal study used data from the annual health examinations and personnel records of a company with branches in all prefectures of Japan. Data from 2018 and 2019 were used as the baseline and follow-up data, respectively. The commuting mode was assessed using the commuting mode code included in the personnel records and classified into 3 types: walking, public transport, and car or motorcycle. The participants were classified into 9 categories based on the combination of their commuting modes in 2018 and 2019. Body weight was measured objectively during health examinations. The 1-year changes in body weight were calculated for the 9 categories and assessed using an analysis of covariance with adjustments for covariates.
RESULTS: The analysis included 6551 workers (men: 86.8%; mean age: 42.8 years). Overall, body weights tended to increase (+0.40 kg/y). The participants who switched to more active commuting, such as from car or motorcycle to walking (-0.13 kg/y), from car or motorcycle to public transport (+0.10 kg/y), and from public transport to walking (-0.07 kg/y), exhibited small weight gains or losses. A similar trend was observed even after adjustment.
CONCLUSIONS: Changing to a more active commuting mode may prevent weight gain among workers.

Public transportation plays a critical role in meeting transportation demands, particularly in densely populated areas. The COVID-19 pandemic has highlighted the importance of public health measures, including the need to prevent the spread of the virus through public transport. The spreading of the virus on a passenger ship is studied using the Computational Fluid Dynamic (CFD) model and Monte Carlo simulation. A particular focus was the context of Bangladesh, a populous maritime nation in South Asia, where a significant proportion of the population utilizes passenger ships to meet transportation demands. In this regard, a turbulence model is used, which simulates the airflow pattern and determines the contamination zone. Parameters under investigation are voyage duration, number of passengers on board, social distance, the effect of surgical masks, and others. This study shows that the transmission rate of SARS-CoV-2 infection on public transport, such as passenger ships, is not necessarily directly proportional to voyage duration or the number of passengers onboard. This model has the potential to be applied in various other modes of transportation, including public buses and airplanes. Implementing this model may help to monitor and address potential health risks effectively in the public transport networks.

Public transport priority systems such as Bus Rapid Transit (BRT) and Buses with High Level of Service (BHLS) are top-rated solutions to mobility in low-income and middle-income cities. There is scientific agreement that the safety performance level of these systems depends on their functional, operational, and infrastructure characteristics. However, there needs to be more evidence on how the different characteristics of bus corridors might influence safety. This paper aims to shed some light on this area by structuring a multivariate negative binomial model comparing crash risk on arterial roads, BRT, and BHLS corridors in Bogotá, Colombia. The analyzed infrastructure includes 712.1 km of arterial roads with standard bus service, 194.1 km of BRT network, and 135.6 km of BHLS network. The study considered crashes from 2015 to 2018 -fatalities, injuries, and property damage only- and 30 operational and infrastructure variables grouped into six classes -exposure, road design, infrastructure, public means of transport, and land use. A multicriteria process was applied for model selection, including the structure and predictive power based on [i] Akaike information criteria, [ii] K-fold cross-validation, and [iii] model parsimony. Relevant findings suggest that in terms of observed and expected accident rates and their relationship with the magnitude of exposure -logarithm of average annual traffic volumes at the peak hour (LOG_AAPHT) and the percentage of motorcycles, cars, buses, and trucks- the greatest risk of fatalities, injuries, and property damage occurs in the BHLS network. BRT network provides lower crash rates in less severe collisions while increasing injuries and fatalities. When comparing the BHLS network and the standard design of arterial roads, BHLS infrastructure, despite increasing mobility benefits, provides the lowest safety performance among the three analyzed networks. Individual factors of the study could also contribute to designing safer roads related to signalized intersection density and curvature. These findings support the unique characteristics and traffic dynamics present in the context of Bogotá that could inform and guide decisions of corresponding authorities in other highly dense urban areas from developing countries.

The importance of public transportation service quality research is significantly increasing in recent years, it is the key to understanding and analyzing passengers\' preferences. Different approaches are utilized to explore users\' preferences however, dominantly these apply merely subjective scoring of the attributes and alternatives of the mobility. In this paper, we design a specific model for public transportation mode choice which is capable of integrating subjective scoring with scoring by objective measures such as distance or time. Owing to this purpose, we combine the outranking Preference Ranking Organization METHod for Enrichment Evaluation (PROMETHEE) as a method to evaluate passengers\' preferences for tangible and intangible criteria with the fuzzy theory, and the Graphical Analysis for Interactive Aid (GAIA) plane to visualize the interactions between attributes as well as to test the robustness of the results via sensitivity analysis. The contribution of this paper is the constructed integrative method that is less subjective than the well-known models but also keeps the freedom of individual evaluators in expressing their preferences. Moreover, another significant issue of mode choice analysis is the group consideration, which is also refined in the new methodology by taking into account not only the mean of group preferences but also their range. A common characteristic of public surveys, the possible vague responses of the layman pattern is solved with the fuzzy approach to reduce the risk of uncertain scoring. The proposed model acts as a great base for the fuzzy inference system that can facilitate mode choice for passengers within a changing environment. The efficiency of the new methodology is demonstrated through a real-world case study of Budapest city, the obtained results are supporting underground mode service quality and highlighting its impact on citizens\' behavior in favor of public transport.

Public transport has become an essential part of urban existence with increased population densities and environmental awareness. Large quantities of data are currently generated, allowing for more robust methods to understand travel behavior by harvesting smart card usage. However, public transport datasets suffer from data integrity problems; boarding stop information may be missing due to imperfect acquirement processes or inadequate reporting. This study introduces a supervised machine learning method to impute missing boarding stops based on ordinal classification using GTFS timetable, smart card, and geospatial datasets. A new metric, Pareto Accuracy, is suggested to evaluate algorithms where classes have an ordinal nature. The results are based on a case study in the city of Beer Sheva, Israel, consisting of one month of smart card data. We show that our proposed method is robust to irregular travelers and significantly outperforms well-known imputation methods without the need to mine any additional datasets. The data validation from another Israeli city using transfer learning shows the presented model is general and context-free. The implications for transportation planning and travel behavior research are further discussed.

The current paper focuses on a comparative analysis of both public transport (PT) and private vehicle (PV) users\' perceptions on the quality of the service. To detect the key components of PT attributes a new hybrid methodology is applied, combining the importance-performance analysis and the importance-performance map analysis. The proposed hybrid approach is simpler and more integrated than the existing methods in the literature. The sample comprises an online panel and a total of 1028 questionnaires for PV and PT users surveyed during the pandemic period in Budapest. The results of the applied methods show that among the different groups, the service hour, the proximity, and the frequency attributes are important and performed well in the years of COVID-19. On the other hand, the temperature and the cleanliness factors are not significant predictors of the PV and PT users\' general satisfaction. The obtained results can be used by local governments and authorities, who seek to identify areas to enhance the service quality of PT during movement restrictions in a pandemic wave.

UNASSIGNED: We present a sketch for a nationwide \"Mobility Service Guarantee\" (MSG) for Austria. The approach follows a new paradigm, turning away from car-centric transport policy and planning and towards the extensive provision of public transport. The approach is complemented by the provision of demand-responsive transport services and the support of vehicle sharing as well as active mobility. This combination should serve as an effective alternative option to the use of private cars.
UNASSIGNED: The aim of this study is to develop a tangible definition of a nationwide MSG in the Austrian context as well as possible design scenarios.
UNASSIGNED: We took a multi-dimensional approach, using literature review to research existing concepts of mobility guarantees, analysing secondary data on current mobility behaviour and public transport provision and conducting stakeholder workshops.
UNASSIGNED: We define possible scenarios envisioning a nationwide MSG including different extents of maximum distance to public transport stops and minimum frequency. We discuss the limitations of the MSG with respect to spatial, temporal and modal coverage, as well as how such a guarantee could be embedded in the existing legal system.
UNASSIGNED: We conclude that a nationwide MSG could be an important element of sustainable transport policy that should be embedded in a wider strategy of infrastructure and service design as well as demand management.