Daniel OviedoMaria Jose Nieto-CombarizaAlexandria Z.W. Chong
104472.1-104472.22页
查看更多>>摘要：Walking is the primary mode of access to livelihood opportunities and resources in cities across Sub-Saharan Africa (SSA). Despite growing research and policy attention to retaining and promoting walking as a viable mechanism for access, the development of walking infrastructure and contextually relevant understandings of the links between accessibility, walking, and social inequalities continue to lag in SSA. This study explores the everyday walking practices, experiences, attitudes, and preferences of urban residents in Accra, Ghana and Maputo, Mozambique, focusing on their levels of perceived accessibility. Qualitative and quantitative evidence from three neighbourhoods across the two cities informs an assessment of the main drivers and factors influencing walking as a mode of access. We deploy multiple correspondence analysis (MCA) to determine the role of emotive responses, perceived risk and comfort, and the purpose of walking on the choice of walking as a mode of access. Findings are relevant to understanding the factors influencing walking and its perceived benefits and can inform initiatives for improving walking conditions in apparently unwalkable cities in SSA.
查看更多>>摘要：This paper experimentally investigates morning commute behavior under stochastic demand and information provision. To understand the effects of information on departure time choice behavior and how commuters respond to the provided information under stochastic demand, we conducted a laboratory experiment involving two treatments with different amounts of information provided to the subjects. Our experimental results indicated that (Ⅰ) the departure rates under different demands could be unified as a set of normalized departure rates, (Ⅱ) feedback information affected departure time choice behavior, and more feedback information might induce worse outcomes (i.e., information paradox), (Ⅲ) subjects showed heterogeneous departure time preferences, and providing more feedback information might make more subjects choose to depart early, and (Ⅳ) a small increase in the number of subjects with early departure preferences could increase traffic congestion under high demand and reduce the efficient use of transport systems. Our experimental studies shed light on the importance and complexity of information provision and departure time preferences on the morning commute traffic patterns and congestion.
查看更多>>摘要：As COVID-19 becomes a close distant memory for many, we are seeing the impact it has had on where working hours throughout the week are being undertaken. It is reasonable to assume that the support for greater flexibility in where work is completed compared to pre-COVID-19 is here to stay and that transport planning needs to move this new pattern of location behaviour centre stage in the revision of strategic transport models. Throughout a seven-day week, we are seeing days in which an individual goes to the main office all day or works from home all day, or undertakes a blended location workday, or does not work at all on a particular day. These four alternatives for each day of the week define a discrete choice model setting which together with the actual hours worked at each location on each day represents a discrete-continuous modelling setting. The paper is interested in identifying where work takes place and the committed hours for each day of the week and treats the seven days of the week as an instantaneous panel. For days where there is commuting involved, we split the discrete alternatives to account for whether commuting occurs during the peak or off-peak period of a day, which is important in terms of the commuting activities in the transport network. We account for the presence of errpr correlation between the discrete (mixed logit with error components) and continuous (seemingly unrelated regression equations) choices through a selectivity correction for each alternative where it is shown to be statistically significant. A series of direct and cross elasticities provide behaviourally informative evidence on the key drivers of the choice amongst the discrete location alternatives and the continuous choice of hours associated with each. The model system has a very practical feature, in the sense that it can be easily programmed into a strategic transport model system in order to adjust commuting travel activity by mode and time of day in the presence of a more flexible and hence less rigid profiling of when and where work takes place.
Anna-Lena van der VlugtKatrin LaettmanJanina WelschEdward Prichard...
104498.1-104498.12页
查看更多>>摘要：Walking is a healthy, cheap and environment-friendly way of travelling. Besides some studies finding effects of the built environment on walking behaviour, the influence of perceived neighbourhood walkability on walking remains largely unknown. In this study, we apply and validate the Short Perceived Walkability Scale (SPWS), a recently developed and compact scale to measure perceived walkability, and analyse its determinants in three European cities, i.e., Gothenburg, Dortmund, and Genoa. Additionally, we examine how perceived walkability can influence walking behaviour. Results show that the SPWS is a reliable measure of perceived walkability and that three types of perceived walkability can be distinguished. This perceived walkability is mainly affected by walking attitudes and to a certain extent by the spatial context. Respondents with higher levels of perceived walkability also walk more frequently, and have longer walk durations and distances, although variations occur depending on the type of perceived walkability and purpose of travel. Increasing perceived walkability levels can therefore stimulate walking and help in realising a modal shift away from car use. This could be done by improving people's walking attitudes, for instance by improving pedestrian infrastructure and removing walking barriers.
查看更多>>摘要：Car-based mobility is a significant contributor to inefficient land use, global carbon emissions, and air pollution, exacerbating urban challenges such as congestion and mobility inequality. Integrated Mobility Concepts (IMCs) in residential complexes have emerged as a promising solution, combing urban planning with sustainable transport strategies through both restrictive (push) and incentive-based (pull) measures to reduce car dependency in residential complexes. This study investigates the impact of IMCs on travel behavior by analyzing survey data from 911 residents across 19 residential complexes in Switzerland, spanning both urban and suburban contexts. The methodology involved comparing mobility patterns between 10 complexes with IMCs and 9 without, utilizing both traditional statistical methods and machine learning models. Descriptive statistics and t-tests were used for group comparisons, while multivariate regression and machine learning techniques, such as Random Forest and Lasso regression, were applied to identify key predictors of car ownership and use. The results show that urban complexes with IMCs experience 39% lower car ownership and significantly reduced reliance on private motorized transport (9% of trips, compared to 17% in conventional complexes). Parking availability was identified as the most critical factor influencing car ownership and transport behavior, with a pronounced self-selection effect where residents with sustainable mobility preferences are more likely to choose these complexes. These findings emphasize the need for context-specific mobility solutions, as the impact of IMCs is heterogeneous and varies across different demographic and spatial contexts.
查看更多>>摘要：This article uses survival analysis to model and predict passengers' tolerance for bus waiting times. It first defines and analyzes what constitutes tolerable waiting time. A Weibull distribution-based parametric model is then developed, incorporating various influencing factors. The findings show that passengers at terminal stations tolerate longer waiting times compared to those at intermediate stops. For passengers at intermediate stops, the probability of tolerating waiting times longer than 10 min is over 80% but drops below 50% for times exceeding 15 min. Median tolerance is 15 min for those with alternative routes and 20 min for those without. Tolerance is positively correlated with average weekly bus usage, and current trip duration. As waiting times increase, passengers are more likely to abandon their wait.
Raul F. Elizondo-CandanedoAldo Arranz-LopezVeronique Van AckerSusan Grant-Muller...
104505.1-104505.12页
查看更多>>摘要：This paper addresses a key gap in the literature by examining the dynamic and bidirectional relationship between in-store and e-shopping frequency during different stages of the COVID-19 pandemic. Previous studies primarily rely on cross-sectional data which fail to capture the temporal evolution and bidirectional nature of these behaviours. To overcome these limitations, this study implements a Random Intercept Cross-lagged Structural Equation Modelling (RI-CLPM) approach using three waves of panel data. Taking Luxembourg as the case study, the paper investigates the modifications in in-store shopping-related travel behaviour by evaluating shifts in trip frequency for three periods: pre-pandemic, post-peak, and relaxed measures phase. The results showed a significant shift in shopping frequency between the pre-pandemic and post-peak phase, evidencing substitution and complementarity effects both on individual as well as group level. Moreover, ANOVA and chi-square tests suggested that age and gender significantly influence in-store shopping frequency for these periods. However, no significant differences in e-shopping and in-store shopping frequencies were observed between the post-peak and the relaxed measures period. These findings provide critical insights for understanding shopping behaviour transitions and offer valuable guidance for transport policymaking. The paper closes by discussing how RI-CLPM models may improve transport policymaking, in the context of future disruptions, considering their potential for: (ⅰ) isolating policy impacts amid individual differences, (ⅱ) addressing stable and dynamic shopping behaviours, and (ⅲ) dealing with longitudinal data that allows for adaptive policy design.
查看更多>>摘要：This research develops stakeholder behavioral models (SBMs) for carriers and receivers, incorporating Social Interaction Attributes (SIAs) to assess the Willingness To Change (WTC) towards off-hour deliveries. The study uses Structural Equation Models (SEM) to tests hypotheses aimed to evaluate the impact on the WTC of the SIAs: Trust, Power, Infrastructure and Insecurity. We conducted Stated Preferences (SP) surveys targeting two primary groups: owner-operators and managers of the trucking industry (the carriers), and establishments from diverse industry and commerce segments (the receivers). The models highlight the importance of interaction between agents in shaping behavioral responses to off-hour delivery initiatives. Additionally, decisions by real estate and city agencies on infrastructure and security impact readiness to adopt off-hour deliveries. Understanding power dynamics in urban freight transportation is crucial for successful policymaking. The results support statistical evidence that powerful agents impose delivery times, affecting other stakeholders' choices and interactions. Targeting decision-makers responsible for externalities, including receivers, city agencies, and the real estate sector, is crucial. Social interactions must be included to accurately represent stakeholder behaviors and effective policymaking for off-hour delivery initiatives. The study's findings emphasize the importance of addressing stakeholders' preferences and interactions to promote sustainable freight transport policies such as off-hour deliveries.
查看更多>>摘要：The "danger zone" phenomenon refers to a counterintuitive effect in public transport service planning, observed here in a simple corridor with an express service and an "all-stop" service, where increasing the express frequency (while holding all other conditions constant) can unexpectedly worsen system performance, leading to longer queues and increased total travel times (considering waiting and in-vehicle times). This study advances the understanding of this effect through three key contributions. First, it refines the analytical model by introducing explicit service-use categories (flexible express users, flexible all-stop users, and captive users) which improves clarity and strengthens the simulation framework. Second, it proposes and validates three key performance indicators (frequency amplitude, maximum waiting time, and severity) to quantify the impact of the danger zone and provide actionable tools for transit planners. Third, it develops a microsimulation model (DZ-SIM) that incorporates realistic station-level dynamics, passenger heterogeneity, and stochastic arrivals, offering insights into the conditions that exacerbate the danger zone and supporting future research. All simulation experiments are conducted over a realistic base scenario, which represents a congested corridor served by an all-stop and an express service. Across this fixed scenario, we test different assumptions regarding passenger behavior, bus and passenger arrival patterns, access to information, and system parameters. The simulation results validate the robustness of the danger zone effect: as express frequency increases, expected travel times initially rise (due to a sudden shift in demand toward the express service and the resulting congestion) and then stabilize at a plateau, offering no significant improvement until queues are fully dissipated. This nonmonotonic behavior reinforces the principle that only sufficiently large frequency increases yield meaningful improvements, supporting a "go big or go home" approach to express service planning. Our findings also reveal that the danger zone is most likely to occur when express services are highly attractive (i.e., offering significant time savings and serving a high proportion of flexible users) but are not frequent enough to accommodate the demand they generate. These insights support more effective express service planning by helping transit agencies avoid costly frequency increases that fail to deliver meaningful user benefits.
查看更多>>摘要：The COVID-19 pandemic had an unprecedented and devastating impact on the aviation industry. Although the pandemic has subsided, there are many lessons to learn from this experience that could be useful for navigating the possible future recurrence of similar events. In this study, we develop differential game models to investigate airlines' competition strategies during the pandemic, and governments' regulations (i.e., travel restriction and travel bubble policies) are examined and compared. We find the travel bubble policy to be superior to the travel restriction policy in terms of social welfare. We also present the conditions under which governments should bail out airlines to avoid potential bankruptcies. Furthermore, our models are extended to incorporate ambiguity in key information regarding the pandemic, such as when governments and airlines do not know the infection-recovery ratio of the pandemic exactly. We find that improving pandemic information (e.g., using measures such as COVID passports) can benefit social welfare only when the targeted infection is low. We conclude that reducing ambiguity performs better under the travel restriction policy than the travel bubble policy.
NETL
NSTL
Elsevier