Commute Mode Research Articles

Does mental health influence commuters’ mode choice? A cross-sectional assessment from the Netherlands

BackgroundPeople’s mental health may play a role in influencing their travel behaviors; however, few studies have quantified the association between mental health and commuting mode choice. ObjectiveThis study examined 1) how mental health is associated with commute mode choice and 2) whether gender differences exist. Data and methodsWe used cross-sectional data from a population-representative sample of 7,280 adults aged 18-65 from the Netherlands. We applied multilevel multinomial logit regression models to investigate the associations between commuting mode choice and self-perceived mental health controlled for multiple person-level and built environmental characteristics. We also assessed possible effect modification by gender. ResultsOur covariate-adjusted regression results based on the entire sample showed no compelling evidence for an association between self-perceived mental health and commute mode choice. While we found null associations between mental health and commute mode choice for women, stratified analyses showed that men with relatively poorer mental health were likelier to commute via bus/tram. ConclusionOur cross-sectional findings weakly support the notion that men’s mental health may be related to commute mode choice and no such relationship was found for women. However, we advocate more research before ruling out the possibility of complex interactions between mental health and commuting behavior.

Tracing long-term commute mode choice shifts in Beijing: four years after the COVID-19 pandemic

The COVID-19 pandemic has brought urban mobility into a new era. This study traces post-pandemic shifts in commute mode switch behaviors and their environmental effects based on an event study design and a mobile phone signaling dataset for Beijing from April 2018 to November 2023. The results show that in the outbreak stage, public transit mode share nosedived, with transit riders 5.11 and 3.75 times more likely to switch to private car and active modes, respectively; in the post-pandemic stage, public transit recovered rapidly and to a large extent, but the increase of private mode dependency persisted, as transit riders were 1.88 times more likely to switch to private cars, and transit riders and car drivers were 1.37 and 1.32 times more likely to adopt active modes, respectively; in the pandemic-free stage, signs of private car dominance began to emerge, as driving habits strengthened and more active travelers resorted to driving, indicating the closing of the window of opportunity to promote low-carbon private transport. This study presents the longest longitudinal tracking of post-pandemic travel mode choice so far. The challenges and opportunities faced by the transportation system are discussed, and policy implications and future research directions are provided.

Differences in Fibromyalgia Characteristics by Mode of Commute and Age in Women: The Al-Ándalus Project.

This study aimed to test whether fibromyalgia-related characteristics differ by mode of commute and by age in women with fibromyalgia. A total of 450 women with fibromyalgia (aged 52.0 ± 8.0 years old) were included. Data on their body composition, socioeconomic factors, health-related quality of life (HRQoL), depressive symptoms, sleep quality, pain-related outcomes, fatigue, and mode of commute, as well as the impact of fibromyalgia on their lives, were obtained. We performed linear regression analyses to test the differences in fibromyalgia-related characteristics between the participants engaged in active/passive modes of commuting. To analyze in depth the differences, a one-way analysis of covariance with Bonferroni's correction for multiple comparisons was conducted. In the younger group, active commuters presented differences in fibromyalgia-related characteristics (all, p < 0.01): they were less impacted by having fibromyalgia, had lower levels of fatigue, and had a higher HRQoL than passive commuters. We observed no differences in symptoms between active and passive commuters in the older group (all, p > 0.05). The possible positive effect of active commuting on fibromyalgia-related characteristics might be reduced by age and by a decrease in total physical activity. Physical activity programs for women with fibromyalgia focused on improving fibromyalgia-related characteristics should consider active commuting behaviors to increase their effectiveness.

Sickness absence patterns during the COVID-19 pandemic among Finnish public sector employees

Abstract Background The patterns of sickness absence (SA), that is, the clustering of differing lengths of episodes and total number of days absent, have not been examined. We examined these SA patterns and factors associated with the patterns during the COVID-19 pandemic. Methods We used survey data from employees of four large Finnish cities in 2020 linked with SA data in 2021 retrieved from employer registers (n = 39 791). SA patterns were defined through cluster analysis (K-means) including number of SA days, short (1-9 days), and long (10-365 days) SA episodes within one year. The associations of employee and work characteristics in 2020 with SA clusters in 2021 were analysed with multinomial regression. Results Four SA patterns (=clusters) were identified: 1) Optimal SA pattern (n = 31 320, 79%), 2) Recurring short SA episodes (n = 5149, 13%), 3) Recurring long SA episodes (n = 2964, 7%), and 4) Very high levels of SA with long episodes (n = 358, 1%). Compared to optimal SA pattern, female gender, higher body mass index, former smoking, abstinence from alcohol, not being in high occupational socioeconomic position, on-site work during COVID-19, and COVID-19 infection were associated with all suboptimal SA patterns. Recurring short SA episodes were more likely in younger employees (odds ratio=0.98, 95% confidence interval 0.97-0.98), those with a temporary job (1.10, 1.00-1.20), current smokers (1.34, 1.21-1.48), those using passive commute modes (1.03, 1.01-1.05 [car]; 1.02, 1.00-1.04 [public transport]), and those who had experienced a team reorganization due to COVID-19 (1.27, 1.10-1.46). The two most adverse SA patterns were more likely among older employees, and less likely among those cycling to work (0.91, 0.84-0.98; 0.97, 0.95-0.99). Conclusions We identified three differential suboptimal SA patterns. Compared to the optimal SA pattern, several individual-level risk factors, but also some COVID-19 related factors were found to associate with suboptimal SA patterns. Key messages • We identified three suboptimal sickness absence patterns during COVID-19 pandemic. • Individual characteristics, but also COVID-19 related factors were associated with the observed sickness absence patterns.

Overlooked factors contributing to U.S. highway fatalities

This study aimed to examine the effects of highway expenditure, number of transportation employees, and four work commute modes (driving alone, carpooling, public transportation, and motorcycle), and road condition on highway safety across Louisiana, the Gulf of Mexico states region, the Southern states region, and the U.S. as a whole. Data spanning from 2004 to 2021 were collected and analyzed using the stepwise multiple linear regression method. The analysis focused on their relationships with two key highway fatality rates: Fatality Rate 1 (number of fatalities per vehicle miles traveled) and Fatality Rate 2 (number of fatalities per number of drivers). Eight regression equations were developed and validated. The findings will provide valuable insights for policymakers, facilitating the development of effective policies and strategies to enhance highway safety and reduce fatalities.

Development of a multifactorial prediction model for commute mode choice in 10 983 Finnish public sector employees: a cross-sectional study

ObjectiveThe objective of this study is to examine the feasibility of using survey data to identify factors that predict commute mode choice.DesignThe study design is cross-sectional.SettingSurvey data from the Finnish...

Logit and Probit Models Explaining Mode Choice and Frequency of Public Transit Ridership among University Students in Krakow, Poland

The predictors of urban trip mode choice and one of its important components, public transit ridership, have still not been thoroughly investigated using case studies in Central Europe. Therefore, this study attempts to clarify the correlates of mode choices for commute travel and shopping, and entertainment travel to distant places, as well as the frequencies of public transit use of university students, using a wide range of explanatory variables covering individual, household, and socio-economic attributes as well as their perceptions, mobility, and the nearby built environment. The correlation hypothesis of these factors, especially the role of the street network, was tested by collecting the data from 1288 university students in Krakow and developing Binary Logistic and Ordinal Probit models. The results show that gender, age, car ownership, main daily activity, possession of a driving license, gross monthly income, duration of living in the current home, daily shopping area, sense of belonging to the neighborhood, quality of social/recreational facilities of the neighborhood, and commuting distance can predict commute and non-commute mode choices, while gender, daily activity, financial dependence from the family, entertainment place, quality of social/recreational facilities, residential self-selection, number of commute trips, time living in the current home, and street connectivity around home are significantly correlated with public transit use. Some of these findings are somewhat different from those regarding university students in Western Europe or other high-income countries. These results can be used for policy making to reduce students’ personal and household car use and increase sustainable modal share in Poland and similar neighboring countries.

License to drive: State driver’s licensing laws and the travel of unauthorized immigrants

Since 1993, eighteen states and the District of Columbia have adopted laws allowing unauthorized immigrants to acquire driver’s licenses. California is one of these states, passing the Safe and Responsible Drive Act (AB 60) in 2013. In this paper, we examine the relationship between the adoption of state driver’s licensing laws and the commute mode of unauthorized immigrants. We focus specifically on the proportion of unauthorized Latin American immigrants in California who commute by car, drive alone to work, and commute by public transit, testing a number of model specifications and proxies for identifying undocumented immigrant residents. We find that the implementation of AB 60 was associated with a 2.0 percentage-point increase in car commuting and a 4.2 percentage-point increase in driving to work alone by unauthorized immigrants. Results also show a 1.4 percentage-point decline in the rate of commuting by public transit after AB 60′s implementation. This drop in transit use, however, was less statistically robust than findings regarding car commuting.

Car Ownership, Commute Distance, and Commute Mode Choice in the Dense Megacity of a Developing Country: The Direct and Indirect Role of the Built Environment

Despite much having been published about the effects of the built environment (BE) on urban travel in the developed world, few articles have so far been published based on studies using a megacity in a developing country. The paper addresses the existing gaps in research by conducting a study in Dhaka, one of the densest urban areas globally. An integrated framework based on the structural equation model and discrete choice model is used to examine how individual commute mode choice behavior is influenced by the BE, as mediated by car ownership and commute distance. Three BE features—population density, street connectivity, and job-to-household ratio—have a direct and total positive association with non-motorized transport use. Although being close to bus stops does not directly affect people’s choice to take non-motorized transport, it does promote non-motorized travel in an indirect way by decreasing car ownership and commute distance. Population density, job-to-household ratio, proximity to the nearest central business district, and bus stop proximity all have a positive direct and total impact on transit use, although larger employment densities directly support automobile use over transit. Understanding how the BE affects commute distance, car ownership, and mode choice is a useful reference for the development of practical measures to reduce demand for automobiles.

Travel behaviour changes among post-secondary students after COVID-19 pandemic – A case of Greater Toronto and Hamilton Area, Canada

Recent research has reported travel behaviour changes during the COVID-19 pandemic. Speculatively, these short-term disruptions in travel may lead to new habit formation and longer-term travel behaviour changes among young adults belonging to generations Y and Z. Focusing on post-secondary students within Greater Toronto and Hamilton Area, Canada and using longitudinal data collected in fall 2019 and spring 2022, our exploratory study examined the post-COVID-19 travel behaviour changes and analyzed whether these changes are associated with their socio-demographic characteristics and life events experienced over the course of pandemic. Results show that many public transit users and active travellers (pedestrians and cyclists) switched to cars for commuting post-pandemic. The post-pandemic retention of public transit use was lower compared to cars, while active transportation modes had the lowest post-pandemic retention rate. Some socio-demographic characteristics such as age, living situation, work hours and access to cars were significantly associated with these changes. In terms of life events, students who joined workforce after completion of education between 2019 and 2022 were more likely to shift their commute mode from public transit to cars, implying some influence of this life event on commute mode changes, in addition to pandemic-induced changes. Our findings suggest that the post-pandemic commute mode changes observed among young adults in the GTHA may not be a result of only COVID-19 pandemic and may also be partly associated with important life events that they experienced over the course of pandemic. Future transportation planning and policy implications, and directions for future research have been discussed.

Post-pandemic transit commute: Lessons from focus group discussions on the experience of essential workers during COVID-19

Public transit services, which provide a critical lifeline for many essential workers, were severely interrupted during the COVID-19 pandemic. As institutions gradually return to normal in-person operations, it is critical to understand how the pandemic affected essential workers' commute and what it will take to ensure the effective recovery of transit ridership and enhance the long-term resiliency and equity of public transportation systems for those who need it the most. This study used focus group discussions with essential workers who were pre-pandemic transit riders to understand how the COVID-19 pandemic has impacted their commute perceptions, experiences, motives, and challenges and explore the potential changes in their travel behavior post-pandemic. We used NVivo 12 Pro to conduct a thematic analysis of the transcripted discussion data and examined patterns of commute mode change with respect to participants' attributes, including job type, home location, and gender. The results show that public transit had multiple reliability and frequency challenges during the pandemic, which resulted in most participants switching away from public transportation. With the increased availability of hybrid remote work and pandemic-related parking policies, driving emerged as a safer and more affordable commute mode for many pre-pandemic transit riders, rendering transit services less efficient for those who continued to rely on it. Planning for post-COVID resilient and reliable mobility requires a major rethinking of providing an efficient and effective transport system and a more fundamental approach to long-term public transport policy. To recover transit ridership, transit agencies need to ensure transit service availability and provide reliable transit information through smartphone apps. Similarly, transit agencies need to coordinate with other employers to provide free or heavily subsidized transit passes, to facilitate the recovery of transit demand effectively.

Commute mode — physical activity and the possibility of change to active commuting among Japanese workers: a descriptive study by region

Changing the mode of commuting from nonactive by car or motorcycle to active by walking, cycling, or public transport is expected to benefit health. However, the proportion of nonactive commuters who can change their commute mode to active forms remains unclear. The aim of this study was to determine the proportions of nonactive commuters and of those who can change their commute mode to an active form in various regions in Japan. In this descriptive study, data were used from an online survey conducted from April to May 2021. Participants included 3,000 adults (20 to 79 years), who were registered with an online survey company. Workers were asked their means of transportation to work and commuting time. Workers using a car or motorcycle for more than 1 minute for commuting were defined as nonactive commuters, and the others were defined as active commuters. Then, nonactive commuters were asked about the possibility of changing their commute mode to active commuting (0%-100%, 11 options in 10% increments). The possibility of change was classified into four groups, i.e., impossible (0%), difficult (10%-40%), probably possible (50%-90%), and possible (100%). The proportions of nonactive commuters and nonactive commuters who can transition to active commuting were described by region. A total of 2,683 participants answered the survey, including 1,647 workers, of whom 1,551 were commuters. The nonactive commuters accounted for 41.4% of commuters overall. The proportion of nonactive commuters was higher in rural than in urban regions. The proportion of nonactive commuters who could change their commute mode was 32.9% of the nonactive commuters or 12.8% of all workers. Among the nonactive commuters, the proportion who could change their commute mode was higher in urban than in rural regions. Of the total workers, the proportion of nonactive commuters who could change their commute mode was higher in rural regions. Nonactive commuters accounted for 41.4% of all commuters. The proportion of nonactive commuters who could change their commute mode among nonactive commuters was higher in urban regions. However, in rural regions, as the proportion of nonactive commuters was high, the proportion of nonactive commuters who could change their commute mode among total workers was also high. These results suggest that some of nonactive commuters can change their commute mode from nonactive to active commuting, in rural as well as in urban regions.

Unveiling the drivers of modal switch from motorcycles to public transport in Southeast Asia

Most studies on commuter and public transport mode choice rely on theoretical frameworks that draw boundaries between the utility function, social-ecological system, demographic and socio-economic attributes, and psychological theory. While models predicting the shift towards public transport are commonly applied in developed countries, there is a lack of similar studies that construct these models in developing countries. In addition, in some developing countries, the motorcycle is one of the main private motorised travel modes. Therefore, the modal shift from motorcycles to public transport in Southeast Asia to reduce private mobility is one of the important topics to examine. This paper presents a systematic literature review, utilising a comprehensive search strategy across electronic databases and reputable sources to identify directed acyclic graphs (DAGs), revealing factors influencing the choice and intention to shift to public transport. Data synthesis from selected studies highlights the intrinsic and extrinsic variables influencing public transport use, motorcycle use, and the modal shift to public transport. The study also proposes a theoretical framework for the modal shift in usage from motorcycles to public transport.

Built environment influences commute mode choice in a global south megacity context: Insights from explainable machine learning approach

In this study, we aimed to investigate the influence of the built environment (BE) on commuter mode choice using machine learning models in a dense megacity context. We collected 10,150 home-based commuting trips data from Dhaka, Bangladesh. We then utilized three machine learning classifiers to determine the most accurate prediction model for predicting the mode of transportation chosen for commuting in Dhaka. Based on the predictive performance of the classifiers, we identified that the Random Forest (RF) algorithm performed the best. Using the RF model, this study also explored the relative importance of BE factors in predicting commute mode choice, identified nonlinear relationships between the BE factors and mode choice, and examined the interaction effects of these factors on mode selection. Our results reveal that, compared to socio-demographic factors, the BE substantially influence commuter travel behavior. The BE characteristics have a specific nonlinear threshold limit at which they can have a notable impact on lowering private car use, and private car use does not display a constant return of scale with BE. Their interaction effects illustrate the potential optimal combination of BE interventions to lower private car use for commuting. These findings hold substantial implications for urban environmental policy, emphasizing the need for transit-oriented development, travel demand management, and integrated land-use transportation planning to foster low-carbon transportation systems in cities like Dhaka.

A decision-aid system for subway microenvironment health risk intervention based on backpropagation neural network and permutation feature importance method

Subway has become an important commute mode in daily life. However, subway microenvironment poses a threat to people's health and there is growing concern about its health risks. In this paper, a decision-aid system for subway microenvironment health risk intervention was proposed based on the combination of backpropagation neural network algorithm and permutation feature importance method. The non-linear relationship between indicators and the risks of subway microenvironment was established using the neural network. On this basis, the implementation of stepwise intervention, neural network prediction, and the generation of strategies was achieved utilizing MATLAB programming. Moreover, a subway station in Nanjing was taken as an example to illustrate the implementation and verify the effectiveness of the system. With the help of the system, health risks in the subway microenvironment can be systematically analyzed, efficiently optimized, and gradually solved. Our research contributes to breaking the deadlock in subway microenvironment intervention, which has long been confined to predicting and summarizing strategies. It provides more objective and effective intervention strategies for the health risk management of subway microenvironments.

Exploring the changes in the interrelation between public transit mode share and accessibility across income groups in major Canadian cities in the post-pandemic era

The COVID-19 pandemic has impacted the travel behaviour of urban residents in an unprecedented manner, especially public transit (PT) users. PT has experienced a decline in ridership around the world early in the pandemic and has been struggling to rebound again to the pre-pandemic levels, whereas other modes have reached their pre-pandemic levels. PT agencies have been trying to attract users back through service improvements and other policies; nevertheless, the impacts of policies that were effective prior to the pandemic are not guaranteed in the post-pandemic world due to the lasting effects of the pandemic on travel behaviour. This study compares the changes in the impacts of accessibility, the ease of reaching destinations, to jobs by PT on commute mode share pre- and post-pandemic (2016 and 2021) with an equity lens in the three largest metropolitan regions in Canada: Toronto, Montreal, and Vancouver. Results show that planning for accessibility is still an impactful tool to increase PT mode share in the post-pandemic era, yet the magnitude of the impact has declined by almost 50% in Toronto and Montreal and 30% in Vancouver for low-income groups. In the post-pandemic era, the impact of accessibility on PT mode share remains higher for the low-income compared to other-income groups, which is similar to the pre-pandemic times. Understanding the changing effects of accessibility, a major land use and transport planning tool, on travel behaviour is important as PT agencies are developing strategies to restore pre-pandemic levels of ridership and increase it to reach their sustainability goals.

Identifying employee, workplace and population characteristics associated with COVID-19 outbreaks in the workplace: a population-based study

ObjectivesTo identify risk factors that contribute to outbreaks of COVID-19 in the workplace and quantify their effect on outbreak risk.MethodsWe identified outbreaks of COVID-19 cases in the workplace and investigated...

Comparative Analysis of Public Transportation Comfort in Addis Ababa: Objective and Subjective Performance Metrics

Passenger comfort significantly influences commuter satisfaction and mode preferences in urban transportation systems. To maintain competitiveness and attract more passengers, conducting continuous performance evaluations based on key performance indicators is commendable. Therefore, this study is aimed at conducting a mode‐wide comfort performance evaluation and comparisons to identify the strengths and weaknesses of respective mass transport alternatives found in Addis Ababa, Ethiopia. The study employs a comprehensive approach by integrating both subjective surveys and objective measurements on key comfort determinants, including in‐vehicle passenger loading, travel time, vibration, and sound, across five transport modes: minibus taxis, midi buses, PSETSE, Anbesa City Bus Service Enterprise (ACBE), and Sheger Mass Transport Enterprise (SMTE). Analysis of variance (ANOVA) reveals variations among transport modes, with minibus taxis emerging as the most comfortable, featuring a travel time of 1.7 min/km, 2.6 min/km during off‐peak and peak times of the day, respectively, and an average of 1.13 passengers per seat in both periods of the day. In contrast, midi buses are identified as the least comfortable, characterized by elevated noise production (77.46 and 80 dB) and an average vibration rating of 3.9 and 4.2 at peak and off‐peak periods of the day. Following midi buses, the ACBE exhibits the highest passenger loading and travel time (2.113 and 1.548 passengers per seat and takes 4.2 and 3.34 min) to cover 1 km during peak and off‐peak periods, respectively. The holistic evaluation demonstrates an average correlation of 81.75%, indicating a strong alignment between peak‐hour objective and subjective assessments. This could help commuters make relevant mode choice decisions and transport companies make market‐oriented decisions in this competitive environment.

Analysis of contributing factors in decision to bicycle in developing countries context

Bicycling is a healthy and environmentally beneficial mode of transportation. Despite substantial benefits of bicycling, it is mostly overlooked as a daily form of transportation. Due to urbanization and development in the motorized industry, commuters are attracted to motorized transport modes. The present study was carried out to evaluate the bicycle users' behaviour corresponding to the decision to use a bicycle as a commuter mode and contributing factors in the decision to bicycle in developing countries. To achieve the proposed objectives, an offline face-to-face survey was conducted at a selected stretch in Nagpur city, India. To understand the user's behaviour and attitudes towards bicycling, a Structural Equation Model (SEM) was proposed. The study has revealed that important factors like environmental factors, a lack of existing infrastructure facilities, personal norms, and specific socio-demographic characteristics are responsible for influencing the users' decision to use a bicycle as a commuter mode. From the result, it is concluded that the absence of alternative (motorized) transport modes encourages users to cycle. The lack of cycle infrastructure, the distance, and the purpose of the trip significantly impact the decision to choose a bicycle as a commuter mode. Additionally, it also found that the hot climate and heavy rains demotivate commuters towards cycling. The findings of this study might be useful for transport planners to help them promote sustainable transport modes such as bicycles in the Indian context.

Examining commute mode choice of essential workers before and during the COVID-19 pandemic – A case study of the University of Washington

During disruptive events and major crises such as the COVID-19 pandemic, essential workers, defined in this study as employees who must continue to make frequent commute trips, play a critical role in maintaining the basic function of society. It is therefore vital for transportation planners and policymakers to ensure that adequate mobility services are provided to meet the travel needs of this group of workers. To better understand essential workers’ mobility barriers and inform future transportation policy, this research examines their pre- and during-pandemic commutes, as well as prospects on future commuting, using data from the Transportation Needs Assessment Survey conducted by the University of Washington in Seattle. The results show that, first, over 60% of pre-pandemic public transit riders switched to other modes, especially driving alone. In contrast, almost all the essential workers who drove alone, biked, or walked before the pandemic continued to do so during the pandemic. Second, the shift to driving alone was most pronounced among essential workers with high incomes, whereas public transit remained as a primary mode choice of lower-income groups. As travel distance increased, the probability of driving alone over public transit also went up, although the relationship was not linear. We did not find consistently significant associations between mode choice and other sociodemographic variables. Finally, our analysis indicated that most essential workers anticipated to return to their pre-pandemic commute frequency and mode choice when the pandemic is under control. Transportation planners and policymakers can facilitate mobility for essential workers through planning and policy innovations, especially during disruptive events and major crises.