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Despite decades of research, it is unclear under which circumstances travel is most onerous. While studies have found that some individuals derive positive utility from aspects of commuting, others have shown that traffic congestion can entail important time, monetary, and mental stress costs. Moreover, responses to traffic congestion-related stressors differs by individual characteristics. In response, this research captures how exposure to traffic congestion events, the duration of this exposure, and individual trait susceptibility to congestion affect the utility of commuting. Working through the lens of individual satisfaction with the duration of their commute, we show that not every minute of travel is valued the same by car commuters in Canadian cities. Results suggest a complex relationship between travel time, congestion, and individual predisposition to congestion-related stress. While improvements in travel time matter for increasing commute satisfaction, it is reductions in travel in congested conditions that matter most, particularly among those susceptible to congestion-related stressors.

Occupancy models were originally developed to better understand species distribution while accounting for imperfect detection. Because species distribution is not only shaped by habitat quality but also by the ability of individuals to reach suitable habitats, spatial dynamic occupancy models have been proposed to extend the original framework by defining that site colonisation was a function of the Euclidean distance to occupied sites. However, not all sites in the landscape are equally accessible due to the presence of barriers, that of corridors, etc. To account for connectivity between sites, the Euclidean distance has recently been replaced by a least-cost path distance, which explicitly accounts for landscape resistance, but assumes that individuals will follow the optimal route.To relax this assumption, we first developed a new spatial occupancy model that incorporates commute-time distance derived from circuit theory to model accessibility across sites. This distance has the advantage of modelling movement as a random walk and accounting for the fact that colonisation could be achieved from multiple paths. Our approach allows for the explicit estimation of landscape connectivity from detection/non-detection data and a direct measure of connectivity uncertainty.We implemented the model in the Bayesian framework using the nimble R package, which allows useful R connectivity functions to be called from within the model. Second, we carried out a simulation study to assess the performance of our model by considering four scenarios depicting an increasing level of landscape resistance. Third, to illustrate our new approach, we studied the recolonisation of two carnivores in France.We quantified the degree to which rivers facilitate Eurasian otter (Lutra lutra) colonisation and highways impede Eurasian lynx (Lynx lynx) colonisation. Overall, spatial occupancy models provide a flexible framework to accommodate any distance metric designed to align with species dispersal ecology.

Sleep debt is associated with presenteeism and mental health; however, the association of sleep debt with presenteeism and well-being in the context of work-related social factors (commuting time, workdays, and working hours) has not been fully elucidated. This study aimed to examine whether work-related social factors are associated with presenteeism and well-being via sleep debt. The participant group comprised 872 full-time and 526 part-time workers (mean age: 44.65 ± 12.37 and 48.47 ± 12.93 years, respectively). For both the full-time and part-time workers, increased sleep debt was significantly associated with presenteeism (β = −0.171; β = −0.160) and low well-being (β = −0.135; β = −0.153). Notably, commuting time was significantly associated with increased sleep debt in full-time workers (β = 0.09). In contrast, the number of workdays was significantly associated with increased sleep debt in part-time workers (β = −0.102). Working hours were not significantly associated with sleep debt for both full- and part-time workers. These results reveal that sleep debt might lead to various risks among workers, elucidating the work-related social factors related to sleep debt. They also highlight the importance of considering work-related social factors when addressing sleep debt.

The use of electric bikes (e-bikes) is attracting increasing attention from researchers and policymakers as a way to promote sustainable transportation. However, knowledge about the built environment factors that influence e-bike use is lacking. In China, most evidence on e-bikes and travel behavior stems from big cities; there is much less evidence concerning small cities and their adjacent rural areas. Using travel data collected in a small Chinese city (Ganyu), the present research explores the impact of the built environment around residential and work locations on individuals’ commute mode choice, with a particular focus on e-bike use. Consistent with the few previous studies on travel behavior in small Chinese cities, we find that most residents of Ganyu commute only short distances and that the e-bike is the primary mode for their daily commutes. The results of a nested logit model show that e-bike use is more popular among females and low-income groups, and that certain built environment characteristics at the work location promote e-bike use. Moreover, the built environment in different geographical contexts has different influences on commute mode choice. In particular, the presence of city/town roads without bike lanes at work locations promotes e-bike use among rural residents but much less so among urban residents.

In Kenya’s capital city, Nairobi, streets are regularly gridlocked. While it is clear that roads are congested at peak hours, it is not known which commuters are experiencing that congestion or what their commute times actually are. Even less is known about commuting patterns in other Kenyan cities. This paper contributes new evidence on commuting from a survey of 14,580 households, conducted in 15 Kenyan cities in 2013. Walking and matatus—privately-operated paratransit—account for 89% of all adult commuting in urban Kenya. As cities increase in size, the proportion relying on walking falls and matatu use increases. Within a city, commuters with higher income and education, and those living further from the city center, are more likely to use matatus rather than walk. Commute times are surprisingly short. In smaller Kenyan cities the median commute time is just 20 min. In Nairobi, the median commute time is 30 min, and only 5% of those surveyed reported commuting an hour or longer. These data paint a remarkably sustainable picture of urban travel patterns in Kenya. As incomes, education levels, and demand for motorized travel rise, the challenge will be to expand and improve the system while maintaining its sustainability.

Transportation planners, engineers, and researchers have long lamented the highly emotional public responses generated by changes to parking policies. We know that reducing the supply and increasing the price for parking—while intended to advance sustainability and other important community goals—seems to fuel an angry response, but this knowledge is often vague and anecdotal. This study combines qualitative coding of open-ended survey responses with quantitative analyses of sociodemographic and commute characteristics using descriptive statistics and binary logistic regression models to reveal a strong correlation between parking and anger among University of Wisconsin-Milwaukee (UWM) campus users. Higher probabilities of anger are also positively associated with annual household incomes below $50,000, bus pass holders, and residential locations outside of the immediate UWM neighborhood. Qualitative themes from angry comments include frustrations about parking price, supply, and duration; questions about the motivations for university parking policies; and a sense of entitlement among campus users to free and inexpensive parking options. The study interprets these variables and themes together to provide insights into the complicated relationship between parking and anger and the importance of analyzing angry feedback to inform future policies.

PurposeThis empirical research aims to provide organisations with useful information on how teleworking has affected employee commuting, allowing organisations to adapt working conditions to the new social context. This research sets out to provide evidence on the behaviour of teleworkers in terms of the mode of transport chosen when commuting to work physically.Design/methodology/approachThis research is based on a survey conducted in Madrid based on a theoretical approach grounded in the theory of planned behaviour (TPB) and discrete choice models. Exploratory factor analysis (EFA) and discriminant analysis have been used to determine the variables that influence the mode of transport chosen by teleworkers when commuting in person.FindingsThe results indicate the prevalence of private car use by teleworkers when working at the office, finding that attitudes and satisfaction with modes of transport significantly influence their choice. The characteristics and frequency of teleworking, however, are not significant, which indicates that teleworkers attach greater importance to their preferred mode of transport, regardless of the disadvantages.Originality/valueThis research provides empirical evidence using an inductive approach to understand the challenges that organisations are facing with regard to teleworking since commuting behaviour has changed for teleworkers. This requires organisations to give significant reconsideration to the issue of commuting as an important component of working time that could condition employee satisfaction and, therefore, the retention or recruitment of talent. Furthermore, residence and mobility changes afford organisations better access for recruitment, notwithstanding urban planning implications.

This work studies how the usage of shared mobility services could be influenced by latent factors. An integrated choice and latent variable model is adopted to explore the effects of three attitudinal and perceptual factors on bike- and car-sharing choices while simultaneously investigating the causes associated with each of the latent variables. A group of Chinese commuters’ stated preference mode choice data are collected. It is found that the probability to choose bike-sharing could be positively affected by “willingness to be a green traveler” and “satisfaction with cycling environment,” and car-sharing choice is positively correlated with “advocacy of car-sharing service.” By taking into account the interaction effects between the latent variables and travel time of the two services, a significant difference is discovered on the estimated value of travel time savings (VTTS) compared with other more restrictive model specifications. The finding highlights the importance to derive different VTTS for travelers with differentiated attitudes and perceptions as the tastes toward travel time spent could vary substantially. In other words, there would be different trade-off preferences across attitudinal groups, according to which transport service operators could customize their strategies on prices and levels of service offered.

Abstract In partial ♭-metric spaces, we first define F ρ ♭F_(ρ ♭)-weak contraction mappings and develop fixed point theorems in these mappings. In the context of ♭-metric and partial ♭-metric spaces, this study aims to establish the concept of proximally F ρ ♭F_(ρ ♭)-weakly dominated pair of mappings and derive common best proximity point theorems using this pair of mappings. The best proximity point and associated fixed point theorems in the literature are generalized by our new findings. Furthermore, we illustrate our findings with examples. Finally, as evidence for our conclusion, we demonstrate that an integral equation has a solution.