Walking Trips Research Articles

Understanding walking behaviour during COVID-19: binary logit and ANN approach

The coronavirus disease 2019 (COVID-19) pandemic had severe impacts on society. It negatively affected many sectors, and transportation is one of those. Naturally, the walking trip behaviour of individuals was also altered. This study aims to investigate the changes in walking trips of individuals by using two models: binary logit (BL) and artificial neural network (ANN). An online survey was conducted with 387 individuals. BL model investigated if respondents’ walking trips would increase during and after the pandemic. On the other hand, ANN models were developed to determine the significant factors in changes in walking behaviour. Results indicate that ANN models capture more factors than BL models. Demographics and attitudes toward public transportation, taxi, and walking trips during the pandemic are found to be effective in walking behaviour changes. Policies can be made to increase public transit ridership, and infrastructure for walking can be improved. Future research suggestions are given.

Association between land use features and changes in walking patterns from pre-pandemic to post-pandemic: A case study of city of Sydney (2013–2023)

While the impact of the pandemic on active mobility patterns is widely studied in several cities, the underlying characteristics that describe the heterogeneity in changes in active mobility are less understood. This is particularly important for post-pandemic active mobility planning. This study aims to investigate and describe the association between urban population and land-use features, as well as changes in the spatio-temporal patterns of walking from pre-pandemic to post-pandemic through a case study of the city of Sydney, Australia, using 11 years of pedestrian count data from 2013 to 2023. The findings indicate that during the pandemic, the average daily pedestrian traffic in Sydney decreased significantly compared to the pre-pandemic period. However, since experiencing the lowest pedestrian traffic in 2020, activities in the study area have shown signs of partial recovery, with a 51% increase observed in 2023. The observed changes in pedestrian activities are, however, spatially heterogeneous. Modeling results reveal that areas with greater commercial land use, more points of interest (POIs), higher population density, and higher network connectivity experienced a significant negative change in the number of walking trips from the pre-pandemic to the pandemic period. Areas with higher percentages of educational and residential use and with higher personal income experienced smaller changes in pedestrian activities during the pandemic compared to the pre-pandemic period. During the post-pandemic recovery, the influential features remain mostly unchanged; however, the association direction is the opposite.

Enabling gender responsive low-carbon transport in India using SDG5 framework

<p>Gender and mobility are strongly related and address challenges of safety and accessibility for women. Studies worldwide highlight the need to create more gender-responsive transport systems that maximize women’s mobility, civic participation, and safety. Gender inequality in urban transport is evident in Indian cities in terms of women’s longer walking trip lengths, longer time spent in commute and hence time poverty, impoverished health, and compromised personal safety. Even the public transport systems, often perceived as more gender-equal, overlook women’s needs and mobility concerns such as affordability and scheduling. This article presents transportation challenges faced by women (recorded through primary surveys and focus-group discussions) and further investigates how low-carbon urban transport, as perceived under the Paris Agreement and Sustainable Development Goals (SDGs), can be delivered with gender-equitable outcomes. For a more holistic perspective, the assessment is grounded in two Indian cities, Surat (4.5 million population), a fast-growing industrial metropolis, and Udaipur (0.5 million population), a small but important tourist destination in the nation.</p>

Unveiling environmental inequalities in high-density Asian city: City-scaled comparative analysis of green space coverage within 10-minute walk from private, public, and rural housing

While increasing studies acknowledge the potential of green spaces to alleviate urban environmental problems in high-density cities, there is growing attention to the socio-spatial inequalities in green space allocation. Few studies have assessed these inequalities by considering the green space coverage along citizens’ walking trips from their homes within the context of pedestrian-centric and mixed-residential developments in high-density cities. Therefore, this study (1) evaluated green space coverage near home and within residents’ 10-minute walk from each residential building in Hong Kong, (2) estimated the population living in green space-deprived environments, and (3) explored their relationships with socioeconomic and built-environment characteristics. Results revealed that private housing residents living in lower-income and higher-density areas in the urban core were the most prone to low green space coverage. In contrast, public housing consistently offered medium levels of green space coverages regardless of community income and urban form. Additionally, high-density new town development demonstrated the potential for equitable green space allocation across different housing types. As cities increasingly embrace high-density development and promote active transportation, this study provides valuable insights for implementing housing and greening initiatives that foster healthy living environments in high-density cities.

Assessment and Modelling of Walk Trips in Akure, Nigeria

The study examined and modeled the walking behavior patterns of residents in Akure, Nigeria. A multi-stage sampling approach was used to collect relevant data for assessing and modeling the walking trip patterns. The questionnaires were administered to 300 participants between May to November 2019 (6 months) across three primary residential neighborhoods in the city; high-density, medium-density, and low-density areas. The obtained data were analyzed using SPSS software and subsequently modeled using multi-variable regression techniques. The study found that 48.7% of the sampled population preferred to walk, and 49.7% perceived walking as an alternative to motorized trips. Significant differences were observed in the socioeconomic characteristics of residents, such as age and income, across the residential zones (F = 54.731, p<0.001; F = 68.278, p<0.001). The key factors that greatly influenced decision of respondents to walk included socioeconomic factors, such as income, personal car ownership, educational qualifications, and employment status, with age and sex being the least significant socioeconomic determinants. Generally, the factors that motivated respondents to choose walking as a travel mode included its relative affordability, the lack of personal vehicles, awareness of health benefits, safety and security concerns, avoidance of motorized traffic congestion, and favorable weather conditions. The findings of this study have important implications for transportation planning. The paper recommends the need to incorporate non-motorized spaces and walkways into various levels of urban planning and implementation to foster a more walkable environment and encourage active transportation in the city.

A sidewalk-level urban heat risk assessment framework using pedestrian mobility and urban microclimate modeling

Climate change and the associated increase in heat-related hazards pose a pressing threat to urban residents’ health and well-being. People, when walking in particular, are at risk of experiencing heat stress as they navigate urban environments. This study proposes a novel heat risk assessment framework combining pedestrian mobility modeling with urban microclimate modeling. Using this framework, we assessed pedestrian heat-related exposure and risk in urban areas by integrating the Universal Thermal Climate Index (UTCI) as the hazard and pedestrian trips to critical destinations as exposure. We considered temporal variation, in both hazard and exposure, by examining different time periods during the day—morning peak, midday, and evening peak. In addition to hazard and exposure, we also considered vulnerability by focusing on young children and older adults. We contribute to improving the spatial resolution of heat risk assessment by analyzing the hazard for pedestrian trips between home locations and five critical destinations—bus stops, rail stations, parks, schools, and commercial amenities—at the address-point level and using a pedestrian network comprising sidewalks and crosswalks. Our framework helps identify sidewalks with high heat exposure levels as well as home locations with high cumulative heat risk, accounting for walking trips to critical destinations along feasible routes. We demonstrated the effectiveness of this framework by applying it to a 36-square-kilometer area of central Los Angeles, CA. Our findings offer valuable information to urban planners and policy-makers, supporting evidence-based prioritization of intervention sites, climate adaptation strategies, and policy decisions essential for climate-proof planning. By implementing targeted interventions in areas where heat hazard is expected to affect the most vulnerable pedestrians, planners can create heat-resilient, pedestrian-friendly environments while prioritizing the health and well-being of vulnerable groups. This study contributes to the growing knowledge of robust risk assessment methodologies for climate-proof planning, specifically with regard to addressing outdoor heat-related risks during extreme heat events.

An Analysis of the Health Effects of Physical Activity due to Active Travel Policies in Rennes, France.

Rennes, a midsize city in France, features many opportunities for active travel. City officials seek to increase walking and cycling by 2030 to improve public health. Physical inactivity, a leading risk factor for premature mortality around the globe, has been shown to be associated with many chronic diseases including heart disease, type 2 diabetes, and cancer. Using the 2018 household travel survey of Rennes residents, we apply the Health-Oriented Transportation statistical model to assess health impacts associated with population-level rates of walking and cycling. We consider two proposed mobility and climate objectives which outline sustainable transportation goals by 2030. These include a shift in transportation mode share to increase walking and cycling trips, as well as a broad reduction in vehicle miles traveled (VMT) across the metropolitan area. Our regression analysis demonstrated that factors of household car access and inner-city residency were predictors of prevalence (observed one-day proportion engaging in walking or cycling), participation (weekly proportion), and intensity (mean individual physical activity achieved through walking/cycling) of active travel. Age and education were additionally associated with prevalence. The 2030 mobility objective (mode share: 9% cycle, 35% walk) was associated with a reduction of 1,051 DALYs (disability-adjusted life-years), translating to $73 million USD ($23-$177) in averted costs. The climate objective (10% reduction in VMT) was associated with a reduction of 369 DALYs when replaced entirely by walking and 714 DALYs with cycling, translating to $26 million ($8-$62) and $50 million ($15-$121) saved, respectively. Rennes residents experience high participation in active travel, particularly those in the inner city. If residents achieve the city's active travel goals for 2030, there is potential for a large reduction in health burden and subsequent costs. Reaching these goals may require significant investment in transportation programming and infrastructure to improve active travel opportunities.

Socioeconomic variations in walking rates in the United States: Recent evidence from the 2022 National Household Travel Survey

IntroductionWe use the 2022 National Household Travel Survey for the USA—the first since the peaking of the COVID-19 pandemic—to examine variations in walking rates related to differences in socioeconomic characteristics. Our analysis provides the most recent national estimates of socioeconomic variation in walking, by far the most important form of daily physical activity in the USA. MethodsWe used graphical bivariate analysis and multiple regressions to explore the relationship between each of the socioeconomic variables and the following daily walk rates: the number of walk trips, time walked, and distance walked. We also analyzed three binary variables indicating whether a person made at least one walk trip during the travel day, achieved the equivalent of 150 min of walking per week, and walked on five or more days during the previous 30 days. ResultsHigher education levels, not owning a car, not having a driver's license, not working, working from home, and high density are strongly related to higher levels of walking. We found no significant differences or mixed results for gender, age, race, and income. Because the 2022 NHTS incorporated significant changes in methodology, sample size, survey questions, and variable definitions, its estimated trip rates cannot be compared directly to the 2017 NHTS—the last survey prior to COVID. Moreover, the 2022 NHTS greatly underestimated walk trips because—unlike previous NHTS surveys—it omitted the trip diary as well as multiple prompts to remember short trips, especially walk trips. ConclusionsThe relationships we estimated between various walk rates and the nine socioeconomic variables for 2022 were generally consistent with the results of previous studies, including those examining the 2001, 2009, and 2017 NHTS. That suggests that these relationships have remained stable over time—even if absolute rates of walking have changed, as indicated by other studies.

A framework to include socio-demographic characteristics in potential job accessibility levels in low-car and car-free development areas in the Netherlands

Car-free development has become popular in recent years due to concerns regarding transport-related health issues in urban areas as well as a growing trend toward sustainability and environmentally friendly living. Although car-free development is regarded as progress to promote active transport modes and healthier cities, the accessibility impacts for its residents remain unclear. To address this knowledge gap, this paper proposes a job accessibility assessment framework that integrates individual and household socio-demographic characteristics into a job accessibility assessment, making it possible to account for commuting preferences of different population groups in accessibility analyses. For this purpose, a stated choice survey was conducted in existing low-car areas in the Netherlands to determine transport use and perception of public transport trip characteristics. Then, the influence of socio-demographic characteristics on trip perceptions was analyzed using a Latent Class Logit (LCL) regression model and Monte Carlo simulations. Finally, a multi-modal transport network combining walking and public transport trips was used to assess potential job accessibility levels of different population groups in a car-free development area. The proposed framework was implemented in a case study in the province of Utrecht (the Netherlands). Results show notable differences between the job accessibility levels within different population groups, reflecting distinct perceptions toward commuting trip characteristics based on socio-demographic characteristics and demonstrating the suitability of the applied approach to assess accessibility levels in car-free development areas. Compared to the sample average distribution, more than 15% lower accessibility levels were observed for starters (age 18-35) in some urban areas, indicating the aversion to longer and more expensive commuting trips. Contrarily, increased accessibility levels for families (>2 persons in household) were observed, demonstrating the acceptance to experience longer commuting travel times and additional costs. No differences were observed between accessibility levels of the sample average and senior adults (age >50).

Exploring pedestrian thermal risk exposure and its determinants among various types of walking trips: A gendered examination from a GPS-based study in Nanjing

Previous research has found that components of the natural and built environment play an important role in regulating ambient temperature. However, existing research regarding the association between these environmental characteristics and thermal exposure has focused mainly at the macro level, leaving this relationship at the individual level underexplored. It remains unknown how the environment functions differently in determining thermal exposure among various types of trips and how this mechanism differs by gender. Using GPS walking trajectory data collected in Nanjing, China, this study examines the extent to which male and female pedestrians experience different levels of thermal exposure, and how the thermal exposure determinants work differently between utilitarian and recreational trips. Descriptive analysis shows that men experience higher per-minute thermal exposure than women, and both male and female pedestrians face higher thermal exposure per minute during utilitarian walks compared to recreational walks. Generalized linear mixed model results indicate that green spaces significantly reduce thermal exposure for both male and female pedestrians during utilitarian walking trips, but this effect only works among women regarding recreational walking. We also identified a negative relationship between water bodies and thermal exposure during recreational walks, but this correlation only occurs among women. Our study suggests that the natural environment’s mitigating effect on thermal exposure differs by gender among different types of walking trips. Policymakers should consider these disparities to avoid exacerbating gender inequality in the arena of thermal exposure and health.

Uncovering physical activity trade-offs in transportation policy: A spatial agent-based model of Bogotá, Colombia

BackgroundTransportation policies can impact health outcomes while simultaneously promoting social equity and environmental sustainability. We developed an agent-based model (ABM) to simulate the impacts of fare subsidies and congestion taxes on commuter decision-making and travel patterns. We report effects on mode share, travel time and transport-related physical activity (PA), including the variability of effects by socioeconomic strata (SES), and the trade-offs that may need to be considered in the implementation of these policies in a context with high levels of necessity-based physical activity.MethodsThe ABM design was informed by local stakeholder engagement. The demographic and spatial characteristics of the in-silico city, and its residents, were informed by local surveys and empirical studies. We used ridership and travel time data from the 2019 Bogotá Household Travel Survey to calibrate and validate the model by SES. We then explored the impacts of fare subsidy and congestion tax policy scenarios.ResultsOur model reproduced commuting patterns observed in Bogotá, including substantial necessity-based walking for transportation. At the city-level, congestion taxes fractionally reduced car use, including among mid-to-high SES groups but not among low SES commuters. Neither travel times nor physical activity levels were impacted at the city level or by SES. Comparatively, fare subsidies promoted city-level public transportation (PT) ridership, particularly under a ‘free-fare’ scenario, largely through reductions in walking trips. ‘Free fare’ policies also led to a large reduction in very long walking times and an overall reduction in the commuting-based attainment of physical activity guidelines. Differential effects were observed by SES, with free fares promoting PT ridership primarily among low-and-middle SES groups. These shifts to PT reduced median walking times among all SES groups, particularly low-SES groups. Moreover, the proportion of low-to-mid SES commuters meeting weekly physical activity recommendations decreased under the 'freefare' policy, with no change observed among high-SES groups.ConclusionsTransport policies can differentially impact SES-level disparities in necessity-based walking and travel times. Understanding these impacts is critical in shaping transportation policies that balance the dual aims of reducing SES-level disparities in travel time (and time poverty) and the promotion of choice-based physical activity.

Is a 15-Minute City Within Reach? Measuring Multimodal Accessibility and Carbon Footprint in 12 Major American Cities

Enhanced efforts in the transportation sector should be implemented to mitigate the adverse effects of CO2 emissions resulting from zoning-based planning paradigms. The concept of a 15-minute city, emphasizing proximity-based planning, holds promise in reducing unnecessary travel and progressing towards carbon neutrality. However, a critical research question remains inadequately explored: to what extent is the 15-minute city concept feasible for American cities? This paper presents a comprehensive framework to evaluate the 15-minute city concept using SafeGraph Point of Interest (POI) check-in data across 12 major American cities. Our findings suggest a prevailing reliance on cars among residents due to the spatial distribution of essential activities beyond convenient walking, cycling, and public transit distances. Nevertheless, there exists significant promise for realizing the 15-minute city vision, given that most residents' daily activities can be accommodated within a 15-minute radius by low-emission modes transportation modes. When comparing cities, it appears that achieving a 15-minute walking city is more feasible for metropolises like New York City, San Francisco, Boston, and Chicago, while proving to be challenging for cities such as Atlanta, Dallas, Houston, and Phoenix. In examing inter-group comparisons, neighborhoods with higher proportion of White residents and higher median incomes tend to have more accessible POIs, with a substantial percentage of activities concentrated within a 15-minute radius. This demographic also shows a greater propensity to fulfill daily activities through walking, cycling, or public transit trips within a 15-minute travel time, thus presenting a greater potential in CO2 reduction compared to African Americans. This study can offer policymakers insight into how far American cities are away from the 15-minute city concept. It also highlights the potential CO2 emissions reductions that could be achieved through successful implementation.

The Impact of Urban Design on Utilitarian and Leisure Walking—The Relative Influence of Street Network Connectivity and Streetscape Features

Road network connectivity determines the accessibility of urban activities for pedestrians, while streetscape characteristics have an impact on route attractiveness. Methods used to measure the influence of connectivity and streetscape characteristics on walking behavior differ substantially, while trip purpose is a key factor. This paper explores the respective contributions of network connectivity and streetscape features to explain leisure walking and utilitarian trips on 740 street segments in Santarém (Portugal). The indicators cover the most commonly used factors in walkability indexes, such as density, diversity, design, and accessibility. The streetscape features measure imageability, enclosure, human scale, transparency, and complexity. The walking trip information was collected via survey. The results show that connectivity measures have a greater overall explanatory power for both trip motives. However, the findings highlight the need to consider a variety of design indicators to explain walking behavior due to the higher explanation power of the model with two types of indicators.

An Analysis of the Health Effects of Physical Activity due to Active Travel Policies in Rennes, France

Background Rennes, a midsize city in France, features many opportunities for active travel. City officials seek to increase walking and cycling by 2030 to improve public health. Physical inactivity, a leading risk factor for premature mortality around the globe, has been shown to be associated with many chronic diseases including heart disease, type 2 diabetes, and cancer. Methods Using the 2018 household travel survey of Rennes residents, we apply the Health-Oriented Transportation statistical model to assess health impacts associated with population-level rates of walking and cycling. We consider two proposed mobility and climate objectives which outline sustainable transportation goals by 2030. These include a shift in transportation mode share to increase walking and cycling trips, as well as a broad reduction in vehicle miles traveled (VMT) across the metropolitan area. Results Our regression analysis demonstrated that factors of household car access and inner-city residency were predictors of prevalence (observed one-day proportion engaging in walking or cycling), participation (weekly proportion), and intensity (mean individual physical activity achieved through walking/cycling) of active travel. Age and education were additionally associated with prevalence. The 2030 mobility objective (mode share: 9% cycle, 35% walk) was associated with a reduction of 1,051 DALYs (disability-adjusted life-years), translating to $73 million USD ($23-$177) in averted costs. The climate objective (10% reduction in VMT) was associated with a reduction of 369 DALYs when replaced entirely by walking and 714 DALYs with cycling, translating to $26 million ($8-$62) and $50 million ($15-$121) saved, respectively. Conclusions Rennes residents experience high participation in active travel, particularly those in the inner city. If residents achieve the city’s active travel goals for 2030, there is potential for a large reduction in health burden and subsequent costs. Reaching these goals may require significant investment in transportation programming and infrastructure to improve active travel opportunities.

Using mobile phone big data and street view images to explore the mismatch between walkability and walking behavior

Stimulating more citizens to walk plays an essential role in building a healthy city. This paper explores the mismatch between walkability and walking behavior, using mobile phone data, street view images, and various sources of open data. Using Shenzhen as our case study, we identified walking trips of 6 months in 2021 from cellular mobile data, taking the rule-based heuristics approach. We collected ground truth GPS data to validate the walking trip extraction method. Open data and deep learning enabled quantifying walkability from the perspective of four pedestrian needs: safety, convenience, continuity, and attractiveness. We employed geospatial techniques to identify the mismatch areas between walkability and walking behavior in the city. We also explored the spatially varying effects of walkability on walking behavior. Our results showed that the mismatch areas with high-level walking trips but low-level walkability mainly occurred in the fringe areas of the central business district (CBD) and subcenters that require prioritizing more interventions. Moreover, walkability showed strong effects on walking trips in the inner suburbs. For the four aspects of our walkability framework, safety and convenience had greater positive effects on walking trips in suburbs than in urban areas. Continuity promotes walking trips mainly in the city’s western sector. The positive effect of attractiveness on walking trips clustered in the central and western parts of the city. Based on the findings, we provide prioritized and contextualized built-environment intervention strategies and policy recommendations for urban designers and transportation planners.

Which factors influence the use of shared and privately-owned e-scooters in the city of Madrid? Implications for urban mobility

Micromobility using fully-electric two-wheeled vehicles is increasing in cities worldwide. E-scooters, whether shared or privately-owned, provide short door-to-door trips by facilitating the first/last mile stage of the journey. They are expected to improve livability in cities by reducing harmful emissions and space occupation. In this respect, understanding travel behavior and usage patterns is essential to regulate them appropriately. The purpose of this study is to determine individuals' sociodemographic variables, mobility-related attributes, and latent constructs influencing e-scooter usage. To that end, an individual-level model is estimated to explain the adoption and frequency of use of both shared and private e-scooters based on survey data. The research takes the city of Madrid as a case study, and contributes to a deeper understanding of the differences in the use of privately-owned and shared e-scooters, with a particular focus on the influence of mobility habits and attitudinal variables. The study is complemented with some insights on shared e-scooter usage at the trip-level, which shows the substitution caused on walking trips, and their limited ability to promote modal shifts from the private car. Finally, the research provides valuable implications for urban dynamics and feedback for policymakers and transport planners.

Smartphone Google Location History: A Novel Approach to Outdoor Physical Activity Research.

Outdoor physical activity (PA) is an important component of overall health; however, it is difficult to measure. Passively collected smartphone location data like Google Location History (GLH) present an opportunity to address this issue. To evaluate the use of GLH data for measuring outdoor PA. We collected GLH data for 357 individuals from the Washington State Twin Registry. We first summarized GLH measurements relevant to outdoor PA. Next, we compared accelerometer measurements to GLH classified PA for a subset of 25 participants who completed 2 weeks of global positioning system and accelerometer monitoring. Finally, we examined the association between GLH measured walking and obesity. Participants provided a mean (SD) average 52 (18.8)months of GLH time-activity data, which included a mean (SD) average of 2421 (1632) trips per participant. GLH measurements were classified as the following: 79,994 unique walking trips (11.6% of all trips), 564,558 (81.8%) trips in a passenger vehicle, 11,974 cycling trips (1.7%), and 890 running trips (0.1%). Sixty-two percent of these trips had location accuracy >80%. In the accelerometry evaluation, GLH walking trips had a corresponding mean vector magnitude of 3150 counts per minute, compared with 489 counts per minute for vehicle trips. In adjusted cross-sectional analyses, we observed an inverse association between both walking minutes and trips per month and the odds of being obese (odds ratio = 0.78; 95% CI, 0.60-0.96, and odds ratio = 0.91; 95% CI, 0.82-0.98, respectively). GLH data provide a novel method for measuring long-term, retrospective outdoor PA that can provide new opportunities for PA research.

ГАСТРОНОМІЧНА СПАДЩИНА ЯК МЕХАНІЗМ ЗБЕРЕЖЕННЯ НАЦІОНАЛЬНОЇ ІДЕНТИЧНОСТІ УКРАЇНЦІВ

The article examines the concepts of "identity" "national identity", "European identity", gastronomic heritage. In the conditions of transformation of global economic relations international trade in services offers research and implementation of tourist services to meet the demand of various categories of consumers. Gastronomic tourism is one of the options for recreation in modern conditions. The catalog of the gastronomic heritage of the cultural and pilgrimage route "Camino Podolico" of the cultural and educational route from Vinnytsia to Kamianets-Podilskyi similar to the Ways of St. James leading to the city of Santiago de Compostela. The route connects 13 points of Vinnytsia and Khmelnytskyi regions. It allows you to plan a walking or cycling trip with the necessary infrastructure for food and overnight stays every 20–25 kilometers. The uniqueness of the Camino Podolico lies in the fact that it passes through the most picturesque places of eastern Podillia. In the first part of it travelers have the opportunity to walk along the picturesque banks of the Southern Bug and Riv rivers. The route popularizes communities in Vinnytsia and Khmelnytskyi regions as a tourist attraction among domestic and foreign tourists and creates the necessary conditions for the development of local businesses. Moreover an electronic track of the route which is constantly being improved. Everyone who completes the route on foot or by bicycle will receive a passport for markings at the beginning of the route and a certificate of completion. "Camino Podolico" is implemented by territorial communities of Vinnytsia and Khmelnytskyi regions and DART. The catalog is a bilingual edition containing 22 recipes of unique dishes collected in 11 communities of Vinnytsia and Khmelnytskyi. Kamianets-Podilskyi is the final point on the Camino Podolico where we explored the intangible cultural heritage of communities. It is also planned to study and prospects of the development of tourism during the war and the mechanisms of the post-war recovery of the industry which were determined at the 1st National Tourism Summit.

Sociodemographic matters: Analyzing interactions of individuals' characteristics with walkability when modelling walking behavior

The concept of walkability encompasses a multitude of features of the built and social environments that impact walking behavior, leading to the creation of a wide range of walkability indices. While past studies have compared the research outputs from multiple walkability indices, little research has looked at how relevant each index is across sociodemographic groups and how the relationship between sociodemographic characteristics and behavior vary from one index to another. Using trip data from Montréal, Canada, this paper evaluates two commonly used walkability indices at different scales – Walk Score© (meso-scale) and the MAPS-Mini audit tool (micro-scale) – and their interactions with sociodemographic characteristics. Weighted binary logistic regressions are used to model the probability of adults taking a homebased utilitarian walking trip. A total of ten models are generated, including eight models in which one of four socio-demographic variables – gender, age, household income, and presence of children below 13 years old in the household – is interacted with one of the two walkability indices. Sensitivity analyses are then conducted using the interaction variables' outputs by varying the values of the interacted sociodemographic variable. Results show significant interactions for all variables for both indices except from Walk Score©’s interaction with gender. Opposite effects are observed between the two indices in the sensitivity analysis for household income. The differential results observed between the indices and between sociodemographic groups underscore the need to properly test the equity implication of using certain walkability measures in research.

Calibrating walkability indicators for commute walk trips: A structural equation modeling approach

Walking plays a significant role in promoting public health, decreasing air pollution, and vitalizing cities. Walkability is an important notion that transportation planners and policymakers often use to quantify the suitability of and to promote travelers’ propensity for walking in an urban area. This paper adopts a data-driven approach using structural equation modeling for simultaneous estimation of 1) a latent construct of walkability using different walkability indicators (thus estimation of weights of the indicators), and 2) the effect of walkability on commute walking behavior for an urban area. Doing so accounts for the effects of various indicators of walkability as well as socio-economic and security characteristics. A Partial Least Square Structural Equation Model is developed to estimate both direct and indirect effects of walkability on the share of commute walk trips in total commute trips for the city of Chicago using census tract-level data. We find that walkability is the most important factor affecting the share of commute walk trips. Among the indicators of walkability, transit- and job density-related indicators are the most important ones. Some socio-economic factors, especially travel time, vehicle ownership, and college student share, also critically influence the propensity for walking to commute. We further find that our calibrated walkability score results in a different hotspot distribution in Chicago than using the uncalibrated walkability score, as is currently practiced by the Chicago Metropolitan Agency for Planning, but is more consistent with hotspot distribution of the actual commute walk trips in the city. These findings advance the understanding and characterization of walkability and actual walking behavior in urban areas, which in turn helps inform pedestrian infrastructure investment and policy making.