Evaluating COVID-19’s impacts on Puerto Rican’s travel behaviors

The COVID-19 pandemic has completely disrupted and possibly permanently changed the way humans travel.In Puerto Rico,major travel restrictions to the island have persisted at different levels since March 2020,which heavily influenced residents’travel behaviors.However,it remains unclear about how big the impact is and how inequitable it might be.The goal of this study is to evaluate COVID-19’s impacts on Puerto Rican’s travel behaviors by analyzing travel flows from Puerto Rico to the contiguous US with a modified gravity model.The roles of socioeconomic factors regarding the Puerto Rican travelers and COVID-19 factors regarding the destination US states have been assessed.COVID-19 was a strong deterring factor of travel at the beginning of the pandemic and also in the winter of 2020,but it did not keep Puerto Ricans from traveling during the summer 2020 when most travel restrictions were lifted.We found that the elderly population of Puerto Rico,despite being more vulnerable to COVID-19,were much more likely to travel during the pandemic.We also found that,during the holiday season in 2020,some socioeconomically disadvantaged populations were more likely to be traveling,a direct contradiction to their travel flows the year prior.These findings shed light on about how disproportionately affected populations behavior changed from pre-pandemic to after the pandemic started.With the continuance of the pandemic,this information is extremely valuable for future planning with respect to emergency management,travel regulation,and social benefit.

A RESEARCH ON URBAN RECREATIONISTS' TRAVELING BEHAVIORS IN SHANGHAI

Urban recreationists consist of those who have used urban recreational facilities, no matter they are local residents or nonlocals. Traveling models will exert impacts not only on the use of urban recreational facilities but also on the development and management of recreational resources. Taking Shanghai as a sample of destinaton and origin of urban recreationists, the author did his study based on data from comprehensive travel measurement and users' survey, including field questionnaire survey, mailing questionnaire survey, home survey, and cordon monitonng. To analyze traveing models of urban recreationists in Shanghai, the author used techniques of Recreational Activity Space (RAS) and the Use Curve (UC) Analysis. Rogarding Shanghai as an origin, the author first discussed types and characteristics of the RASs which are presented by isotourist lines in the proper and outskirts of Shanghai, the Yangtze Delta and the China's Mainland respectively. These RASs reflect the trave directional bias of Shanghainese. Then the author regarded Shanghai as a deshnahon and analyzed the RASs of tounsts from Otier provinces, which demonstrated the attractiveness of and distance decay of Shanghai. He found that a U-shaped UC model existed in the distance decay under the influence of attractiveness and distance. Finally, the author suggested, that the availability, periodicity and attractiveness, besides distance, are the basic mechanisms that affect the urban recreationists' traveling models in a city such as Shanghai.

Travel Patterns and Street Networks: A Novel Visualization Methodology of City-Level Traffic Flows and Network Usability

Street Networks, knitted in the urban fabric, facilitate spatial movement and control the flow of urbanization. The interrelation between a city’s spatial network and how the residents travel over it has always been of high interest to scholars. Over the years, multifaceted visualization methods have emerged to better express this travel trend from small to large scale. This study proposes a novel approach to 1) visualize city-wide travel patterns with respect to the street network orientation and 2) analyze the discrepancies between travel patterns and streets to evaluate network usability. The visualizations adopt histograms and rose diagrams to provide several insights into network-wide traffic flows. The visualization of four New York City (NYC) boroughs including Queens, Brooklyn, Bronx, and Staten Island was generated for the daily traffic and the average hourly flows in the morning and evening rush hours. Then the contrasts between built-in street network topology and travel orientation were drawn to show where people travel over the network, travel demand, and finally which segments experience high or light traffic, revealing the true picture of network usability. The findings of the study provide an insight into the novel and innovative approach that can help better understand the travel behavior lucidly and assist policymakers in decision making to maintain a balance between urban topology and travel demands. In addition, the study demonstrates how to further investigate city street networks and urbanization from different diverse dimensions.

Riding towards a sustainable future:an evaluation of bike sharing’s environmental benefits in Xiamen Island,China

In the pursuit of sustainable urbanization,Bike-Sharing Services(BSS)emerge as a pivotal instrument for promoting green,low-carbon transit.While BSS is often commended for its environmental benefits,we offer a more nuanced analysis that elucidates previously neglected aspects.Through the Dominant Travel Distance Model(DTDM),we evaluate the potential of BSS to replace other transportation modes for specific journey based on travel distance.Utilizing multiscale geographically weighted regression(MGWR),we illuminate the relationship between BSS’s environmental benefits and built-environment attributes.The life cycle analysis(LCA)quantifies greenhouse gas(GHG)emissions from production to operation,providing a deeper understanding of BSS’s environmental benefits.Notably,our study focuses on Xiamen Island,a Chinese“Type Ⅱ large-sized city”(1–3 million population),contrasting with the predominantly studied“super large-sized cities”(over 10 million population).Our findings highlight:(1)A single BSS trip in Xiamen Island reduces GHG emissions by an average of 19.97 g CO_(2)-eq,accumulating monthly savings of 144.477 t CO_(2)-eq.(2)Areas in the southwest,northeast,and southeast of Xiamen Island,characterized by high population densities,register significant BSS environmental benefits.(3)At a global level,the stepwise regression model identifies five key built environment factors influencing BSS’s GHG mitigation.(4)Regionally,MGWR enhances model precision,indicating that these five factors function at diverse spatial scales,affecting BSS’s environmental benefits variably.

Transportation mobility during COVID-19:a systematic review and bibliometric analysis

The COVID-19 pandemic has significantly affected global transportation mobility,presenting unprecedented challenges to transportation management.Public transit and ride-hailing services saw a drastic reduction in ridership,leading to an increased inclination towards private vehicles.The pandemic also altered travel patterns and individual mobility due to various COVID-19 protocols.This study conducted a comprehensive review of 96 academic papers spanning from January 1,2020,to December 31,2022,focusing on transportation and mobility using the Scopus database.Three major themes were identified:‘Impact on Ride-Hailing Services',‘Impact on Mode Preference',and‘Impact on Trip Purpose',with subdivisions based on keywords and key findings extracted using VOSviewer.The pandemic significantly impacted ride-hailing services,altering demand,usage,and safety measures.Mode preference shifted towards private vehicles due to safety concerns.The present study underscores the long-term implications of the pandemic,emphasizing recovery strategies for ride-hailing services and mode preferences post-pandemic.It highlights the need for sustainable transportation policies,advocating for enhanced public transportation systems,promoting active travel modes,and addressing socioeconomic disparities in mobility patterns.The findings emphasize the need for resilient transportation strategies in the face of future disruptions.

Alpha-reliable combined mean traffic equilibrium model with stochastic travel times

Based on the reliability budget and percentile travel time(PTT) concept, a new travel time index named combined mean travel time(CMTT) under stochastic traffic network was proposed. CMTT here was defined as the convex combination of the conditional expectations of PTT-below and PTT-excess travel times. The former was designed as a risk-optimistic travel time index, and the latter was a risk-pessimistic one. Hence, CMTT was able to describe various routing risk-attitudes. The central idea of CMTT was comprehensively illustrated and the difference among the existing travel time indices was analyzed. The Wardropian combined mean traffic equilibrium(CMTE) model was formulated as a variational inequality and solved via an alternating direction algorithm nesting extra-gradient projection process. Some mathematical properties of CMTT and CMTE model were rigorously proved. Finally, a numerical example was performed to characterize the CMTE network. It is founded that that risk-pessimism is of more benefit to a modest(or low) congestion and risk network, however, it changes to be risk-optimism for a high congestion and risk network.

Travelers'attitudes toward carpooling in Lahore:motives and constraints

Traffic congestion has become a critical issue in developing countries,as it tends to increase social costs in terms of travel cost and time,energy consumption and environmental degradation.With limited resources,reducing travel demand by influencing individuals’ travel behavior can be a better long-term solution.To achieve this objective,alternate travel options need to be provided so that people can commute comfortably and economically.This study aims to identify key motives and constraints in the consideration of carpooling policy with the help of stated preference questionnaire survey that was conducted in Lahore City.The designed questionnaire includes respondents’ socioeconomic demographics,and intentions and stated preferences on carpooling policy.Factor analysis was conducted on travelers’ responses,and a structural model was developed for carpooling.Survey and modeling results reveal that social,environmental and economic benefits,disincentives on car use,preferential parking treatment for carpooling,and comfort and convenience attributes are significant determinants in promoting carpooling.However,people with strong belief in personal privacy,security,freedom in traveling and carpooling service constraints would have less potential to use thecarpooling service.In addition,pro-auto and pro-carpooling attitudes,marital status,profession and travel purpose for carpooling are also underlying factors.The findings implicate that to promote carpooling policy it is required to consider appropriate incentives on this service and disincentives on use of private vehicle along with modification of people’s attitudes and intentions.

Dry cupping therapy and the wellness management of health travelers

Objective:Individuals travel locally and internationally in order to find alternative treatments which are less-toxic and more beneficial to their health and wellness.Despite the popularity of the western system of medicine,cupping therapies are gaining enormous attention in Pakistan as a system of traditional and complementary medicine to ensure the quality of life and wellness notions of the people.The present study aims to examine the effectiveness of dry cupping therapy(DCT)on the health,wellness,and quality of life preferences of health-seeking travelers in a sample of Faisalabad.Methods:DCT was performed for 15-20 minutes on subjects by using 3-5 disposable cupping glasses.Study participants filled the questionnaires before and after DCT interventions.Partial least square structural equation modeling technique is used in order to statistically analyze the data.Results:A total of 187 subjects participated in two DCT interventions at Coural Wellness Center Faisalabad and provided their final responses after 30 days from 2nd DCT.Respondents’perceptions of their physical feelings were generally found in a significantly positive and direct relation with DCT and health status(HS),i.e.,body pain(β=0.019),vitality(β=0.138),and bodily movement(β=0.207).This trend was observed in the psychological feelings of respondents as well,i.e.,emotional feelings(β=0.169).DCT significantly mediated the overall phenomenon and variance account for values were found between 20%and 80%for all the study constructs.The scores of all the health and wellness items on the questionnaire were significantly improved in 79.68%of studied participants after 1st and 2nd DCT interventions except for social functioning.Conclusion:Findings of the present study suggest that DCT has an important role in determining the health perceptions and HS of health travelers without potential side-effects.It can improve the health and overall quality of life of the people by positively influencing their physical and psychological health perceptions.It additionally leads to improve travelers’emotion,behavior,and other daily matters.

Travel Decision Model of Heterogeneous Commuters under Uncertain Environment

In order to better describe the commuter's travel decision-making behavior under different travel environment,heterogeneous commuters and types are defined,and the commuters are divided into three types,including conservative type,neutral type and adventure type,respectively,analysis on the travel environment supply and the travel environment demand.Suppose the travel demand obeys the gamma distribution and the capacity obeys the beta distribution,and the travel time function of different commuter type is deduced,the travel decision model based on the cumulative foreground theory is established.Analyze the example results,compared with the fluctuation of travel demand,the degradation of traffic capacity has a more significant impact on travel decision-making behavior;and different types of commuters cause different disturbances to travel decision-making behavior.

Research on Behavior on Travel Mode, Going to Metro Station at Ho Chi Minh City

This research presents an analysis of travel mode choice for trips to Ho Chi Minh City metro station. Research methods were inherited through a formula to calculate passenger traffic forecasts to predict passengers, going to the station. Based on the collected data of interviews, traffic surveys, and ＂Irwin ＆ Von Cube＂ function, forecast the proportion of travel mode, and use to go to the station and leaving from the station. The results of study are used for the purpose of calculating the size of the metro station parking lots and parking layout plan.

Consumers' Travel Behavior to Shopping Centers

Based on the questionnaire data,this study analyzes the characteristics of Wuhu citizens' travel behavior in shopping centers.The following conclusions are drawn:(1)the frequency of trips to shopping centers has a great correlation with consumersJ economic level and social status;(2)the time spent to purchase goods is positively correlated with the level of goods;(3)multipurpose shopping becomes the mainstream;(4)traffic becomes the primary factor for consumers to consider;(5)the availability of supermarkets and cinemas at shopping centers affect consumers'choice of shopping centers.

Evidence-based practices in sustainable travel behavior intervention: A knowledge graph-based systematic review

Sustainable travel behavior intervention is an essential strategy to promote the development of urban transportation.The interventions offer personalized strategies based on certain scenario and participants to promote its effectiveness over hard travel restrictions.However,personalized strategies may also bring about difficulties to identify the actual effect of the measures.Furthermore,based on current practice,to make full use of travel behavior interventions,it is necessary to construct a unified methodological evidencebased framework to assess the reliability and effectiveness of travel behavior intervention studies.In response to these issues,we applied evidence-based knowledge graph to the field of sustainable travel behavior interventions to help decision supporters design sustainable travel behavior interventions wisely and in turn avoid excessive use of hard travel restrictions.We introduced concept of evidence-based practice to conduct a systematic analysis concerning reliability and validity of current full volume empirical studies by dimensions of scenarios,types of interventions and targets.In addition,we took advantage of high extensivity and integrability of knowledge graph to organize evidence-based related elements.Result of the systematic analysis shows that in terms of reliability of evidence,school intervention is the best scenario,knowledge incentive is the best intervention type and promoting public transit and walking proportion are the best targets.Oppositely,the reliability of interventions in workplace,belonging to reward and threat along with aiming at changing travel patterns generally and lowering travel carbon emission need to be enhanced.From the study,various research prospects are raised to promote evidence quality in the field of travel behavior intervention implementation.As a pioneer study,our research contributes to the field of urban transportation in introducing concepts of evidence-based practice and enabling optimization and extension of our achievement via the usage of knowledge graph,enhancing reliability and objectivity in urban transportation decision-making.

Potential effects of automated driving on vehicle travel demand: A comparison of three case cities

Automated vehicles(AVs)hold the potential to reduce road accidents,mitigate traffic congestion,and improve travel experience.However,the possible countervailing impacts from the changes in underserved populations’vehicle travel demand tend to be overlooked.To determine the vehicle travel demand changes that resulted from underserved populations aged between 6 and 80,this paper explores the latent effect of AVs on vehicle kilometers traveled(VKT)in a fully AV environment using person trip survey data from the cities of Sanya,Shijiazhuang,and Shenzhen in China.This paper uses the natural decline hypothesis of travel demand and proposes a regression model to investigate the difference among the cities’latent vehicle travel demand.Results show that the average VKT of the overall population in Sanya,Shijiazhuang,and Shenzhen increased by 33.4%,47.0%,and46.8%,respectively.The analysis of the regression model confirms that the current travel behavior of individuals can affect the degree of increase in their average VKT.Integrating AVs into public transport,increasing the acceptance of automated shared mobility options,transforming road space use type,and prototyping AV designs with various features and needs are potential methods to cope with the countervailing impacts.The total VKT of the overall population increased by approximately 10%-25%depending on the city.The conclusions of this paper provide informative insights into the evaluation of VKT for underserved populations and contribute to the deployment of AVs to address equity and inclusion issues.

Effect of Increase in Price of Oil on Behavior of Private Car Owners in Beijing

In order to understand the short-term response of private car owners to changes in the price of oil,a survey was conducted in Beijing after the gasoline price in China rose in June 2008.It showed that private car drivers in Beijing reduced their trips in the one month period following the price adjustment.Certain trip characteristics and drivers' demographics significantly influenced price elasticity in the short term,including the purpose of the trip,the distance covered and the income of the car driver.

Relationship Between Built Environment, Socio-economic Factors and Carbon Emissions from Shopping Trip in Shenyang City, China

Promoting active travel behavior and decreasing transport-related carbon dioxide （CO2） emissions have become a priority in many Chinese cities experiencing rapid urban sprawl and greater automobile dependence. However, there are few studies that holistically examine the physical and social factors associated with travel CO2 emissions. Using a survey of 1525 shoppers conducted in Shenyang, China, this study estimated shopping-related travel CO2 emissions and examined how the built environment and individual socioeconomic characteristics contribute to shopping travel behavior and associated C02 emissions. We found that, firstly, private car trips generate nearly eight times more carbon emissions than shopping trips using public transport, on average. Second, there was sig- nificant spatial autocorrelation with CO2 emissions per trip, and the highest carbon emissions were clustered in the inner suburbs and between the first and second circumferential roads. Third, shopping travel CO2 emissions per trip were negatively correlated with sev- eral built environment features including population density, the quantity of public transport stations, road density, and shop density. They were also found to be significantly related to the individual socio-eeonomic characteristics of car ownership, employment status, and education level using a multinomial logistic regression model. These empirical findings have important policy implications, assisting in the development of measures that contribute to the sustainability of urban transportation and meet carbon mitigation targets.

Tour Level Mode Choice Analysis of Madison Area in Wisconsin

This study is to investigate what factors and how they affect tours (trip chains) behavior. The key issue is the understanding and definition of tour and tour level mode. Also, these definitions should fit for the data. A semi-home based tour definition is stated, and a competing mode based tour mode is defined. Based on the definition, this study used Madison Area Data from National Household Survey to estimate a MNL structured model. It is found that travel distance could be a positive factor for car mode. Meanwhile, the number of trips is also a positive factor for choosing car.

A comparative study of automotive trip characteristics between older drivers and others among densely inhabited district and other areas

This paper examines older driver＇s automotive trip （abbreviation： trip） characteristics which include trip frequency, trip length, destination distribution, and non- home-based （NHB） trips. A two-month experiment of 108 participants was carried out to collect GPS tracking data in Aichi Prefecture, Japan. To identify the effect of living area, a comparative analysis between older drivers and others is conducted in densely inhabited district （DID, i.e., urban） and other areas （non-DID, i.e., suburban, rural, etc）, separately. The present study found that there was no sig- nificant difference between the trip characteristics of older drivers and others who were living in DID. Thus, we suggest that the education of safety driving and the rec- ommendation of public transportation should be given to DID-living older drivers. However, the results of non-DID reflected that older drivers＇ trip frequency, trip length, destination, and NHB trips rate were shorter and lower than others＇. This implies that electric vehicles may be suit- able for promotion among older drivers in suburban and rural area. Furthermore, the regression analysis confirmed that ＂older driver＂ was a significant independent variable on trip frequency, trip length, and NHB trips, and there were interaction effects between ＂older driver＂ and ＂living areas＂ on all trip characteristics.

Transportation Users’ Attitudes and Choices of Ride-Hailing Services in Two Cities with Different Attributes

The rapid technological developments in the 21st century created new opportunities for shared-use economy applications around the globe. Among other services, Transportation Network Companies (TNCs) like Uber and Lyft emerged in the US as a transportation alternative that offered a higher level of availability, reliability, and convenience than traditional modes. However, TNCs deployment was also blamed for increases in vehicle miles traveled (VMT) in large cities that embraced TNC services early on. Concerns about TNC adoption are also magnified by the current controversy in policy and legislation as to the regulation of TNCs. These new realizations create a need to examine the transportation users’ attitudes and perceptions regarding ride-hailing service, after nearly a decade of service in the Unites States market. In doing so, this paper compares and contrasts results from two recently completed studies aiming at creating links between socio-demographic factors and TNC use. The paper describes the methods employed to collect the data and presents findings from the analysis of 790 users’ responses in the Birmingham, AL and Miami Beach, FL markets. The study documents preferences and attitudes toward TNCs and highlights similarities and differences in travel behaviors related to local considerations. Moreover, the study uses the Least Absolute Shrinkage and Selection Operator (Lasso) method to identify predictors for TNC use based on the users’ responses in Birmingham and Miami Beach case studies. Vehicle availability and waiting time emerged as the only significant predictors for the Birmingham region whereas vehicle ownership, vehicle use, residency, and prior use of transit and TNC where some of the predictors identified for the Miami Beach area. Understanding the characteristics of TNC users and the leading reasons that drive people towards the use of TNCs services is expected to help transportation agencies and TNC providers in their efforts to plan for transportation services that meet customer needs in the future.

Climate and Tourism： Generational Differences and Effects on Satisfaction

Climate, weather, and its attributes such as temperature and number of rainy days are essential for the success of many tourism destinations. As climate scientists have determined that climate changes are inevitable, tourism destinations need to determine how to best manage these changes and mitigate any negative consequences. In addition, the perceived weather and/or climate at a destination can have as much weight on an individual＇s travel experience as the actual weather. The purpose of this study was to examine climate attributes and their importance on a traveler＇s behavior and satisfaction. Two hundred and sixty four surveys were gathered in the Mediterranean regions of Europe in the summer of 2009. Regression analysis revealed that climate attributes play a role in a traveler＇s satisfaction with their choice of a destination, but the traveler does not feel that climate changes are affecting their destinations as a whole. Analysis of variance （ANOVA） determined generational age differences in importance of climate attributes and if climate changes are affecting destinations. Management considerations for destination planners are explored.

Correlation between travel experiences and post-COVID outbound tourism intention:a case study from China

The COVID-19 pandemic has devastated global tourism and recovery is proceeding very slowly.For many countries,tourism served as a major economic sector,so investigating how to recover is essential.As China was the largest source of outbound travelers before the outbreak,study of the factors influencing Chinese intentions to travel overseas in the post-COVID era is revealing.In Apr.2022,among seven provinces(or cities)with the most outbound tourists from 2019 to 2021,2450 individuals responded to a questionnaire on daily mobility,tourism experiences,and the shifts due to the pandemic.Light gradient boosting machine(LightGBM),a robust ensemble learning method,was adopted to quantify and visualize the impact of explanatory factors on outbound travel intention.In addition,the Optuna mechanism and Shapley additive explanation(SHAP)instruments were employed for tuning hyperparameters and interpreting results,respectively.Findings suggest neither one-day nor multi-day tours have resumed to pre-COVID levels.Higher frequency of multi-day tours with further destinations,less car utilization in daily shopping trips,and moderate pandemic restrictions can boost the intention to travel abroad.The concerns and desires of different age groups for overseas travel need different responses.This study reveals the factors affecting Chinese outbound travel intentions and provides suggestions for the recovery of tourism in the post-COVID period.