scholarly journals The Public Bicycle as a Feeder Mode for Metro Commuters in the Megacity Beijing: Travel Behavior, Route Environment, and Socioeconomic Factors

2022 ◽  
Vol 148 (1) ◽  
Author(s):  
Pengjun Zhao ◽  
Dandan Yuan ◽  
Yixue Zhang
Keyword(s):  
Socioeconomic Factors ◽  
Travel Behavior ◽  
The Public

scholarly journals Identifying Protective Health Behaviors on Twitter: Observational Study of Travel Advisories and Zika Virus (Preprint)

2018 ◽  
Author(s):  
Ashlynn R Daughton ◽  
Michael J Paul
Keyword(s):  
Zika Virus ◽  
Travel Behavior ◽  
English Language ◽  
Disease Modeling ◽  
Control Sample ◽  
Emerging Infectious Diseases ◽  
The United States ◽  
The Public ◽  
Machine Learning Classification ◽  
Twitter Users

BACKGROUND An estimated 3.9 billion individuals live in a location endemic for common mosquito-borne diseases. The emergence of Zika virus in South America in 2015 marked the largest known Zika outbreak and caused hundreds of thousands of infections. Internet data have shown promise in identifying human behaviors relevant for tracking and understanding other diseases. OBJECTIVE Using Twitter posts regarding the 2015-16 Zika virus outbreak, we sought to identify and describe considerations and self-disclosures of a specific behavior change relevant to the spread of disease—travel cancellation. If this type of behavior is identifiable in Twitter, this approach may provide an additional source of data for disease modeling. METHODS We combined keyword filtering and machine learning classification to identify first-person reactions to Zika in 29,386 English-language tweets in the context of travel, including considerations and reports of travel cancellation. We further explored demographic, network, and linguistic characteristics of users who change their behavior compared with control groups. RESULTS We found differences in the demographics, social networks, and linguistic patterns of 1567 individuals identified as changing or considering changing travel behavior in response to Zika as compared with a control sample of Twitter users. We found significant differences between geographic areas in the United States, significantly more discussion by women than men, and some evidence of differences in levels of exposure to Zika-related information. CONCLUSIONS Our findings have implications for informing the ways in which public health organizations communicate with the public on social media, and the findings contribute to our understanding of the ways in which the public perceives and acts on risks of emerging infectious diseases.

scholarly journals People’s responses to the COVID-19 pandemic during its early stages and factors affecting those responses

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Junyi Zhang
Keyword(s):  
Travel Behavior ◽  
Structural Equation ◽  
Public Involvement ◽  
Population Distribution ◽  
Scientific Evidence ◽  
Large Set ◽  
Initial Attempt ◽  
Long Distance ◽  
The Public ◽  
Early Stages

AbstractThe world has suffered from the COVID-19 pandemic. While it is expected that societies will learn lessons from this experience, knowledge about how people responded to the pandemic in its early stages is very limited. With the aim of urgently providing policymakers with scientific evidence about how to better inform the public about fighting against COVID-19, this study made an initial attempt to assess how people responded to the COVID-19 outbreak during its early stages. Based on a life-oriented approach, this study collected data on a large set of behaviors and attitudes through a nationwide retrospective panel survey conducted in Japan at the end of March 2020, when the country had 1953 confirmed infection cases in total. Valid data were collected from 1052 residents from the whole of Japan, taking into account a balanced population distribution in terms of age, gender, and region. Respondents were asked to report changes in their daily activity-travel behavior, long-distance trips, and other life activities caused by the COVID-19 pandemic and associated factors (information reliability, risk perception, attitudes about policy-making and communications with the public, etc.). Results of both aggregate and modeling analyses (using a structural equation model and a data mining approach) indicate that poor communication with the public may have been closely related to the spread of COVID-19 in Japan, and that effective interventions should be made by focusing on interactions between target persons and close members of their social networks. It is also revealed that differentiated communications are necessary to encourage different types of behavioral changes. Risk communication should be better designed to encourage people to voluntarily modify their needs in life [L] and perform the needed activities [A] at places with sufficient spaces [S] and proper duration of time and at the proper timing [TING]. Such a LASTING approach may be crucial to enhance the effects of massive public involvement in mitigating the spread of COVID-19. The findings from this study are not only useful to tackle the current pandemic, but also have a long-term value for addressing future pandemics.

Analysis on effect of EV car sharing of one-way service on the public attitude and travel behavior

2013 ◽  
Vol 48 (3) ◽  
pp. 465-470
Author(s):  
akira ANDO ◽  
toshiyuki YAMAMOTO ◽  
takayuki MORIKAWA
Keyword(s):  
Travel Behavior ◽  
Public Attitude ◽  
Car Sharing ◽  
The Public

scholarly journals Long-Term Atmospheric Visibility Trends and Characteristics of 31 Provincial Capital Cities in China during 1957–2016

Atmosphere ◽  
2018 ◽  
Vol 9 (8) ◽  
pp. 318 ◽  
Author(s):  
Weicong Fu ◽  
Ziru Chen ◽  
Zhipeng Zhu ◽  
Qunyue Liu ◽  
Jinda Qi ◽  
...  
Keyword(s):  
Air Quality ◽  
Socioeconomic Factors ◽  
Urban Areas ◽  
Meteorological Factors ◽  
Ambient Air ◽  
Ambient Air Quality ◽  
Capital Cities ◽  
The Public ◽  
Provincial Capital

Millions of pulmonary diseases, respiratory diseases, and premature deaths are caused by poor ambient air quality in developing countries, especially in China. A proven indicator of ambient air quality, atmospheric visibility (AV), has displayed continuous decline in China’s urban areas. A better understanding of the characteristics and the factors affecting AV can help the public and policy makers manage their life and work. In this study, long-term AV trends (from 1957–2016, excluding 1965–1972) and spatial characteristics of 31 provincial capital cities (PCCs) of China (excluding Taipei, Hong Kong, and Macau) were investigated. Seasonal and annual mean values of AV, percentage of ‘good’ (≥20 km) and ‘bad’ AV (<10 km), cumulative percentiles and the correlation between AV, socioeconomic factors, air pollutants and meteorological factors were analyzed in this study. Results showed that annual mean AV of the 31 PCCs in China were 14.30 km, with a declining rate of −1.07 km/decade. The AV of the 31 PCCs declined dramatically between 1973–1986, then plateaued between 1987–2006, and rebounded slightly after 2007. Correlation analysis showed that impact factors (e.g., urban size, industrial activities, residents’ activities, urban greening, air quality, and meteorological factors) contributed to the variation of AV. We also reveal that residents’ activities are the primary direct socioeconomic factors on AV. This study hopes to help the public fully understand the characteristics of AV and make recommendations about improving the air environment in China’s urban areas.

Density and Captivity in Public Transit Success: Observations from the 1995 Nationwide Personal Transportation Study

2000 ◽  
Vol 1735 (1) ◽  
pp. 10-18 ◽  
Author(s):  
Steve E. Polzin ◽  
Xuehao Chu ◽  
Joel R. Rey
Keyword(s):  
Travel Behavior ◽  
Public Transit ◽  
Good Time ◽  
Transit Planning ◽  
Economic Changes ◽  
The Public ◽  
Transit Market ◽  
Personal Transportation ◽  
Transit Use ◽  
In Transit

The new millennium provides a good time to reflect on transportation-industry trends in some fundamental external factors that influence transportation behavior and planning response. In the public-transit industry, urban density and transit captivity have long been fundamental conditions driving transit planning and service and facility investment decisions. In light of demographic and economic changes, it is useful to revisit the issue of the importance of these factors to the transit market. Findings from a comprehensive analysis of the 1995 Nation-wide Personal Transportation Study (NPTS), which explored current transit-travel behavior, are reported. Two key findings reflect on two historical axioms in transit: ( a) the extent to which density influences transit use and ( b) the importance of the transit-dependent market. The research findings reiterate the significant influence that development density has on public transit mode share and bring to light some revealing data on the influence of urban-area size on transit use. The importance of transit dependency on transit use is documented, and trends in transit dependency over the past few decades are revealed. Finally, the implications of these trends for the public-transit industry are discussed.

scholarly journals The Influence of Introducing Autonomous Vehicles on Conventional Transport Modes and Travel Time

Energies ◽  
2021 ◽  
Vol 14 (14) ◽  
pp. 4163
Author(s):  
Jamil Hamadneh ◽  
Domokos Esztergár-Kiss
Keyword(s):  
Travel Time ◽  
Public Transport ◽  
Travel Behavior ◽  
Autonomous Vehicles ◽  
Fleet Size ◽  
The Public ◽  
Levels Of Automation ◽  
Multi Agent ◽  
Transport Modes ◽  
The Impact

Introducing autonomous vehicles (AVs) on the market is likely to bring changes in the mobility of travelers. In this work, extensive research is conducted to study the impact of different levels of automation on the mobility of people, and full driving automation needs further study because it is still under development. The impacts of AVs on travel behavior can be studied by integrating AVs into activity-based models. The contribution of this study is the estimation of AVs’ impacts on travelers’ mobility when different travel demands are provided, and also the estimation of AVs’ impact on the modal share considering the different willingness of pay to travel by AVs. This study analyses the potential impacts of AVs on travel behavior by investigating a sample of 8500 travelers who recorded their daily activity plans in Budapest, Hungary. Three scenarios are derived to study travel behavior and to find the impacts of the AVs on the conventional transport modes. The scenarios include (1) a simulation of the existing condition, (2) a simulation of AVs as a full replacement for conventional transport modes, and (3) a simulation of the AVs with conventional transport modes concerning different marginal utilities of travel time in AVs. The simulations are done by using the Multi-Agent Transport Simulation (MATSim) open-source software, which applies a co-evolutionary optimization algorithm. Using the scenarios in the study, we develop a base model, determine the required fleet size of AVs needed to fulfill the demand of the different groups of travelers, and predict the new modal shares of the transport modes when AVs appear on the market. The results demonstrate that the travelers are exposed to a reduction in travel time once conventional transport modes are replaced by AVs. The impact of the value of travel time (VOT) on the usage of AVs and the modal share is demonstrated. The decrease in the VOT of AVs increases the usage of AVs, and it particularly decreases the usage of cars even more than other transport modes. AVs strongly affect the public transport when the VOT of AVs gets close to the VOT of public transport. Finally, the result shows that 1 AV can replace 7.85 conventional vehicles with acceptable waiting time.

scholarly journals Individual Travel Behavior Modeling of Public Transport Passenger Based on Graph Construction

2018 ◽  
Vol 2018 ◽  
pp. 1-13 ◽  
Author(s):  
Quan Liang ◽  
Jiancheng Weng ◽  
Wei Zhou ◽  
Selene Baez Santamaria ◽  
Jianming Ma ◽  
...  
Keyword(s):  
Public Transport ◽  
Travel Behavior ◽  
Behavior Modeling ◽  
The Public ◽  
Demand Prediction ◽  
Study Results ◽  
Characteristics Analysis ◽  
Significant Change ◽  
The Individual ◽  
Behavior Choice

This paper presents a novel method for mining the individual travel behavior regularity of different public transport passengers through constructing travel behavior graph based model. The individual travel behavior graph is developed to represent spatial positions, time distributions, and travel routes and further forecasts the public transport passenger’s behavior choice. The proposed travel behavior graph is composed of macronodes, arcs, and transfer probability. Each macronode corresponds to a travel association map and represents a travel behavior. A travel association map also contains its own nodes. The nodes of a travel association map are created when the processed travel chain data shows significant change. Thus, each node of three layers represents a significant change of spatial travel positions, travel time, and routes, respectively. Since a travel association map represents a travel behavior, the graph can be considered a sequence of travel behaviors. Through integrating travel association map and calculating the probabilities of the arcs, it is possible to construct a unique travel behavior graph for each passenger. The data used in this study are multimode data matched by certain rules based on the data of public transport smart card transactions and network features. The case study results show that graph based method to model the individual travel behavior of public transport passengers is effective and feasible. Travel behavior graphs support customized public transport travel characteristics analysis and demand prediction.

scholarly journals Understanding Gender, Income and Travel Behavior in Casablanca City – Morocco

2021 ◽  
Vol 15 (1) ◽  
pp. 272-279
Author(s):  
Zineb Chamseddine ◽  
Asmaa Ait Boubkr
Keyword(s):  
Low Income ◽  
Travel Behavior ◽  
Cultural Context ◽  
Vulnerable Groups ◽  
Transit System ◽  
The Public ◽  
Work Related ◽  
Income Groups ◽  
Private Car ◽  
The City

Objective: The purpose of this paper is to extend the research on gendered differences in travel behavior in developing countries by analyzing travel behavior variability within as well as across gender and income groups in the case of Casablanca city. Methods: Data from the 2018 Casablanca Travel Survey show that overall, women are less mobile than men, make fewer work-related trips and more household maintenance trips, but these differences are heterogeneously distributed across income groups. With the increase in income, women tend to carry out more trips than men; the inverse is observed for the middle- and low-income categories. Results: While for the lowest income groups, walking is the most predominant mode for both men and women, we notice that the private car has the highest modal share within the highest income groups as with the increase in household income, both genders avoid non-motorized transport modes. The particular status of women in some households as breadwinners and reproducers as well as the socio-cultural context of the city shape their mobility and the choice of their activities. Conclusion: Hence, these findings suggest, from a policy perspective, that the public transit system along with spatial planning strategies need to be improved to help overcome women's mobility constraints, especially when they belong to low-income households so they can fully access the city amenities and opportunities. On the other hand, transport policies need to be not only gender-sensitive but also “vulnerable groups” sensitive as mobility impediments are similarly experienced by males and females in some contexts.

scholarly journals The impact of COVID-19 on trips to urban amenities: Examining travel behavior changes in Somerville, MA

PLoS ONE ◽  
2021 ◽  
Vol 16 (9) ◽  
pp. e0252794
Author(s):  
Andres Sevtsuk ◽  
Annie Hudson ◽  
Dylan Halpern ◽  
Rounaq Basu ◽  
Kloe Ng ◽  
...  
Keyword(s):  
Consumer Behavior ◽  
Travel Behavior ◽  
Discrete Choice Models ◽  
Behavior Changes ◽  
The Public ◽  
Location Data ◽  
Home Location ◽  
Urban Amenities ◽  
Location Patterns ◽  
The Impact

While there has been much speculation on how the pandemic has affected work location patterns and home location choices, there is sparse evidence regarding the impacts that COVID-19 has had on amenity visits in American cities, which typically constitute over half of all urban trips. Using aggregate app-based GPS positioning data from smartphone users, this study traces the changes in amenity visits in Somerville, MA from January 2019 to December 2020, describing how visits to particular types of amenities have changed as a result of business closures during the public health emergency. Has the pandemic fundamentally shifted amenity-oriented travel behavior or is consumer behavior returning to pre-pandemic trends? To address this question, we calibrate discrete choice models that are suited to Census block-group level analysis for each of the 24 months in a two-year period, and use them to analyze how visitors’ behavioral responses to various attributes of amenity clusters have shifted during different phases of the pandemic. Our findings suggest that in the first few months of the pandemic, amenity-visiting preferences significantly diverged from expected patterns. Even though overall trip volumes remained far below normal levels throughout the remainder of the year, preferences towards specific cluster attributes mostly returned to expected levels by September 2020. We also construct two scenarios to explore the implications of another shutdown and a full reopening, based on November 2020 consumer behavior. While government restrictions have played an important role in reducing visits to amenity clusters, our results imply that cautionary consumer behavior has played an important role as well, suggesting a likely long and slow path to economic recovery. By drawing on mobile phone location data and behavioral modeling, this paper offers timely insights to help decision-makers understand how this unprecedented health emergency is affecting amenity-related trips and where the greatest needs for intervention and support may exist.

scholarly journals The Influence of Socio-Economics on Travel Behavior of Public Transportation in Malaysia

2021 ◽  
Vol 6 (17) ◽  
pp. 269-275
Author(s):  
Rohana Ngah ◽  
Jamalunlaili Abdullah ◽  
Muhammad Khalique ◽  
Sanjar Bakhodirovich Goyipnazarov
Keyword(s):  
Public Transport ◽  
Public Transportation ◽  
Travel Behavior ◽  
Publishing House ◽  
Face To Face ◽  
The Public ◽  
Strategic Plans ◽  
International Publishing ◽  
Open Access Article ◽  
Public Transport Service

This paper explores the influence of socioeconomics on travel behavior among public transport commuters to increase modal share. A face-to-face survey was carried out, and 904 usable questionnaires were analyzed using SPSS. The findings showed that level of education strongly influences travel behavior while there is not much difference in gender, age, income, and occupation. However, the categories in the groups provide good information relating to travel behavior. Suggestions and recommendations are provided to help the public transport service provider setting more strategic plans to encourage more individual riders to switch to public transport and sustain existing users.   Keywords: Socio-economics, travel behavior, public transport   eISSN: 2398-4287© 2021. The Authors. Published for AMER ABRA cE-Bs by e-International Publishing House, Ltd., UK. This is an open access article under the CC BYNC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer–review under responsibility of AMER (Association of Malaysian Environment-Behaviour Researchers), ABRA (Association of Behavioural Researchers on Asians/Africans/Arabians) and cE-Bs (Centre for Environment-Behaviour Studies), Faculty of Architecture, Planning & Surveying, Universiti Teknologi MARA, Malaysia. DOI:  https://doi.org/10.21834/ebpj.v6i17.2833

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