Changes In Travel Behavior Research Articles

ЕФЕКТИВНІСТЬ ТА ПРІОРИТЕТНІ НАПРЯМИ РОЗВИТКУ СТРАТЕГІЧНОГО УПРАВЛІННЯ ТУРИСТИЧНОЮ ДЕСТИНАЦІЄЮ МІСТОМ КИЄВОМ В УМОВАХ ПАНДЕМІЇ COVID-19 ТА ВОЄННОГО СТАНУ

The main purpose of this study is to develop a mechanism for strategic management of the tourist destination of Kyiv in the context of the COVID-19 pandemic and martial law. The methodology involves a mixed approach that combines the collection and analysis of qualitative and quantitative data to assess the impact of these conditions on tourism and develop recommendations for strategic management. The results showed a significant decline in tourism revenues, shifts in the demographic structure of tourists, and changes in travel behavior. Strategic management measures, such as strengthening digital marketing, diversifying tourism products, and strengthening local partnerships, were identified as crucial for the recovery and sustainability of Kyiv’s tourism sector. The study offers practical recommendations for improving strategic tourism management, ensuring sustainability and resilience to future challenges.

Monitoring the impact of COVID-19 on the travel behavior of train travelers in the Netherlands

Mobility patterns and transport systems have been heavily impacted due to the COVID-19 pandemic. Public transport is impacted heavily, as governments worldwide advised against using it. This paper presents the data collection effort initiated by NS (Dutch Railways) and Delft University of Technology to capture changes in travel behavior, attitudes and intentions related to the COVID-19 pandemic among Dutch train travelers. The survey set-up, data collection process, data validation and potential of the dataset are discussed. The data collection effort proves to be a valuable longitudinal data set that is ground for many research opportunities and policy insights.

State-of-the-art of Longitudinal Travel Surveys – A Comparison of the MOP and MPN

Longitudinal travel surveys are needed to capture individual travel behaviour changes. Only two longitudinal tavel surveys of national relevance are currently in operation, the German Mobility Panel (MOP) since 1994 and the Netherlands Mobility Panel (MPN) since 2013. This paper provides an overview of both panels' differences and similarities in design and data collection. Furthermore, representativeness, diary fatigue and non-random attrition are assessed in both panels to show the challenges panel surveys have to deal with. Overall, this paper shows important aspects of a panel survey that should be considered when designing a new longitudinal travel survey.

Travel Behavior Changes during the COVID-19 Pandemic in Indonesia: Present, Past and Future

COVID-19 (Coronavirus Pandemic2019) brought major changes to the behavior and mobility of people all over the world. This change is mainly a consequence of the lockdownand social distancing taken by governments in most countries around the world. This article presents an analysis of a survey conducted in major cities from 6 big islands in Indonesia (Java, Bali, Sumatera, Kalimantan, Maluku, Papua) where citizens were asked about their mobility preferences before, during, and after the lockdown due to the virus and about factors that influence the decision in choosing a mode. The surveyors distributed the closed questionnaireusing Googleformsto reduce the contact time with the respondents. The data is processed through a comparative test with the Friedman Test revealed that there is an average difference in the choice of transportation mode before, during,and after the pandemic and there is also a difference about the main travel purpose of the community before, during, and after the pandemic. The main purpose of respondents' travel before the pandemic was work/school, during the pandemic it was shopping the daily needs (except those working in the essential sector) and after the pandemic returning to work/school as the main purpose of travel.The resultsof the influence test on ninesocio-demographic conditions revealed that before the pandemic there were 6 factors that influenced the mode choice, which is: gender, type of job, working in the essential sector or not, the number of people in the family, vehicle ownership and marital status influenced the modal choice, during pandemic COVID-19there was 5 influential factors, which is: age, occupation, working in the essential sector/not, number of family members and vehicle ownership, after the pandemic are the same as before the pandemic except working in the essential sector/not.

Workshop synthesis: Virtual reality, visualization and interactivity in travel survey, where we are and possible future directions

This paper summarizes the discussion of the workshop B16 “Virtual reality, visualization and interactivity in travel survey, where we are and possible future directions”. The workshop involved three sessions over the course of the conference. First two sessions discussed the current state of research, challenges, and possible future directions. The last session focused on synthesis of a research agenda for the next five years. It was concluded that the VR/AR tools and platforms provide a unique opportunity to proactively investigate the travel behaviour changes that are expected to happen due to the development and adoption of disruptive mobility technologies and services as well as virtual worlds and digital twins.

Detecting Pattern Changes in Individual Travel Behavior Based on a Bayesian Method

Detecting Pattern Changes in Individual Travel Behavior Based on a Bayesian Method

An Evaluation and Prioritization Framework for Pilot First- and Last-Mile Ridesharing Services

Ridesharing is part of the innovative shared transport regime which aims to maximize the utilization of mobility resources. Gaining knowledge of ridesharing’s impacts and how to assess them can significantly improve such services and thus contribute to their adoption among broader groups of travelers and to travel behavior change. This paper presents the framework deployed for assessing the impacts of a first-/last-mile ridesharing pilot in Athens, Greece, and capturing stakeholders’ (i.e., a researcher organization, a public authority and an infrastructure provider) point of view about planning objectives. Four impact areas are defined in total, and Key Performance Indicators (KPIs) are used. In parallel, in order to understand the stakeholder priorities when designing ridesharing services, the Analytical Hierarchical Process is implemented to estimate weights for each impact area. Increasing rail ridership is considered the top priority for all stakeholders during the planning phase for a first-/last-mile ridesharing service, which may have various implications for future initiatives. In total, 28 participants used the ridesharing service as drivers and passengers during the demonstration period. Results show that although a ridesharing service is expected to be an asset in daily transport for city travelers, the technological constraints currently burden its usage. However, as supported by demo results and travelers’ experience, there is great potential of ridesharing to contribute to a sustainable transport system and serve as a first- and last-mile solution to public transport.

Digital technologies of transportation-related communication: Review and the state-of-the-art

Information and communication technologies (ICTs) play a significant role in transportation systems as they provide the connection between transportation system users, system planners, operators, and managers. Over the last few years, with advancements in ICTs, there has been a rapid change in travel behaviour. However, little is known about how ICTs and other emerging digital technologies are being utilised in transportation-related communication for public, private, and active transportation. To bridge this gap, this study aims to explore academic and grey literature focused on the use of digital technologies in transportation-related communication. The methodological approach employs a systematic literature review, with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) protocol, to identify digital technologies that are found promising among scholars and practitioners for research, testing and deployment. The study analysed 158 publications and identified some common themes of how these digital technologies can be implemented to improve access to transportation communication. The study finds that: (a) The main literature focus is how information is gathered and shared with transportation users; (b) Advances in mobile applications afford real-time route updates, easy navigation of complex routes, and personalised journey planning; (c) Some notable knowledge gaps exist in how these technologies are implemented—including, willingness to use and digital literacy to understand them; (d) Many digital technologies are at the trial or development phases, which have potential to improve how transportation information can be made readily accessible to all users.

The potential of changing habitual car user travel modes: The case of Czech towns

With the constant and ever-growing pressure from governing bodies for increased sustainability of transportation systems, the need for changes in the travel behaviours of the inhabitants of suburban and urban areas seems inevitable. Thus a shift from cars to vehicles with higher occupancy rates or other more environmental friendly travel modes needs to be a priority. This requires understanding the reasons why people choose cars as their preferred mode of travel for commutes in order to make informed decisions about how to encourage changes in commuter travel behaviors. This paper presents a case study of four medium-sized Czech towns, including a survey concerning pre- and post-COVID-19 travel habits focused on identifying and understanding the willingness of car-dependent commuters to change their mode of travel choice. This three-stage survey revealed a small, COVID pandemia -based effect on the habits of respondents and helped to identify sensitivities survey participants had to particular travel parameters and characteristics that might be used by municipalities to implement informed policies that could lead to changes in travel behaviours.

Impact of COVID-19 on Student’s Travel Behavior in Bangalore City, Karnataka

The COVID-19 tragedy had a significant impact on travel and demand for transportation in India before everything returned to normal. The current study is focused on students’ travel behavior in Bangalore City because commutes to college and university were most adversely affected during the pandemic. The modeling of travel demand and transportation planning in and around educational regions depend heavily on the investigation of student travel behavior in large cities like Bengaluru. An online questionnaire survey was used to gather information about changes in travel behavior before and after the COVID-19 outbreak. Gender, age, vehicle ownership, household income, travel expenditure, and travel distance all have a substantial impact on the primary trip taken according to the findings. It is also observed that the frequency of student trips reduced from 6 days per week to 3 to 4 days per week. The analysis also shows that many students chose to stay at home than PG or hostel post-COVID-19 due to concerns about the virus’s spread. To simulate the behavior change, multiple linear regression, and artificial neural networks were employed. The ANN model showed the best fit for forecasting travel behavior in terms of travel duration before COVID-19 and after the COVID-19 outbreak, according to the AUC values. The finding of the work can be used for better planning of their operations and services, especially, near colleges and universities.

Evaluating the Interplay between Trajectory Segmentation and Mode Inference Error

Travel behavior changes are essential to transportation decarbonization. Travel diaries, consisting of sequences of trips between places, are typically used to instrument human travel behavior. However, these diaries are only as accurate as the underlying methods used to construct them. Travel diary algorithms have been a popular research topic since the advent of Global Positioning System tracking surveys. These algorithms have typically been validated using prompted recall of presegmented trips, thus disregarding the continuity of mode inference. Phone operating systems have adopted battery-conserving techniques, but the resulting data collection errors have not been studied extensively. We introduce a framework to evaluate the accuracy of trip length computations and mode inference by analyzing continuous mode-segmented trajectories for groups of trips. We then use the framework to identify the input data quality and the impact of postprocessing. Our primary inputs to this evaluation are MobilityNet, a public dataset containing information from three artificial timelines covering 15 different travel modes, and sample open-source travel diary creation algorithms from the OpenPATH project. Our framework concretely shows that the variance of the distance error drops from [Formula: see text] to [Formula: see text] (Android, iOS) after postprocessing. Similarly, the weighted F-scores for mode inference increase from [Formula: see text] to [Formula: see text] (iOS, Android) between random forest and geographic information system-based models. We hope that this standardized method will be adapted to evaluate other, potentially proprietary, travel diary algorithms. The results can be used to understand and improve the state of the art in the travel diary creation field.

“I saw a fox in Melbourne CBD”: Urban travel behaviour changes during COVID-19 and beyond

An unexpected outcome of the COVID-19 pandemic were the dramatic travel behaviour changes experienced in cities worldwide, which, could result in more sustainable transport systems. Consequently, there is a need for longer-term post-pandemic travel behaviour change research. This study aimed to investigate city-level travel behaviour changes during and post-pandemic. To our knowledge, this is the first qualitative study exploring the permanency of COVID-19 travel behaviour changes. This study involved a literature review of 41 studies and in-depth interviews with 19 transport stakeholders in metropolitan Melbourne, Australia. Melbourne is a valuable study area, given that it was the most locked-down city globally. Overall, the results of this study suggest that post-pandemic travel behaviour will be different to pre-pandemic, with working from home (WFH) an integral influence on travel behaviour. In addition, several overarching travel behaviour changes were identified: WFH significantly increased during the pandemic and is anticipated to continue post-pandemic. Both public transport and private motor vehicle (PMV) trips decreased during lockdowns; while PMV rebounded quickly, public transport remained low, and a long recovery is expected. Active transport (cycling and walking) increased during the pandemic and appear likely to endure. Finally, while shared travel modes have received less attention, modal variance is expected in the future. This study has made several key contributions. It consolidated our understanding of the wide range of urban travel behaviour changes experienced during and anticipated post-COVID-19. Secondly, it synthesised current knowledge of recent post-COVID-19 travel behaviour change research. Thirdly, this study demonstrated that complementary qualitative studies strengthen transport research by unearthing new insight into the reasons underpinning travel behaviours, which could be vital for developing solutions. Furthermore, this study identified critical future research topics. Given that most countries are learning to live with the virus, it is an opportune time to investigate whether these intended travel behaviours have endured.

A framework of routine transitions in daily travel

The occurrence of life events increases the likelihood of changes in travel behaviour and these are often discussed as windows of opportunity for interventions aimed at improving sustainable travel. Hence, theoretical knowledge of the process of change due to life events is important for enabling the development of interventions suited to these naturally-occurring situations. In this paper, the Framework of RoUtIne Transitions in daily travel (FRUIT) is presented, depicting the internal processes involved when one chapter of life, characterized by stability in daily travel, gives way to another. Building on theory relating to habit disruption and formation, and designed for the inclusion of existing models and concepts relating to deliberate decision-making, the framework points to two critical phases as focus areas. Using an empirical case, the applicability of FRUIT is illustrated, with the implications of the framework for future research and policy being outlined and discussed.

A qualitative study on transportation experiences of public transport users in Türkiye during the COVID-19 pandemic

Due to the COVID-19 outbreak, people refrained from crowded places; public transport is one of them. The need for movement was restricted as part of governmental precautions. However, some people continue to go to workplaces as usual, and the ones who do not have personal vehicles continue using public transportation. The current study aims to investigate the experiences of public transport users (i.e., passengers) in Türkiye during the COVID-19 pandemic. Semi-structured interviews were conducted with ten people living in Ankara. As a result of thematic analysis, four overarching themes and fifteen sub-themes were determined. These overarching themes include changes in travel behavior during COVID-19, factors influencing transportation preferences, suggestions for better planning of public transport services, and suggestions for better crisis management. The results suggest significant policy implications at the municipal and governmental level, emphasizing the need for transparent risk communication, timely measures, and enforcement. Additionally, the study highlights transportation inequity, which becomes visible after the pandemic. We believe that qualitative data provided valuable insight to road authorities about road users' transportation experiences during the pandemic and, thus, how to manage better the pandemic's effect on the transport system based on the mobility needs of the citizens. We hope the results could benefit road authorities in developing effective policies and plans for all countries in the world, especially for the ones having a specific need to improve safety in traffic settings.

COVID-19 and the demand for transit access: Residential real estate prices in the Tokyo metropolitan area

To better understand the spatial implications of the COVID-19 pandemic on demand for both housing and transportation, this analysis examines sales price data from condominiums in the Tokyo metropolitan area. Demand for high-access condominiums—both those near transit stations and those in close proximity to the city center—was strong throughout the study period (2017–2022), and showed neither a positive nor negative association with the onset of the pandemic. Price growth for lower-access properties—those further from transit stations and those in peripheral suburban locations—was, by contrast, far more robust during the COVID era than in the pre-pandemic period. Results suggest that COVID-related changes in travel behavior—particularly the decreased commute burden associated with remote work—may have made lower-access locations more attractive to home buyers. This has not, however, tempered demand for properties near transit and in the central city, which remained strong throughout the pandemic period.

Impact of Covid-19 on Mobility: The Case of Lahore

Coronavirus pandemic has caused severe consequences on traveling behavior since its inception into the world in 2019. The government authorities have declared protective means to limit transportation while discouraging community congregations by giving guidelines to have social distancing with maintaining a healthy lifestyle which will lower the growth of the viral infection. This study aims to evaluate and assess the considerable changes in the mobility pattern and travel behavior of the residents of Lahore during lockdown which have slow down the virus’ spread. The mobility patterns were studied through Google database 1 in the form of google mobility reports. Data obtained from the COVID-19 website of Pakistan was examined by GIS and converted into statistical data comprising of graphs and figures by authors. The findings of this research are that the COVID-19 pandemic has had a profound impact on transportation and air quality in Lahore, resulting in changes in travel behavior, reduced traffic congestion, and improved air quality, which have both positive and negative effects on public health and the environment. These findings indicate that the implementation of air quality control plans can lead to a significant improvement in air quality in Pakistan. However, the economic hardships caused by the pandemic also need to be addressed. This research shows that the public can adapt to changes in policies and travel behaviors during the pandemic. These implications can be applied to design more sustainable transportation policies in the future.

Investigating the changes in travel behaviour during an economic crisis in a developing country: A case study of the Greater Beirut Area, Lebanon

Lebanon is currently facing one of the worst economic crises in its history, which has been compounded by the economic consequences of the COVID-19 pandemic and the devastating explosion at the Port of Beirut in August 2020. This research focuses on the Greater Beirut area in Lebanon, aiming to examine the impact of the ongoing economic crisis on travel behavior. The study analyzes changes in travel behavior before and during the crisis for various trip purposes, including the number of trips and modes of transportation used. Socio-economic factors that may have influenced these changes are also considered. Descriptive analyses and multivariate statistics reveal that the economic crisis had a significant influence on people's travel behavior. Multinomial logistic regression models highlight the impact of factors such as age, nationality, occupation, household size, income, and spending fluctuations on trip frequency changes during the crisis. The analysis of the data indicates a decrease in all trip types during the crisis, partly due to the adoption of online study and work, resulting in fewer commuting trips. Private car usage declined for shopping trips, while motorcycles and public transport witnessed an increase. Recreational trips reduced significantly, with more respondents opting for fewer trips per year, showing a noticeable preference for buses. Despite the shift away from private cars, the adoption of public transport remains modest, partly due to limited accessibility, safety concerns, and unreliable services.

Role of income on travel behavior in polluted air

IntroductionPolluted air causes health problems and disrupts people's daily lives. Under polluted air conditions, people's travel behavior tends to change, and this can be different by their economic status. In this context, this study explored how travel behavior (i.e., whether to make a trip and what transportation mode to take) changes during times of poor air quality and how the changes vary according to income level. MethodsWe conjoined and analyzed the data from a national household travel survey and from air quality measurements collected in South Korea's capital region. Multilevel logistic regression modeling was used to consider the structure of the conjoined data. ResultsThe modeling results show that people generally responded to polluted air by reducing their trips and by avoiding walking outside or riding bikes. Higher-income groups made fewer trips during weekends and used motorized transportation modes more than those in lower-income groups. However, people with lower incomes also sensitively responded to poor air quality by changing their transportation mode to a more protective one, notably from non-motorized modes to public transit. ConclusionsThe results demonstrate social disparity regarding travel-related options in polluted air and emphasize the importance of public transit for lower-income communities to minimize their exposure to polluted air. This study contributes to the existing literature by providing contextualized insight into the role of income on trip generation and mode choice when air quality worsens. The findings from this study can assist in making policies that better protect the whole of society from the growing number of days with polluted air.

In search of causality in the relationship between the built environment and travel behaviour. On the challenges of planning and realising an ambitious mixed-methods panel travel survey among relocating households in Germany

Household residential location changes have become an important life event to study changes in travel behaviour. However, most related studies suffer from the shortcomings of collecting retrospective pre-move data, i.e. recall errors and ex-post rationalisation of change. What is more, the overwhelming majority of research in the field relies on quantitative data that do not adequately reflect the subjective perspective of the households or individuals under study, and that are prone to causality issues. Based on a solid theoretical discussion of causality between the built environment (on two interconnected scales) and travel behaviour, the paper reports on a mixed-methods (qualitative/quantitative) panel survey among movers and a control group of non-movers in Germany. Substantial effort was required to conduct the survey due to the dependence on collaboration partners who provided access to households planning to move in the near future. Therefore the paper focuses on the sampling and recruitment process, for which various channels were used. Results pertaining to representativeness and the costs and effectiveness of recruitment channels are presented, and implications for data analysis are briefly discussed. Conclusions are drawn with respect to the relevance of the approach for researchers and practitioners.

A ridehailing access program for regional rail

Transit agencies and municipalities partner with ridehailing providers to establish programs that improve first/last mile connections, extend service areas, or provide service at times when transit does not operate. Though many agencies that have implemented these programs report success, there are still open questions about what types of programs best serve what types of communities and geographies. At the same time, the COVID-19 pandemic caused a disruption in travel patterns and presented an opportunity for individuals to re-evaluate travel choices. As the pandemic wanes, we may observe longer-term changes in travel behaviors including the adoption of alternatives to driving alone. Introducing a new program at this time might spur more use than would have occurred if one of these things were to happen on its own. In this paper I use survey data collected in the City of Davis, California in the summer of 2020 to assess the expected use of planned shared use mobility programs to access regional rail for different types of travelers and trips; and whether and how the pandemic is relevant to those expectations. For those living in the Davis area, the programs would provide ridehailing and rideshare access to the Davis Amtrak station and the Capitol Corridor rail service that runs between Sacramento and San Jose, California. The majority of participants reported that they have an interest in the programs. The programs would likely increase the use of the train for non-commute travel.