Accounting for the spatial incidence of working from home in an integrated transport and land model system.

The COVID-19 pandemic has resulted in a seismic shift in the way in which work is conducted. Remote working or working from home is becoming a centrepiece of the next normal with strong support from both employers and employees. With reduced commuting activity associated with an expected 1 to 2 days working from home for many occupations and industries, associated with releasing commuting time to spend on other activities including changed levels and patterns on non-commuting travel, it is necessary, indeed essential, to allow for the incidence of working from home in integrated strategic transport and location model systems. In this paper we show the extent of changes in travel behaviour and the performance of the transport network before and after allowing for working from home, which is more impactful than any new infrastructure project. The differences are significant and suggest that even within the existing modelling frameworks used pre-COVID-19, we need to make adjustments in the modal activity overall and by location. Using the MetroScan platform in the Greater Sydney Metropolitan area, we present a number of outputs to illustrate the significant impacts of working from home such as modal activity (total and shares), emissions, government revenues, and generalised cost of travel.

Uneven domestic tourism demand in times of pandemic

This study investigates the short-run impact of the COVID-19 pandemic on the number of domestic overnight stays at the regional level in the summer season 2020. Official data for 65 regions in four countries are used for the analysis (Austria, the Czech Republic, Germany and Switzerland). Dynamic panel data models are employed to estimate a tourism demand equation (real GDP and price fluctuations) augmented by average temperatures. Estimation results reveal that domestic overnight stays evolve unevenly in the first summer after the outbreak of the COVID-19 pandemic. The short-run effects show that the number of domestic overnight stays in densely populated regions decreases by 27% in July as well as in August 2020, in comparison with the same months in previous years, ceteris paribus. To the contrary, there is a surge of 27 and 10%, respectively, for sparsely populated areas in the same months.JEL: Z3, R11 and R12.

Examining Impacts of COVID-19-Related Stay-At-Home Orders through a Two-Way Random Effects Model.

The COVID-19 pandemic has had far-reaching impacts on public health and safety, economics, and the transportation system. To reduce the spread of this disease, federal and local governments around the world have introduced stay-at-home orders and other restrictions on travel to "non-essential" businesses to implement social distancing. Preliminary evidence suggests substantial variability in the impacts of these orders in the United States, both across states and over time. This study examines this issue using daily county-level vehicle miles traveled (VMT) data for the 48 continental U.S. states and the District of Columbia. A two-way random effects model is estimated to assess changes in VMT from March 1 to June 30, 2020 as compared with baseline January travel levels. The implementation of stay-at-home orders was associated with a 56.4 percent reduction in VMT on average. However, this effect was shown to dissipate over time, which may be attributable to "quarantine fatigue." In the absence of full shelter-in-place orders, travel was also reduced where restrictions on select businesses were introduced. For example, restrictions on entertainment, indoor dining, and indoor recreational activities corresponded to reductions in VMT of 3 to 4 percent while restrictions on retail and personal care facilities showed 13 percent lower traffic levels. VMT was also shown to vary based on the number of COVID case reports, as well as with respect to other characteristics, including median household income, political leanings, and how rural the county was in nature.

Impact of COVID-19 restrictions on South African air transport and tourism indicators

Background: Air travel restrictions to prevent the spread of coronavirus disease 2019 (COVID-19) impacted air travel to and from and within South Africa significantly. The duration of the pandemic was more protracted than initially expected as new variants of the pandemic (in ‘waves') resulted in additional restrictions. Objectives: To determine the nature of COVID-19-related air travel restrictions, their impact on annual passenger demand, the number of flights operated (supply of services), the related average passenger loads carried as well as on tourism indicators of the direct contribution of travel and tourism, the total contribution to Gross Domestic Product (GDP) and employment. Method: The study identifies the number of passengers carried and flights operated and calculates the average passenger load per flight and trends. The impact on tourism indicators is based on the unit values of metrics published by the World Travel and Tourism Council for the 2019 calendar year, adapted for the reduction in passengers in the first and second years following the COVID-19 lockdown. Results: Significant decreases in the annual number of passengers carried, flights operated (in the three geographic areas), and their impact on tourism and employment indicators were identified. Conclusion: The decline in passengers exceeded the decrease in flights operated, which resulted in a decline in the average load of passengers carried per flight. The significance of COVID-19 restrictions on tourism indicators and employment was also calculated. Contribution: The study identifies the impact of COVID-19 air travel restrictions on both air transport and tourism indicators for South Africa.

Potential impacts of the Covid-19 pandemic on the future of travel demand

The Covid-19 pandemic has dramatically cut the amount people travel, with possible long-term effects on demand. Greg Marsden of the University of Leeds says civil engineers need to reconsider how they plan future transport infrastructure accordingly.

Estimating post-pandemic effects of working from home and teleconferencing on travel behaviour

Like in many other countries, the Dutch government instructed people to work from home where possible during the COVID-19 pandemic to halt the transmission of the virus. This policy seems to have resulted in a structural increase in working from home and teleconferencing that will outlast the pandemic. However, the longer-term effects on travel behaviour are still unclear. Making use of panel data collected using the Netherlands Mobility Panel, this paper has two main aims. First, it analyses developments in working from home and teleconferencing since COVID-19. Second, it estimates the expected post-pandemic effects on travel behaviour. The results show that compared to before the pandemic, the average number of hours that people work from home has doubled and roughly two-thirds of respondents indicate that they teleconference more often. We estimate that structural, post-pandemic increases in working from home and teleconferencing will result in a negative effect on distances travelled by train (-3% to-9%), by bus, tram, and metro (-1% to-5%) and car (-1 to-5%). The estimated effect on the distance travelled by bicycle (-2% to 0%), and walking (0% to +1%) is smaller or even positive, due to people making more complementary trips for other purposes when working from home. When interpreting these results, we should keep in mind that due to various other factors, such as population growth, total travel demand will still grow in the near future. © 2023, TU Delft. All rights reserved.

A social-ecological model of working from home during COVID-19.

Working from Home (WFH) is emerging as a critical measure for reducing transport demand. Indeed, the COVID-19 pandemic has revealed that trip avoidance measures, especially WFH, could help address Sustainable Development Goal 11.2 (creating sustainable transport systems in cities) by decreasing commuter trips by private motor vehicles. This study aimed to explore and identify the attributes that supported WFH during the pandemic and construct a Social-Ecological Model (SEM) of WFH within the context of travel behaviour. We conducted in-depth interviews with 19 stakeholders from Melbourne, Australia and found that WFH during COVID-19 has fundamentally changed commuter travel behaviour. There was a consensus among participants that a hybrid-work model will emerge post-COVID-19 (e.g., working three days in the office and two days at home). We identified 21 attributes that influenced WFH and mapped these attributes across the five traditional SEM levels (intrapersonal, interpersonal, institutional, community and public policy). In addition, we proposed a sixth higher-order level: "global", to reflect the worldwide phenomena of COVID-19 and computer programs that also supported WFH. We found that WFH attributes were concentrated at the intrapersonal (individual) and institutional (workplace) levels. Indeed, workplaces are key to supporting WFH in the long-term. Whereby, workplace provision of laptops, office equipment, internet connection and flexible work policies enable WFH, and unsupportive organisational cultures and managers are potential barriers to WFH. This SEM of WFH benefits both researchers and practitioners by providing guidance of the key attributes required to sustain WFH behaviours post-COVID-19.

COVID-19 and suburban public transport in the conditions of the Czech Republic.

This article focuses on possible approaches to safe regional public transport during the COVID-19 pandemic. The purposes of the research are examination the conditions for ensuring safe transport and the impact on the planning of transport services. The result is an assessment of the operation of regional public transport, consisting of the possibility of maintaining safe distances in public transport. Authors work on suburban transport cases in selected regions of the Czech Republic (Prague and Moravian-Silesian Region). Census devices in public transport, periodical transport surveys, Google mobility reports and data on fare sales from regional transport were used as data sources. Emphasis is placed on a safe distance between commuters, this condition leads to lower occupancy of the vehicle while maintaining the capacity of the vehicles. The value of this new occupancy is determined for selected vehicles and the coefficient that represents the maximum occupancy level to ensure safe transport is established. The capacity of the connections is examined in the period before and during the COVID-19 pandemic. Compared to the period before COVID-19, the daily variation of passengers is expected to change significantly, leading to different occupancy rates during the day.

Flight reliability during periods of high uncertainty

In times of great uncertainty for the airline industry, travelers are in search of reliable itineraries now more than ever. With condensed airline schedules and less options, air travelers must rely on making flight connections and manage layover times to arrive at their final destination on time. In an era with readily available information, passengers expect accurate and transparent reliability information to help improve decision making for multi-leg itineraries. However, often for reliability in air travel, this information is incomplete or not useful. In this paper we utilize historical probability distributions of flight arrival and departure times using publicly available data to give an intuitive and predictive flight itinerary reliability metric. The COVID-19 pandemic significantly affected air-travel in the US and this uncertainty is still being felt with cancellations and delays due to staff shortages and reduced demand. Therefore, we extend the stochastic network model from our previous research to air travel during COVID-19 to see the effects on flight reliability. Using this model, we conduct computational experiments to evaluate air travel through multiple reliability metrics. We show that during periods of high uncertainty, predictive historical distributions of flight data considering recency and seasonal effects are less accurate given many cancellations and a reduced flight schedule. © 2022 Elsevier Ltd

The impact of COVID-19 on route-level changes in transit demand an analysis of five transit agencies in Florida, USA

This study examined the impacts of COVID-19 on changes in route-level transit demand across five transit agencies in the state of Florida. Data for 120 routes from five transit agencies were used to develop two-stage instrumental variable models. Data from January of 2019 to December of 2020 were used in the analysis. Routes that served a greater mix of land-uses experienced a smaller decline in ridership. The impacts of several other land-use variables were, however, not consistent across the five transit agencies. Fare suspension was estimated to have a positive impact on ridership. In contrast, occupancy reduction measures (to promote social distancing within the transit vehicle) had a very strong negative impact on demand. The magnitude of the negative impact of occupancy reduction was larger than the positive impacts of fare suspension. Extending this analysis to a larger set of routes across more agencies would be useful in enhancing the robustness of the findings from our models. Extending our analysis to include data from 2021 and later to capture the recovery phase is also an important direction for future work. © 2022

Estimating inter-regional mobility during disruption: Comparing and combining different data sources

A quantitative understanding of people's mobility patterns is crucial for many applications. However, it is difficult to accurately estimate mobility, in particular during disruption such as the onset of the COVID-19 pandemic. Here, we investigate the use of multiple sources of data from mobile phones, road traffic sensors, and companies such as Google and Facebook in modelling mobility patterns, with the aim of estimating mobility flows in Finland in early 2020, before and during the disruption induced by the pandemic. We find that the highest accuracy is provided by a model that combines a past baseline from mobile phone data with up-to-date road traffic data, followed by the radiation and gravity models similarly augmented with traffic data. Our results highlight the usefulness of publicly available road traffic data in mobility modelling and, in general, pave the way for a data fusion approach to estimating mobility flows. © 2022 The Author(s)

A review of air travel behavior and climate change

Air transport challenges the world's net-zero carbon ambitions. The sector has consistently grown and causes warming as a result of both CO2 and other, short-lived emissions. Two principal solutions have been proposed to reduce the contribution of aviation to climate change: innovations of technology and the development of interventions to trigger behavioral change. Technological innovations include new propulsion technologies and the use of sustainable aviation fuels. Behavioral change includes flight avoidance, substitution with other means of transport, the choice of efficient flight options, and carbon offsetting. This article focuses on behavior;it offers an overview of factors that lead to consumers traveling by air and discusses demand distribution complexities. The importance of price for air travel decisions is assessed, and evidence of travel "wants” are contrasted with "needs,” the latter investigated in light of the COVID-19 pandemic. The review of relevant scholarly work culminates in an action list enabling air travelers, policy makers, the aviation industry, researchers and society to meaningfully advance low-carbon air transport trajectories. This article is categorized under: Perceptions, Behavior, and Communication of Climate Change > Behavior Change and Responses The Carbon Economy and Climate Mitigation > Policies, Instruments, Lifestyles, Behavior. © 2022 The Authors. WIREs Climate Change published by Wiley Periodicals LLC.

The asymmetric response of travel demand to twitter-based uncertainty: A global empirical assessment

This paper examines the impact of two new Twitter-based uncertainty metrics on global travel demand, using linear and non-linear methods with daily data for the period 15 December 2020 and 20 March 2022. According to the linear results, an increase (decrease) in Twitter-based uncertainty affects travel demand negatively (positively). However, nonlinear estimations show that the relationship is asymmetrical, not symmetrical. Accordingly, travel demand is responding to the Twitter-based increase in uncertainty but is unaffected by reductions in uncertainty. Finally, it is pointed out that there may be asymmetries between tourism and uncertainty for future research.

Travel Demand Management Implications during the COVID-19 Pandemic: The Case Study of Tehran

The COVID-19 pandemic has had an unprecedented impact on the transportation sector, with changes expected to last for a long time. Following the reopening phases, increased use of private vehicles and continued avoidance of exposure to the infectious virus in public transportation exacerbated urban traffic and environmental problems. The paper aims to evaluate the impact of travel demand management strategies during the COVID-19 pandemic in Tehran, Iran. That city provided a unique case study because of its high COVID-19 contagion and death rates, traffic congestion, and lack of government restriction plans, which are common in developing countries. Four scenarios combining various travel demand management strategies were considered during the pandemic. The findings highlight the importance of considering the tradeoffs between different performance measures when selecting a suitable travel demand management strategy. Depending on the goals that decision-makers have set, the strategies may not be additive. While teleworking, e-learning, and rescheduling working hours all help reduce traffic congestion, the pricing strategy contributes significantly to meeting environmental and health goals. The findings also highlight the nonlinear pattern of change associated with each strategy.

Impact of perceptions and attitudes on air travel choices in the post-COVID-19 era: A cross-national analysis of stated preference data.

The COVID-19 pandemic and the consequent travel restrictions have had an unprecedented impact on the air travel market. However, a rigorous analysis of the potential role of safety perceptions and attitudes towards COVID-19 interventions on future air passenger choices has been lacking to date. To investigate this matter, 1469 individuals were interviewed between April and September 2020 in four multi-airport cities (London, New York City, Sao Paulo, Shanghai). The core analysis draws upon data from a set of stated preference (SP) experiments in which respondents were asked to reflect on a hypothetical air travel journey taking place when travel restrictions are lifted but there is still a risk of infection. The hybrid choice model results show that alongside traditional attributes, such as fare, duration and transfer, attitudinal and safety perception factors matter to air passengers when making future air travel choices. The cross-national analysis points towards differences in responses across the cities to stem from culturally-driven attitudes towards interpersonal distance and personal space. We also report the willingness to pay for travel attributes under the expected future conditions and discuss post-pandemic implications for the air travel sector, including video-conferencing as a substitute for air travel.

Who is returning to public transport for non-work trips after COVID-19? Evidence from older citizens' smart cards in the UK's second largest city region.

Harnessing a unique data source - longitudinal travel smartcard data linked to passenger demographics from 2019 to 2022 - we use methods of survival analysis to model the recovery of public transport patronage among 183,891 senior citizens resident in the West Midlands metropolitan region in the United Kingdom. Comparing pre and peri-pandemic patronage, we identify pronounced social and spatial inequalities in the speed of return to public transport. We find that male, younger and non-White passengers are more likely to return to public transport as soon as movement restrictions were lifted, whereas passengers from White ethnic background and affluent areas do not return to public transport within the first year after the outbreak. Pronounced social inequalities persist into the middle of 2021, and only thence they began to attenuate as part of a wider return to public transport among passengers post retirement age. In 2022, 80% of these passengers have returned to public transport but the frequency of use has remained lower than prior to the pandemic. We discuss implications for transport policy and planning.

Aircraft operators rebound but continue to struggle with delays

Reynolds discusses the rebound of aircraft operators and struggle with delays. After a 70% drop in aviation operations and a 90% reduction in passengers during the first half of 2020 due to the covid-19 pandemic, passenger demand by mid-2022 was close to pre-pandemic levels. However, flight numbers were still down slightly due to airline flight crew and air traffic control staffing challenges, which led to large numbers of delays, cancellations and other disruptions worldwide. Nearly a quarter of all US flights were delayed by an average of an hour each during June-August. There was an increased focus on climate impacts of aviation throughout the year following the publication of the US Aviation Climate Action Plan in Nov 2021, which details the key role that aircraft operations enhancements will continue to play in reducing climate impacts.

Air transportation encounters inflationary headwinds on its recovery from pandemic

Puranik et al discuss air transportation which encounters inflationary headwinds on its recovery from pandemic. A strong and growing global air travel demand, supported by the lifting of air travel restrictions in most countries, fueled the global airline industry's continued recovery this year from the impacts of covid-19. In June, the International Air Transport Association projected a total of 3.8 billion passengers for the year--83% of pre-pandemic levels--and a record high air cargo volume of more than 68 million tons, resulting in a global airline industry loss of $9.7 billion this year down from $42.1 billion in 2021. Only the North America region was expected to achieve profitability, with an estimated $8.8 billion profit. In October, member states of the International Civil Aviation Organization adopted the goal of achieving net-zero carbon emissions by 2050, a target that IATA member airlines had committed to in Oct 2021.

The Impact of COVID-19 on Route-Level Changes in Transit Demand An Analysis of Five Transit Agencies in Florida, USA

This study examined the impacts of COVID-19 on changes in route-level transit demand across five transit agencies in the state of Florida. Data for 120 routes from five transit agencies were used to develop two-stage instrumental variable models. Data from January of 2019 to December of 2020 were used in the analysis. Routes that served a greater mix of land-uses experienced a smaller decline in ridership. The impacts of several other land-use variables were, however, not consistent across the five transit agencies. Fare suspension was estimated to have a positive impact on ridership. In contrast, occupancy reduction measures (to promote social distancing within the transit vehicle) had a very strong negative impact on demand. The magnitude of the negative impact of occupancy reduction was larger than the positive impacts of fare suspension. Extending this analysis to a larger set of routes across more agencies would be useful in enhancing the robustness of the findings from our models. Extending our analysis to include data from 2021 and later to capture the recovery phase is also an important direction for future work.

Travel mode choice changes due to covid-19- case study of Yelahanka

India had repeated lockdowns from 2020 to 2022, however changes in commuters' travel mode preferences were noted both before and after COVID-19.. In total 950 participant response were created through Microsoft Forms and sent through different forms of social media like WhatsApp, LinkedIn and Facebook and 12% of the responses were recorded out the study area so it was excluded during the study purpose, the total responses were carried out for the study were 827 responses. The study also attempted to quantify the effects of influencing factors which can explain change in the commuter’s travel mode choice. The findings revealed that employment growth as seen after COVID-19 of 6% were the main purpose of travelling was to office, recreational and medical services of 19% after COVID-19. Mode choice model were created accordingly for the data analysed. The MLR Model created for Before Covid-19 data shows a good fit and the independent variables are significantly affecting the outcome variable and the Multiple Linear Regression Model created for Post-Covid-19 shows the independent variables are affecting significantly affecting the dependent variable i.e. Mode Choice. Therefore, Multiple Linear Regression Model is finalized and the collected data of the present study shows good model fit. The goal of the current study is to help policymakers better understand the dynamics of shifting travel demand and trip purpose before and after events like COVID-19.