Best–Worst Method for Modelling Mobility Choice after COVID-19: Evidence from Italy

The relation between barrier-free environment perception and campus commuting satisfaction

Introduction

The COVID-19 pandemic, which began in the last quarter of 2019, has had a significant impact on urban transportation. With increasing demand for urban transport, the internal roads and public spaces of university campuses play an important role in facilitating commuting and communication between various functional zones. While considerable research has been conducted on route planning, pedestrian-vehicle segregation, and safety management in the internal transportation environment of university campuses, empirical investigations exploring barrier-free inclusive campus environment design and the subjective evaluation of road and public space users in the aftermath of the COVID-19 pandemic are lacking. Recent developments in travel behavior models and positive psychology have led to an increased focus on the correlation among subjective perceptions, attitudes, emotions, and commuting satisfaction in urban transportation and planning design.

Methods

To elucidate this relationship, a study was conducted on the new campus of Central South University in Changsha, Hunan Province, China. Using 312 valid samples, a structural equation model was constructed to analyse the relationship between commuting satisfaction and the barrier-free environment perception of university students regarding the internal transportation environment of the campus.

Results

The results revealed that individuals' instantaneous barrier-free environment perceptions and long-term established positive emotions had a significant positive effect on commuting satisfaction. Furthermore, positive emotions were found to mediate the relationship between commuting attitudes induced by COVID-19, barrier-free environment perceptions, and commuting satisfaction.

Discussion

The results of this study provide a theoretical basis for the necessity of accessibility design in the post-COVID era. In addition, this study considers the perspective of users to provide ideas for the planning and construction of barrier-free campus environments that are based on convenient and inclusive design.

Supply chain optimization for environmental sustainability and economic growth

As the globe strives to solve severe environmental challenges, the concept of a low-carbon economy that prioritizes low energy use, little pollution, and sustainable development is gaining support. The supply chain management industry is not safe from the possibilities and threats posed by this new development. In light of the emerging norm, it is imperative that all supply chain links be economically and ecologically sustainable. For conventional businesses, ensuring environmental advantages and practicing the issue of equitably dividing supply network node profits is exacerbated by green supply chain management. This paper was prompted by the increasing need for information on green supply chain management (GSCM). GSCM is based on the idea of incorporating ecological considerations into traditional SCM practices. Therefore, GSCM is vital in shaping the cumulative environmental effect of businesses engaged in supply chain operations. To assess environmental sustainability requirements, we provide a best-worst method (BWM), a subset of China-based sectors in order to fill this void. The BWM was used to evaluate and quantify the impact of a variety of industrial operations and criteria on environmental quality. To make sure this approach is effective and reliable, we polled 34 experts for their input on which indications from our preliminary literature analysis would be most useful. This study's findings, supported by a sensitivity analysis, indicated stated "waste management" was the single most important indication for China-area businesses to achieve environmental sustainability. The results of this study provide industry managers, decision-makers, and practitioners with the information they need to choose areas of focus during the implementation phase that will have the most impact on promoting social sustainability in their organizational supply chain and moving toward sustainable growth.

Leisure mobility changes during the COVID-19 pandemic - An analysis of survey and mobile phone data in Sweden

The COVID-19 pandemic affected travelling in general, and the leisure mobility and the spatial distribution of travellers in particular. In most parts of the world, both domestic and international travel has been replaced by restrictive policies and recommendations on mobility. A modal shift from public transport towards private cars and micro-mobility was also observed. This study seeks to trace the implications of the COVID-19 pandemic for leisure mobility. We use a unique Swedish database containing daily mobility patterns of pseudonymised mobile phone users, combined with a survey on vacation transport behaviour. By contrasting mobility patterns for selected holiday days during the unaffected summer of 2019 with corresponding dates in 2020 and 2021, we are able to model and detect the pandemic effects on tourism and recreational mobility. Moreover, by identifying the general mobility patterns, we analyse whether and how the transport mode has changed. Using data on the spatial distribution of recreational amenities, we identify locations that were favoured during the pandemic. In Sweden, even though the pandemic decreased in spread and severity during the summers, most travel restrictions were still enforced, international vacations uncommon, and larger vacation spots, such as amusement parks and cultural institutions, were closed down. Swedish vacation homes in remote or rural areas were quickly booked. This change in recreational behaviour, where less populated areas, open air and nature recreation were favoured over indoor or crowded urban cultural activities, was more substantial in 2021 than in 2020. This result shows how policies can effectively be developed, so that Swedes respond properly to recommendations and adjust their vacation plans.

Systematic literature review on impacts of COVID-19 pandemic and corresponding measures on mobility

The unprecedented COVID-19 outbreak has significantly influenced our daily life, and COVID-19's spread is inevitably associated with human mobility. Given the pandemic's severity and extent of spread, a timely and comprehensive synthesis of the current state of research is needed to understand the pandemic's impact on human mobility and corresponding government measures. This study examined the relevant literature published to the present (March 2023), identified research trends, and conducted a systematic review of evidence regarding transport's response to COVID-19. We identified key research agendas and synthesized the results, examining: (1) mobility changes by transport modes analyzed regardless of government policy implementation, using empirical data and survey data; (2) the effect of diverse government interventions to reduce mobility and limit COVID-19 spread, and controversial issues on travel restriction policy effects; and (3) future research issues. The findings showed a strong relationship between the pandemic and mobility, with significant impacts on decreased overall mobility, a remarkable drop in transit ridership, changes in travel behavior, and improved traffic safety. Government implemented various non-pharmaceutical countermeasures, such as city lockdowns, travel restrictions, and social distancing. Many studies showed such interventions were effective. However, some researchers reported inconsistent outcomes. This review provides urban and transport planners with valuable insights to facilitate better preparation for future health emergencies that affect transportation.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11116-023-10392-2.

A model for green-resilient supplier selection: fuzzy best-worst multi-criteria decision-making method and its applications

Supplier selection is regarded as the primary goal of supply chain management (SCM) because it affects its performance, productivity, pleasure, flexibility, and system speed in lockdown. A new method is proposed based on a multi-stage fuzzy sustainable supplier index (FSSI). Experts can use the triple bottom line (TBL) criteria to select the best supplier. In addition, the worst method is proposed based on trapezoidal membership and fuzzy membership functions, which can cover uncertainties and ambiguous environments. Because it collects the related criteria and sub-criteria and uses a direct fuzzy methodology, this research has impacted the SCM literature because it helps solve previous expert methods' computational difficulties. In addition, an ordered mean integration representation method has been implemented to prioritize the selection of the best supplier (SS) based on the sustainability performance of the best supplier, which improves the selection accuracy compared to the previous ranking method. This study can be used as a benchmark to determine which supplier is the best in sustainability. To provide the superiority and broad applicability of the proposed model, a practical case study was completed. On the other hand, the COVID-19 pandemic harms productivity, company performance, and selecting the best suppliers based on sustainability performance. The lockdown situation caused by the COVID-19 pandemic hurts company performance and management.

Modeling the COVID-19 Travel Choices in Colombia and India: A Hybrid Multiple Discrete-Continuous Nested Extreme Value Approach

The COVID-19 pandemic has affected many daily activities, primarily as a result of the perceived contagion risk and government restrictions to mitigate the spread of the virus. To this end, drastic changes in the trip choices for commuting to work have been reported and studied, mostly through descriptive analysis. On the other hand, modeling-based research that can simultaneously understand both changes in mode choice and its frequency at an individual level has not been much used in existing studies. As such, this study aims to understand the changes in mode-choice preference and the frequency of trips, comparing pre-COVID with during-COVID scenarios, in two different countries of the Global South: Colombia and India. A hybrid multiple discrete-continuous nested extreme value model was implemented using the data obtained from online surveys in Colombia and India during the early COVID-19 period of March and April 2020. This study found that, in both countries, utility related to active modes (more used) and public transportation (less used) changed during the pandemic. In addition, this study highlights potential risks in likely unsustainable futures where there may be increased use of private vehicles such as cars and motorcycles, in both countries. It was also identified that perceptions toward government responses had a significant impact on the choices in Colombia, though this was not the case in India. These results may help decision makers focus on public policies to encourage sustainable transportation by avoiding the detrimental long-term behavioral changes resulting from the COVID-19 pandemic.

Modeling the resilience of urban mobility when exposed to the COVID-19 pandemic: A qualitative system dynamics approach

In December 2019, coronavirus disease (COVID-19) was detected in Wuhan, China. Due to the rapid spread of the disease, containment measures were adopted, which caused unprecedent shifts in individual mobility. Although some studies explored the impacts of the COVID-19 pandemic on travel patterns and resilience of transport systems based on different analysis techniques, there is a lack of studies addressing the impacts of the pandemic on the sustainability and resilience of urban mobility systems using in-depth and holistic methods, such as system dynamics. This research aims to characterize the dynamics present in urban mobility systems when exposed to pandemics and analyze the changes needed for systems to increase their resilience to pandemics using qualitative system dynamics modeling. The framework comprises the characterization of cause-and-effect relationships and the creation of systems' causal loop diagrams (CLD) in their basic state of functionality, when affected by pandemics, and still operating owing to its resilience. Our findings indicated that the CLD of a resilient system is driven by strategic preparedness and response plans, as well as research and development, which balance the spread of the pandemic and increase support on technological strengths and the activities performed from home.

Interval valued intuitionistic fuzzy analytic hierarchy process-based green supply chain resilience evaluation methodology in post COVID-19 era

Supply chain organizations should calmly and cautiously take the most accurate and sustainable decisions quickly and put them into practice. It is obvious that traditional time series-based demand and supply planning approaches are insufficient to meet current business needs due to factors such as sharp changes in market and commercial dynamics, pandemics, and natural disasters on the management of green supply chains, especially these days. In the near future, there will be a need for more resilient supply chains with a flexible business models that are not affected by sudden changes and that can make sustainable decisions dynamically. Additionally, all stakeholders must act with a green supply chain approach to conduct production and service activities in a way that causes the least damage to nature. Companies must build more resilient supply chains by considering environmental sensitivities to compete in the market and ensure their continuity. In this context, the green supply chains should be evaluated according to their resilience. For this purpose, Supply Chain Operations Reference (SCOR) model is extended with novel performance attributes to evaluate resilience of green supply chains in this study. The SCOR-embedded novel green supply chain resilience evaluation model is structured as a three-level performance attribute hierarchical structure. Then, the model is handled as a multi-criteria decision-making problem to determine importance of the performance attributes. Best Worst Method integrated Interval Valued Intuitionistic Fuzzy Analytic Hierarchy Process is used to determine the importance of performance attributes. Most important performance attributes are determined in each level of hierarchy. According to results, organizational factors play a key role to build more resilient supply chains. Especially, integrated systems are required for supply chain resilience.

Space and social distancing in managing and preventing COVID-19 community spread: An overview

The spread of COVID-19 at a large scale and at a rapid pace indicates the lack of social distancing measures at multiple levels. The individuals are not to be blamed, nor should we assume the early measures were ineffective or not implemented. It is all down to the multiplicity of transmission factors that made the situation more complicated than initially anticipated. Therefore, in facing the COVID-19 pandemic, this overview paper discusses the importance of space in social distancing measures. The methods used to investigate this study are literature review and case study. Many scholarly works have already provided us with evidence-based models that suggest the influential role of social distancing measures in preventing COVID-19 community spread. To further elaborate on this important topic, the aim here is to look at the role of space not only at the individual level but at larger scales of communities, cities, regions, etc. The analysis helps better management of cities during the pandemics such as COVID-19. By reflecting on some of the ongoing research on social distancing, the study concludes with the role of space at multiple scales and how it is central to the practice of social distancing. We need to be more reflective and responsive to achieve earlier control and containment of the disease and the outbreak at the macro level.

Human Mobility Restrictions and COVID-19 Infection Rates: Analysis of Mobility Data and Coronavirus Spread in Poland and Portugal

This study examines the possibility of correlation between the data on human mobility restrictions and the COVID-19 infection rates in two European countries: Poland and Portugal. The aim of this study is to verify the correlation and causation between mobility changes and the infection spread as well as to investigate the impact of the introduced restrictions on changes in human mobility. The data were obtained from Google Community Mobility Reports, Apple Mobility Trends Reports, and The Humanitarian Data Exchange along with other reports published online. All the data were organized in one dataset, and three groups of variables were distinguished: restrictions, mobility, and intensity of the disease. The causal-comparative research design method is used for this study. The results show that in both countries the state restrictions reduced human mobility, with the strongest impact in places related to retail and recreation, grocery, pharmacy, and transit stations. At the same time, the data show that the increase in restrictions had strong positive correlation with stays in residential places both in Poland and Portugal.

Characterising public transport shifting to active and private modes in South American capitals during the COVID-19 pandemic

During the year 2020, the COVID-19 pandemic affected mobility around the world, significantly reducing the number of trips by public transport. In this paper, we study its impact in five South American capitals (i.e., Bogotá, Buenos Aires, Lima, Quito and Santiago). A decline in public transport patronage could be very bad news for these cities in the long term, particularly if users change to less sustainable modes, such as cars or motorbikes. Notwithstanding, it could be even beneficial if users selected more sustainable modes, such as active transport (e.g., bicycles and walking). To better understand this phenomenon in the short term, we conducted surveys in these five cities looking for the main explanation for changes from public transport to active and private modes in terms of user perceptions, activity patterns and sociodemographic information. To forecast people's mode shifts in each city, we integrated both objective and subjective information collected in this study using a SEM-MIMIC model. We found five latent variables (i.e., COVID-19 impact, Entities response, Health risk, Life related activities comfort and Subjective well-being), two COVID-19 related attributes (i.e., new cases and deaths), two trip attributes (i.e., cost savings and time), and six socio-demographic attributes (i.e., age, civil status, household characteristics, income level, occupation and gender) influencing the shift from public transport to other modes. Furthermore, both the number of cases and the number of deaths caused by COVID-19 increased the probability of moving from public transport to other modes but, in general, we found a smaller probability of moving to active modes than to private modes. The paper proposes a novel way for understanding geographical and contextual similarities in the pandemic scenario for these metropolises from a transportation perspective.

Changes to household food shopping practices during the COVID-19 restrictions: Evidence from the East of England

Measures to control the spread of COVID-19 have changed the way we shop for food and interact with food environments. This qualitative study explored food shopping practices in the East of England, a large diverse region including coastal, urban and rural settings. In 2020/2021 we interviewed 38 people living in the region and 27 professionals and volunteers providing local support around dietary health. Participants reported disruption to supermarket shopping routines; moving to online shopping; and increased reliance on local stores. COVID-19 has impacted disproportionately upon lower-income households and neighbourhoods. The longer-term implications for dietary health inequalities must be investigated.

New Habits of Travellers Deriving from COVID-19 Pandemic: A Survey in Ports and Airports of the Adriatic Region

The aim of this paper is to analyse the variations in the habits and the modes of transport of travellers departing from airports and ports during the COVID-19 outbreak. In the second year of the pandemic (i.e., from August to October 2021), travellers were invited to take part in an anonymous online survey at the terminal buildings of nine Italian and Croatian airports and ports located in the Adriatic region. Around 73% of respondents used public transport when travelling in the pre-COVID-19 period, whereas the corresponding share of respondents in the COVID-19 period was less than 50% and approximately 56% in the post-COVID-19 future. The main reason for not travelling by public transport was related to personal or sanitary reasons in the time of COVID-19. During the pandemic, around 39% of travellers preferred their own vehicle to public transport for moving to/from the airports and ports because of safety and sanitary reasons. With the pandemic, health was the main reason behind daily choices for up to 49% of the respondents. Moreover, a similar share of travellers considered health when choosing the transportation mode during and after the pandemic.

Exploring mobility pattern changes between before, during and after COVID-19 lockdown periods for young adults

The paper aims to investigate changes in travel behavior due to COVID-19 focusing in one of the most active social groups in Greece. A questionnaire survey was conducted and 306 young adults (age 18-34 years) living in various Greek cities responded. The survey collected information about travel-related preferences before, during and after the 1st lockdown and during the 2nd lockdown of the COVID-19 pandemic in Greece. City attributes of the respondent's residency location before and after the 1st lockdown were collected. The data are analyzed descriptively and through statistical modelling techniques. During the 1st lockdown an important increase in physical exercise frequency was observed, but this increase was not permanent. The COVID-19 pandemic resulted in essential reductions in the frequency of public transport use and in an increase of walking frequency. The public transport use reduction was mainly attributed to people that had access to a private car and after the 1st lockdown moved to a smaller city. On the other hand, the changes in walking frequency are closely linked to the city's attributes. Useful policy implications are being derived about how the pandemic can assist in promoting sustainable urban mobility goals.

Rise of multiattribute decision-making in combating COVID-19: A systematic review of the state-of-the-art literature

Considering the coronavirus disease 2019 (COVID-19) pandemic, the government and health sectors are incapable of making fast and reliable decisions, particularly given the various effects of decisions on different contexts or countries across multiple sectors. Therefore, leaders often seek decision support approaches to assist them in such scenarios. The most common decision support approach used in this regard is multiattribute decision-making (MADM). MADM can assist in enforcing the most ideal decision in the best way possible when fed with the appropriate evaluation criteria and aspects. MADM also has been of great aid to practitioners during the COVID-19 pandemic. Moreover, MADM shows resilience in mitigating consequences in health sectors and other fields. Therefore, this study aims to analyse the rise of MADM techniques in combating COVID-19 by presenting a systematic literature review of the state-of-the-art COVID-19 applications. Articles on related topics were searched in four major databases, namely, Web of Science, IEEE Xplore, ScienceDirect, and Scopus, from the beginning of the pandemic in 2019 to April 2021. Articles were selected on the basis of the inclusion and exclusion criteria for the identified systematic review protocol, and a total of 51 articles were obtained after screening and filtering. All these articles were formed into a coherent taxonomy to describe the corresponding current standpoints in the literature. This taxonomy was drawn on the basis of four major categories, namely, medical (n = 30), social (n = 4), economic (n = 13) and technological (n = 4). Deep analysis for each category was performed in terms of several aspects, including issues and challenges encountered, contributions, data set, evaluation criteria, MADM techniques, evaluation and validation and bibliography analysis. This study emphasised the current standpoint and opportunities for MADM in the midst of the COVID-19 pandemic and promoted additional efforts towards understanding and providing new potential future directions to fulfil the needs of this study field.

Will the Effects of COVID-19 on Commuting and Daily Activities of the University Students Be Maintained? Evidence from a Small Town in Sicily

As many studies have already shown, the COVID-19 pandemic has had a great impact on the daily routines of people all over the world. University students form one of the most affected groups of people, since they have had to interrupt many of the activities that they usually perform, and have also had to get used to a new way of learning (e-learning). An important question that now arises is whether the changes that were identified within the pandemic period are to be maintained when the risk of being infected is eliminated. To this end, 537 university students of the Kore University of Enna, Italy, were surveyed. Their responses are analyzed descriptively, and an ordinal regression model is being developed to shed more light on the likelihood of retaining changes related with to transport mode choice. The results show that the likelihood of retaining all the changes when commuting and during daily activities is very high, demonstrating such willingness from the participants. Moreover, it has been shown that public transport has increased the probability of people being negatively affected by the pandemic in the long-term, and opportunities appear for increasing the modal share of active modes.

The Effect of the COVID-19 Pandemic on Traffic Flow Characteristics, Emissions Production and Fuel Consumption at a Selected Intersection in Slovakia

The surveyof traffic intensity is used to obtain information on the number of vehicles on roads during the day. Subsequently, it is possible to derive from this the daily, weekly, and other road traffic intensity information. This survey represents the basis for the calculation of the annual average daily traffic volume and the basic characteristics of traffic flow. The COVID-19 pandemic has caused extensive economic and social damage around the world. These damages have also affected traffic. Changes in traffic behavior have mainly affected the reduction in traffic intensity on road networks. Thanks to the reduction in the demand for transport, there has also been a significant reduction in traffic delays, fuel consumption and emissions. An examination of changes in traffic intensity took place at a selected intersection in 2019, 2020 and 2021. This paper describes the effects of reducing the traffic intensity, fuel consumption and emissions obtained by microsimulation. The results obtained confirmed the reduction in traffic, which also contributed to a significant reduction in vehicle delays.

Assessment of Urban Mobility via a Pressure-State-Response (PSR) Model with the IVIF-AHP and FCE Methods: A Case Study of Beijing, China

Urban transportation issues continue to emerge and evolve as a result of rapid urbanization, and the systematic and scientific assessment of urban mobility is becoming increasingly essential. In this work, a Pressure-State-Response (PSR) model with 25 indicators was established to reflect the status of urban mobility. Then, the importance of indicators was determined with the interval-valued intuitionistic fuzzy analytic hierarchy process (IVIF-AHP) method, and the fuzzy comprehensive evaluation (FCE) method was applied to assess the overall status of urban mobility. The validity of the proposed model was demonstrated using the mobility system of Beijing as a case study, and the pressure, state, and response scores were calculated. The proposed assessment model can help to improve urban transportation monitoring and can also provide a scientific foundation for future urban transportation policymaking, planning, and traffic management, thereby further ensuring the sustainable development of urban transportation systems.

Transportation Planning, Mobility Habits and Sustainable Development in the Era of COVID-19 Pandemic

Starting from December 2019, the world has faced an unprecedented health crisis caused by the new coronavirus (COVID-19) due to SARS-CoV-2 [...]

Role of latent factors and public policies in travel decisions under COVID-19 pandemic: Findings of a hybrid choice model

Policy measures to control the spread of COVID-19 imposed by different countries have a devastating impact on people's travel behaviors. Differing from the normal situation where general concerns on travel time and cost determine the travel choices, the uncertainty underlying behavior change in the case of a pandemic might be largely attributed to the latent aspects, i.e., social responsibility, risk perception, attitudes, which could diminish the effects of main attributes on travel decisions. Therefore, this paper examines the effects of COVID-19 related policies on individuals' travel choices influenced by the latent aspects. A stated choice experiment was designed to collect people's responses under policy measures to various transportation modes. Results of a hybrid choice model show that COVID-19 related policies significantly affect individuals' transportation mode choice decisions during pandemic situations. The attributes, like travel time and travel cost, which significantly impact travel behavior in normal situations, become less relevant. Moreover, the travel preferences during the pandemic are significantly associated with latent factors of social responsibility, fear of infection, perceived risk, and travel anxiety. In general, public transportation is identified as an insecure alternative compared with other private modes, and people who are more socially responsible tend to travel less during the pandemic. Outcomes of this study could be of value to policymakers and public health emergencies, e.g., government authorities to utilize such knowledge in providing social support for these COVID-19 countermeasures and designing customized policies for specific population groups.

Household mobility in food purchasing during COVID-19 lockdown: Evidence from Torino, Italy

During the first wave of COVID-19, lockdown restrictions limited people's movements mainly to food purchasing. Using survey data collected in Torino, Italy, from university students, this study analyses the lockdown's impact on the transportation means used for purchasing food compared to the pre-lockdown period. Food store businesses were not limited by the restrictions and people had to purchase food; however, national and local rules limited citizens' movements, potentially leading to a different choices of transportation means than before the pandemic. The results show that both the lockdown and, perhaps, the fear of contagion, moved the preferences of people from public and shared means to foot and private vehicles. These findings can help in rethinking how transportation is organised in an urban environment, such as that in Torino. Ensuring the safety of public and shared transportation may help sustain mobility during health emergencies.

Multi-criteria decision-making for coronavirus disease 2019 applications: a theoretical analysis review

The influence of the ongoing COVID-19 pandemic that is being felt in all spheres of our lives and has a remarkable effect on global health care delivery occurs amongst the ongoing global health crisis of patients and the required services. From the time of the first detection of infection amongst the public, researchers investigated various applications in the fight against the COVID-19 outbreak and outlined the crucial roles of different research areas in this unprecedented battle. In the context of existing studies in the literature surrounding COVID-19, related to medical treatment decisions, the dimensions of context addressed in previous multidisciplinary studies reveal the lack of appropriate decision mechanisms during the COVID-19 outbreak. Multiple criteria decision making (MCDM) has been applied widely in our daily lives in various ways with numerous successful stories to help analyse complex decisions and provide an accurate decision process. The rise of MCDM in combating COVID-19 from a theoretical perspective view needs further investigation to meet the important characteristic points that match integrating MCDM and COVID-19. To this end, a comprehensive review and an analysis of these multidisciplinary fields, carried out by different MCDM theories concerning COVID19 in complex case studies, are provided. Research directions on exploring the potentials of MCDM and enhancing its capabilities and power through two directions (i.e. development and evaluation) in COVID-19 are thoroughly discussed. In addition, Bibliometrics has been analysed, visualization and interpretation based on the evaluation and development category using R-tool involves; annual scientific production, country scientific production, Wordcloud, factor analysis in bibliographic, and country collaboration map. Furthermore, 8 characteristic points that go through the analysis based on new tables of information are highlighted and discussed to cover several important facts and percentages associated with standardising the evaluation criteria, MCDM theory in ranking alternatives and weighting criteria, operators used with the MCDM methods, normalisation types for the data used, MCDM theory contexts, selected experts ways, validation scheme for effective MCDM theory and the challenges of MCDM theory used in COVID-19 studies. Accordingly, a recommended MCDM theory solution is presented through three distinct phases as a future direction in COVID19 studies. Key phases of this methodology include the Fuzzy Delphi method for unifying criteria and establishing importance level, Fuzzy weighted Zero Inconsistency for weighting to mitigate the shortcomings of the previous weighting techniques and the MCDM approach by the name Fuzzy Decision by Opinion Score method for prioritising alternatives and providing a unique ranking solution. This study will provide MCDM researchers and the wider community an overview of the current status of MCDM evaluation and development methods and motivate researchers in harnessing MCDM potentials in tackling an accurate decision for different fields against COVID-19.

Impact of Teleworking on Travel Behaviour During the COVID-19 Era: The Case Of Sicily, Italy

As a result of the travel restrictions and governmental guidelines imposed on many countries during the COVID-19 crisis, a significant increase in teleworking has been observed. New policies led to major changes in the lifestyle of millions of citizens all around the world and will permanently affect their travel behaviour. This paper aims to investigate and analyse the impact of teleworking on transportation habits, focusing on walking and commuting before and during the pandemic. Data regarding the walking frequency fluctuations due to teleworking were collected through structured questionnaires in Sicily, Italy. Most respondents seem to believe that it can be a factor leading to a decrease in their walking trips and to a change in their associated walking habits and behaviour. In this study, the rebound effects of telecommuting with respect to vehicle usage are taken into consideration. Although, it can result in a smaller number of trips weekly, the net amount of distance travelled per person can be larger, as employees are more willing to commute farther considering they will not commute as often. However, for longer distances, people tend to use trains since it allows working while commuting. This can result in reduced traffic, especially at peak times and consequently have a positive social and environmental impact, less stress and less air and noise pollution from private vehicles. An increasing number of companies is announcing the decision of pivoting to teleworking even after the pandemic is over. Policy makers and urban planners can use telecommuting as a tool that contributes to relieving traffic and seek ways to introduce a more sustainable future of work and mobility in the post-pandemic world.

Transport disrupted - Substituting public transport by bike or car under Covid 19

The Covid 19 pandemic has caused dramatic disruptions in the public transport sector that has seen a stark downturn in many cities across the globe, calling into question previous efforts to reduce air pollution and CO2 emissions by expanding this sector. Especially, the current surge of individual car use is worrying and the question remains which users might be able and willing to substitute public transport by cycling. This effect is interesting to study for the case of Hanover Region, because of the well-developed biking infrastructure that makes biking a viable alternative to individual car use. In this paper, we analyze survey data from June 2020 on the use of transportation modes before and during the pandemic in the Hanover Region. We ask if and how the over 4.000 participants substitute public transport and what characterizes those who chose biking over individual car use. We use multivariate regression models and find evidence that Stadtbahn (local light rail) and bus are substituted by bike, car and working from home, while train use is not significantly replaced by car and seems to be positively related to bike use. The data also shows that women have a higher level of fear of infection than men have during public transport use and therefore reduce public transport use more. Moreover, income displays a positive effect on increased car use while cycling is independent of socio-economic indicators but instead driven by the eco-consciousness of users. Surprisingly, we find that car use was increased in particular by residents of Hanover city, while it was decreased by residents of less densely populated urban areas in the region.

Implications of COVID-19 lockdowns on surface passenger mobility and related CO2 emission changes in Europe

The coronavirus pandemic has severely affected our daily lives, with direct consequences on passenger transport. This in turn has strongly impacted the energy demand of the transport sector and associated CO2 emissions. We analyse near real-time passenger mobility and related emission trends in Europe between 21 January and 21 September 2020. We compiled a dataset of country-, sector- and lockdown- specific values, representing daily activity changes in private, public, and active passenger transport. In the aggregate, surface passenger transport emissions fell by 11.2% corresponding to 40.3 MtCO2 in Europe. This decline was predominantly due to the reduction of private passenger transport in five European countries (France, Germany, Italy, Spain, and the UK). During the first lockdown in April 2020, CO2 emissions from surface passenger transport declined by 50% in Europe, resulting in a 7.1% reduction in total CO2 emissions. After April 2020, private passenger travel recovered rapidly, while public passenger flows remained low. Solely prompted by the private sector, a rebound in total emissions and surface passenger transport emissions of 1.5% and 10.7%, respectively, was estimated at the end of the study period. The resulting situation of increased private and decreased public passenger transport is in contradiction to major climate goals, and without reversing these trends, emission reductions, as stated in the European Green Deal are unlikely to be achieved. Our study provides an analysis based on a detailed and timely set of data of surface passenger transport and points to options to grasp the momentum for innovative changes in passenger mobility.

Public transport versus solo travel mode choices during the COVID-19 pandemic: Self-reported evidence from a developing country

A sharp decline in public transport use has been reported worldwide since the outbreak of the COVID-19 pandemic. As the virus spreads through close contacts, particularly in closed environments, public transport vehicles could be considered as hotspots for its transmission. However, public transport operations cannot be entirely stopped as many people in developing countries rely on them for their travel needs. This study aims to provide insights into people's travel mode choices during the COVID-19 pandemic. Data, i.e., 1,516 complete survey responses, were obtained through a questionnaire that was conducted in Lahore, Pakistan. A binary logistic model was developed using the collected data to model the likelihood of choosing solo or public transport modes during COVID-19. The results explained that the respondents preferred solo modes more than the public transport modes during the pandemic. Gender, income, education, profession, trip frequency, car ownership, motorbike ownership, and an underlying factor that was defined as “safety precautions” were found to be significant predictors of the public transport choice relative to solo modes. Females tend to choose public transport modes relative to solo modes as compared to males. Private vehicle (car or motorbike) owners were less likely to use public modes relative to solo modes when compared to those who do not own private vehicles. The outcomes of this study could be important for the government authorities, policymakers, and transport operators to understand the public transport use in developing countries during pandemics. Such information will be useful to devise regulations and preventive measures to control infectious diseases associated with public transport use, particularly in developing countries, where private transport options are limited.

Application-Based COVID-19 Micro-Mobility Solution for Safe and Smart Navigation in Pandemics

Short distance travel and commute being inevitable, safe route planning in pandemics for micro-mobility, i.e., cycling and walking, is extremely important for the safety of oneself and others. Hence, we propose an application-based solution using COVID-19 occurrence data and a multi-criteria route planning technique for cyclists and pedestrians. This study aims at objectively determining the routes based on various criteria on COVID-19 safety of a given route while keeping the user away from potential COVID-19 transmission spots. The vulnerable spots include places such as a hospital or medical zones, contained residential areas, and roads with a high connectivity and influx of people. The proposed algorithm returns a multi-criteria route modeled on COVID-19-modified parameters of micro-mobility and betweenness centrality considering COVID-19 avoidance as well as the shortest available safe route for user ease and shortened time of outside environment exposure. We verified our routing algorithm in a part of Delhi, India, by visualizing containment zones and medical establishments. The results with COVID-19 data analysis and route planning suggest a safer route in the context of the coronavirus outbreak as compared to normal navigation and on average route extension is within 8%–12%. Moreover, for further advancement and post-COVID-19 era, we discuss the need for adding open data policy and the spatial system architecture for data usage, as a part of a pandemic strategy. The study contributes new micro-mobility parameters adapted for COVID-19 and policy guidelines based on aggregated contact tracing data analysis maintaining privacy, security, and anonymity.

Promoting Sustainability: Wastewater Treatment Plants as a Source of Biomethane in Regions Far from a High-Pressure Grid. A Real Portuguese Case Study

Wastewater treatment plants (WWTP) located in regions far from a high-pressure grid can produce renewable biomethane, which can partially substitute the natural gas locally consumed. However, the economic viability of implementing biomethane plants in WWTP has to be guaranteed. This paper uses the discount cash flow method to analyze the economic viability of producing biomethane in a WWTP located in Évora (Portugal). The results show that, under the current conditions, it is unprofitable to produce biomethane in this WWTP. Since selling the CO2 separated from biogas may result in an additional income, this option was also considered. In this case, a price of 46 EUR/t CO2 has to be paid to make the project viable. Finally, the impact of potential government incentives in the form of feed-in premia was investigated. Without selling CO2, the project would only be profitable for feed-in premia above 55.5 EUR/MWh. If all the CO2 produced was sold at 30 EUR/t CO2, a premium price of 20 EUR/MWh would make the project profitable. This study shows that the economic attractiveness of producing biomethane in small WWTP is only secured through sufficient financial incentives, which are vital for developing the biomethane market with all its associated advantages.

An Integrated Multi Criteria Decision Making Model for Evaluating Park-and-Ride Facility Location Issue: A Case Study for Cuenca City in Ecuador

A park-and-ride (P&R) system is a set of facilities where private vehicle users can transfer to public transport to continue their journey. The main advantage of the system is decreasing the congestion in the central business district. This paper aims to analyze the most significant factors related to a Park-and-Ride facility location by adopting a combined model of Analytic Hierarchy Process (AHP) and Best Worst Method (BWM). The integrated model is applicable for complex problems, which can be structured as a hierarchy with at least one 5 × 5 pairwise comparison matrix (PCM) (or bigger). Applying AHP for at least 5 × 5 PCM may generate inconsistent matrices, which may cause a loss of reliable information. As a solution for this gap, we conducted BWM, which generates more consistent comparisons compared to the AHP approach. Moreover, the model requires fewer comparisons compared to the classic AHP approach. That is the main reason of adopting the AHP-BWM model to evaluate Park-and-Ride facility location factors for a designed two-level hierarchical structure. As a case study, a real-world complex decision-making process was selected to evaluate the Park-and-Ride facility location problem in Cuenca city, Ecuador. The result shows that the application of multi-criteria methods becomes a planning tool for experts when designing a P&R system.

Measuring changes in travel behavior pattern due to COVID-19 in a developing country: A case study of Pakistan

Travel behavior has been affected around the world since the eruption of corona virus disease (COVID-19). Several industries including transportation industry have been hard hit by the pandemic. As the virus is transmitted through close contact with infected people, number of outdoor trips has reduced causing roads and public transport to be less crowded than before. In order to develop transport-related policies for the post COVID-19 world, it is necessary to explore how the pandemic has affected the travel behavior pattern. This study explored the influence of the COVID-19 pandemic on travel pattern and mode preferences in Pakistan using a questionnaire survey. The results showed significant shift in primary traveling purpose from work and studying to shopping during the pandemic. Number of trips performed for non-commuting purposes were also significantly different before and during the pandemic. A significant modal shift from motorbike to non-motorized modes of travel was found for distances less than 5 km. For longer distances, people shifted from public transport to private car. These findings suggest that past policies regarding different modes may be revisited in the post COVID-19 world. The statistical tests performed on the factors affecting mode choices indicated that the respondents put more priority on pandemic-related items such as infection concern, social distance, hand sanitizers' availability, and cleanliness, etc., during the pandemic. The findings of this study will certainly help in shaping up the policies for the post COVID-19 world especially in the developing countries.

Human mobility behavior in COVID-19: A systematic literature review and bibliometric analysis

This article maps the scientific literature in human mobility behavior in the context of the current pandemic. Through bibliometrics, we analyze the content of published scientific studies indexed on the Web of Science and Scopus during 2020. This enables us the detection of current hotspots and future directions of research. After a co-occurrence of keywords and evidence map analysis, four themes are identified, namely, Land Transport - Operations, Land Transport - Traffic Demand, Air Transport and Environment. We show how air transportation- and environmental-related studies tend to be more mature research whereas the understanding of changes in travel behavior (e.g., telecommuting, preventive measures or health protection behavior) tends to be immature. By using a topic modeling approach, we identify multiple sub-themes within each theme. Our framework adopts a smart literature review approach that can be constantly updated, enabling an analysis of many articles, with little investment of the researcher's time, but also provides high degree of transparency and replicability. We also put forth a research agenda that can help inform and shape transport policy and practice responses to COVID-19.

Public Transportation Service Quality Evaluation during the COVID-19 Pandemic in Amman City Using Integrated Approach Fuzzy AHP-Kendall Model

The COVID-19 pandemic has affected public transportation worldwide, and its implications need to be evaluated and study deeply on all public transportation aspects. Therefore, an analysis has been created to examine the effects of the pandemic on public transportation service quality decisions to have a better vision of the different stakeholders’ needs to keep the system functioning in a profitable way. Stakeholder participation in complex, multi-criteria decision-making often produces very different results in prioritizing the decision attributes. Rank correlation techniques generally measure the degree of agreement or non-agreement among the evaluator groups. However, the multi-criteria methodology can determine not only ordinal but also cardinal priorities. Consequently, except for the attributes’ positions, the weight values are also significant in the final decision. This paper aims to apply a more sophisticated measure of group agreement than rank correlation. First, the Fuzzy-hierarchical analytical process (FAHP) has been used to find out the aggregated weights, then the Kendall correlation values are computed to reveal stakeholder opinions. Finally, the agreement measure approach has been tested in a real-world case study: the public transport development decision of Amman, Jordan. The analysis shows that by applying the Kendall technique, Kendall could gain a more profound insight into the priority characteristics of different evaluator groups.

Sustainable Urban Transportation Criteria and Measurement—A Systematic Literature Review

Sustainable transportation plays a key role in social participation and climate change. However, no universally accepted set of criteria for tracking the progress of urban sustainable transportation projects currently exists; one reason for this is the absence of a standardized lexicon for sustainability measurement elements. Therefore, this paper conducts a systematic literature review and analysis of sustainable transportation criteria using 21 papers from journals listed in the German rating system JOURQUAL3 (JQ3) and published between 2010 and 2020. The paper thus develops a unified vocabulary for sustainability measurement elements that is structured into a hierarchy. The goal (sustainable transportation) presides over the following three sustainability dimensions: objectives (e.g., minimization of traffic clogging), criteria (e.g., congestion), and indicators (e.g., cost of traffic congestion). Within the hierarchy, the main criteria for urban multimodal sustainable transportation are identified as follows: 13 social, 11 economic, and 9 environmental main criteria are determined. The three main criteria used most in the literature exclusively concern the environment. Future research is recommended to assess the interrelations between the criteria as their assignment to sustainability dimensions is ambiguous in the existing literature. This paper helps mobility managers to make decisions about urban transportation concepts and while overseeing projects.

Spatial Modelling of Modal Shift Due to COVID-19

The outbreak of COVID-19 caused many changes in people’s life. One of the most significant is the travel behaviour and transport mode choice. This study focus on the changes that the inhabitants of Vienna made in their travel choices because of the virus. The same research about spatial modelling the transport mode choice of commuters in Vienna was completed in 2019 and is a topic addressed in our previous work. Based on our developed methodology, this article indicates that public transport is not a dominant transport mode choice as it was before the virus outbreak. The main result of this paper is geographically defined areas of application of individual alternatives shown on the final map of modal shift in Vienna, which could provide theoretical support for policymakers and transportation planners. For the city of Vienna, we found that the area of the city where cars are now used has increased, which certainly has a negative impact on air quality and life in the city. The advantage of the methodology is that it can also be applied to other cities in the world.

Extracting Road Traffic Volume in the City before and during covid-19 through Video Remote Sensing

Continuous, automatic measurements of road traffic volume allow the obtaining of information on daily, weekly or seasonal fluctuations in road traffic volume. They are the basis for calculating the annual average daily traffic volume, obtaining information about the relevant traffic volume, or calculating indicators for converting traffic volume from short-term measurements to average daily traffic volume. The covid-19 pandemic has contributed to extensive social and economic anomalies worldwide. In addition to the health consequences, the impact on travel behavior on the transport network was also sudden, extensive, and unpredictable. Changes in the transport behavior resulted in different values of traffic volume on the road and street network than before. The article presents road traffic volume analysis in the city before and during the restrictions related to covid-19. Selected traffic characteristics were compared for 2019 and 2020. This analysis made it possible to characterize the daily, weekly and annual variability of traffic volume in 2019 and 2020. Moreover, the article attempts to estimate daily traffic patterns at particular stages of the pandemic. These types of patterns were also constructed for the weeks in 2019 corresponding to these stages of the pandemic. Daily traffic volume distributions in 2020 were compared with the corresponding ones in 2019. The obtained results may be useful in terms of planning operational and strategic activities in the field of traffic management in the city and management in subsequent stages of a pandemic or subsequent pandemics.

Travel Demand Prediction during COVID-19 Pandemic: Educational and Working Trips at the University of Padova

The diffusion of the COVID-19 pandemic has induced fundamental changes in travel habits. Although many previous authors have analysed factors affecting observed variations in travel demand, only a few works have focused on predictions of future new normal conditions when people will be allowed to decide whether to travel or not, although risk mitigation measures will still be enforced on vehicles, and innovative mobility services will be implemented. In addition, few authors have considered future mandatory trips of students that constitute a great part of everyday travels and are fundamental for the development of society. In this paper, logistic regression models were calibrated by using data from a revealed and stated-preferences mobility survey administered to students and employees at the University of Padova (Italy), to predict variables impacting on their decisions to perform educational and working trips in the new normal phase. Results highlighted that these factors are different between students and employees; furthermore, available travel alternatives and specific risk mitigation measures on vehicles were found to be significant. Moreover, the promotion of the use of bikes, as well as bike sharing, car pooling and micro mobility among students can effectively foster sustainable mobility habits. On the other hand, countermeasures on studying/working places resulted in a slight effect on travel decisions.

Behavior of Traffic Congestion and Public Transport in Eight Large Cities in Latin America during the COVID-19 Pandemic

This comparative study analyzes the impact of the COVID-19 pandemic on motorized mobility in eight large cities of five Latin American countries. Public institutions and private organizations have made public data available for a better understanding of the contagion process of the pandemic, its impact, and the effectiveness of the implemented health control measures. In this research, data from the IDB Invest Dashboard were used for traffic congestion as well as data from the Moovit© public transport platform. For the daily cases of COVID-19 contagion, those published by Johns Hopkins Hospital University were used. The analysis period corresponds from 9 March to 30 September 2020, approximately seven months. For each city, a descriptive statistical analysis of the loss and subsequent recovery of motorized mobility was carried out, evaluated in terms of traffic congestion and urban transport through the corresponding regression models. The recovery of traffic congestion occurs earlier and faster than that of urban transport since the latter depends on the control measures imposed in each city. Public transportation does not appear to have been a determining factor in the spread of the pandemic in Latin American cities.

Towards Sustainable Mobility? The Influence of the COVID-19 Pandemic on Romanian Mobile Citizens in Spain

Using the case study of Romanians in Spain, this article highlights how the COVID-19 crisis presents both challenges and opportunities when it comes to human mobility and sustainability. Drawing on in-depth interviews with mobile people during the period of lockdown and circulation restrictions, and in accordance with the objectives of the Sustainable Development Goals (SDGs), the paper advances and contributes to the relevance of sustainability and its impact on people’s mobility in the context of the COVID-19 pandemic. I argue that even in the midst of the crisis, sustainable ways may be found to promote and protect human mobility. The paper raises the way sustainability acts as a driver, gains relevance and influence, and contributes to the creation of new models of resilient mobility in times of crisis. The conclusions defend the respect for the SDGs regarding human mobility and emphasise the role of people on the move as sustainable actors learning to overcome distance and the barriers to their mobility during the pandemic.

An Integrated Approach of Multi-Criteria Decision-Making and Grey Theory for Evaluating Urban Public Transportation Systems

Improving the local urban transport system’s quality is often seen as one of the critical points for the government and the local operator. An amelioration of the system can improve users’ satisfaction and attract new users while simultaneously decreasing traffic congestion and pollution. Efficient methodologies are required to achieve sustainable development regarding complex issues associated with traffic congestion and pollution. In this study, we propose using the analytic hierarchy process (AHP) grey values to overcome the limitations of the uncertainty in the classical AHP approach. The presented grey-AHP model assumes an efficient contrivance to facilitate the public transport system’s supply quality evaluation, especially when respondents are non-experts. Finally, we estimate and rank the public transport system’s supply quality criteria by adopting the proposed model for a real-world case study (Amman city, Jordan). The study’s outcome shows the effectiveness and the applicability of the developed approach for enhancing the quality of the public transport system.

Challenges and Strategies for Post-COVID-19 Gender Equity and Sustainable Mobility

The COVID-19 pandemic has forced countries around the world to take unprecedented measures to contain it. In particular, its impact on mobility has been enormous, causing a sudden decrease in the number of trips and changes in the choice and use of modes of transport. Furthermore, the effects of this health crisis on the social and economic spheres have aggravated inequalities between population groups, with women being one of the most affected groups, which may accentuate the already known gender gap in mobility. Based on these premises, we carried out a strategic analysis of urban mobility from the perspective of sustainability and gender equity in the context of the pandemic, identifying a set of effective strategies to address the post-COVID-19 urban mobility scenario. To this end, based on the review of the literature and expert opinions, we carried out a Strengths, Weaknesses, Opportunities and Threats (SWOT) analysis that allowed us to formulate 16 strategies after careful consideration of the weaknesses, strengths, threats and opportunities encountered. Our results provide useful recommendations for making successful policy decisions on post-COVID-19 mobility planning towards a more sustainable, equitable and safe model.

Investigating Sustainable Commuting Patterns by Socio-Economic Factors

This research aims to analyze how modes of transportation differ according to socio-economic factors in an urban space. The study area is Ramsey County, the most densely populated county in Minnesota. The primary data used were from the recent 2012–2016 Census Transportation Planning Products (CTPP). We performed regression models to identify the relationship between mode of transport and socio-economic variables, and further analyzed disaggregate trip data to provide a more realistic evaluation of commuting patterns by use of multiple variables in combination. The research found that sustainable commuting patterns correlated significantly with both poverty and minority group status, but bore no significant relationship to older workers. Additionally, there was a significant correlation between commuting alone by car with both minority group status and older workers, but not with poverty. This research also confirmed that the sustainable commuting patterns of the working poor were mostly located in the downtown area, while causes of low-income workers driving alone typically involved much longer commutes to and from points throughout the study area, suggesting that more efficient commutes are a significant quality of life factor for the urban poor when evaluating residential and employment opportunities in the central city.

The Risk of Dissolution of Sustainable Innovation Ecosystems in Times of Crisis: The Electric Vehicle during the COVID-19 Pandemic

Innovation ecosystems evolve and adapt to crises, but what are the factors that stimulate ecosystem growth in spite of dire circumstances? We study the arduous path forward of the electric vehicle (EV) ecosystem and analyse in depth those factors that influence ecosystem growth in general and during the pandemic in particular. For the EV ecosystem, growth implies outcompeting the less sustainable internal combustion engine (ICE) vehicles, thus achieving a transition towards sustainable transportation. New mobility patterns provide a strategic opportunity for such a shift to green mobility and for EV ecosystem growth. For innovation ecosystems in general, we suggest that a crisis can serve as an opportunity for new innovations to break through by disrupting prior behavioural patterns. For the EV ecosystem in particular, it remains to be seen if the ecosystem will be able to capitalize on the opportunity provided by the unfortunate disruption generated by the pandemic.

Impact of Car Sharing on Urban Sustainability

The article gives us an insight into the key issues of car sharing and its impact on urban sustainability. A selection of 314 articles published in peer-reviewed journals from the Scopus database were analysed using Leximancer 5.0 for Automated Content analysis. A total of seven themes were identified explaining the researched topic of the car sharing situation in Europe, which are sharing, economy, model, systems, electrical car sharing, policy and travel. There are two ways of sharing owned cars in Europe; access to cars from the fleet of private organisations and P2P car sharing. Sustainable environmental solutions in the context of the electrification of cars are used. Car sharing usually takes place online and can be free or for a fee as defined by The European Economic and Social Committee. The article provides an overview of understanding the concept of urban car sharing in Europe.

Mobility Patterns of Students: Evidence from Tricity Area, Poland

Generational change is one of the vital socioeconomic forces affecting the global economic environment. In many studies, the youngest generations are presented as the ones changing the market trends. This can also be observed in areas of travel demand and mobility patterns. However, research on those topics in many countries, for many societies, is scarce. This study aimed to examine the travel behavior of Polish young adults, namely students living in the Tricity area. Factor analysis and ANOVA were used to analyze the data gathered via an online survey assessing the characteristics of mobility patterns of students born between 1981 and 1999. Factor analysis allowed grouping the attitudes towards traveling among those young adults (Y Generation, Y’s, Y Gen). Three factors were identified, and they were associated with luxury and self-expression, freedom and comfort, safety and environmental friendliness. The driver’s characteristics were the least consistent with the classic image of typical Y’s, and those using the active commute—the most. In turn, the largest group were people using public transport, which partially presented convergent opinions with drivers and users of the active commute. It turned out that the car drivers, active commuters and respondents utilizing public transport differed not only in their behavior and presentation of Y Gen characteristics but also in their attitude towards categories such as comfort, desire for luxury, economy or ecology. This study is a complex analysis of the mobility patterns of students in the Tricity area. It presents the set of variables influencing the travel demand of the chosen age group. The study also compares the presented travel choices with those declared by representatives of other nations. Finally, it indicates the next research problems to be addressed in future research.

Mobility Behaviour in View of the Impact of the COVID-19 Pandemic—Public Transport Users in Gdansk Case Study

The COVID-19 pandemic, like an earthquake, shocked our civilization and is still having a devastating effect on our lives. Guaranteeing an appropriate level of safety in the conditions of an epidemic is a highly problematic issue due to the subjectivism of social individuals, their diverse attitudes, and past life experiences. Taking into account the World Health Organisation (WHO) guidelines regarding the pandemic, authorities all around the world have reacted by issuing the necessary sets of advice and legal acts. This resulted in immediate and severe implications on mobility styles. The purpose of this paper was to investigate the impact of COVID-19 on mobility behaviours with special regard to public transport users, in terms of their willingness to travel and their safety criteria perceptions. The city of Gdańsk, in Poland, located on the Baltic Sea, has been taken as an example. The hypothesis was as follows: the epidemic phenomenon may substantially affect mobility behaviours in terms of subjective levels of safety and the mental comfort of public transport users, resulting in avoiding this form of transport. In accordance with the survey results, carried out among the users, 90% of respondents resigned or limited their usage. Almost 75% of them plan to return to using public transport when the epidemic situation has stabilized. The others, unfortunately, have completely lost hope that public transport will ever be safe. These results indicate decisively that the future of public transport in cities, and the willingness of passengers to use it once the epidemic is over, depends majorly on the perceived comfort and safety during the epidemic. This means that transport policies should be focused on enhancing these perceptions and making sure that the image of public transport is not in further decline; otherwise, it could mean an almost impossible effort to encourage passengers to return to using sustainable modes of transport in the future.

RSSGM: Recurrent Self-Similar Gauss–Markov Mobility Model

Understanding node mobility is critical for the proper simulation of mobile devices in a wireless network. However, current mobility models often do not reflect the realistic movements of users within their environments. They also do not provide the freedom to adjust their degrees of randomness or adequately mimic human movements by injecting possible crossing points and adding recurrent patterns. In this paper, we propose the recurrent self-similar Gauss–Markov mobility (RSSGM) model, a novel mobility model that is suitable for applications in which nodes exhibit recurrent visits to selected locations with semi-similar routes. Examples of such applications include daily human routines, airplane and public transportation routes, and intra-campus student walks. First, we present the proposed algorithm and its assumptions, and then we study its behavior in different scenarios. The study’s results show that different and more realistic mobility traces can be achieved without the need for complex computational models or existing GPS records. Our model can flexibly adjust its behavior to fit any application by carefully tuning and choosing the right values for its parameters.

Using Best Worst Method for Sustainable Park and Ride Facility Location

The Park and Ride (P&R) system is a set of facilities available to private vehicle users to transfer to public transportation in order to complete their journey. The location of the facilities is determined by the purpose for which they have been created, for example, to reduce traffic in the central business district (CBD), reduce pollution, or increase the use of public transportation. Thus, a set of six main criteria and 19 sub-criteria are considered that are particularly important for decision-makers about the location of P&R facilities in a city. In order to identify which criteria are relevant, a method belonging to the multiple criteria decision is needed. The central point of this study is to evaluate the problem of the location of the facilities of the P&R system according to the point of view of the experts. For this aim, the Best Worst Method (BWM) is adopted to estimate the location of the facilities of the P&R system. The questionnaire survey has been designed estimated by ten transport experts in the related field. The recently created BWM was conducted. The results highlighted that “accessibility of public transportation” is the most important aspect of the problem of the location of P&R facilities. The results obtained provide greater accuracy in the location of facilities problem than the pure analytic hierarchy process method (AHP).

How to Create Walking Friendly Cities. A Multi-Criteria Analysis of the Central Open Market Area of Rijeka

Current mobility strategies tend to pursue sustainable solutions with low environmental and economic impact, such as the disincentive to the use of private vehicles. Mobility on foot is among the most advantageous forms for short distances, especially if different technological and infrastructural solutions are inserted in the urban context such as underpasses that limit the likely conflicts with motor vehicles. These solutions, however, are not easily perceived as positive because people often do not like to change their usual routes or because they feel psychological discomfort when they pass through closed places. This research work focuses on the evaluation of the benefits of including a small underpass in the city of Rijeka, Croatia and through an Analytical Hierarchy Process (AHP), a multi-criteria analysis, it was possible to prioritize a number of decision-making alternatives, related to qualitative and quantitative evaluations, otherwise not directly comparable, and combining multidimensional measurement scales into a single priority scale. This analysis allows to provide cues for local and non-local urban planning, encouraging through the participatory form an active comparison between the population and local authorities and at the same time allows to assess which multidisciplinary processes (psychological/engineering) are possible to put in place to encourage the research on pedestrian behavior.

The Impact of COVID-19 Pandemic on the Resilience of Sustainable Mobility in Sicily

The COVID-19 pandemic has resulted in unprecedented measures changing travel habits in many countries. Many users have started to prefer traveling by private cars, which is against the sustainability policies of the European cities. The necessity of gaining a deeper understanding of road users’ travel habit changes, their feelings on public transport use, and their perceptions of using sustainable urban mobility modes has emerged for future transport planning. Considering these facts, the study in this paper aimed to investigate the influence of the COVID-19 pandemic on road users’ perceptions, needs, and use of sustainable travel modes (i.e., public transport, walking, and cycling). An online survey was carried out during the period from March to May 2020 in the case study area, Sicily of Southern Italy. Regarding the population of the case study, the survey was representative, with 431 individuals. The survey included variables, namely gender, age, city of residence, private car ownership, walking and cycling frequency before and during the pandemic, public transport use frequency for leisure activities before and during the pandemic, need for remote working, and the stress and anxiety perception of using public transport during the pandemic. The analysis started with descriptive statistics and it was followed by correlation analysis in order to explore the characteristics of the dataset and relationship between variables. It was found that these were not statistically significantly correlated at a 95% confidence level. An ordinal regression model was applied for determining the predictions. The results suggested that women were less likely to walk during the pandemic than men. Participants were more likely to resume remote work even after the second phase in order to reduce their daily travel needs and keep their isolation. Participants have expressed a positive opinion on the use of micromobility during pandemic situations. These results can be considered as a basis for sustainable urban planning and a guide for decision-makers who aim to encourage the use of public transport, walking, cycling, and micromobility.