Walking,cycling, and public transport for commuting and non-commuting travels across 5 European urban regions: Modal choice correlates and motivations

The objective of this study was to explore individual and contextual-level characteristics associated with active (walking and cycling) and public transport as main travel modes for both non-commuting and commuting purposes, in residents of five European urban regions. We also described participant-reported motivations for modal choice for each journey purpose. The study used multilevel models to investigate cross-sectional associations of individual (i.e. age, gender, educational level) and contextual (defined by a combination of residential neighbourhood characteristics in typologies) characteristics with the choice of active and public transport as outcome. Based on an online survey of 6037 residents of Ghent and suburbs (Belgium), Paris and inner suburbs (France), Budapest and suburbs (Hungary), the Randstad (including the cities of Amsterdam, Rotterdam, The Hague and Utrecht in the Netherlands) and Greater London (United Kingdom), we observed associations with both individual and contextual characteristics.Results of the multilevel modelling show that the probability of using active or public transport as main mode varies depending on both individual and contextual characteristics. At individual level, relations with gender, age, education, weight status and having at least one child varied according to main transport mode and/or purpose. For example, overweight participants reported lower level of cycling for commuting and non-commuting travels than normal-weight participants. In the context of non-commuting travels, participants with one or more child reported less public transport use and more walking (vs participants without children). Among contextual-level variables, urban characteristics of the residential neighbourhood defined by four clusters (according to food environment, recreational facilities and active mobility opportunities) were associated with public transport and walking but not with cycling. For active transport the most important reasons were “I like to travel (on foot or by bike)” and “I want to be physically active” for both travel purposes. “Public transport facilities nearby” was indicated as the most important reason for public transport (for both trip purposes) – the second was “Journey time”.Our findings highlight the importance of exploring a combination of multiple correlates at individual and contextual level according to journey purposes and suggest that the role of health-related individual characteristics such as weight status need further exploration.     

Social networks' group tie strength and travel behavior

The last decades saw an increased interest in the social aspects of urban mobility, particularly in understanding the linkage between social network (SN) ties and travel behavior. Most studies analyzed ego-centric networks, focused on dyadic relations and distinguished between weak and strong ties. The purpose of this study is to understand the hidden layers connecting social network group ties and its associated travels within a meeting context. Data included 315 relations based on 137 group meetings that took place in the city of Tel Aviv, Israel at either a cafe, pub or a restaurant and involved three or more participants.We developed a group tie strength index as a spectrum ranged from weak to strong ties based on four parameters: intimacy, duration of connection, frequency, and modes of communication among group members. The study reveals that majority of the connections tend to be at the medium of the spectrum. This indicates that the common classification into weak/strong ties in relation to travel behavior is overlooking important segments of ties and that there is a difference in tie strength between dyadic and triadic/group meetings. Classification and Regression Trees (CART) model analysis explored how Social Network group tie strength (SNGTS) of members participating in a meeting event can be predicted by the event context and the contextual travel pattern. Two CART trees were found. Each started with a different variable for the first split differentiation and showed different tree paths for explaining the group tie strength for an event-based participants. These include the “communication means” that were used to arrange the meeting and the “meeting type” (i.e.- friends, family, and business- oriented meetings) variables. Five more variables were found to be related to predicting the SN group tie strength including: meeting duration, distance of meeting place from residence, transport means and travel duration to the meeting and age.     

The built environment and vehicle ownership modeling: Evidence from 32 diverse regions in the U.S.

Vehicle ownership is an important determinant of the travel demand forecasting process. Vehicle ownership models are used by policy makers to identify factors that affect vehicle miles traveled, and therefore address problems related to energy consumption, air pollution, and traffic congestion. For the conventional travel demand forecasting, it logically follows land use forecasting, before trip generation, which is commonly treated as step one. The most critical limitation of the vehicle ownership models, especially in the conventional process, is that they are often related mainly to sociodemographic variables, not so much to built environmental variables. In this study, by pooling regional household travel survey data from 32 diverse regions (almost 92,000 households) of the U.S., and by controlling for socio-demographic and the built environmental variables, we estimated a vehicle ownership model that contributes to the understanding of vehicle ownership and improves the accuracy of travel demand forecasts. Two main findings of this research are: 1) The number of vehicles owned by a household increases with socio-demographic variables and decreases with almost all of the built environmental variables. For the urban planning and design practices, this finding suggests that car shedding occurs as built environments become more dense, mixed, connected, and transit-served. 2) We used both count regression and discrete choice models, and the results suggest that count regression models have better predictive accuracy. The model developed in this study can be directly used for travel demand modeling and forecasting by metropolitan planning organizations.     

Urban mobility with a focus on gender: The case of a middle-income Latin American city

This study analyzes gender differences in travel patterns for the Metropolitan Area of Montevideo, Uruguay. By applying multilevel regression models, it provides estimates of the impact of individual and contextual factors on travel behavior. The paper's findings lend support to the household responsibility hypothesis, which claims that women's travel patterns are affected by the type of household in which they live and the consequent responsibilities or roles they assume. Furthermore, gender differences in travel patterns are reinforced across census tracts. The results indicate that policy makers need to consider gender differences when seeking to enhance urban planning decisions.     

Tourist Perceptions of Climate Change: A Study of International Tourists in Zanzibar

A study was conducted in Zanzibar, Tanzania, in order to understand tourist perceptions of climate change, the importance of climate for travel decisions, and the likely consequences of ongoing climate change for travel decisions. The results show that climatic characteristics of destinations are important, though not the only factor shaping travel decisions. Under a scenario of climate change, certain climate variables, such as more rain, storms, and higher humidity are also likely to negatively influence travel decisions, rather than higher temperatures alone, which are not necessarily perceived as negative. Regarding the contribution of travel to climate change, the study reveals that leisure tourists in Zanzibar are largely unaware of their impact on the natural environment, while the analysis of stated travel behaviour shows that they frequently travel by air. Overall, the results indicate that travel flows might change in more complex ways than currently assumed, and that a small share of high-intensity air travellers is responsible for a considerable environmental impact in terms of climate change.     

Car ownership as a mediating variable in car travel behaviour research using a structural equation modelling approach to identify its dual relationship

Car ownership is generally considered an important variable in car travel behaviour research, but its specific role is often not well understood. Certain empirical studies consider car ownership as the dependent variable explained by the built environment, whereas other studies deem it to be one of the independent variables explaining car travel behaviour. This paper takes note of the dual influence car ownership has in explaining car travel behaviour by assuming that car ownership mediates the relationship between the built environment and car use. The relationship is estimated using a structural equation model since it accounts for mediating variables. This approach confirms the intermediary nature of car ownership.     

Mobility biographies: A review of achievements and challenges of the mobility biographies approach and a framework for further research

In transport research, important changes in an individual’s life, so-called key events, are of particular interest because changes in one’s environment and surrounding context weaken routines, and a ‘window of opportunity’ opens up for behavioural change. In the framework of the mobility biographies approach, several studies have been undertaken to improve understanding of travel behaviour change in the last decade. This paper critically and systematically reviews emerging results from mobility biographies research, focusing on key events which potentially induce contextual and travel behaviour changes. The first step was to identify 25 of the most important studies for this approach and their related concepts. Next, notions other than key events in the literature are discussed and a theoretical framework for the longitudinal interaction of four dimensions of key events and other factors for travel behaviour change are identified: (i) life events in private and professional careers, (ii) adaptation of long-term mobility decisions, (iii) exogenous interventions, and (iv) other long-term processes which are not key events (e.g. socialisation). Furthermore, the understanding of key events, methodological challenges and further research gaps are critically discussed in this review.     

Errors in variables in multinomial choice modeling: A simulation study applied to a multinomial logit model of travel mode choice

Modeling travel demand is a vital part of transportation planning and management. Level of service (LOS) attributes representing the performance of transportation system and characteristics of travelers including their households are major factors determining the travel demand. Information on actual choice and characteristics of travelers is obtained from a travel survey at an individual level. Since accurate measurement of LOS attributes such as travel time and cost components for different travel modes at an individual level is critical, they are normally obtained from network models. The network-based LOS attributes introduce measurement errors to individual trips thereby causing errors in variables problem in a disaggregate model of travel demand. This paper investigates the possible structure and magnitude of biases introduced to the coefficients of a multinomial logit model of travel mode choice due to random measurement errors in two variables, namely, access/egress time for public transport and walking and cycling distance to work. A model was set up that satisfies the standard assumptions of a multinomial logit model. This model was estimated on a data set from a travel survey on the assumption of correctly measured variables. Subsequently random measurement errors were introduced and the mean values of the parameters from 200 estimations were presented and compared with the original estimates. The key finding in this paper is that errors in variables result in biased parameter estimates of a multinomial logit model and consequently leading to poor policy decisions if the models having biased parameters are applied in policy and planning purposes. In addition, the paper discusses some potential remedial measures and identifies research topics that deserve a detailed investigation to overcome the problem. The paper therefore significantly contributes to bridge the gap between theory and practice in transport.     

A comparative study of social interaction frequencies among social network members in five countries

Social interaction patterns are relevant to explain (social) travel behavior. As such, the objective of this paper is to comparatively study the factors that influence social interaction frequency among social network members with different communication modes. Based on data from seven surveys on social networks, this analysis seeks to shed some light on (i) the similarities and differences in social interaction frequency patterns, (ii) the relation of personal and network characteristics with observed patterns, and (iii) the extent to which these associations are consistent across contexts, in terms of effect direction and magnitude.A multilevel-multivariate lognormal hurdle model is used to jointly analyze social interaction frequency patterns across all datasets. Level 1 includes information on ego-alter dyad characteristics, level 2 includes ego-level socio-demographic and aggregate social network characteristics, while level 3 includes information specific to each context where data was collected. In line with network capital theory, results show the existence of very consistent associations between social interaction frequency and some network and dyad characteristics such as network size, ego-alter distance, and emotional closeness, which showed some degree of generality irrespective of context. Building up on previous research, results also suggest that the effect of a higher transport cost-to-earnings ratio is more likely to manifest in the tie-formation phase, in such a way that the geographical spread of the network will tend to be smaller, but conditional on such a network distribution, the cost-to-earnings ratio effect becomes negligible. For other variables such as education level, gender and relationship type, effect patterns were less clear, which might be explained by socio-economic, and other contextual factors, as well as methodological differences across studies.The model presented here can provide average levels of demand for social interactions, which bounded by the geographical distribution of networks, can be used to further understand travel demand in urban environments and transportation systems at the local or regional level.     

The desired quality of integrated multimodal travel information in public transport: Customer needs for time and effort savings

Travel information is one of the factors that contribute to the quality of public transport. In particular, integrated multimodal travel information (IMTI) is expected to affect customers’ modal choice. The objective of this research is to identify customers’ desired quality of IMTI provision in public transport. Customers’ desired IMTI quality can vary throughout the pre-trip, wayside and on-board stages of a journey. The main determinants are time savings (travel and search time) and effort savings (physical, cognitive, and affective effort). In a sample of Dutch travellers with a substantial share of young persons, the pre-trip stage turns out to be the favourite stage to collect IMTI when planning multimodal travel; desired IMTI types in this stage are used to plan the part of the journey that is made by public transport. Wayside IMTI is most desired when it helps the traveller to catch the right vehicle en route. On-board travellers are most concerned about timely arrival at interchanges in order to catch connecting modes. In the whole travel process, travel time is the most important saving. Apart from that, pre-trip search time savings are also desired, while en route affective effort is more important than cognitive effort.     

An exploratory analysis of relationships between socioeconomic,land use,activity participation variables and travel patterns

This paper aims to find relations between the socioeconomic characteristics, activity participation, land use patterns and travel behavior of the residents in the São Paulo Metropolitan Area (SPMA) by using Exploratory Multivariate Data Analysis (EMDA) techniques. The variables influencing travel pattern choices are investigated using: (a) Cluster Analysis (CA), grouping and characterizing the Traffic Zones (TZ), proposing the independent variable called Origin Cluster and, (b) Decision Tree (DT) to find a priori unknown relations among socioeconomic characteristics, land use attributes of the origin TZ and destination choices. The analysis was based on the origin–destination home-interview survey carried out in SPMA in 1997. The DT application revealed the variables of greatest influence on the travel pattern choice. The most important independent variable considered by DT is car ownership, followed by the Use of Transportation “credits” for Transit tariff, and, finally, activity participation variables and Origin Cluster. With these results, it was possible to analyze the influence of a family income, car ownership, position of the individual in the family, use of transportation “credits” for transit tariff (mainly for travel mode sequence choice), activities participation (activity sequence choice) and Origin Cluster (destination/travel distance choice).     

ICT and transport behavior: A conceptual review

Information and communication technologies (ICTs) have considerable importance for transport systems, as they provide access to travel information, planning tools, opportunities to share transport modes, to work at-a-distance, compare transport mode cost, make payment, improve safety and health, and to communicate travel patterns. Over the past decade, there has been massive growth in the availability of transportation ICT, in particular, smartphone applications. There is considerable evidence that ICTs have profoundly changed the ways in which transport systems are perceived and used, and mobilities performed, with far-reaching implications for transport mode choices and transport demand. Against this background, the paper seeks to conceptualize ICT with relevance for transport systems, and to discuss the implications for the environmental sustainability of the transport sector. Findings suggest that while some ICT innovations foster and support sustainable transport choices, others raise new and significant barriers to more sustainable transport futures.     

Information searching and the travel behaviours of MICE travellers: a cross‐cultural study

Despite growing academic interest in meetings, incentives, conventions and exhibitions (MICE) travel in recent years, there has been little investigation of the comparative information search behaviours of MICE travellers on the basis of their country of origin and cultural background. This paper proposes that country of residence and primary language spoken are significant factors in explaining the information searching and travel behaviours of MICE travellers. The sample population included Japanese‐, English‐ and Chinese‐speaking MICE travellers. A self‐completion questionnaire was administered to travellers undertaking MICE‐related travel in Taipei, Taiwan. Some significant differences were identified between the three respondent groups. The findings demonstrate the important role that is played by internal and external information sources among MICE travellers as a predictor of their subsequent travel to Taiwan. Copyright © 2011 John Wiley & Sons, Ltd.     

Estimating the impact of COVID-19 on air travel in the medium and long term using neural network and Monte Carlo simulation

The COVID-19 pandemic has had a substantial impact on the airline industry. Air travel in the United States declined in 2020 with significantly lower domestic and international flights. The dynamic change and uncertainty in the trend of COVID-19 have made it difficult to predict future air travel. This paper aims at developing and testing neural network models that predict domestic and international air travel in the medium and long term based on residents' daily trips by distance, economic condition, COVID-19 severity, and travel restrictions. Data in the United States from various sources were used to train and validate the neural network models, and Monte Carlo simulations were constructed to predict air travel under uncertainty of the pandemic and economic growth. The results show that weekly economic index (WEI) is the most important predictor for air travel. Additionally, daily trips by distance play a more important role in the prediction of domestic air travel than the international one, while travel restrictions seem to have an impact on both. Sensitivity analysis results for four different scenarios indicate that air travel in the future is more sensitive to the change in WEI than the changes in COVID-19 variables. Additionally, even in the best-case scenario, when the pandemic is over and the economy is back to normal, it still takes several years for air travel to return to normal, as before the pandemic. The findings have significant contributions to the literature in COVID-19's impact on air transportation and air travel prediction.     

The indirect effect of the built environment on travel mode choice: A focus on recent movers

Many studies have demonstrated that the built environment has a strong impact on people's travel mode choice. However, the built environment also influences elements such as travel distance and car ownership, which might be the true predictors of which travel modes are chosen. In this study, we analyse the effects of changes in residential neighbourhood on changes in travel mode (for commute trips and leisure trips), both directly and indirectly through changes in car ownership, travel distances and travel attitudes. This study applies a structural equation modelling approach using quasi-longitudinal data from 1650 recently relocated residents in the city of Ghent, Belgium. Results indicate that the built environment has strong direct effects on active leisure trips and car use. However, distance (for car use) and attitudes (for active travel) were found to be important mediating variables. In sum, the effect of the built environment on travel mode choice might be more complex than commonly assumed as it partly seems mediated by travel distance and travel attitudes.     

Non-linear associations between built environment and active travel for working and shopping: An extreme gradient boosting approach

Active travel has environmental, social, and public health-related benefits. Researchers from diverse domains have extensively studied built-environment associations with active travel. However, limited attention has been paid to distinguishing the associations between built environment characteristics at both the origins and destinations and active travel for working and shopping. Scholars have started to examine non-linear associations of built environment with travel behaviour, but active travel has seldom been a focus. Therefore, this study, selecting Xiamen, China, as the case, utilises a state-of-the-art machine learning method (i.e., extreme gradient boosting) to explore the non-linear associations between built environment and active travel for working and shopping. Our findings are as follows. (1) For both purposes, trip characteristics contribute the greatest, and the built environment is also quite important and has larger collective contributions for active travel than does socioeconomics. (2) The relative importance of built environment on active travel for shopping is evidently larger than that for working. (3) All built-environment variables have non-linear associations with active travel, and associations with active travel for working are generally in inverted U or V shapes, while those with shopping trips have much more complex patterns. (4) Differences in the threshold value and gradient exist between built-environment associations with active travel for working and shopping and between variables at origins and destinations. Decision makers are recommended to meticulously disentangle the complex influences of built environment on active travel and distinguish between diverse purposes to make informed and targeted interventions.     

Making plans or “just thinking about the trip”? Understanding people’s travel planning in practice

ICT solutions have been proposed as a means for changing environmentally unfavourable traffic behaviour by providing better, real-time and more accessible travel information. However, prevailing models of travel choice and travel behaviour tend to overemphasise the impact and importance of information and the individualistic perspective. The issue of choice and travel planning in everyday life situations, and how information is used and acted on in these processes, was examined in a qualitative study in Stockholm, Sweden. Practice Theory was used as the theoretical framework for the study. Interviews were supplemented with an explorative diary and photo assignment to bring unreflected choices and actions of planning travel to the conscious level.The results showed that travel planning involves the immediate situation where planning and decisions are made, but also aspirations, cognitive/time/material limitations, social norms and social relations that extend widely in time and space. Definitions of travel planning and travel information based on the situated practices of planning are suggested. In the muddle of everyday life, travel planning takes place in the brief moments where circumstances at different levels – time, place, the social realm - interact and are considered or directly acted upon. In the development of new ICT-based travel information services, the role of technology in changing normal practices should be considered.     

“Nomads at last”? A set of perspectives on how mobile technology may affect travel

This paper’s goal is to propose a set of perspectives on how mobile phones and computers might affect travel: by tapping into basic needs of travellers; by affecting some preconditions for its spatial configuration; and by altering its costs and benefits. In the age of “digital nomadism,” mobile technology is likely to play an important role for the new mobility and work-life arrangements put into practice by a multitude of creative knowledge professionals. What emerges from our multi-perspective exploration is the realisation that mobile technology might offer people numerous new reasons to be mobile: by making them more informed; more capable of using a larger variety of physical spaces and re-negotiating obligations in real-time; and potentially more efficient in the allocation of their travel time and resources. On the other hand, it also appears that mobile technology can impose new burdens on travellers and make travel less appealing in some ways. Additional research is called for to improve our understanding of the circumstances under which each of these opposing outcomes occurs. The findings from such research could be used to better calibrate traffic simulation models, as well as to weigh the implications of emerging forms of travel behaviour for the environment.     

Spatial context and the complexity of daily travel patterns: an international comparison

The analysis of travel patterns is an important research topic in transportation research and urban planning. It provides the background information necessary to better understand the complex relationship between urban structure, the transportation system and household travel patterns. To what extent do travel behaviour reflect the properties of the urban structure and the transportation network, or do these patterns largely follow their own regularities? Can different patterns be observed across different space-time settings, or can common patterns be observed, largely independent from such contexts? To better understand these relationships, this paper reports on some of the findings of analyses, conducted to identify underlying structures in various aspects of travel patterns. Travel patterns, derived from activity and travel diary data collected in Portland (USA), Midlands (UK), Fukuoka (Japan), Canadian metropolitan areas, and the South-Rotterdam region (The Netherlands) are compared. The results indicate that travel patterns are largely independent from spatial setting, except for some extreme cases.     

A GIS toolkit for exploring geographies of household activity/travel behavior

Recent developments in geographic information systems (GIS) and increasing availability of activity/travel micro-data combine to encourage innovation in visualization and exploration of behavioral outcomes of urban processes. Understanding how households and individuals are using cities to conduct their daily activities has important implications for understanding policy response to urban travel reduction strategies. This paper describes a prototype object-oriented, GIS-based system designed to support exploration of household level activity/travel behavior. The capabilities of the system are demonstrated using households from the 1994/1995 Portland Household Activity and Travel Behavior Survey. An illustrative case study demonstrates that exploratory systems of this sort can be useful tools for generating timely activity/travel hypotheses for further study.