The impacts of Internet use upon activity participation and travel: Results from a longitudinal diary-based panel study

At the outset of this research, two fields of transport research were in the ascendant. The first reflected technological change, considering the growth of new information and communications technologies and their impacts for transport systems and travel behaviour. The second reflected social change, considering the growth in inequality and disadvantage and the contribution of transport systems and travel behaviour to the same. This paper investigates a potential link between the two, exploring the hypothesis that virtual mobility, via the Internet, could provide a viable alternative to physical mobility in reducing mobility-related social exclusion. The paper presents data from a longitudinal, panel-based diary study. Results support the hypothesis that virtual mobility can provide a viable alternative to physical mobility in reducing aspects of mobility-related exclusion, by providing additional accessibility (virtual accessibility) without an increase in physical mobility. Furthermore, there is no evidence in this research to support a link between physical mobility and virtual mobility; and no evidence to suggest a negative effect of virtual mobility for sociability.     

Travel-based multitasking: review of the empirical evidence

This paper reviews 58 studies with empirical evidence on travel-based multitasking, identifies gaps in terms of data collection methods and provides a comprehensive review of findings about the significance of variables with an impact on the prevalence and type of multitasking. We identified the limitations of quantitative or qualitative surveys and advocate a mixed methods approach to provide an in-depth understanding of travel-based multitasking. We revealed that cross-country comparisons are missing due to the lack of empirical evidence outside the developed countries. While there are indications of increasing multitasking with mobile devices, we found only two longitudinal surveys that provide evidence. We call for a standardisation of definitions of multitasking activities to enable more longitudinal research. We identified 75 variables that were tested for impact on travel-based multitasking in previous research, of which 60 were found to be significant. Sufficient evidence (i.e. minimum three papers), however, only exists for age, gender, trip duration, travel mode, trip purpose, time of the day and day of the week of the trip and the presence of a travel companion. Therefore, more research is suggested to determine the influence of attitude, comfort, availability of equipment, time use and spatial attributes on the type and prevalence of travel-based multitasking.     

Tour-based mode choice of joint household travel patterns on weekend and weekday

Joint household travel, with or without joint participation in an activity, constitutes a fundamental aspect in modelling activity-based travel behaviour. This paper examines joint household travel arrangements and mode choices using a utility maximising approach. An individual tour-based mode choice model is formulated contingent on the choice of joint tour patterns where joint household activities and shared ride arrangements are recognised as part of the joint household decision-making that influences the travel modes of each household member. Two models, one for weekend and one for weekday, are estimated using empirical data from the Sydney Household Travel Survey. The results show that weekend travel is characterised by a high joint household activity participation rate while weekday travel is distinguished by more intra-household shared ride arrangements. The arrangements of joint household travel are highly associated with travel purpose, social and mobility constraints and household resources. On weekends, public transport is mainly used by captive users (i.e., no-car households and students) and its share is about half of that on weekdays. Also, the value of travel time savings (VOTs) are found to be higher on weekends than on weekdays, running entirely counter to the common belief that weekend VOTs are lower than weekday VOTs. This paper highlights the importance of studying joint household travel and using different transport management measures for alleviating traffic congestion on weekdays and weekends.     

Value of travel time: An activity‐based analysis with combined RP and SP data

Under certain assumptions, values of travel time (VOT) can be divided into two parts: one associated with travel (i.e., the value of reducing travel time disutility) and the other associated with activities (the shadow price of time). The empirical results of combining RP and SP data showed that the VOT of travel was greater than that of activity. The results also showed that SP experiments that did not take or only took part of activities into consideration would underestimate VOT.     

Participation in online activities while travelling: an application of the MDCEV model in the context of rail travel

Transportation - Travel-based multitasking, i.e. using travel time to conduct enjoyable and/or productive activities, is the subject of an increasing number of theoretical and empirical studies....     

Well-being and activity-based models

We present empirical and theoretical analyses to investigate the relationship between happiness (or subjective well-being) and activity participation and develop a framework for using well-being data to enhance activity-based travel demand models. The overriding hypothesis is that activities are planned and undertaken to satisfy needs so as to maintain or enhance subjective well-being. The empirical analysis consists of the development of a structural equations exploratory model of activity participation and happiness using data from a cross-sectional survey of a sample of commuters. The model reveals significant correlations between happiness and behavior for different types of activities: higher propensity of activity participation is associated with greater activity happiness and greater satisfaction with travel to the activity. The theoretical analysis consists of the development of a modeling framework and measures for the incorporation of well-being within activity-based travel demand models. The motivation is that activity pattern models have been specified in ad-hoc ways in practice as a function of mobility, lifestyle, and accessibility variables. We postulate that well-being is the ultimate goal of activity patterns which are driven by needs and propose two extensions of activity pattern models. The first extension consists of the use of well-being measures as indicators of the utility of activity patterns (in addition to the usual choice indicators) within a random utility modeling framework. The second extension models conceptually the behavioral process of activity generation based on needs satisfaction. We present an example of an operational activity pattern model and propose well-being measures for enhancing it.     

Leisure mobility styles in Swiss conurbations: construction and empirical analysis

Leisure travel is the most difficult travel purpose to analyse due to the lack of fixed spatial and temporal referents and the consequent flexibility in patterns. This paper addresses lifestyles, social influence, and the travellers’ social networks, issues that have proved valuable for travel behaviour research in confronting the complexity of leisure travel. An approach for constructing leisure mobility styles, based on orientations towards leisure and mobility, will be presented first and then the hypotheses that transport behaviour can be better explained through analysis of leisure mobility styles will be tested. Multivariate analysis reveals that the leisure mobility style group makes a significant contribution towards clarifying variance for the activities ‘Visiting friends and relatives’, ‘Travel participation’, ‘Mode choice’, and ‘Travel distance for leisure’. The use of leisure mobility styles is most useful for developing practical intervention pointers where the in-group homogeneity of lifestyle should be addressed in greater detail.     

Impacts of Information and Communication Technologies (ICT) on time use and travel behavior: a structural equations analysis

The objective of this paper is to contribute an empirical study to the literature on transportation impacts of Information and Communications Technologies (ICT). The structural equation model (SEM) is employed to analyze the impacts of ICT usage on time use and travel behavior. The sample is derived from the travel characteristic survey conducted in Hong Kong in 2002. The usage of ICT is defined as the experience of using e-mail, Internet service, video conferencing and videophone for either business or personal purposes. The results show that the use of ICT generates additional time use for out-of-home recreation activities and travel and increases trip-making propensity. Individuals at younger age or with higher household income are found to be more likely ICT users. The findings of this study provide further evidence on the complementarity effects of ICT on travel, suggesting that the wide application of ICT probably leads to more, not less, travel. The study also demonstrates the importance of considering the interactions between activity and travel for better understanding of the nature and magnitude of the impacts of ICT on time use and trip making behavior.     

Walking short distances. The socioeconomic drivers for the use of proximity in everyday mobility in Barcelona

Many studies have found that cities, with residents that are co-located with jobs and services in compact and diverse urban environments, generate positive outputs for a number of areas of social policy, with issues ranging from environmental to social and including public health. This evidence supports promoting rich and thriving neighbourhoods in order to encourage short distance mobility. In this context, we use a wide travel survey (EMQ06), undertaken in Spain, to measure short-distance travelling within Barcelona and to assess how distinct social groups make use of the local scale for their everyday mobility. The effects of socioeconomics and access to transport are discussed, prior to applying a Chi-squared Automatic Interaction Detection (CHAID) method, in order to explore heterogeneity among the different social groups, in terms of local travelling. We found that nearly a quarter of all daily mobility in Barcelona is performed with a local trip, and that short trips are more frequently undertaken for personal purposes. Also, age, gender and access to private transport appear as significant factors. Overall, our results suggest that a proximity scale is being used by those groups with greater time–space constraints, such as working women or low income people without access to private vehicles, opening important implications on transport policy regarding the design of proximity-prone environments.     

Gender,Residential Location,and Household Travel: Empirical Findings from Low‐income Urban Settlements in Durban,South Africa

Abstract

Urban development and transport policies designed to improve the livelihoods of poor communities need to consider the particular needs of women to be effective. Gender roles are played out in a spatial world, and can thus be expected to vary across the urban landscape. The paper examines empirical relationships between spatial factors—in particular residential location within the city—and travel behaviour for men and women in a cross‐section of low‐income communities in a large metropolitan area in South Africa. Data from a comprehensive household survey show that locality has a significant influence on gender experiences of mobility. Gender differences are greatest in more distant, rural localities, although site‐specific characteristics such as walking access to social services, informal work, and small‐scale agriculture help alleviate women’s inequitable travel burdens. Central localities display the smallest differences between men and women’s travel habits, supporting the notion that the high access afforded by centrally located housing helps to promote the satisfaction of women’s daily needs as well as their strategic empowerment. Households in peri‐urban and peripheral localities suffer the highest travel burdens, having neither the high access of a central location nor the livelihoods‐enhancing amenities of a rural environment. Women bear a large part of this burden. Urban development strategies to benefit the urban poor while promoting gender equity are highlighted, including an added emphasis on the provision of social and educational infrastructure within closer proximity to peripheral residential areas, coupled with better pedestrian access.     

The Impacts of Ict on leisure Activities and Travel: A Conceptual Exploration

This paper offers a conceptual exploration of the potential impacts of ICTs on leisure activities and the associated travel. We start by discussing what leisure is and is not. We point out that the boundaries between leisure, mandatory, and maintenance activities are permeable, for three reasons: the multi-attribute nature of a single activity, the sequential interleaving of activity fragments, and the simultaneous conduct of multiple activities (multitasking). We then discuss four kinds of ways by which ICT can affect leisure activities and travel: the replacement of a traditional activity with an ICT counterpart, the generation of new ICT activities (that may displace other activities), the ICT-enabled reallocation of time to other activities, and ICT as a facilitator of leisure activities. We suggest 13 dimensions of leisure activities that are especially relevant to the issue of ICT impacts: location (in)dependence, mobility-based versus stationary, time (in)dependence, planning horizon, temporal structure and fragmentation, possible multitasking, solitary versus social activity, active versus passive participation, physical versus mental, equipment/media (in)dependence, informal versus formal arrangements required, motivation, and cost. The primary impact of ICT on leisure is to expand an individual’s choice set; however whether or not the new options will be chosen depends on the attributes of the activity (such as the 13 identified dimensions), as well as those of the individual. The potential transportation impacts when the new options are chosen are ambiguous.     

Modelling daily activity program generation considering within-day and day-to-day dynamics in activity-travel behaviour

This paper presents a comprehensive econometric modelling framework for daily activity program generation. It is for day-specific activity program generations of a week-long time span. Activity types considered are 15 generic categories of non-skeletal and flexible activities. Under the daily time budget and non-negativity of participation rate constraints, the models predict optimal sets of frequencies of the activities under consideration (given the average duration of each activity type). The daily time budget considers at-home basic needs and night sleep activities together as a composite activity. The concept of composite activity ensures the dynamics and continuity of time allocation and activity/travel behaviour by encapsulating altogether the activity types that are not of our direct interest in travel demand modelling. Workers’ total working hours (skeletal activity and not a part of the non-skeletal activity time budget) are considered as a variable in the models to accommodate the scheduling effects inside the generation model of non-skeletal activities. Incorporation of previous day’s total executed activities as variables introduces day-to-day dynamics into the activity program generation models. The possibility of zero frequency of any specific activity under consideration is ensured by the Kuhn-Tucker optimality conditions used for formulating the model structure. Models use the concept of random utility maximization approach to derive activity program set. Estimations of the empirical models are done using the 2002–2003 CHASE survey data set collected in Toronto.

Travel-based multitasking: review of the role of digital activities and connectivity

ABSTRACT

Travel-based multitasking, also referred to as travel time use, is now a well-established concept, whose existence is supported by the technological trajectories, with mobile information and communication technologies (ICT) and vehicle automation working together to allow travel time to be more productive and enjoyable. Despite existence of reviews of travel-time multitasking studies, the systematic overview of the role digital activities, i.e. those that necessarily require modern ICT equipment to participate, has been limited, often wrapped under the umbrella term “use of ICT”, potentially obscuring their complexity and sophistication. Similarly, the role of connectivity and its attributes, e.g. speed (bandwidth), reliability, price, ease of use, data allowance or security, deserves a more systematic overview given its key role in enabling digital online activities and hence the travel-based multitasking options. This paper provides a review of 77 empirical travel-based multitasking-studies that explored the role of digital activities or connectivity. In particular, the review discusses the existing typologies of digital activities, dividing them into hardware-centric, function-centric or a combination of both (mixed). Subsequently, key contributions are discussed with respect to the treatment of digital activities and connectivity and its attributes. Based on the review, it is possible to observe that the existing studies have looked only at a handful of rather restricted online activities that do not sufficiently capture the sophistication with which individuals interact with the virtual world nowadays. Furthermore, the role of connectivity, although deeply embedded in the “C” of the “ICT” concept, has not been looked at or modelled in any detail in studies related to travel time use or its quality. This existing shortcoming might have resulted in an insufficient understanding of the mechanisms driving travel time use, the associated experience indicators of customer satisfaction, productivity or the consequences for relative attractiveness of transport modes. All of these considerations remain, however, crucial for designing, appraising and operating transport infrastructure and services that are able to take the advantage of lifestyle digitisation to meet the increasing customer needs while also delivering broader economic, social benefits and possibly also environmental benefits.     

Time use in travel surveys and time use surveys – Two sides of the same coin?

An in-depth understanding of travel behaviour determinants, including the relationship to non-travel activities, is the foundation for modelling and policy making. National Travel Surveys (NTS) and time use surveys (TUS) are two major data sources for travel behaviour and activity participation. The aim of this paper is to systematically compare both survey types regarding travel activities and non-travel activities. The analyses are based on the German National Travel Survey and the German National Time Use Survey from 2002.The number of trips and daily travel time for mobile respondents were computed as the main travel estimates. The number of trips per person is higher in the German TUS when changes in location without a trip are included. Location changes without a trip are consecutive non-trip activities with different locations but without a trip in-between. The daily travel time is consistently higher in the German TUS. The main reason for this difference is the 10-min interval used. Differences in travel estimates between the German TUS and NTS result from several interaction effects. Activity time in NTS is comparable with TUS for subsistence activities.Our analyses confirm that both survey types have advantages and disadvantages. TUS provide reliable travel estimates. The number of trips even seems preferable to NTS if missed trips are properly identified and considered. Daily travel times are somewhat exaggerated due to the 10-min interval. The fixed time interval is the most important limitation of TUS data. The result is that trip times in TUS do not represent actual trip times very well and should be treated with caution.We can use NTS activity data for subsistence activities between the first trip and the last trip. This can potentially benefit activity-based approaches since most activities before the first trip and after the last trip are typical home-based activities which are rarely substituted by out-of-home activities.     

A structural equation model based analysis of non-workers’ activity-travel behaviour from a city of a developing country

This paper presents an empirical analysis of non-workers’ activity-travel behaviour from Bangalore city, India. The paper builds a causal model—to describe the relationships among socio-demographics, activity-participation, and travel behaviour of non-workers—following structural equation modelling methodology. The results indicate that in-home maintenance activity-duration drives the time allocation decisions of non-workers. The model also shows the presence of ‘time-budget’ effects i.e., excess travel time cuts into in-hhome discretionary activity duration, implying the trade-off between daily travel time and in-home discretionary activity duration. The out-of-home activity durations of non-workers are found to be insensitive to travel time—an important finding of this research. The model also suggests that mixed residential development reduce travel distance and indirectly contribute to more trips. An indirect effect of mixed residential development on daily travel distance offsets the direct effect, which leads to a limited total effect of this variable on travel distance. The basic model was expanded further by separating the time spent on others’ activity (children and elders) from in-home maintenance activity duration. The stable model reveals that the time spent on others’ activity also influences in-home and out-of-home activities, and travel behaviour. This indicates that the time spent on others’ activity is an important time allocation of its own.     

A comprehensive study of life course,cohort, and period effects on changes in travel mode use

This paper studies changes in people’s travel mode use from one year to the next. It is informed by three distinct discourses: travel behaviour change, the mobility biographies approach, and cohort analysis. The data used is the German Mobility Panel (GMP) 1994–2008 in which households and their members are asked three times in three subsequent years to report the trips they made over a week. The changes reported are regressed to key events over the life course, cohort effects and period effects, while various sociodemographic and spatial attributes are controlled. Due to the non-independent nature of panel observations, a cluster-robust regression approach is used. The findings suggest that behind the aggregate stability in travel mode use over time there is much change ‘under the surface’, induced by life course changes, individual and household sociodemographic, and spatial context. The changes found induced by life course related key events favour the notion of mobility biographies. However, taken over all key events seem to be relatively loosely associated with mode use changes. Nonetheless, various significant effects of baseline variables suggest that mode use may change even in the absence of a key event.     

A conceptual framework of individual activity program generation

The research in this paper attempts to better understand the process by which activities are generated at an individual level. Activity-based travel analyses have gained popularity in recent years because they recognize the complexity of activity behavior and view travel as a derivative of this behavior. Most activity-based studies have focused on the spatial and temporal linkage of trips; that is, the scheduling of activities. They consider the agenda of activities for participation, and associated attributes of the activity participation (such as mode to activity and location of activity performance), as predetermined. This paper develops a comprehensive conceptual framework of the relatively unexplored area of activity agenda generation. Such a framework will be valuable in empirical modeling of activity generation behavior. A subsequent paper focuses on translating a part of this conceptual framework into an empirical model.     

Discussing the “positive utilities” of autonomous vehicles: will travellers really use their time productively?

ABSTRACT

Autonomous vehicles (AVs) are expected to reshape travel behaviour and demand in part by enabling productive uses of travel time—a primary component of the “positive utility of travel” concept—thus reducing subjective values of travel time savings (VOT). Many studies from industry and academia have assumed significant increases in travel time use and reductions in VOT for AVs. In this position paper, I argue that AVs’ VOT impacts may be more modest than anticipated and derive from a different source. Vehicle designs and operations may limit activity engagement during travel, with AV users feeling more like car passengers than train riders. Furthermore, shared AVs may attenuate travel time use benefits, and productivity gains could be limited to long-distance trips. Although AV riders will likely have greater activity participation during travel, many in-vehicle activities today may be more about coping with commuting burdens than productively using travel time. Instead, VOT reductions may be more likely to arise from a different “positive utility”—subjective well-being improvements through reduced stresses of driving or the ability to relax and mentally transition. Given high uncertainty, further empirical research on the experiential, time use, and VOT impacts of AVs is needed.     

Impact of different shopping stages on shopping-related travel behaviour: analyses of the Netherlands Mobility Panel data

From the moment e-shopping emerged, there have been speculations about its impact on personal mobility. A fair amount of research has already been carried out on Internet shopping itself as well as on its consequences for mobility. Most studies focus on the overall impact of online shopping on personal mobility. However, little is known about how personal shopping mobility can be characterised when differentiating its constituent stages, being browsing/orienting, comparing, selecting and purchasing products, and how this is affected by e-shopping. This will be the main topic of this paper. We will investigate this using recently collected data from the Netherlands Mobility Panel [in Dutch: MobiliteitsPanel Nederland (MPN)]. It is the unique combination of reported shopping trips in the three-day travel diary, the large amount of personal and household characteristics combined with the detailed information from the e-shopping questionnaire that enables us to perform this research. Using factor analysis, we explore the underlying factors related to the browsing and selection behaviour prior to the purchase of a product. Using these factors as a starting point, we apply cluster analysis resulting in three homogeneous groups of shoppers with different pre-purchase shopping behaviour. The groups differ clearly with respect to personal and household characteristics, in the frequency with which they buy and sell products online and in their perception of (dis-)advantages of online shopping. Once relevant groups have been distinguished and characterised, differences in shopping-related mobility between them are studied in two different ways. Firstly, we analyse statements from shoppers on how their shopping-related mobility has changed. Secondly, we analyse shopping trips reported in the three-day travel diary. Only one group, which consists of shoppers that rely on the Internet to search for product information, compare prices and get new product ideas, states that their shopping-related travel behaviour has changed since they started shopping online. Approximately 50% of all shoppers experienced no difference in their shopping mobility. The analysis of actual shopping mobility using the travel diary data showed only minor differences in shopping-related travel behaviour between the identified groups. Finally, we fit a multi-variate linear regression model of shopping trip distance to determine if (e)-shopping characteristics influence trip distances. The frequency with which people shop online as well as some stated changes in shopping-related travel behaviour (shopping in a similar manner and shopping longer) turn out to influence non-grocery shopping trip distance. No significant influence could be found of shopping cluster membership on shopping trip distances.