Day-to-day variability in travellers’ activity-travel patterns in the Jakarta metropolitan area

Using four consecutive days of SITRAMP 2004 data from the Jakarta metropolitan area (JMA), Indonesia, this study examines the interactions between individuals’ activity-travel parameters, given the variability in their daily constraints, resources, land use and road network conditions. While there have been a significant number of studies into day-to-day variability in travel behaviour in developed countries, this issue is rarely examined in developing countries. The results show that some activity-travel parameter interactions are similar to those produced by travellers from developed countries, while others differ. Household and individual characteristics are the most significant variables influencing the interactions between activity-travel parameters. Different groups of travellers exhibit different trade-off mechanisms. Further analyses of the stability of activity-travel patterns across different days are also provided. Daily commuting time and regular work and study commitments heavily shape workers’ and students’ flexibility in arranging their travel time and out-of-home time budget, leading to more stable daily activity-travel patterns than non-workers.     

On distinguishing between physically active and physically passive episodes and between travel and activity episodes: an analysis of weekend recreational participation in the San Francisco Bay area

This paper examines the out-of-home recreational episode participation of individuals over the weekend, with a specific focus on analyzing the determinants of participation in physically active versus physically passive pursuits and travel versus activity episodes (travel episodes correspond to recreational pursuits without any specific out-of-home location, such as walking, bicycling around the block, and joy-riding in a car, while activity episodes are pursued at a fixed out-of-home location, such as playing soccer at the soccer field and swimming at an aquatics center). The above disaggregation of recreational episodes facilitates the better analysis and modeling of activity-travel attributes, such as travel mode, episode duration, time-of-day of participation and location of participation. From a broader societal standpoint, the disaggregation of recreational episodes provides important information to encourage active participatory recreational pursuits, which can serve to relieve mental stress, improve the physical health of the population, and contribute to a socially vibrant society through increased interactions among individuals.The paper employs a mixed multinomial logit formulation for examining out-of-home recreational episode type participation using the 2000 San Francisco Bay area travel survey. A variety of variables, including individual and household sociodemographics, location attributes, and day of week and seasonal effects, are considered in the model specification. Individual-specific unobserved factors affecting the propensity to participate in different types of recreational episodes are also accommodated.     

The social dimension in action: A multilevel,personal networks model of social activity frequency between individuals

This paper presents a social activity-travel generation model, which explicitly incorporates the individual’s social dimension through the concept of personal networks, modeling the multilevel structure of social relations defined by these networks. The objective of the analysis is to study the relevance of the social dimension as a source of explanation of social activity-travel generation behavior between an individual and each relevant person of their social life. The paper uses a disaggregated perspective of personal networks, explicitly incorporating the characteristics of each network member as well as the characteristics of the overall social structure. Using an ordinal multilevel specification that accounts for the social network in which individuals are embedded, four dimensions are studied: personal characteristics, “with whom” activities are performed, social network composition and structure, and ICT (information and communication technology) interaction. The results show that a proper and complete understanding of social activity generation requires going beyond the individualistic paradigm, explicitly incorporating the role of the social dimension in the study of this decision-making process.     

Discretionary activity location choice: in-home or out-of-home?

This paper examines the location choice associated with discretionary activities (in-home vs. out-of-home). These substitution patterns are important in terms of travel demand as in-home activities do not necessitate travel while out-of-home activities incur travel. Mixed logit models are estimated using an activity dataset (2003 CHASE data) to analyze the factors associated with this choice at the individual activity-level. Results suggest that the attributes of an activity significantly contribute to understanding the likelihood of engaging in out-of-home activities. Activity type interaction terms reveal the varying influence that socio-demographics, activity attributes and travel have over four different activity types modeled. The results reveal that the location choice (in-home vs. out-of-home) is sensitive to travel characteristics. As the travel time and cost increases, an individual is less likely to engage in an activity out-of-home. Compared to passive and social activities, the location of active activities is more sensitive to changes in travel attributes.     

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.     

Urban activity pattern classification using topic models from online geo-location data

Location-based check-in services in various social media applications have enabled individuals to share their activity-related choices providing a new source of human activity data. Although geo-location data has the potential to infer multi-day patterns of individual activities, appropriate methodological approaches are needed. This paper presents a technique to analyze large-scale geo-location data from social media to infer individual activity patterns. A data-driven modeling approach, based on topic modeling, is proposed to classify patterns in individual activity choices. The model provides an activity generation mechanism which when combined with the data from traditional surveys is potentially a useful component of an activity-travel simulator. Using the model, aggregate patterns of users’ weekly activities are extracted from the data. The model is extended to also find user-specific activity patterns. We extend the model to account for missing activities (a major limitation of social media data) and demonstrate how information from activity-based diaries can be complemented with longitudinal geo-location information. This work provides foundational tools that can be used when geo-location data is available to predict disaggregate activity patterns.     

An empirical investigation into the time-use and activity patterns of dual-earner couples with and without young children

This paper examines the time-use patterns of adults in dual-earner households with and without children as a function of several individual and household socio-demographics and employment characteristics. A disaggregate activity purpose classification including both in-home and out-of-home activity pursuits is used because of the travel demand relevance of out-of-home pursuits, as well as to examine both mobility-related and general time-use related social exclusion and time poverty issues. The study uses the Nested Multiple Discrete Continuous Extreme Value (MDCNEV) model, which recognizes that time-decisions entail the choice of participating in one or more activity purposes along with the amount of time to invest in each chosen activity purpose, and allows generic correlation structures to account for common unobserved factors that might impact the choice of multiple alternatives. The 2010 American Time Use Survey (ATUS) data is used for the empirical analysis. A major finding of the study is that the presence of a child in dual-earner households not only leads to a reduction in in-home non-work activity participation (excluding child care activities) but also a substantially larger decrease in out-of-home non-work activity participation (excluding child care and shopping activities), suggesting a higher level of mobility-related social exclusion relative to overall time-use social exclusion. To summarize, the results in the paper underscore the importance of considering household structure in activity-based travel demand models, as well as re-designing work policies in the United States to facilitate a reduction in work-family conflict in dual-earner families.     

An activity-based approach of investigating travel behaviour of older people

The paper presents the results of an investigation on daily activity-travel scheduling behaviour of older people by using an advanced econometric model and a household travel survey, collected in the National Capital Region (NCR) of Canada in 2011. The activity-travel scheduling model considers a dynamic time–space constrained scheduling process. The key contribution of the paper is to reveal daily activity-travel scheduling behaviour through a comprehensive econometric framework. The resulting empirical model reveals many behavioural details. These include the role that income plays in moderating out-of-home time expenditure choices of older people. Older people in the highest and lowest income categories tend to have lower variations in time expenditure choices than those in middle-income categories. Overall, the time expenditure choices become more stable with increasing age, indicating that longer activity durations and lower activity frequency become more prevalent with increasing age. Daily activity type and location choices reveal a clear random utility-maximizing rational behaviour of older people. It is clear that increasing spatial accessibility to various activity locations is a crucial factor in defining daily out-of-home activity participation of older people. It is also clear that the diversity of out-of-home activity type choices reduces with increasing age and older people are more sensitive to auto travel time than to transit or non-motorized travel time.     

Scheduling decision styles on leisure and social activities

This paper investigates scheduling decisions associated with different types of leisure and social activities. Correlations among decisions and self-selection biases are explicitly investigated by using a sample selection model with a bivariate probit selection rule. A dataset collected in the first wave of a recent activity-travel scheduling panel survey carried out in Valencia (Spain) was used for empirical investigation. Significant differences are revealed in the empirical models for leisure and social activities in planning decisions, including different effects of temporal, companionship and demographic factors. The findings of the empirical model have important implications to travel behavior and activity-travel scheduling model developments. These results confirm the existence of different mechanisms underlying the activity-travel decision processes when leisure and social activities are of concerns. Results provide significant insights into enhancing the performances of an activity scheduling model by capturing accurate activity-travel scheduling tradeoffs in flexible activity types e.g. leisure and social activities.     

An integrated analysis of workers’ physically active activity and active travel choice behavior

Using Texas add-on sample data from the 2009 National Household Travel Survey, this study examines adult workers’ daily active choice decisions in the context of physical activity and attendant health benefits. The study looked at workers’ two choice behaviors: active activity and active travel. The first choice behavior, active activity, is developed as an ordered-response model based on the number of physically active recreational activities pursued during the workday. The second choice behavior, active travel, is developed as a binary-response model that examines workers’ active travel choices—whether or not the worker used any active mode of travel during the same workday. The study improves the understanding and knowledge of observed factors influencing workers’ physically active activity-travel behavior. The study also provides several observations regarding the role (and constraints) of employment in individuals’ active choices. Using a flexible copula modeling methodology, we explore the true correlation (or dependence) between the two behavior choices that could occur due to the presence of unobserved factors, suggesting a simultaneously low or simultaneously high propensity for being physically active across workers. The study findings suggest that transportation and public health policy makers can mutually benefit from encouraging workers to be physically active (from an activity and/or travel perspective). Overall, the study draws attention to the integrated nature of the public health and transportation fields, thereby providing a distinct view of active/inactive choice behavior. To our knowledge, this is the first study exploring a rich variety of components for workers’ active activity-travel behavior through a robust copula approach.     

An empirical analysis of children’s after school out-of-home activity-location engagement patterns and time allocation

Children are an often overlooked and understudied population group, whose travel needs are responsible for a significant number of trips made by a household. In addition, children’s travel and activity participation during the post-school period have direct implication for adults’ activity-travel patterns. A better understanding of children’s after school activity-travel patterns and the linkages between parents and children’s activity-travel needs is necessary for accurate prediction and forecasting of activity-based travel demand modeling systems. In this paper, data from the 2002 Child Development Supplement of the Panel Study of Income Dynamics is used to undertake a comprehensive assessment of the post-school out-of-home activity-location engagement patterns of children aged 5–17 years. Specifically, this research effort utilizes a multinomial logit model to analyze children’s post-school location patterns, and employs a multiple discrete–continuous extreme value model to study the propensity of children to participate in, and allocate time to, multiple activity episode purpose-location types during the after-school period. The results show that a wide variety of demographic, attitudinal, environmental, and others’ activity-travel pattern characteristics impact children’s after school activity engagement patterns.     

Modeling duration choice in space–time multi-state supernetworks for individual activity-travel scheduling

Multi-state supernetworks have been advanced recently for modeling individual activity-travel scheduling decisions. The main advantage is that multi-dimensional choice facets are modeled simultaneously within an integral framework, supporting systematic assessments of a large spectrum of policies and emerging modalities. However, duration choice of activities and home-stay has not been incorporated in this formalism yet. This study models duration choice in the state-of-the-art multi-state supernetworks. An activity link with flexible duration is transformed into a time-expanded bipartite network; a home location is transformed into multiple time-expanded locations. Along with these extensions, multi-state supernetworks can also be coherently expanded in space–time. The derived properties are that any path through a space–time supernetwork still represents a consistent activity-travel pattern, duration choice are explicitly associated with activity timing, duration and chain, and home-based tours are generated endogenously. A forward recursive formulation is proposed to find the optimal patterns with the optimal worst-case run-time complexity. Consequently, the trade-off between travel and time allocation to activities and home-stay can be systematically captured.     

Modeling household interactions in daily in-home and out-of-home maintenance activity participation

The activity travel patterns of individuals in a household are inter-related, and the realistic modeling of activity-travel behavior requires that these interdependencies be explicitly accommodated. This paper examines household interactions impacting weekday in-home and out-of-home maintenance activity generation in active, nuclear family, households. The in-home maintenance activity generation is modeled by examining the duration invested by the male and female household heads in household chores using a seemingly unrelated regression modeling system. The out-of-home maintenance activity generation is modeled in terms of the decision of the household to undertake shopping, allocation of the task to one or both household heads, and the duration of shopping for the person(s) allocated the responsibility. A joint mixed-logit hazard-duration model structure is developed and applied to the modeling of out-of-home maintenance activity generation. The results indicate that traditional gender roles continue to exist and, in particular, non-working women are more likely to share a large burden of the household maintenance tasks. The model for out-of-home maintenance activity generation indicates that joint activity participation in the case of shopping is motivated by resource (automobiles) constraints. Finally, women who have a higher propensity to shop are also found to be inherently more efficient shoppers.     

Relationship between well-being and daily time use of elderly: evidence from the disabilities and use of time survey

According to US Census Bureau, the number of individuals in the age group above 65 years is expected to increase by more than 100% from the year 2000 to 2030. It is anticipated that increasing elderly population will put unforeseen demands on the transportation infrastructure due to the atypical mobility and travel needs of the elderly. Consequently, transportation professionals have attempted to understand the travel behavior of the elderly including the trip frequency, trip distance and mode choice decisions. Majority of the research on elderly travel behavior have focused on the mobility outcomes with limited research into understanding the tradeoffs made by this population segment in terms of their in-home and out-of-home activity engagement choices. The goal of the current research is to contribute to this line of inquiry by simultaneously exploring the daily activity engagement choices of the elderly Americans including their in-home and out-of-home activity participation (what activities to pursue) and time alloocation (duration of each activity) decisions while accounting for the temporal constraints. Further, the study attempts to explore the relationship between physical and subjective well-being and daily activity engagement decisions of the elderly; where subjective well-being is derived from reported needs satisfaction with life and different domains of it. To this end, data from the Disabilities and Use of Time survey of Panel Study of Income Dynamics was used to estimate a panel version of MDCEV model. In addition to person- and household-level demographic variables, activity participation and time use choices of elderly were found to vary across different levels of reported physical and subjective well-being measures. The model estimation results were plausible and provide interesting insights into the activity engagement choices of the elderly with implications for transportation policy development. Among other socio-demographic variables, living arrangements (living with family versus in elderly homes) were found to have significant influence on how people participate into different in-home versus out-of-home activities. For example, elderly living in the elderly home were found to participate more into out-of-home activities compared to people living with families. Elderly with disabilities were found to compensate lower participation into out-of-home activities with more participation into in-home activities. Considerable heterogeneity was observed in time engagement behavior of the elderly across reported levels of satisfaction with finance, job and cognitive needs. For example, elderly expressing high satisfaction with job was found to spend less time in in-home social activities. Elderly reporting higher satisfaction with finance were found to spend more time into OH social and shopping activities.     

Effects of land-use transport scenarios on travel patterns: a multi-state supernetwork application

Understanding travellers’ response is essential to address policy questions arising from spatial and transport planning sectors. This paper demonstrates the usefulness of the multi-state supernetwork approach to investigate the effects of land-use transport scenarios on individuals’ travel patterns. In particular, it illustrates that multi-state supernetworks are capable of representing activity-travel patterns at a high level of detail, including the choice of mode, route, parking and activity location. Multi-faceted activity-travel preferences can be accommodated in supernetworks. Using a micro-simulation approach, the adaptation of individuals’ travel patterns to policies can be readily captured. The illustration concerns hypothetical land-use and transport scenarios for the city of Rotterdam (The Netherlands), focusing on accessibility changes, modal substitution and shift in the use of transport and location facilities.     

Analysis of within-household effects and between-household differences in maintenance activity allocation

This paper investigates the allocation of household individuals to out-of-home maintenance activities using the rich activity-travel diary data from the San Francisco Bay Area. Two inter-related decisions are considered in this context: (i) whether the given activity episode is performed individually (solo) or jointly, and (ii) the person who participates in the activity, if it is a solo activity. To account for the conditional nature of the solo activity person selection, a nested mixed logit modeling framework is proposed and implemented to jointly analyze person allocation for all maintenance activities performed by a household on a given day. The model is used to investigate within-household effects and between-household differences. The proposed model relaxes some important restrictions in person allocation models by accounting for various sources of correlations and relaxing the assumption of constant variance across households. The proposed model is used to analyze the differences in person allocation between different types of households. The results indicate that life-cycle and household role, income, gender, employment status, and several types of constraints (activities including cost, time-availability, vehicle-availability, coordination constraints, and child-care obligations) affect person allocation decisions in the context of maintenance activities. The empirical results indicate the presence of various sources of correlations across persons, over activities, and within-household that are significant. In addition, the data also provides evidence that the unobserved variances in person selection utilities are not constant across households. A better understanding of these within-household interactions and between-household differences may be used in activity-based simulation models and to develop more effective and focused demand management measures.     

Social networks,social influence and activity-travel behaviour: a review of models and empirical evidence

ABSTRACT

The study of social networks in activity-travel research has recently gained momentum because social activities and social influence were relatively poorly explained in activity-based models of travel demand. Over the last decade, many scholars have shown interest in identifying personal social networks that constitute an important source of explanation of activity-travel behaviour. This paper seeks to review two research streams: social networks and activity-travel behaviour, and social influence and travel decisions. We classify models, summarise empirical findings and discuss important issues that require further research.     

Women’s mode and trip structure choices in daily activity-travel: a developing country perspective

ABSTRACT

In this paper, we analyze the travel patterns of Iranian women, where typical patriarchal views and specific social and cultural norms may differ from the patterns of those in western societies. In addition to inherent psycho-physical gender differences, women in Iran can face special constraints forcing them not to be involved in all activity-travel patterns that people in developed countries usually undertake. We pay special attention to the role of marital and employment status on women’s activity-travel patterns. To this end, we develop a joint mode and daily activity pattern (DAP) discrete choice model, which is a two-level mixed nested Logit. The upper nest of the proposed model embodies women’s DAP choices, and the lower nest belongs to the mode choices. In this paper, we try to show how different factors in a patriarchal Muslim society like Iran affect or restrict women’s type and structure of activity-travel patterns.     

Investigating the temporal changes in the relationships between time spent on the internet and non-mandatory activity-travel time use

The amount of time we spend online has been increasing dramatically, influencing our daily travel and activity patterns. However, empirical studies on changes in the extent to which the amount of time spent online are related to changes in our activity and travel patterns are scarce, mainly due to a lack of available longitudinal or quasi-longitudinal data. This paper explores how the relationships between the time spent using the Internet, and the time spent on non-mandatory maintenance and leisure activities, have evolved over a decade. Maintenance activities include out-of-home activities such as shopping, banking, and doctor visits, while leisure activities include entertainment activities, visiting friends, sporting activities, and so forth. Our approach uses two datasets from two major cross-sectional surveys in Scotland, i.e. the 2005/06 Scottish Household Survey (SHS) and the 2015 Integrated Multimedia City Data (iMCD) Survey, which were similarly structured and formed. The multiple discrete–continuous extreme value (MDCEV) model and difference-in-differences (DD) estimation are applied and integrated to examine how the relationships between the time spent on the Internet and travel have changed over time and the direction and magnitude of the changes. Our findings suggest that the complementary associations between Internet use and individuals’ non-mandatory activity-travel time use are diminishing over time, whereas their substitutive associations are increasing. We additionally find that such temporal changes are significant in the case of those who spent moderate to high levels of time on the Internet (5 h or more online) per week.