Adam Astrid Kemperman

Influences of Built Environment on Walking and Cycling by Latent Segments of Aging Population

Walking and bicycling are relatively easy ways for the growing group of older adults to be physically active. The built environment may facilitate or restrict participation in walking and bicycling trips. A study was done to describe aspects of participation in walking and bicycling activities and to explore their role for various segments of the aging population. Specifically, the effect of environmental characteristics, various types of land use, and degree of urbanization on participation in walking and bicycling, for both leisure and transportation, was examined. Detailed individual travel data were correlated with objectively defined environmental attributes. The results show that people make more walking trips in more highly urbanized areas, whereas they use their bikes more often in less-urbanized areas. A significant effect was found for the impact of total surface of recreation areas on both types of physical activity. Specifically, highly urbanized neighborhoods with a low percentage of recreation and green areas are related to physical inactivity. The study suggests that compact, high-density neighborhoods may not be a good urban design concept if health is considered.

Comparing first-time and repeat visitors activity patterns

This article compares activity patterns of first-time and repeat visitors in a theme park. A sequence alignment method and CHAID are used to classify the visitors with regard to their activity patterns and identify predictor variables. The results indicate that first-time and repeat visitors differ in their activity patterns in the park, specifically with respect to the order of activities chosen. First-time visitors follow a strict route in the park, while repeaters have a more diverse activity pattern. However, the difference between the two groups is reduced when first-time visitors use information about the available activities in the park.

Environmental Correlates of Active Travel Behavior of Children

This study explored the participation of children in walking and bicycling for transportation, school, and various leisure purposes, and the relation with social and physical environmental characteristics and sociodemographics. Detailed individual travel data, including all walking and bicycling trips from a random sample of 4,293 children in the primary-school-age category in the Netherlands were investigated. Specifically, a Bayesian belief network was proposed that derives and represents all direct and indirect relations between the variables. The participation in active travel behavior has a direct relationship with all trip characteristics such as travel time and distance, and trip purpose, and is related to the car possession of the household. The degree of urbanization also is an important explanatory variable for participation in walking and bicycling by children. All the other social and physical environmental characteristics have an indirect influence on travel mode choice.

Social Commitments and Activity-Travel Scheduling Decisions

Social activities have received only scant attention in activity-based analysis. These activities commonly have been considered as one coherent group or have been combined with other discrete activities. Because more knowledge about social activities and commitments is needed, several descriptive and explanatory analyses are presented to examine the differences in the scheduling of various social activities. Results indicate that different kinds of social commitments and activities show distinct scheduling patterns.

Incorporating variety seeking and seasonality in stated preference modeling of leisure trip destination choice : test of external validity

The results of a test to assess the external validity of a stated preference model of destination choice in the context of leisure trips are reported. This model differs from conventional stated preference models in transportation in that it incorporates variety seeking and seasonality in specification of the choice model. The results indicate that the model performed reasonably well; seasonality is predicted quite well, but in some specific situations the model overpredicts observed variety-seeking choices.

Analyzing heterogeneity and substitution in trip-making propensity to urban parks : a mixed logit model

The aim of this study is to describe and predict residents’ trip making propensity to urban parks. The parks are classified in four categories: local parks, neighborhood parks, district parks and city parks. Specifically, a mixed multinomial logit model is estimated from data collected from a sample of 991 households (1107 members) in the Eindhoven region in the Netherlands in 2002. The effects of household and individual characteristics and temporal aspects such as time of day, day of week and season are examined. The mixed logit model accommodates for individuals’ differences in trip making propensity to the various urban parks. Furthermore, a pattern of correlation across urban park types, and hence substitution is obtained. Results indicate that residents prefer the smaller, local and neighborhood, parks to the larger, district and city, parks for their leisure trips. In addition, there is heterogeneity in trip making propensity to the particular parks types, specifically with regard to the district parks. Moreover, the local and neighborhood parks are substitutes of each other while they are complements of the district park in terms of residents’ leisure trip behavior.

Facet-Based Analysis of Vacation Planning Processes: A Binary Mixed Logit Panel Model

This article documents the design and results of a study on vacation planning processes with a particular focus on aggregate relationships between the probability that a certain facet of the vacation decision has been decided at a particular point in time, as a function of lead time to the actual trip, life cycle characteristics, income, travel experience, and any other facet already being decided. A binary mixed logit panel model was formulated and estimated to examine the assumed relationships. The Dutch Continuous Vacation panel was used to collect the data. Results indicate that the closer to the actual date of the trip, the higher the probability of a facet being planned. Moreover, vacation facets are planned at different points in time. We also found differences in the level of planning for different life cycle groups, levels of income, and travel experience. A discussion of the limitations of the study and possible future research directions completes the article.

Social interaction location choice : a latent class modelling approach

Social contacts are an important aspect of an individuals quality of life. Social contacts take place at a certain time and location: Geography matters, for instance, at home or a work location or at different types of (local) facilities such as schools, shops, sports, and catering facilities. For urban planners, it is essential to know which locations provide opportunities for social interaction. As this knowledge is currently largely lacking, more empirical research is needed. The purpose of this study, therefore, is to analyze the diversity of participation in social activities at different locations and the relationship among social interaction location, sociodemographic characteristics, and characteristics of the residential environment. The analyses are based on two-day social interaction diary data that were collected in 2008 among 747 respondents living in the Eindhoven region in The Netherlands. A latent class multinomial logit model is used to segment respondents in terms of their social activity location choices. The article reports findings of several descriptive analyses and the latent class model. Four latent classes are identified, showing different patterns in choices for social activity locations. Latent class membership can be explained by household and personal time-use characteristics (e.g., gender, age, household type, number of face-to-face social interactions, frequency of contact with neighbors), as well as characteristics of the residential environment (e.g., urban density, distance to several facilities, and satisfaction with local facilities). The findings could provide useful information for local governments and planners regarding the importance of public facilities for social interaction of various segments of the population to support individual well-being and neighborhood livability.

Car Drivers' Compliance with Route Advice and Willingness to Choose Socially Desirable Routes

This study describes the results of a stated choice experiment conducted to analyze route choice behavior of car drivers under the influence of advice and feedback on environmental consequences of their trips. Framing of the route advice is varied in regard to the goal of the agency providing the advice (system or individual optimality) and extent to which it is generic or tailored to the specific preferences of the person. Findings suggest that under conditions of rich information about the attributes of choice alternatives, advice is discarded when it is supposed to serve the drivers own interests, and information allows the individuals to evaluate outcomes independently, but advice is taken into account when it is said to serve traffic management objectives. In line with expectations, the effect of advice is larger when it is labeled as personal compared with when it is labeled as generic. Another finding is that the effect of advice on evaluations of route alternatives is not uniform across attributes. Whereas some attributes become suppressed in the evaluation, others become more salient. The study further provides evidence that travelers are willing to trade social objectives against individual-level objectives. Implications of these findings for the design and use of travel information systems as an instrument for traffic management are discussed and problems for future research are identified.

A Personalised Recommender System for Tourists on City Trips: Concepts and Implementation

In this paper we introduce a new recommender system for urban tourists. The goal of the system is to enrich tourists’ experience by offering them personalised tour recommendations tailored to their dynamic user profiles. Particular attention in the proposed approach is paid to the influence of basic leisure needs of an individual, which include new experiences, entertainment, being in open area, relaxation, physical exercise, and socialising, on the tour composition. These needs tend to be dynamic and give rise to saturation effects and variety seeking behaviour. The system is developed as part of the larger c-Space framework, in which a number of technologies, such as projective augmented reality, a newly proposed near real-time 4D dynamic scene reconstruction, and affective computing, are brought together and used to enrich experiences of users in their interactions with built environments. The paper describes the main concepts of the recommender system and its implementation in the specified context of the city of Trento, Italy.