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Household members physically share various resources, such as their house, cars, etc. Consequently, models of mobility decisions ideally are models of family decision-making. To contribute to the further development of the relatively thin line of research on household decision-making in travel behavior analysis, a dynamic Bayesian network approach is suggested to investigate temporal interdependencies between various life course events within families. Results indicate that effects of child birth on residential mobility and car ownership change are much stronger than the effects on work mobility for both spouses in dual-worker households. Moreover, the probability of residential mobility and car ownership change strongly increases when both spouses have relatively long commuting times. However, in case only the husband faces excessive commuting time, households have a larger probability of moving to a new house or purchasing an additional car. In contrast, in case only the wife experiences an excessive commuting time, the wife is more likely to change job rather than the household choosing other actions to cope with the situation.

Exploring influencing factors of place attachment is important to understand individuals’ sense of belonging and adaptation in a new neighborhood, which is also important to an individual's well-being. Cities in China are expanding at a phenomenal pace and undergoing a rapid suburbanization. This is mainly achieved through large-scale appropriation and circulation of rural land in suburbs, leading to displacement of landless farmers and development of alternative housing. In the process of redeveloping suburbs, the market economy in China has led to a flourishing real estate market and many real-estate developers have actively participated in the construction of suburban commercial housing. Therefore, sub-urbanization induced residential mobility can be divided into resettlement of involuntary movers to replacement housing and relocation of voluntary movers to commercial housing. The aim of this study is to determine which factors in terms of household and neighborhood characteristics, type of residential mobility (voluntary vs. involuntary), neighborhood satisfaction, neighborhood adaptation and place attachment before the resettlement influence place attachment after the resettlement. This is done by a path analysis based on survey data collected in 2015 from a survey of 786 respondents in eight neighborhoods in Changchun, a city in China that is experiencing large-scale residential mobility to suburbs. The results indicate that type of residential mobility, personal social-demographics and neighborhood characteristics have direct and indirect effects on the place attachment after the resettlement, while, surprisingly, place attachment before the resettlement has no influence on the post place attachment. The post place attachment is influenced by personal social-demographics, such as age, gender, car ownership and income level. Regarding the effects of neighborhood characteristics the results show that only neighborhood social interactions and the housing space have effects on place attachment. Neighborhood adaptation and satisfaction are not only direct predictors of post place attachment, but also mediators between exogenous variables and post place attachment.

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Recently, regret-based choice models, which postulate that individuals systematically compare attribute values of pairs of alternatives in terms of the amount of regret that may be generated, and then choose the alternative that minimizes their anticipated regret, have attracted the attention of transportation researchers as an alternative to utility-maximizing models. Most studies have assumed that regret depends on attribute differences in objective, physical space. Perception is not taken into account. However, an overwhelming amount of empirical evidence suggests that the relationship between perceived and objective attributes is non-linear. Therefore, in the authors' previous work, the authors explored the predictive performance of random regret minimization models that incorporate the perception of attributes, based on the (generalized) Weber law. In this study, the authors expand their previous work by allowing asymmetric non-linear perception functions. The authors investigate the existence and nature of asymmetry for small and large attribute intensities. The proposed model specifications of the regret choice models are tested using two data sets. Estimation results and out-of-sample validation tests indicate that incorporating asymmetric perception functions of objective attribute differences significantly improves the predictive power of the considered regret-based choice models.

This paper introduces a two-stage model to extend the modeling of social influence in the context of sequential stated adaptation experiments, where an individual is requested to complete the same choice task twice, once before and once after knowing the choice of a social network member. The magnitude of social influence is made a function of individuals’ socio-demographics and the nature of the relationship with a certain social network member. To eliminate the influence of the structure of sequential experiments, two effects, labeled “choice consistency” and “similarity” are singled out. Choice consistency says individuals exhibit the tendency to make consistent choices in sequential choice tasks, while similarity says individuals are more likely to adopt the alternative chosen by the social network member if it shares a high degree of similarity with the one chosen by the individuals in the first stage. Choice of city trip itinerary is taken as an example to investigate the model validity. Results support the assumptions underlying the model.

This chapter provides an overview of Asian studies on transport and land use. The chapter consists of four sections. After the introduction, section 14.2 reviews empirical studies on the relationship between land use and transport. In particular, subsection 14.2.1 summarizes studies on the effects of transport on land use. This is followed by a review of transport effects on property prices in subsection 14.2.2. Then, section 14.3 reviews empirical studies of land use effects on transport, especially focusing on the built environment and travel behavior. Subsequently, section 14.4 reviews applications of integrated land use transportation models. Lastly, section 14.5 concludes our chapter.

This paper presents a tool for integrated imputation and annotation of GPS tracking data, Trace Annotator. The tool is designed to efficiently and effectively transform raw GPS data into segmented activity and travel data where transportation modes, travel purpose at destinations, time and route information related to the spatial and temporal profiles were automatically generated. Bayesian belief network and other main machine learning approaches have been incorporated. The tool has been empirically applied and validated in several national and international pilots., Adjunct Proceedings of the 14th International Conference on Location Based Services

This chapter reviews the inherited features of post-socialist cities from socialist times and their recent transformation towards the 'space of consumption', considers the basic approaches to study cities in urban sociology in relation to the changes in the organization of urban space. Primary focus is given to the specific characteristics of space-time behaviours: how the 'network society' appropriates and perceives public space. Indeed, the transition from state-organized top-down management to commodified consumption has brought significant changes within public space and spatial distribution of facilities. Globalization is understood as a socio-cultural phenomenon driven by the space-time compression effects and the 'dissembling' effects of the application of new transport and information and communications technology (ICT). Individual perception and the individualism of using public space offer a different perspective for the creation and the design of public space in the network city.

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This study addresses the so-called uncertainty problem due to measurement error in random utility and random regret choice models. Based on formal analysis and empirical comparison, we provide new insights about the uncertainty problem in discrete choice modeling. First, we formally show how measurement error affects the random regret model differently from the random utility model. Then, random measurement error is introduced into level-of-service variables and the effect of measurement error is analyzed by comparing the estimated parameters of the concerned choice models, before and after introducing measurement error. We argue that although measurement error leads to biased estimation results in both types of models, uncertainty tends to accumulate in random regret models because this model involves a comparison of alternatives. Therefore, input uncertainty tends to lead to larger bias in random regret models. Moreover, since random regret models assume semi-compensatory decision processes, bias in random utility models is homogenous across individuals and alternatives, while bias in random regret models is heterogeneous. Several approaches are discussed to overcome this uncertainty problem in random regret models.

This chapter explains and summarizes models of behavioral change and adaptation, which have received less application in the life choice analysis associated with urban policy. Related to various life choices, life trajectory events are major decisions with a relatively long-lasting impact, such as demographic events, job change and purchase of major resources such as a house and a car. These life trajectory events may co-vary over time and lead to dynamic changes in activity-travel repertoires. Such decision problems have hitherto been predominantly modeled in urban and transportation science using classic discrete choice models. However, because such decisions differ from daily choices, other modeling approaches may be more beneficial. The authors present discrete choice models with lifetime utility and social dynamics, attitudinal models, technology acceptance model, norm activation model, and value belief norm theory for modeling lifecycle decisions and/or lifecycle driven behavioral change.

Session: 510 Behavioral Dimensions of Travel Choice

This chapter investigates household time use behavior by especially focusing on timing decisions on interdependent daily activities. Timing decisions on various life choices have been unsatisfactorily presented in literature. At best, such timing decisions have been presented based on survival analysis, which has various attractive statistical features, however, ignores decision-making mechanisms. This chapter argues that the utility of activity participation and trip-making behavior changes over time, and timing decisions within a given period of time interact across activities/trips and across household members. This study derives the optimal timing functions for both nonshared and shared activities/trips by different household members, where interdependencies among activities/trips over time and household’s coupling constraints are endogenously represented. The applicability of the developed model is empirically examined. Behavioral implications of analysis results are finally discussed.

This editorial is the introduction to a special issue on smart cities. The concept of a smart city is not well-defined, yet expectations among urban planners and decision-makers are high. This special issue contains three papers that discuss three different manifestations of smart cities and the success—or lack of it—of the solutions discussed. The papers highlight some limitations of the concept of smart cities, but at the same time also pinpoint some potentially beneficial solutions.

This article investigates consumers' anticipation of other consumers' service time choices in capacity-constrained services and how this is affected by publicly announced access recommendations. Empirical results from an experiment with simulated congestion experiences show that the impact of consumers' anticipation of other consumers' service time choices is lower for first-time than for the repeated encounters. Despite consumers greater information need in first-time encounters, we predict that the impact of publicly announced access recommendations is lower in first-time than in repeated service encounters. The reason is that consumers have not yet learned how to take into account the impact of recommendations on other consumers' choices. However, we hypothesize that consumers do benefit from recommendations in that recommendations allow them to better anticipate other consumers' choices and are also able to learn about others' choices sooner than in case no recommendations are provided.Keywords: Services marketing, Service time choice, Congestion, Consumer decision making