A GPS data-based analysis of built environment influences on bicyclist route preferences

This study examines the effects of built environment features, including factors of land use and road network, on bicyclists' route preferences using the data from the city of Seattle. The bicycle routes are identified using a GPS dataset collected from a smartphone application named “CycleTracks.” The route choice set is generated using the labeling route approach, and the cost functions of route alternatives are based on principal component analyses. Then, two mixed logit models, focusing on random parameters and alternative-specific coefficients, respectively, are estimated to examine bicyclists' route choice. The major findings of this study are as follows: (1) the bicycle route choice involves the joint consideration of convenience, safety, and leisure; (2) most bicyclists prefer to cycle on shorter, flat, and well-planned bicycle facilities with slow road traffic; (3) some bicyclists prefer routes surrounded by mixed land use; (4) some bicyclists favor routes which are planted with street trees or installed with street lights; and (5) some bicyclists prefer routes along with city features. This analysis provides valuable insights into how well-planned land use and road network can facilitate efficient, safe, and enjoyable bicycling.     

Analysing bicycle-sharing system user destination choice preferences: Chicago’s Divvy system

In recent years, there has been increasing attention on bicycle-sharing systems (BSS) as a viable and sustainable mode of transportation for short trips. However, due to the relatively recent adoption of BSS, there is very little research exploring how people consider these systems within existing transportation options. Given recent BSS growth around the world, there is substantial interest in identifying contributing factors that encourage individuals to use these systems. The current study contributes to this growing literature by examining BSS behavior at the trip level to analyze bicyclists’ destination preferences. Specifically, we study the decision process involved in identifying destination locations after picking up a bicycle at a BSS station, using a random utility maximization approach in the form of a multinomial logit model (MNL). The quantitative frameworks developed have been estimated using 2013 data from the Chicago’s Divvy system. In our modeling effort, we distinguish between BSS users with annual membership and short-term customers with daily passes. The developed model should allow bicycle-sharing system operators to plan services more effectively by examining the impact of travel distance, land use, built environment, and access to public transportation infrastructure on users’ destination preferences. Using the estimated model, we generated utility profiles as a function of distance and various other attributes, allowing us to represent visually the trade-offs that individuals make in the decision process. To illustrate further the applicability of the proposed framework for planning purposes, destination station-choice probability prediction is undertaken.     

Catalysts and magnets: Built environment and bicycle commuting

What effects do bicycle infrastructure and the built environment have on people’s decisions to commute by bicycle? While many studies have considered this question, commonly employed methodologies fail to address the unique statistical challenge of modeling modes with small mode shares. Additionally, personal characteristics that are not adequately accounted for may lead to overestimation of built environment impacts.This study addresses these two key issues by using an ordered probit Heckman selection model to jointly estimate participation in and frequency of commuting by bicycle, controlling for demographics, residential preferences, and travel attitudes. The findings suggest a strong influence of attitudinal factors, with modest contributions of bicycle accessibility. Bicycle lanes act as “magnets” to attract bicyclists to a neighborhood, rather than being the “catalyst” that encourages non-bikers to shift modes. The results have implications for planners and policymakers attempting to increase bicycling mode share via the strategic infrastructure development.     

Children's school commuting in the Netherlands: Does it matter how urban form is incorporated in mode choice models?

Walking and cycling to school is environmentally sustainable and increases children's physical activity. Although it is known that the built environment influences children's travel behavior, there is scant knowledge of how urban form along children's commuting routes affects walking and cycling separately, or of how to incorporate urban form exposures in transport mode choice models. This research investigated (a) the associations between children's transport mode choice and urban form correlates en route, and (b) the consequences of different urban form operationalizations (i.e., individual variables, composite measure, and principal components [PCs]). Global Positioning System devices were used to track 623 trips to and from school made by Dutch children aged 6–11 years. Urban form exposures were derived with geographic information systems, and their relationships with mode choice were tested with mixed multinomial logit models in a cross-sectional research design. Differences between the number of associated urban form variables, their magnitudes, and their significance levels were found for both walking and cycling, independent of the operationalization. Urban form was most influential for walking, whereas distance-related effects were absorbed when modeled as PCs. The highest model fit was achieved through PCs; the composite measure resulted in the lowest fit. To maximize the effectiveness of planning and health interventions, walking and cycling must be targeted separately. Policymakers should avoid “one-fits-all policies,” which are deemed to be inefficient. Because urban form affects model interpretation and fit, careful attention should be paid to how urban form is modeled, and sensitivity analyses should be performed.     

The decision-making process of and the decisive factors in accommodation choice

This study examines tourists’ decision-making process of and highlights the decisive factors in accommodation choice, employing the discrete choice (multinomial logit and nested logit) models and using the international tourist data of Taiwan. The results of this study may be indicative of the hierarchical nature of tourists’ decision-making process of accommodation choice. In addition, we find that price is a significant factor in accommodation choice, whereas income has only limited explanatory power. The results also indicate that tourists with a longer length of stay tend to choose hotels of lower quality, and, in contrast, elder people prefer better accommodations.     

How do the effects of local built environment on household vehicle kilometers traveled vary across urban structural zones?

Many studies have examined the effects of the local built environment (LBE) on household car usage. However, it remains unclear how these effects vary across urban structural zones. This study examines the case of Shenzhen and employs a multigroup structural equation model to reveal the varying LBE effects among car-owning households in inner-city, inner-suburban, and outer-suburban zones. The empirical modeling results indicate that the distance from the residence to the city center and the work-home distance have the greatest influence on household vehicle kilometers traveled (VKT). Average household VKT decreases with the distance from the residence to the city center after it peaks at the threshold radius distance of 8–10 km to the city center. In general, dense, mixed, small-block land use patterns reduce household VKT. However, the magnitude and significance of the LBE effects on household VKT vary across urban structural zones. These findings suggest that land-use policies can be developed specifically for different urban structural zones to effectively decrease household VKT.     

The origin–destination airport choice for all-cargo aircraft operations in Europe

In this paper, we analyze the origin–destination airport choice for freighter operations of combination and all-cargo carriers in Europe. First, we discuss the choice process of airlines qualitatively. Next, using a stated choice experiment, we show that the presence of forwarders at an airport is the primary factor in explaining airlines’ choices, especially for airlines serving main airports. For airlines primarily serving regional airports, the possibility for night-time flights is most important. Finally, the presence of passenger operations at an airport is not a significant factor and the level of origin–destination demand is of limited importance.     

Determinants and spatial variability of after-school travel by teenagers

This research work targeted teenagers to investigate after-school travel patterns and factors affecting their modal choice characteristics in Okinawa, Japan, where teenagers are not allowed to drive. The analysis is based on the cross-sectional data collected for discrete choice modeling of students’ travel in the prefecture. In this study, high school students’ trips from school to home have been analysed using a multinomial logit model. This has revealed the impact of individual, modal, and spatial variables on the mode choice decisions and return trip patterns. A comparative analysis made of downtown and suburb schools exposed differences in travel patterns induced by spatial factors and some existing constraints in modal choice options.     

基于收益管理理论的铁路客运专线价格策略研究简

在我国高速铁路网快速发展的背景下,有必要对铁路客运网络与旅客出行行为的关系进行深入研究,为路网规划提供参考依据。基于路网规划阶段确定的包含高速铁路与普速铁路的网络布局结构特征,对铁路旅客出行路径的选择倾向进行研究,建立了用于反映铁路旅客出行路径选择倾向的多项Logit模型,提出了相应的铁路旅客出行路径搜索算法,通过算例分析,验证了模型与算法的有效性,并对铁路路网规划工作提出建议。