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.     

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.     

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。     

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.     

Accommodating spatial correlation across choice alternatives in discrete choice models: an application to modeling residential location choice behavior

This paper presents a modeling methodology capable of accounting for spatial correlation across choice alternatives in discrete choice modeling applications. Many location choice (e.g., residential location, workplace location, destination location) modeling contexts involve choice sets where alternatives are spatially correlated with one another due to unobserved factors. In the presence of such spatial correlation, traditional discrete choice modeling methods that are often based on the assumption of independence among choice alternatives are not appropriate. In this paper, a Generalized Spatially Correlated Logit (GSCL) model that allows one to represent the degree of spatial correlation as a function of a multi-dimensional vector of attributes characterizing each pair of location choice alternatives is formulated and presented. The formulation of the GSCL model allows one to accommodate alternative correlation mechanisms rather than pre-imposing restrictive correlation assumptions on the location choice alternatives. The model is applied to the analysis of residential location choice behavior using a sample of households drawn from the 2000 San Francisco Bay Area Travel Survey (BATS) data set. Model estimation results obtained from the GSCL are compared against those obtained using the standard multinomial logit (MNL) model and the spatially correlated logit (SCL) model where only correlations across neighboring (or adjacent) alternatives are accommodated. Model findings suggest that there is significant spatial correlation across alternatives that do not share a common boundary, and that the GSCL offers the ability to more accurately capture spatial location choice behavior.     

Changing trip behavior in a higher education institution: The role of parking fees

Higher education institutions are major trip-generating locations and the transportation to and from them has negative environmental influences. To discourage car owners from solo driving and encourage them to use more environmentally friendly travel modes, it is important to understand what factors influence their travel mode choice. Using a discrete choice model, we examined the motivations to leave the car at home, with and without parking fee. Besides parking fees, we examined the effects of other variables known to predict commuting choice, such as time and social discomfort, pro-environmental attitudes, reduced vehicle maintenance expenses and awareness of alternative commuting options. Results show that adding a parking fee not only increased the tendency to leave the car at home, it also influenced the relative weight given to the considerations that determine to leave the car at home. Specifically, after the introduction of a parking fee, the previously significant impacts of pro-environmental attitudes and social discomfort on leaving the car at home became non-significant, and the impacts of other, more instrumental factors (e.g., time discomfort, costs related to car ownership and maintenance, time wasted searching for a parking space and in traffic jams) which were insignificant beforehand, became the significant predictors. Parking fees were found to be effective and can change to accommodate different policies (revenue collection, pollution reduction, and students’ discomfort). The implications of such a study are the trade-off between monetary (parking fee) and non-monetary variables to accommodate more sustainable traffic management.     

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.