Factors influencing the choice of shared bicycles and shared electric bikes in Beijing

China leads the world in both public bikeshare and private electric bike (e-bike) growth. Current trajectories indicate the viability of deploying large-scale shared e-bike (e-bikeshare) systems in China. We employ a stated preference survey and multinomial logit to model the factors influencing the choice to switch from an existing transportation mode to bikeshare or e-bikeshare in Beijing. Demand is influenced by distinct sets of factors: the bikeshare choice is most sensitive to measures of effort and comfort while the e-bikeshare choice is more sensitive to user heterogeneities. Bikeshare demand is strongly negatively impacted by trip distance, temperature, precipitation, and poor air quality. User demographics however do not factor strongly on the bikeshare choice, indicating the mode will draw users from across the social spectrum. The e-bikeshare choice is much more tolerant of trip distance, high temperatures and poor air quality, though precipitation is also a highly negative factor. User demographics do play a significant role in e-bikeshare demand. Analysis of impact to the existing transportation system finds that both bikeshare and e-bikeshare will tend to draw users away from the “unsheltered modes”, walk, bike, and e-bike. Although it is unclear if shared bikes are an attractive “first-and-last-mile solution”, it is clear that e-bikeshare is attractive as a bus replacement.     

Office location — city or suburbs?

Suburban offices constitute a growing proportion of the metropolitan office stock in Melbourne. The relocation of around 1700 Coles Myer employees from the Central Business District to Tooronga, 8.5 km south east from the GPO, is an example of office decentralisation. A study of the resultant impacts arising from the relocation has been conducted utilising a before-the-move and after-the-move survey of Coles Myer employees. Both surveys generated response rates in excess of 60%. Office relocation can have various short and long term impacts on employees and will influence decisions relating to residential location, car ownership and the resultant travel and activity patterns. It is not until these impacts are quantified that planners can gain acceptance for strategies designed to minimise the negative impacts associated with dispersed employment opportunities.This paper discuses the suburbanisation of office employment in Melbourne and studies the travel related effect on the employees, whose headoffice is relocated from the CAD to a suburban location. One of the great challenges for transport in the 90's will be the successful management of office location and the resultant impacts on travel.Abbreviations CAD Central Activities District; the CAD is defined as a slightly larger area than that previously referred to as the Central Business District (CBD)     

A review of separate and joint strategies for the use of data on revealed and stated choices

This paper examines recent developments in household travel surveys that collect data for use in transportation planning and modeling efforts. The paper then introduces the notion of a total survey design and elaborates on what is meant by this concept. This is done first in the context of standard surveys of revealed choices. The paper discusses aspects of content and respondent burden and illustrates the potential to reduce respondent burden through careful consideration of content, question design, and question ordering. The paper also explores some issues of survey "friendliness" particularly with respect to activity surveys versus time-use surveys, with some observations about the potential of time-use surveys to eliminate some of the burden and content problems of previous diary designs. The remainder of the paper concentrates on the issue of collecting stated-response data and examines two alternative methods for collection: simultaneous collection of the contextual information and "on-the-fly" development of the alternatives for the stated-response questions, or sequential collection of contextual data and development of the stated-response questions. The paper also addresses issues of respondent burden that arise in the administration of stated-response surveys. The paper concludes with exploration of some of the reasons for collecting stated-response data, with particular emphasis on the US situation. In conclusion, the paper stresses again the need for a total design concept for collection of stated-response data, as well as for the simpler collection of more standard revealed choice data.     

Investigating preference heterogeneity in Value of Time (VOT) and Value of Reliability (VOR) estimation for managed lanes

This paper presents an empirical study in investigating user heterogeneity of Value of Time (VOT) and Value of Reliability (VOR). Combined Revealed Preference (RP) and Stated Preference (SP) data were used to understand traveler choice behavior regarding the usage of managed lanes (MLs). The data were obtained from the South Florida Expressway Stated Preference Survey, which focused on automobile drivers who had traveled on the I-75, I-95, or SR 826 corridors in South Florida. Mixed logit modeling was applied and indicated an average value of $13.55 per hour for VOT and $16.13 per hour for VOR. Potential sources of heterogeneity in user sensitivities to time, reliability, and cost were identified and quantified by adding interaction effects of the variables in the mixed logit model. The findings indicated that various socioeconomic demographic characteristics and trip attributes contributed to the variations in VOT and VOR at different magnitudes. The results of this study contribute to a better understanding on what attributes lead to higher or lower VOT and VOR and to what extent. These findings can be incorporated into the demand forecasting process and lead to better estimates and enhanced analytical capabilities in various applications, such as toll feasibility studies, pricing strategy and policy evaluations, and impact analysis.     

Methodological challenges in modelling the choice of mode for a new travel alternative using binary stated choice data – The case of high speed rail in Norway

Binary stated choices between traveller’s current travel mode and a not-yet-existing mode might be used to build a forecasting model with all (current and future) travel alternatives. One challenge with this approach is the identification of the most appropriate inter-alternative error structure of the forecasting model.By critically assessing the practise of translating estimated group scale parameters into nest parameters, we illustrate the inherent limitations of such binary choice data. To overcome some of the problems, we use information from both stated and revealed choice data and propose a model with a cross-nested logit specification, which is estimated on the pooled data set.     

Would personal carbon trading reduce travel emissions more effectively than a carbon tax?

The application of personal carbon trading (PCT) to transport choices has recently been considered in the literature as a means of reducing CO₂ emissions. Its potential effectiveness in changing car travel behavior is compared to the conventional carbon tax (CT) by means of a stated preferences survey conducted among French drivers (N ∼ 300). We show evidence that PCT could effectively change travel behavior and hence reduce transport emissions from personal travel. There is however a definite reluctance to reduce car travel. We were unable to demonstrate any significant difference between the effectiveness of PCT and the CT with regard to changing travel behavior. However, in the experiment, the PCT scheme provided consistent results while this was not the case for the CT scheme. Further research is needed into the “social norm” conveyed by a personal emissions allowance.     

Modelling mode choice for freight transport using advanced choice experiments

In this paper we use advanced choice modelling techniques to analyse demand for freight transport in a context of modal choice. To this end, a stated preference (SP) survey was conducted in order to estimate freight shipper preferences for the main attributes that define the service offered by the different transport modes. From a methodological point of view, we focus on two critical issues in the construction of efficient choice experiments. Firstly, in obtaining good quality prior information about the parameters; and secondly, in the improved quality of the experimental data by tailoring a specific efficient design for every respondent in the sample.With these data, different mixed logit models incorporating panel correlation effects and accounting for systematic and random taste heterogeneity are estimated. For the best model specification we obtain the willingness to pay for improving the level of service and the elasticity of the choice probabilities for the different attributes. Our model provide interesting results that can be used to analyse the potential diversion of traffic from road (the current option) to alternative modes, rail or maritime, as well as to help in the obtaining of the modal distribution of commercial traffic between Spain and the European Union, currently passing through the Pyrenees.     

Drivers’ parking location choice under uncertain parking availability and search times: A stated preference experiment

To assess parking pricing policies and parking information and reservation systems, it is essential to understand how drivers choose their parking location. A key aspect is how drivers’ behave towards uncertainties towards associated search times and finding a vacant parking spot. This study presents the results from a stated preference experiment on the choice behaviour of drivers, in light of these uncertainties. The attribute set was selected based on a literature review, and appended with the probabilities of finding a vacant parking spot upon arrival and after 8 min (and initially also after 4 min, but later dropped to reduce the survey complexity). Efficient Designs were used to create the survey design, where two rounds of pilot studies were conducted to estimate prior coefficients. Data was successfully collected from 397 respondents. Various random utility maximisation (RUM) choice models were estimated, including multinomial logit, nested logit, and mixed logit, as well as models accounting for panel effects. These model analyses show how drivers appear to accept spending time on searching for a vacant parking spot, where parking availability after 8 min ranks second most important factor in determining drivers’ parking decisions, whilst parking availability upon arrival ranks fourth. Furthermore, the inclusion of heterogeneity in preferences and inter-driver differences is found to increase the predictive power of the parking location choice model. The study concludes with an outlook of how these insights into drivers’ parking behaviour can be incorporated into traffic assignment models and used to support parking systems.     

Hypothetical bias in Stated Choice Experiments: Is it a problem? And if so,how do we deal with it?

The extent to which Stated Choice (SC) experiments suffer from hypothetical bias continues to be a controversial topic in the literature. This research provides further evidence in this debate by examining the existence of hypothetical bias in a transport-related SC experiment. Data for this research were sourced from a University of Sydney study exploring the effect of exposure-based charging on motorist behaviour. The sample included 148 Sydney motorists who were recruited to take part in the 10-week GPS driving field study (Revealed Preference/RP data). In addition, participants were also required to complete an SC survey which was designed to mimic the RP decision context in order to capture what participants indicated they would do as opposed to what participants actually did in reaction to the charging regime.The current state of practice for measuring hypothetical bias in the literature is to compare aggregate differences in model outcomes using SC and RP data sources. Aggregate analysis is limited in its scope and does not allow for the calculation of the prevalence of hypothetical bias (i.e., how many participants are affected by hypothetical bias). This research is uniquely structured to allow for individual categorisation of hypothetical bias by comparing SC and RP data from the same sample for the direct purpose of investigating the prevalence of hypothetical bias. Furthermore, the extent to which mitigation techniques (cheap talk and certainty scales) influence hypothetical bias is also explored. The findings from this research show that the SC model estimates are prone to hypothetical bias and that the mitigation techniques have potential to compensate for this inherent bias.     

Applying measures of modelling quality to a national time series: a benchmark for transport demand models

ABSTRACT

In current urban planning practice, macroscopic transport demand and assignment models are essential for the evaluation of mid- and long-term land use developments and infrastructure investments. The credibility of their projections strongly depends on their ability to reproduce present day traffic volumes. Obviously, a simplified model of reality will display some shortcomings, and the effect of these is asserted by quality measures that quantify the divergence from observed traffic volumes. There is, however, only rough guidance regarding acceptable ranges of these measures. Most of the literature on this subject approach these ranges from below, by discussing measures attained by operational models and using these as a benchmark, or by using the adverse effects of modelling errors to derive a minimum quality level. On the contrary, this study suggests upper limits for quality measures by analysing year-on-year variations in traffic volumes that result from changing land use and infrastructure.