Publications

Does high-speed rail mitigate peak vacation car traffic to tourist city? Evidence from China

Published in , 2023

Tourist travel contributes greatly to transport problems in attractive tourist cities. To take full advantage of high-speed rail (HSR) for alleviating massive car traffic during the peak vacation period, this paper analyses the travel modes of domestic visitors to Shaoxing before and after the operation of HSR. Scenario-based comparison and a random-coefficients structure Mixed Logit (MXL) model with error components were adopted to analyze the travel mode change and the factors explaining tourists’ travel mode choices. Our findings show that the HSR modal share increased substantially at the expense of express buses, more than cars. Also, HSR was found to be less competitive than cars on toll-free days for medium short travel distances. The MXL model results indicate that HSR was more likely to be used over automobiles by young people, females, and one-destination travellers, for longer travel distances, and with high service frequency to Shaoxing. Besides, online booking services were highly associated with HSR use. Driving was favoured over HSR by higher income level groups, when travelling with family or friends, on toll-free national holidays. Current government policy to waive road tolls during the peak holiday period further induced car traffic to tourist cities. When individual taste was considered, tourists showed a similar preference in their valuation of the travel time variable, while were heterogenous in their preference for low per-distance cost. Our findings suggest that the adjustment of the road-toll policy, pre-booking design for targeted tourists, and measures to reduce the total travel time of HSR should be considered to promote HSR as well as impede the use of cars during peak periods. This study offers empirical evidence of achieving effective travel demand management and reducing car dependence through HSR and complementary measures.

Understanding patients heterogeneity in healthcare travel and hospital choice - A latent class analysis with covariates

Published in , 2023

Access to health care is key to well-being, and it is increasingly clear that aggregated accessibility analysis is hard to reflect people’s actual healthcare behaviour. This paper employs a patient-based healthcare travel survey to obtain a nuanced picture of how healthcare travel varies across patients. The existing literature shows transportation is an essential factor in accessing health care; however, most studies focus on separate healthcare travel mode choices or hospital choices for certain segments of patients, making it difficult to derive clear profiles of patients. Also, the attitudinal factors in healthcare travel have long been neglected. This research explores the joint hospital choice and travel behaviour of patients. We conducted an online survey with patients in Shanghai to identify the heterogeneity in healthcare travel behaviour and hospital choice. A latent class model with covariates is adopted to identify different patient types that exhibited distinct hospital choices and healthcare travel behaviour. Attitudinal factors are included in our model to form clear-separated clusters. Four categories of patients are identified: public transit patients, car-oriented patients, near-hospital patients, and non-downtown hospital patients, which differ in sociodemographic characteristics, healthcare-seeking behaviour, and public transit accessibility. Our research shows that a substantial share of non-downtown hospital patients should not be underestimated in healthcare travel demand analysis. The behaviour of public transit and non-downtown patients requires improvement of quality and public transit accessibility in non-downtown tertiary hospitals. Our study contributes to a better understanding of the market segments of patients and tailored healthcare and transport policies to meet patient healthcare travel demand.

The Impact of HSR on Same-Day Intercity Mobility: Evidence from the Yangtze River Delta Region

Published in , 2023

One objective of China’s High-speed rail (HSR) development is to promote regional cohesion, which can be reflected by the flow of people between city pairs. As a fast-speed intercity transport mode, same-day intercity mobility has been regarded as an essential measurement for regional cohesion and transport integration. The reduced time by HSR has redefined the business and commute trips which highlights time efficiency. Due to the difficulty in obtaining large samples of data for such trips, we adopted mobile phone data to detect and analyze the spatial distribution and travel behaviour characteristics of same-day return travellers. The efficiency analysis measured by total travel time between city pairs indicates that HSR is less competitive with cars within 300 km for same-day return trips. The variance in HSR passengers’ travel time over the same distances could be due to no direct services and the time required for access/egress. Using a 20-week mobile phone data, we adopted a rule-based method for detecting intercity travellers based on their temporal and spatial geographic locations. Results showed that most travellers travelled within 3–3.5 h, and few conducted a same-day return trip regularly. GDP, service frequency, and distance between origin and destination have been examined to explain the mobility of same-day return travel. The findings of our paper are expected to improve our understanding of same-day return travel behaviour and promote HSR travel for efficient round trips.

Exploring the choice between in-store versus online grocery shopping through an application of Semi-Compensatory Independent Availability Logit (SCIAL) model with latent variables

Published in , 2022

This paper examines individuals’ choice of in-store and online grocery shopping channels using stated preference (SP) choice experiments. The study uses 1,391 records from a stated preference choice experiment in the Greater Toronto Area (GTA), Canada. It applies a Semi-Compensatory Independent Availability Logit (SCIAL) Model with latent variables. The methodology accounts for semi-compensatory choice behaviour through probabilistic choice set formation considering effects from socioeconomic and psychological variables. This study demonstrates the advantage of considering probabilistic choice set formation and semi-compensatory behaviour in modelling the adoption of innovative products. Empirical results reveal that shoppers demonstrated similar myopic behaviours once they firmly considered in-store grocery and subscribed to free delivery services in their choice sets. They are equally likely to choose both channels without careful comparison to alternative channels once they firmly consider both channels in the choice set. However, considering the latter in choice sets is much costlier than in-store shopping. Therefore, in-store grocery shopping will still dominate the grocery shopping channel unless all home delivery services become free. Moreover, grocery shoppers value same-day delivery service. For typical delivery services charged between $4 and $20 in the GTA, Canada, grocery shoppers are willing to pay between $3.91 and $8.44 for same-day delivery. The latent variable describing shoppers’ perceived pandemic fear significantly contributes to the choice set inclusion probability of in-store grocery pick-up services, but the effect is not significant for other home delivery channels. This highlights heterogeneity in grocery shoppers’ choice behaviour within the online channel.