Quantifying errors in travel time and cost by latent variables

Discrete choice models are a key technique for estimating the value of travel time (VTT). Often, stated choice data are used in which respondents are presented with trade-offs between travel time and travel cost and possibly additional attributes. There is a clear possibility that some respondents experience time constraints, leaving some of the presented options unfeasible. A model not incorporating information on these constraints would explain choices for faster and more expensive options as an indication that those respondents have a higher VTT when in reality they may be forced to select the more expensive option as a result of their personal constraints. This paper puts forward the hypothesis that this can have major impacts on findings in terms of heterogeneity in VTT measures. This paper examines via simulation the bias in VTT estimates and especially preference heterogeneity when such constraints are (not) accounted for. Empirical evidence is provided that preference heterogeneity is confounded with the travel budget impact on the availabilities of alternatives, and it is shown that there is a risk of producing biased estimates for appraisal VTT if studies do not explicitly model choice set formation. The inclusion of an opt-out alternative could be an effective measure to reduce the bias. This paper also explores the potential use of non-linear functional forms to capture the time budget impacts.

In MOH pharmacies, prescriptions for chronic medications are partially dispensed with a supply duration of 1 month, to ensure the quality use of medicines. Monthly visits may impose nontrivial travel time and costs on patients. This study aimed to assess travel time and costs to collect repeat prescriptions at district hospitals in Sabah. A cross-sectional study, with 310 respondents was recruited using convenient sampling, over 3 months (April to June 2019). The questionnaire was adapted from a study conducted in Denmark, which was pilot-tested before the main study. Data collected were analyzed using SPSS (version 18) and presented using descriptive statistics. A statistically significant difference was defined at p-value < 0.05. 310 participants responded in 6 district hospitals (Beluran Hospital, Kinabatangan Hospital, Beaufort Hospital, Kuala Penyu, Hospital, Ranau Hospital, Pitas Hospital) in Sabah. The results of this study suggested that for patients collecting repeat prescriptions at government hospitals in Sabah, the median travelling cost for a return trip was RM 8.00 (IQR RM 11.00), while the median travelling time for a return trip was 30 minutes (IQR 45 minutes). Overall, the reported median cost and time spent to collect repeat prescriptions were not surprising. Among the problems faced were the unavailability of a method to validate the travel time and cost estimates, and it was suspected that some respondents might have a lack of knowledge regarding travel costs. However, the detailed data on travel time fits well with expectations based on the relatively sparse distribution of healthcare facilities within a relatively large state of Sabah. This study was not powered to detect the social impact on patients in marginalized groups (high cost and lengthy time of travel), and future studies should focus on this section of the population, to review the current policy for this group of patiens.

Preferences of public transit commuters: Evidence from smart card data in Singapore

PurposeTertiary hospital utilization for patients with mild diseases creates inefficiencies in medical utilization for medical consumers and providers, collapses the healthcare delivery system, and has negative consequences for the public health system. This study aims to identify the factors that lead to the selection of tertiary hospitals and the medical needs of patients with mild diseases. We evaluate the value of using medical institutions by comparing and analyzing regional and individual patient characteristics.MethodsThe travel cost method based on the travel cost incurred according to the consumer’s temporal choice, was used to evaluate the medical use. We considered data from Ajou University Hospital from 2017 to 2022. The variables used for travel costs are travel costs, time costs, and medical costs. The Quantum Geographic Information System(QGIS) network analysis was used to calculate travel costs and time costs, and independent sample t-tests and analysis of variance (ANOVA) were used to compare the evaluated values between groups.ResultsThe analysis revealed that travel costs were the highest for patients with diabetes. Regarding personal characteristics, men exhibited higher rates than women, and individuals under 65 years of age and those receiving type 2 medical benefits demonstrated higher travel costs. Travel costs and outpatient visit rates for mild diseases exhibited a direct proportional relationship. We compared the total economic value assessed for each type of mild disease and found the highest value for diabetes patients with the highest number of outpatient visits.ConclusionThese findings highlight the importance of incorporating patient segmentation into policy formulation to alleviate the overcrowding of patients with mild diseases in tertiary care hospitals. Furthermore, they advocate adopting a primary care-centered approach to enhance the healthcare delivery system and address imbalances in community healthcare resources.

The value of travel time is an important element in cost-benefit analysis of transportation projects, by encapsulating the willingness to pay of the population for improvements in the transport system. Those values are typically obtained from mobility behavior data from revealed or stated preference surveys. Although short-term decisions are typically used for this purpose, a growing number of authors is arguing that long-term decisions might provide more meaningful values for the evaluation of transportation projects, as those decisions have a longer-lasting effect on the experienced travel times. This paper uses data which contains both short- and long-term experiments to investigate the impact of different time horizons on the valuation of time. Using a joint model including all short term, together with workplace choice situations, the differences in the valuation of time coming from different kinds of experiments are investigated. The results reveal difficulties to isolate the willingness to pay from other aspects of monetary compensation, such as income as a status or career progression symbol. The results confirm that the chosen time horizon has a significant effect on the valuation of travel time and cost. The richer data, compared to previous attempts at such an estimation, does reveal, however, potential pitfalls in the underlying theory, namely that there is a perfect substitution between travel costs and income. In particular, focusing on salary neutral situations instead of situations with salary gains changes the direction of the effect of long term decisions. Recommendations are derived for forthcoming studies.

Influence of pricing on mode choice decision in Jakarta: A random regret minimization model

Economic assessment of a Dynamic Autonomous Road Transit system for Singapore

Some insight into the benefits of regularly and frequently maintaining traffic signal timing within and across jurisdictional boundaries is provided. The rapidly growing Cranberry Township, located at the crossroads of two interstate highways (Pennsylvania Turnpike [Interstate-76] and Interstate-79) 20 miles north of Pittsburgh, Pennsylvania, is used as a case study. Environmental and economic costs due to the absence of monitoring and updating traffic signal timing are estimated. While traffic signal timing optimization and coordination is a cost effective strategy to reduce travel time and its consequential air emissions along corridors, implementing such timing plans is only effective at and around the time of implementation, while travel demand remains constant. As time passes, with the fluctuation of vehicular demands, especially in rapidly developing areas, timing plans need to be monitored and modified. In Cranberry Township such developments and travel demand fluctuations result in a significant increase in costs of travel (time and fuel) and external environmental costs. Estimates show that timing plans that were at their optimal level at the time of implementation, if left unmodified, result in an 18% increase in the cost of fuel, a 13% increase in the cost of travel time, and an 11% increase in the external environmental costs in less than two years.

Value of travel time and travel time reliability

Response time patterns in a stated choice experiment

Carpooling, as an emerging travel mode, has not yet been paid sufficient attention despite its merits of convenience, cost-efficiency, and sustainability. The studies of carpooling, especially on the factors influencing carpooling, are inadequate. To tackle this problem, what and how the factors influence travelers' mode choice are studied with a practical trial. Based on a qualitative survey, we found that the travel time, travel cost, safety, punctuality, comfort, social contact, and identity promotion are potential influencing factors. Then a stated preference (SP) survey is conducted to address the main factors influencing carpooling. Finally, three key factors (travel time, travel cost, and safety) are singled out and the interaction of travel time and travel cost are explored by a binary logit regression analysis, respectively. Following the findings of the main factors and their interaction, related suggestions are proposed to promote the future application of carpooling.

Valuation of Travel Time and Traveller Information in Multimodal Personal Travel under Uncertainty

270 Background: Cancer creates a tremendous financial burden. Cancer-related costs are categorized into direct, indirect and psychosocial costs. Although there have been many reports on medical care costs, which are direct, those on other costs are extremely scarce. We estimated travel time and costs required for cancer patients to receive outpatient treatment. Methods: We studied 524 cancer patients given anti-cancer treatment between February 2009 and December 2012 at the Outpatient Chemotherapy Center of Teikyo University Chiba Medical Center. Address data were extracted from Data Warehouse electronic medical records, and travel distance and time required for outpatient treatment were calculated via MapInfo and ACT Distance Calculator Package. Transportation costs were estimated on the basis of ¥274 (= $3.00) per kilometer. Results: Average round-trip travel distances, times, and costs by cancer type are shown below. Average round-trip travel distance, time, and cost for all patients were 26.7 km, 72.5 minutes, and ¥7,303 ($79.99), respectively. Conclusions: Cancer patients incurred a travel cost of approximately ¥4,000 to ¥9,000 ($40.00 to $100.00) for each outpatient treatment. With population aging, seniors living alone and senior households are increasing, and outpatient visits are becoming a common burden. [Table: see text]

The increasing societal cost of vehicle travel in urban networks is causing higher social and environmental impacts on road users and urban residents. The societal cost of travel can be reduced through implementation of more efficient traffic management solutions, deeper integration of connected vehicles in the traffic stream, and increased deployment of vehicle-to-infrastructure (V2I) systems. This work proposes an innovative traffic management solution, based on Urban Connected Intelligent Transport Systems. The solution dynamically manages traffic by controlling for speed and acceleration in connected vehicles through V2I to minimize societal cost in urban networks. This is achieved by minimizing all four components of societal cost of travel, i.e., traffic accidents, fuel consumption, pollutant emissions and travel time. By minimizing societal cost, this research contributes to safer, greener and more sustainable transport in urban networks, while reducing the adverse environmental and economic impact. Experimental and field data as well as data from simulation were used to test the proposed solution at an urban coastal area in Patras, Greece.

A prerequisite for any monetary estimation of economic losses arising from traffic congestion is a reliable estimate of the value of travel time. Although the available evidence from abroad reveals significant differences in the values of individual components of time travel, specific valuations of travel time are rather rare in the Czech Republic. The aim of this paper is to expand the data base in the Czech Republic by presenting selected estimates of the travel time components for Czech drivers and passengers. Specifically, we elaborate on the value of travel time and time spent in congestion for medium-long domestic routes (represented by the Prague-Brno route). The results of our valuation study (N = 602) show that the value of travel time spent in congestion is almost twice as high as the value of travel time in free-flow traffic and suggest that the reduction of congestion and of the variation in travel time in general will bring significant economic benefits compared to shortening travel time in free-flow traffic. This evidence confirms the importance of distinguishing between different components of travel time when assessing the benefits of transport infrastructures. Importantly, our estimates of the value of travel time are much lower than those officially endorsed by Czech Ministry of Transport (MoT) for analysing benefits of new transport infrastructure.