Multilevel structural equation modeling of willingness-to-pay for fatality risk reduction: perspectives of driver and district levels.

Road accidents remain a serious problem and directly affect drivers. Therefore, the perspectives of drivers are important in improving road safety. The objectives of this study are to empirically examine damage due to road accidents using the willingness-to-pay (WTP) approach and to analyze the factors that influence WTP at the driver and district levels. This study obtained data on WTP derived from car drivers across Thailand, which covers 96 districts. The value of statistical life was 824,344 USD per fatality (2,296 million USD annually). The results of Multilevel Structural Equation Modeling revealed a statistically important insight. At the driver level, the Health Belief Model and sociodemographic exert influence on the intention to pay. The demographic factor that has the greatest influence on perceived risk and leads to a high intention to pay is the working age group (γ = 0.826). However, when considering the HBM, perceived susceptibility (γ = 0.901) emerges as the most valuable factor influencing drivers' concerns about road accidents. On the other hand, district-level factors have a negative influence on the intention to pay for road safety measures. Among these factors, the law enforcement (γ = -0.555) practices implemented by local authorities have the most significant impact on drivers' perspectives and intentions regarding WTP. This finding can be used as a guideline for budget allocation and policy recommendation for policymakers in improving road safety according to the area contexts.

Examining the Impact of Service Quality on Passengers' Intentions to Utilize Rail Transport in the Post-Pandemic Era: An Integrated Approach of SERVQUAL and Health Belief Model.

The COVID-19 pandemic has significantly disrupted railway transportation in developing countries, resulting in reduced passenger demand and economic activity. As a result of the pandemic effect, there is an increased focus on health and safety among potential passengers. To address this issue, the present study aimed to investigate the fundamental factors that contribute to railway transportation service quality (SERVQUAL) and the intention to use intercity train services in Thailand using the health belief model (HBM), with 1600 passenger participants using structural equation modeling (SEM). The findings demonstrated that train operators' service standards remain vital to passengers, and the HBM had a statistically significant impact on shaping passengers' intentions to use train services after an epidemic. These results can inform rail agencies and health authorities when developing policies and strategies to prioritize both business and passenger safety on intercity trains.

Temporal instability and differences in injury severity between restrained and unrestrained drivers in speeding-related crashes.

Upon detecting a crash impact, the vehicle restraint system locks the driver in place. However, external factors such as speeding, crash mechanisms, roadway attributes, vehicle type, and the surrounding environment typically contribute to the driver being jostled within the vehicle. As a result, it is crucial to model unrestrained and restrained drivers separately to reveal the true impact of the restraint system and other factors on driver injury severities. This paper aims to explore the differences in factors affecting injury severity for seatbelt-restrained and unrestrained drivers involved in speeding-related crashes while accounting for temporal instability in the investigation. Utilizing crash data from Thailand between 2012 and 2017, mixed logit models with heterogeneity in means and variances were employed to account for multi-layered unobserved heterogeneity. For restrained drivers, the risk of fatal or severe crashes was positively associated with factors such as male drivers, alcohol influence, flush/barrier median roadways, sloped roadways, vans, running off the roadway without roadside guardrails, and nighttime on unlit or lit roads. For unrestrained drivers, the likelihood of fatal or severe injuries increased in crashes involving older drivers, alcohol influence, raised or depressed median roadways, four-lane roadways, passenger cars, running off the roadway without roadside guardrails, and crashes occurring in rainy conditions. The out-of-sample prediction simulation results are particularly significant, as they show the maximum safety benefits achievable solely by using a vehicle's seatbelt system. Likelihood ratio test and predictive comparison findings highlight the considerable combined impact of temporal instability and the non-transferability of restrained and unrestrained driver injury severities across the periods studied. This finding also demonstrates a potential reduction in severe and fatal injury rates by simply replicating restrained driver conditions. The findings should be of value to policymakers, decision-makers, and highway engineers when developing potential countermeasures to improve driver safety and reduce the frequency of severe and fatal speeding-related single-vehicle crashes.

Correlated random parameters model with heterogeneity in means for analysis of factors affecting the perceived value of road accidents and travel time.

Road safety funding and management have become important issues in improving the quality of life of road users and there is evidence of a difference in driving behavior and the factor of road use between urban and rural areas, which is, in turn, reflected in different road safety evaluations. The purpose of this study is to assess the financial losses caused by road accidents on Thailand's highways and the related factors empirically, deploying the willingness-to-pay (WTP) approach. Data were obtained from 640 urban and 960 rural car drivers using a stated choice questionnaire and face-to-face interviews. This study used Correlated Random Parameters Binary Logit with Heterogeneity in Means (CRPBLHM) approach to analyze factors affecting WTP. According to the results, the value of a statistical life and injury for urban drivers was 1.63 times higher than that for rural drivers, and the value of travel time reduction per hour for urban drivers is âˆ¼1.14 times higher than that found for rural drivers. Furthermore, the results of the CRPBLHM model reported that there are significant differences between urban and rural drivers' safety intentions and WTP. In the urban model, it was found that driving behavior (ticket, seatbelts, and speed) and weekday trips significantly increase the WTP, whereas household size and gender are unobserved characteristics among drivers. The rural model revealed that a driver's education (bachelor's and master's degrees held), and a necessary trip were significantly associated with drivers' valuation of safety; moreover, it was found that household size, sole earner status, own accident, in possession of a doctoral degree, and being young were significant in acting as unobserved characteristics. The results demonstrated differences in the value of road safety and unobserved heterogeneity among drivers, which influence risk perception and valuation with reference to the area context. Relevant agencies can use the results as a guideline for budget allocation and practical policy-related road safety management.

Influence of Psychological Perspectives and Demographics on Drivers' Valuation of Road Accidents: A Combination of Confirmatory Factor Analysis and Preference Heterogeneity Model.

Property damage and loss from road traffic accidents are a major concern in developing countries; thus, studies on accident damage in such countries may include more latent factors. This study aims to examine the effect of psychological perspectives and sociodemographic status on drivers' willingness-to-pay (WTP) for road accident risk reduction, using confirmatory factor analysis (CFA) and the random parameters multinomial logit model with heterogeneity in means and variances (RPMNLHMV). The CFA results from interviews with 1650 car drivers in Thailand demonstrate that concepts of the theory of planned behavior and health access process approach are key factors for describing drivers' behavioral intention and WTP. The RPMNLHMV results indicate that drivers' demographics affected drivers' WTP to reduce road accidents, and psychological perspectives were also found to have an influence on WTP. The results also reveal unobserved characteristics that could affect drivers' WTP. The study concludes that ignoring unobserved heterogeneity in studies on WTP to reduce road accidents can lead to biased results and neglect important influential factors. The methodological approaches applied herein offer another layer of insight into unobserved characteristics in road accident valuation. These findings could be used to provide relevant authorities practical insights for policy development on road accident mitigation and road safety education programs in accordance with drivers' characteristics.

Factors influencing willingness to pay for accident risk reduction among personal car drivers in Thailand.

Thailand ranks near the top for the road accident fatality rate worldwide, and more and more vehicles are being registered in Thailand every year. Obtaining the opinions of road commuters may help us reduce road accidents in Thailand. This study seeks to understand damage value in road accidents for personal car drivers in Thailand, using the willingness to pay approach and establishing factors affecting willingness to pay with the theory of planned behavior (TPB). This study obtained data using questionnaires in face-to-face interviews with 1,650 personal cars drivers in Thailand. The average willingness to pay (WTP) for 50% fatality or injury reduction was 23.00 baht/person/50 km trip (US $0.74/person/50 km trip). We obtained the value of statistical life (VSL), assessing this to fall between US $815,385 and US $872,942, and the value of statistical injury (VSI), between US $150,059 and US $160,652. Overall, national damage was assessed at US $4,701,981,170 annually. According to the analysis of factors affecting WTP, TPB comprises four factors, namely, driver attitude, subjective norm, perceived behavioral control, and behavioral intention. Analysis using structural equation modeling (SEM) found all mentioned factors were relevant and positively influenced personal car drivers' WTP in Thailand, with a statistical significance at a 99% confidence interval (p < 0.01). This study can develop recommendations for relevant organizations to analyze the results as part of considerations regarding budget allocation and developments on road safety policy due to driver attitude as important as environmental factors or any other factors.