Investigating Rural Single-Vehicle Crash Severity by Vehicle Types Using Full Bayesian Spatial Random Parameters Logit Model

The effect of risk factors on crash severity varies across vehicle types. The objective of this study was to explore the risk factors associated with the severity of rural single-vehicle (SV) crashes. Four vehicle types including passenger car, motorcycle, pickup, and truck were considered. To synthetically accommodate unobserved heterogeneity and spatial correlation in crash data, a novel Bayesian spatial random parameters logit (SRP-logit) model is proposed. Rural SV crash data in Shandong Province were extracted to calibrate the model. Three traditional logit approaches—multinomial logit model, random parameter logit model, and random intercept logit model—were also established and compared with the proposed model. The results indicated that the SRP-logit model exhibits the best fit performance compared with other models, highlighting that simultaneously accommodating unobserved heterogeneity and spatial correlation is a promising modeling approach. Further, there is a significant positive correlation between weekend, dark (without street lighting) conditions, and collision with fixed object and severe crashes and a significant negative correlation between collision with pedestrians and severe crashes. The findings can provide valuable information for policy makers to improve traffic safety performance in rural areas.

Using Choice Experiments to Estimate the Value of Differentiated Cow's Milk in Puerto Rico

In Puerto Rico, we use a choice experiment method through in-person interviews to estimate consumer willingness to pay (WTP) for a half gallon of cow's milk that is produced locally, friendly to the environment and with ethics in animal management. The results from a random parameters logit model show that consumers are willing to pay a premium of up to 41% for differentiated milk, indicating a potential market for these products. We also find that consumer's income and education, and number of dependents affect WTP estimates. Implications for the development of differentiated milk products are discussed.