Key factors contributing to crash severity at highway-rail grade crossings

The purpose of this paper is to develop and com- pare the preferred multinomial logit （MNL） and ordered logit （ORL） model in identifying factors that are important in making an injury severity difference and exploring the impact of such explanatory variables on three different severity levels of vehicle-related crashes at highway-rail grade crossings （HRGCs） in the United States. Vehicle-rail crash data on USDOT highway-rail crossing inventory and public crossing sites from 2005 to 2012 are used in this study. Preferred MNL and ORL models are developed and marginal effects are also calculated and compared. A majority of the variables have shown similar effects on the probability of the three different severity levels in both models. In addition, based on the Akaike information criterion, it is found that the MNL model is better than the ORL model in predicting the vehicle crash severity levels on HRGCs in this study. Therefore, the researchers recommend the use of MNL model in predicting severity levels of vehicle-rail crashes on HRGCs.

Impact of social capital on farmers' response to different policies for controlling agricultural non-point source pollution

Chinese society in rural areas is typically a geographically and genetically related society.Scattered farmers can be connected to form small groups through their social capital,which can affect farmers' agricultural activities in the process of controlling agricultural Non-point Source pollution.An ordered Logit model can be built to analyze the effects of social capital to farmers' responsive willingness to different measurements of controlling agricultural NPS pollution by using survey data in Shaanxi Province.This paper characterizes farmers' social capital in three dimensions:social trust,social participation and social network.The results indicated that farmers' social capital significantly affects farmers' response to different policies.When governments construct and implement policies to control agricultural NPS pollution,the effects of social capital need to be considered at same time with the effects of governmental supervision,market and education measurements.

Does Gender Affect Travelers' Intention to Use New Energy Autonomous Vehicles? Evidence from Beijing City, China

To explore the factors and paths that influence the willingness to use sharing new energy autonomous vehicles(SNEAVs), this paper incorporates the unified theory of acceptance and use of technology(UTAUT2) as the basic frameworks, with gender serving as a moderating variable. Seven psychological latent variables, including performance expectancy, social influence, hedonic motivation,price sensitivity, perceived risk, trust in technology, and innovativeness, are considered to examine their effects on behavioral intention. Quantitative data(n=1082) was collected via an online questionnaire in Beijing. The ordered logit model was used to preliminarily demonstrate the significant impact of gender, with further parameter fitting confirming the good fit of the psychological latent variable model. Path analysis results reveals that gender influences the willingness to use SNEAVs in multiple aspects. Specially, females are more significantly influenced by hedonic motivation, whereas males prioritize performance expectation. Furthermore, price sensitivity positively has a positive impact on male behavioral intention, but a negative effect on female behavioral intention. Additionally, trust in technology plays a more important role for women compared to men. These findings are crucial in promoting the development of SNEAVs.