Understanding how various factors influence travel satisfaction can assist in traffic policy-making.In the study,it is aimed to develop innovative urban resident travel satisfaction evaluation models by building a com...Understanding how various factors influence travel satisfaction can assist in traffic policy-making.In the study,it is aimed to develop innovative urban resident travel satisfaction evaluation models by building a comprehensive travel satisfaction evaluation index system and considering the asymmetric traffic flow and difference in travel time urgency during the morning and evening peak hours.Both the internal factors reflecting resident-related characteristics including socio-economic attributes and travel characteristics,and the external factors reflecting road-related characteristics including traffic facilities,road traf-fic conditions,traffic environments,and service levels are considered.Then,for the morn-ing and evening peak hours,a structural equation model(SEM)to capture the intrinsic interactions between latent factors,and an ordered logit model(OLM)to describe the direct influencing factors of travel satisfaction considering its ordered nature are built respectively.Finally,the proposed models are examined with the travel survey data col-lected in the Yizhuang district of Beijing,China.The numerical results show that both the internal and external factors have significant impacts on travel satisfaction.The SEM models capture the interactions between latent variables such as the positive relation between traffic facilities and traffic environments.The OLM results show that most exter-nal factors except the satisfaction of the road obstacles have positive influences on travel satisfaction.The research findings provide a better understanding of the intrinsic interac-tions between latent variables and direct influencing factors of travel satisfaction and put forward guidance on how to improve travel satisfaction.展开更多
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 explo...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.展开更多
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' agricultu...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.展开更多
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 basi...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.展开更多
基金supported by the National Natural Science Foundation of China under contract 52072264.
文摘Understanding how various factors influence travel satisfaction can assist in traffic policy-making.In the study,it is aimed to develop innovative urban resident travel satisfaction evaluation models by building a comprehensive travel satisfaction evaluation index system and considering the asymmetric traffic flow and difference in travel time urgency during the morning and evening peak hours.Both the internal factors reflecting resident-related characteristics including socio-economic attributes and travel characteristics,and the external factors reflecting road-related characteristics including traffic facilities,road traf-fic conditions,traffic environments,and service levels are considered.Then,for the morn-ing and evening peak hours,a structural equation model(SEM)to capture the intrinsic interactions between latent factors,and an ordered logit model(OLM)to describe the direct influencing factors of travel satisfaction considering its ordered nature are built respectively.Finally,the proposed models are examined with the travel survey data col-lected in the Yizhuang district of Beijing,China.The numerical results show that both the internal and external factors have significant impacts on travel satisfaction.The SEM models capture the interactions between latent variables such as the positive relation between traffic facilities and traffic environments.The OLM results show that most exter-nal factors except the satisfaction of the road obstacles have positive influences on travel satisfaction.The research findings provide a better understanding of the intrinsic interac-tions between latent variables and direct influencing factors of travel satisfaction and put forward guidance on how to improve travel satisfaction.
文摘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.
基金supported by the National Social Sciences Foundation of China(14CJY046)Circular Economics Research Center of Sichuan Province(14SD0105)
文摘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.
基金Supported by the National Natural Science Foundation of China(71971020)。
文摘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.
