期刊文献+

Measuring students’satisfaction levels for transit services:An application of latent class analysis

在线阅读 下载PDF
导出
摘要 Past studies have identified the general public’s level of satisfaction with the service attri-butes of conventional fixed-route transit and ridesharing services,but few have limited their focus to students.This study employs latent class cluster analysis(LCCA)to identify clusters of university students,based on their satisfaction levels of the attributes of con-ventional fixed-route and ridesharing services,and uses a latent class behavioral model of a sample of university students in Arlington,Texas to explore the heterogeneity of their preferences toward ridesharing services.The results indicate that younger-and lower-income populations are more likely to be satisfied with on-demand ridesharing services than older-and higher-income populations,females are more likely to be satisfied with ridesharing services than males,and domestic students are more likely to be satisfied with ridesharing services than international students.The outcomes of the study will provide transportation planners with new insights about the significance of sociodemographic fac-tors on the satisfaction level of those who use conventional transit and on-demand ridesharing services and will help them incorporate strategies that will make their services more attractive to their potential ridership.
出处 《International Journal of Transportation Science and Technology》 2024年第3期284-297,共14页 交通科学与技术(英文)
  • 相关文献

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部