{"title":"Assessing travelers’ preferences for online bus-hailing service across various travel distances: Insights from Chinese metropolitan areas","authors":"","doi":"10.1016/j.tra.2024.104159","DOIUrl":null,"url":null,"abstract":"<div><p>This study conducts a stated preference survey to assess travelers’ preferences for online bus-hailing service across various travel distances in Chinese metropolitan areas. By collecting personal attributes, travel characteristics, and scenario variables (including fares, walking distance, waiting time, and travel time for various ground transportation services), we develop a travel mode choice model based on XGBoost and examine the positive and negative effects and elasticity of different influencing factors. Empirical results demonstrate that the XGBoost-based travel mode choice model performs best in predictive accuracy, proving its superior fitting capability. Meanwhile, travel distance is pivotal in determining travelers’ preferences. Short-distance travelers prioritize time efficiency, whereas as travel distance increases, travelers become less sensitive to time, and fares become the primary consideration. This shift provides service operators with opportunities to implement differentiated strategies. The remaining travel modes also significantly influence choice preferences, with travelers critically concerned about the time cost of regular bus service and highly sensitive to taxi/car-hailing service fares. Personal attributes and travel characteristics, such as gender, age, and the number of companions, also impact choice preferences, providing opportunities for service operators to offer personalized services. Elasticity analysis further confirms the role of each influencing factor in increasing the attractiveness of choosing online bus-hailing service. Ultimately, we derive significant insights at the planning level, including single-factor optimization and prioritizing optimization for different dual-factor combinations. These insights serve as a basis for urban managers to formulate and enhance online bus-hailing service, covering aspects such as fare incentive policies and route service frequencies.</p></div>","PeriodicalId":49421,"journal":{"name":"Transportation Research Part A-Policy and Practice","volume":null,"pages":null},"PeriodicalIF":6.3000,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Transportation Research Part A-Policy and Practice","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0965856424002076","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ECONOMICS","Score":null,"Total":0}
引用次数: 0
Abstract
This study conducts a stated preference survey to assess travelers’ preferences for online bus-hailing service across various travel distances in Chinese metropolitan areas. By collecting personal attributes, travel characteristics, and scenario variables (including fares, walking distance, waiting time, and travel time for various ground transportation services), we develop a travel mode choice model based on XGBoost and examine the positive and negative effects and elasticity of different influencing factors. Empirical results demonstrate that the XGBoost-based travel mode choice model performs best in predictive accuracy, proving its superior fitting capability. Meanwhile, travel distance is pivotal in determining travelers’ preferences. Short-distance travelers prioritize time efficiency, whereas as travel distance increases, travelers become less sensitive to time, and fares become the primary consideration. This shift provides service operators with opportunities to implement differentiated strategies. The remaining travel modes also significantly influence choice preferences, with travelers critically concerned about the time cost of regular bus service and highly sensitive to taxi/car-hailing service fares. Personal attributes and travel characteristics, such as gender, age, and the number of companions, also impact choice preferences, providing opportunities for service operators to offer personalized services. Elasticity analysis further confirms the role of each influencing factor in increasing the attractiveness of choosing online bus-hailing service. Ultimately, we derive significant insights at the planning level, including single-factor optimization and prioritizing optimization for different dual-factor combinations. These insights serve as a basis for urban managers to formulate and enhance online bus-hailing service, covering aspects such as fare incentive policies and route service frequencies.
期刊介绍：
Transportation Research: Part A contains papers of general interest in all passenger and freight transportation modes: policy analysis, formulation and evaluation; planning; interaction with the political, socioeconomic and physical environment; design, management and evaluation of transportation systems. Topics are approached from any discipline or perspective: economics, engineering, sociology, psychology, etc. Case studies, survey and expository papers are included, as are articles which contribute to unification of the field, or to an understanding of the comparative aspects of different systems. Papers which assess the scope for technological innovation within a social or political framework are also published. The journal is international, and places equal emphasis on the problems of industrialized and non-industrialized regions.
Part A''s aims and scope are complementary to Transportation Research Part B: Methodological, Part C: Emerging Technologies and Part D: Transport and Environment. Part E: Logistics and Transportation Review. Part F: Traffic Psychology and Behaviour. The complete set forms the most cohesive and comprehensive reference of current research in transportation science.
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