调查乘客对交通服务质量偏好的异质性来源

IF 2 4区 工程技术 Q3 TRANSPORTATION
Hadi Gholi , Mohammad Kermanshah , Amir Reza Mamdoohi
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引用次数: 1

摘要

提高公共交通的服务质量对于保持现有用户的忠诚度和吸引新的旅客是必要的。过去的研究表明,用户对交通服务质量的偏好是异质性的,但对描述这种异质性的因素的认识尚未深入研究。本文旨在评估德黑兰普通公交系统中乘客对公交服务属性偏好的异质性来源。考虑了公交出行的四个属性,包括车内出行时间、车费、车辆拥挤程度和车头距。通过面对面访谈收集360名有工作目的的通勤者的陈述偏好(SP)数据。随机参数logit (RPL)模型考虑随机系数均值周围的异质性,表明异质性可以在一定程度上用观测特征来解释。这可以帮助交通运营商采取更有效的措施来改善服务方面。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Investigating the sources of heterogeneity in passengers’ preferences for transit service quality

Improving the service quality of public transport is necessary to maintain the loyalty of current users and attract new travelers. Past studies show that users’ preferences for transit service quality are heterogeneous, but recognizing the factors describing this heterogeneity has not been investigated in depth. This paper aims to evaluate the sources of heterogeneity in passengers’ preferences for service attributes of bus transit regarding the regular bus system in the city of Tehran. Four attributes of bus travel, including in-vehicle travel time, fare, vehicle crowding, and headway, were considered. Stated preference (SP) data of 360 commuters with work purpose was collected through face-to-face interviews. The random parameter logit (RPL) model, considering the heterogeneity around the mean of random coefficients, shows that heterogeneity can be explained to some extent by observed characteristics. It can be helpful for transit operators to adopt more efficient measures to improve service aspects.

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来源期刊
CiteScore
6.40
自引率
0.00%
发文量
29
审稿时长
26 days
期刊介绍: The Journal of Public Transportation, affiliated with the Center for Urban Transportation Research, is an international peer-reviewed open access journal focused on various forms of public transportation. It publishes original research from diverse academic disciplines, including engineering, economics, planning, and policy, emphasizing innovative solutions to transportation challenges. Content covers mobility services available to the general public, such as line-based services and shared fleets, offering insights beneficial to passengers, agencies, service providers, and communities.
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