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Unraveling the travel patterns of ride-hailing users: A latent class cluster analysis across income groups in Yogyakarta, Indonesia
Travel Behaviour and Society ( IF 5.1 ) Pub Date : 2024-05-24 , DOI: 10.1016/j.tbs.2024.100836
Muchlis Muchlisin , Jaime Soza-Parra , Yusak O. Susilo , Dick Ettema

This study provides valuable insights into ride-hailing trip patterns among various income groups, including lower-income groups and those living below the poverty line, groups often overlooked in previous research. Using latent class cluster analysis (LCCA) based on a survey in Yogyakarta Province, Indonesia, we examine how variations in trip pattern characteristics are influenced by socio-demographics, household characteristics, and travel-related attitudes toward ride-hailing usage. Our results establish that six distinct clusters representing different ride-hailing travel patterns can be identified. We found dominant clusters for short and less expensive trips using motorcycle-based ride-hailing services (RH MC). In contrast, longer and more expensive trips are associated with car-based ride-hailing (RH CAR). Moreover, ride-hailing plays an important role in essential trips such as returning home, commuting, and maintenance activities, highlighting its importance in addressing transportation challenges, particularly in regions with limited public transportation access. Lower-income individuals and those living in poverty tend to use ride-hailing primarily for shorter and cheaper trips with RH MC, while those from higher-income brackets utilize it for a broader range of purposes. These findings highlight the diverse effects of ride-hailing across income groups and suggest the potential for ride-hailing to enhance accessibility for low-income individuals in Indonesia. We propose policy recommendations to alleviate transport poverty and enhance transport equity in light of these findings.

中文翻译:


揭示网约车用户的出行模式:印度尼西亚日惹跨收入群体的潜在阶层聚类分析



这项研究为不同收入群体的网约车出行模式提供了宝贵的见解,包括低收入群体和生活在贫困线以下的群体,这些群体在之前的研究中经常被忽视。我们利用基于印度尼西亚日惹省的一项调查的潜在类别聚类分析 (LCCA),研究了社会人口统计、家庭特征以及与出行相关的网约车使用态度如何影响出行模式特征的变化。我们的结果表明,可以识别出代表不同网约车出行模式的六个不同集群。我们发现使用基于摩托车的乘车服务 (RH MC) 的短途且便宜的旅行占主导地位。相比之下,更长、更昂贵的行程与汽车网约车 (RH CAR) 相关。此外,网约车在回家、通勤和维护活动等基本出行中发挥着重要作用,凸显了其在解决交通挑战方面的重要性,特别是在公共交通有限的地区。低收入人群和贫困人群倾向于使用 RH MC 的叫车服务来进行更短、更便宜的旅行,而高收入人群则将其用于更广泛的目的。这些发现凸显了网约车对不同收入群体的不同影响,并表明网约车有可能提高印度尼西亚低收入人群的出行便利性。根据这些调查结果,我们提出了缓解交通贫困和加强交通公平的政策建议。
更新日期:2024-05-24
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