Heterogeneity in activity and travel mode patterns of older Indonesians

Muhammad Zudhy Irawan , Muhamad Rizki , Prawira Fajarindra Belgiawan , Tri Basuki Joewono , Saksith Chalermpong , Phathinan Thaithatkul , Hironori Kato
{"title":"Heterogeneity in activity and travel mode patterns of older Indonesians","authors":"Muhammad Zudhy Irawan ,&nbsp;Muhamad Rizki ,&nbsp;Prawira Fajarindra Belgiawan ,&nbsp;Tri Basuki Joewono ,&nbsp;Saksith Chalermpong ,&nbsp;Phathinan Thaithatkul ,&nbsp;Hironori Kato","doi":"10.1016/j.trip.2024.101159","DOIUrl":null,"url":null,"abstract":"<div><p>Older adults aged 50 years and over may experience varied participation levels in out-of-home activities and travel modes, with their ability to walk being a significant factor. However, the heterogeneity of the activity–travel patterns of people at this age, especially in the Indonesian context, is not well understood. Using Yogyakarta as a case study and applying a latent class cluster analysis, this study is the first to categorize older adults’ participation in activities and use of travel modes and to understand the distinct characteristics of older adults. The model results revealed four discrete groups based on older adults’ activity participation and another four discrete groups based on their travel mode use. In the activity participation group, active older adults are the largest group, followed by inactive, working, and very active older adults. Meanwhile, those reliant on their motorized vehicles make up the largest travel mode group, followed by low-cost-vehicle users, captive riders of personal motorcycles, and car users. The model results also reveal that captive riders of personal motorcycles tend to be male and the youngest-old, while smartphone users are more likely to belong to the car users group. Walking ability constraints also significantly affect heterogeneity in older adults’ activity and travel mode, where those with no constraints on their ability to walk tend to be categorized as active older adult car users. The findings of this study may help policymakers identify older people with particular activity patterns and travel modes and develop policies to accommodate their mobility needs.</p></div>","PeriodicalId":36621,"journal":{"name":"Transportation Research Interdisciplinary Perspectives","volume":null,"pages":null},"PeriodicalIF":3.9000,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2590198224001453/pdfft?md5=5a88380cdea5bf1527adbb6a0b2f3402&pid=1-s2.0-S2590198224001453-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Transportation Research Interdisciplinary Perspectives","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2590198224001453","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"TRANSPORTATION","Score":null,"Total":0}
引用次数: 0

Abstract

Older adults aged 50 years and over may experience varied participation levels in out-of-home activities and travel modes, with their ability to walk being a significant factor. However, the heterogeneity of the activity–travel patterns of people at this age, especially in the Indonesian context, is not well understood. Using Yogyakarta as a case study and applying a latent class cluster analysis, this study is the first to categorize older adults’ participation in activities and use of travel modes and to understand the distinct characteristics of older adults. The model results revealed four discrete groups based on older adults’ activity participation and another four discrete groups based on their travel mode use. In the activity participation group, active older adults are the largest group, followed by inactive, working, and very active older adults. Meanwhile, those reliant on their motorized vehicles make up the largest travel mode group, followed by low-cost-vehicle users, captive riders of personal motorcycles, and car users. The model results also reveal that captive riders of personal motorcycles tend to be male and the youngest-old, while smartphone users are more likely to belong to the car users group. Walking ability constraints also significantly affect heterogeneity in older adults’ activity and travel mode, where those with no constraints on their ability to walk tend to be categorized as active older adult car users. The findings of this study may help policymakers identify older people with particular activity patterns and travel modes and develop policies to accommodate their mobility needs.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
印度尼西亚老年人活动和出行方式的异质性
50 岁及以上的老年人参与户外活动和出行方式的程度各不相同,其中步行能力是一个重要因素。然而,人们对这一年龄段的人的活动-出行模式的异质性还不甚了解,尤其是在印尼的情况下。本研究以日惹为案例,采用潜类聚类分析法,首次对老年人参与活动和使用出行方式进行分类,并了解老年人的不同特征。模型结果显示,根据老年人的活动参与情况分为四个离散组,根据出行方式的使用情况分为另外四个离散组。在活动参与组中,活跃的老年人是最大的群体,其次是不活跃、工作和非常活跃的老年人。同时,依赖机动车辆的老年人是最大的出行方式群体,其次是低成本车辆使用者、个人摩托车骑手和汽车使用者。模型结果还显示,私人摩托车骑士多为男性且年龄最小,而智能手机用户则更有可能属于汽车用户群体。步行能力限制也显著影响了老年人活动和出行方式的异质性,那些步行能力不受任何限制的老年人往往被归类为活跃的老年人汽车使用者。这项研究的结果可以帮助政策制定者识别具有特殊活动模式和出行方式的老年人,并制定政策来满足他们的出行需求。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Transportation Research Interdisciplinary Perspectives
Transportation Research Interdisciplinary Perspectives Engineering-Automotive Engineering
CiteScore
12.90
自引率
0.00%
发文量
185
审稿时长
22 weeks
期刊最新文献
Electric mobility investment in the power and transport sector coupling context: Lessons from Argentina, the Philippines, Poland and Romania Comparative Analysis of barriers to Battery electric vehicle adoption between BEV and ICE Users: A case study of Thailand Disparities in ridehailing travel times for accessing non-work destinations Optimal bus reassignment considering in-vehicle overcrowding Drones for automated parcel delivery: Use case identification and derivation of technical requirements
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1