1983年至2019年日本铁路乘客基于旅行的多任务处理的元分析:直接观察和YouTube视频

IF 3.5 2区 工程技术 Q1 ENGINEERING, CIVIL
Nobuhiro Sanko, Sota Yamaguchi
{"title":"1983年至2019年日本铁路乘客基于旅行的多任务处理的元分析:直接观察和YouTube视频","authors":"Nobuhiro Sanko, Sota Yamaguchi","doi":"10.1007/s11116-024-10522-4","DOIUrl":null,"url":null,"abstract":"<p>This meta-analysis aims to analyse how the activities of rail passengers have changed in Japan as a result of rapid technological developments. To be eligible for inclusion in this analysis, source studies must have reported the number of passengers performing specific activities, and the number must have been directly counted by surveyors who actually ride on trains. Databases searched included CiNii, J-STAGE, Web of Science, and Google Scholar. References in selected studies were trialled using a snowballing method. In addition, past onboard activities were retrospectively identified by content analysis of YouTube videos in which the surveyors hypothetically travelled on a train and observed the passengers. The use of YouTube videos for meta-analysis of rail passengers’ activities is a novel contribution of this study. The search for the YouTube video was entirely manual. In total, 23 independent studies with 332,355 passengers were included in the analysis. Data were collected from 1983 to 2019. The effect sizes were the proportion of each of the following activities: ‘(a) mobile phones’, ‘(b) sleeping’, ‘(c) reading’, ‘(d) music’, and ‘(e) other’. Meta-regressions were performed with the year of data collection as a moderator. Demonstrating historical changes in activities through statistical analysis is another novel contribution: ‘(a) mobile phones’ and ‘(d) music’ had a significantly increasing trend, ‘(c) reading’ had a significantly decreasing trend, and ‘(b) sleeping’ and ‘(e) other’ did not change. Studies with and without YouTube videos did not affect the conclusions, which supports the use of YouTube videos for the purposes of this study. Ideas are presented for research methods that use directly observed data to explain the possible social factors behind longitudinal variation in travel-based multitasking.</p>","PeriodicalId":49419,"journal":{"name":"Transportation","volume":"8 1","pages":""},"PeriodicalIF":3.5000,"publicationDate":"2024-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Meta-analysis of travel-based multitasking by railway passengers in Japan between 1983 and 2019: direct observation and YouTube videos\",\"authors\":\"Nobuhiro Sanko, Sota Yamaguchi\",\"doi\":\"10.1007/s11116-024-10522-4\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>This meta-analysis aims to analyse how the activities of rail passengers have changed in Japan as a result of rapid technological developments. To be eligible for inclusion in this analysis, source studies must have reported the number of passengers performing specific activities, and the number must have been directly counted by surveyors who actually ride on trains. Databases searched included CiNii, J-STAGE, Web of Science, and Google Scholar. References in selected studies were trialled using a snowballing method. In addition, past onboard activities were retrospectively identified by content analysis of YouTube videos in which the surveyors hypothetically travelled on a train and observed the passengers. The use of YouTube videos for meta-analysis of rail passengers’ activities is a novel contribution of this study. The search for the YouTube video was entirely manual. In total, 23 independent studies with 332,355 passengers were included in the analysis. Data were collected from 1983 to 2019. The effect sizes were the proportion of each of the following activities: ‘(a) mobile phones’, ‘(b) sleeping’, ‘(c) reading’, ‘(d) music’, and ‘(e) other’. Meta-regressions were performed with the year of data collection as a moderator. Demonstrating historical changes in activities through statistical analysis is another novel contribution: ‘(a) mobile phones’ and ‘(d) music’ had a significantly increasing trend, ‘(c) reading’ had a significantly decreasing trend, and ‘(b) sleeping’ and ‘(e) other’ did not change. Studies with and without YouTube videos did not affect the conclusions, which supports the use of YouTube videos for the purposes of this study. Ideas are presented for research methods that use directly observed data to explain the possible social factors behind longitudinal variation in travel-based multitasking.</p>\",\"PeriodicalId\":49419,\"journal\":{\"name\":\"Transportation\",\"volume\":\"8 1\",\"pages\":\"\"},\"PeriodicalIF\":3.5000,\"publicationDate\":\"2024-08-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Transportation\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.1007/s11116-024-10522-4\",\"RegionNum\":2,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, CIVIL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Transportation","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1007/s11116-024-10522-4","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, CIVIL","Score":null,"Total":0}
引用次数: 0

摘要

本荟萃分析旨在分析日本铁路乘客的活动是如何随着技术的快速发展而发生变化的。要符合纳入本分析的条件,来源研究必须报告了从事特定活动的乘客人数,且人数必须由实际乘坐火车的调查人员直接统计。搜索的数据库包括 CiNii、J-STAGE、Web of Science 和 Google Scholar。采用 "滚雪球 "法对所选研究的参考文献进行了试用。此外,还通过对 YouTube 视频进行内容分析,对调查人员假设乘坐火车并观察乘客的视频进行了回顾性分析,从而确定了以往的车载活动。利用 YouTube 视频对铁路乘客的活动进行元分析是本研究的一项新贡献。YouTube 视频的搜索完全由人工完成。共有 23 项独立研究、332,355 名乘客被纳入分析范围。数据收集时间为 1983 年至 2019 年。效果大小为以下各项活动的比例:(a)手机"、"(b)睡觉"、"(c)阅读"、"(d)音乐 "和"(e)其他"。以数据收集年份为调节因子进行元回归。通过统计分析展示活动的历史变化是另一项新贡献:"(a) 手机 "和"(d) 音乐 "呈显著上升趋势,"(c) 阅读 "呈显著下降趋势,而"(b) 睡眠 "和"(e) 其他 "没有变化。有YouTube视频和没有YouTube视频的研究对结论没有影响,这支持了本研究使用YouTube视频的目的。本研究提出了使用直接观察数据来解释基于旅行的多任务处理纵向变化背后可能存在的社会因素的研究方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Meta-analysis of travel-based multitasking by railway passengers in Japan between 1983 and 2019: direct observation and YouTube videos

Meta-analysis of travel-based multitasking by railway passengers in Japan between 1983 and 2019: direct observation and YouTube videos

This meta-analysis aims to analyse how the activities of rail passengers have changed in Japan as a result of rapid technological developments. To be eligible for inclusion in this analysis, source studies must have reported the number of passengers performing specific activities, and the number must have been directly counted by surveyors who actually ride on trains. Databases searched included CiNii, J-STAGE, Web of Science, and Google Scholar. References in selected studies were trialled using a snowballing method. In addition, past onboard activities were retrospectively identified by content analysis of YouTube videos in which the surveyors hypothetically travelled on a train and observed the passengers. The use of YouTube videos for meta-analysis of rail passengers’ activities is a novel contribution of this study. The search for the YouTube video was entirely manual. In total, 23 independent studies with 332,355 passengers were included in the analysis. Data were collected from 1983 to 2019. The effect sizes were the proportion of each of the following activities: ‘(a) mobile phones’, ‘(b) sleeping’, ‘(c) reading’, ‘(d) music’, and ‘(e) other’. Meta-regressions were performed with the year of data collection as a moderator. Demonstrating historical changes in activities through statistical analysis is another novel contribution: ‘(a) mobile phones’ and ‘(d) music’ had a significantly increasing trend, ‘(c) reading’ had a significantly decreasing trend, and ‘(b) sleeping’ and ‘(e) other’ did not change. Studies with and without YouTube videos did not affect the conclusions, which supports the use of YouTube videos for the purposes of this study. Ideas are presented for research methods that use directly observed data to explain the possible social factors behind longitudinal variation in travel-based multitasking.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Transportation
Transportation 工程技术-工程:土木
CiteScore
10.70
自引率
4.70%
发文量
94
审稿时长
6-12 weeks
期刊介绍: In our first issue, published in 1972, we explained that this Journal is intended to promote the free and vigorous exchange of ideas and experience among the worldwide community actively concerned with transportation policy, planning and practice. That continues to be our mission, with a clear focus on topics concerned with research and practice in transportation policy and planning, around the world. These four words, policy and planning, research and practice are our key words. While we have a particular focus on transportation policy analysis and travel behaviour in the context of ground transportation, we willingly consider all good quality papers that are highly relevant to transportation policy, planning and practice with a clear focus on innovation, on extending the international pool of knowledge and understanding. Our interest is not only with transportation policies - and systems and services – but also with their social, economic and environmental impacts, However, papers about the application of established procedures to, or the development of plans or policies for, specific locations are unlikely to prove acceptable unless they report experience which will be of real benefit those working elsewhere. Papers concerned with the engineering, safety and operational management of transportation systems are outside our scope.
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信