About: Do commuters adapt to in-vehicle crowding on trains?

Facets (new session)
Description
Metadata
Settings
- owl:sameAs
- Inference Rule:

About: Do commuters adapt to in-vehicle crowding on trains? Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Do commuters adapt to in-vehicle crowding on trains?
Creator	Kumagai, Junya Managi, Shunsuke Wakamatsu, Mihoko Shunsuke Managi, ·
Source	Medline; PMC
abstract	In-vehicle crowding on public transportation is a serious problem that transportation planners must address. Recent studies have emphasized that in-vehicle crowding impacts travelers’ stress and health, while other studies have investigated how daily travel affects subjective well-being (SWB). Based on the findings of these studies, we provide useful insights into the value of a reduction in crowding in terms of SWB. The other factor we should consider is adaptation, as the effects of travel discomfort disappear after travelers become accustomed to them. In this paper, we analyzed the direct and stress-related indirect effects of dissatisfaction with in-vehicle crowding on life satisfaction, focusing on whether these effects differ by the length of time commuters have been using trains. Using a sample of 8296 train commuters in Tokyo, we found that (1) dissatisfaction with in-vehicle crowding directly lowers life satisfaction among some groups of short-term train commuters and (2) dissatisfaction with in-vehicle crowding indirectly lowers life satisfaction through stress and health, regardless of whether commuters have used trains for more or less than one year. These results revealed the importance of focusing on the stress-related indirect effects of dissatisfaction with crowding, while direct effects on SWB exist only among some commuters. Our results demonstrated the possibility of adaptation to direct effects.
has issue date	2020-07-28(xsd:dateTime)
bibo:doi	10.1007/s11116-020-10133-9
bibo:pmid	32836506
has license	no-cc
sha1sum (hex)	31562f2ac24b8a14307f6188e36211bf9faf5f88
schema:url	https://doi.org/10.1007/s11116-020-10133-9
resource representing a document's title	Do commuters adapt to in-vehicle crowding on trains?
has PubMed Central identifier	PMC7386388
has PubMed identifier	32836506
schema:publication	Transportation (Amst)
resource representing a document's body	covid:31562f2ac24b8a14307f6188e36211bf9faf5f88#body_text
is schema:about of	named entity 'IMPACTS' named entity 'HEALTH' named entity 'HAVE' named entity 'EFFECTS' named entity 'FACTOR' named entity 'STUDIES' named entity 'TERMS' named entity 'BASED' named entity 'SWB' named entity 'subjective well-being' named entity 'transportation planners' named entity 'life satisfaction' named entity 'in-vehicle' named entity 'Subjective well-being' named entity 'BC 15' named entity 'daily travel' named entity 'MLIT' named entity 'explanatory variable' named entity 'natural log' named entity 'Tokyo' named entity 'logarithmic function' named entity 'Japan' named entity 'public transportation' named entity 'public transportation' named entity 'Tokyo' named entity 'eudemonic' named entity 'Hyogo' named entity 'probability' named entity 'Nagoya' named entity 'social distancing' named entity 'public transportation' named entity 'modal shift' named entity 'Tokyo' named entity 'life satisfaction' named entity 'traffic congestion' named entity 'dummy variable' named entity 'Japan' named entity 'travel modes' named entity 'Tokyo' named entity 'independent variable' named entity 'disutility' named entity 'goodness-of-fit' named entity 'time-invariant' named entity 'life satisfaction' named entity 'omitted variables' named entity 'endogeneity' named entity 'SWB' named entity 'CFI' named entity 'Tokyo' named entity 'habituation' named entity 'omitted variables' named entity 'population density' named entity 'choice model' named entity 'travel mode' named entity 'Tokyo' named entity 'life satisfaction' named entity 'transportation mode' named entity 'disutility' named entity 'reverse causality' named entity 'probability' named entity 'linear function' named entity 'life satisfaction' named entity 'commuted by train' named entity 'life satisfaction' named entity 'Kobe City' named entity 'Tokyo' named entity 'difference equation' named entity 'Tokyo' named entity 'y-intercepts' named entity 'SEM' named entity 'Tokyo' named entity 'route choice' named entity 'travel modes' named entity 'public transportation' named entity 'Japan' named entity 'selection bias' named entity 'travel behavior' named entity 'willingness to pay'

Faceted Search & Find service v1.13.91 as of Mar 24 2020

Alternative Linked Data Documents: Sponger | ODE Content Formats:

RDF

ODATA

Microdata

About

OpenLink Virtuoso version 07.20.3229 as of Jul 10 2020, on Linux (x86_64-pc-linux-gnu), Single-Server Edition (94 GB total memory)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2024 OpenLink Software