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https://doi.org/10.32866/7124...
Article
License: CC BY NC
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DOAJ
Article . 2019
Data sources: DOAJ
https://doi.org/10.32866/7124...
Article . 2019 . Peer-reviewed
Data sources: Crossref
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Understanding Trip Happiness using Smartphone-Based Data: The Effects of Trip- and Person-Level Characteristics

Authors: Yingling Fan; Roland Brown; Kirti Das; Julian Wolfson;

Understanding Trip Happiness using Smartphone-Based Data: The Effects of Trip- and Person-Level Characteristics

Abstract

Understanding trip happiness—a measurement of people’s emotional well-being during trips—is an essential aspect of people-oriented transportation planning. We use data collected via smartphones from 350 residents in the Minneapolis-St. Paul region to examine trip- and person-level factors associated with trip happiness. Trip mode, purpose, duration, distance, companionship, activities during the trip, and temporal characteristics of the trip are significantly associated with trip happiness. Mode and companionship are the strongest predictors of trip happiness. Among personal factors, age is the strongest predictor, followed by general happiness of the person. Race, gender, and neighborhood have modest effects on trip happiness.

Keywords

Urban groups. The city. Urban sociology, HT101-395, Transportation and communications, HE1-9990

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    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    17
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
Powered by OpenAIRE graph
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
17
Top 10%
Average
Top 10%
gold