Commute happiness in Xi’an, China: Effects of commute mode, duration, and frequency

Zhu, Jiabin; Fan, Yingling

doi:10.1016/j.tbs.2018.01.001

Cited by 92 publications

(63 citation statements)

References 38 publications

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“…In fact, while academic interests in travel happiness are relatively new (Chen et al., 2019; Singleton, 2019), over the last decade (see De Vos, 2019b; De Vos, Schwanen, Van Acker, & Witlox, 2013; Ettema, Gärling, Olsson, & Friman, 2010), studies have extensively explored various happiness determinants (Chen et al., 2019), focusing on trip and traveler characteristics (Zhu & Fan, 2018a, 2018b) although other dimensions such as the built environment and climate were also investigated (Abenoza, Cats, & Susilo, 2017; De Vos, Ettema, & Witlox, 2019; Park, 2017; Park & Kim, 2017). Frequently analyzed variables include travel modes (Morris, 2015; Morris & Guerra, 2015; Singleton, 2019; St‐Louis, Manaugh, van Lierop, & El‐Geneidy, 2014; Zhu & Fan, 2018b)—those for active travel, including walk and bike [but not for commute (Singleton, 2019)], and public transit were often found as the happiest and unhappiest modes, respectively, although the reciprocal relationship between mode choice and travel happiness was also conceptually acknowledged (De Vos, 2019b; De Vos et al., 2013; De Vos & Witlox, 2017)—activities/experiences on the way to the destination (De Vos et al., 2013; Ettema, Friman, Gärling, Olsson, & Fujii, 2012), presence/characteristics of companions (De Vos, 2019a; Zhu & Fan, 2018b), trip purposes (in relation to the compulsion level of the trip) (De Vos, Mokhtarian, Schwanen, Van Acker, & Witlox, 2016; Mokhtarian, Papon, Goulard, & Diana, 2015; Zhu & Fan, 2018b) and frequencies (Zhu & Fan, 2018a), and weather conditions at the time of the trip (Ettema, Friman, Olsson, & Gärling, 2017). In empirical studies on these variables, sociodemographics (e.g., gender, age, education, and income) were typically included for statistical control or as research variables (Chen et al., 2019; Zhu & Fan, 2018a) although analytical results on their impacts on travel happiness are mixed, except the consistent argument that older travelers are generally happier (Ingvardson & Nielsen, 2019; Singleton, 2019).…”

Section: Literature Reviewmentioning

confidence: 99%

“…Frequently analyzed variables include travel modes (Morris, 2015; Morris & Guerra, 2015; Singleton, 2019; St‐Louis, Manaugh, van Lierop, & El‐Geneidy, 2014; Zhu & Fan, 2018b)—those for active travel, including walk and bike [but not for commute (Singleton, 2019)], and public transit were often found as the happiest and unhappiest modes, respectively, although the reciprocal relationship between mode choice and travel happiness was also conceptually acknowledged (De Vos, 2019b; De Vos et al., 2013; De Vos & Witlox, 2017)—activities/experiences on the way to the destination (De Vos et al., 2013; Ettema, Friman, Gärling, Olsson, & Fujii, 2012), presence/characteristics of companions (De Vos, 2019a; Zhu & Fan, 2018b), trip purposes (in relation to the compulsion level of the trip) (De Vos, Mokhtarian, Schwanen, Van Acker, & Witlox, 2016; Mokhtarian, Papon, Goulard, & Diana, 2015; Zhu & Fan, 2018b) and frequencies (Zhu & Fan, 2018a), and weather conditions at the time of the trip (Ettema, Friman, Olsson, & Gärling, 2017). In empirical studies on these variables, sociodemographics (e.g., gender, age, education, and income) were typically included for statistical control or as research variables (Chen et al., 2019; Zhu & Fan, 2018a) although analytical results on their impacts on travel happiness are mixed, except the consistent argument that older travelers are generally happier (Ingvardson & Nielsen, 2019; Singleton, 2019). Also, not only the statistical significance of travel happiness determinants, but also studies began to evaluate their relative magnitudes (Chen et al., 2019).…”

Section: Literature Reviewmentioning

confidence: 99%

“…Another group of studies (e.g., Bergstad et al., 2011; De Vos et al., 2013; Ettema et al., 2010; Gao et al., 2017) confirmed in different settings the relationship that travel happiness or satisfaction with daily trips has with overall happiness. Most studies (e.g., Ettema et al., 2017; Olsson, Gärling, Ettema, Friman, & Fujii, 2013; Singleton, 2019; St‐Louis et al., 2014; Zhu & Fan, 2018a) analyzed commuting while the importance of leisure trips was recently highlighted (De Vos, 2019a). Alternately, several studies (e.g., Delbosc & Currie, 2011a, 2011b) reported that overall happiness is generally low among transportation‐disadvantaged populations with low travel happiness.…”

Section: Literature Reviewmentioning

confidence: 99%

See 2 more Smart Citations

The relationship between overall happiness and perceived transportation services relative to other individual and environmental variables

Gim

2020

Growth and Change

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Studies on happiness determinants have mainly focused on individual characteristics, but recently, the focus was extended to public services. Regarding the role of transportation services, however, few discussions exist on the overall happiness beyond the transitory happiness from a single trip, which differs by the mechanical characteristics of the transportation means, and particularly, those in non-Western areas are very few. This study analyses the perceived transportation services-happiness relationship using a social survey of 46 thousand citizens in Seoul, South Korea. How transportation services contribute to happiness is discussed in relation to the auxiliary travel utility through activities/ non-activities on the way to the destination and to the intrinsic utility, which is generated by satisfying mobility instincts, in addition to the derived utility by those activities that are conducted at the destination, the traditional focus in the transportation literature. An analytical model based on partial least squares structural equation modeling estimates the relationship between happiness and the factor of perceived transportation services while controlling for seven factors. Analytical findings are that except for gender, the significance and magnitude of each of the indicators are comparable to those reported in previous studies and as expected, perceived transportation services significantly encourage happiness. Specifically, satisfaction with 714 | GIM major determinants of happiness on life situation (sociodemographics), attitudes/intentions, behavior, environmental conditions, leisure amenities, and urban risks. The Seoul Survey is conducted every year, but the 2009 version uniquely asked about fitness and diet, both of which are known to affect happiness (Lee & Jung, 2013). Thus, this study used the 2009 data in particular. Data on research variables are available online: https://drive.google.com/open?id=1zjt6 Qait_yniJy tPWWF ztoVe sH4k-w0Gb. A figure for the structure of the relationships between respective factors and their indicator variables will be given later.The remainder of the paper is structured as follows. The next section will provide a review of the literature on the definition and measurement of happiness followed by its determinants including transportation services. Then, the paper will present research variables and their data for the empirical analysis. Analytical results will be separately given for indicator-factor relationships and factor-factor relationships. The paper will conclude with a discussion on research findings and their differences from those conducted on Western areas and the relative importance of transportation service indicators and its policy implications.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

See 1 more Smart Citation

The relationship between overall happiness and perceived transportation services relative to other individual and environmental variables

Gim

2020

Growth and Change

View full text Add to dashboard Cite

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“…What is the impact of commuting on residents' physical and psychological states? These conclusions, however, may not be generalisable to developing countries such as China [32]. Only a limited number of studies examined the impact of transport mode and commuting time on residents' psychological well-being in China specifically.…”

Section: Introductionmentioning

confidence: 95%

“…Only a limited number of studies examined the impact of transport mode and commuting time on residents' psychological well-being in China specifically. For example, Zhu and Fan [32] demonstrated that residents of Xi'an who commute by shuttle bus reported the highest happiness with their commute, followed by residents commuting by private bicycle and walking, while residents who use regular city buses reported the lowest happiness with their commute. Differences in modes of transport could further exacerbate socioeconomic inequality in Chinese society.…”

Section: Introductionmentioning

confidence: 99%

Transportation Equity in China: Does Commuting Time Matter?

Chen

Shi

et al. 2019

Sustainability

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Urban commuting, a facet of transportation equity, is an important factor that shapes social equity. Little is known about how commuting practices shape individuals' perceptions of social equity. To fill this gap, we conducted a multilevel regression using data from the China Labour-force Dynamics Survey 2016. We found that commuters who used private cars had the highest level of perceived social equity, while those who used bicycles had the lowest. Commuting time had a significant negative effect on respondents' perceived social equity. This study verifies the "commuting paradox" to some extent, as income had no moderating effect on the relationship between commuting time and perceived social equity, which suggests that the social inequity caused by long commutes is not alleviated by higher wages. We also found that the perceived social equity of respondents who commuted on foot or by motorcycle was significantly negatively affected by commuting time. Based on our findings, we propose four ways to alleviate social inequity caused by commuting inequities: consider the commuting time sensitivity of different types of commuters, pay attention to the social equity issues caused by different transportation modes, provide more equitable commuting ways for low-income people, and prioritise public transportation.

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Self-Reporting as a Determination Method for the Travel Fatigue of Mass Transit Commuters

Kopytkov,

Ponkratov,

Samchuk

et al. 2023

Lecture Notes in Networks and Systems

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Commute happiness in Xi’an, China: Effects of commute mode, duration, and frequency

Cited by 92 publications

References 38 publications

The relationship between overall happiness and perceived transportation services relative to other individual and environmental variables

The relationship between overall happiness and perceived transportation services relative to other individual and environmental variables

Transportation Equity in China: Does Commuting Time Matter?

Self-Reporting as a Determination Method for the Travel Fatigue of Mass Transit Commuters

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