Satisfaction with the commute: The role of travel mode choice, built environment and attitudes

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Highlights

  • Examines the role of travel mode, built-environment and attitudes on commute satisfaction.

  • Active travel users have the highest level of commute satisfaction.

  • Travel attitudes have both direct and indirect effects on commute satisfaction.

  • The objectively measured built-environment only has indirect effects.

  • Congestion is strongly associated with poor commute satisfaction.

Abstract

Most of previous research that investigates the connections between the travel and satisfaction with travel has focused on the effect of the travel characteristics (e.g. travel mode choice, travel time, level of service, etc.) on satisfaction with travel. Little research has explored the role of the built environment or travel attitudes, two important factors for transport policies. Using data from a recent survey conducted in Xi’an, China, this study aims to quantitatively explore the relative effects of the built environment, travel attitudes, and travel characteristics on commute satisfaction. The data was analyzed using structural equation modeling. The model results suggest that commuting characteristics, including mode choice, congestion, and level of services of transit, all directly influence commute satisfaction. Attitudes have both direct and indirect effects on commute satisfaction, while the built environment only has indirect effects through influencing commuting characteristics.

Introduction

Subjective wellbeing (SWB), as an alternative and enrichment to utility, has recently attracted significant attention from transportation researchers. SWB offers a direct measurement of individuals’ mood, emotion and cognitive judgment (Kahneman and Krueger, 2006, Kahneman et al., 1997), and therefore could be a better tool to capture individual “true” preferences on travel choice. Previous studies have generally not used SWB partially because of the argument that subjective hedonic experience cannot be observed and measured (Kahneman et al., 1997). The development of psychological research has enabled the measurement of SWB, and various measures have been proposed and validated. As a specific domain of SWB, travel satisfaction has also recently been measured (Ettema et al., 2011, Stradling et al., 2007). A growing number of studies have investigated the connections between travel characteristics (e.g. travel mode choice, travel time, level of service, etc.) and satisfaction with travel (Abou-Zeid, 2009, Cao, 2013, Ettema et al., 2012, Friman and Fellesson, 2009, Gatersleben and Uzzell, 2007, Hine and Mitchell, 2001, Mokhtarian et al., 2014, Olsson et al., 2013, Paez and Whalen, 2010, Susilo and Cats, 2014). Several recent studies further explored the role of the built environment (Cao and Ettema, 2014, De Vos et al., 2016, Friman et al., 2013) or travel attitudes (Manaugh and El-Geneidy, 2013, St-Louis et al., 2014) in influencing travel satisfaction; both are important factors for transport policies. However, these studies have several limitations. First, only one study (Cao and Ettema, 2014) measures the built environment at a disaggregate (household) level using different dimensional measures (e.g. density, diversity, design). The others only use very simple built environment indicators at an aggregate level (e.g. urban vs. suburban neighborhood). Second, all of these studies treat the built environment, travel attitudes and other travel characteristics as separate determinants of travel satisfaction; few of them explore the potential interactions between various types of factors and the structural relationships between these factors. Finally, few of these studies focus on commuting trips and commuting satisfaction.

The built environment potentially influences travel satisfaction both directly and indirectly. First, travel characteristics, such as travel mode choice and travel time, are affected by the built environment (Ewing and Cervero, 2010). The “New urbanism” and related planning paradigms employing designs of higher density, mixed land use, and pedestrian-friendly design, for example, could shorten the time traveling from one location to various other locations, thereby improving travel satisfaction. Second, the built environment around one’s home and job may directly influence the ease and comfort of one’s commuting trip. A pedestrian friendly environment, for example, may make a walking trip go smoothly and with enjoyment. Similarly attitudes could also influence travel satisfaction in both direct and indirect ways. People’s attitudes towards different modes may have a direct influence on their moods while commuting. For example, pro-bike bicycling commuters are more likely to be happy and satisfied with their commuting trip than those who use the bike for their daily commute through lack of suitable alternatives. Attitudes could also indirectly affect travel satisfaction by influencing the travel mode choice. Travel behavior theory has long recognized the role of attitudes and preferences in influencing travel behavior. Even though attitudes are often included as control variables for self-selection, many studies have concluded that attitudes play a significant role in influencing travel behavior (Cao et al., 2009, Handy et al., 2005, Handy et al., 2006, Kitamura et al., 1997, Naess, 2005).

Using results from a recent survey conducted in Xi’an, China, this study aims to quantitatively explore the structural relationships between the built environment, travel attitudes, and travel characteristics and travel satisfaction, focusing on commuting trips. Exploring this question helps to not only build a comprehensive framework linking the built environment, travel behavior and satisfaction with travel, but will also help identify potential interventions to improve individual satisfaction with travel and levels of wellbeing. The unique context of this study also contributes to the literature by providing empirical evidence from a developing country and fast growing city. China has been undergoing a period of rapid urbanization and its cities have been changed radically (Ding, 2007, Ma, 2002). Alongside increasing urban expansion, China has seen increasing travel distances and worsening transportation conditions, particularly for the daily commute (Guan and Cui, 2003). For many residents in the big cities of China, commuting may have become a physical and mental burden, significantly influencing their wellbeing. This highlights the importance of improving people’s commuting experience and satisfaction.

Previous research on Chinese cities has primarily focused on Beijing, Shanghai, and Guangzhou, the mega cities of China, those with a population over 10 million. However, the policy implications derived from studying those cities may not be transferrable to other Chinese cities because of their very unique characteristics. Few previous researches have explored these urban issues for cities at the second level of scale. According to 2010 Census data (China City Statistical Yearbook, 2010), there are 47 cities in China, including Xi’an, that have a population of 2–10 million. By focusing on Xi’an, therefore, the study will have a broader impact on urban policies that address travel problems and social wellbeing in China.

Section snippets

Conceptual model

Previous research linking the built environment and attitudes with travel behavior and travel satisfaction provides the conceptual basis of the analysis. First, a growing number of studies have linked travel behavior and travel satisfaction (Abou-Zeid, 2009, Cao and Ettema, 2014, De Vos et al., 2016, Ettema et al., 2011, Morris and Guerra, 2014, Olsson et al., 2013, St-Louis et al., 2014), and found a significant association between the two. For example, Gatersleben and Uzzell (2007) found that

Data and methods

The data used in this study was gathered through a specially designed survey. The study was limited to residents of Xi’an aged over 18 who are in employment within Xi’an and do not work from home. Participants for the questionnaire survey were recruited through their employers and the survey was conducted at their employers’ sites. Employers were sampled by industry type from the current industry listings (Xi’an Bureau of Statistics, 2011); a quota-based approach was taken to ensure that each

Model results

A model specified as in Fig. 3, which is a simplified version of the conceptual model, was estimated. Correlation tests were conducted before creating the model. The model results, including model fits, standardized coefficients and significance, are provided in Table 4. The RMSEA fit index suggests a good fit and CFI fit index suggests an acceptable fit (CFI = 0.938, RMSEA = 0.035) based on Hu and Bentler (1999), who suggest a cutoff value close to 0.95 for CFI and a cutoff value close to 0.06 for

Conclusion

Studies linking travel and satisfaction with travel have recently received increasing attention in the field of transportation. This study contributes to the previous studies by further including the built environment and travel-related attitudes and by focusing on commuting, aiming to build a more comprehensive framework that helps to explain the complex relationships between the built environment, attitudes, travel, and travel satisfaction. By conducting surveys at selected employers in

Acknowledgments

We thank the Royal Geographical Society with IBG Hong Kong Research Grant for providing funding support to conduct the survey. Runing Ye thanks the joint funding support from UCL Overseas Research Scholarships and China Scholarship Council. We also thank the editor (Professor Jason Cao) and two anonymous reviewers for their constructive comments on earlier drafts of the paper. We would also like to show our gratitude to the International Association for China Planning (IACP) who sponsored this

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