Travel satisfaction inequality and the role of the urban metro system

Transport Policy 79 (2019) 66–81

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Transport Policy journal homepage: www.elsevier.com/locate/tranpol

Travel satisfaction inequality and the role of the urban metro system Pengjun Zhao

a,b

, Peilin Li

T

c,d,∗

a

Department of Urban and Regional Planning, College of Urban and Environmental Sciences, Peking University, Beijing, 100871, China The Centre for Urban Planning and Transport Studies, Peking University, Beijing, 100871, China Academy of Macroeconomic Research, NDRC, Beijing, 100038, China d Institute of Spatial Planning and Regional Economy(ISPRE), NDRC, Beijing, 100038, China b c

A R T I C LE I N FO

A B S T R A C T

Keywords: Travel satisfaction Discrepancy Rail transport Expectation Beijing

Transport equality is one of the key aspects of sustainable urban transport. Personal satisfaction with travel among different communities and social groups has become a main theme in the field of transport equality research. However, there has been little investigation of the expectation confirmation mechanism underneath this affective feeling. Moreover, there is not enough evidence on how the discrepancy between expected and actual travel relates to satisfaction. This study first identifies the regional and social disparity in general travel satisfaction among residents in Beijing, then discusses how the satisfaction response to the dissonance between expected and actual travel, and finally investigates the role of urban rail transport in this disparity. The results show that general travel satisfaction presents both regional and social disparities, with city-centre and middleincome residents having higher travel satisfaction. Disconfirmation of travel expectations partly explains travel dissatisfaction. The inconsistency between travel discrepancy level and satisfaction for lower income residents further reflects transport inequality issues, and it provides a clue for transport policymakers to promote transport equity from a sufficientarianism perspective. Public transport-related development has an important role in improving different aspects of travel satisfaction. Among them, higher level of mixed land use in metro station catchment areas and higher metro network centrality of the home nearest station help to increase the travel satisfaction of disadvantaged residents. This is realised via enhancing destination options for low-income or suburban residents, and via providing a relatively smooth and tidy travel experience for disadvantaged groups, who tend to use metro as a major travel mode.

1. Introduction Travel satisfaction is widely defined as the extent to which a transport system lives up to its users' expectations (Morfoulaki et al., 2010). Many believe that travel satisfaction influences residents' general well-being. Urban transport policymakers and urban planners have been spending efforts on public transport improvement in order to facilitate residents' satisfaction with the transport service itself, and to create a better off situation for the city as a whole. The underlying assumption of these city managers is that improvement in transport access improves residents’ satisfaction. But is that really the case? Many studies in recent years have focused on the link between public transport and satisfaction. These studies have unveiled hints on the nature of satisfaction in transport. First, travel satisfaction might have regional disparities, which is led by disparity of transport service accessibility within urban areas (Fellesson and Friman, 2012). This finding provides partial support on some infrastructural-based

∗

satisfaction-improvement policies such as transit-oriented development. Second, travel satisfaction, unlike travel cost or time use, involves subjective judgement. This makes it sensitive to individuals’ economics, demographics and experience. Although abundant research has been conducted, three research gaps still need to be filled. The first gap is that existing research on travel satisfaction is based on user satisfaction with certain transport systems, such as bus or metro. Fewer attempts have been made to study general travel experience. Although discussion within certain transport system bridge reality and opinion directly, it risk neglecting the increasing complexity and integration of urban transport systems, as travel choice differs not only between person and trip types, but also between areas and times. Therefore, it is necessary to observe from a more extensive perspective. The second gap is that there is little empirical evidence on the relationship between transport inequality and satisfaction differences. It is not clear whether the spatially disadvantaged groups who have difficulties in accessing public transport (but need it) also dissatisfy on a

Corresponding author. Academy of Macroeconomic Research, NDRC, Beijing, 100038, China. E-mail address: [email protected] (P. Li).

https://doi.org/10.1016/j.tranpol.2019.04.014 Received 28 June 2018; Received in revised form 14 February 2019; Accepted 20 April 2019 Available online 24 April 2019 0967-070X/ © 2019 Elsevier Ltd. All rights reserved.

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Fig. 1. Factors influencing travel satisfaction.

Federal Transit Administration, 1999). Since the 1980s, the object of satisfaction surveys has gradually expanded from physical products to the service industry. In 2000, as social problems associated with urban transportation became more prominent, and residents' subjective well-being became a concern of governments, studies of residents' satisfaction with their daily travel increased (Abenoza et al., 2017; Cantwell, Caulfield, & O'Mahony, 2009; Diana, 2012; Stuart et al., 2000; Woldeamanuel and Cyganski, 2011). Travel satisfaction is defined as the extent to which transportation services offer to customer satisfaction (Morfoulaki et al., 2010). In the area of travel satisfaction, the importance of service reliability, frequency, comfort and short-distance commuting were originally studied and supported the assumption of maximum utility for public transport users (Cantwell et al., 2009). At the same time, studies have found that variables such as cleanliness, privacy, safety, convenience, stress, social interaction and landscape influence the degree of travel satisfaction (Stradling et al., 2007). Decent public transport services can not only increase users' loyalty by improving satisfaction and attracting new users (Aoyagi et al., 1999), but also influence their choice of travel modes by changing the attitudes of urban residents, especially for short-distance and intra-city travel (Diana, 2012). Although many studies have attempted to observe satisfaction directly or to analyse its determinants, less efforts have been made to investigate expectations and actual discrepancies in travel experience, or the relation between disconfirmation and satisfaction. These two important topics can be commonly seen in business and psychological studies (the conceptual framework is in Fig. 1). Relevant marketing and psychological studies were deeply rooted in psychological theory on the expectation-reality discrepancy. According to Helson's (1964) adaptation level theory, expectation serves as a reference for subjective satisfaction judgement. However, different theories have varied opinions on how satisfaction might follow when there is a dissonance between expectation and reality. For example, when the reality does not fulfil the expectation, psychological discomfort follows. Under this circumstance, assimilation theory contends that product users will adjust their evaluations of products to reduce discomfort, while contrast theory states that users will exaggerate the incongruity. The concept of gradation has also been introduced to combined these two theories, on the thinking that when the discrepancy between expectation and reality is low, users tend to convince themselves to lower their expectations, while when the gap is larger, greater disappointment follows (Ross et al., 1987). Travel satisfaction itself received more emphasis as a tool or goal to improve a certain transport system's quality than to reduce social inequality, though quality and equality improvement might overlap in some occasions. Previous attempts on satisfaction inequality investigation focused on the low travel or life satisfaction of certain disadvantaged groups, such as migrants, low incomers or senior citizens

higher level with travel experience. The third gap is the inadequate evidence of regional disparities in travel satisfaction research in the context of the Global South, especially in contexts where cities are rapidly growing and socially transforming. This study addresses these gaps by looking at Beijing, the capital city of China, as a case. At the end of 2015, the number of permanent residents in Beijing reached 21.7 million, with US$17,064 in GDP per capita. The city government has invested enormously in metro transport to relieve job-housing imbalance as a result of housing marketisation and fast urban expansion. This effort has brought rapid gain in metro mileage and ridership. However, many are concerned that it might aggravate some of the problems in the city (such as gentrification of the housing market in station areas), rather than relieving the inequalities of daily travel experience (Baker and Lee, 2019; Dong, 2017; Grube-Cavers and Patterson, 2015). However, knowledge on the influence of these developments on travel satisfaction is inadequate. Specifically, this paper investigates the spatial and social disparities in general travel satisfaction in urban areas, based on a survey of 4043 observations. It addresses three research questions: (1) Do these disparities exist? (2) How are they linked to residents’ expectations and actual travel experience? (3) Does urban rail transport play a role? The remaining part of the paper is organised as follows. Section 2 reviews the background of travel satisfaction studies and how they were shaped. Section 3 introduces the background of Beijing, its spatial structure evolution and the city government's relevant efforts in transport policy and investment. Section 4 provides a summary of the data context and the survey content. Sections 5 and 6 present the results and a discussion of the findings. 2. Literature review 2.1. Travel satisfaction The concept of satisfaction originates from American studies on marketing (Fornell et al., 1996). It refers to the state of people's feelings about products, a psychological feelings that people experience when they compare their actual experience with the expected product performance or output. Expectation is generally formed based on previous experience. The difference between the overall value and the overall cost is the value of expropriation. The degree of customer satisfaction with the product lies in the value that the enterprise gives to the customer, generally reflected as happiness or disappointment (Oliver, 1980). Satisfaction research began in the mid-1960s, and it developed rapidly in the mid-1970s. This is due, on the one hand, to the increasing attention to the understanding and resolution of specific customer issues, and on the other to the more rational and systematic voice of government officials in planning and policy development (United States 67

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differences in transport access and travel costs transfer to a more subjectively based satisfaction.

(Abenoza et al., 2017). Recent travel satisfaction studies tended to draw conclusions based on equity, referring to the disconfirmation level between travel expectation and reality. However, the disconfirmation of expectation in reality might be different from satisfaction, as some have found in the field of medical care (Ross et al., 1987). For example, patients with moderate positive expectations who receive service that does not meet their expectations might have higher satisfaction than patients with moderately negative expectations who receive service that exceeds their expectations. Dissatisfaction might be exacerbated when a very positive expectation is met with an average or poor experience. Existing studies have provided evidence on the existence of disparities in travel, such as destination choice (Huang and Levinson, 2015; Kitamura, 1984; Matthews et al., 2018), mode choice (Böcker et al., 2016; Munshi, 2016; Shen et al., 2016; Yun et al., 2017), and travel time (El-Geneidy et al., 2016; Geyer and Molayi, 2018; Zhao, 2013). But there is less investigation on whether level of travel satisfaction equal level of disconfirmation between expected and actual travel. In addition, main body of travel satisfaction investigation seems to constrain in either the transport facilities or the service. In fact, residents' travel satisfaction is not only affected by their experience in the transport system itself, but also accessibility to the transport system and relevant activities (Brons et al., 2009; Ettema et al., 2016; Tyrinopoulos and Antoniou, 2008). For instance, for residents mainly using public transport to commute, their journey to and from the station, as well as their experience in catchment areas, might influence their general travel experience. Besides, experiences outside the public transport system not only have a strong influence on passengers' destination choice and travel intensity, but they also impact general residents’ mode choice and travel experience, as the public transport system is tightly integrated into the whole transport system. It is necessary to consider this “spill-over effects” of urban rail system on travel choice and experience. On this basis, general travel satisfaction as a whole might be a more appropriate indicator to form a comprehensive image from a well-being perspective.

2.3. Attributes of the disparity in residents’ travel satisfaction Public transport travel satisfaction is affected by many factors. This can be summed up in four aspects: personal socioeconomic attributes, travel habits, environmental variables, and service quality and attitude (Zhang et al., 2017). The effect of the built environment, either objectively measured or subjectively perceived, on travel satisfaction has received increasing attention. Many studies have directly established the connection between subjective and objective accessibility and travel satisfaction. For example, Ye and Titheridge (2015) used the structural equation model to analyse the travel satisfaction of 1364 residents in Xi'an, China. Structural equations establish connections between demographic economic attributes, travel times, travel mode choices, travel satisfaction and subjective well-being. The results showed that there was a significant positive correlation between the level of traffic service for objective accessibility and travel satisfaction; mode selection, travel time and the need for public transfer in subjective travel choices also have a significant effect. The longer the travel time, the lower the degree of satisfaction for travellers who need public transfers, whereas residents choosing slow travel modes (e.g., walking and cycling) have higher satisfaction. Travel intensity and habits might influence satisfaction via physiological responses. Several psychological studies have evaluated the impact of accessibility by analysing the psychological pressure experienced by and the well-being of rail commuters. For example, Evans and Wener (2006) analysed the subway commuting of 208 people living in the suburbs of New York City and working in Manhattan (city centre). As the subway commuting time increases, the respondent's saliva cortisol rises at the destination. The greater the patience needed to perform a job, the easier it is to feel depressed and annoyed. This pressure has not been taken into account in the general equity analysis, but it has a greater impact on the commuter's performance and rest time. Sposato, Röderer, and Cervinka (2012) conducted a multiple linear regression on an online survey data of 363 commuters in Vienna, Austria, and they found that long-term commuting might weaken the traveller's sense of control over travel and generate pressure, resulting in dissatisfaction with the journey. Morris and Guerra (2015) further found that bus commuting had the greatest negative impact on mood in long-duration commutes of different modes. Socioeconomics also matters. According to Ajzen (1991)'s planned travel theory, the subjective perceptions of objective accessibility by different groups of people have impacts on both specific travel decisions and satisfaction. Office workers pay more attention to punctuality, frequency, driving safety and information (Guirao et al., 2016); student groups pay more attention to ticket purchase, onboard safety and reliability (Eboli and Mazzulla, 2009); some place more emphasis on comfort (Dell’Olio, Ibeas and Cecin, 2011); women are more concerned with neatness and security (Abenoza et al., 2017; Yavuz and Welch, 2010). Therefore, it is necessary to examine the impact of subjective and objective accessibility on travel satisfaction, and to control socioeconomic factors and attitude preferences. Susilo and Cats (2014) summarised the satisfaction with different modes of travel in different travel groups. They found that overall travel satisfaction was affected by past travel experience, expectations and subjective well-being. Abenoza et al. (2017), based on a Swedish study, also found that residents who travel frequently using public transport were more likely to feel satisfied with it. Mouwen (2015) found that increasing public transport levels led to different degrees of satisfaction in different social groups. An increase in service density increases the satisfaction of senior citizens over 65 years of age, suburban line commuters and downtown residents more than other groups. Current discussions on travel satisfaction concentrate on public

2.2. Regional disparities of travel satisfaction in an urban context Increasing research has provided evidence of a link between transport access difference and transport inequality in the cities. Low income, low education, rural migrant or minority people who live in places where transport options and access are undesirable also suffer from high travel times and costs (Li and Zhao, 2018; Zhao, 2015). As a result, their travel destinations for both work and non-work purposes are limited; longer travel times also have negative impacts on their performance in the workplace or in household responsibility. From this perspective, inequality in transport access might bring more extensive social inequality. One of the goals of city government in promoting vertical social equity is to provide improved transport service to areas where many people cannot afford travel options other than public transport (Deakin, 2007; Garrett and Taylor, 1999; Murray and Davis, 2001). Many Canadian and Australian cities have better equity promoting public transport service than other areas. For example, Currie and Delbosc (2011) found that in Melbourne, young and low-income people have good access to public transport; El-Geneidy et al. (2016) found that in Montreal, disadvantaged groups have good job accessibility. Neighbourhoods with higher proportions of disadvantaged people, in turn, have lower working commute times and costs. However, evidence on regional and social disparities in travel satisfaction is scarce. Exceptions include Abenoza et al. (2017)'s study in the Swedish context, where the authors found differences in travel satisfaction between urban and rural areas, and among different market segments. But further research is needed to clarify the already heterogeneous urban and suburban areas where living with different proximity to activity and employment centres might influence residents' daily travel. It is necessary and important to investigate whether large 68

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informal housing, which is built on rural, collectively owned land, is isolated from the urban metro system. In the past decade, as Beijing has expanded, different studies have investigated the problem of unequal access to employment and service opportunities due to disparity of residential locations. Most studies have shown that the difference in spatial and economic attributes (mainly the income and employment attributes and their extended choices for transport modes) create an unfair opportunity acquisition. (1) Spatially, the farther away from the city centre, the higher the cost of commuting (Denstadli et al., 2017). (2) In terms of income, lowincome people are less able to obtain opportunities and need to pay higher prices. This is on the one hand because of gentrification. It is on the other hand due to the lower car ownership and worse public transport accessibility. Zhao and Li (2016) identified a significant transport inequity problem in Beijing in their research on job-housing balance. They found that the work commute duration of low-income and middle-income earners was significantly higher than that of highincome earners. Denstadli et al. (2017) found that there was a significant positive correlation between annual household income and commuting time in Beijing.

transport or wider transport service user experience, aiming to facilitate service quality in urban transport systems. The techniques used in existing studies emphasise selecting the most representative factors that reflect users' experience. There is, however, little discussion on travel satisfaction as an important transport equity indicator, with few exceptions (Abenoza et al., 2017). This might be because of the highly subjective and affective characteristics of satisfaction. In fact, disparity in satisfaction in an urban context has strong links to social inequality. If under a certain level of satisfaction psychological or physical infringement may occur, efforts should be made to fulfil this satisfaction. Rawls's primary good concept is extended here to primary travel satisfaction. Primary travel satisfaction is distinguished from advanced travel satisfaction, the reduction of which might result from Dworkin's “brute luck” (dissatisfied travel because all available traveling options for a resident exceed her or his budget for travel time or expense). In comparison, if unsatisfied travel experience is due to “option luck” as defined by Dworkin (such as dissatisfaction with the cost due to choosing expensive limousine services for traveling), it is not the fault of policymakers (Dworkin, 2002, 2017). It might also be legitimate to apply sufficientarianism to the judgement of satisfaction equity, which encourages policymakers to allocate more resources to disadvantaged groups. Due to the inadequate evidence of spatial and social inequality in residents' satisfaction with general travel and the mechanisms beneath it, this paper contributes evidence from a rapidly growing context.

3.3. The fast development of the Beijing metro To cope with the possible social problems brought about by the evolution of social-spatial structure, the Beijing Municipal Government has implemented three policies: (1) increasing the proportion of small residential units, (2) increasing the supply of public housing, and (3) building rail transport on a large scale. In the effort to increase the occupancy rate of public transport, the construction of rail transport has become key capital investment. Beijing's rail transport mileage has grown from 114 km in 2000 to 554 km in 2015, and it will be nearly 1000 km in 2021. In 2015, the total length of the Beijing subway was 554 km, and the average daily passenger capacity was approximately 11 million. It has become the largest metro network in China. Metro has been playing an increasingly important role in residents' daily travel since the early 2000s. As Figs. 3 and 4 show, the mode share of metro in public transport has increased from a little more than 10% to around 40% in only 10 years. In 2015, the mode split of metro in all travel modes reached 25%. Taking the metro is almost twice as fast as the regular public bus in peak hours. However, over similar distances, the average traveling time by car is still much shorter than by using metro (Table 1).

3. Context 3.1. The city of Beijing Since the reform and its opening up, Beijing has experienced rapid urbanization and economic development, with its population increasing from 8.71 million in 1978 to 21.729 million by the end of 2016, and its urbanization rate increasing from 55% in 1978 to 86.5% in 2017 (National Statistical Bureau, 2018). Per capita GDP doubled from 1996 to 2003, quadrupled from 1996 to 2009, and was 6.4 times that of 1996 in 2016. Urban construction land expanded from 1150 km2 in 2003 to 1586 km2 in 2014. Average salary increased from ¥10,616 in 1996 to ¥122,749 in 2016, a 13.75% annual growth. Average green space increased from 8.57 km2/person to 16.01 km2/person in 2017, while the unemployment rate has decreased from 2.1% in 2005 to 1.4% in 2016 (National Statistical Bureau, 2018). Increasing daily travel is the result of changes in daily life, rather than work or school commuting. Trips for personal business, shopping, visiting friends and receiving packages grew 5.8% from 2014 to 2015 (Beijing Transport Institute, 2016). These indicate rapid economic development and fast social transformation in the city.

4. Data and methodology 4.1. Survey data The survey of this study was conducted in May 2017. The questionnaire sample was stratified and sampled according to the proportion of population (PPS sampling). Firstly, there was a preliminary analysis of the job-housing situation in each neighbourhood (jiedao), according to the sixth national census data (2010) and the third national economic census data (2013). Second, based on the population density, the distribution of employment opportunities and the overall urban planning objectives, typical areas were selected, which mainly consist of residential, work-based, mixed-use and planning oriented land. Third, based on housing sources (units, commercial housing, government welfare housing), housing prices, community built-up years and built environment around the community, a total of about 40 residential communities in Beijing were selected. Fourth, according to the proportion of the population in each of the 40 communities, 50 samples were taken for communities with less than 1000 households, 100 samples were taken for those with 1000–2000 households and 150 samples were taken for those with more than 2000 households. Finally, the number of samples was adjusted according to the population distribution within the city. A total of 4043 valid questionnaires were

3.2. Spatial structural evolution in Beijing With the rapid economic and social change came the change in social-spatial urban structure. This brings profound impact on residents’ daily lives, especially with the legacy of Danwei system. The supply of urban resources and the desire of residents for a better life conflicted with the pursuit of opportunities. As the city continues to expand, jobhousing imbalance starts to appear. Fig. 2 shows the main job and residence centres, which were also surveyed in this study. The job centres in the city are in the east (Guomao, Chaowai, Jianwai), southwest (financial district and Fengtai) and northwest (Zhongguancun) within the fourth ring road, whereas residences in the city centre are concentrated more in the east (Wangjing) and centre (Qianmen, Jiaodaokou). Job centres in the suburbs are mainly in the northwest (Shangdi), east (Tongzhou) and south (Yizhuang and Tiangongyuan). Suburban areas contain huge numbers of residences. They are scattered outside the fifth ring road in different directions. Suburban residence and job centres have radial metro connections to the city centre. However, most 69

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Fig. 2. Spatial distribution of residential areas (pink points) and respondents (red points) in Beijing. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

Existing studies have shown that these variables have connections with residents’ travel in the city. They include not only regular socio-economic variables such as gender, income, age and education, but also some contextual information. For example, there is a binary variable indicating whether the resident has a Beijing hukou or not. A hukou is a

collected. As shown in Fig. 2, pink points represent central points of Beijing's residential areas, which include all the selected residential areas. The locations of respondents surveyed in these areas are marked as red points. The socio-economic attributes of residents are shown in Table 2.

Fig. 3. The evolution of public transport mode shares in Beijing. Source: Beijing Transport Institute (2016) 70

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Fig. 4. Mode split of Beijing residents in daily travel in 2015. Source: Beijing Transport Institute (2016)

studies. Besides travel time, another four indicators were collected using a Likert-type scale, namely travel cost, travel distance, travel convenience and travel comfort. The perceived travel time, cost and distance comprise the dimension of travel intensity, while the perceived travel convenience and comfort together indicate travel experience. The selection of these four succinct but comprehensive indicators is founded on two considerations. First, it is based on existing investigation into travel satisfaction of public transport users, including Stuart et al. (2000) research into the New York City Subway (they designed 11 indicators on service quality and delivery such as travel cost), Lai and Chen (2011) study in Kaohsiung, and Friman and Fellesson (2009) studies in nine European cities (using principal component analysis to summarise 17 satisfaction indicators into four categories: comfort, efficiency, safety and professionalism). Second, satisfaction on a single mode might not reflect residents’ complex combinations of daily travel choice, ranging from mode choice combinations to trip chaining. As indicated by Ettema et al. (2016), public transport experience is also influenced by the journey to and from the station. Furthermore, subordinate transport systems in the cities are interconnecting, therefore

household registration in China. Residents who have hukou in a city have permanent residency in that city. It entitles them to exclusive education, healthcare resources and the right to commodity housing and private vehicle purchases without other documents. Also, in several studies of Beijing, commute expense and costs vary among different occupations and residence types. Residents who work in governments or public institutions have advantages over other job types in accessing job and other opportunities. On the other hand, residents who live in affordable housing or social housing have disadvantages in public transport access. The distributions of different categories broadly match the population, except that age is slightly right-skewed. The finding regarding age is consistent with previous studies (Dill and Voros, 2007). Candidate variables and the according measurements are in Table 3. Residences were classified in five categories to observe differences in regional disparities of expectation-reality discrepancy and the relationship between this gap and travel satisfaction. This mainly focused on work commute times, as travel intensity is easier to compare quantitatively, and travellers perceive it more accurately. As the previous section showed, it is also a regular indicator in satisfaction

Table 1 Average travel distance, time use and speed per trip by mode traveling in Beijing city (inside the 6th ring). Source: Beijing Transport Institute (2016). Travel mode

public bus subway taxi private cars Employee shuttle bus bicycle walking

average travel distance (km)

7.3 13.3 9.9 13.2 16.7 3.6 1.9

average time usage (min)

average speed (min)

am peak (7:00–8:00)

pm peak (17:00–18:00)

am peak (7:00–8:00)

pm peak (17:00–18:00)

60.5 62.3 44.2 39.9 59.4 21.4 15.5

58.1 56.8 47.5 40 61.5 23.1 15.7

7.9 13.3 8.9 14.7 16.4 10.6 6.9

6.3 9.9 9.2 15.1 17.7 8.9 10.1

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the efficiency of one system might have an impact on another. For example, the ridership share of metro in total public transport in the morning peak of a city might have a visible influence on the level of congestion, thus impacting other modes of travel such as the travel time of private cars, or the comfort of cycling.

Table 2 Survey data description. Observations

4043

Gender N % Male 2034 50.3% Female 2009 49.7% Personal Monthly Income (after tax) < ¥3000 477 11.8% ¥3000–5000

835

20.7%

¥5000–8000

1056

26.1%

¥8000–10,000 ¥10,000–20,000 > ¥20,000 Age < 20 20–30 30–40 40–50

686 768 219

17.0% 19.0% 5.4%

146 1865 1378 442

3.6% 46.2% 34.2% 11.0%

151 52

3.7% 1.3%

1708 2335

42.2% 57.8%

3354 186 503 0.38

83.0% 4.6% 12.4%

50–60 > 60 Hukou Beijing hukou Non-Beijing hukou Employment Full-time Part-time Unemployed Average car ownership

Housing Type Commodity housing Public housing Social housing Urban renewal replace housing Rent housing—privately owned Rent housing—publicly owned Inherited housing Job type Government Institution Stated-owned company Foreign company Private company Self-owned small business Education Middle school High school College Postgraduate

N 1161 108 195 189

% 31.1% 2.9% 5.2% 5.1%

1534

41.1%

255

6.8%

289

7.7%

148 476 640 205 1795 220

4.2% 13.7% 18.4% 5.9% 51.5% 6.3%

366 543 2422 655

10.1% 32.4% 43.6% 14.0%

4.2. Rail transport-related opportunity measurement The characteristics of service land use were indicated by geocoded establishment address density. The geocoded address data was retrieved from the Application Programming Interface (API) of Baidu Map (http://lbsyun.baidu.com), a leading Chinese online map provider. Some 35 services under four categories (dining, shopping, personal businesses, and leisure) were retrieved from the 110 total formats, representing 280,088 of the total 640,000 total geocoded points, as shown in Table 4. The remaining addresses included residences and accommodations, companies/governments/non-government organizations/institutes, places of interest and transport infrastructure. These four categories were selected to indicate service provision based on their maintenance (household activities that people need to perform on daily basis) and discretionary (social, recreational and entertainment activities) features as well as “higher measurement reliability and validity for empirical investigation” (Fan and Khattak, 2009; Gould and Golob, 1997). Bus stop locations were retrieved as accessibility indicators. A gross density indicator counting all sorts of addresses was generated, and it was intended to distinguish different levels of general development density among stations. The number of each of the 35 types of addresses as well as the gross service density indicators were calculated using 800 m scales for each of

Table 3 Candidate variables in the models. Category

Variable

Explanation and Measurement

Socio-demographics

Gender Age Monthly income

Binary variable (1 = male, 0 = female) Continuous variables Monthly individual income of the respondent (Unit: CNY) in the form of Categorical variable (< 3,000, 3000–5,000, 5001–8,000, 8001–10,000, 10,001–20,000, > 20,000) Categorical variable (junior school, high school, college, postgraduate) Binary variable (1 = have Beijing hukou, 0 = do not have Beijing hukou) Continuous variable (entropy index on the level of mixture among dining, shopping, life service and leisure service of the respondent residence's nearest metro station) Continuous variable on the gross density of POI within 800 m of the station nearest to the respondents' home Continuous variable (entropy index on the level of mixture among different type of enterprises by the nearest metro station to the respondent's residence) Continuous variable on the enterprise density of POI within 800 m of the nearest station to the respondent's home Closeness of the respondent residence to the nearest metro station in the Beijing metro system Betweenness of the respondent residence's nearest metro station in the Beijing metro system Perceptual levels of time value during travel (−2 = very dissatisfied, −1 = dissatisfied, 0 = neutral, 1 = satisfied, 2 = very satisfied)

Built environment

Education Hukou Land use mixed Land use density Employment diversity Employment density

Attitude towards time

Expectation-reality discrepancy Community characteristics

Travel satisfaction

Closeness centrality Betweenness centrality Travel time is wasted The only purpose of travel is to reach the destination Expected commute time Actual commute time Number of households Residential area in city centre Employment area in city centre Residential area in city suburb Employment area in city suburb Informal housing Travel time Travel distance Travel cost Perceived convenience Perceived comfort

Expected ideal work commute travel time Actual work travel time per trip continuous variable (number of households in the respondent's community) Binary variable: whether respondent's residence is in this category (1 = yes, 0 = no) Binary variable: whether respondent's residence is in this category (1 = yes, 0 = no) Binary variable: whether respondent's residence is in this category (1 = yes, 0 = no) Binary variable: whether respondent's residence is in this category (1 = yes, 0 = no) Binary variable: whether respondent's residence is in this category (1 = yes, 0 = no) Perceptual levels of satisfaction in general daily travel time (−2 = very dissatisfied, −1 = dissatisfied, 0 = neutral, 1 = satisfied, 2 = very satisfied) Perceptual levels of satisfaction in general daily travel distance (−2 = very dissatisfied, −1 = dissatisfied, 0 = neutral, 1 = satisfied, 2 = very satisfied) Perceptual levels of satisfaction in general daily travel cost (−2 = very dissatisfied, −1 = dissatisfied, 0 = neutral, 1 = satisfied, 2 = very satisfied) Perceptual levels of satisfaction in general daily travel convenience on the way (−2 = very dissatisfied, −1 = dissatisfied, 0 = neutral, 1 = satisfied, 2 = very satisfied) Perceptual levels of satisfaction in general daily travel comfort on the way (−2 = very dissatisfied, −1 = dissatisfied, 0 = neutral, 1 = satisfied, 2 = very satisfied)

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Table 4 Services under the four generic categories selected as land use indicators. Generic Category

Service

Number

Generic Category

Service

Number

Dining

Tea house, Bakery, Café, Fast food restaurant, Casual dining, Overseas cuisine, Chinese cuisine Convenience store Supermarket Clothing Personal/beauty Home electrics Housing and building materials Shopping centre Traditional Chinese fresh market Speciality store Drug store

1835

Leisure

11,275

88,414

Personal businesses

Cinema and theatre Gym and sports Entertainment Park Square Hospital and clinic, Barber and beauty, Bath and massage, Ticket, Gas station, Auto maintenance, Intermediary, Law/accounting consulting, Post and parcel delivery, Utility service centre, Laundry and dry cleaning, Travel agent, Bank

13,231

Parking

Shopping

Bus stop

81,391

9537

Fig. 5. Spatial layout of land use diversity and density in the studied metro station area using point-of-interest indicators, compared with traditional land use characteristics.

method has clear implications for urban planners on how the combination of land uses is linked to different travel behaviour, one of the limits of using this approach is that it may underestimate diversity within a certain type of land use that attracts different shoppers, and it may further overlook vertical density and diversity. Diversity was calculated using an adapted Shannon entropy equation, expressed as:

the 220 stations studied. Traditionally, land use characteristics are measured by calculating the area of certain types of land use within a certain radius of a station (i.e., density) and calculating the entropy of various land types within a certain radius of a station (i.e., diversity). The picture on the left in Fig. 5 shows the combination of several land uses in one of the station areas in Beijing, Pingxifu Station on the northern suburban fringe of the 6th ring road. Within a 1,500 m buffer zone of Pingxifu station, there are nine types of land use, as described by the National Classification of Urban Land and the Standard of Land for Planning and Construction (No. GB50137-2011). Although this

Ei =

∑ Pi i

73

ln(Pi ) ln(i)

(1)

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difference between the expectation of the urban transport system and the actual travel experience (Lai and Chen, 2011; Susilo and Cats, 2014; Woldeamanuel and Cyganski, 2011). When urban transport design and public transport supply exceed residents' expectations, high travel satisfaction may result. When transport service quality cannot live up to residents’ expectations, travel satisfaction might be low. Therefore, it is possible that people living in areas with decent transport accessibility may have lower travel satisfaction due to higher travel expectations in terms of time or experience, whereas people living in less transportaccessible regions might have higher satisfaction due to lower expectations. This indicates the complexity of satisfaction-targeted transport policy. Here, travel satisfaction on time is compared with the discrepancy between travel time expectation and actual travel time. This comparison aims at examining whether these two measurements are consistent. Discrepancies between expectation and actual work commute time for residents living in different locations and with different monthly income are estimated. Table 7 displays the expected commute time of residents living in different urban regions. It does not show significant differences in between urban regions. However, significant regional disparities exist in actual travel time. As shown in Fig. 6, the discrepancy between expected and actual travel time is generally lower in urban areas and higher in suburban areas, especially those with large concentrations of residential communities. When compared with travel time satisfaction, higher discrepancies in travel time generally correspond with lower levels of satisfaction. These results are more likely to happen in suburban areas. Although living in Beijing's suburban job centre might help to reduce discrepancies via commute time saving, satisfaction is not significantly different from other suburban areas. On the other hand, residents living in job centres in the city centre have higher levels of travel time satisfaction than other groups. Measurements of other travel satisfaction indicators present a similar pattern to travel time, as shown in Fig. 7, as there are significant regional disparities in satisfaction between the city centre and suburban areas. The relatively larger gap appears in travel cost, with which suburban residents have significantly lower satisfaction. Disparity of satisfaction exists not only among different regions and resident types, but also within each community. Fig. 8 shows an example of spatial disparity in travel convenience satisfaction, which provides two instances of satisfaction of residents living in two major residential areas; the bottom left displays the suburban residential area Huilongguan, while the bottom right displays the city centre residential area Wangjing. They both have significant variations within the surveyed communities. We conducted a comparison of residents with different monthly income, as displayed in Fig. 9. Discrepancies increased as income increased, which resulted from higher actual travel time for the higher income group, while expectations for travel time stayed similar among different groups. When we compared this travel time discrepancy with satisfaction, it was interesting to note that the pattern was consistent with current theory for residents with average or above average income. However, for residents with below average income, a lower discrepancy between expected and actual travel time brings lower travel time satisfaction, rather than the opposite. Fig. 10 shows that this unexpected lower satisfaction for lower income residents exists not only in travel time, but also in all other indicators. Many existing studies tend to attribute the lower travel or life satisfaction of disadvantaged groups to their unsatisfied expectations. However, it seems as though the discrepancy or actual burden alone cannot explain travel dissatisfaction for lower income residents. In fact, actual travel time for lower income residents is lower than other groups in Beijing. This is easy to understand since their skill set and daily life need can be fulfil in local neighbourhood. While chasing higher pay jobs and higher quality goods many of the times need to commute further. This calls for a more thorough investigation of travel

Table 5 Summary statistics for the land use in different metro station catchment areas in Beijing: indicated by point of interest counted using 800 radial scale. Category

Variable

Mean (Std. Dev.)

Land use diversity

General service diversity Dining diversity Shopping diversity Life service diversity Leisure diversity Employment diversity Dining density Shopping density Leisure density Life service density Employment density Number of bus stops Number of public car parks/on-street parking spots

0.81 (0.10) 0.44 (0.21) 0.67 (0.16) 0.64 (0.24) 0.70 (0.15) 0.59 (0.19) 175 (152) 210 (244) 120 (98) 41 (36) 122 (128) 11 (6) 46 (37)

Land use density

Where i = type of development under the general category, Pi = proportion of the development count of the i th type. The results are in Table 5.

5. Analysis and results 5.1. Regional and social disparity in travel satisfaction Unlike many other studies, which have tried to build a link between public transport systems and their users' satisfaction, this study attempts to describe a more general travel satisfaction. This effort had two foundations. First, from the perspective of transport policymakers, general satisfaction in daily travel is more capable of reflecting the ultimate purpose of public transport investment. Such public fiscal inputs aim either to enhance the satisfaction of those in need of public transport themselves (from a sufficientarian or horizontal perspective) or to facilitate the satisfaction of all residents, including those who do not regularly use public transport-related services but benefit from its improvement (from a utilitarian or vertical perspective). Second, individuals’ travel mode selection can be quite flexible. This is especially the case for non-work travel, such as shopping. As Hanson (1980) has mentioned, shopping destination can be altered due to more attractive sales elsewhere. The change of destination in some daily travel might change the mode used as well. Travel mode used also varies due to personal moods on specific occasions, as travel itself might not primarily be utilitarian and time-saving. Sometimes it can have a more recreational purpose. Moreover, the function of public transport system goes far beyond the use of train itself; it also includes travel experience changes due to changes in the built environment along the transport lines near people's residences. Accumulating evidence globally has shown that more compact and diverse land use (which is usually advocated in transitorient development) might have impacts on residents' travel destination choice, mode choice and trip chaining preference. Thus, it is important to provide a more panoramic view of residents' travel satisfaction. In this study, general travel satisfaction is measured in two dimensions: perceived travel intensity and travel experience. Intensity measures travel time, monetary cost and distance, while travel experience evaluation is divided into convenience and comfort, as explained in Table 3. Resident satisfaction in different regions is in Table 6. Looking at the average values, general travel satisfaction of residents living in the city centre is higher than that of suburban residents. Those who live in suburban employment centres have the lowest travel satisfaction, when compared with other areas. Travel satisfaction difference is usually explained using the 74

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Table 6 Average resident travel satisfaction in different types of residence.

Residential area in city centre Employment area in city centre Residential area in city suburb Employment area in city suburb Informal housing

Observations

Time

Distance

Cost

Convenience

Comfort

1025 859 891 911 261

3.52 3.6 3.4 3.38 3.41

3.56 3.62 3.43 3.46 3.44

3.4 3.44 3.23 3.19 3.3

3.56 3.62 3.43 3.46 3.44

3.57 3.5 3.36 3.37 3.42

five satisfaction types. On the other hand, betweenness centrality of the home nearest subway station to residents has significant positive impact on their satisfaction with travel duration, distance, convenience and comfort. One possible explanation is that travel from a metro station with higher betweenness means a lower chance to transfer to other lines. This might not reduce cost but it saves time and distance needed to walk, considering the long distance walking needed in transferring. Second, the attitude towards time also influences all five satisfaction categories. Residents who prefer to save travel time have higher overall satisfaction with travel. Superficially, this finding is counterintuitive, since people who are keen on saving time might be more easily frustrated with long travel times. However, it is possible that residents who prefer short travel times might significantly reduce their commute time by selecting alternative destinations or faster modes of travel. Higher satisfaction with travel might then result from reduced travel time. Third, the impacts of socioeconomic factors on the population is significant. Gender and age have greater impacts. The elderly and men are less likely to feel satisfied with travel. The negative relationship between age and satisfaction is inconsistent with some international research findings (Mouwen, 2015). One possible explanation is that disabled assistant facilities and social friendliness are not expected for senior citizens who travel, whether using public transport or on foot. For example, there are few vehicle separation trails on pedestrian lanes; non-motorised lanes are full of bicycles or other obstacles. Women's satisfaction is higher than men's. On the one hand, women may be relatively more patient. On the other hand, if they use the subway to travel, the clean and orderly and safe environment of the Beijing Subway makes them feel more satisfied when they travel. This is consistent with some international studies (Dell’Olio et al., 2011).

Table 7 Expected travel time of residents living in different regions (unit: minute).

Residential area in city centre Employment area in city centre Residential area in city suburb Employment area in city suburb Informal housing

Average

Std. Dev.

Max

Min

Observations

25.03 23.79 24.24 23.18

12.97 12.93 14.30 13.11

120 100 120 100

1 0 0 1

1025 859 891 911

26.82

13.95

120

1

261

satisfaction determinants. 5.2. Modelling the role of rail transport-related opportunities in satisfaction The above analysis shows that a disconfirmation between expected and actual travel time might contribute to some level of satisfaction disparity among either regions or income groups. This cannot simply be explained by descriptive analysis. Increasing empirical evidence in recent years suggests that the accessibility of not only metro stations, but also opportunities along the metro system might have the potential to lower travel times or costs. However, there is still little evidence on how different levels of accessibility of metro and its related opportunities might further impact travel satisfaction. Accordingly, models are designed as an attempt to assess the impact of the built environment and metro-related accessibility on residents’ travel satisfaction, with attitude and socioeconomic characteristics controlled. Table 8 shows the modelling result of the order-logit regression of residents’ travel satisfaction on travel cost, time, distance, convenience and comfort. Based on the results, there are three findings. First, the accessibility of rail transport has an impact on travel satisfaction, but different kinds of accessibility vary in their influence. In comparison, the greatest impact on travel intensity is the degree of mixture land use in the core area of the home nearest metro station (800 m scale from the station). The higher the degree of mixture, the higher the satisfaction with travel. This effect is significant for all the

6. Discussion This paper continues the current investigation on the spatial and social disparity of travel satisfaction in urban areas, discusses how travel satisfaction depends on the discrepancy between travel time

Fig. 6. Expected and actual time discrepancy in work commute by type and location of residence. 75

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Fig. 7. Travel satisfaction by residence location and type.

level of travel satisfaction, compared with higher incomes. One possible reason for this is that as part of life satisfaction, travel satisfaction is shaped by other factors besides the transport system. These factors profoundly influence residents’ non-work travel choices and experience, but might not be perceived as part of travel. It can be possible that lower travel time satisfaction is due to less accessible life service opportunities in local communities. In this situation, individuals need to spend longer time to fulfil non-work needs. Lower incomers, with less car ownerships and living in retail inadequate areas, are more likely to confront with this circumstance. Modelling results in the fifth section empirically confirm this assumption by finding that opportunities and land use along the transport system might have significant impacts on residents' travel satisfaction. For example, higher level of mixed land use of residents’ homes nearest metro station have positive effects on travel satisfaction. This finding also extends previous investigation on the role of TOD in sustainable travel (Zhao and Li, 2018). This study thus supports the assertion that the public transport system might play a role in mitigating travel satisfaction inequality from a sufficientarianism perspective. Designing more mixed land use and station centrality in areas disadvantaged groups concentrate might increase vertical equity. This equity goal can be realised by increasing destination options for people with lower incomes or those living in suburban areas. Lower satisfaction of higher income residents is not considered to be socially unequal because this belongs to option luck, rather than brute luck (from Dworkin's point of view). Higher income people's longer actual travel times are more likely to result from pursuing better opportunities (Dworkin, 2017). Another benefit of Beijing's metro system is that many newly built stations and facilities are tidy and clean, which might improve disadvantaged groups' travel satisfaction and reduce inequality, as can be seen from the result that lower income residents have higher perceived satisfaction with comfort. The positive role of the rail system in promoting equity in travel satisfaction is consistent with studies contending that accessibility is an important determinant of satisfaction. For example, Woldeamanuel and Cyganski (2011) concluded based on a German travel panel data analysis that low accessibility resulted in lower overall travel satisfaction. However, it is also necessary to pay attention to significant effects from some control variables. These variables together indicate that there are significant differences within the community. In the same community, even within the same family, satisfaction levels may differ. Older people are less satisfied. This might be due to a perceived lack of security in the travel environment, such as lack of accessibility and

expectation and reality, and further explores the impact of public transport-promoting policies and planning on residents’ general travel satisfaction. Inequality in travel satisfaction is indicated by regional disparities and socioeconomic variations. Regional disparity in travel satisfaction exists in Beijing. Overall commuting satisfaction of residents is higher for travel time, distance and convenience, but significantly lower for travel cost. Travel cost displays larger gap in regional satisfaction disparity. Residents in suburban areas are less satisfied with travel than those who live in central areas. In particular, they are less satisfied with travel cost. Residents living in job-rich areas in the city centre have higher satisfaction with travel duration, distance, cost and convenience. This might indicate both a decent job-housing-service balance (ideal job and service opportunities in close proximity) and convenient transport facilities for residents living in city centre. However, they perceived lower levels of comfort in travel than their counterparts in residence-concentrated areas in city centre. This might result from annoyance with the large population inflow into the neighbourhood in peak hours, bringing difficulties in parking, crowdedness on pavement, in public transport sites or even restaurants. Residents in major suburbs have the lowest satisfaction rates with travel when compared with other groups, including those in informal housing. The distribution of travel satisfaction among different regions is consistent with the discrepancy between actual and expected travel time. The conclusions of regional differences in satisfaction and the disparity between actual and expected travel time are consistent with several existing studies (Bocarejo S & Oviedo H, 2012; Fellesson and Friman, 2012). For example, Bocarejo S and Oviedo H (2012) found from a case study of Bogota's BRT system that the gap between actual and desired travel time in high-income areas was less than 10%, while the gap enlarged dramatically in lower- and middle-income regions. In the same study, the expected travel expenses in high-income areas were about 14% lower than the actual cost. However, this gap was more than 50% in middle-income areas and more than 85% in low-income areas. But this study further identified the inconsistent distribution of travel satisfaction and level of disconfirmation (expected and actual time difference) among income groups. The distribution of travel satisfactions is in bell-shape, while the distribution of the travel time disconfirmation continuously increases as income increases. This finding questions the common practice in equalling level of disconfirmation with level of satisfaction. The results show that for lower income residents, though they have relatively lower disconfirmation between expected and actual travel time, they seem not to have higher 76

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Fig. 8. Regional disparities of satisfaction on perceived travel convenience.

that smaller disconfirmation does not necessarily lead to higher travel satisfaction, as can be seen in the analysis of lower income residents. The mismatched disconfirmation and travel satisfaction for lower income residents actually reflects transport inequality, as it might impair the primary satisfaction of disadvantaged groups. However, as many recent studies on transport inequality have suggested that one of the shortcomings of sufficientarianism is a lack of criteria for determining a lowest threshold (Lucas et al., 2016; Nahmias-Biran et al., 2017; Pereira et al., 2017) (in this case, the minimum satisfaction for different dimension), a subjective evaluation scale might still provide hints for this minimum setting. This mismatched disconfirmation and travel satisfaction also indicates that travel satisfaction might be influenced by

social friendliness, reducing the chance of a trustworthy and safe travel experience. Gender difference is also significant. Women's satisfaction is relatively higher than that of men. This might be because women are generally more patient and more sensitive to travel safety and tidiness. The clean, orderly and safe environment of the Beijing subway satisfies these needs well. This paper carefully proposes two theoretical contributions: First, disconfirmation reflects, but is not necessarily equal to, satisfaction in travel, at least not as clearly as that in marketing or psychological research. Existing definitions of travel satisfaction tend to describe it as a good reflection of the discrepancy between expectation and reality in different travel attributes, such as travel time. We contend 77

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Fig. 9. Expected and actual time discrepancy in work commute by income group.

facilitated policies that better integrate transit and land use for disadvantaged groups and areas, such as: (1) locate affordable housing in close proximity to metro stations with higher betweenness centrality; (2) integrate metro system with life service provision by locating more public services and retail in the catchment areas of major suburban metro stations. Second, provide disadvantaged groups and areas with higher accessible service options, such as: (1) promote general mixed land use from the level of city's master plan, ensuring equivalent supply of residential, commercial and green space lands; (2) cooperate with private sectors like e-commerce or delivery platforms to locate branch distribution centre in major suburban residential areas. This strategy might help to enhance accessibility of lower incomers for their nonwork needs (considering the higher smartphone ownerships and relatively low cost of delivery in Beijing). Third, a more advanced fare system design and future metro line planning that reduce monetary and time cost of lower incomers living in suburban areas. Fourth, a higher walkable and elderly-friendly neighbourhood design that provide safe and convenient living experience. These efforts altogether are supportive in mitigating transport inequality.

factors other than travel itself. The significant effects from attitudes and socioeconomic characteristics empirically support this assumption. Second, the urban rail system might play a role in mitigating the inequality of travel satisfaction from a vertical perspective. The results reveal that the centrality of residents' home nearest metro station has significant positive relationship with different travel satisfaction measurements. This means that living near a metro station with better access to other nodes facilitates travel satisfaction. This has an impact not only on public transport users, but also on a more extensive group of residents, including those who only drive cars, since the scope of urban rail system in this study not only include rail service but also built environment surrounding the stations. This 800 m of catchment areas service as a good indicator of nearby communities’ service and job provision. In this sense, disadvantaged groups such as lower wage earners or lower skilled workers might further benefit from more equal rail distribution. In this situation skill-matching jobs or affordable shopping and services are easier to be accessed. For policy implication, on the one hand, current metro transit developments have some merits that are helpful for equality promotion. These include the high design standard of metro station environment (creating clean and tidy experience), and high efficient metro train operation in term of frequency, punctuality, and safety. While on the other hand, future improvements need to be addressed to enhance primary satisfaction. These include efforts from four aspects. First,

7. Conclusion Transport equality is one of the key aspects of sustainable urban transport. The variations in residents' travel satisfaction between

Fig. 10. Travel satisfaction by income group. 78

79

beta −0.0289 −0.0639 0.0129 −0.0101 −0.0196 0.0964 0.0568 0.0147 −0.0193 −0.0780 0.0739 0.0259 −0.0407 0.0135 −0.0043 0.0437

coefficient −0.00022*** −0.161*** 0.0336 −0.0148 −0.0493 0.0963*** 0.0654*** 0.0159 −2.39e-05 −3.45e-05*** 1.700*** 6.31e-05 −0.338* 0.000170 −0.367 1.556** 3.052*** 2309 0.053

Socioeconomic characteristic

Age Gender Marriage Education Beijing hukou Attitude towards travel time Travel time is wasted Would plan travel to reduce time The only purpose of travel is to reach destination Residential community accessibility Distance from home to the nearest station Number of households in the community Land use diversity – 800 m Land use density– 800 m Job opportunity diversity – 800 m Job opportunity density – 800 m Centrality – closeness Centrality – betweenness

Constant Observation Pseudo R2

***p < 0.01, **p < 0.05, *p < 0.1.

Satisfaction with travel duration

Variables

Table 8 Order logit regression on residents’ travel satisfaction.

2.988*** 2309 0.047

−5.12e-06 −3.53e-05*** 1.304** 3.10e-05 −0.206 0.000477 −0.537 1.561**

0.0957*** 0.0454* 0.0277

−0.00020*** −0.114*** 0.0657 0.00232 −0.0721*

coefficient

−0.0042 −0.0801 0.0569 0.0128 −0.0250 0.0381 −0.0064 0.0441

0.0962 0.0396 0.0257

−0.0269 −0.0456 0.0254 0.00159 −0.0288

beta

Satisfaction with travel distance

3.842*** 2309 0.056

2.85e-05 −3.72e-05*** 1.410*** 5.46e-05 −0.301* 0.000169 0.696 0.408

0.0810*** 0.0756*** 0.0399*

−0.00021*** −0.115*** −0.0194 0.0426* −0.0330

coefficient

0.0231 −0.0842 0.0613 0.0224 −0.0363 0.0135 0.00820 0.0115

0.0811 0.0657 0.0369

−0.0273 −0.0459 −0.0075 0.0291 −0.0131

beta

Satisfaction with travel cost

3.099*** 2308 0.043

−4.89e-05** −5.34e-05*** 2.650*** 2.01e-05 −0.652*** 0.000161 −3.268 2.868***

0.105*** 0.0430* 0.0288

−0.00022*** −0.218*** −0.0296 −0.0226 −0.0688

coefficient

−0.0381 −0.116 0.111 0.00792 −0.0756 0.0123 −0.0370 0.0775

0.101 0.0359 0.0256

−0.0276 −0.0832 −0.0109 −0.0148 −0.0263

beta

Satisfaction with travel convenience

3.554*** 2309 0.061

2.05e-05 −4.33e-05*** 1.265** 4.12e-05 −0.524*** 0.000550 −0.828 1.591**

0.111*** 0.0333 0.0443**

−0.00019*** −0.106*** 0.0235 −0.0470* 0.0144

coefficient

0.0165 −0.0972 0.0546 0.0168 −0.0627 0.0434 −0.0097 0.0445

0.110 0.0288 0.0407

−0.0252 −0.0419 0.00898 −0.0318 0.00567

beta

Satisfaction with travel comfort

P. Zhao and P. Li

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different social groups has been a new issue in the field of transport inequality. Although some empirical evidence for this issue has been reported, there is still little investigation of the expectation confirmation mechanism underneath satisfaction, as well as inadequate attempts to probe how the discrepancies in expected and actual travel relate to satisfaction. Based on an analysis of regional and socioeconomic disparities in travel satisfaction, this study has discussed how travel satisfaction responds to discrepancies between travel time expectation and reality, and it has further explored the impact of public transportpromoting policies and planning on residents' general travel satisfaction. The results show disparities of region and income in Beijing. The suburban residents and those earning the least and the most perceive lower travel satisfaction. Higher income residents' lower travel satisfaction is not applicable to primary satisfaction, as it is the result of pursuing better opportunities and option luck. However, the travel discrepancy in lower income residents reflects transport equity issues, as it is the result of lack of options to access necessary and affordable opportunities, or brute luck. The relationship between low-income residents’ disconfirmation of travel time expectation and satisfaction is not consistent with theoretical satisfaction assumptions, which assert that satisfaction is negatively correlated with the gap between expectation and reality. The results indicate that an urban rail system might play a role in mitigating the inequality of travel satisfaction from a vertical perspective. In particular, mixed land use and locating affordable housing in close proximity to metro stations with higher connection convenience would be useful to promote transport equity. For future research, more attention is needed on the comparison of discrepancies between disconfirmation and satisfaction in measurements other than travel time to establish a better and more comprehensive understanding of how travel satisfaction develops.

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