周素红, 宋江宇, 宋广文.
[ZHOU Suhong, SONG Jiangyu, SONG Guangwen.
Examining the dual-levels impact of neighbourhood and individual variables on car use on weekdays in Guangzhou[J]. Acta Geographica Sinica
Examining the dual-levels impact of neighbourhood and individual variables on car use on weekdays in Guangzhou
ZHOU Suhong1,2,, SONG Jiangyu1,2, SONG Guangwen1,2
1. School of Geography and Planning, Sun Yat-sen University, Guangzhou 510275, China
2. Guangdong Key Laboratory for Urbanization and Geo-simulation, Guangzhou 510275, China
Excellent Youth Scientist Program of National Natural Science Foundation of China, No.41522104;
Key Program of National Natural Science Foundation of China, No.41531178;
Fundamental Research Funds for the Central Universities, No.15lgjc24;
The relationship between car travel and built environment is one of the hot issues in the urban studies. The existing researches mainly focus on the respective effects on car travel of individual demographic variables and built environment variables on car travel. Under the background of China's urban transformation and the social space differentiation, a growing number of scholars have examined the relationship between residents' demographics and their residential built environment. Quantifying the relative roles of the individual social attributes and the built environment in influencing car travel has a policy implication. This study applied a multilevel logit model which contains individual-level variables and neighbourhood-level variables to explore the impact on car use. It is concluded that urban residents' working-day car travel is influenced by multilevel variables associated to neighbourhood types. Most of the variation in the travel mode choice is caused by the difference among neighbourhoods. Travel mode choices have a strong neighbourhood contextual effect on car travel. As for the individual level, lower income and education level, collective unit profession, less minors in a family may help refrain the choice of automobile travel. As for the community level, improving bus stops density, building density, land mixing degree and commercial accessibility may help reduce car use ratio of working-day activities' travel. The mechanism of the relationship between two kinds of variables lies in the strength of market effect on urban residential space reconstruction. The residents who have similar social and economic attributes tend to choose the same type of neighbourhood, which has a similar built environment. These conclusions help us to have a better understanding of the mechanism behind the urban residents' working-day car travel and provide suggestions to alleviate the traffic problem by adjusting the multilevel variables in the similar type of community.
multilevel logit model;
多层Logit模型有多种参数设置,针对本文的研究问题和实际情况,不同社区关于小汽车出行的回归线拥有不同的斜率和不同的截距,在多层模型的个体层随机效应模型中将斜率和截距设为随机参数。同时本研究关注不同社区小汽车出行的差异（截距的不同）,并寻找社区层能够解释这种差异的变量,因此将个体层得出的截距看作随机系数,添加社区层的解释变量。斜率并不添加解释变量,仍然保持随机,设为随机成分的固定参数。本文借助HLM软件来完成多层模型,模型采用限制性极大似然（restricted maximum likelihood）估计（也称为收缩估计）,回归系数采用双尾t检验,方差/协方差部分采用卡方检验。多层模型由于分两层,拟合度衡量较为复杂,采用方差缩减比例来近似估计模型拟合度,类似单一层次回归中的R2 [36-37]。
① 工作日城市居民小汽车出行社区间分异明显,同时受个体层因素与社区层因素影响,社区层因素影响比例更大,受到明显的地理背景效应的作用。② 对于影响居民工作日出行方式的两层因素,个体社会经济因素方面,更高的文化水平、更高的个人月收入水平、非集体单位性质和家庭存在更多未成年孩子的居民工作日小汽车使用率较高;社区建成环境因素方面,提高建筑密度、用地混合度、商业可达性和公交站点密度会降低社区居民工作日出行使用小汽车的可能,而社区内更高的POI密度却会增多居民对小汽车的使用。③ 社区层面因素,建成环境因素和社区类型因素均在一定程度上解释个体层小汽车出行社区变异的背景效应（建成环境因素解释社区间21.38%个体出行方式的变异,社区类型因素解释社区间变异达78.83%）,其中社区类型因素的解释程度更好,即住在相同类型社区中的居民在出行方式选择上更加趋同,而社区类型表征的是社会分异。
Chatman DG.How density and mixed uses at the workplace affect personal commercial travel and commute mode choice. , 2003,1831(1): 193-201.
A high density of shops and services near the workplace may make it easier to carry out personal commercial activities on foot before, during, and after work, enabling reduced vehicle use during the rest of the day. Investigating this question is an important addition to the current research, which has focused on residential neighborhoods. Data from the 1995 Nationwide Personal Transportation Survey are used to investigate the influence of workplace employment density and share of retail employment on commute mode choice and vehicle miles traveled (VMT) to access personal commercial activities. The analysis controls for socioeconomic characteristics and accounts for the endogeneity of commute mode choice and personal commercial VMT by employing a joint logit-Tobit model. Employment density at the workplace is found to be associated with a lower likelihood of automobile commuting and reduced personal commercial VMT, while the presence of employment in the retail category does not play a significant role. Workplace density is more clearly related to reduced VMT and automobile commuting than to characteristics of workers' residential neighborhoods and could have significant influences on personal commercial VMT and automobile commuting when increasing over a large area. The results suggest that land use planners should focus on encouraging employment density to a greater extent than is the current practice, although further research is needed on the role played by correlated factors such as higher parking costs, increased road congestion, and better transit service.
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China’s market-oriented reform has not only revitalized the economy but also changed the physical structure of Chinese cities, which used to be largely determined by the socialist Danwei (or work unit) system. In order to understand the impacts of the reform and the influence of Danwei on jobs–housing relationships and commuting behavior, this study investigates whether there are differences in commuting behavior between individuals who live in houses provided by Danwei and those who reside in houses from private market sources in urban China. We apply the structural equations model to investigate the interactions between housing source (from Danwei or not), jobs–housing relationship, transport mode and commuting time in Beijing, the capital city of China. The results show that Danwei housing commuters have shorter commuting trips and higher usage of non-motorized transport mode than those who live in houses from the market sources. This finding implies that the diminishing influence of the traditional Danwei system and the market-oriented reform in urban development may have changed the jobs–housing balance and increased travel demand in Chinese cities.
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This paper contributes to the limited number of investigations into the influence of the spatial configuration of land use and transport systems on mode choice for medium- and longer-distance travel (defined here as home-based trips of 50聽km and over) in the Netherlands. We have employed data from the 1998 Netherlands National Travel Survey to address the question as to how socioeconomic factors, land use attributes, and travel time affect mode choice for medium- and longer-distance travel, and how their role varies across trip purposes: commuting, business, and leisure. The empirical analysis indicates that land use attributes and travel time considerations are important in explaining the variation in mode choice for medium- and longer-distance travel when controlling for the socioeconomic characteristics of travellers.
With the rise of humanism and improvement of living standards, improving the quality of lives is now one of the hot topics, which is also the foremost purpose of Time Geography. The using of T-GIS helps to meet the needs of Time Geography, with a strong requirement of representing the temporal and spatial relations. Based on the theories of T-GIS and Time Geography, the household survey is conducted on people's daily activities and travel logs in Guangzhou, China. A series of functions for recording and representing the spatio-temporal pattern for daily activities and travel chains is developed by VBA secondary development platform of ArcGIS. It is shown that urban center in inner cities is still attractive, which lure a lot of people during the whole day. Residents, especially those who live in suburban areas have to change their daily activity pattern to adapt to the sprawl of the city. The spatio-temporal patterns of residents' activities are different among people who come from different classes. on this basis, three classes are divided. The activity space of lower class is smaller, mostly concentrated in inner city and the area around their residential communities, and their payment for transportation is the lowest. But the activity space of upper class is larger, and most of the activity space is around new center of the city, Their time spending on outdoor activities is well-regulated, and their payment for transportation is the highest. There is a close relationship between resident behavior and urban internal spatial structure, which will provide a reliable basis for urban planning and urban management.
Kwan MP.Gender and individual access to urban opportunities: A study using space-time measures. , 1999, 51(2): 210-227.
Conventional accessibility measures based on the notion of locational proximity ignore the role of complex travel behavior and space–time constraints in determining individual accessibility. As these factors are especially significant in women's everyday lives, all conventional accessibility measures suffer from an inherent “gender bias.” This study conceptualizes individual accessibility as space–time feasibility and provides formulations of accessibility measures based on the space–time prism construct. Using a subsample of European Americans from a travel diary data set collected in Franklin County, Ohio, space–time accessibility measures are implemented with a network-based GIS method. Results of the study indicate that women have lower levels of individual access to urban opportunities when compared to men, although there is no difference in the types of opportunities and areas they can reach given their space–time constraints. Further, individual accessibility has no relationship with the length of the commute trip, suggesting that the journey to work may not be an appropriate measure of job access.
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61Assistive technologies influence where and how older people will live.61Scenario planning reveals plausible but divergent futures for older people.61Assistive technologies coupled with state support for care indirectly affect travel.61Shaping change rather than anticipating change may be a better policy response.
ZhouS, DengL, Kwan MP, et al.Social and spatial differentiation of high and low income groups' out-of-home activities in Guangzhou, China., 2015(45): 81-90.
With China’s rapid urbanisation driving its growing economy, the enlarging socio-spatial inequalities in the cities have received wide attention. Rather than following the largely studied residential spaces, this paper focuses on socio-spatial differentiation based on the spaces of one’s out-of-home activities. Using data of 1006 individuals collected by door to door questionnaires, this paper sets up the spatial and temporal autocorrelation GT coefficient to examine the spatial heterogeneity characteristics of high- and low income groups’ out-of-home activities in a continuous spatiotemporal framework. The factors and different mechanisms influencing the clustering of the activities are discussed to better understand social diversity in post-reform urban China. The results suggest that there is obvious spatial and temporal variation in high- and low income groups’ out-of-home activities, indicating that differing social spaces are not just limited to the macro-static residence-based living space, but also exist in the individual’s daily-activities space. Both high- and low income people have drastically different activity spaces and they may not interact much with each other. This is socially very significant because it means that there is considerable social isolation or segregation for both groups. The results also show that within the same income group there exists a divisive cluster with different formation mechanisms, including the job–housing relationship, the correlation of activity opportunities with those surrounding residential areas and the individual’s ability to access activities (that is, space–time accessibility). Structural transition can also impact on activities choices of various social groups.
SrinivasanS, RogersP.Travel behavior of low-income residents: Studying two contrasting locations in the city of Chennai, India. , 2005, 13(3): 265-274.
Data on travel behavior in developing countries like India is minimal. This is especially true for the relatively poor residents of urban India. They are dependent on fewer options for transportation and have little choice in terms of employment location given their dependence on walking or bicycles. This is significant in cities like Chennai because employment is highly concentrated in the center of the city. In this study, the results of a survey of 70 households in Chennai were analyzed to estimate statistical models of travel behavior with respect to mode choice and trip frequency. The households were located in two different parts of the city: one group of households lived close to the city center (in a settlement called Srinivasapuram) and the other at the periphery (in a location called Kannagi Nagar). We analyze the differences in travel behavior due to differences in accessibility to employment and services between the two settlement locations. The results indicate that differences in accessibility appear to strongly affect travel behavior. Residents in the centrally located settlement were more likely to use non-motorized modes for travel (walk or bicycle) than the peripherally located residents. It is vital therefore that, policy makers in India consider location of employment in the planning of new housing for low-income households.
De Jong GC. An indirect utility model of car ownership and private car use. , 1990, 34(5): 971-985.
In this paper a model is developed for the simultaneous determination of private car ownership and private car use, measured as the annual number of kilometers. This model is a micro-economic utility model, in which the fixed and variable car costs enter through the budget restriction. This allows us to do micro-simulations of increasing those costs, which is a policy issue in the Netherlands. It turns out that in this model both fixed and variable car costs are effective measures for reducing traffic (growth), the former working primarily through decreasing car ownership levels, the latter having a more direct effect on car use.
Gliebe JP, Koppelman FS.A model of joint activity participation between household members. , 2002, 29(1): 49-72.
A proportional shares model of daily time allocation is developed and applied to the analysis of joint activity participation between adult household members. The model is unique in its simultaneous representation of each decision maker's decisions concerning independent activity participation, allocation of time to joint activities, and the interplay between individual and joint activities. Further, the model structure ensures that predicted shares of joint activity outcomes be the same for both decision makers, an improvement over models that do not make interpersonal linkages explicit. The empirical analysis of travel diary data shows that employment commitments and childcare responsibilities have significant effects on tradeoffs between joint and independent activities. In addition, evidence is presented for the continued relevance of gender-based role differences in caring for children and employment participation.
ZhaoP.The impact of the built environment on individual workers' commuting behavior in Beijing. , 2013, 7(5): 389-415.
The increasing emission of transport-related pollutants has become a key issue in relation to climate change mitigation and the improvement of air quality in China's cities. This article aims to examine the effects of changes in the built environment on transportation by examining the case of Beijing. Looking at household survey data, the analysis found that individual workers鈥 commuting behavior (concerning travel destination, mode choice and travel time) is significantly related to some aspects of the built environment when socioeconomic and demographic characteristics are taken into account. There are obvious differences in the effects of the built environment on commuting across income groups, occupations and industries.
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The built environment is thought to influence travel demand along three principal dimensions —density, diversity, and design. This paper tests this proposition by examining how the ‘3Ds’ affect trip rates and mode choice of residents in the San Francisco Bay Area. Using 1990 travel diary data and land-use records obtained from the U.S. census, regional inventories, and field surveys, models are estimated that relate features of the built environment to variations in vehicle miles traveled per household and mode choice, mainly for non-work trips. Factor analysis is used to linearly combine variables into the density and design dimensions of the built environment. The research finds that density, land-use diversity, and pedestrian-oriented designs generally reduce trip rates and encourage non-auto travel in statistically significant ways, though their influences appear to be fairly marginal. Elasticities between variables and factors that capture the 3Ds and various measures of travel demand are generally in the 0.06 to 0.18 range, expressed in absolute terms. Compact development was found to exert the strongest influence on personal business trips. Within-neighborhood retail shops, on the other hand, were most strongly associated with mode choice for work trips. And while a factor capturing ‘walking quality’ was only moderately related to mode choice for non-work trips, those living in neighborhoods with grid-iron street designs and restricted commercial parking were nonetheless found to average significantly less vehicle miles of travel and rely less on single-occupant vehicles for non-work trips. Overall, this research shows that the elasticities between each dimension of the built environment and travel demand are modest to moderate, though certainly not inconsequential. Thus it supports the contention of new urbanists and others that creating more compact, diverse, and pedestrian-orientated neighborhoods, in combination, can meaningfully influence how Americans travel.
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Some of today’s most vexing problems, including sprawl, congestion, oil dependence, and climate change, are prompting states and localities to turn to land planning and urban design to rein in automobile use. Many have concluded that roads cannot be built fast enough to keep up with rising travel demand induced by the road building itself and the sprawl it spawns. The purpose of this meta-analysis is to summarize empirical results on associations between the built environment and travel, especially nonwork travel.
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CerveroR.Mixed land-uses and commuting: Evidence from the American housing survey. , 1996, 30(5): 361-377.
Past research suggests that mixed land-uses encourage non-auto commuting; however, the evidence remains sketchy. This paper explores this question by investigating how the presence of retail activities in neighborhoods influences the commuting choices of residents using data from the 1985 American Housing Survey. Having grocery stores and other consumer services within 300 feet of one's residence is found to encourage commuting by mass transit, walking and bicycling, controlling for such factors as residential densities and vehicle ownership levels. When retail shops are beyond 300 feet yet within 1 mile of residences, however, they tend to encourage auto-commuting, ostensibly because of the ability to efficiently link work and shop trips by car. The presence of nearby commercial land-uses is also associated with relatively low vehicle ownership rates and short commuting distances among residents of a mixed-use neighborhood. Overall, residential densities exerted a stronger influence on commuting mode choices than levels of land-use mixture, except for walking and bicycle commutes. For non-motorized commuting, the presence or absence of neighborhood shops is a better predictor of mode choice than residential densities.
Acker VV, WitloxF.Commuting trips within tours: How is commuting related to land use? , 2011, 38(3): 465-486.
Studies that model the effects of land use on commuting generally use a trip-based approach or a more aggregated individual-based approach: i.e. commuting is conceptualized in terms of modal choice, distance and time per single trip, or in terms of daily commuting distance or time. However, people try to schedule activities in a daily pattern and, thus, consider tours instead of trips. Data from the 2000 to 2001 Travel Behaviour Survey in Ghent (Belgium) illustrate that car use and commuting times significantly differ between commuting trips within work-only tours and more complex tours. Therefore, this paper considers trip-related decisions simultaneously with tour-related decisions. A multiple group structural equation model (SEM) confirmed that the relationship between land use and commuting differs between work-only tours and more complex tours. Trips should be considered within tours in order to correctly understand the effect of land use scenarios such as densifying on commuting. Moreover, the use of multiple group SEM enabled us to address the issue of the complex nature of commuting. Due to interactions between various explanatory variables, land use patterns do not always have the presumed effect on commuting. Land use policy can successfully influence commuting, but only if it simultaneously accounts for the effects on car availability, car use, commuting distance and commuting time.
ZhangM.The role of land use in travel mode choice: Evidence from Boston and Hong Kong. , 2004, 70(3): 344-360.
This article presents a study that analyzed the influence of land use on travel mode choice using survey data from Metropolitan Boston and Hong Kong. In Boston, the focus of inquiry was on whether land use would still matter for mode choice (and if so, to what extent) when mode attributes and traveler socioeconomic characteristics were taken into account. In Hong Kong, where the role of land use in mode choice is obvious due to the densely built environment, the focus was on whether land use completely explained the transit-dominated travel pattern. The empirical modeling confirmed that the role of land use in influencing travel was independent from travel time and monetary costs. Elasticity estimates show that the composite effect of land use on driving could be comparable in magnitude to that of driving cost. Yet being place specific, land use strategies are limited by the spatial extent to which they can be implemented. Land use strategies influence travel more effectively when complemented by pricing policies.
CaoX, FanY.Exploring the influences of density on travel behavior using propensity score matching. , 2012, 39(3): 459-470.
The causality issue has become one of the key questions in the debate over the relationship between the built environment and travel behavior. Since a residential self-selection effect exists, it is important to know if the observed influence of the built environment on travel behavior diminishes substantially once we control for self-selection. Using 5537 adult respondents to the 2006 Great Triangle Travel Survey in North Carolina, this study applied the propensity score matching approach to identify the causal effect of density on travel behavior and the relative contribution of self-selection to travel behavior. The results showed that, after removing self-selection bias, residents living in high-density neighborhoods travel, on average, 3.31 fewer miles per person per day than those who live in low-density neighborhoods. Self-selection effects account for 28%, 64%, and 49% of the observed influences of density on personal miles travelled, driving duration, and transit duration, respectively. We also found that different modeling approaches produce different point estimates, and that interval estimates of treatment effects tend to have a large variation. This points to a caveat of using point estimates to evaluate the impacts of the built environment on travel behavior.
WangD, LinT.Residential self-selection, built environment, and travel behavior in the Chinese context. , 2014, 7(3): 5-14.
Residential self-selection has been reported to be a factor confounding the observed relationship between built environment and travel behavior. By incorporating residential self-selection, studies have generated much insight into the causalities involved in the relationship between built environment and travel behavior. However, most of these studies were conducted in North American cities, where individuals may have the opportunity to realize their preferences in residential and transport mode choices. There are not many similar studies for other parts of the world, such as China, where residential and transport choices are probably more constrained than in North America. This paper aims to partly fill the gap by discussing the specificities of the residential self-selection issue in urban China and suggesting how to cope with this issue when examining the relationship between built environment and travel behavior in the Chinese context. We argue that studies addressing the residential self-selection issue in China need to consider the housing source, which has implications for residential choice, and acknowledge the importance of some travel-related attitudes such as preferences for short commutes, good accessibility to public transport, and proximity to markets for daily goods shopping.
NaessP.Residential location, travel, and energy use in the Hangzhou metropolitan area. , 2010, 3(3): 27-59.
This paper presents the results of a study examining the influence of residential location on travel behavior in the Hangzhou Metropolitan Area, China. The location of the dwelling relative to the center hierarchy of the metropolitan area is found to exert a considerable influence on the travel behavior of the respondents. On average, living close to the center of Hangzhou contributes to less overall travel, a higher proportion of trips by bicycle and on foot, and lower consumption of energy for transport. The location of the dwelling relative to the closest second-order and third-order center also influences travel, but not to the same extent as proximity to the city center. These geographical differences in travel behavior are independent of residential preferences and of attitudes toward transport and environmental issues, and therefore cannot be explained by residential self-selection.
WangD, ChaiY, LiF.Built environment diversities and activity-travel behavior variations in Beijing, China. , 2011,19(6): 1173-1186.
The association between built environment and travel behaviour has received considerable research attention in recent years. In an attempt to contribute to this growing literature, this paper investigates the connections between urban built environments and activity–travel patterns in Beijing, the capital city of China. We characterize the built environment in Beijing and establish associations between built environment and activity–travel behaviour in terms of car ownership, time spent for out-of-home activities, and daily trip frequencies and travel time. Activity diaries from 1119 respondents living in ten different neighbourhoods were collected by face-to-face interviews. A household-level structure equations model incorporating intra-household interactions is developed to analyse this data. The empirical results show that residents of different types of neighbourhoods in Beijing demonstrate significant differences in car ownership, time spent for out-of-home activities, trip rate, and travel time. Further, the characteristics of the built environment are found to have more significant impacts on the activity–travel behaviour of the male head than that of the female head.Highlights? Establish the association between built environment and activity-travel behavior in Beijing, China. ? Develop a household-level structure equations model incorporating intra-household activity-travel interactions. ? Study how the built environment impacts on different members of household. ? Examine the interaction effects of built environment variables.
The increased private car ownership in China especially large cities has facilitated trip making and activity engagement behavior of citizens, but also led to many urban problems including traffic congestion and air pollution. While car ownership control has received much attention from academics and policy makers, not much research on private car usage in Chinese cities has been conducted. To fill in this gap, this paper examines the patterns and determinants of private car use in Beijing. Data are derived from an activitytravel behavior survey conducted in Beijing from November 2011 to July 2012. We develop econometric models from the data and find that the intensity of car usage in Beijing is significantly influenced by the purpose of car use, built environment variables and personal and household socioeconomic characteristics. Specifically, commuting is the most important purpose for car use in Beijing and the share of car use for this purpose is much higher than for other purposes; poor public transportation service and convenient parking facilities are two major driving forces of car use in Beijing; individual and household socioeconomic characteristics, such as marriage status, employment, household size and age, also play an important role. There is not much difference in frequency and duration of car usage between weekdays and weekends. These findings have important implications for transportation policymaking. Policies aiming at controlling car use may need to act on the factors that are found here as significant determinants of car use (e.g., built environment variables). It is argued that more studies on car use are required to better understand patterns and determinants of car use in Chinese cities and inform policies that can effectively reduce car use and alleviate car dependency.
ZhangLei, LeiLi, GuoBoliang, et al.Beijing: Educational Science Publishing House, 2003.
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XuY, WenM, WangF.Multilevel built environment features and individual odds of overweight and obesity in Utah. , 2014, 60: 197-203.
Based on the data from the Behavioral Risk Factor Surveillance System (BRFSS) in 2007, 2009 and 2011 in Utah, this research uses multilevel modeling (MLM) to examine the associations between neighborhood built environments and individual odds of overweight and obesity after controlling for individual risk factors. The BRFSS data include information on 21,961 individuals geocoded to zip code areas. Individual variables include BMI (body mass index) and socio-demographic attributes such as age, gender, race, marital status, education attainment, employment status, and whether an individual smokes. Neighborhood built environment factors measured at both zip code and county levels include street connectivity, walk score, distance to parks, and food environment. Two additional neighborhood variables, namely the poverty rate and urbanicity, are also included as control variables. MLM results show that at the zip code level, poverty rate and distance to parks are significant and negative covariates of the odds of overweight and obesity; and at the county level, food environment is the sole significant factor with stronger fast food presence linked to higher odds of overweight and obesity. These findings suggest that obesity risk factors lie in multiple neighborhood levels and built environment features need to be defined at a neighborhood size relevant to residents' activity space.
RajamaniJ, Bhat CR, HandyS, Knaap G and Song Y. Assessing impact of urban form measures on nonwork trip mode choice after controlling for demographic and level-of-service effects. , 2003(1831): 158-165.
The relationship between travel behavior and the local built environment remains far from entirely resolved, despite several research efforts in the area. The current paper investigates the significance and explanatory power of a variety of urban form measures on nonwork activity travel mode choice. The travel data used for analysis is the 1995 Portland Metropolitan Activity Survey conducted by Portland Metro. The database on the local built environment was developed by Song (2002) and includes a more extensive set of variables than previous studies that have examined the relationship between travel behavior and the local built environment using the Portland data. The results of the multinomial logit mode choice model indicate that mixed-uses promote walking behavior for nonwork activities.