Subway Accessibility Research Articles

An Empirical Study on the Determinants of Housing Prices in Beijing and Model Optimization

This paper aims to investigate the potential factors influencing housing prices in Beijing and optimize the prediction model. Using the Kaggle dataset "Housing Price in Beijing", multiple factors affecting housing prices were examined, including square footage, bedroom count, bathroom count, follower count, the presence of an elevator, and subway proximity. The study initially established a multiple linear regression model (MLR) and then optimized the model through variable selection and hypothesis testing. The final model indicates that square footage, bathroom count, follower count, elevator presence, and subway accessibility significantly impact housing prices. Additionally, subway proximity positively correlates with housing prices, while increased square footage is negatively associated with price, possibly due to lower unit costs for larger properties and the higher market demand for smaller homes. By validating the model's performance using a test dataset, the final model demonstrates effective predictive capability and offers insights for future model improvements.

Impact of COVID-19 Pandemic on Airbnb Listings in New York City: Challenges and Opportunities for Urban Housing Sustainability

Short-term rental (STR) platforms like Airbnb have significantly impacted urban housing sustainability, particularly in cities like New York City. The COVID-19 pandemic disrupted the STR market, raising questions about its resilience and effects on sustainable urban housing. This study addresses the following research questions: (1) How did unit and neighborhood characteristics influence the survival of Airbnb listings during the pandemic? (2) What changes occurred in the factors determining the emergence of new listings during the pandemic? Using data from Inside Airbnb, we applied Cox proportional hazard models and negative binomial regression to analyze changes before and after the pandemic. We found that during the pandemic, price discounts became crucial for listing survival, while traditional quality indicators like superhost status and high ratings lost significance. The importance of subway accessibility decreased, reflecting shifts in traveler preferences. Additionally, new listings were less likely to emerge in high-density Airbnb areas and more likely in neighborhoods with higher crime rates. These findings highlight the need for sustainable regulatory approaches that balance the benefits of STR platforms with protecting housing affordability and community well-being. Our study provides insights for policymakers aiming to promote sustainable urban housing during global crises.

Assessing spatial and racial equity of subway accessibility: Case study of New York City

Enhancing the utility of public transportation through easy and equitable access has become one of the focal points in the pursuit of social justice goals. This study aims to provide a comprehensive analysis of equitable access to the subway system in New York City (NYC) based on geography and race/ethnicity, shedding light on the complex relationship between transportation equity, racial diversity, and urban dynamics. New York City is selected as the case study due to its diverse demographic makeup, extensive public transportation system, and paucity of previous research on the racial justice dimensions of its subway system. Gravity index is employed to investigate the accessibility of the NYC subway system in terms of distance from stops and the frequency of service while equity is analyzed by Gini coefficients and Lorenz curves. To conduct this analysis, American Community Survey (ACS) data and The General Transit Feed Specifications (GTFS) are used. The findings reveal that accessibility to the subway system varies across New York City's outer boroughs, with Queens, the largest borough by area, notably standing out due to its limited availability of subway stations. Moreover, the study uncovers stark racial disparities in accessibility within boroughs, with the non-Hispanic Black community in Queens (which represents 17 % of the borough's population) facing a pronounced lack of easy access to subway stations. These insights underscore the urgent need for targeted interventions and policy reforms to address the identified disparities. Policymakers and transportation planners should prioritize initiatives such as increasing subway infrastructure in underserved areas, improving the frequency of service, and enhancing connectivity to reduce racial and spatial inequities in subway accessibility.

Still prefer, but not that much: the premium of subway access on house prices during the COVID-19 pandemic period

ABSTRACT Rail access has traditionally been considered a factor that enhances the amenity value of urban areas, resulting in a price premium for properties located near these stations. However, the Covid-19 pandemic has exerted a profound influence on people's mobility patterns and travel behavior within urban areas. One of the most conspicuous changes is a substantial decrease in subway ridership. This study investigates whether the decline in public transit ridership has led to shifts in housing location preferences driven by proximity to rail access during the Covid-19 pandemic. This study focuses on assessing the impact of the pandemic on the premium associated with rail access in relation to house prices. Using approximately 180,000 apartment transaction records from Seoul, South Korea, the empirical findings, based on a difference-in-differences approach, reveal an immediate and significant depreciation effect resulting from this exogenous shock during the 25-month pandemic period. The premium decreases significantly within a 1.2-kilometer radius from a subway station, and this reduction exhibits a distance-decay pattern within the designated area. Highlights Traditional amenity value of rail access challenged by Covid-19. Profound decline in subway ridership during pandemic. Investigation into pandemic's impact on housing location preferences. Assessment of pandemic's effect on rail access premium. Immediate and significant depreciation effect within 1.2 km from subway stations.

Examining the non-linear association between the built environment around residence and the risk of obesity among children and adolescents at different school stages in Guangzhou and Shenzhen, China

Recent evidence suggests that the built environment around residence is linked to the risk of obesity among children and adolescents. However, most previous studies focus on the linear relationships between the built environment around home and the risk of obesity among adults, failing to explore potential non-linear relationships among children and adolescents at different school stages. Here, we use XGBoost to investigate the non-linear relationships between neighborhood built environment factors and the risk of obesity among 41,220 children and adolescents in Guangzhou and Shenzhen, two metropolitan cities in South China. Results from XGBoost indicate that the built environment plays an important role in predicting the risk of obesity among primary school students, middle school students, and high school students, and the relative importance of the built environment increases with age. Obesogenic food environment and population density are found to be leading predictors for all three school stages. Subway accessibility is an important predictor for primary school students, while bus accessibility is an important predictor for secondary school students. Interestingly, proximity to greenspaces is not important in predicting obesity risk. Non-linear relationships are found between several built environment predictors and obesity risks. Our findings may inform policymakers, planners, and designers on how to create an anti-obesogenic environment for children and adolescents in high-density Chinese cities.

전국 일반 사립대학의 대학 충원율과 소재지, 규모 및 교통 접근성과의 관계에 관한 탐색적 분석

This study analyzed the relationship between the location, size and accessibility of private universities nationwide and the freshman enrollment rate and college retention rate. Using university disclosure data and Google Maps, the location, size, subway accessibility were set as independent variables and the over the last 5 years university recruitment rate(freshman enrollment and college retention) as the dependent variables and analyzed by a Linear Mixed Effect Regression method using R. As a result, firstly, there was a regional gap in university subway accessibility, and the metropolitan area showed better than other regions. Second, it was found that freshman enrollment rate and college retention rate have decreased significantly over the past five years nationwide. Third, the location and size of the university were significant in both freshman enrollment rate and college retention rate, and college accessibility was significant only in the college retention rate. The explanatory power was the highest in the location of the university (approximately 27% of freshman recruitment rate, 34% of college retention rate), followed by the size of university(approximately 9% of freshman recruitment rate, 7% college retention rate) and subway accessibility (approximately 2% of college retention rate) was the lowest. Based on the study results it was discussed whether the gap in university recruitment rate would widen depending on the location, size and accessibility and the need for improvement as a representative university performance indicator and the relationship between university-regional interdependent development were discussed.

Modeling interactions between the Montreal subway and other urban transportation modes at the station level

Subway systems are an example of how underground space can contribute to developing more sustainable cities. Their use can be encouraged by integrating other urban transportation modes to provide easy access to the stations, thus facilitating intermodal connectivity. However, few studies have addressed data and modeling issues with multiple modes. This gap, mainly due to the lack of appropriate methods, explains why relationships between traditional and emerging modes remain poorly understood; there is still debate about whether they are complementary or competitive. This paper investigates this question by examining interactions between three alternative modes (bikesharing, free-floating carsharing and taxi) and the Montreal (Quebec, Canada) subway over two months. To this end, several operational passive datasets are merged. A two-level growth model, including both fixed and random effects, is then developed based on time series of daily numbers of boardings at subway stations. This longitudinal model quantifies the effect of various variables (calendar, weather, socio-demographic and economic, network connectivity, land use and built environment attributes) on each station use. The correlations between subway boardings and alternative mode destinations are also measured to detect potential intermodal relations. Finally, a further categorical analysis is conducted by period and station type to specify these interactions in time and space. Results reveal that alternative modes tend to complement the subway in the network periphery (as possible access mode to the subway stations), but may compete with the subway in areas closer to the city center. Such findings could help policymakers determine the location of the mobility services to enhance first-mile subway access, as well as the best mode integration around subway stations in planning strategies.

The geography of subway development and commuting behavior

This paper explores the impact of subway development on commuting behavior that arises from changes in network access induced by travel time reductions under geographical contexts of China’s mega-city subway network expansion. The analysis is carried out on a cohort of residential areas in Beijing built from geographically-referenced data on individual surveys, administrative records and changes in subway network. We find that improved subway access increase subway use, mainly due to road-side distance reductions to subway stations rather than subway-side distance contractions. Automobile use is significantly reduced due to subway-side access changes along with the subway network expansion. The effects are robust to the consideration of travel attitudes, residential self-selection and other social and spatial gradients. Our results highlight an important implication that access is dynamic in nature and its decomposed subway-side and road-side access can be a key force for guiding metro-system development and station location placements.

Research on the spatial coupling relationship between subway accessibility and commercial facilities in large cities—a case study of Xi’an city

The coupling and mutual feedback between subway accessibility and commercial facilities is one of the important prerequisites for promoting the coordinated development of cities. This paper uses spatial syntax to measure the accessibility of Xi'an subway, and combines GIS kernel density analysis and bivariate spatial autocorrelation analysis to explore the spatial distribution of subway accessibility and commercial facilities, as well as the coupling and spatial structure between them. The study found that: 1)Subway accessibility presents the characteristics of multi-center spatial layout, and has spatial imbalance. 2)The commercial facilities present a center-periphery spatial layout, with the bell tower as the center and the core density gradually decreasing to the surrounding areas. 3)From the perspective of spatial correlation, the subway accessibility and the layout of commercial facilities have a high spatial correlation. The local spatial pattern is relatively stable. The High-High and Low-Low aggregation areas constitute the main spatial correlation mode, and the distribution proportion of High-Low and Low-High types is relatively low.

Equity of subway accessibility: A perspective from work commute trips

The equity of subway accessibility is of great concern to policy makers. This study measures the subway accessibility of work commute trips for commuters. Based on multi-source geographic data, we calculated the subway accessibility by extending traditional two-step floating catchment area method based on locations to trips. The results show that: (1) subgroups including women, younger people, and those who lived in lower-priced housing areas and worked in areas with less high-paying jobs were disadvantaged in subway accessibility; (2) people live or work in areas far from the city center had lower subway accessibility; and (3) the subway accessibility is influenced by people’s socio-economic status and the environmental characteristics of their home and the workplace. The findings of this study provide evidence to show the impact of subways on transport equity in developing countries and will be of practical value when undertaking city or transportation planning in the future.

Estimation of Urban Housing Vacancy Based on Daytime Housing Exterior Images—A Case Study of Guangzhou in China

The traditional methods of estimating housing vacancies rarely use daytime housing exterior images to estimate housing vacancy rates (HVR). In view of this, this study proposed the idea and method of estimating urban housing vacancies based on daytime housing exterior images, taking Guangzhou, China as a case study. Considering residential quarters as the basic evaluation unit, the spatial pattern and its influencing factors were studied by using average nearest neighbor analysis, kernel density estimation, spatial autocorrelation analysis, and geodetector. The results show that: (1) The urban housing vacancy rate can be estimated by the method of daytime housing exterior images, which has the advantage of smaller research scale, simple and easy operation, short time consumption, and less difficulty in data acquisition. (2) Overall, the housing vacancy rate in Guangzhou is low in the core area and urban district, followed by suburban and higher in the outer suburb, showing a spatial pattern of increasing core area–urban district–suburban–outer suburb. Additionally, it has obvious spatial agglomeration characteristics, with low–low value clustered in the inner circle and high–high value clustered in the outer suburb. (3) The residential quarters with low vacancy rates (<5%) are distributed in the core area, showing a “dual-core” pattern, while residential quarters with high vacancy rates (>50%) are distributed in the outer suburb in a multi-core point pattern, both of which have clustering characteristics. (4) The results of the factor detector show that all seven influencing factors have an impact on the housing vacancy rate, but the degree of impact is different; the distance from CBD (Central Business District) has the strongest influence, while subway accessibility has the weakest influence. This study provides new ideas and methods for current research on urban housing vacancies, which can not only provide a reference for residents to purchase houses rationally, but also provide a decision-making basis for housing planning and policy formulation in megacities.

A Computational Approach of Displacement Prediction in an Engineering Project

In this paper, a fuzzy information granulation method combined with a support vector machine time series prediction model(FIG-SVM) is established for a subway cross passage project of Ningbo Metro Line 3. The FIG-SVM prediction model was used to predict the ground settlement of the subway access during the shield construction process. It was found that the FIG-SVM prediction model can effectively predict the ground settlement trend for the next construction stage based on the historical data of the ground settlement.

Influencing Factors of Housing Sales Vacancy in the Guangzhou Metropolitan Area, China

In this paper, nine indicators selected from three perspectives (convenience, environmental and location characteristics) and three regression models (OLS, SLM and SEM) are used to explore the influencing factors of housing sales vacancy in the Guangzhou Metropolitan Area, China. The results show that subway accessibility, peripheral aversion municipal facilities and distance from the CBD (Central Business District) are consistent with theoretical expectations. Subway accessibility is negatively correlated with the housing sales vacancy rates, while peripheral aversion municipal facilities and distance from the CBD are positively correlated with housing vacancy rates.

서울시 지하철에 대한 가로망 접근성의 토지가격 효과 연구*

As metropolitan cities around the world face multiple urban issues, public transport attracts attention as a measure for sustainable development. Therefore, the effects of access to public transit on neighborhoods are important academic and policy subject. This study measures five accessibility indicators for the Seoul subway system, considering both the frequency of subway operation and the characteristics of the street network, and analyzes their effects on residential and non-residential land prices. The key findings of this study confirm that the five subway accessibility indicators have a positive effect on residential and non-residential land prices. In particular, they generate a high premium to the prices of non-residential land rather than residential land. In addition, the higher the operation frequency of the nearest subway station or the straighter the street network reaching the subway stations, the greater the land price premium. Further, a land that people are frequently passing through to access a station or has more routes to a station generates higher price premium. The results of this study provide a reference for understanding the effects of public transport services and predicting the response of neighborhood real estate markets to the service.

Elaborating non-linear associations and synergies of subway access and land uses with urban vitality in Shenzhen

Previous studies on the built environment and urban vitality often assume that they follow a pre-defined (mostly linear in parameters) relationship, and few studies substantiate whether high-quality transit (T) and supportive land development (D) are synergistic to vibrant urban places. This study employs gradient boosting decision trees to examine the irregularly non-linear associations between the built environment and urban vitality, using Shenzhen as the case study and the Baidu Heat Index as a proxy for vitality. It reveals that their associations change drastically past some thresholds of built environment attributes, and that there are non-linear synergies between T and D. The findings provide guidance for neighborhood planning and have implications for cities that seek transit investments and transit-oriented development.

Dockless bike sharing alleviates road congestion by complementing subway travel: Evidence from Beijing

Dockless bike sharing provides a flexible transportation alternative, enriching the potential of both a feeder mode for subway access and a direct substitute for subway trips. This research evaluates the interaction between dockless shared bikes and Beijing's existing subway system. Based on 3.2 million geo-coded bike-sharing trips for two weeks of May 2017, we constructed an innovative framework to distinguish subway-complementing and subway-substituting trips. Employing a generalized Difference-in-Differences identification strategy, we find that subway lines with higher bike-sharing intensity showed an 8% larger growth rate in subway ridership compared to ones with lower intensity, while the substitution effect of bike sharing on subway trips was insignificant. The rush hour road congestion level around subway stations drops by 4% for those stations with bike-sharing trips in the highest quartile. This complementarity between two green travel modes is stronger on workdays, and its congestion alleviation effect is larger in urban areas with poorer access to the existing subway network, revealing its potential to solve the “last mile” problem in areas with inadequate public transit access. We demonstrate that the synergy between dockless bike sharing and the subway system outweighs substituting effects and can help achieve a greener and healthier city.

The Effect of Subway Access on School Choice

One of the goals of school choice is to allow parents to send their children to higher-performing schools. Several studies have shown that distance to school is one of the main determinants of school choice, but challenges to address endogeneity issues remain. To address these concerns, in this paper I take advantage of the construction of a new subway line in Santiago, Chile, that crosses a large area of the city previously unconnected to the subway network. I provide convincing evidence to show that the introduction of the subway line was arguably exogenous for families living close to the new subway stations. With rich administrative data, which includes all high-school seniors that registered to take a national university entrance exam, I use a repeated cross-section difference-in-differences analysis and find that (i) students near the new subway stations travel significantly farther to school than students who live in nearby areas with no subway stations, and (ii) that students near the subway are willing to travel slightly farther to attend schools that perform better in standardized tests, although this effect is small and only significant for language test scores. This set of results is particularly informative in the context of the broader school-choice debate, contributing causal evidence on the effects of transit access on school-choice.

Understanding Spatio-Temporal Characteristics of Urban Travel Demand Based on the Combination of GWR and GLM

Taxis are an important part of the urban public transit system. Understanding the spatio-temporal variations of taxi travel demand is essential for exploring urban mobility and patterns. The purpose of this study is to use the taxi Global Positioning System (GPS) trajectories collected in New York City to investigate the spatio-temporal characteristic of travel demand and the underlying affecting variables. We analyze the spatial distribution of travel demand in different areas by extracting the locations of pick-ups. The geographically weighted regression (GWR) method is used to capture the spatial heterogeneity in travel demand in different zones, and the generalized linear model (GLM) is applied to further identify key factors affecting travel demand. The results suggest that most taxi trips are concentrated in a fraction of the geographical area. Variables including road density, subway accessibility, Uber vehicle, point of interests (POIs), commercial area, taxi-related accident and commuting time have significant effects on travel demand, but the effects vary from positive to negative across the different zones of the city on weekdays and the weekend. The findings will be helpful to analyze the patterns of urban travel demand, improve efficiency of taxi companies and provide valuable strategies for related polices and managements.

Trade-off relationship between public transportation accessibility and household economy: Analysis of subway access values by housing size

This study examines whether different income groups have different trade-off preferences between public transportation accessibility and income and economic power. In this study, apartments, the most typical housing type in Seoul, were categorized according to size (small, medium, and large) based on the premise that apartment size is a measure of the economic status of an individual or household. Subsequently, the effect of subway accessibility on apartment prices for the three types of apartments was examined through the conventional hedonic price model and the spatial autoregressive combined model, followed by an investigation of the spatial patterns of the effect with a focus on a geographically weighted regression. As a result, this study finds that, although subway accessibility serves as a positive factor in housing location decisions for most socioeconomic classes, the positive effect is not spatially unanimous, indicating that households with relatively robust economic stability preferred housing locations further away from subway stations in pursuit of a more attractive residential environment. Although high-income households trade greater accessibility to public transportation for a more attractive neighborhood environment, middle-income households more actively pursued convenience and the greenness of their neighborhoods. Households with less economic stability preferred neighborhoods featuring relatively low-cost housing and greater accessibility. These results confirm the prevalence of trade-off between public transportation accessibility and housing size in Seoul, Korea. This also verifies that the spatial division along economic class lines is intensifying, and that perspectives on subway accessibility vary depending on consumers' economic status. The results suggest the need for consumer-tailored public transportation policies that consider the residential location patterns of the socioeconomic classes that are dependent on public transportation. This perspective can improve our understanding of how to distribute mass transportation systems spaces in large cities, particularly where the wealth gap is relatively high.

Decade-Long Changes in Disparity and Distribution of Transit Opportunity in Shenzhen China: A Transportation Equity Perspective

Efficiency and equity have always been the two points of focus of transport projects. Compared with efficiency, equity is easily overlooked in the evaluation of transport projects. Many studies emphasize that defining and operationalizing costs and benefits and the distributive principle are critical parts in the assessment of transportation equity. However, the scope and time frame of the assessment target are also critical. In this paper, we took China’s fastest urbanizing city, Shenzhen, as a case study to assess transport equity by comparing accessibility among groups. First, the public transport system was divided into bus and subway, and the residents were divided into two groups: urban village and nonurban village. Second, we adopted an enhanced potential opportunity model to measure residents’ bus and subway accessibility and summarized them as transit opportunity. Third, we used the Dagum Gini coefficient decomposition and kernel density estimation method to explore the fair distribution of transit opportunity among groups and districts from 2011 to 2020. Decade-long changes in disparity and distribution of transit opportunity gave us a clear picture. On the one hand, the development of Shenzhen public transport system had a positive effect. All populations are benefiting, and their accessibility is increasing. On the other hand, it also had a negative effect to exacerbate inequality between populations. For the absolute value of the opportunity, Shenzhen’s urban village populations do have fewer transportation opportunities than nonurban villages, and this gap between them will be wider more and more. The public transport system is more inclined to improve the population with high initial opportunity and make them higher. The results illustrated the importance of examining transportation equity over an extended period and could provide information on urban development strategies.