Journal of Transport and Land Use <p>The Journal of Transport and Land Use is the leading international journal that publishes original interdisciplinary papers on the interaction of transport and land use. The Editors welcome original submissions across the globe and from a wide range of domains, including engineering, planning, modeling, behavior, economics, geography, regional science, sociology, architecture and design, network science, and complex systems.</p> Center for Transportation Studies at the University of Minnesota en-US Journal of Transport and Land Use 1938-7849 <p>Authors who publish with JTLU agree to the following terms: 1) Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under <a href="">Creative Commons Attribution-Noncommercial License 4.0</a> that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal. 2) Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal. 3) Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.</p> A Markovian measure for evaluating accessibility to urban opportunities Accessibility is a fundamental notion in urban planning and its related fields. While accessibility is dynamic and varies during different time moments, most of the accessibility metrics are static and do not take this variation into account. In doing so, to address the questions of (1) how accessible urban opportunities are in different time moments and (2) how accessibility value of a person to a certain place changes regarding his/her spatiotemporal restrictions in time instants, this article—by using semi-Markovian and Brownian Bridge stochastic processes—offers a probabilistic time-dependent accessibility model that blends the magnitude of opportunities magnitude with the probability of individuals visiting. To show the model’s applicability, it was applied on a hypothetical case, along with two common accessibility metrics, and the outputs were compared. Then the proposed model was implemented in a study area for measuring temporal accessibility in two real policies made for daily markets in Isfahan, Iran. The first policy that presented the model application for analytical purposes was “market exclusion and area expansion,” and the second policy that depicted the model implementation for normative usage was “new market location.” Results of the model execution on the hypothetical cases indicated there was a significant difference between the outputs of the common metrics and the ones of the proposed model. In addition, in the study area, the first policy generated higher total accessibility value in comparison with the second policy when market 2 was excluded and the area for market 8 was doubled. Alireza Sahebgharani Hossein Haghshenas Mahmoud Mohammadi Copyright (c) 2019 Alireza Sahebgharani, Hossein Haghshenas & Mahmoud Mohammadi 2019-01-28 2019-01-28 12 1 10.5198/jtlu.2019.1408 Transferring land use rights with transportation infrastructure extensions: Evidence on spatiotemporal price formation in Shanghai To address the efficiency and sustainability of residential suburbanization under state leasehold systems, this study examines the price formation of long-term land-use rights for general and compensational housing empirically, considering the successive expansions of new metro lines and highway networks during 2004–2016 in Shanghai—one of the world’s fastest growing megacities. The results of our spatial autoregressive models infer that the accessibility benefits of metro extensions are considerably capitalized into both the ask and transaction prices of land-use rights for general housing in the suburbs, whereas those for highway construction are insignificant. A series of spatiotemporal regressions demonstrate that the premiums for proximity to new metro stations bid by private developers are much higher than those asked by local governments during pre-metro years, probably due to local governments’ strategic site arrangements for transit-oriented suburbanization and/or developers’ speculative land acquisitions in Shanghai’s upward suburban housing market. This study further reveals that the prices of land-use rights for compensational housing do not reflect any economic externalities attributable to metro stations and highway interchanges, which might trigger the unfair redistribution of property rights, accessibility, and economic opportunities among relocated farmers around city-fringe areas. Zheng Chang Jin Murakami Copyright (c) 2019 Zheng Chang, Jin Murakami 2019-01-28 2019-01-28 12 1 10.5198/jtlu.2019.1357 Understanding autonomous vehicles: A systematic literature review on capability, impact, planning and policy Advancement in automated driving technology has created opportunities for smart urban mobility. Automated vehicles are now a popular topic with the rise of the smart city agenda. However, legislators, urban administrators, policymakers, and planners are unprepared to deal with the possible disruption of autonomous vehicles, which potentially could replace conventional transport. There is a lack of knowledge on how the new capabilities will disrupt and which policy strategies are needed to address such disruption. This paper aims to determine where we are, where we are headed, what the likely impacts of a wider uptake could be, and what needs to be done to generate desired smart urban mobility outcomes. The methodology includes a systematic review of the existing evidence base to understand capability, impact, planning, and policy issues associated with autonomous vehicles. The review reveals the trajectories of technological development, disruptive effects caused by such development, strategies to address the disruptions, and possible gaps in the literature. The paper develops a framework outlining the inter-links among driving forces, uptake factors, impacts and possible interventions. It concludes by advocating the necessity of preparing our cities for autonomous vehicles, although a wider uptake may take quite some time. Asif Faisal Tan Yigitcanlar Md. Kamruzzaman Graham Currie Copyright (c) 2019 Asif Faisal, Tan Yigitcanlar, Md. Kamruzzaman & Graham Currie 2019-01-28 2019-01-28 12 1 10.5198/jtlu.2019.1405 The influence of education level and job type on work-related travel patterns within rural metro-adjacent regions: The case of Castilla-La Mancha, Spain Contemporary functional linkages and their relationships with the underlying settlement structure have been widely explored within polycentric urban configurations, but little attention has been paid to their adjacent rural regions. This paper examines the spatial patterns of commuting versus business travel in rural metro-adjacent regions to explain their reconfigured urban structures. These travel patterns are compared by considering workers’ education levels and occupations to investigate how rural metro-adjacent regions offer different opportunities for highly and non-highly skilled workers. Based on two surveys conducted by the authors in 2012, this work focuses on Castilla-La Mancha (CLM, Spain), a rural region under the influence of Madrid. The empirical results demonstrate the effectiveness of considering different functional linkages when explaining the underlying urban network. In particular, the results reinforce the idea of consolidating the polycentric spatial organization of urban centers in CLM, although this concentration is greater for commuting travel purposes and for highly skilled professionals. Conversely, the openness of CLM to other Spanish regions (including the adjacent metropolitan region) is greater for business travel than for commuting. The results also illustrate that the level of engagement, both in commuting and in business travel, increases with education. Finally, the results show that business travel occurs over longer distances than commuting does for all workers residing in rural metro-adjacent regions, regardless of education. Inmaculada Mohino José M. Ureña Eloy Solís Copyright (c) 2019 Inmaculada Mohino, José M. Ureña, Eloy Solis 2019-01-28 2019-01-28 12 1 10.5198/jtlu.2019.1219 Heterogeneity in the relationship between biking and the built environment Bicycling is an environmentally friendly, healthy, and affordable mode of transportation that is viable for short-distance trips. Urban planners, public health advocates, and others are therefore looking for strategies to promote more bicycling, including improvements to the built environment that make bicycling more attractive. This study presents an analysis of how key built environment characteristics relate to bicycling frequency based on a large sample from the 2012 California Household Travel Survey (California Department of Transportation, 2012) and detailed built environment data. The built environment characteristics we explore include residential and intersection density at anchor locations (home, work, school), green space, job access, land-use mix, and bicycle infrastructure availability. Analyses are conducted separately for three distinct demographic groups: school-age children, employed adults, and adults who are not employed. The key conclusion from this work is that the relationship between bicycling and some built environment characteristics varies between types of people — most dramatically between adults and children. To develop targeted policies with scarce resources, local policymakers need specific guidance as to which investments and policy changes will be most effective for creating “bikeable” neighborhoods. Our work indicates that the answer depends — at least in part — on who these bikeable neighborhoods are meant to serve. Deborah Salon Matthew Wigginton Conway Kailai Wang Nathaniel Roth Copyright (c) 2019 Deborah Salon, Matthew Wigginton Conway, Kailai Wang, Nathaniel Roth 2019-01-28 2019-01-28 12 1 10.5198/jtlu.2019.1350 The impact of ride hailing on parking (and vice versa) Investigating emerging transportation services is critical to forecasting mode choice and providing appropriate infrastructure. One such infrastructure is parking, as parking demand may shift with the availability of ride-hailing services. This study uses ethnographic methods—complemented with passenger surveys collected when driving for Uber and Lyft in the Denver, Colorado, region—to gather quantitative and qualitative data on ride-hailing and analyze the impacts of ride-hailing on parking, including changes in parking demand and parking as a reason to deter driving. The study also examines relationships between parking time and cost. This includes building a classification tree-based model to predict the replaced driving trips as a function of car ownership, destination land type, parking stress, and demographics. The results suggest that: i) ride-hailing is replacing driving trips and could reduce parking demand, particularly at land uses such as airports, event venues, restaurants, and bars; ii) parking stress is a key reason respondents chose not to drive; and iii) respondents are generally willing to pay more for reduced parking time and distance. Conversely, parking supply, time, and cost can all influence travel behavior and ride-hailing use. This study provides insight into potential benefits and disadvantages of ride-hailing as related to parking. Alejandro Henao Wesley E. Marshall Copyright (c) 2019 Alejandro Henao & Wesley E. Marshall 2019-02-17 2019-02-17 12 1 10.5198/jtlu.2019.1392 Beyond geometries of activity spaces: A holistic study of daily travel patterns, individual characteristics, and perceived wellbeing in Helsinki metropolitan area Activity space (AS) is a measure of spatial behavior used to summarize the mobility behavior of individuals. Current studies often highlight the fact that AS is highly complex and multidimensional in character. Therefore, the need for more holistic approaches providing more comprehensive descriptions of mobility patterns is evident. This article assesses the activity spaces of young adults aged 25–40 living in the Helsinki metropolitan area using a dataset collected with an online map survey. Using a wide range of measurements covering different aspects of AS, we identified seven components that define activity spaces, namely size, intensity of activities, volume of trips, exteriority, polycentricity, elongation, and destination specialization. We then used the components together with travel mode use to identify a typology of daily mobility patterns. The results show that individuals with different types of AS differ significantly in their socio-demographic characteristics, such as age, gender, employment, household characteristics, and residential neighborhood. Furthermore, the study reveals interesting associations between AS characteristics and different aspects of wellbeing. Overall, the results highlight the importance of multidimensional and comprehensive approaches to understanding daily mobility of urban residents. Kamyar Hasanzadeh Michal Czepkiewicz Jukka Heinonen Marketta Kyttä Sanna Ala-Mantila Juudit Ottelin Copyright (c) 2019 Kamyar Hasanzadeh, Michal Czepkiewicz, Jukka Heinonen, Marketta Kyttä, Sanna Ala-Mantila, Juudit Ottelin 2019-02-21 2019-02-21 12 1 10.5198/jtlu.2019.1148 Effects of toll road construction on local road projects in Indonesia This study investigates the extent to which the construction of national toll roads in the Jakarta–Bandung region in Indonesia induces the development of local road projects nearby. In doing so, we disentangle the direct and indirect supply effects by considering the year of construction and urban development, respectively. We formulate four binary logit models to examine the direct and indirect relationships between toll road construction and local road projects. The dataset comprises 94 road projects planned or carried out between 2004 and 2016. We conduct interviews with local officials in the Jakarta–Bandung area to obtain data on the projects’ decision-making processes. Our modelling results show that existing and planned toll roads induce the development of local road projects both directly and indirectly. Local road projects tend to be developed in anticipation of the opening of a toll road. The changes in residential area and population around the toll roads also induce local road construction. I.G. Ayu Andani Lissy La Paix Puello Karst Geurs Copyright (c) 2019 I. Gusti Ayu Andani, Lissy La Paix Puello, Karst Geurs 2019-03-11 2019-03-11 12 1 10.5198/jtlu.2019.1258 Analysis of trip generation rates in residential commuting based on mobile phone signaling data In this paper, mobile phone signaling data are first processed to extract information such as the trip volume and spatial distribution from the starting point to the termination point. This information is then used to identify the residential and employment locations of users. Next, multiple Thiessen polygons based on cell towers are aggregated into Traffic Analysis Zones (TAZs) to minimize differences between the actual cell tower coverage and the theoretical coverage. Then, based on TAZ cluster analysis involving transport accessibility and commuting population density, multiple stepwise regression is applied to obtain the commuting trip production rates and attraction rates for overall residential land and each subdivided housing type during the peak morning hours. The obtained commuting trip generation rates can be directly applied to local transport analysis models. This paper suggests that as information and data sharing continue, mobile phone signaling data will become increasingly important for use in future trip rate research. Fei Shi Le Zhu Copyright (c) 2019 Fei Shi, Le Zhu 2019-03-28 2019-03-28 12 1 10.5198/jtlu.2019.1431 A bikeshare station area typology to forecast the station-level ridership of system expansion The continuous introduction and expansion of docked bikeshare systems with publicly available origin-destination data have opened exciting avenues for bikeshare research. In response, a flux of recent studies has examined the sociodemographic determinants and safety or natural environment deterrents of system ridership. An increasing abundance of disaggregate spatial data has also spurred recent calls for research aimed at extending the utility of these contextual data to model bikeshare demand and trip patterns. As planners and operators seek to expand bikeshare services into underserved areas, a need exists to provide a data-driven understanding of the spatial dynamics of bikeshare use. This study of the Washington, DC, metro region’s Capital Bikeshare (CaBi) program answers this call by performing a latent class cluster analysis to identify five bikeshare station area types based on variation in a set of land development pattern, urban design, and transportation infrastructure features. This typology is integrated into a planning application exploring the potential for system expansion into nearby jurisdictions and forecasting the associated trip-making potential between existing and proposed station locations. Steven R. Gehrke Timothy F. Welch Copyright (c) 2019 Steven R. Gehrke, Timothy F. Welch 2019-04-11 2019-04-11 12 1 10.5198/jtlu.2019.1395 Examining the effects of proximity to rail transit on travel to non-work destinations: Evidence from Yelp data for cities in North America and Europe Urban planners often seek to establish land use patterns around transit stations that encourage non-auto travel. However, the willingness of travelers to use different modes in the vicinity of transit remains understudied, in part because of the lack of spatially-precise data on destination and mode choices. Using transportation content extracted from Yelp, a location-based social network (LBSN), we investigate how travel mode to non-work destinations is influenced by proximity to transit. We use textual analysis to analyze travel for non-work activities in seven cities across North America and Europe. Mixed-effect and binomial logistic models show how reported travel by mode varies by distance to rail transit stations. We find that for most non-work activity purposes, reported rail use is highly sensitive to proximity to stations, but some purposes are more amenable to rail use overall. Additionally, compared to non-US cities, US cities are far more parking-dependent near rail stations. The results suggest that not all activities elicit the same levels of non-auto travel, and transit-oriented planning should account for specific activities and regional factors that may modify willingness to travel by different modes. While subject to limitations, LBSNs can illuminate local travel with greater spatial specificity than traditional surveys. Zhiqiu Jiang Andrew Mondschein Copyright (c) 2019 Zhiqiu Jiang, Andrew Mondschein 2019-05-10 2019-05-10 12 1 10.5198/jtlu.2019.1409 Willingness to change car use to commute to the UPTC main campus, Colombia: A hybrid discrete choice modeling approach This paper studies the willingness to change car use when commuting to a university campus. We estimated a hybrid discrete choice (HDC) model to test the hypothesis that, in addition to traditional tangible attributes, the willingness to change car use to more sustainable transportation modes also depends on the pro-environmental attitude and the perceived convenience of each transportation alternative. We found that teachers have better pro-environmental attitudes than students and administrative staff, but senior individuals and people who own an above-average priced car have negative effects on this attitude. We concluded that in addition to car ownership, the price of a car is also a decisive factor in the willingness to change car use. On-campus parking fees were identified as a key variable for reducing car use when commuting to campus and for financing more sustainable transportation modes. This paper contributes to the literature on sustainable mobility on university campuses and is the first based on an HDC modeling approach that integrates tangible attributes and latent variables into this context. Luis Márquez Luis F. Macea Jose J. Soto Copyright (c) 2019 Luis Márquez, Luis F. Macea, Jose J. Soto 2019-05-14 2019-05-14 12 1 10.5198/jtlu.2019.1460 Advancing cycling among women: An exploratory study of North American cyclists Past studies show that women cycle at a lower rate than men due to various factors; few studies examine attitudes and perceptions of women cyclists on a large scale. This study aims to fill that gap by examining the cycling behaviors of women cyclists across multiple cities in North America. We analyzed an online survey of 1,868 women cyclists in the US and Canada, most of whom were confident when cycling. The survey recorded respondents’ cycling skills, attitude, perceptions of safety, surrounding environment, and other factors that may affect the decision to bicycle for transport and recreation. We utilized tree-based machine learning methods (e.g., bagging, random forests, boosting) to select the most common motivations and concerns of these cyclists. Then we used chi-squared and non-parametric tests to examine the differences among cyclists of different skills and those who cycled for utilitarian and non-utilitarian purposes. Tree-based model results indicated that concerns about the lack of bicycle facilities, cycling culture, cycling’s practicality, sustainability, and health were among the most important factors for women to cycle for transport or recreation. We found that very few cyclists cycled by necessity. Most cyclists, regardless of their comfort level, preferred cycling on facilities that were separated from vehicular traffic (e.g., separated bike lanes, trails). Our study suggests opportunities for designing healthy cities for women. Cities may enhance safety to increase cycling rates of women by tailoring policy prescriptions for cyclists of different skill groups who have different concerns. Strategies that were identified as beneficial across groups, such as investing in bicycle facilities and building a cycling culture in communities and at the workplace, could be useful to incorporate in long-range planning efforts. Huyen TK Le Alyson West Fionnuala Quinn Steve Hankey Copyright (c) 2019 Huyen TK Le, Alyson West, Fionnuala Quinn, Steve Hankey 2019-05-14 2019-05-14 12 1 10.5198/jtlu.2019.1461 Identifying residential and workplace locations from transit smart card data Public transit is highly promoted worldwide to reduce traffic congestion. An evidence-based planning of stop locations and routes with regard to residential and workplace locations can reduce walking distances to transit and the number of transfers, which can improve service quality of public transport and thus increase ridership. This paper proposes a novel method of identifying residential and workplace locations from smart card data. The proposed method identifies relevant stops first and then refines their catchments to narrow down residential and workplace locations in three steps: defining constraints from the design of the public transport network, movement logic, and land use. In 2017, we tested the method using Beijing smart card data. The results show close to 69% residential locations inference rates and more than 72% workplace locations inference rates. The mean value of inferred areas is approximately 20% of the areas derived by traditional methods. Available data on alighting stops verify the inferred results at least for flat fare systems. Yuan Tian Stephan Winter Jian Wang Copyright (c) 2019 Yuan Tian, Stephan Winter, Jian Wang 2019-05-16 2019-05-16 12 1 10.5198/jtlu.2019.1247 Life events, poverty, and car ownership in the United States: A mobility biography approach What causes families to buy or give up a car in the U.S.? Following the mobility biography approach, we use a nationally representative panel data set, the Panel Study of Income Dynamics (PSID), to examine the role of life events and changes in the built environment and compare the effect that these events have on changes in car ownership. We find that coupling, graduating from college, and the birth or adoption of a child all are associated with increases in car ownership, while breaking up is associated with decreases in car ownership. Moving to or away from transit-rich, dense, walkable neighborhoods matters but only when one moves to a very different type of neighborhood. We also find that life events have a stronger association with gaining a car for non-poor families than for families in poverty. Life events are windows of opportunity when families reevaluate their travel patterns. Interventions at these critical junctures could be an expedient way to decrease car ownership and its attendant problems, especially when combined with improving alternatives to the automobile. Nicholas J. Klein Michael J. Smart Copyright (c) 2019 Nicholas J. Klein & Michael J. Smart 2019-05-20 2019-05-20 12 1 10.5198/jtlu.2019.1482 Understanding the effects of individual attitudes and residential neighborhood types on university commuters’ bicycling decisions This study investigates the effects of individual perceptions and residential neighborhoods on university commuters’ bicycling decisions using the 2015 Ohio State University Travel Pattern Survey data. We generate eight attitudinal/perceptual components based on the 26 bicycling-related questions that capture detailed perceptions of commuters toward bicycling, neighborhood environments, and residential location choice. We create distinct neighborhood typologies combining land use and socioeconomic characteristics, including population, employment, housing and intersection densities, housing types, median age of housing stock, and median household income. Probit regression models are estimated to assess the effects of sociodemographic, attitudinal/perceptual components and neighborhood types while accounting for the residential self-selection effect. Results show that people residing in different neighborhood types reveal significant attitudinal differences in terms of their conditional willingness to bicycle, and evaluation of bicycle friendliness of neighborhoods and routes. We find that bicyclists are more likely to live in neighborhoods that they perceive as having good-quality for bicycling in terms of access to bicycle facilities and lower traffic levels. Results also show the significant association of neighborhood types with bicycle commuting outcomes. People from medium-density, mixed-use, and suburban single-family neighborhoods are less likely to commute by bicycle as compared to those from high-density, mixed-use neighborhoods. Yujin Park Gulsah Akar Copyright (c) 2019 Yujin Park & Gulsah Akar 2019-05-23 2019-05-23 12 1 10.5198/jtlu.2019.1259 On the accuracy of schedule-based GTFS for measuring accessibility In this paper we assess the accuracy with which General Transit Feed Specification (GTFS) schedule data can be used to measure accessibility by public transit as it varies over space and time. We use archived Automatic Vehicle Location (AVL) data from four North American transit agencies to produce a detailed reconstruction of actual transit vehicle movements over the course of five days in a format that allows for travel time estimation directly comparable to schedule-based GTFS. With travel times estimated on both schedule-based and retrospective networks, we compute and compare a variety of accessibility measures. We find that origin-based accessibility even when averaged over one-hour periods can vary widely between locations. Origins with lower scheduled access tend to produce less reliable estimates with more variability from hour to hour in real accessibility, while higher access zones seem to converge on an estimate 5-15 percent lower than the schedule predicts. Such over- and under-predictions exhibit strong spatial patterns which should be of concern to those using accessibility metrics in statistical models. Momentary measures of accessibility are briefly discussed and found to be weakly related to momentary changes in real access. These findings bring into question the validity of some recent applications of GTFS data and point the way toward more robust methods for calculating accessibility. Nate Wessel Steven Farber Copyright (c) 2019 Nate Wessel, Steven Farber 2019-06-18 2019-06-18 12 1 10.5198/jtlu.2019.1502 Gendered walkability: Building a daytime walkability index for women Urban walkability is influenced both by built environment features and by pedestrian demographics. Research has shown that factors influencing women’s walking differ from those affecting men’s. Using a mixed-method approach, this study creates a new women-specific, GIS-based walkability index using San Francisco as a case study, and answers two questions: Which variables most influence women’s propensity to walk? And Does the leading walkability index, Walk Score, reflect women’s walkability? Focus group participants (n=17) ranked crime, homelessness and street/sidewalk cleanliness as the three most influencing factors on women’s walkability, accounting for 58% to 67% of the Women’s Walkability Index’s total score. The least walkable areas in San Francisco, according to this index, are rated as some of the most walkable neighborhoods in the city by Walk Score, despite high crime and homelessness density. Walk Score is negatively correlated with the new Women’s Walkability Index (Spearman’s rho = -0.585) and inaccurately represents women’s walkability. If the new index accurately captures the reality of women’s walking, then some of the most widely accepted conventions about what kind of areas promote walking could be inaccurate when it comes to women. Yael Golan Nancy Wilkinson Jason M Henderson Aiko Weverka Copyright (c) 2019 Yael Golan, Nancy Wilkinson, Jason M Henderson, Aiko Weverka 2019-06-25 2019-06-25 12 1 10.5198/jtlu.2019.1472 Modelling residential location choices with implicit availability of alternatives Choice set generation is a challenging aspect of disaggregate level residential location choice modelling due to the large number of candidate alternatives in the universal choice set (hundreds to hundreds of thousands). The classical Manski method (Manski, 1977) is infeasible here because of the explosion of the number of possible choice sets with the increase in the number of alternatives. Several alternative approaches have been proposed in recent years to deal with this issue, but these have limitations alongside strengths. For example, the Constrained Multinomial Logit (CMNL) model (Martínez et al., 2009) offers gains in efficiency and improvements in model fit but has weaknesses in terms of replicating the Manski model parameters. The rth-order Constrained Multinomial Logit (rCMNL) model (Paleti, 2015) performs better than the CMNL model in producing results consistent with the Manski model, but the benefits disappear when the number of alternatives in the universal choice set increases. In this study, we propose an improved CMNL model (referred to as Improved Constrained Multinomial Logit Model, ICMNL) with a higher order formulation of the CMNL penalty term that does not depend on the number of alternatives in the choice set. Therefore, it is expected to result in better model fit compared to the CMNL and the rCMNL model in cases with large universal choice sets. The performance of the ICMNL model against the CMNL and the rCMNL model is evaluated in an empirical study of residential location choices of households living in the Greater London Area. Zone level models are estimated for residential ownership and renting decisions where the number of alternatives in the universal choice set is 498 in each case. The performance of the models is examined both on the estimation sample and the holdout sample used for validation. The results of both ownership and renting models indicate that the ICMNL model performs considerably better compared to the CMNL and the rCMNL model for both the estimation and validation samples. The ICMNL model can thus help transport and urban planners in developing better prediction tools. Md Bashirul Haque Charisma Farheen Choudhury Stephane Hess Copyright (c) 2019 Md Bashirul Haque, Charisma Farheen Choudhury, Stephane Hess 2019-07-23 2019-07-23 12 1 10.5198/jtlu.2019.1450 Complete streets state laws & provisions: An analysis of legislative content and the state policy landscape, 1972–2018 Across the U.S., states have adopted Complete Streets legislative statutes—state laws that direct transportation agencies to routinely design and operate roadways to provide safe access for all users, including pedestrians, bicyclists, motorists, and public transit users. To date, there has not been a systematic and comprehensive analysis of the content and provisions of these laws. In this study, Complete Streets state statutes were identified using legal research databases. Using established legal mapping methods, a qualitative analysis was conducted of state laws that were effective through December 2018. A codebook and open-source data set were developed to support the public use of the data. Eighteen states and Washington, DC, have adopted Complete Streets legislative statutes. A total of 21 have been adopted, with 76% (n=16) of laws adopted since 2007. While the laws vary in content, detail, and specificity, several common provisions were identified across statutes. Complete Streets legislative statutes may be essential to ensure that road networks throughout states are safe, connected, and accessible for all users. This study provides key insights into the legislative landscape of Complete Streets state laws and makes available a new data set that can support future evaluations of these laws. Jamila Porter Shenée Bryan Joel Lee Phaedra Corso Marsha Davis Stephen Rathbun Copyright (c) 2019 Jamila Porter, Shenée Bryan, Joel Lee, Phaedra Corso, Marsha Davis, Stephen Rathbun 2019-07-23 2019-07-23 12 1 10.5198/jtlu.2019.1512 Analysis of the acceptance of park-and-ride by users: A cumulative logistic regression approach Park-and-ride (P&R) schemes are an important way of increasing the public transport mode share, which relieves the negative impact caused by excessive automobile usage. Several existing studies have been conducted in the past to explore the factors that can influence the acceptance of P&R by travelers. However, quantitative analyses of the pertinent factors and rates of traveler choice are quite rare. In this paper, the data collected from a survey in Melbourne, Australia, is used to analyze the acceptance of P&R by travelers going to the central business district (CBD). In particular, we explore the influence that specific factors have on the choice of travel by those who are currently using P&R. The results indicate that the parking fee in the CBD area, travel time on public transport, and P&R transfer time affect traveler use of P&R. A quantitative assessment of the impact of these three factors is conducted by using a cumulative logistic regression model. Results reveal that the P&R transfer time has the highest sensitivity while public transport travel time has the least. To maximize the use of P&R facilities and public transport, insights into setting parking fees and designing P&R stations are presented. Kai Huang Zhiyuan Liu Ting Zhu Inhi Kim Kun An Copyright (c) 2019 Kai Huang, Zhiyuan Liu, Ting Zhu, Inhi Kim, & Kun An 2019-07-29 2019-07-29 12 1 10.5198/jtlu.2019.1390 Measuring full cost accessibility by auto Traditionally accessibility has been analyzed from the perspective of the mean or expected travel time, which fails to capture the full cost, especially the external cost, of travel. The full cost accessibility (FCA) framework, proposed by Cui and Levinson (2018), provides a theoretical basis to fill the gap. It combines temporal, monetary, and non-monetary internal and external travel costs into accessibility evaluations, considering the time cost, crash cost, emission cost, and monetary cost. This paper extends the FCA framework and measures the full cost accessibility by auto for the Minneapolis - St. Paul Metropolitan area, demonstrating the practicality of the FCA framework on real networks. Mengying Cui David Levinson Copyright (c) 2019 Mengying Cui, David Levinson 2019-08-05 2019-08-05 12 1 10.5198/jtlu.2019.1495 Mode choice in access and egress stages of high-speed railway travelers in China High-speed railway (HSR) has become a sustainable transport mode for inter-city travel, especially in China. As public transport (PT), the use of HSR involves access and egress to and from HSR stations. However, the literature focusing on the intra-city mode choice of HSR travelers is limited, especially regarding their differential socio-demographic and trip characteristics. This paper aims to fill that gap with an analysis of access/egress mode choice for business and leisure journeys in the Yangzi River Delta region. Using the HSR survey from Fudan University, we found that in China older and wealthier travelers have a strong preference for car use. For leisure travel, the explanatory power of the socio-demographic variables is much more influential in the egress than the access stage. With increasing access time, business travelers may be enticed to shift to a faster form of PT (e.g., subway rather than bus) in the access stage. With increasing line-haul time, only business travelers have a stronger preference for car use as their intra-city mode choice for business activities. A higher number of subway lines and diversity of land use around HSR stations is associated with less car use for business travelers in the egress stage. Haoran Yang Martin Dijst Jianxi Feng Dick Ettema Copyright (c) 2019 Haoran Yang, Martin Dijst, Jianxi Feng, Dick Ettema 2019-09-26 2019-09-26 12 1 10.5198/jtlu.2019.1420 Using location-based social network data for activity intensity analysis: A case study of New York City Location-based social networks (LBSN) are social media sites where users check-in at venues and share content linked to their geo-locations. LBSN, considered to be a novel data source, contain valuable information for urban planners and researchers. While earlier research efforts focused either on disaggregate patterns or aggregate analysis of social and temporal attributes, no attempt has been made to relate the data to transportation planning outcomes. To that extent, the current study employs LBSN service-based data for an aggregate-level transportation planning exercise by developing land-use planning models. Specifically, we employ check-in data aggregated at the census tract level to develop a quantitative model for activity intensity as a function of land use and built-environment attributes for the New York City (NYC) region. A statistical exercise based on clustering of census tracts and negative binomial regression analyses are adopted to analyze the aggregated data. We demonstrate the implications of the estimated models by presenting the spatial aggregation profiling based on the model estimates. The findings provide insights on relative differences of activity engagements across the urban region. The proposed approach thus provides a complementary analysis tool to traditional transportation planning exercises. Haluk Laman Shamsunnahar Yasmin Naveen Eluru Copyright (c) 2019 Haluk Laman, Shamsunnahar Yasmin, & Naveen Eluru 2019-10-09 2019-10-09 12 1 10.5198/jtlu.2019.1470 Distributional effects of transport policies on inequalities in access to opportunities in Rio de Janeiro The evaluation of social impacts of transport policies has been attracting growing attention in recent years. Yet studies thus far have predominately focused on developed countries and overlooked whether equity assessment of transport projects is sensitive to the modifiable areal unit problem (MAUP). This paper investigates how investments in public transport can reshape socio-spatial inequalities in access to opportunities, and it examines how MAUP can influence the distributional effects of transport project evaluations. The study looks at Rio de Janeiro (Brazil) and the transformations carried out in the city in preparation for the 2014 World Cup and the 2016 Olympics, which involved substantial expansion in public transport infrastructure followed by cuts in service levels. The paper uses before-and-after comparison of Rio's transport network (2014-2017) and quasi-counterfactual analysis to examine how those policies affect access to schools and jobs for different income groups and whether the results are robust when the data is analyzed at different spatial scales and zoning schemes. Results show that subsequent cuts in service levels have offset the accessibility benefits of transport investments in a way that particularly penalizes the poor, and that those investments alone would still have generated larger accessibility gains for higher-income groups. These findings suggest that, contrary to Brazil’s official discourse of transport legacy, recent policies in Rio have exacerbated rather than reduced socio-spatial inequalities in access to opportunities. The study also shows that MAUP can influence the equity assessment of transport projects, suggesting that this issue should be addressed in future research. Rafael H. M. Pereira David Banister Tim Schwanen Nate Wessel Copyright (c) 2019 Rafael H. M. Pereira, David Banister, Tim Schwanen, & Nate Wessel 2019-10-11 2019-10-11 12 1 10.5198/jtlu.2019.1523 Mobility nodes and economic spaces: Links, tensions and planning implications <p>While transport hubs function largely as mobility interchanges, they also serve as spaces of conflict and negotiation, particularly when informal livelihoods of poor populations take place in public spaces like streets and transport terminals. This condition poses challenges to urban planners and transport officials on how to promote inclusive cities without sacrificing urban mobility. We examine how informal trading has become embedded in the land-use patterns of Baclaran, a strategic transport hub in Metro Manila. Three factors emerge as critical in understanding how and why informal trading thrives in Baclaran: a) the presence of commuters as captive market; b) mixed land use and activity agglomeration; and c) multi-layered socio-spatial relations. Our empirical data also shows how normalized informal trading in a mobility node has triggered transport route diversion and supported the growth of small-scale informal transport.</p> Redento Bolivar Recio Sonia Roitman Iderlina Mateo-Babiano Copyright (c) 2019 Redento Bolivar Recio 2019-11-04 2019-11-04 12 1 10.5198/jtlu.2019.1478 Workplace location, polycentricism, and car commuting <p>Although significant strides have been made regarding the relationship between urban structure and travel, some doubt appears to be lingering concerning the impacts of polycentric urban development. For example, the debate on whether a polycentric or monocentric workplace location pattern is favorable for reducing negative environmental effects from transportation has not been entirely settled. This study intends to contribute to clearing up some of the misconceptions by focusing on the implications of spatial distribution of jobs on commuting patterns among employees within the Oslo metropolitan area. Results show a strong tendency for a higher share of car commuting among employees working in suburban workplaces. This pattern persists also for suburban workplaces located close to suburban transit nodes. The share of transit commuters shows the opposite pattern. Commuting distances also tend to increase the farther from the city center the workplace is located. These conclusions are based on cross-sectional and quasi-longitudinal survey data as well as semi-structured in-depth interviews of workers, including several interviewees who had changed their workplace locations. To our knowledge, this is the first mixed-methods study on the influence of workplace location on commuting behavior. The results raise doubt about the appropriateness of polycentric intra-metropolitan workplace development as a strategy for sustainable mobility.</p> Fitwi Wolday Petter Naess Anders Tønnesen Copyright (c) 2019 Fitwi Wolday, Petter Naess, Anders Tønnesen 2019-11-11 2019-11-11 12 1 785 810 10.5198/jtlu.2019.1488 Examining interaction effects among land-use policies to reduce household vehicle travel: An exploratory analysis <p>Numerous studies have suggested that land-use policies can reduce vehicle travel through mode shifting and reduced trip lengths and generation of fewer or more efficient trips. The findings from previous studies also suggest that the combined effect of two or more land-use policies can be significant, although the effects of individual policies appear to be modest. These studies present area-wide impacts of land-use policies on travel and suggest that their effects are additive. However, very little is known about how each land-use policy interacts with the others at different levels of development intensity to reduce vehicle travel. In this study, we explore how three well-known land-use strategies (densification, mixed-use development, and street network improvement) interact with each other by testing possible combinations of land-use factors and focus on how these interactive effects vary by the level of development intensity. Employing ordinary least squares regression analysis using a dataset created for the Austin metropolitan statistical area (MSA) (using 2006 Austin Travel Survey data), we examine the impact of land use on household vehicle travel. Our findings suggest that interaction effects occur, but they vary by development intensity. The results of this study show the importance of considering both threshold (development intensity) and interaction (combination of policies) effects in understanding how land-use factors do and do not affect travel (based on their interactive opposed to only their direct and additive effects). Though this paper uses data from just one MSA and thus is merely suggestive, it does point to a possibly more nuanced use of the commonly prescribed planning and design policy variable to account for variation in effectiveness based on differences in development intensity. For example, we find that greater land-use intensification has higher efficacy in changing vehicle travel behavior in areas with relatively higher development intensity. Future research should include data from a broader array of metropolitan areas and incorporate additional predictor variables that were unavailable for this analysis.</p> Kwangyul Choi Robert Paterson Copyright (c) 2019 Kwangyul Choi and Robert Paterson 2019-11-15 2019-11-15 12 1 839 851 10.5198/jtlu.2019.1337 Planning for nodes, places and people in Flanders and Brussels: Developing an empirical railway station assessment model for strategic decision-making <p>Against the backdrop of current policy discussions in Flanders dealing with differentiated urban development schemes for strategic railway stations, this paper develops an empirical railway station assessment tool. We build on the node-place modeling literature, and more specifically on the tradition of quantitative station assessment models which has emerged from it. First, a series of methodological contributions are proposed in which we suggest strategies to improve the analytical strength of some standard node-place parameters, we broaden the model with temporal variability in accessibility, and we complement the model with a user-based accessibility account. Second, the conceptual model is applied to the case of Flanders and Brussels (the north of Belgium). Drawing on factor and cluster analysis, two intelligible station typologies are produced for both node-place and user-based data. Both typologies are interpreted and complemented with station-specific rose diagrams summarizing a station’s accessibility profile. These diagrams reveal insightful and detailed knowledge about station-specific accessibility characteristics, some of which are not captured by standard node-place analyses. Lastly, a more in-depth discussion focusing on five exemplary cases reveals what the results of these analyses may mean for planning practice.</p> Freke Caset Filipe Marques Teixeira Ben Derudder Kobe Boussauw Frank Witlox Copyright (c) 2019 Freke Caset, Filipe Marques Teixeira, Ben Derudder, Kobe Boussauw, Frank Witlox 2019-11-22 2019-11-22 12 1 811 837 10.5198/jtlu.2019.1483 Combining accessibilities for different activity types: Methodology and case study <p>Accessibility is a key concept in transport planning. Most studies only focus on specific activity types, but for policy making it is more relevant to aggregate accessibility overall or at least several activity types. However, to the best of our knowledge, there is no study that combines accessibilities for different activity types. Since access to spatially separated activities is one dimension of quality of life, and activity types are not equally important for quality of life, we propose a methodology that is based on weighing activity types according to their relative importance to quality of life to assess overall accessibility. Four principles are adopted to develop the weighting factors: 1) the human needs the activity types satisfy; 2) the activity types' contribution to quality of life; 3) the activity types' trip frequency; 4) further modifications, based on principles such as whether the activity types are needed in emergent situations, and social values and policy preferences. We combine these four principles and apply the methodology in a case study focused on Germany.</p> Lijuan Zheng Bert van Wee Markus Oeser Copyright (c) 2019 Lijuan Zheng, Bert van Wee, Markus Oeser 2019-12-03 2019-12-03 12 1 853 872 10.5198/jtlu.2019.1529 A joint model of place of residence (POR) and place of work (POW): Making use of Gibbs sampling technique to overcome arbitrary assumptions in contexts of data limitation <p>Place or residence (POR) and place of work (POW) are two spatial pivots defining patterns of travel behavior. These choices are considered part of long-term choice influencing short-term daily travel choices. Hence, POR-POW distributions are input into almost all daily travel demand models. However, in many cases, POW-POR is modelled in an ad-hoc way considering the gravity-based or entropy is maximizing aggregate modelling approach. Lack of data on the sequence of choices related to POR and POW is often blamed for avoiding using disaggregate choice model. Recognizing such data limitation, this paper presents an alternative methodology of modelling joint distribution of POW-POW that uses disaggregate choice models without necessarily knowing the sequence of POR and POW choices. It uses the conditional probability break downs of joint POR-POW choice probabilities as depicted in the Gibbs sampling approach. This allows capturing effects of household socioeconomic characteristics, zonal land-use characteristics, and modal accessibility factors in the POR-POW models. The model is applied for a case study in the city of Ottawa. Results reveal that the proposed methodology can replicate observed patterns of POR-POW with a high degree of accuracy.</p> Hengyang Zhang Jason Hawkins Khandker Nurul Habib Copyright (c) 2019 Hengyang Zhang, Jason Hawkins, & Khandker Nurul Habib 2019-12-03 2019-12-03 12 1 873 892 10.5198/jtlu.2019.1624 Temporal sampling and service frequency harmonics in transit accessibility evaluation In the context of public transit networks, repeated calculation of accessibility at multiple departure times provides a more robust representation of local accessibility. However, these calculations can require significant amounts of time and/or computing power. One way to reduce these requirements is to calculate accessibility only for a sample of time points over a time window of interest, rather than every one. To date, many accessibility evaluation projects have employed temporal sampling strategies, but the effects of different strategies have not been investigated and their performance has not been compared. Using detailed block-level accessibility calculated at 1-minute intervals as a reference dataset, four different temporal sampling strategies are evaluated using aggregate sample error metrics as well as indicators of spatially clustered error. Systematic sampling at a regular interval performs well on average but is susceptible to spatially-clustered harmonic error effects which may bias aggregate accessibility results. A constrained random walk sampling strategy provides slightly worse average sample error, but eliminates the risk of harmonic error effects. Andrew Owen Brendan Murphy Copyright (c) 2019 Andrew Owen, Brendan Murphy 2019-12-08 2019-12-08 12 1 893 913 Re-examination of the standards for transit oriented development influence zones in India Transit oriented development (TOD) is a land-use and transport integrated urban planning strategy that is highly acclaimed for promoting sustainable city development. This review aims to identify the problems regarding adoption of TOD standards or guidelines formulated by developed countries in developing countries, such as India, and the necessity of conducting adaptability studies on TOD influence areas. The existing studies show that the size of the influence area varies among different cities and travel modes. Accordingly, no single size influence zone is suitable for all cases. This review highlights the necessity of carefully considering the spatial extent of influence areas and modes other than walking as access or egress modes in the Indian context. Moreover, this review aims to provide insight on how to plan TOD in the context of developing countries, because the mobility patterns in these countries differ considerably from those in the developed world. Sangeetha Ann Meilan Jiang Toshiyuki Yamamoto Copyright (c) 2019 Sangeetha Ann, Meilan Jiang, Toshiyuki Yamamoto 2019-09-23 2019-09-23 12 1 10.5198/jtlu.2019.1534 Integrated modeling in the UK: Practical usability of integrated models This short paper reviews the range of planning issues that are currently being addressed in Britain and considers how the nature of these issues and the ways in which choices are being assessed impact the modeling approaches being adopted, in particular, by the author’s own consultancy practice. The paper briefly outlines current developments in governance and analytical requirements; implications of trends toward more detailed (and more time-consuming) transport modeling; and the role of microsimulation in both research and planning practice. It concludes primarily that the practicality of model operation, particularly in terms of model run times, is of critical importance, and in many cases, determines whether major planning decisions are made on the basis of formal analysis rooted, albeit indirectly, in research, or without such a basis at all. A secondary conclusion relates to the possible use of output from detailed microsimulation models as a basis for calibrating aggregate models. David Simmonds Copyright (c) 2019 David Simmonds 2019-05-13 2019-05-13 12 1 10.5198/jtlu.2019.1206 Building a PECAS Activity Allocation Module: The experience from Caracas We applied the PECAS Framework, a spatial economic system for forecasting and policy analysis, to the region of Caracas, Venezuela. In this paper, we describe in 12 steps the elements developed for an Activity Allocation model in this region. A detailed inventory of built space and household characteristics was developed using a population synthesis technique. The model design and implementation reflected informal (slum) housing and social equity (with 20 residential space types), while accounting for the industrial mix of the region. Transport costs for economic interactions were calculated using a TRANUS travel demand model. We also describe the calibration of the model and the application to two policy scenarios: provision of public housing and increasing transit fares. The 12 steps can guide future researchers, specifically listing the data and processes that were applied in this context. The sensitivity tests showed how this type of model can be used to anticipate social equity effects due to policy. Based on the know-how gained, we provide valuable insights for other modelling teams, particularly for applications in developing economies. Geraldine J. Fuenmayor John E. Abraham John Douglas Hunt Copyright (c) 2019 Geraldine J. Fuenmayor, John E. Abraham, John Douglas Hunt 2019-06-14 2019-06-14 12 1 10.5198/jtlu.2019.1188 Introduction to special issue: Rail transit development in China and beyond Rail transit is widely considered an efficient and environment-friendly means to address the increasing demand for travel. In the past decades, the scale and speed of China's rail transit development has been unprecedented. By the end of 2017, a total of 165 urban rail lines including heavy rail and light rail were in operation in 34 cities in mainland China, with a total track length of 5,033 kilometers (km), and the vast majority of them were built after 2000 (China Association of Metros, 2017). At the intercity scale, China has built the largest high-speed rail (HSR) network in the world, with over 29,000 km HSR lines by the end of 2018 (Central Government of China, 2019). Efforts to develop rail transit are also observed in other cities in both developing and developed countries. We planned this special issue in response to the rapid development of rail transit in China and beyond. In preparation for the special issue, we organized two symposiums to facilitate debates on related research topics in June 2017, including a special session on rail transit at the 11th annual conference of the International Association for China Planning (IACP) hosted by the Harbin Institute of Technology in Harbin, China, and the second Symposium on the HSR Network in China hosted by Jinan University in Guangzhou, China. Mi Diao Yingling Fan Xueliang Zhang Copyright (c) 2019 Mi Diao, Yingling Fan, Xueliang Zhang 2019-04-22 2019-04-22 12 1 10.5198/jtlu.2019.1571 The impacts of light rail on residential property values in a non-zoning city: A new test on the Houston METRORail transit line The impacts of rail transit system on residential property values have been examined for many metropolitan areas in the U.S. But there are few studies on the effects of light rail in a non-zoning city. As the rail transit in the largest non-zoning city, Houston’s light rail transit line, or the so-called METRORail, has not received much attention from the planning research society since it opened to the public in 2004. A previous study by the author utilized 2007 household data to analyze the impacts of Houston’s METRORail line and found the net effects of the rail transit line change significantly at different distances from the rail stations. One limitation of that study was that the physical environment and neighborhood characteristics of the station areas may not have had notable changes over a relatively short time span, i.e., three years after the opening of the light rail. This study employs 2010 InfoUSA household data to re-examine the effects of Houston’s METRORail line. Similar to the previous studies, the author adopts a traditional ordinary linear regression (OLS) to investigate the contribution of a set of variables representing the physical, neighborhood, and accessibility characteristics of properties, and also employs a multi-level regression model (MLR) to examine the hierarchical structures of spatial data explicitly. In addition, this study tests the spatial autocorrelation in the modeling process and analyzes its effects on the results. The modeling results suggest that the METRORail line has had significant net positive effects on residential property values. The MLS model captures the difference of these effects with more spatial details. The spatial regression model improves model fit, but spatial autocorrelation is not completely eliminated. Qisheng Pan Copyright (c) 2019 Qisheng Pan 2019-04-22 2019-04-22 12 1 10.5198/jtlu.2019.1310 Impact of high-speed rail on intercity travel behavior change: The evidence from the Chengdu-Chongqing Passenger Dedicated Line This paper investigates the impact of high-speed rail (HSR) on intercity travel behavior changes using the Chengdu-Chongqing (Chengyu) Passenger Dedicated Line (PDL) as an example. Based on the statistical analysis of survey data that consists of 1384 samples, the result shows that HSR has become the primary mode of intercity travel between Chengdu and Chongqing. Specifically, travel demand has increased by 60% after the operation of the HSR system and the demand change is affected by several factors, such as trip purpose, gender, and travel time savings. The result also shows that the variation of travel demand in both directions declined after the opening of HSR, which suggests that HSR tends to promote a convergent growth of intercity travel demand. Although most passengers ride the Chengyu HSR for a personal reason, the number of riders using it for commuting and business purposes has also increased substantially. Overall, the study confirms that the economic link between Chengdu and Chongqing has been enhanced by the operation of HSR. Xiaohong Ren Zhenhua Chen Fang Wang Jiamei Wang Chunyang Wang Ting Dan Zongyang Du Copyright (c) 2019 Xiaohong Ren, Zhenhua Chen, Fang Wang, Jiamei Wang, Chunyang Wang,Ting Dan, & Zongyang Du 2019-04-22 2019-04-22 12 1 10.5198/jtlu.2019.1302 Estimating the economic benefits of high-speed rail in China: A new perspective from the connectivity improvement This paper evaluates the economic benefits of high-speed rail (HSR) in China, with a focus on the connectivity change resulting from HSR development. The effect of HSR, measured in degree centrality, is assessed using a spatial econometric modeling technique based on a panel dataset that covers 268 Chinese cities from 2008-2015. To provide a robust assessment, statistical issues including heterogeneous effects, endogeneity, and spatial dependence are addressed simultaneously in the spatial panel modeling process. Our empirical results confirm that connectivity improvement brought by HSR plays a vital role in facilitating economic growth. Specifically, the contribution of HSR to urban economic growth is found to be 0.11, most of which comes from a local effect rather than a spillover effect. Overall, the research findings suggest that urban economic growth can benefit from the development of HSR. Zhaohui Chong Chenglin Qin Zhenhua Chen Copyright (c) 2019 Zhaohui Chong, Chenglin Qin, Zhenhua Chen 2019-04-22 2019-04-22 12 1 10.5198/jtlu.2019.1264