Mobility and travel behavior in urban China: The role of institutional factors

Yao, Mingzhu; Wang, Donggen

doi:10.1016/j.tranpol.2018.05.012

Cited by 28 publications

(10 citation statements)

References 50 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Particularly, early studies published in Chinese tended to be descriptive without statistically testing the urban structure-travel relationship, and later studies tended to use simple regression models, such as the ordinary least squares models or multinomial logit models, although some recent studies published in English have adopted advanced modeling techniques (D. Wang and Chai 2009;B. Sun et al 2017;Jing Ma, Liu, and Chai 2015;Yao and Wang 2018).…”

Section: Summary Of the Scoping Review Resultsmentioning

confidence: 99%

“…Wang and Chai 2009; H. Hu et al 2018) and jobs–housing distance (Yao and Wang 2018). These simple indicators already reflect commuting distance, and therefore, a tight jobs–housing relationship, based on these measures, for sure reduces commutes.…”

Section: Scoping Review Of the Urban Structure–travel Relationship Inmentioning

confidence: 99%

“…We noted evolution in the methodological approaches in the scoping review. Although most existing studies still only detect correlations, recent studies have started to adopt advanced modeling techniques, such as the structural equation models (e.g., Jing Ma, Liu, and Chai 2015; Yao and Wang 2018), to separate the effects of endogenous and exogenous factors. Future studies should embark on the challenging tasks to untangle the causal relationship, particularly by developing comprehensive and dynamic analysis frameworks.…”

Section: Research Agendamentioning

confidence: 99%

“…Simple indicators include relative jobs-housing locations (whether work and live in the same district; e.g., D. Lin, Allan, and Cui 2016; D. Wang and Chai 2009;H. Hu et al 2018) and jobs-housing distance (Yao and Wang 2018). These simple indicators already reflect commuting distance, and therefore, a tight jobs-housing relationship, based on these measures, for sure reduces commutes.…”

Section: Jobs-housing Relationshipmentioning

confidence: 99%

See 3 more Smart Citations

Urban Spatial Structure and Travel in China

Yang

et al. 2019

Journal of Planning Literature

View full text Add to dashboard Cite

This article first provides a critical scoping review of empirical literature on the relationship between urban structure and travel in China. The review finds that residential suburbanization alone increases travel, polycentric development has mixed effects, and jobs–housing balance reduces travel. Second, this article compares the empirical findings of the urban structure–travel relationships in China with those observed in other countries, and it identifies contextual factors that can explain the differing relationships in China. We suggest that future research improve data and methodology and broaden the research scope to investigate the complex mechanisms that affect the urban structure–travel relationship in China.

show abstract

Section: Summary Of the Scoping Review Resultsmentioning

confidence: 99%

Section: Scoping Review Of the Urban Structure–travel Relationship Inmentioning

confidence: 99%

Section: Research Agendamentioning

confidence: 99%

Section: Jobs-housing Relationshipmentioning

confidence: 99%

See 2 more Smart Citations

Urban Spatial Structure and Travel in China

Yang

et al. 2019

Journal of Planning Literature

View full text Add to dashboard Cite

show abstract

“…The distribution pattern and density of POIs influence the travel activity behaviours by significantly affecting the urban land use planning [37]. For example, Yao and Wang [38] note that in China, danwei or type of work unit is an important institutional factor in explaining jobs -housing relationship and commuting behaviour. In particular, hukou, or household registration, is a crucial institutional factor that influences the individuals' mobility and travel behaviour.…”

Section: Related Studiesmentioning

confidence: 99%

Spatial Distribution of Travel Activities and its Relationship with Points of Interest

Cao

Yin

et al. 2021

PROMET

View full text Add to dashboard Cite

This study explores the spatial distribution characteristics of travel activities and their relationship with land use, using data from the resident travel survey in 2015 of Xiaoshan District of Hangzhou City, China. A new classification method is proposed to classify the travel activity patterns into three groups: single-activity travel, multi-activity intermittent travel, and multi-activity continuous travel. The main findings are: (a) the length of activity chain and the proportion of multi-activity travels increase with the distance between residence and activity centre; (b) the non-home destinations of single-activity travel, multi-activity intermittent travel and multi-activity continuous travel agglomerate towards the activity centre, and the degree of agglomeration increases in this order; (c) the distribution density of Point Of Interest (POI) and activity destinations have strong positive correlations in space; (d) some attributes of POIs and demographics have significant influence on multi-activity continuous travels. These findings are useful in inducing the activities through reasonable combinations and spatial interconnections of POIs in urban planning.

show abstract

Studies of the effectiveness of transport sector interventions in low‐ and middle‐income countries: An evidence and gap map

Malhotra

White

Cruz³

et al. 2021

Campbell Systematic Reviews

View full text Add to dashboard Cite

Background There are great disparities in the quantity and quality of infrastructure. European countries such as Denmark, Germany, Switzerland, and the UK have close to 200 km of road per 100 km2, and the Netherlands over 300 km per 100 km2. By contrast, Kenya and Indonesia have <30, Laos and Morocco <20, Tanzania and Bolivia <10, and Mauritania only 1 km per 100 km2. As these figures show, there is a significant backlog of transport infrastructure investment in both rural and urban areas, especially in sub‐Saharan Africa. This situation is often exacerbated by weak governance and an inadequate regulatory framework with poor enforcement which lead to high costs and defective construction. The wellbeing of many poor people is constrained by lack of transport, which is called “transport poverty”. Lucas et al. suggest that up to 90% of the world's population are transport poor when defined as meeting at least one of the following criteria: (1) lack of available suitable transport, (2) lack of transport to necessary destinations, (3) cost of necessary transport puts household below the income poverty line, (4) excessive travel time, or (5) unsafe or unhealthy travel conditions. Objectives The aim of this evidence and gap map (EGM) is to identify, map, and describe existing evidence from studies reporting the quantitative effects of transport sector interventions related to all means of transport (roads, rail, trams and monorail, ports, shipping, and inland waterways, and air transport). Methods The intervention framework of this EGM reframes Berg et al's three categories (infrastructure, prices, and regulations) broadly as infrastructure, incentives, and institutions as subcategories for each intervention category which are each mode of transport (road, rail trams and monorail, ports, shipping, and inlands waterways, and air transport). This EGM identifies the area where intervention studies have been conducted as well as the current gaps in the evidence base. This EGM includes ongoing and completed impact evaluations and systematic reviews (SRs) of the effectiveness of transport sector interventions. This is a map of effectiveness studies (impact evaluations). The impact evaluations include experimental designs, nonexperimental designs, and regression designs. We have not included the before versus after studies and qualitative studies in this map. The search strategies included both academic and grey literature search on organisational websites, bibliographic searches and hand search of journals. An EGM is a table or matrix which provides a visual presentation of the evidence in a particular sector or a subsector. The map is presented as a matrix in which rows are intervention categories (e.g., roads) and subcategories (e.g., infrastructure) and the column outcome domains (e.g., environment) and subcategories as (e.g., air quality). Each cell contains studies of the corresponding intervention for the relevant outcome, with links to the available studies. Included studies were coded according to the interve...

show abstract

Mobility and travel behavior in urban China: The role of institutional factors

Cited by 28 publications

References 50 publications

Urban Spatial Structure and Travel in China

Urban Spatial Structure and Travel in China

Spatial Distribution of Travel Activities and its Relationship with Points of Interest

Studies of the effectiveness of transport sector interventions in low‐ and middle‐income countries: An evidence and gap map

Contact Info

Product

Resources

About