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Data Details

Commuting Efficiency by Travel Mode Dataset in Shanghai (2015)


YUE Liying1ZHU Yu*1LI Kaiming2
1 Asian Demographic Research Institute，Shanghai University，Shanghai 200444，China2 Department of Architecture，Shanghai Academy of Fine Arts，Shanghai University，Shanghai 200444，China

DOI:10.3974/geodb.2024.09.05.V1

Published:Sep. 2024

Visitors：1845       Data Files Downloaded：15      
Data Downloaded：233.19 MB      Citations：

Key Words：

Commuting efficiency,excess commuting,jobs-housing balance,mode,Shanghai

Abstract：

Based on data at sub-district scale from the 2015 1% National Population Sampling Survey in Shanghai, the authors describes the characteristics of urban commuting efficiency from the perspectives of average travel distance and spatial organization under the excess commuting framework, and explores its heterogeneity across travel mode subgroups. The dataset includes the following data in Shanghai in 2015: (1) the commuting flows number in sub-districts; (2) descriptive statistics of travel modes for different educational worker subgroups; (3) results of commuting efficiency metrics for different travel modes; (4) observed commuting flows matrix for each education-mode subgroup. The dataset is archived in .xlsx data format, and consists of one file with data size of 15.5 MB. The analysis paper based on the dataset was published at Geographical Research, Vol. 43, No. 2, 2024.

Foundation Item：

Ministry of Education of P. R. China (23YJCZH287)

Data Citation：

YUE Liying, ZHU Yu*, LI Kaiming. Commuting Efficiency by Travel Mode Dataset in Shanghai (2015)[J/DB/OL]. Digital Journal of Global Change Data Repository, 2024. https://doi.org/10.3974/geodb.2024.09.05.V1.

References：


     [1] Wu, H. M., Zhu, B. S., Gu, H. H. Spatial mismatch of job-housing and the structure variation for employed population in Shanghai [J]. Chinese Journal of Population Science, 2017(7): 101-115.
     [2] Chai, Y. W., Zhang, Y., Liu, Z. L. Spatial differences of home-work separation and the impacts of housing policy and urban sprawl: Evidence from household survey data in Beijing [J]. Acta Geographica Sinica, 2011, 66(2): 157- 166.
     [3] He, M. W., Zhao, S. C., He, M. Tolerance threshold of commuting time: Evidence from Kunming, China [J]. Journal of Transport Geography, 2016, 57: 1-7.
     [4] Taylor, B. D., Ong, P. M. Spatial mismatch or automobile mismatch: An examination of race, residence and commuting in US metropolitan areas [J]. Urban Studies, 1995, 32(9): 1453-1473.
     [5] Murphy, E. Excess commuting and modal choice [J]. Transportation Research Part A: Policy and Practice, 2009, 43(8): 735-743.
     [6] Zhou, J. P., Murphy, E., Long, Y. Commuting efficiency in the Beijing metropolitan area: An exploration combining smartcard and travel survey data [J]. Journal of Transport Geography, 2014, 41: 175-183.
     [7] Han, H. R., Yang, C. F., Song, J. P. Impact factors and differences in commuting efficiency between public transit and private automobile travel: A case study on the Beijing metropolitan area [J]. Geographical Research, 2017, 36(2): 253-266.
     [8] Yue, L. Y., O’Kelly, M. E., Wu, R. J. An empirical study of commuting efficiency between different educational categories of workers in Shanghai [J]. Geographical Analysis, 2022, 54(4): 820-838.
     [9] Yue, L. Y., O’Kelly, M. E. Variations in excess commuting by educational and occupational worker subgroups: A case study of Shanghai [J]. Socio-Economic Planning Sciences, 2023, 87: 101518.
     [10] Yue, L. Y., Niedzielski, M. A., O'Kelly, M. E. Modal disparity in commuting efficiency: A comparison across educational worker subgroups in Shanghai [J]. Cities, 2024, 147: 104790.
     

Data Product:

ID Data Name Data Size Operation
1 CommutingEfficiencyShanghai2015.xls 15919.00KB
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