IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v564y2021ics0378437120307913.html
   My bibliography  Save this article

Research on the coupling degree of regional taxi demand and social development from the perspective of job–housing travels

Author

Listed:
  • Hu, Beibei
  • Zhang, Shuang
  • Ding, Yang
  • Zhang, Min
  • Dong, Xianlei
  • Sun, Huijun

Abstract

Due to the urban industrial transformation and upgrading in China, the relationship between residential and employment spaces in large cities has changed significantly, resulting in an increasingly prominent job–housing separation phenomenon. Based on the taxi GPS trajectory data, this paper firstly analyzes the time and space distribution of job–housing–travel and the commuting characteristics of residents. Then, we construct the evaluation index systems of regional jobs–housing–taxi demand and regional social development level for Beijing. After calculating the weight of each index by using an entropy weight method, we analyze the coupling relationship between regional taxi demand and social development by building the coupling coordination degree model (CCDM). Conclusions are as follows: Firstly, it shows imbalance of space distribution of taxi orders in different administrative and functional areas. The order quantity gradually decreases from the main urban area to the edge, with the most in the living area, accounting for 46.23% of the total orders. Secondly, the daily variation trend of taxi orders in different functional areas is significantly different. During the morning rush hour, taxi orders flow out of residential areas and into office areas; however, during the evening rush hour, they flow out of the office and into the living area. For example, the residence area has a higher proportion of getting on passengers during the morning rush hour, which is 1.46 times that of the getting off ones. Thirdly, a low coupling coordination degree is observed between the regional social development level and the job–housing–taxi demand in Beijing, with a gradually decreasing from the main urban area to the outside, which is mainly caused by the imbalance between supply and demand. Therefore, it is suggested that the relevant government departments should formulate specific control schemes to traffic congestion according to local commuting features, and promote job–housing balance. Meanwhile, the taxi resources are supposed to be allocated reasonably by the striving to information symmetry, to promote the coordination and sustainability between the regional job–housing–taxi demand and social development level.

Suggested Citation

  • Hu, Beibei & Zhang, Shuang & Ding, Yang & Zhang, Min & Dong, Xianlei & Sun, Huijun, 2021. "Research on the coupling degree of regional taxi demand and social development from the perspective of job–housing travels," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 564(C).
  • Handle: RePEc:eee:phsmap:v:564:y:2021:i:c:s0378437120307913
    DOI: 10.1016/j.physa.2020.125493
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437120307913
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

    File URL: https://libkey.io/10.1016/j.physa.2020.125493?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Dong Lin & Andrew Allan & Jianqiang Cui, 2016. "Exploring Differences in Commuting Behaviour among Various Income Groups during Polycentric Urban Development in China: New Evidence and Its Implications," Sustainability, MDPI, vol. 8(11), pages 1-17, November.
    2. Kim S. So & Peter F. Orazem & Daniel M. Otto, 2001. "The Effects of Housing Prices, Wages, and Commuting Time on Joint Residential and Job Location Choices," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 83(4), pages 1036-1048.
    3. Xiang Zhou & Xiaohong Chen & Tianran Zhang, 2016. "Impact of Megacity Jobs-Housing Spatial Mismatch on Commuting Behaviors: A Case Study on Central Districts of Shanghai, China," Sustainability, MDPI, vol. 8(2), pages 1-22, January.
    4. Giuliano, Genevieve, 1991. "Is Jobs-Housing Balance a Transportation Issue?," University of California Transportation Center, Working Papers qt4874r4hg, University of California Transportation Center.
    5. Tam, Maggie C. Y. & Tummala, V. M. Rao, 2001. "An application of the AHP in vendor selection of a telecommunications system," Omega, Elsevier, vol. 29(2), pages 171-182, April.
    6. Rowe, Gene & Wright, George, 1999. "The Delphi technique as a forecasting tool: issues and analysis," International Journal of Forecasting, Elsevier, vol. 15(4), pages 353-375, October.
    7. So, Kim Sui & Orazem, Peter & Otto, Daniel, 2001. "The Effects of Housing Prices, Wages, and Commuting Time on Urban-Rural Residential Choice," Staff General Research Papers Archive 1204, Iowa State University, Department of Economics.
    8. Kevin Manaugh & Luis Miranda-Moreno & Ahmed El-Geneidy, 2010. "The effect of neighbourhood characteristics, accessibility, home–work location, and demographics on commuting distances," Transportation, Springer, vol. 37(4), pages 627-646, July.
    9. Tang, Zi, 2015. "An integrated approach to evaluating the coupling coordination between tourism and the environment," Tourism Management, Elsevier, vol. 46(C), pages 11-19.
    10. Yang Yang & Zhenzhou Yuan & Xin Fu & Yinhai Wang & Dongye Sun, 2019. "Optimization Model of Taxi Fleet Size Based on GPS Tracking Data," Sustainability, MDPI, vol. 11(3), pages 1-19, January.
    11. Yaoqing Yuan & Maozhu Jin & Jinfei Ren & Mingming Hu & Peiyu Ren, 2014. "The Dynamic Coordinated Development of a Regional Environment-Tourism-Economy System: A Case Study from Western Hunan Province, China," Sustainability, MDPI, vol. 6(8), pages 1-21, August.
    12. Jianqi Liu & Jiafu Wan & Qinruo Wang & Pan Deng & Keliang Zhou & Yupeng Qiao, 2016. "A survey on position-based routing for vehicular ad hoc networks," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 62(1), pages 15-30, May.
    13. Zhao, Pengjun & Lü, Bin & Roo, Gert de, 2011. "Impact of the jobs-housing balance on urban commuting in Beijing in the transformation era," Journal of Transport Geography, Elsevier, vol. 19(1), pages 59-69.
    14. Cervero, Robert, 1989. "Jobs-Housing Balancing and Regional Mobility," University of California Transportation Center, Working Papers qt7mx3k73h, University of California Transportation Center.
    15. Dong, Xianlei & Zhang, Min & Zhang, Shuang & Shen, Xinyi & Hu, Beibei, 2019. "The analysis of urban taxi operation efficiency based on GPS trajectory big data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 528(C).
    16. Wang, Donggen & Chai, Yanwei, 2009. "The jobs–housing relationship and commuting in Beijing, China: the legacy of Danwei," Journal of Transport Geography, Elsevier, vol. 17(1), pages 30-38.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Li, Ze-Tao & Nie, Wei-Peng & Cai, Shi-Min & Zhao, Zhi-Dan & Zhou, Tao, 2023. "Exploring the topological characteristics of urban trip networks based on taxi trajectory data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 609(C).
    2. Min Zhang & Yufu Liu & Wenqi Sun & Yixiong Xiao & Chang Jiang & Yong Wang & Yuqi Bai, 2021. "Impact of Rainfall on Traffic Speed in Major Cities of China," Sustainability, MDPI, vol. 13(16), pages 1-17, August.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Islam, Md Rabiul & Saphores, Jean-Daniel M., 2022. "An L.A. story: The impact of housing costs on commuting," Journal of Transport Geography, Elsevier, vol. 98(C).
    2. Zheng, Zhong & Zhou, Suhong & Deng, Xingdong, 2021. "Exploring both home-based and work-based jobs-housing balance by distance decay effect," Journal of Transport Geography, Elsevier, vol. 93(C).
    3. Jiangping, Zhou & Chun, Zhang & Xiaojian, Chen & Wei, Huang & Peng, Yu, 2014. "Has the legacy of Danwei persisted in transformations? the jobs-housing balance and commuting efficiency in Xi’an," Journal of Transport Geography, Elsevier, vol. 40(C), pages 64-76.
    4. Mitra, Suman K. & Saphores, Jean-Daniel M., 2019. "Why do they live so far from work? Determinants of long-distance commuting in California," Journal of Transport Geography, Elsevier, vol. 80(C).
    5. Qin, Ping & Wang, Lanlan, 2019. "Job opportunities, institutions, and the jobs-housing spatial relationship: Case study of Beijing," Transport Policy, Elsevier, vol. 81(C), pages 331-339.
    6. Li, Si-ming & Liu, Yi, 2016. "The jobs-housing relationship and commuting in Guangzhou, China: Hukou and dual structure," Journal of Transport Geography, Elsevier, vol. 54(C), pages 286-294.
    7. Zhou, Xingang & Yeh, Anthony G.O. & Yue, Yang, 2018. "Spatial variation of self-containment and jobs-housing balance in Shenzhen using cellphone big data," Journal of Transport Geography, Elsevier, vol. 68(C), pages 102-108.
    8. Xiaoxu, Xing & Qiangmin, Xi & Weihao, Shi, 2024. "Impact of urban compactness on carbon emission in Chinese cities: From moderating effects of industrial diversity and job-housing imbalances," Land Use Policy, Elsevier, vol. 143(C).
    9. Andrew R. Watkins, 2016. "Commuting Flows and Labour Market Structure: Modelling Journey to Work Behaviour in an Urban Environment," Growth and Change, Wiley Blackwell, vol. 47(4), pages 612-630, December.
    10. Wang, Donggen & Chai, Yanwei & Li, Fei, 2011. "Built environment diversities and activity–travel behaviour variations in Beijing, China," Journal of Transport Geography, Elsevier, vol. 19(6), pages 1173-1186.
    11. Jie Huang & David Levinson & Jiaoe Wang & Haitao Jin, 2019. "Job-worker spatial dynamics in Beijing: Insights from Smart Card Data," Working Papers 2019-01, University of Minnesota: Nexus Research Group.
    12. Keone Kelobonye & Feng Mao & Jianhong (Cecilia) Xia & Mohammad Shahidul Hasan Swapan & Gary McCarney, 2019. "The Impact of Employment Self-Sufficiency Measures on Commuting Time: Case Study of Perth, Australia," Sustainability, MDPI, vol. 11(5), pages 1-21, March.
    13. Zhao, Pengjun & Zhang, Yixue, 2019. "The effects of metro fare increase on transport equity: New evidence from Beijing," Transport Policy, Elsevier, vol. 74(C), pages 73-83.
    14. Xiaoyun Li & Hongsheng Chen & Yu Shi & Feng Shi, 2019. "Transportation Equity in China: Does Commuting Time Matter?," Sustainability, MDPI, vol. 11(21), pages 1-17, October.
    15. Bindong Sun & Chun Yin, 2020. "Impacts of a multi-scale built environment and its corresponding moderating effects on commute duration in China," Urban Studies, Urban Studies Journal Limited, vol. 57(10), pages 2115-2130, August.
    16. Zhao, Pengjun & Zhang, Yixue, 2018. "Travel behaviour and life course: Examining changes in car use after residential relocation in Beijing," Journal of Transport Geography, Elsevier, vol. 73(C), pages 41-53.
    17. Juan Zhu & Xinyi Niu & Cheng Shi, 2019. "The Influencing Factors of a Polycentric Employment System on Jobs-Housing Matching—A Case Study of Hangzhou, China," Sustainability, MDPI, vol. 11(20), pages 1-18, October.
    18. Zhong Zheng & Suhong Zhou & Xingdong Deng, 2022. "The spatially heterogeneous and double-edged effect of the built environment on commuting distance: Home-based and work-based perspectives," PLOS ONE, Public Library of Science, vol. 17(3), pages 1-24, March.
    19. Yan Chen & Xiaohong Chen & Hongshan Ai & Xiaoqing Tan, 2022. "Temperature and Migration Intention: Evidence from the Unified National Graduate Entrance Examination in China," IJERPH, MDPI, vol. 19(16), pages 1-23, August.
    20. Ta, Na & Zhao, Ying & Chai, Yanwei, 2016. "Built environment, peak hours and route choice efficiency: An investigation of commuting efficiency using GPS data," Journal of Transport Geography, Elsevier, vol. 57(C), pages 161-170.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:564:y:2021:i:c:s0378437120307913. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.