Author
Listed:
- Dan Wan
(College of Urban and Environmental Sciences, Peking University, Beijing 100871, China)
- Lindan Zhao
(Research Center for Special Economic Zone in China, Shenzhen University, Shenzhen 518060, China
Shenzhen Real Estate and Urban Development Research Center, Shenzhen 518028, China)
- Xiaoli Chong
(Shenzhen Real Estate and Urban Development Research Center, Shenzhen 518028, China)
- Yanzhe Cui
(School of Urban Planning & Design, Peking University Shenzhen Graduate School, Shenzhen 518055, China)
Abstract
Excess commuting reflects the inefficiency of urban land resource allocation, generating additional greenhouse gas emissions and social costs, and has therefore become a central concern in the pursuit of sustainable cities. While exogenous shocks inevitably alter the efficiency of land resource allocation, it remains unclear how such shocks affect overall urban efficiency. To address this gap, this paper proposes a generalized framework for measuring excess commuting that accounts for imbalances between the numbers of jobs and residences. Drawing on mobile signaling big data, we trace the daily commuting patterns of more than 900,000 residents in Beijing, comparing the pre-pandemic period (March–October 2019) with the pandemic period (March–October 2020). The results show that: (1) Excess commuting increased significantly after the outbreak of COVID-19, with the observed average commuting distance (Tact) of the full sample rising from 6267 m to 10,058 m (an increase of 59%), indicating a decline in urban land resource allocation efficiency; (2) A more pronounced center-periphery pattern emerged at the metropolitan scale: the average Jobs–Housing Ratio (JHR) increased from 1.08 to 1.11, and its standard deviation rose from 0.54 to 0.70, with the JHR of central urban areas decreasing by 3% and that of suburban areas increasing by 20%—suggesting a marked increase in commuting distances; (3) Heterogeneous impacts were observed across age groups: the Difference-in-Differences (DID) regression confirmed a significant negative interaction term (Group × COVID-19 = −0.2991 **, p < 0.05), indicating that older adults experienced a greater increase in commuting inefficiency than younger adults. These findings reveal the dynamic mechanisms linking exogenous shocks, jobs–housing mismatch, and urban land resource allocation efficiency and provide policy implications for improving spatial resource allocation in the post-pandemic era.
Suggested Citation
Dan Wan & Lindan Zhao & Xiaoli Chong & Yanzhe Cui, 2026.
"The Mechanism by Which Jobs–Housing Mismatch Affects Urban Land Resource Allocation Efficiency Under External Shocks: An Excess Commuting Perspective,"
Land, MDPI, vol. 15(1), pages 1-21, January.
Handle:
RePEc:gam:jlands:v:15:y:2026:i:1:p:166-:d:1840435
Download full text from publisher
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:gam:jlands:v:15:y:2026:i:1:p:166-:d:1840435. 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.
We have no bibliographic references for this item. You can help adding them by using 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: MDPI Indexing Manager The email address of this maintainer does not seem to be valid anymore. Please ask MDPI Indexing Manager to update the entry or send us the correct address
(email available below). General contact details of provider: https://www.mdpi.com .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.