Lockdown and restaurant closures: evidence from large-scale data in China
Abstract This study examines the impact of the COVID-19 lockdown on China’s restaurant industry, a critical contributor to national GDP and employment. Using a large-scale dataset of 14,488,951 restaurant-year observations covering 5,560,345 unique restaurants across 301 cities (2020–2023), we emplo...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Springer Nature
2025-07-01
|
| Series: | Humanities & Social Sciences Communications |
| Online Access: | https://doi.org/10.1057/s41599-025-05412-8 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849388300400328704 |
|---|---|
| author | Yuxiao Ye Li Wang Shenyang Jiang Yu Xiong |
| author_facet | Yuxiao Ye Li Wang Shenyang Jiang Yu Xiong |
| author_sort | Yuxiao Ye |
| collection | DOAJ |
| description | Abstract This study examines the impact of the COVID-19 lockdown on China’s restaurant industry, a critical contributor to national GDP and employment. Using a large-scale dataset of 14,488,951 restaurant-year observations covering 5,560,345 unique restaurants across 301 cities (2020–2023), we employ the Cox proportional hazard model to examine how lockdown influences restaurant closure. We find that each additional 12 days of local lockdown increases the closure risk by 12.7%. While most restaurants face elevated risks, those with higher star ratings are more resilient. Chain restaurants, older establishments, higher-priced venues, and those offering unique cuisines or located near commercial hubs and transit stations are less likely to close. In contrast, newer, independent, lower-priced restaurants, especially those offering common cuisines, providing delivery, or located in less accessible areas, are more vulnerable. These findings highlight the uneven impact of lockdowns across restaurant types and locations and point to the key factors that support restaurant resilience during disruptions. |
| format | Article |
| id | doaj-art-bcff287c56544b32a555b138d77b226c |
| institution | Kabale University |
| issn | 2662-9992 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Springer Nature |
| record_format | Article |
| series | Humanities & Social Sciences Communications |
| spelling | doaj-art-bcff287c56544b32a555b138d77b226c2025-08-20T03:42:20ZengSpringer NatureHumanities & Social Sciences Communications2662-99922025-07-0112111410.1057/s41599-025-05412-8Lockdown and restaurant closures: evidence from large-scale data in ChinaYuxiao Ye0Li Wang1Shenyang Jiang2Yu Xiong3University of Nottingham Ningbo ChinaHong Kong Polytechnic UniversityHong Kong Polytechnic UniversityUniversity of SurreyAbstract This study examines the impact of the COVID-19 lockdown on China’s restaurant industry, a critical contributor to national GDP and employment. Using a large-scale dataset of 14,488,951 restaurant-year observations covering 5,560,345 unique restaurants across 301 cities (2020–2023), we employ the Cox proportional hazard model to examine how lockdown influences restaurant closure. We find that each additional 12 days of local lockdown increases the closure risk by 12.7%. While most restaurants face elevated risks, those with higher star ratings are more resilient. Chain restaurants, older establishments, higher-priced venues, and those offering unique cuisines or located near commercial hubs and transit stations are less likely to close. In contrast, newer, independent, lower-priced restaurants, especially those offering common cuisines, providing delivery, or located in less accessible areas, are more vulnerable. These findings highlight the uneven impact of lockdowns across restaurant types and locations and point to the key factors that support restaurant resilience during disruptions.https://doi.org/10.1057/s41599-025-05412-8 |
| spellingShingle | Yuxiao Ye Li Wang Shenyang Jiang Yu Xiong Lockdown and restaurant closures: evidence from large-scale data in China Humanities & Social Sciences Communications |
| title | Lockdown and restaurant closures: evidence from large-scale data in China |
| title_full | Lockdown and restaurant closures: evidence from large-scale data in China |
| title_fullStr | Lockdown and restaurant closures: evidence from large-scale data in China |
| title_full_unstemmed | Lockdown and restaurant closures: evidence from large-scale data in China |
| title_short | Lockdown and restaurant closures: evidence from large-scale data in China |
| title_sort | lockdown and restaurant closures evidence from large scale data in china |
| url | https://doi.org/10.1057/s41599-025-05412-8 |
| work_keys_str_mv | AT yuxiaoye lockdownandrestaurantclosuresevidencefromlargescaledatainchina AT liwang lockdownandrestaurantclosuresevidencefromlargescaledatainchina AT shenyangjiang lockdownandrestaurantclosuresevidencefromlargescaledatainchina AT yuxiong lockdownandrestaurantclosuresevidencefromlargescaledatainchina |