Identifying effective measures to enhance the recovery of small and micro enterprises after multiple waves of COVID-19 – A case study from Dongguan, China

Abstract

The ability of a small and micro enterprise (SME) to recovery after a pandemic outbreak can directly affect national economic growth and sustainable development (Sustainable Development Goal 11). Thus, the current study quantitatively identifies, based on the spatial probit model, effective measures that enhance the performance and survival of SMEs after multiple waves of shocks induced by COVID-19. Additionally, this work explores the spatial correlation for post-pandemic recovery performance of businesses adopting a novel approach. Two field investigations were conducted in Dongguan City, in China, where questionnaires were released to 592 SMEs over a two-year period. The results obtained showed that the overall recovery performance of SMEs after the pandemic showed a positive spatial correlation, while this correlation varied at different local regions. More in detail, self-media marketing, borrowing money from family or friends, requesting bank loans and tax relief have been identified to be the key measures to effectively support the recovery and the increase chances for small businesses to remain operative after the pandemic. However, the success of these measures varies across businesses with different characteristics (owner's age and industry experience, primary market and business size, pre-pandemic financial condition). It is then suggested based on the results obtained that policy managers should formulate differentiated policies in terms of assistance measures for businesses targeting dissimilar characteristics as well as the needs of different regions, because those may have been impacted differently by the pandemic.

Publication DOI: https://doi.org/10.1016/j.ijdrr.2024.104427
Divisions: College of Engineering & Physical Sciences > School of Infrastructure and Sustainable Engineering > Civil Engineering
College of Engineering & Physical Sciences > School of Infrastructure and Sustainable Engineering
Funding Information: This research work is supported by the National Natural Science Foundation of China (No. 72304064 ), Guangdong Basic and Applied Basic Research Foundation (No. 2022A1515110339 ) and Guangdong Provincial Key Laboratory of Intelligent Disaster Prevention an
Additional Information: Copyright © 2024 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (https://creativecommons.org/licenses/by/4.0/).
Uncontrolled Keywords: Business recovery,Multiple waves of pandemics,SMEs,Spatial correlation,Spatial probit model,Geology,Geotechnical Engineering and Engineering Geology,Safety Research,SDG 13 - Climate Action,SDG 11 - Sustainable Cities and Communities
Publication ISSN: 2212-4209
Last Modified: 19 Dec 2024 08:22
Date Deposited: 18 Sep 2024 15:22
Full Text Link:
Related URLs: https://www.sci ... 212420924001894 (Publisher URL)
http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Article
Published Date: 2024-05
Published Online Date: 2024-03-22
Accepted Date: 2024-03-19
Authors: Li, Fan
Rubinato, Matteo (ORCID Profile 0000-0002-8446-4448)
Zhou, Tao

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