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Unraveling the Non-Linear Impact of Multiple Pandemics on Small and Micro Enterprises: A Longitudinal Study of Operational Challenges

  • Fan Li
  • , Matteo Rubinato*
  • , Kai Wu
  • , Lin Wang
  • , Songdong Shao
  • *Corresponding author for this work
  • Dongguan University of Technology
  • Chongqing University
  • Trine University

Research output: Contribution to journalArticlepeer-review

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Abstract

Understanding the dynamic impacts of multiple Covid-19 pandemic waves on operational challenges is crucial for mall and micro enterprises (SMEs) to enhance resilience and reduce vulnerability. This study employs a Threshold Vector Autoregression (TVAR) model to analyze operational challenges faced by SMEs during the COVID-19 pandemic, based on time-series data collected from 592 SMEs in Dongguan, China, between June 2021 to December 2022. The findings reveal that COVID-19 pandemic growth has nonlinear impacts on customer loss, business interruptions, and supply chain issues, while its influence on cost increases is linear. These effects vary by lag periods and risk regimes. Customer loss and supply chain challenges show greater fluctuations in high-risk regimes but moderate responses in low-risk regimes. Conversely, business interruptions exhibit milder fluctuations in high-risk regimes and pronounced shifts in low-risk ones. This study offers a scientific basis for SMEs owners and policymakers to design adaptive, stage-specific measures. Insights from these findings can strengthen SMEs’ crisis management strategies, contributing to the stability and sustainable development of the economy and society.
Original languageEnglish
Article number105737
Number of pages21
JournalInternational Journal of Disaster Risk Reduction
Volume128
Early online date30 Jul 2025
DOIs
Publication statusPublished - 1 Oct 2025

Bibliographical note

Copyright © 2025 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license
(https://creativecommons.org/licenses/by/4.0/ ).

Data Access Statement

Data will be made available on request.

Funding

This research work is supported by the National Natural Science Foundation of China 933 (No. 72304064), Guangdong Basic and Applied Basic Research Foundation (No. 934 2022A1515110339) and Guangdong Provincial Key Laboratory of Intelligent Disaster 935 Prevention and Emergency Technologies for Urban Lifeline Engineering (2022) (Grant 936 No. 2022B1212010016).

FundersFunder number
National Natural Science Foundation of China72304064
Guangdong Basic and Applied Basic Research Foundation2022A1515110339
Guangdong Provincial Key Laboratory of Intelligent Disaster Prevention and Emergency Technologies for urban Lifeline Engineering (2022)2022B1212010016

    Keywords

    • COVID-19 pandemic shock
    • Nonlinear impact
    • Operational challenges
    • Small and micro enterprises (SMEs)
    • Threshold vector autoregression (TVAR) model

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