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Multistate Models for the Recovery Process in the Covid-19 Context: An Empirical Study of Chinese Enterprises
The Covid-19 pandemic has severely affected enterprises worldwide. It is thus of practical significance to study the process of enterprise recovery from Covid-19. However, the research on the effects of relevant determinants of business recovery is limited. This article presents a multistate modelin...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Nature Singapore
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9109752/ http://dx.doi.org/10.1007/s13753-022-00414-5 |
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author | Yang, Lijiao Chen, Yu Jiang, Xinyu Tatano, Hirokazu |
author_facet | Yang, Lijiao Chen, Yu Jiang, Xinyu Tatano, Hirokazu |
author_sort | Yang, Lijiao |
collection | PubMed |
description | The Covid-19 pandemic has severely affected enterprises worldwide. It is thus of practical significance to study the process of enterprise recovery from Covid-19. However, the research on the effects of relevant determinants of business recovery is limited. This article presents a multistate modeling framework that considers the determinants, recovery time, and transition likelihood of Chinese enterprises by the state of those enterprises as a result of the pandemic (recovery state), with the help of an accelerated failure time model. Empirical data from 750 enterprises were used to evaluate the recovery process. The results indicate that the main problems facing non-manufacturing industries are supply shortages and order cancellations. With the increase of supplies and orders, the probability of transition between different recovery states gradually increases, and the recovery time of enterprises becomes shorter. For manufacturing industries, the factors that hinder recovery are more complex. The main problems are employee panic and order cancellations in the initial stage, employee shortages in the middle stage, and raw material shortages in the full recovery stage. This study can provide a reference for enterprise recovery in the current pandemic context and help policymakers and business managers take necessary measures to accelerate recovery. |
format | Online Article Text |
id | pubmed-9109752 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer Nature Singapore |
record_format | MEDLINE/PubMed |
spelling | pubmed-91097522022-05-17 Multistate Models for the Recovery Process in the Covid-19 Context: An Empirical Study of Chinese Enterprises Yang, Lijiao Chen, Yu Jiang, Xinyu Tatano, Hirokazu Int J Disaster Risk Sci Article The Covid-19 pandemic has severely affected enterprises worldwide. It is thus of practical significance to study the process of enterprise recovery from Covid-19. However, the research on the effects of relevant determinants of business recovery is limited. This article presents a multistate modeling framework that considers the determinants, recovery time, and transition likelihood of Chinese enterprises by the state of those enterprises as a result of the pandemic (recovery state), with the help of an accelerated failure time model. Empirical data from 750 enterprises were used to evaluate the recovery process. The results indicate that the main problems facing non-manufacturing industries are supply shortages and order cancellations. With the increase of supplies and orders, the probability of transition between different recovery states gradually increases, and the recovery time of enterprises becomes shorter. For manufacturing industries, the factors that hinder recovery are more complex. The main problems are employee panic and order cancellations in the initial stage, employee shortages in the middle stage, and raw material shortages in the full recovery stage. This study can provide a reference for enterprise recovery in the current pandemic context and help policymakers and business managers take necessary measures to accelerate recovery. Springer Nature Singapore 2022-05-16 2022 /pmc/articles/PMC9109752/ http://dx.doi.org/10.1007/s13753-022-00414-5 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Yang, Lijiao Chen, Yu Jiang, Xinyu Tatano, Hirokazu Multistate Models for the Recovery Process in the Covid-19 Context: An Empirical Study of Chinese Enterprises |
title | Multistate Models for the Recovery Process in the Covid-19 Context: An Empirical Study of Chinese Enterprises |
title_full | Multistate Models for the Recovery Process in the Covid-19 Context: An Empirical Study of Chinese Enterprises |
title_fullStr | Multistate Models for the Recovery Process in the Covid-19 Context: An Empirical Study of Chinese Enterprises |
title_full_unstemmed | Multistate Models for the Recovery Process in the Covid-19 Context: An Empirical Study of Chinese Enterprises |
title_short | Multistate Models for the Recovery Process in the Covid-19 Context: An Empirical Study of Chinese Enterprises |
title_sort | multistate models for the recovery process in the covid-19 context: an empirical study of chinese enterprises |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9109752/ http://dx.doi.org/10.1007/s13753-022-00414-5 |
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