The operational performance of fashion companies in the context of the coronavirus pandemic: static and dynamic analyses

Author:

Huang HeORCID,Huang JingORCID,Zhong Yanfeng

Abstract

PurposeThis study clarifies the operational performance of fashion companies during the coronavirus pandemic. Meanwhile, improvement strategies have been provided in the post-pandemic era.Design/methodology/approachThe static and dynamic perspectives were combined to comprehensively analyze the operational performance of fashion companies before, during and after the COVID-19 outbreak. A comparative analysis among five representative countries was conducted to achieve global conclusions. Additionally, data envelopment analysis (DEA) theory and various DEA models were employed for the analysis.FindingsThe fashion industry has not achieved overall effectiveness. American companies have the best operational performance, followed by European and Chinese companies. In contrast, the impact of the pandemic on American companies was severe, whereas Chinese and European companies showed operational resilience. In addition, the pandemic had a devastating influence on the global fashion industry. This resulted in a decline in total factor productivity, and the main reason was technological regress. Furthermore, labor redundancy is a critical issue for the fashion industry in the post-pandemic era, even if it shows a decrease because of the pandemic.Originality/valueThe existing theory on the fashion industry during the pandemic was improved by expanding the time and geographical dimensions and integrating the advantages of various DEA models. Scientific improvement strategies were presented in the post-pandemic era with application value.

Publisher

Emerald

Subject

Marketing,Business and International Management

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