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Application of Mathematical Models to Assess the Impact of the COVID-19 Pandemic on Logistics Businesses and Recovery Solutions for Sustainable Development

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  • Han Khanh Nguyen

    (Faculty of Economics, Thu Dau Mot University, Number 6, Tran Van On Street, Phu Hoa Ward, Thu Dau Mot 590000, Vietnam)

Abstract

The logistics industry can be considered as the economic lifeline of each country because of its role in connecting production and business activities of enterprises and promoting socio-economic development between regions and countries. However, the COVID-19 pandemic, which began at the end of 2019, has seriously affected the global supply chain, causing heavy impacts on the logistics service sector. In this study, the authors used the Malmquist productivity index to assess the impact of the pandemic on logistics businesses in Vietnam. Moreover, the authors used a super-slack-based model to find strategic alliance partners for enterprises. The authors also used the Grey forecasting model to forecast the business situation for enterprises during the period 2021–2024, in order to provide the leaders of these enterprises with a complete picture of their partners as a solid basis for making decisions to implement alliances that will help logistics enterprises in Vietnam to develop sustainably. The results have found that the alliance between LO 7 and LO 10 is the most optimal, as this alliance can exploit freight in the opposite direction and reduce logistics costs, creating better competitiveness for businesses.

Suggested Citation

  • Han Khanh Nguyen, 2021. "Application of Mathematical Models to Assess the Impact of the COVID-19 Pandemic on Logistics Businesses and Recovery Solutions for Sustainable Development," Mathematics, MDPI, vol. 9(16), pages 1-21, August.
  • Handle: RePEc:gam:jmathe:v:9:y:2021:i:16:p:1977-:d:616994
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    References listed on IDEAS

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    1. Guofeng Wang & Ziyu Qian & Xiangzheng Deng, 2020. "Analysis of Environmental Policy and the Performance of Sustainable Agricultural Development in China," Sustainability, MDPI, vol. 12(24), pages 1-16, December.
    2. Guo-Feng Fan & An Wang & Wei-Chiang Hong, 2018. "Combining Grey Model and Self-Adapting Intelligent Grey Model with Genetic Algorithm and Annual Share Changes in Natural Gas Demand Forecasting," Energies, MDPI, vol. 11(7), pages 1-21, June.
    3. Chia-Nan Wang & Han-Khanh Nguyen, 2017. "Enhancing Urban Development Quality Based on the Results of Appraising Efficient Performance of Investors—A Case Study in Vietnam," Sustainability, MDPI, vol. 9(8), pages 1-22, August.
    4. Hedayet Chowdhury & Walter Wodchis & Audrey Laporte, 2011. "Efficiency and technological change in health care services in Ontario," International Journal of Productivity and Performance Management, Emerald Group Publishing Limited, vol. 60(7), pages 721-745, September.
    5. Roman Lacko & Zuzana Hajduová & Marcin Zawada, 2021. "The Efficiency of Circular Economies: A Comparison of Visegrád Group Countries," Energies, MDPI, vol. 14(6), pages 1-13, March.
    6. Małgorzata Kokocińska & Marcin Nowak & Paweł Łopatka, 2020. "Measuring the Efficiency of Economic Growth towards Sustainable Growth with Grey System Theory," Sustainability, MDPI, vol. 12(23), pages 1-17, December.
    7. Tien-Muoi Le & Chia-Nan Wang & Han-Khanh Nguyen, 2020. "Using the optimization algorithm to evaluate and predict the business performance of logistics companies–a case study in Vietnam," Applied Economics, Taylor & Francis Journals, vol. 52(38), pages 4196-4212, July.
    8. Isa Ebtehaj & Keyvan Soltani & Afshin Amiri & Marzban Faramarzi & Chandra A. Madramootoo & Hossein Bonakdari, 2021. "Prognostication of Shortwave Radiation Using an Improved No-Tuned Fast Machine Learning," Sustainability, MDPI, vol. 13(14), pages 1-23, July.
    9. Zoran Gligorić & Miloš Gligorić & Dževdet Halilović & Čedomir Beljić & Katarina Urošević, 2020. "Hybrid Stochastic-Grey Model to Forecast the Behavior of Metal Price in the Mining Industry," Sustainability, MDPI, vol. 12(16), pages 1-21, August.
    10. Yahong Liu & Hailian Sun & Lei Shi & Huimin Wang & Zhai Xiu & Xiao Qiu & Hong Chang & Yu Xie & Yang Wang & Chengjie Wang, 2021. "Spatial-Temporal Changes and Driving Factors of Land-Use Eco-Efficiency Incorporating Ecosystem Services in China," Sustainability, MDPI, vol. 13(2), pages 1-15, January.
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