IDEAS home Printed from https://ideas.repec.org/a/gam/jjrfmx/v14y2021i10p465-d649005.html
   My bibliography  Save this article

Assess the Impact of the COVID-19 Pandemic and Propose Solutions for Sustainable Development for Textile Enterprises: An Integrated Data Envelopment Analysis-Binary Logistic Model Approach

Author

Listed:
  • Han-Khanh Nguyen

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

  • Mai-Nam Vu

    (Graduate Training Institute, Thu Dau Mot University, Number 6, Tran Van On Street, Phu Hoa Ward, Thu Dau Mot 590000, Vietnam)

Abstract

The COVID-19 pandemic impacted many socio-economic areas of countries around the world. It has made the production and business situations of enterprises face substantial difficulties. In this study, the authors used data envelopment analysis (DEA) models to assess the impact of the COVID-19 pandemic on Vietnam’s textile and garment enterprises. The authors have used the binary logistic model to determine the factors affecting employees’ decision to change jobs in the textile industry. The research results showed that the COVID-19 pandemic greatly affected the business performance of the textile and garment enterprises in Vietnam. Moreover, the results helped identify the factors affecting employee turnover and proposed solutions to help businesses stabilize their personnel situation and develop sustainable businesses in the post-COVID-19 era.

Suggested Citation

  • Han-Khanh Nguyen & Mai-Nam Vu, 2021. "Assess the Impact of the COVID-19 Pandemic and Propose Solutions for Sustainable Development for Textile Enterprises: An Integrated Data Envelopment Analysis-Binary Logistic Model Approach," JRFM, MDPI, vol. 14(10), pages 1-23, October.
    • Handle: RePEc:gam:jjrfmx:v:14:y:2021:i:10:p:465-:d:649005
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1911-8074/14/10/465/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1911-8074/14/10/465/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Yu, Ming-Miin & Lin, Chung-I & Chen, Kuan-Chen & Chen, Li-Hsueh, 2021. "Measuring Taiwanese bank performance: A two-system dynamic network data envelopment analysis approach," Omega, Elsevier, vol. 98(C).
    2. 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.
    3. Lin, Tzu-Yu & Chiu, Sheng-Hsiung, 2013. "Using independent component analysis and network DEA to improve bank performance evaluation," Economic Modelling, Elsevier, vol. 32(C), pages 608-616.
    4. Tone, Kaoru, 2001. "A slacks-based measure of efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 130(3), pages 498-509, May.
    5. Cristian Negrutiu & Cristinel Vasiliu & Calcedonia Enache, 2020. "Sustainable Entrepreneurship in the Transport and Retail Supply Chain Sector," JRFM, MDPI, vol. 13(11), pages 1-12, November.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Chiang Kao & Yuan-Ying Wang & Tsai-Chi Ho & Yu-Shian Chen & Ping-Chieh Chen, 2022. "The Impact Of Covid-19 On The Productivity Of Large Companies In Taiwan," Economy & Business Journal, International Scientific Publications, Bulgaria, vol. 16(1), pages 30-40.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Chen, Kuan-Chen & Lin, Sun-Yuan & Yu, Ming-Miin, 2022. "Exploring the efficiency of hospital and pharmacy utilizations in Taiwan: An application of dynamic network data envelopment analysis," Socio-Economic Planning Sciences, Elsevier, vol. 84(C).
    2. Yu‐Chuan Chen & Tai‐Yu Lin & Yung‐ho Chiu & Ching‐I Yang, 2024. "An exploration of operational efficiency, market efficiency, and sustainable development in the banking industry," Corporate Social Responsibility and Environmental Management, John Wiley & Sons, vol. 31(5), pages 4819-4848, September.
    3. Wu, Yueh-Cheng & Wei Kiong Ting, Irene & Lu, Wen-Min & Nourani, Mohammad & Kweh, Qian Long, 2016. "The impact of earnings management on the performance of ASEAN banks," Economic Modelling, Elsevier, vol. 53(C), pages 156-165.
    4. Mohammad Nourani & Qian Long Kweh & Irene Wei Kiong Ting & Wen-Min Lu & Anna Strutt, 2022. "Evaluating traditional, dynamic and network business models: an efficiency-based study of Chinese insurance companies," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 47(4), pages 905-943, October.
    5. Wen‐Min Lu & Qian Long Kweh & Irene Wei Kiong Ting & Chunya Ren, 2023. "How does stakeholder engagement through environmental, social, and governance affect eco‐efficiency and profitability efficiency? Zooming into Apple Inc.'s counterparts," Business Strategy and the Environment, Wiley Blackwell, vol. 32(1), pages 587-601, January.
    6. Wen-Min Lu & Qian Long Kweh & Chung-Wei Wang, 2021. "Integration and application of rough sets and data envelopment analysis for assessments of the investment trusts industry," Annals of Operations Research, Springer, vol. 296(1), pages 163-194, January.
    7. Franz R. Hahn, 2007. "Determinants of Bank Efficiency in Europe. Assessing Bank Performance Across Markets," WIFO Studies, WIFO, number 31499, April.
    8. Alperovych, Yan & Hübner, Georges & Lobet, Fabrice, 2015. "How does governmental versus private venture capital backing affect a firm's efficiency? Evidence from Belgium," Journal of Business Venturing, Elsevier, vol. 30(4), pages 508-525.
    9. Chen, Ya & Pan, Yongbin & Liu, Haoxiang & Wu, Huaqing & Deng, Guangwei, 2023. "Efficiency analysis of Chinese universities with shared inputs: An aggregated two-stage network DEA approach," Socio-Economic Planning Sciences, Elsevier, vol. 90(C).
    10. Kristiaan Kerstens & Jafar Sadeghi & Ignace Van de Woestyne, 2020. "Plant capacity notions in a non-parametric framework: a brief review and new graph or non-oriented plant capacities," Annals of Operations Research, Springer, vol. 288(2), pages 837-860, May.
    11. Ashrafi, Ali & Seow, Hsin-Vonn & Lee, Lai Soon & Lee, Chew Ging, 2013. "The efficiency of the hotel industry in Singapore," Tourism Management, Elsevier, vol. 37(C), pages 31-34.
    12. Juan Aparicio & Jesus T. Pastor & Jose L. Sainz-Pardo & Fernando Vidal, 2020. "Estimating and decomposing overall inefficiency by determining the least distance to the strongly efficient frontier in data envelopment analysis," Operational Research, Springer, vol. 20(2), pages 747-770, June.
    13. Qin, Quande & Li, Xin & Li, Li & Zhen, Wei & Wei, Yi-Ming, 2017. "Air emissions perspective on energy efficiency: An empirical analysis of China’s coastal areas," Applied Energy, Elsevier, vol. 185(P1), pages 604-614.
    14. Atris, Amani Mohammed & Goto, Mika, 2019. "Vertical structure and efficiency assessment of the US oil and gas companies," Resources Policy, Elsevier, vol. 63(C), pages 1-1.
    15. Chen, Yufeng & Ni, Liangfu & Liu, Kelong, 2021. "Does China's new energy vehicle industry innovate efficiently? A three-stage dynamic network slacks-based measure approach," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
    16. Mohammad Nourani & Qian Long Kweh & Evelyn Shyamala Devadason & V.G.R. Chandran, 2020. "A decomposition analysis of managerial efficiency for the insurance companies: A data envelopment analysis approach," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 41(6), pages 885-901, September.
    17. Honma, Satoshi, 2012. "Environmental and economic efficiencies in the Asia-Pacific region," MPRA Paper 43361, University Library of Munich, Germany.
    18. Bao Jiang & Enxin Chi & Jian Li, 2022. "Uncertain Data Envelopment Analysis for Cross Efficiency Evaluation with Imprecise Data," Mathematics, MDPI, vol. 10(13), pages 1-9, June.
    19. Jia Li & Yahong Zheng & Bing Liu & Yanyi Chen & Zhihang Zhong & Chenyu Dong & Chaoqun Wang, 2024. "The Synergistic Relationship between Low-Carbon Development of Road Freight Transport and Its Economic Efficiency—A Case Study of Wuhan, China," Sustainability, MDPI, vol. 16(7), pages 1-22, March.
    20. Yongqi Feng & Haolin Zhang & Yung-ho Chiu & Tzu-Han Chang, 2021. "Innovation efficiency and the impact of the institutional quality: a cross-country analysis using the two-stage meta-frontier dynamic network DEA model," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(4), pages 3091-3129, April.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jjrfmx:v:14:y:2021:i:10:p:465-:d:649005. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.