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Assessment of Vietnam Tourism Recovery Strategies after COVID-19 Using Multi-Criteria Decision-Making Approach

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  • Wu-Chung Lin

    (Tourism Management Department, Business Intelligence School, National Kaohsiung University of Science and Technology, Kaohsiung 811213, Taiwan)

  • Chihkang Kenny Wu

    (Tourism Management Department, Business Intelligence School, National Kaohsiung University of Science and Technology, Kaohsiung 811213, Taiwan)

  • Thi Kim Trang Le

    (Tourism Management Department, Business Intelligence School, National Kaohsiung University of Science and Technology, Kaohsiung 811213, Taiwan)

  • Ngoc Anh Nguyen

    (Tourism Management Department, Business Intelligence School, National Kaohsiung University of Science and Technology, Kaohsiung 811213, Taiwan)

Abstract

Tourism is the economic sector most heavily influenced by COVID-19, and it has suffered unprecedented losses. The competitiveness and resilience of the tourism industry have recently become a topic of great concern for global stakeholders. A series of ambitious recovery strategies have been announced by countries to rebuild the tourism industry, that aim to make “smokeless industry” more resilient and sustainable. The objective of this study is to evaluate and rank the effectiveness of nine recovery strategies in the post-COVID-19 period for Vietnam’s tourism industry. A combined model of the Best–Worst Method (BWM) and the Group Best Worst Method (GBWM), an efficient tool using the multi-criteria decision-making (MCDM) approach, is used to rank the tourism solutions. The assessment process is carried out by six stakeholder groups considered decision makers, including tourism operators, enterprises, scholars, employees, residents, and tourists. In the context of Vietnam, the most influential tourism recovery strategy is using innovative tourism business models (ST2), which is a solid step forward in utilizing potential resources, meeting current tourism needs, and adapting to natural changes. The model results reflect that the tourism model’s restructuring is necessary to provide new types of experiences and entertainment suitable for the new tourism context. The findings illustrate that the priority of strategies depends on the perception of decision-makers, levels of involvement in the tourism industry, and local conditions. The study has contributed a theoretical framework for tourism recovery solutions and decision support in the post-pandemic stage. The model can be applied to other countries worldwide in improving tourism performance or assisting in decision-making for similar issues.

Suggested Citation

  • Wu-Chung Lin & Chihkang Kenny Wu & Thi Kim Trang Le & Ngoc Anh Nguyen, 2023. "Assessment of Vietnam Tourism Recovery Strategies after COVID-19 Using Multi-Criteria Decision-Making Approach," Sustainability, MDPI, vol. 15(13), pages 1-22, June.
  • Handle: RePEc:gam:jsusta:v:15:y:2023:i:13:p:10047-:d:1178875
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    References listed on IDEAS

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    1. Nguyen Thi Thanh Van & Vasiliki Vrana & Nguyen Thien Duy & Doan Xuan Huy Minh & Pham Tien Dzung & Subhra R. Mondal & Subhankar Das, 2020. "The Role of Human–Machine Interactive Devices for Post-COVID-19 Innovative Sustainable Tourism in Ho Chi Minh City, Vietnam," Sustainability, MDPI, vol. 12(22), pages 1-30, November.
    2. Judy Alyssa T. Absalon & Dorwyn Kate C. Blasabas & Esehl May A. Capinpin & Maryanne D. Daclan & Kafferine D. Yamagishi & Lanndon A. Ocampo, 2022. "Impact assessment of farm tourism sites using a hybrid MADM-based composite sustainability index," Current Issues in Tourism, Taylor & Francis Journals, vol. 25(13), pages 2063-2085, July.
    3. Sigala, Marianna, 2020. "Tourism and COVID-19: Impacts and implications for advancing and resetting industry and research," Journal of Business Research, Elsevier, vol. 117(C), pages 312-321.
    4. Rezaei, Jafar, 2015. "Best-worst multi-criteria decision-making method," Omega, Elsevier, vol. 53(C), pages 49-57.
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    Cited by:

    1. Govindan, Kannan, 2025. "Analyzing the dynamic capabilities of emerging technologies for industrial emergency situations," International Journal of Production Economics, Elsevier, vol. 281(C).

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