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Analyzing the impact of COVID-19 vaccination requirements on travelers' selection of hotels using a fuzzy multi-criteria decision-making approach.
Wang, Yu-Cheng; Chen, Tin-Chih Toly.
  • Wang YC; Department of Aeronautical Engineering, Chaoyang University of Technology, Taichung City, Taiwan.
  • Chen TT; Department of Industrial Engineering and Management, National Yang Ming Chiao Tung University, 1001, University Road, Hsinchu, Taiwan.
Healthc Anal (N Y) ; 2: 100064, 2022 Nov.
Article in English | MEDLINE | ID: covidwho-2178974
ABSTRACT
In the later stages of the COVID-19 pandemic, hotels are taking various measures to balance pandemic prevention and business operations. Some hotels require travelers to be fully vaccinated prior to check-in, while others do not. In the latter type of hotels, fully vaccinated travelers may encounter others who are not vaccinated. All of these have created constraints for travelers to choose suitable hotel accommodation during this time. To address this issue, a fuzzy multi-criteria decision-making approach is proposed in this study to help traveler choose suitable hotel accommodation. In the proposed methodology, firstly, hotels are divided into two types considering their requirements for COVID-19 vaccination. Travelers are then asked to list the key factors to consider when choosing between these two types of hotels. To derive the priorities of these key factors, the proportionally calibrated fuzzy geometric mean (pcFGM) method is proposed. Subsequently, the fuzzy VIsekriterijumskoKOmpromisnoRangiranje (fuzzy VIKOR) method is applied to evaluate and compare the overall performances of different types of hotels for recommendations to travelers. The applicability of the proposed methodology is illustrated by a real case study. According to the experimental results, most hotels did not request travelers to be full vaccinated. Nevertheless, the hotels recommended to travelers covered both hotel types.
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Experimental Studies Topics: Vaccines Language: English Journal: Healthc Anal (N Y) Year: 2022 Document Type: Article Affiliation country: J.health.2022.100064

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Experimental Studies Topics: Vaccines Language: English Journal: Healthc Anal (N Y) Year: 2022 Document Type: Article Affiliation country: J.health.2022.100064