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A calibrated piecewise-linear FGM approach for travel destination recommendation during the COVID-19 pandemic.
Chen, Toly; Wang, Yu-Cheng.
  • Chen T; Department of Industrial Engineering and Management. National Yang Ming Chiao Tung University, Hsinchu, Taiwan.
  • Wang YC; Department of Aeronautical Engineering, Chaoyang University of Technology, Taichung City, Taiwan.
Appl Soft Comput ; 109: 107535, 2021 Sep.
Article in English | MEDLINE | ID: covidwho-1252469
ABSTRACT
After months of lockdown due to the COVID-19 pandemic, more people are planning regional trips because overseas travel is still not feasible. However, choosing a suitable travel destination during the COVID-19 pandemic is challenging because the factors critical to the selection process are very different from those usually considered. Furthermore, without sufficient literature or data for reference, existing methods based on psychological analyses or mining past experiences may not be applicable. Consequently, a fuzzy multi-criteria decision-making method - the calibrated piecewise-linear fuzzy geometric mean (FGM) approach - is proposed in this study for travel destination recommendation during the COVID-19 pandemic. The contribution of this research is twofold. First, the critical factors that affect the selection of a suitable travel destination during the COVID-19 pandemic are discussed. Second, the accuracy and efficiency using existing fuzzy analytic hierarchy process (FAHP) methods have been enhanced. The calibrated piecewise-linear FGM approach has been successfully applied to recommend suitable travel destinations to fifteen travelers for regional trips in Taiwan during the COVID-19 pandemic.
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Qualitative research Language: English Journal: Appl Soft Comput Year: 2021 Document Type: Article Affiliation country: J.asoc.2021.107535

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Qualitative research Language: English Journal: Appl Soft Comput Year: 2021 Document Type: Article Affiliation country: J.asoc.2021.107535