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A fuzzy analytic hierarchy process-enhanced fuzzy geometric mean-fuzzy technique for order preference by similarity to ideal solution approach for suitable hotel recommendation amid the COVID-19 pandemic.
Toly Chen, Tin-Chih; Wu, Hsin-Chieh; Hsu, Keng-Wei.
Affiliation
  • Toly Chen TC; Department of Industrial Engineering and Management, National Yang Ming Chiao Tung University, Hsinchu City.
  • Wu HC; Department of Industrial Engineering and Management, National Yang Ming Chiao Tung University, Taichung City.
  • Hsu KW; Department of Industrial Engineering and Management, National Yang Ming Chiao Tung University, Hsinchu City.
Digit Health ; 8: 20552076221084457, 2022.
Article in En | MEDLINE | ID: mdl-35284086
ABSTRACT
Cities around the world have reopened from the lockdown caused by the COVID-19 pandemic, and more and more people are planning regional travel. Therefore, it is a practical problem to recommend suitable hotels to travelers amid the COVID-19 pandemic. However, it is also a challenging task since the critical factors that affect hotel selection amid the COVID-19 pandemic may be different from those usually considered. From this perspective, the fuzzy analytic hierarchy process-enhanced fuzzy geometric mean-fuzzy technique for order preference by similarity to ideal solution approach is proposed in this study for hotel recommendation. The proposed methodology not only considers the critical factors affecting hotel selection amid the COVID-19 pandemic, but also establishes a systematic mechanism, that is, enhanced fuzzy geometric mean, to simultaneously improve the accuracy and efficiency of the recommendation process. The fuzzy analytic hierarchy process-enhanced fuzzy geometric mean-fuzzy technique for order preference by similarity to ideal solution approach has been successfully applied to recommend suitable hotels to 10 travelers for regional trips amid the COVID-19 pandemic.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Guideline Language: En Journal: Digit Health Year: 2022 Type: Article

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Guideline Language: En Journal: Digit Health Year: 2022 Type: Article