Selecting the Low-Carbon Tourism Destination: Based on Pythagorean Fuzzy Taxonomy Method

• Main Authors: Guiwu Wei, Yanxin Tang, Mengwei Zhao, Rui Lin, Jiang Wu
• Format: Article
• Language: English
• Published: MDPI AG 2020-05-01
• Series: Mathematics
• Subjects: multiple attribute group decision making (MAGDM); Pythagorean fuzzy sets (PFSs); information entropy; Taxonomy method; low-carbon tourist destination selection
• Online Access: https://www.mdpi.com/2227-7390/8/5/832

Low-carbon tourism plays the increasingly significant role in carbon emission reduction and natural environmental protection. The choice of low-carbon tourist destination (LCTD) often involves the multiple attributes or criteria and can be regarded as the corresponding multiple attribute group decision making (MAGDM) issues. Since the Pythagorean fuzzy sets (PFSs) could well depict uncertain information or fuzzy information and cope with the LCTD selection, thus this essay develops a framework to tackle such MAGDM issues under the Pythagorean fuzzy environment. In this essay, due to few methods can compare with different alternatives along with their advantages from designed attributes, therefore, to overcome this challenge, the taxonomy method is utilized to integrate with PFSs. What’s more, the entropy method is also utilized to determine the attribute weights. Eventually, an application related to LCTD selection and some comparative analysis have been given to demonstrate the superiority of the designed method. The results illustrate that the designed framework is useful for identifying optimal tourist destination among the potential tourist destinations.