Selecting the Low-Carbon Tourism Destination: Based on Pythagorean Fuzzy Taxonomy Method
School of Business, Sichuan Normal University, Chengdu 610101, China
Department of Finance, School of Economics and Business Administration, Chongqing University, Chongqing 400044, China
School of Economics and Management, Chongqing University of Arts and Sciences, Chongqing 402160, China
School of Statistics, Southwestern University of Finance and Economics, Chengdu 611130, China
Author to whom correspondence should be addressed.
Mathematics 2020, 8(5), 832; https://doi.org/10.3390/math8050832
Received: 22 April 2020 / Revised: 15 May 2020 / Accepted: 18 May 2020 / Published: 21 May 2020
(This article belongs to the Special Issue Applications of Mathematical Methods and Fuzzy Techniques in Decision Making)
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.