A novel approach based on similarity measure for the multiple attribute group decision-making problem in selecting a sustainable cryptocurrency

【Author】 Yin, Wei; Zhang, Mengyuan; Zhu, Zheyi; Zhang, Erhao

【Source】HELIYON

【影响因子】3.776

【Abstract】Environmental impact and sustainability challenges in the cryptocurrencies has become increasingly examined in the literature. However, studies of the multiple attribute group decision making (MAGDM) method for major selection of cryptocurrencies in advancing sustainability are still at an early stage. In particular, research on the fuzzy-MAGDM method in the evaluation of sustainability in cryptocurrencies is scarce. This paper adds contributions by developing a novel MAGDM approach to evaluate the sustainability development of major cryptocurrencies. It pro-poses a similarity measure for interval-valued Pythagorean fuzzy numbers (IVPFNs) based on whitenisation weight function and membership function in grey systems theory for IVPFNs. It further developed a novel generalised interval-valued Pythagorean fuzzy weighted grey similarity (GIPFWGS) measure approach to provide a more rigorous evaluation in complex decision marking problem with embedding ideal solution and membership degree. It also conducts a sustainability evaluation model of major cryptocurrencies as a numerical application and per-forms a robustness assessment with different variations of the expert's weight to test how different values of parameter theta can affect the ranking results of alternatives. The results suggest that Stellar is the most sustainable cryptocurrency, while Bitcoin with its intensive energy con-sumption, high mining cost and high computing power provides the least effective support for its sustainable development. A comparative analysis with the average value method and Euclidean distance method was performed to validate the reliability of the proposed decision-making model and provides evidence that the GIPFWGS has better fault tolerance.

【Keywords】Cryptocurrency; MAGDM; Sustainability evaluation

【发表时间】2023 MAY

【收录时间】2023-07-07

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