DOI: 10.35378/gujs.1772402 ISSN: 2147-1762

Service Quality Analysis of Cryptocurrency Exchanges: An Innovative Approach Integrating Quality Scale, Fermatean Fuzzy Multi-criteria Decision Making and Chatbots

Müberra Terzi Kumandaş, Barış Özkan
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The development of technology has given rise to various investment instruments, such as cryptocurrencies. As interest in cryptocurrencies has increased, cryptocurrency exchanges have become critical platforms facilitating transactions between digital assets and fiat currencies. Since exchanges differ in service quality, identifying those offering superior performance has become an important issue for investors. This study proposes a four-stage approach to evaluate cryptocurrency exchanges based on service quality. First stage, 20 criteria derived from the electronic service quality (Es-Qual) scale, and five major cryptocurrency exchanges are identified. Criteria weights are determined using Fermatean fuzzy numbers (FFNs). In the second stage, expert evaluations are aggregated, and the alternatives are ranked using the Fermatean Fuzzy Technique for Order Preference by Similarity to the Ideal Solution (FF-TOPSIS) method. Third stage, evaluations are generated using different versions of Artificial Intelligence (AI)-based chatbots to examine their analytical consistency within the predefined conceptual framework. In the fourth stage, the level of agreement between expert-based and AI-assisted evaluations is analyzed comparatively, and a sensitivity analysis is conducted to test ranking robustness. The findings indicate that System Availability and Privacy are the most influential criteria in the weighting process. In the ranking, Binance is ranked first, while Bitstamp is ranked last. The sensitivity analysis confirms the stability of the top-ranked alternative under varying weight scenarios. Furthermore, AI-generated evaluations exhibit structural similarity with expert-based results under controlled conditions, suggesting that AI-based tools may serve as supportive analytical instruments in multi-criteria decision-making (MCDM) contexts rather than as replacements for expert judgment.

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