## 2 Research on Evaluation and Analysis of Criteria for GenAI Tools Based on Multi-Criteria Methods  
With the proliferation of GenAI tools, selecting the right one suitable for academic research can be a challenging task. It is important to evaluate these tools based on specific criteria to ensure they meet the needs of researchers and contribute effectively to the research process. In the specialized literature, this problem has been approached from several points of view and has been solved by various methods. The papers [6; 7; 8; 9] approach the topic from a conceptual or descriptive perspective, outlining general criteria for selecting or adopting the AI tools for academic research without employing a multi-criteria decision-making framework. These works do not propose weighting methods for establishing relationships between criteria. The paper [8] outlines the general criteria for selecting artificial intelligence tools, with a particular focus on those used in publishing. They emphasize that researchers should consider ethical standards, regulatory compliance, and societal impact when choosing AI tools. The paper [6] provides an overview of AI tools applicable to academic research, offering guidance to educators on effectively integrating these technologies. The paper [7] examines the role of AI in research, identifying two major limitations: the exclusion of commercial AI tools and the narrow focus on those designed for direct research queries. The study highlights the need to explore how paid AI tools and multi-system integrations can enhance research outcomes. Future research should assess the effectiveness of commercial AI, the impact of combining multiple AI tools, and the variability of AI-generated responses. These findings underscore the importance of critically selecting and evaluating AI tools for academic research. The paper [9] is about the adoption of ChatGPT tool for education. The factors for adoption of ChatGPT include hedonic motivation, usability, perceived benefits, system responsiveness and relative advantage, social influence, facilitating conditions, privacy, and security. This paper does not use a weighting method. Comparative Analysis of the Use of Multi-Criteria Decision-Making (MCDM) Methods in the Evaluation of GenAI Tools  
A significant number of articles utilize the Analytic Hierarchy Process (AHP) to assign weights to various criteria. For example, studies such as [10; 11; 12; 13; 14; 15] apply AHP (sometimes combined with Delphi) to assess tools based on qualitative, ethical, or user-experience criteria. However, these studies do not explore causal or dependency relationships between the criteria. Although the BWM or SWARA methods, which are more recent methods, have a much smaller number of pairwise comparisons, the AHP method is preferred. The chapter [10] evaluates AI tools in universities by first reviewing relevant literature and then applying Fuzzy Multi-Criteria Decision-Making to prioritize them. Five key criteria: perceived ease of use, perceived usefulness, personalization, interaction, and trust, were weighted based on expert opinions and literature analysis. This study applies an intuitionistic fuzzy approach to enhance evaluation accuracy and prioritize AI tools effectively. This paper uses an AHP prioritization method but does not establish causal relationships between criteria. The paper [11] examines whether restrictions or legislation should control GenAI, using ChatGPT as a case study. A systematic literature review and Analytic Hierarchy Process (AHP) were used to analyze 10 key ethical concerns, with expert panel evaluations. The criteria considered are copyright, legal, and compliance issues; privacy and confidentiality; academic integrity; incorrect citation practices; and safety/security concerns. The analysis showed that restriction was favored slightly over legislation. This paper onlyconsiders criteria related to restrictions or legislation that should control GenAI tools. No relationships are established between criteria.