## 7 Conclusions  
The integration of Artificial Intelligence (AI) tools into academic research has revolutionized the way scientific researchers approach research subjects. These tools enhance productivity, streamline data analysis, and facilitate the discovery of new insights. Recent research highlights the transformative potential of GenAI tools in academic research, of fering benefits such as increased efficiency in literature reviews, writing, data analysis, and peer review processes. One major drawback of using generative AI tools in academic research is the risk of inaccuracies, biases, and lack of transparency in source selection, which can compromise the reliability and credibility of researchers' work. The paper presents an analysis of the criteria used in the selection and adoption of GenAI tools for academic research. The choice of the DEMATEL method to analyze the influences between criteria and the calculation of the criteria weights is justified in comparison with the commonly used weighting methods AHP, ANP, and BWM. An improved group DEMATEL method, called IDEMATEL, is then proposed to ensure that the powers of the normalized direct relation matrix converge, which guarantees the computation of the total influence matrix under any circumstances. The IDEMATEL method is applied to analyze a set of criteria involved in the selection of GenAI tools for academic research, based on evaluations made by a group of experts. The results highlight that Functionality and Objectives should be prioritized, as they are the main drivers of GenAI tool selection. Additionally, Cost and Value, as well as Data Security, are considerations that can directly impact the decision-making process. Reputation and Community Support play secondary roles, primarily depending on the tool's performance and user experience. These insights can help researchers and institutions focus their evaluation efforts and resources on the most influential factors, ultimately enhancing research productivity and quality. DEMATEL helps to understand which criteria are the key drivers (causes) and which are more dependent (effects). By identifying the \"cause\" criteria (ex: functionality, cost, etc. ), DEMATEL enables decision-makers to focus resources on the most influential factors. While relying on expert judgements, the process of pair-wise comparisons and the mathematical formulation of DEMATEL helps reduce the subjectivity and allows for a more objective analysis than simply brainstorming or intuition. The results of this study have important implications for both individual researchers and institutional decision-makers. By clarifying the causal relationships among selection criteria, institutions can develop more effective procurement policies and support structures, ensuring that investments in GenAI tools yield the greatest impact. The causal analysis also suggests that improvements in core functionalities and data security can have positive ripple effects on reputation and community support, contributing to a more sustainable and trusted research ecosystem. While this study provides a robust framework, several limitations should be acknowledged. The analysis was based on the judgments of a small group of experts, which may affect the generalizability of the results. The selected criteria and their assessments, though grounded in the literature and expert opinions, may not capture all relevant factors or reflect the diversity of academic disciplines and institutional contexts. Additionally, the evaluation focused on a specific set of GenAI tools and may not fully represent the rapidly evolving AI landscape. To build on these findings, future research should explore the application of IDEMATEL in diverse academic domains and organizational settings, as the relative importance of criteria may vary across fields such as the social sciences, natural sciences, or humanities. Integrating IDEMATEL with fuzzy logic or other uncertainty-handling techniques could further enhance its ability to manage ambiguous or imprecise expert judgments.