We offer practical, case-based experiences on sustainability reporting in higher education institutions (HEIs), with a focus on the integration of sustainability activities into strategic planning and quality management. A proposed approach is based on the experience of the University of Split, Croatia, and the lessons learned from the SEA-EU University Alliance. In line with the Sustainable Development Goals (SDGs), our model emphasizes the active engagement of stakeholders and the continuous collection and review of sustainability data. In addition, we propose to automate the collection and dissemination of sustainability research findings through the implementation of a Current Research Information System (CRIS). Our case study provides a roadmap for improving sustainability performance and reporting. The experience of the University of Split (Croatia) could be helpful and generalizable to a number of universities with an intermediate level of maturity in sustainability management and reporting, trying to improve their university rankings.

This paper reviews the theoretical background and potential applications of Large Language Models (LLMs) in educational processes and academic research. Utilizing a novel digital ethnographic approach, we engaged in iterative research with OpenAI’s ChatGPT-4 and Google’s Gemini Ultra—two advanced commercial LLMs. The methodology treated LLMs as research participants, emphasizing the AI-guided perspectives and their envisioned roles in educational settings. Our findings identified the potential LLM roles in educational and research processes and we discussed the AI challenges, which included potential biases in decision-making and AI as a potential source of discrimination and conflict of interest. In addition to practical implications, we used the qualitative research results to advise on the relevant topics for future research.

In this paper, we analyze the scientific productivity and impact of selected public business schools in South East Europe (SEE) in the 2017-2021 period by using the scientific output indexed in the Elsevier Scopus reference database. The region’s most productive and influential authors, institutions, and publication outlets are identified in the field of business research. Empirical results are discussed from the viewpoints of two research questions related to regional business school research patterns and the research cooperation outcomes. Selected public business schools in the SEE region have been found to have a mixed record regarding research productivity and impact. International collaboration is valuable in increasing the research impact, while institutional collaboration seems more effective in raising impact than national one. Recommendations for business school administrators are identified and discussed.

There is minimal research concerning the role of custom-trained artificial intelligence (AI) tools in higher education, with a lack of research concerning the pedagogical qualities of an AI-based personal tutor. To fill this literature gap, we examined how a custom GPT personal tutor shapes key teaching and learning qualities. Using the mixed-methods approach, we aimed to demonstrate preliminary and exploratory empirical evidence concerning the contribution of custom-trained AI tutors to building up students’ competencies. Our research analyzed the subjective assessments of students related to the GPT tutor’s contribution to improving their competencies. Both the qualitative and quantitative empirical results confirmed the positive contribution. In addition, we triangulated the results to evaluate the potential of custom-trained AI chatbots in higher education, focusing on undergraduate business courses. However, the results of this study cannot be generalized to the entire student population of business schools, since the participation in the AI-assisted tutor program was voluntary, attracting only intrinsically motivated students.

This paper analyzes anti-corruption research and the body of knowledge produced by researchers in Southeast Europe (SEE). It compares it to the extant global anti-corruption literature. We consider all available scientific outputs from the SEE region, indexed by the Elsevier Scopus bibliometric database, and employ the Elsevier SciVal software solution to analyze the productivity and impact of the regional anti-corruption research. We also consider the influence of international cooperation on regional scientific productivity and its impact. The bibliometric comparison of the global and regional research and the authors’ qualitative assessment of these differences are performed. We also identify the implications and future research priorities.