Sustainable protein consumption is a key element in the transition toward more environmentally responsible food systems. Poultry, due to its relatively low carbon footprint and favorable health profile, holds significant potential to become an important component of the so-called “protein transition.” The aim of this article is to identify cognitive factors influencing consumer purchasing decisions regarding poultry and to formulate recommendations for marketing communication strategies that position poultry as a choice aligned with sustainability goals. This study is based on an exploratory factor analysis (EFA) conducted on a nationally representative sample of Polish consumers (AgriFood 2024). The results revealed three dominant decision-making determinants—taste, health, and convenience—collectively forming the original THC (Taste–Health–Convenience) model. This model provides a novel interpretive framework, showing how sustainability issues can be communicated through immediate, personally relevant consumer benefits, and subsequently expanded to include environmental and ethical aspects. The findings indicate that effective communication should emphasize tangible, everyday consumer benefits while also leveraging poultry’s lower climate impact compared to red meat. This article makes an original contribution to the debate on sustainable diets by presenting the THC model both as a tool for explaining the mechanisms of the attitude–behavior gap and as a practical instrument for designing campaigns that support the implementation of SDG 3 and SDG 12.

Since the beginning of the COVID-19 pandemic, digital transformation has significantly accelerated in many industries, including somewhat slow-changing higher education. The epidemic situation pushed students, faculties, and administrators to experiment to a much greater degree with online classes, digital cooperation, and virtual student services. For the majority of the academic community, this situation created a completely new reality. Indeed, the digital experience in higher education was for some community members quite challenging, if not traumatic. Fairly soon, however, the digital experiment proved successful in many areas. In some cases, even more effective than conservative practices. The Virtual University Concept (VUC) has been a topic of debate for quite some time, but only now has it found a receptive audience in all sectors of the academic community. In the following articles, the authors will attempt to conceptualize the virtual university as an innovative way to address contemporary challenges for Higher Education Institutions (HEI), specifically their ability to identify, create and capture value for students. The concept of the VUC is grounded in a literature review, the professional experience of the authors, as well as the student survey, which was conducted in one of Cracow’s private colleges. The authors have listed fundamental areas of focus that need to be addressed before attempting to model the VUC. They include the technical and technological capacity of a HEI, faculty development, cost management, innovation, and students' and employers' value perceptions. All this must be done with the goal of providing value to key stakeholders at a reasonable cost. All the authors' inquiry streams seem to suggest that if well designed and implemented, the VUC can be a source of significant value to students and therefore should be considered in HEI expansion and turnaround strategies.

Purpose: This study examines the usage patterns of artificial intelligence (AI) tools among 859 university students in Poland, representing three major academic fields. The research aims to identify discipline-specific differences in AI adoption, usage motivations, perceived benefits, and challenges, contributing to evidence-based strategies for advancing Sustainable Development Goal 4 (Quality Education). Design/methodology/approach: An exploratory quantitative approach was employed using a cross-sectional online survey conducted from February to May 2025. Data from 859 students across humanities and social sciences, natural sciences and technology, and arts and communication were analysed using descriptive statistics and nonparametric methods (Kruskal Wallis and DSCF post-hoc tests). Findings: Significant inter-group differences were identified in AI adoption patterns. Humanities students primarily use AI for knowledge expansion (54%) and translation (48%). Natural sciences students emphasise problem-solving (51%) and knowledge acquisition (62%). Arts students focus on translation (63%) and creative content generation (46%). Despite widespread adoption, students across all disciplines express concerns about data privacy, ethics, and employment impacts. Research limitations/implications: Convenience sampling and unequal group sizes limit generalizability. The cross-sectional design captures a single point during rapid technological change. Future longitudinal and comparative studies are recommended. Practical implications: Universities should develop discipline-specific AI integration strategies, targeted professional development for faculty, and comprehensive AI literacy curricula. Preparing graduates for the evolving business landscape requires aligning AI literacy, critical thinking, and ethical competencies with industry expectations. Social implications: The findings underscore the need for inclusive and equitable AI integration in higher education to prevent new forms of digital inequality, contributing to sustainable economic growth, digital transformation, and responsible workforce development. Originality/value: This study provides empirical evidence on discipline-specific AI adoption patterns in the underexplored Central and Eastern European context, documenting usage during the critical transition from experimental to systematic AI integration in higher education. Keywords: artificial intelligence, higher education, AI literacy, cross-disciplinary differences, sustainable education. Category of the paper: Research paper.