Large language-model chatbots such as ChatGPT and DeepSeek are quickly gaining traction as an easy, first-stop tool for trip planning because they offer instant, conversational advice that once required sifting through multiple websites or guidebooks. Yet little is known about the biases that shape the destination suggestions these systems provide. This study conducts a controlled, persona-based audit of the two models, generating 6480 recommendations for 216 traveller profiles that vary by origin country, age, gender identity and trip theme. Six observable bias families (popularity, geographic, cultural, stereotype, demographic and reinforcement) are quantified using tourism rankings, Hofstede scores, a 150-term cliché lexicon and information-theoretic distance measures. Findings reveal measurable bias in every bias category. DeepSeek is more likely than ChatGPT to suggest off-list cities and recommends domestic travel more often, while both models still favour mainstream destinations. DeepSeek also points users toward culturally more distant destinations on all six Hofstede dimensions and employs a denser, superlative-heavy cliché register; ChatGPT shows wider lexical variety but remains strongly promotional. Demographic analysis uncovers moderate gender gaps and extreme divergence for non-binary personas, tempered by a “protective” tendency to guide non-binary travellers toward countries with higher LGBTQI acceptance. Reinforcement bias is minimal, with over 90 percent of follow-up suggestions being novel in both systems. These results confirm that unconstrained LLMs are not neutral filters but active amplifiers of structural imbalances. The paper proposes a public-interest re-ranking layer, hosted by a body such as UN Tourism, that balances exposure fairness, seasonality smoothing, low-carbon routing, cultural congruence, safety safeguards and stereotype penalties, transforming conversational AI from an opaque gatekeeper into a sustainability-oriented travel recommendation tool.

This research article presents an empirical model that takes economic vulnerability into consideration to measure and address the phenomenon of precarious work and precariousness. In order to achieve this, three satisfactory indicators were formulated, consisting of both individual and institutional levels and taking into account the country-specific relationships among the variables, depending on country-specific conditions. Based on this, the choice of homeownership is introduced instead of the eligibility for employment benefits. In this way, precarity has been examined as a condition in which precariousness and economic vulnerability intersect and interact. In Cyprus, 9.5% of the workers in Cyprus were classified as precarious, while 4.4% were classified as being in precarity (i.e., precarious and economically vulnerable). The empirical findings revealed that precariousness was related to gender, migration, and the employment sector, which is consistent with the well-known literature. One of the most noteworthy findings was the high number of female migrant domestic workers in Cyprus. In this study, new variables and novel empirical approaches were introduced into the discussion of precarious work and precariousness, which may eventually lead to new theoretical and policy avenues for reducing or eliminating this phenomenon.

The evolution of cycle tourism using EU financing is examined in this chapter. The authors begin by defining cycle tourism and outlining its advantages, including the growth of local economies and the promotion of healthy, carbon-neutral modes of transportation. Cycling is an appropriate leisure activity for sustainable regional development through EU funding as it complies with 11 of the 17 Sustainable Development Goals (SDGs) of the United Nations. The chapter places a strong emphasis on the necessity of planning and encouraging private-public stakeholder synergies for the growth of cycling tourism. In its second part, the chapter examines the numerous EU programmes that were backing up the development of cycling tourism, including Interreg, COSME, and the EU Lifelong Learning Program (LLP). Most initiatives carried out using a strategic approach were targeted for enhancing and popularizing the EuroVelo network’s infrastructure, which led to the successful promotion and facilitation of cycling tourism at a pan-European level. <!----> <!----> <!----> <!---->

Management education remains problem-solving-centric, yet real-world management challenges are typically ill-defined. This creates a discrepancy between classroom learning and workplace needs. Fostering divergent thinking is crucial to address this discrepancy, and engaging students in case writing is an effective way to develop this skill. While early exposure to ambiguity is crucial for developing divergent thinking, using student case writing to foster this skill in first-year management students is underexplored in academic literature. To that end, the study explores the theoretical underpinnings of case writing as a pedagogical tool to foster divergent thinking. Data was collected using a mixed-methods approach from 646 students over a 5-year period across two universities. Results show that student case writing is effective across personality types, leading to a five-stage model grounded in the student experience. This model offers a theoretical framework to understand the mechanisms through which case writing fosters critical thinking. Positioning students as coconstructors of managerial meaning under ambiguity, it contributes to our understanding of how learning emerges through storytelling. Finally, practical implications are proposed for educators.