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Application of the New Visit Intention Model for Gastronomy Tourism : An Empirical Study in Vietnam
Trong Tien Bao Bui, Minh Chanh Trinh, Thi Thuy Ngan Dang, original scientific article

Abstract: The study aims to address research gaps in Vietnam’s gastronomy tourism by developing and validating a new visit intention model based on the Theory of Planned Behaviour (TPB). The model incorporates the concepts of gastronomic destination image and novelty-seeking to gain a comprehensive understanding of domestic tourists’ intention to visit Ho Chi Minh City, a leading gastronomic destination in Vietnam. Primary data were collected from 417 domestic tourists through a questionnaire survey conducted in Ho Chi Minh City from April to August 2023. Partial Least Squares Structural Equation Modelling (PLS-SEM) was employed to test the proposed model and examine the relationships among novelty seeking, gastronomic image, attitudes, subjective norms, perceived behavioural control, and visit intention. The findings indicate that novelty-seeking, gastronomic image, and the core TPB constructs play a crucial role in explaining the intention to visit a gastronomic destination. The model explains 71.2% of the variance in visit intention, with domestic tourists’ visit intention being strongly influenced by the desire for novel culinary experiences and the attractiveness of Ho Chi Minh City’s gastronomic image. This study reaffirms the applicability of the extended TPB framework in explaining visit intention toward gastronomy destinations. The significant findings provide empirical evidence from Vietnam, clarifying how novelty-seeking and gastronomic image strengthen visit intention. The study also provides practical guidance for local authorities and tourism marketers to enhance Ho Chi Minh City’s competitiveness and support sustainable tourism development goals (SDG 11).
Keywords: gastronomic image, novelty seeking, TPB model, visit intention, Sustainable Development Goals (SDG 11), Ho Chi Minh City
Published in RUP: 06.03.2026; Views: 617; Downloads: 28
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AI in higher education : analysis of relevant practices and their potential for green transition
Vesna Ferk Savec, Sanja Jedrinović, 2025, independent scientific component part or a chapter in a monograph

Abstract: Artificial Intelligence (AI) has the potential to significantly impact the entire spectrum of sustainable development by targeting the 17 Sustainable Development Goals (SDGs) of the 2030 Agenda for Sustainable Development. In the present study, we analysed reports from university teachers on 26 practises of AI implementation in pedagogical processes at nine faculties of the University of Ljubljana that responded to a call for participation in the Artificial Intelligence in Education project at the University of Ljubljana (2023–2024). We found that various AI tools were mainly used to facilitate the achievement of the sustainable development pillars Economy (SDG9, SDG12) and Society (SDG4) in different areas of KLASIUS-P educational activities, other SDGs were addressed to a lesser extent. Based on the results, we can conclude that the integration of AI into the pedagogical process has great potential but needs to be supported by regulatory insights and monitoring of AI-based technologies to enable sustainable development.
Keywords: sustainable development goals (SDGs), artificial intelligence in education (AIEd), higher education (HE)
Published in RUP: 19.12.2025; Views: 1543; Downloads: 11
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