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The choices that international students make regarding abroad study destination selection or leave the host country after graduation are influenced by a variety of factors that are both related to positive and negative aspects of the host country.

This study builds on the push-pull factor theory and examines the factors that influence international students' decision to choose abroad study destination (Finland) or leave the country after their graduations. The data were collected through an online survey of 195 international students currently studying in Finland and were analysed using partial least squares structural equation modelling (PLS-SEM) technique. This method offers a flexible and robust approach to test relationships, particularly in situations where sample size and the conceptual model are small and complex.

The results show that international students' choice of study destination (Finland) is influenced by the host country's quality of life, academic excellence and economic factors such as salary and benefits. Unfamiliarity with the culture and language barriers have a negative impact on their decisions to stay in the host country after graduation.

By utilising a comprehensive analysis of both push and pull factors in relation to the host country, this study unveils a novel perspective in the field of international student mobility. The results provide insights to the institutional leaders and policymakers into how to attract and retain international students by focusing on the factors that matter most to international students. To attract more international students, higher education institutions (HEIs) should include career development activities, e.g. job fairs, language training, scholarships and internships in their curriculum. Moreover, it provides recommendations on how to create a welcoming and supportive environment that promotes academic excellence and career development.

The pressing issues of climate change and environmental degradation call for a reevaluation of how we approach economic activities. Both leaders and corporations are now shifting their focus, toward adopting practices and embracing the concept of circular economy (CE). Within this context, the Food and Beverage (F&B) sector, which significantly contributes to greenhouse gas (GHG) emissions, holds the potential for undergoing transformations. This study aims to explore the role that Artificial Intelligence (AI) can play in facilitating the adoption of CE principles, within the F&B sector.

This research employs the Best Worst Method, a technique in multi-criteria decision-making. It focuses on identifying and ranking the challenges in implementing AI-driven CE in the F&B sector, with expert insights enhancing the ranking’s credibility and precision.

The study reveals and prioritizes barriers to AI-supported CE in the F&B sector and offers actionable insights. It also outlines strategies to overcome these barriers, providing a targeted roadmap for businesses seeking sustainable practices.

This research is socially significant as it supports the F&B industry’s shift to sustainable practices. It identifies key barriers and solutions, contributing to global climate change mitigation and sustainable development.

The research addresses a gap in literature at the intersection of AI and CE in the F&B sector. It introduces a system to rank challenges and strategies, offering distinct insights for academia and industry stakeholders.