The rapidly evolving space tourism industry faces significant challenges in building consumer trust and balancing emotional appeal with factual accuracy—both essential for reducing uncertainty and fostering long-term public engagement in this high-risk sector. This study examines the key factors shaping individuals’ intentions to participate in space tourism, with a focus on their perceived trustworthiness, usefulness, and immersiveness of information on social media. Applying Mindsponge Theory, we explore the interplay between trust evaluation and subjective cost-benefit judegement of individuals in high-risk tourism (...) context. The findings reveal that while trustworthiness positively influences participation intention, its role diminishes when usefulness and immersiveness are particularly strong. This suggests that space tourists, who are naturally inclined toward risk-taking, prioritize experiential rewards—such as novelty, prestige, and emotional engagement—over concerns about information reliability. These insights offer practical implications for marketing in high-risk industries, highlighting the importance of immersive storytelling, exclusivity, and transformative experiences over conventional trust-building measures. Future research should investigate how personal risk tolerance, prior experience, and cognitive biases shape thought processes, decision-making, and behaviors in extreme tourism contexts. (shrink)

Food security is one of the major concerns in the Philippines. Although livestock and poultry production accounts for a significant proportion of the country’s agricultural output, smallholder households are still vulnerable to food insecurity. The current study aims to examine how livestock production and selling difficulties affect smallholder households’ food-insecure conditions. For this objective, Bayesian Mindsponge Framework (BMF) analytics was employed on a dataset of the Food and Agriculture Organization’s Data in Emergencies Monitoring (DIEM) system. We found that production and (...) selling difficulties significantly adversely affect food insecurity in the Philippines. However, their effects vary according to the severity of food insecurity. In particular, production and selling difficulties affect the households’ likelihood of eating less healthy and nutritious food equally. However, the production difficulties have more negligible impacts on the possibility of skipping meals and even ambiguous impacts on the likelihood of not eating for a whole day compared to the effects of selling difficulties. Moreover, we also found that the market plays a crucial role in facilitating not only livestock trading but also livestock production (e.g., purchase of feed and medicines). Based on these findings, we suggest that the livestock market needs to be expanded and regulated to maintain the balancing prices between livestock products and products and services used for livestock production, and facilitate the product-exchanging mechanism. (shrink)

This paper examines the potential educational uses of chat-based large language models (LLMs), moving past initial hype and skepticism. Although LLM outputs often evoke fascination and resemble human writing, they are unpredictable and must be used with discernment. Several metaphors—like calculators, cars, and drunk tutors—highlight distinct models for student interactions with LLMs, which we explore in the paper. We suggest that LLMs hold a potential in students’ learning by fostering proleptic reasoning through scaffolding, i.e., presenting a technological accompaniment in anticipating (...) and responding to potential objections to arguments. Here, the technical limitations of LLMs can be reframed as beneficial when fostering anticipatory reasoning. Whether their outputs are accurate or not, evaluating them stimulates learning. LLMs require students to critically engage, emphasizing analytical thinking over mere memorization. This interaction helps solidify knowledge. Additionally, we explore how engaging with LLMs can prepare students for constructive collective discussions and provide first steps in addressing epistemic injustices by highlighting potential research blind spots. Thus, while acknowledging the sociopolitical and ethical complexities of using LLMs in education, we suggest that when used in an informed way, they can promote critical thinking through anticipatory reasoning. (shrink)

This paper addresses the challenge of ethically integrating ChatGPT, a sophisticated AI language model, into K-14 economics education. Amidst the growing presence of AI in classrooms, it proposes the “Evaluate, Reflect, Assurance” model, a novel decision-making framework grounded in normative and virtue ethics, to guide educators. This approach is detailed through a theoretical decision tree, offering educators a heuristic tool to weigh the educational advantages and ethical dimensions of using ChatGPT. An educator can use the decision tree to reach a (...) conclusion on using ChatGPT within the classroom environment by using ethical considerations to promote personalized learning and upholding academic integrity. The paper stresses the importance of ongoing professional development for educators in ethical AI usage and calls for institutional support in this pursuit. It also identifies future research directions, including long-term impact studies of ChatGPT and comparative analyses of various AI tools in economics education, underscoring the paper’s relevance to current educational technology discourse. (shrink)