In recent years, artificial intelligence (AI) has been developing rapidly and has had a broad impact on the food industry, with food produced from AI-generated recipes already appearing to actually go on sale. However, people’s trust and willingness to purchase AI food are still unclear. This study builds an integrated theoretical model based on cognitive trust and affective trust, taking into account consumers’ quality value orientations, social norms, and perceived risks of AI food, with the aim of predicting and exploring consumers’ trust and acceptance of AI food. This study utilized the questionnaire method and 315 questionnaires were collected. The results of structural equation modeling (PLS-SEM) indicated that food quality orientation, subjective norms, perceived trust, and affective trust all had a significant positive effect on consumers’ purchase intentions. Perceived risk had a negative effect on affective trust and consequently on consumers’ purchase intention, but the effect on cognitive trust was not significant. The results also suggest that cognitive trust is the basis of affective trust and that consumer trust and acceptance of AI food can be enhanced by augmenting two antecedents of cognitive trust (food quality orientation and subjective norms). Possible practical implications and insights from the current findings are discussed.

The structure and interpersonal interactions of traditional residential communities have also been impacted and recreated as a result of the fast development of urban space and related communities. This study explores the interrelationship between neighborhood social cohesion and the life satisfaction of urban adult residents through the mediating effect of place attachment. A comprehensive theoretical model was constructed to analyze the action mechanism among these variables. Data were collected through an online questionnaire platform (n = 301), and structural equation modeling (PLS-SEM) was employed for analysis. The findings revealed a significant positive relationship between neighborhood social cohesion and residents’ place attachment. Place attachment appeared to play a mediating role between neighborhood social cohesion and life satisfaction, in which place dependence was also a potential effective mediator between the three dimensions of neighborhood social cohesion (neighborliness, sense of community, and neighborhood attractiveness) and life satisfaction. The results suggest that enhancing community cohesion may contribute to urban adult residents’ well-being by strengthening their functional dependence on the community.

Online learning has become an important means of acquiring knowledge. Virtual pedagogical agents have gradually evolved from auxiliary tools into intelligent instructional media capable of affective interaction. However, how these agents affect learning outcomes remains unclear. Integrating social agency theory and cognitive load theory, this study developed a model in which virtual pedagogical agent type was the independent variable; learning experience was the dependent variable; psychological distance, emotional attachment, and attentional engagement were mediators; and instructional content type was the moderator. A 2 (virtual pedagogical agent: human-like vs. non-human) × 2 (instructional content type: traditional knowledge vs. interest-oriented popular science) mixed design was used. Questionnaires, eye tracking, and electroencephalography (EEG) were combined to assess the learning processes of 40 university students. The results showed that the interaction between agent type and instructional content type significantly affected learning experience. Specifically, in learning contexts featuring traditional knowledge content, human-like virtual agents were associated with higher learning satisfaction, greater emotional attachment, and lower psychological distance. In contrast, during interest-oriented content learning, non-human agents achieved superior knowledge recall scores, along with higher learning satisfaction, stronger emotional attachment, and lower psychological distance. Furthermore, eye-tracking data showed that attentional allocation was also affected by this combination. EEG data showed that FCz spectral power varied with it as well, however, because power rose simultaneously in theta, alpha, beta, and gamma; this broadband pattern is not an unambiguous index of deeper processing and may partly reflect a general increase in signal amplitude. In addition, the moderated-mediation analysis revealed that psychological distance and emotional attachment mediated the relationship between virtual-agent type and learning experience, while knowledge type moderated these mediating paths. The practical implications for online learning are discussed.