Mixed reality technology is being increasingly used in cultural heritage attractions to enhance visitors’ experiences. However, how the characteristics of mixed reality affect satisfaction and brand loyalty has not been explored in previous research. The purpose of this study is to identify factors affecting satisfaction with mixed reality experiences at cultural and artistic visitor attractions and their influence on brand loyalty, which is connected with management performance. We propose a theoretical model based on brand equity theory in the context of mixed reality experience. Survey data were gathered from 251 respondents visiting a cultural and artistic visitor attraction in Seoul, Korea, using a stratified sampling method. Partial least squares structural equation modeling (PLS-SEM) was employed for the data analysis. The results suggest that the characteristics of mixed reality (interactivity, vividness) not only influence the affective aspects (perceived immersion, perceived enjoyment) of visitors’ experiences, but also positively affect brand awareness, brand association, and brand loyalty.

Mixed reality technology is being increasingly used in cultural heritage attractions to enhance visitors’ experience. However, how the characteristics of mixed reality affect satisfaction and brand loyalty has not been explored in previous research. The purpose of this study is to identify factors affecting satisfaction with mixed reality experiences at cultural and artistic visitor attractions and their influence on brand loyalty, which is connected with management performance. We propose a theoretical model based on brand equity theory in the context of mixed reality experience. Survey data were gathered from 251 respondents visiting a cultural and artistic visitor attraction in Seoul, Korea using a stratified sampling method. PLS-SEM was employed for the data analysis. The results suggest that the characteristics of mixed reality (interactivity, vividness) not only influence the affective aspects (perceived immersion, perceived enjoyment) of visitors’ experience, but also positively affect brand awareness, brand association, and brand loyalty.

Understanding users and user behaviors in accepting new technologies such as AI has been ever more important. Meanwhile, information systems with AI inevitably engenders such ethical issues as transparency and accountability related to the consequences of recognition, decisions, and recommendations. Our work adds moral psychology variables to Theory of Reasoned Action (TRA) in order to better explicate the adoption aspects of AI. For the research, we employed social desirability, and selfconsistency of moral psychology as underlying attitudes. And also, moral norm is added to TRA to moderate the effect of the attitudes on the outcome variable. The empirical results indicate a direct and indirect role of the morality-related variables in explaining users' AI adoption intentions. It was learned that moral psychology plays an important role in explaining user attitudes toward AI and subsequent intentions of adopting an AI system.

The Nature Relationship Index (NRI) evaluates human–nature relationships through three dimensions (nature thriving, used with care, and safeguarded), but it exists only at the national level, whereas many policies are implemented regionally. Regional statistics describe resource use and protection, but harmonized information on ecological condition is rarely available for regions. This study examines whether satellite imagery can fill this gap. Transformer-based models were trained to estimate the Thriving (ecological condition) dimension from Sentinel-2 and Landsat-8 imagery of 136 countries, with labels constructed from forest cover and two satellite-derived land-condition indicators, while Care and Safeguarded were computed directly from emission, energy, and protected-area statistics. In repeated country-level cross-validation, imagery was essential for Thriving: a statistics-only model had no predictive skill (R² = −0.04), whereas the image model reached R² = 0.36 (p < 0.001), and transformer backbones performed similarly, with no gain from ensembling. The image-based Thriving estimates agreed with regional reference values across 42 Japanese prefectures (Spearman ρ = 0.63) and nine Korean provinces (ρ = 0.85) but not for small metropolitan cities. Combining image-based Thriving with statistics-based Care and Safeguarded yields a sub-national NRI whose profiles show whether a region’s standing is driven by ecological condition, resource use, or protection.