Fig 1.
Conceptual framework illustrating the hypothesized relationships among visual aesthetics, cognition, emotion, trust, and artistic acceptance intention.
Note: VAF = Visual Aesthetic Features; CM = Cognitive Mastery; EA = Emotional Arousal; PAV = Perceived Artistic Value; TA = Trust in AIGC; FC = Familiarity Control; AAI = Artistic Acceptance Intention.
Table 1.
Hypotheses, Path Relationships, and Equation Mapping.
Table 2.
Categories of Prompt Strategies and Representative Examples Used in Midjourney Generation.
Fig 2.
Representative set of 24 AIGC-generated urban sculpture concepts created using Midjourney v6.
Table 3.
Scale Operationalization: Definitions, Sources, and Measurement Items.
Table 4.
Demographic Characteristics of Survey Respondents (N = 326).
Table 5.
Descriptive Statistics and Reliability Coefficients for Latent Constructs.
Table 6.
Goodness-of-Fit Indices for the Structural Equation Model.
Table 7.
Convergent Validity: Composite Reliability (CR), Average Variance Extracted (AVE), and Indicator Loadings.
Fig 3.
Discriminant Validity: Fornell–Larcker Criterion.
Table 8.
Structural Equation Modeling Results: Standardized Path Coefficients and Hypothesis Testing.
Fig 4.
Final structural equation model with standardized path coefficients (N = 326).
All paths significant at p < 0.01.
Fig 5.
Visual analysis heatmap of 24 AIGC-generated sculpture stimuli rated across five perceptual dimensions.