The swift rise of ChatGPT and the growing integration of AI-generated content (AIGC) technologies are reshaping the digital marketing landscape in profound ways. These advancements are not only changing how social media marketing content is produced, but also altering its underlying characteristics. Despite this shift, there remains a noticeable gap in empirical research on how businesses and brands can effectively harness AIGC to drive consumer engagement. This study draws on the Stimulus–Organism–Response (SOR) theoretical framework to examine how AI-generated content influences consumer cognition, builds trust, and ultimately shapes decision-making behavior. Based on 348 valid survey responses, we employed a mixed-methods approach that integrates Partial Least Squares Structural Equation Modeling (PLS-SEM) with Artificial Neural Network (ANN) analysis. The findings indicate that entertainment, interactivity, trend relevance, electronic word-of-mouth, and visual appeal all positively influence both perceived value and trust. In contrast, customization was found to enhance perceived value only. Both perceived value and trust were shown to significantly increase consumers’ purchase intentions. The ANN model further supported the PLS-SEM results, confirming consistency across methods. Among the predictors, entertainment ( $\beta =0.176$ , ni =86.28%) was most influential for perceived value, EWOM ( $\beta =0.192$ , ni =85.94%) played a key role in shaping trust, and perceived value ( $\beta =0.344$ , ni =99.19%) had the strongest impact on purchase intention. These insights contribute to a deeper theoretical understanding of social media marketing and consumer behavior, while also offering actionable recommendations for businesses aiming to refine their content strategies in an AIGC-driven environment. Additionally, the study highlights promising directions for the evolution of digital consumption and the long-term sustainability of brand development.
Exploring the Impact Mechanism of AIGC-Driven Social Media Marketing Content on Consumer Decision-Making Behavior: A Two-Stage Hybrid Approach
Jiacheng Luo,Kewei Zhang,Jiang Du
Published 2025 in IEEE Access
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- Publication year
2025
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IEEE Access
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Business, Psychology, Computer Science
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