Factors Influencing Purchase Intention for Fast-Moving Consumer Goods on Douyin (TikTok): A Bayesian Perspective

This study investigates the factors influencing consumers’ purchase intentions for fast-moving consumer goods (FMCGs) on Douyin (TikTok), one of China’s leading and short-video platforms. Utilizing 454 valid survey responses, we employ A Tree-Augmented Naïve Bayesian (TAN) network model to explore how customized recommendations, discount strategies, emotions, and virality of content influence consumer behavior. simultaneously. It is suggested that algorithmic personalization has a significant impact on purchase intention, followed by discount strategies and emotional perception. Viral marketing demonstrates a weaker but still positive association. The model can reveal hidden relationships between variables and perform well in prediction. Implications of this study are that algorithmic targeting, promotional strategies, and emotionally engaging content that can effectively enhance user purchase intention. Marketing practitioners aiming to enhance user engagement on similar platforms may benefit from tailoring their strategies accordingly. Future work could incorporate behavior tracking and extending the model to other platforms for broader validation.