Research on the Purchase Intention Analysis Algorithm of Virtual Goods Based on Neural Network and SEM Model

With the development of the times, virtual product shopping has become more and more integrated into our daily lives, affecting consumers’ choices and decisions. This not only provides merchants with a broader space for development, but also provides consumers with more convenience and diversity. Therefore, we conduct in-depth research on virtual product purchase intentions to better understand consumers’ psychological construction and shopping decision-making process in the digital age. Combined with the method of structural equation modeling (SEM), special attention is paid to the motivations and behavioral factors of consumers purchasing virtual goods in the digital environment. Through advanced neural network technology, we constructed an SEM model to carefully analyze the relationship between each potential variable. In-depth analysis of real-time shopping data reveals the critical paths and interactions in the formation of virtual product purchase intentions. In this research framework, we not only provide a new perspective on the virtual goods market and provide a basis for formulating more effective marketing strategies, but also provide a more comprehensive understanding of the nature of consumer shopping behavior in the digital era.