Study on the Impact of Live E-commerce Pop-up Information Quality on Consumers' Purchase Intention: A Mediating Role based on Psychological Mechanisms

With the rapid development of mobile Internet, e-commerce live broadcasting, as an emerging business model, has become an important means to promote economic circulation and market vitality by virtue of its immersive product display and interactive information service. As an important interactive communication method in e-commerce live broadcasting, the information quality of the pop-up screen has an important impact on consumers' purchase intention. However, there are relatively few current studies on the impact of the information quality of live e-commerce pop-up screen on consumer purchase intention. Based on the stimulus-organism-response (SOR) theory, this study constructed a model of the influence of pop-up information quality on consumers' purchase intention, and explored the mediating role of trust and emotional resonance. Through a questionnaire survey, 502 valid samples were collected and empirically analyzed using structural equation modelling (SEM). The results of the study show that the quality of e-commerce live pop-up information has a significant impact on consumer purchase intention, with accuracy being the key factor. Trust and emotional resonance play an important mediating role between the quality of pop-up information and consumers' purchase intention, and the accuracy of pop-up information significantly enhances consumers' purchase intention by increasing trust and emotional resonance. This study not only expands the research on the impact of pop-up information quality on consumer behavior in the field of new media interaction, but also provides theoretical basis and practical guidance for e-commerce platforms to optimize pop-up management, anchors to improve their interaction strategies, and consumers to make rational decisions. Future research can further explore the differences in the quality of pop-up information in different live broadcasting types, as well as combining more technical means to deeply mine pop-up data to reveal more complex consumer behavior mechanisms.