Sales through note-sharing: influences on the shopping behavior of "Xiaohongshu" users

通过笔记分享进行销售:对“小红书”用户购物行为的影响

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Abstract

INTRODUCTION: To attract more users and promote purchase habits, social e-commerce platforms constantly propose new interaction techniques and marketing strategies. "Xiaohongshu" immediately became famous due to its popular "grass-planting" function. The platform established the "Sales through note-sharing" approach to interrupt the cycle of "planting without uprooting." The purpose of this study is to investigate the factors influencing online purchase intention of the "Xiaohongshu" Sales through note-sharing model from a human-computer interaction standpoint, as well as the relationships between these factors. To do this, we expanded on the TAM model by including five variables: social identity, social comparison, and knowledge sharing Willingness, interface design, and purchase intention form 12 hypotheses. METHODS: We gathered 287 valid replies from "Xiaohongshu" users and tested them with SPSS and AMOS. RESULTS: According to the study findings, interface design has a greater impact on purchase intention than knowledge-sharing willingness and behavioral intention to use. Interface design significantly influences knowledge sharing Willingness and social identity significantly influence social comparison, which in turn significantly affects interface design. These results underscore the crucial role of interaction factors, particularly interface design, in purchase intention and the Sales through note-sharing model. DISCUSSION: This suggests that "Xiaohongshu" can enhance the Sales through note-sharing model by improving interface design to further enhance users' purchase intention and solidify the "grass-planting and uprooting" loop. In theoretical terms, this study extends the TAM model by integrating social factors (social identity, social comparison, knowledge sharing willingness) and interaction factors (interface design), enriching research in the fields of online purchasing and human-computer interaction on social e-commerce platforms. It also provides relevant insights for stakeholders.

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