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作 者:赵洁[1] 高佳艺 ZHAO Jie;GAO Jiayi(School of Business,Anhui University,Hefei 230601,China)
机构地区:[1]安徽大学商学院,合肥230601
出 处:《重庆科技大学学报(社会科学版)》2024年第4期1-13,共13页Journal of Chongqing university of science and technology(social sciences edition)
基 金:安徽省哲学社会科学规划项目“社交网络背景下的电商用户行为研究”(AHSKY2021D15)。
摘 要:随着社交媒体平台的快速发展,直播销售已成为电子商务的重要部分。然而,电商直播的特性在于实时互动,如何通过有效的互动获得更好的直播效果,特别是主播互动类型如何影响用户参与行为的机制尚不清晰。针对这一问题,本研究基于SOR模型,运用Python爬虫技术获取真实的直播动态数据,探究了任务型和关系型互动对不同用户参与行为(在线观看、点赞与评论)的影响,并研究了感知价值(包括感知信息价值与感知娱乐价值)的中介作用。研究结果显示,任务型互动对于用户评论有显著影响,但对用户在线观看和点赞影响不显著;相比之下,关系型互动对所有因变量均有显著影响。此外,作为中介变量的感知信息价值和感知娱乐价值,在主播互动和用户参与行为之间发挥了部分的中介作用。本研究扩大了SOR理论使用范围,丰富了电商直播中用户参与行为的研究,深化了对电商直播中感知价值的理解,研究结论对提升主播互动策略及优化直播效果具有一定的指导意义。With the rapid development of social media platforms,live sales have become an integral part of e-commerce.However,the defining characteristic of e-commerce live streaming lies in real-time interaction,and how effective interaction can lead to better live streaming outcomes,especially the mechanisms through which different types of anchor interactions affect user engagement behaviors,remains unclear.This study,grounded on the SOR model,employs Python to collect authentic live streaming data.It investigates the influence of task-oriented and relationship-oriented interactions on different user engagement behaviors(including online viewing,likes,and comments)and examines the mediating role of perceived value(including perceived information value and perceived entertainment value).It is found that task-oriented interactions affect user comments significantly but not so significant on user online viewing and likes.In contrast,relationship-oriented interactions have a significant impact on all dependent variables.Furthermore,perceived informational value and perceived entertainment value,acting as mediating variables,partially mediate the relationship between anchor interactions and user engagement behaviors.This study expands the application scope of SOR theory,enriches the research on user engagement behaviors in e-commerce live streaming,and deepens the understanding of perceived value in e-commerce live streaming,providing valuable insights for enhancing anchor interaction strategies and optimizing live streaming outcomes.
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