网络直播购物:影响消费者行动参与的信息策略选择——基于“文本挖掘+QCA”的混合性研究

伴随着网络直播购物的流行,其逐渐被市场、消费者、学者等加以关注,相关的研究也越来越多。本文针对国内排名前30位的网络购物主播的微博文本进行内容分析,运用网络爬虫、自然语言分析、OLS回归、模糊比较分析(QCA)等方法对文本进行分类,分析不同信息类型对消费者参与行为(转发、评论、点赞)的影响,发现存在"属性类信息-转发行为""交互类信息-评论行为""体验类信息-点赞行为"三类特定的匹配关联。同时,还发现不同要素组合对高卷入行为(转发、评论、点赞)有着组合性影响,且视频&图像、积极态度对高卷入行为(高频数)有着差异性影响。最后提出运用信息策略促进精益化运营、关注受众群体的长期性培养以及营造符号消费氛围等启示。

With the popularity of webcast shopping,it is gradually concerned by the market,consumers,scholars,etc.,and the relevant research is also increasing.This paper analyzes the content of microblog texts of the top 30 online shopping anchors in China,and classifies the text content by using the methods of web crawler,natural language analysis,OLS regression and fuzzy comparative analysis(QCA)to analyze the significance of different information types for consumer participation behaviors(forwarding,commenting,praising).Finally,it finds that there are three kinds of specific matching relations:"attribute information forwarding behavior","interactive information comment behavior"and"experience information praising behavior".At the same time,it finds that the combination of different elements has a combined effect on high involvement behavior(forwarding,commenting and praising).Besides,video&image and positive attitude have different influence on high involvement behavior(high frequency).Then,the paper puts forward the inspiration and suggestions of the selective use of information strategy,the long-term cultivation of users,and the construction of the symbol consumption atmosphere.