摘要
在社交媒体平台中,企业生成内容(EGC)赋予了企业与消费者沟通的重要渠道,它既可以向消费者传递与产品、服务细节相关的信息性内容,又可以通过说服性内容增强与粉丝的情感交流,建立更紧密的联系。然而,关于企业应该如何有所侧重地发布EGC才能使沟通效果最理想化的问题,目前尚缺乏明确的答案。为丰富社交媒体营销研究体系,本文首先提出了EGC内容特征细粒度评价标准,其次区分了不同层次的用户卷入行为,并以其规模来评价企业沟通效果。最后,以电影院线企业的官方微博为研究对象,对3437条微博进行内容分析,并分别从聚合与独立层面考察每类内容特征产生的沟通效果。发现信息性内容对高卷入层次的转发行为的推动力大于说服性内容。但对于中卷入层次的评论行为,说服性内容的提升作用更强。而处于低卷入层次的点赞行为仅由说服性内容触发。同时,进一步讨论了每个独立特征的沟通能力,结论有助于指导企业合理制定EGC发布策略和管理EGC内容。
In social media platforms,enterprise generated content(EGC)provides an important channel for enterprises to communicate with consumers.Informative content describes some details related to products or services to users,while persuasive content is able to strengthen emotional ties with fans.However,there is no clear answer to the question how enterprises should release EGC to idealize the communication effect?In order to enrich social media marketing research,this paper first proposes fine-grained EGC content feature evaluation criteria,then distinguishes user engagement behaviors at different levels,and evaluates the effectiveness of enterprise communication based on engagement scale.Finally,taking the official micro-blog of cinema chain enterprise as research object,this study conducts a content analysis of 3,437 pieces of EGC messages,and examines the difference of communication effect among various types of content in aggregation and independent level respectively.The findings are as follows:informative content plays a more important role in promoting reposting which is in high-level of engagement than persuasive content,while the opposite is true of the situation where commenting is in medium-level of engagement.And in low-level of engagement,liking is only triggered by persuasive content.Furthermore,the conclusions about the communication ability of each independent feature are conducive to guide enterprises to formulate EGC releasing strategy and manage EGC content.
作者
刘嘉琪
齐佳音
朱舸
Liu Jiaqi;Qi Jiayin;Zhu Ge(Institute of Journalism and Communication,Chinese Academy of Social Sciences,Beijing 100021;Institute of Artificial Intelligence and Change Management,Shanghai University of International Business and Economics,Shanghai 201620;Key Laboratory of Trustworthy Distributed Computing and Service,Beijing University of Posts and Telecommunications,Beijing 100876;Institute of Economic Management,Beijing University of Posts and Telecommunications,Beijing 100876)
出处
《管理评论》
CSSCI
北大核心
2021年第1期152-163,共12页
Management Review
基金
国家自然科学基金专项项目(72042004)
国家自然科学基金项目(91546121)
国家社会科学基金重大项目(16ZDA055)
关键词
企业生成内容
ELM理论
内容分析
社交媒体营销
用户卷入行为
enterprise generated content(EGC)
ELM Theory
content analysis
social media marketing
customer engagement behavior