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品牌危机情境下精选评论集特征对消费者的危机信息传播意愿的影响 被引量:2

Examining the Impact of the Featured Review Set Characteristics on Consumers'Secondary Crisis Communication
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摘要 为应对品牌危机后负面信息在社交媒体上广泛的传播,许多品牌开始应用社交媒体平台提供的精选评论功能来对评论区进行有目的的内容调控。基于说服知识模型,本文通过3项实验探究精选评论集特征(即平衡性、序列组合与品牌维护评论自身特征)对消费者的危机信息传播意愿的影响。研究发现,品牌精选完全积极的评论集或是将积极评论置于序列前方(即正—负序列)将会激发用户较高水平的潜藏动机推断,进而提高了危机信息传播倾向。其次,捍卫型品牌维护评论(相较于拥护型)会导致消费者更强的潜藏动机的推断,但该效应在正—负序列情况下不显著。研究结果验证了精选评论带来的适得其反的效果,为品牌管理消费者评论和应对社交媒体负面曝光提供了实践启示。 To mitigate the widespread crisis communication of brand negative publicity on social media,many brands have applied comment management strategies(such as managing featured reviews)to moderate unfavorable reviews.Drawing from the Persuasion Knowledge Model,this paper conducts three experiments with Weibo users to examine the impact of featured review set characteristics(balance,sequence,and type)on consumers'crisis communication.The results show that a fully positive set of featured reviews or presenting positive comments earlier in a sequence stimulates stronger inferences of ulterior motives,further triggering secondary crisis communication.Furthermore,defensive featured reviews(as opposed to advocative reviews)lead to stronger inferences of ulterior motive in the negative-positive sequence,while the effect is not significant in the positivenegative sequence.Theoretically,this research observes the counterproductive effect of featured reviews and provides new directions for social media crisis response strategies.In addition,this paper has practical insights for companies to apply comment management strategies in response to negative publicity.
作者 廖俊云 陈嘉雯 江颖 Liao Junyun;Chen Jiawen;Jiang Ying(School of Management,Jinan University;School of Economics and Management,Wuhan University)
出处 《营销科学学报》 2025年第1期96-115,共20页 Journal of Marketing Science
基金 国家自然科学基金(编号:72272061) 教育部人文社会科学基金(编号:22YJC630077) 广东省普通高校类科研创新项目(编号:2024WTSCX007) 暨南大学启明星计划项目(编号:23JNQMX12)的资助。
关键词 精选评论 评论集效价平衡 评论集序列 品牌维护 说服知识模型 featured review balance of review set sequence of review set brand advocacy persuasion knowledge model
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