当事情崩溃时:探索网红代言中的品牌仇恨

IF 13.3 1区 管理学 Q1 BUSINESS
Yan-Rong Pan , Garry Wei-Han Tan , Eugene Cheng-Xi Aw , Keng-Boon Ooi
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引用次数: 0

摘要

在直播日益普及的推动下,品牌越来越青睐有影响力的人,因为他们的影响范围很广。然而,实现更广泛的品牌价值不仅需要全面了解网红代言的积极影响,也需要全面了解网红代言的消极影响。为了解决这一差距,本研究引入并验证了网红-品牌不一致、象征不一致、负面的过去经历、意识形态不相容和负面宣传对网红和品牌态度的影响。采用非对称模型揭示消费者品牌厌恶的前因。研究1采用德尔菲法识别关键前因式,研究2采用偏最小二乘结构方程模型(PLS-SEM)和人工神经网络(ANN)对326名中国直播消费者的数据进行分析。研究结果表明,负面的过去经历和负面宣传分别显著损害了人们对网红和品牌的态度。这些消极的态度会导致对品牌的厌恶,进而导致对品牌的回避、抱怨和负面的口碑。本研究提出了网红代言的理论框架,并为网红营销经理和品牌经理解决负面消费者行为和制定有效管理与网红伙伴关系相关风险的品牌策略提供了实践见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
When things fall apart: Exploring brand hate in influencer endorsements
Driven by the growing popularity of live streaming, brands increasingly favor influencers for their extensive reach. However, realizing broader brand value requires a comprehensive understanding of not only the positive but also the negative implications of influencer endorsements. To address this gap, this study introduces and validates the impact of influencer-brand incongruence, symbolic incongruity, negative past experiences, ideological incompatibility, and negative publicity on attitudes towards both influencers and brands. An asymmetric model is employed to uncover the antecedents of consumer brand hate. A multi-method approach is adopted: Study 1 applies the Delphi method to identify key antecedents, while Study 2 analyzes data from 326 Chinese live streaming consumers using partial least squares structural equation modeling (PLS-SEM) and artificial neural networks (ANN). Findings indicate that negative past experiences and negative publicity significantly harm attitudes towards influencers and brands, respectively. These negative attitudes contribute to brand hate, which subsequently leads to brand avoidance, complaints, and negative word of mouth. This study advances the theoretical framework of influencer endorsement and offers practical insights for influencer marketing managers and brand managers to address negative consumer behaviors and to develop brand strategies that effectively manage risks associated with influencer partnerships.
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来源期刊
CiteScore
21.30
自引率
10.80%
发文量
813
期刊介绍: Technological Forecasting and Social Change is a prominent platform for individuals engaged in the methodology and application of technological forecasting and future studies as planning tools, exploring the interconnectedness of social, environmental, and technological factors. In addition to serving as a key forum for these discussions, we offer numerous benefits for authors, including complimentary PDFs, a generous copyright policy, exclusive discounts on Elsevier publications, and more.
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