Consumers’ persuasion knowledge of algorithms in social media advertising: identifying consumer groups based on awareness, appropriateness, and coping ability

IF 5.3 3区 管理学 Q1 BUSINESS International Journal of Advertising Pub Date : 2023-10-12 DOI:10.1080/02650487.2023.2264045
Hilde A. M. Voorveld, Corine S. Meppelink, Sophie C. Boerman
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Abstract

Advertising and brand communication in social media are increasingly driven by algorithms. Theoretically rooted in the Persuasion Knowledge Model, we aim to identify and investigate the prevalence of specific consumer groups that differ in their awareness levels, critical evaluations, and abilities to cope with such algorithmic persuasion in social media, as well as to investigate the predictors of these groups. By performing an online survey among a Dutch sample (n = 450) and a two-step cluster analysis, we identified four groups: the Control Paradox (the largest group), Fatigued, Uninformed but Critical, and Skilled and Critical. The four groups differed in respect to gender, age, education level, internet skills, self-reported knowledge of algorithms, privacy concerns, and perceived personalization of branded social media messages. Theoretically, this paper contributes to our understanding of algorithmic persuasion by proposing a consumer typology and discussing implications for the Persuasion Knowledge Model. Practically, this study provides evidence-based recommendations for policymakers on how to empower different types of consumers.
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消费者对社交媒体广告算法的说服知识:基于意识、适当性和应对能力来识别消费者群体
社交媒体上的广告和品牌传播越来越多地受到算法的驱动。在说服知识模型的理论基础上,我们旨在识别和调查特定消费者群体的流行程度,这些群体在意识水平、批判性评估和应对社交媒体中这种算法说服的能力方面存在差异,并调查这些群体的预测因素。通过对荷兰样本(n = 450)进行在线调查和两步聚类分析,我们确定了四个群体:控制悖论(最大的群体),疲劳,无知但关键,熟练和关键。这四组人在性别、年龄、教育程度、互联网技能、自我报告的算法知识、隐私问题和品牌社交媒体信息的个性化感知方面存在差异。从理论上讲,本文通过提出消费者类型并讨论说服知识模型的含义,有助于我们对算法说服的理解。实际上,本研究为政策制定者提供了关于如何赋予不同类型消费者权力的循证建议。
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CiteScore
13.90
自引率
19.40%
发文量
66
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