An Experimental Study on the Swaying Effect of Web-Personalization

IF 2.8 4区 管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE
U. MaheshBalan, Saji K. Mathew
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引用次数: 3

Abstract

The multi-dimensionality of online word-of-mouth not only provides rich attribute-level information but also influences the attribute preference construction of the online consumer. Though prior research affirms that consumer reviews impact the attribute preference assessment of a consumer in a non-personalized single-product environment, in a personalized, multiple alternative environment, consumers' behavior could be completely different and requires separate attention. Building on the information processing approach and constructive preference perspective, our research analyzes how personalization influences this swaying effect, i.e., the influence of personalization on the attribute preference of a consumer. We conducted a multi-group experiment with four different types of personalization - non-personalized information (no personalization), self-referent information, relevant information, and both self-referent and relevant information. Our results show evidence of a swaying effect of personalization on consumers' attribute preference for products. We found that users, when exposed to different types of personalization, experience different levels of the swaying effect on their attribute preferences of the product. This study contributes significantly to the current discourse on the setbacks of web personalization and also informs practicing managers on how to develop recommender system strategies.
网络个性化摇摆效应的实验研究
网络口碑的多维性不仅提供了丰富的属性级信息,而且影响着网络消费者的属性偏好构建。虽然先前的研究证实,在非个性化的单一产品环境中,消费者评论会影响消费者的属性偏好评估,但在个性化的、多种可选择的环境中,消费者的行为可能完全不同,需要单独关注。基于信息加工方法和建构性偏好视角,我们的研究分析了个性化如何影响这种摇摆效应,即个性化对消费者属性偏好的影响。我们对非个性化信息(无个性化)、自我参考信息、相关信息、自我参考和相关信息四种不同类型的个性化进行了多组实验。我们的研究结果显示了个性化对消费者产品属性偏好的摇摆效应。我们发现,当用户接触到不同类型的个性化时,他们对产品属性偏好的摇摆效应程度是不同的。本研究对当前关于网络个性化受挫的论述做出了重大贡献,并为实践管理者提供了如何开发推荐系统策略的信息。
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来源期刊
Data Base for Advances in Information Systems
Data Base for Advances in Information Systems INFORMATION SCIENCE & LIBRARY SCIENCE-
CiteScore
3.60
自引率
7.10%
发文量
18
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