Understanding online reviews adoption in social network communities: an extension of the information adoption model

Zheshi Bao, Yun Zhu
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Abstract

PurposeOnline reviews derived from peer communications have been increasingly viewed as an important approach for consumers to gather pre-purchase information. This study aims to examine factors affecting online reviews adoption in social network communities and then indicates the underlying mechanism of this process based on an extended information adoption model (IAM).Design/methodology/approachUsing the data collected from 242 users of a social network community via an online survey, the proposed model is empirically assessed by partial least squares-based structural equation model (PLS-SEM).FindingsThe results show that both perceived diagnosticity and perceived serendipity are drivers of online reviews adoption in social network communities. Meanwhile, community identification is not only an antecedent of diagnosticity and serendipity perceived by community members, but also motivates source credibility which, in turn, positively influences argument quality. Finally, the importance of argument quality and source credibility in reviews adoption process is also presented.Originality/valueThis study extends the IAM and enriches the literature regarding online reviews adoption. It deepens the understanding of serendipitous experiences and community identification in social networking context by addressing their important roles in the authors' extended IAM.
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理解社交网络社区的在线评论采纳:信息采纳模型的扩展
目的:来自同行交流的在线评论越来越被视为消费者收集购买前信息的重要途径。本研究旨在探讨影响社交网络社区在线评论采纳的因素,并基于扩展信息采纳模型(IAM)揭示这一过程的潜在机制。设计/方法/方法利用从242名社交网络社区用户中收集的在线调查数据,采用基于偏最小二乘的结构方程模型(PLS-SEM)对所提出的模型进行了实证评估。研究结果表明,感知诊断性和感知意外发现性都是社交网络社区采用在线评论的驱动因素。同时,社区认同不仅是社区成员感知到的诊断性和偶然性的先决条件,而且还会激发来源可信度,从而对论点质量产生积极影响。最后,论述了论点质量和来源可信度在评论采纳过程中的重要性。原创性/价值本研究扩展了IAM,丰富了关于在线评论采用的文献。它通过在作者的扩展IAM中解决偶然体验和社区识别的重要角色,加深了对社交网络背景下偶然体验和社区识别的理解。
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