ABSTRACT Most previous studies about online product recommendation sources (recommendation agents [RAs], consumers, and experts) have been limited to the evaluation by a single source on a website. Thus, the relative influence of convergent recommendations from different sources on consumers’ acceptance of the advice remains largely unknown. We draw upon and extend the product uncertainty model to theorize how the convergence of recommendations from various sources differentially influences customers’ acceptance of recommendations. Our experiments show that the recommendation convergence between RAs and experts leads to the greater recommendation acceptance of the jointly recommended products than the convergence between experts and consumers or convergence between RAs and consumers. The rationale is that RAs best reduce fit uncertainty, and experts best reduce description and performance uncertainties. Experts and RAs complement each other by reducing all three dimensions of product uncertainty. Online merchants are advised to incorporate multiple sources into their websites, including sources (i.e., RAs and experts) that play complementary roles in reducing product uncertainty.

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来自各种在线来源的产品推荐收敛的相对影响

摘要 以前关于在线产品推荐源（推荐代理 [RA]、消费者和专家）的大多数研究仅限于由网站上的单一来源进行评估。因此，来自不同来源的趋同推荐对消费者接受建议的相对影响在很大程度上仍然未知。我们利用并扩展了产品不确定性模型来理论化来自各种来源的推荐的融合如何不同地影响客户对推荐的接受。我们的实验表明，与专家和消费者之间的融合或 RA 和消费者之间的融合相比，RA 和专家之间的推荐收敛导致对联合推荐产品的推荐接受度更高。基本原理是 RA 最好地减少拟合不确定性，专家最好减少描述和性能的不确定性。通过减少产品不确定性的所有三个维度，专家和 RA 相辅相成。建议在线商家将多种来源纳入其网站，包括在降低产品不确定性方面发挥互补作用的来源（即 RA 和专家）。