E-commerce platforms often use collaborative filtering (CF) algorithms to recommend products to consumers. What recommendations consumers receive and how they respond to the recommendations largely depend on the design of CF algorithms. However, the extant empirical research on recommender systems has primarily focused on how the presence of recommendations affects product demand, without considering the underlying algorithm design. Leveraging a field experiment on a major e-commerce platform, we examine the differential impact of two widely used CF designs: view-also-view (VAV) and purchase-also-purchase (PAP). We found several striking differences between the impact of these two designs on individual products. First, VAV is about seven times more effective in generating additional product views than PAP but only about twice as effective in generating sales due to a lower conversion rate. Second, VAV is more effective in increasing views for more expensive products, whereas PAP is more effective in increasing the sales of cheaper products. Third, VAV is less effective in increasing the views but more effective in increasing the sales of products with higher purchase incidence rates (PIRs). Finally, when aggregated over all products with the same levels of price or PIRs, VAV dominates PAP in generating views and the difference is more striking for products with higher prices or lower PIRs. Interestingly, PAP is more effective than VAV in increasing the sales of products with low prices or moderate PIRs, though VAV generates more sales than PAP overall. Our findings suggest that platforms may benefit from employing different CF designs for different types of products.

中文翻译：

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关于基于视图和基于购买的推荐系统之间的差异

电子商务平台通常使用协同过滤 (CF) 算法向消费者推荐产品。消费者收到什么推荐以及他们如何回应这些推荐在很大程度上取决于 CF 算法的设计。然而，现有的推荐系统实证研究主要集中在推荐的存在如何影响产品需求，而没有考虑底层算法设计。利用在主要电子商务平台上进行的现场实验，我们检查了两种广泛使用的 CF 设计的不同影响：同时查看 (VAV) 和同时购买 (PAP)。我们发现这两种设计对个别产品的影响存在几个显着差异。第一的，VAV 在产生更多产品视图方面的效率大约是 PAP 的七倍，但由于转化率较低，在产生销售方面的效率仅为其两倍。其次，VAV 在增加更昂贵产品的浏览量方面更有效，而 PAP 在增加更便宜产品的销售方面更有效。第三，VAV 在增加浏览量方面效果较差，但在增加购买发生率 (PIR) 较高的产品的销量方面更有效。最后，当对具有相同价格或 PIR 水平的所有产品进行汇总时，VAV 在生成视图方面主导 PAP，并且对于价格较高或 PIR 较低的产品，差异更为显着。有趣的是，尽管 VAV 产生的销售额总体上高于 PAP，但 PAP 在增加低价或中等 PIR 产品的销量方面比 VAV 更有效。