Examining the Impact of Ranking on Consumer Behavior and Search Engine Revenue
Examining the Impact of Ranking on Consumer Behavior and Search Engine Revenue
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DOI：
10.1287/mnsc.2013.1828
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发表时间：
2014-07-01
影响因子：
5.4
通讯作者：
Li, Beibei
中科院分区：
文献类型：
--
作者：
Ghose, Anindya;Ipeirotis, Panagiotis G.;Li, Beibei
本文研究了三种不同类型的搜索引擎排名对消费者行为和搜索引擎收入的影响：直接排名效应、排名与产品排名的交互效应和个性化排名效应。我们结合联合收割机的分层贝叶斯模型估计约一百万在线会话从Travelocity，以及随机实验，使用现实世界的酒店搜索引擎应用程序。我们的档案数据分析和随机实验是一致的，证明了以下几点：（1）基于消费者效用的排名机制可以导致整体搜索引擎收入的显着增加。(2)搜索引擎排名和产品评级之间存在显著的相互作用。在搜索引擎上的劣势地位对“高级”酒店的影响更大。另一方面，客户评分较低的酒店更有可能从被置于屏幕顶部中受益。这些发现表明，产品搜索引擎可以从直接将社交媒体信号纳入其排名算法中获益。(3)我们的随机实验还表明，一个“主动”的个性化排名系统（其中用户可以与排名算法进行交互和自定义）导致更高的点击，但较低的购买倾向和较低的搜索引擎收入相比，“被动”的个性化排名系统（其中用户不能与排名算法进行交互）。这一结果表明，在决策过程中提供更多的信息可能会导致更少的消费者购买，因为信息过载。因此，产品搜索引擎不应默认采用个性化排名系统。总的来说，我们的研究揭示了排名的经济影响及其与社交媒体对产品搜索引擎的相互作用。
In this paper, we study the effects of three different kinds of search engine rankings on consumer behavior and search engine revenues: direct ranking effect, interaction effect between ranking and product ratings, and personalized ranking effect. We combine a hierarchical Bayesian model estimated on approximately one million online sessions from Travelocity, together with randomized experiments using a real-world hotel search engine application. Our archival data analysis and randomized experiments are consistent in demonstrating the following: (1) A consumer-utility-based ranking mechanism can lead to a significant increase in overall search engine revenue. (2) Significant interplay occurs between search engine ranking and product ratings. An inferior position on the search engine affects "higher-class" hotels more adversely. On the other hand, hotels with a lower customer rating are more likely to benefit from being placed on the top of the screen. These findings illustrate that product search engines could benefit from directly incorporating signals from social media into their ranking algorithms. (3) Our randomized experiments also reveal that an "active" personalized ranking system (wherein users can interact with and customize the ranking algorithm) leads to higher clicks but lower purchase propensities and lower search engine revenue compared with a "passive" personalized ranking system (wherein users cannot interact with the ranking algorithm). This result suggests that providing more information during the decision-making process may lead to fewer consumer purchases because of information overload. Therefore, product search engines should not adopt personalized ranking systems by default. Overall, our study unravels the economic impact of ranking and its interaction with social media on product search engines.