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Effects of Online Recommendations on Consumers' Willingness to Pay

机译:在线推荐对消费者支付意愿的影响

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摘要

Recommender systems are an integral part of the online retail environment. Prior research has focused largely on computational approaches to improving recommendation accuracy, and only recently researchers have started to study their behavioral implications and potential side effects. We used three controlled experiments, in the context of purchasing digital songs, to explore the willingness-to-pay judgments of individual consumers after being shown personalized recommendations. In Study 1, we found strong evidence that randomly assigned song recommendations affected participants' willingness to pay, even when controlling for participants' preferences and demographics. In Study 2, participants viewed actual system-generated recommendations that were intentionally perturbed ( introducing recommendation error), and we observed similar effects. In Study 3, we showed that the influence of personalized recommendations on willingness-to-pay judgments was obtained even when preference uncertainty was reduced through immediate and mandatory song sampling prior to pricing. The results demonstrate the existence of important economic side effects of personalized recommender systems and inform our understanding of how system recommendations can influence our everyday preference judgments. The findings have significant implications for the design and application of recommender systems as well as for online retail practices.
机译:推荐系统是在线零售环境的组成部分。先前的研究主要集中在提高推荐准确性的计算方法上,只有最近的研究人员才开始研究其行为含义和潜在的副作用。在购买数字歌曲的过程中,我们使用了三个受控实验,以在向其显示个性化推荐后,探索单个消费者的支付意愿判断。在研究1中,我们发现有力的证据表明,即使控制参与者的喜好和人口统计信息,随机分配的歌曲推荐也会影响参与者的支付意愿。在研究2中,参与者查看了系统生成的实际建议,这些建议被有意地打扰了(引入了建议错误),并且我们观察到了相似的效果。在研究3中,我们表明,即使在定价之前通过立即和强制歌曲采样减少了偏好不确定性,也获得了个性化推荐对付费意愿判断的影响。结果证明了个性化推荐系统的重要经济副作用的存在,并使我们了解系统推荐如何影响我们的日常偏好判断。这些发现对推荐系统的设计和应用以及在线零售实践都具有重要意义。

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