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The influence of knowledge-based e-commerce product recommender agents on online consumer decision-making

机译:基于知识的电子商务产品推荐代理对在线消费者决策的影响

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摘要

Online retailers are providing a large amount of products over the Internet for potential customers. Given the opportunity of accessing vast amounts of products online, customers usually encounter difficulties to choose the right product or service for themselves. Obtaining advice from the Internet is both time consuming and most of the time unreliable. Therefore, some kind of intelligent software is needed to act on behalf of customers in such situations. Recommender agents are intelligent software providing easily accessible, high-quality recommendations for online consumers. They either track online customer behaviour implicitly or obtain information from the customer explicitly and provide the products or services in which the customer might be interested. By utilizing such systems, online retailers not only increase their sales but also assist their customers in finding the products or services they seek. This study assessed the influence of knowledge-based recommender agents on the online-consumer decision-making process. Shopping duration, purchase of desired item, effort spent in searching for the desired product and the decision quality of online consumers were assessed by exposing the participants to a knowledge-based recommender system which has been integrated into one of the online shopping systems developed in the scope of this study. Only objective measures have been utilized in this research; that is, shopping system log data has been used to measure the influence of recommender agents on the consumer decision-making process. Study findings have shown that knowledge-based recommender agents improve the consumer decision-making process by reducing the shopping duration and effort spent in searching for suitable products. Also, it was found that decision quality and the number of consumers who purchase the desired item increase with their use of such systems. The results of this study provide additional proof of the potential benefits of integrating such systems into online web stores.
机译:在线零售商正在通过Internet为潜在客户提供大量产品。如果有机会在线访问大量产品,则客户通常会遇到困难,无法为自己选择合适的产品或服务。从Internet获得建议既耗时又大部分时间不可靠。因此,在这种情况下,需要某种智能软件来代表客户。推荐代理是智能软件,可为在线消费者提供易于访问的高质量建议。他们要么隐式跟踪在线客户的行为,要么明确地从客户那里获取信息,并提供客户可能感兴趣的产品或服务。通过使用这样的系统,在线零售商不仅增加了他们的销售额,而且还帮助他们的客户找到他们想要的产品或服务。这项研究评估了基于知识的推荐代理对在线消费者决策过程的影响。通过将参与者暴露于基于知识的推荐系统,评估购物持续时间,购买所需商品,花费在搜索所需产品上的努力以及在线消费者的决策质量,这些系统已集成到基于知识的推荐系统中,该系统已开发成一个在线购物系统。研究范围。在这项研究中只采用了客观的措施;也就是说,购物系统日志数据已用于衡量推荐代理商对消费者决策过程的影响。研究发现表明,基于知识的推荐代理商可以通过减少购物时间和减少寻找合适产品所花费的精力来改善消费者的决策过程。而且,发现随着使用这种系统,决策质量和购买所需物品的消费者数量增加。这项研究的结果进一步证明了将此类系统集成到在线Web商店中的潜在好处。

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