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嘿,机器人,直截了当地告诉我:不同的服务策略如何影响人机服务结果。

Hey Robot, Tell It to Me Straight: How Different Service Strategies Affect Human and Robot Service Outcomes.

作者信息

Naito Masaharu, Rea Daniel J, Kanda Takayuki

机构信息

Kyoto University, Kyoto, Japan.

University of New Brunswick, Fredericton, Canada.

出版信息

Int J Soc Robot. 2023 May 17:1-14. doi: 10.1007/s12369-023-01013-0.

Abstract

With robots already entering simple service tasks in shops, it is important to understand how robots should perform customer service to increase customer satisfaction. We investigate two methods of customer service we theorize are better suited for robots than human shopkeepers: straight communication and data-driven communication. Along with an additional, more traditional customer service style, we compare these methods of customer service performed by a robot, to a human performing the same service styles in 3 online studies with over 1300 people. We find that while traditional customer service styles are best suited for human shopkeepers, robot shopkeepers using straight or data driven customer service styles increase customer satisfaction, make customers feel more informed, and feel more natural than when a human uses them. Our work highlights the need for investigating robot-specific best practices for customer service, but also for social interaction at large, as simply duplicating typical human-human interaction may not produce the best results for a robot.

摘要

随着机器人已经开始在商店执行简单的服务任务,了解机器人应如何提供客户服务以提高客户满意度变得很重要。我们研究了两种我们认为比人类店主更适合机器人的客户服务方法:直接沟通和数据驱动的沟通。除了一种额外的、更传统的客户服务方式外,我们在三项针对1300多人的在线研究中,将机器人执行的这些客户服务方法与执行相同服务方式的人类进行了比较。我们发现,虽然传统的客户服务方式最适合人类店主,但使用直接或数据驱动客户服务方式的机器人店主能提高客户满意度,让客户感觉信息更丰富,并且比人类使用这些方式时感觉更自然。我们的工作强调了不仅要研究针对机器人的客户服务最佳实践的必要性,而且对于一般的社交互动也是如此,因为简单地复制典型的人与人之间的互动可能不会为机器人带来最佳效果。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4de8/10189699/554d56b3db1e/12369_2023_1013_Fig1_HTML.jpg

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