嘿,机器人,直接告诉我:不同的服务策略如何影响人类和机器人的服务结果。

IF 3.8 2区 计算机科学 Q2 ROBOTICS International Journal of Social Robotics Pub Date : 2023-05-17 DOI:10.1007/s12369-023-01013-0
Masaharu Naito, Daniel J Rea, Takayuki Kanda
{"title":"嘿,机器人,直接告诉我:不同的服务策略如何影响人类和机器人的服务结果。","authors":"Masaharu Naito,&nbsp;Daniel J Rea,&nbsp;Takayuki Kanda","doi":"10.1007/s12369-023-01013-0","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":14361,"journal":{"name":"International Journal of Social Robotics","volume":" ","pages":"1-14"},"PeriodicalIF":3.8000,"publicationDate":"2023-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10189699/pdf/","citationCount":"2","resultStr":"{\"title\":\"Hey Robot, Tell It to Me Straight: How Different Service Strategies Affect Human and Robot Service Outcomes.\",\"authors\":\"Masaharu Naito,&nbsp;Daniel J Rea,&nbsp;Takayuki Kanda\",\"doi\":\"10.1007/s12369-023-01013-0\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>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.</p>\",\"PeriodicalId\":14361,\"journal\":{\"name\":\"International Journal of Social Robotics\",\"volume\":\" \",\"pages\":\"1-14\"},\"PeriodicalIF\":3.8000,\"publicationDate\":\"2023-05-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10189699/pdf/\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Social Robotics\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.1007/s12369-023-01013-0\",\"RegionNum\":2,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ROBOTICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Social Robotics","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1007/s12369-023-01013-0","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ROBOTICS","Score":null,"Total":0}
引用次数: 2

摘要

随着机器人已经进入商店的简单服务任务,了解机器人应该如何执行客户服务以提高客户满意度是很重要的。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沟通。除了一种额外的、更传统的客户服务方式外,我们在3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人类执行相同服务方式进行了比较。我们发现,虽然传统的客服风格最适合人类店主,但机器人店主使用直接或数据驱动的客服风格可以提高客户满意度,让客户感觉更知情,比人类使用它们时感觉更自然。我们的工作强调了研究特定于机器人的客户服务最佳实践的必要性,同时也研究了整个社会互动的最佳实践,因为简单地复制典型的人机互动可能不会为机器人带来最佳结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

摘要图片

摘要图片

摘要图片

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Hey Robot, Tell It to Me Straight: How Different Service Strategies Affect Human and Robot Service Outcomes.

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.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
9.80
自引率
8.50%
发文量
95
期刊介绍: Social Robotics is the study of robots that are able to interact and communicate among themselves, with humans, and with the environment, within the social and cultural structure attached to its role. The journal covers a broad spectrum of topics related to the latest technologies, new research results and developments in the area of social robotics on all levels, from developments in core enabling technologies to system integration, aesthetic design, applications and social implications. It provides a platform for like-minded researchers to present their findings and latest developments in social robotics, covering relevant advances in engineering, computing, arts and social sciences. The journal publishes original, peer reviewed articles and contributions on innovative ideas and concepts, new discoveries and improvements, as well as novel applications, by leading researchers and developers regarding the latest fundamental advances in the core technologies that form the backbone of social robotics, distinguished developmental projects in the area, as well as seminal works in aesthetic design, ethics and philosophy, studies on social impact and influence, pertaining to social robotics.
期刊最新文献
Immersive Commodity Telepresence with the AVATRINA Robot Avatar The Effects of Robot Managers’ Reward-Punishment Behaviours on Human–Robot Trust and Job Performance When is Human–Robot Joint Agency Effective? The Case of Cooperative Reaction Games Does Cultural Robotics Need Culture? Conceptual Fragmentation and the Problems of Merging Culture with Robot Design Observing the Interaction between a Socially-Assistive Robot and Residents in a Nursing Home
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1