Social robot-delivered customer-facing services: an assessment of the experience

ABSTRACT

The ability to install social intelligence protocols in robots in order for them to exhibit conversational skills has made them ideal tools for delivering services with a high cognitive and low emotional load. Little is known about how this capability influences the customer experience and the intention to continue receiving these services. Experiences were assessed in a study simulating customer-facing service delivery, and the constructs of the technology readiness index and stated gender were analysed as possible moderators in a quasi-experiment. Hedonic quality was the most relevant factor explaining attitude, and attitude explained intention to use as well as social influence. As for the constructs of technological readiness and gender, optimism and innovativeness seem to be the most likely candidates for moderating the other variables. The most optimistic and the most innovative route would be for the main actors to continue adapting to social robot technology in the future.

摘要：

在机器人上安装社交智能文本协议，使得它们能展示对话技能，让机器人成为能带有高度认知和低度情感负荷的理想的服务提供工具。对于这种能力如何影响客户体验以及继续接受这些服务的意愿，人们知之甚少。我们的一项研究运用了准实验来模拟了面向客户的服务交付，对体验进行了分析，同时分析了二个可能的调节变量：技术准备度指数（technological readiness index）和声明的性别（stated gender）这二个构念。享乐品质（hedonic quality）是解释消费者态度的最相关因素，而态度解释了使用意图（intention to use）和社会影响（social influence）。至于技术准备度和声明的性别这二个构念，乐观（optimism）和创新度(innovativeness）似乎最有可能调节其他变量：最乐观和最创新的路线将使得服务提供者在将来继续接受社交机器人技术。

KEYWORDS:

• Customer-facing service
• social robot
• social intelligence protocols
• experience
• technology readiness index
• sex

关键词:

• 面向客户的服务，社交机器人，社交智能文本协议，体验，技术准备度指数，性别

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was partially funded by the European Union’s Horizon 2020 under ERC Advanced Grant CLOTHILDE (no. 741930); by MCIN/AEI/10.13039/501100011033 and by the ‘European Union NextGenerationEU/PRTR’ under the project ROB-IN (PLEC2021-007859); by the Research Council of Norway under the project SECUROPS (INT-NO/0875); and by the ‘European Union NextGenerationEU/PRTR’ through CSIC’s Thematic Platforms (PTI + Neuro-Aging); A. Andriella was supported by the European Union’s Horizon 2020 research and innovation programme PRO-CARED (no.801342) under Marie Skłodowska-Curie grant agreement (Tecniospring INDUSTRY) and the Government of Catalonia’s Agency for Business Competitiveness (ACCIÓ).