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Robots or frontline employees? Exploring customers’ attributions of responsibility and stability after service failure or success
Journal of Service Management ( IF 7.8 ) Pub Date : 2020-03-09 , DOI: 10.1108/josm-05-2019-0156
Daniel Belanche , Luis V. Casaló , Carlos Flavián , Jeroen Schepers

Service robots are taking over the organizational frontline. Despite a recent surge in studies on this topic, extant works are predominantly conceptual in nature. The purpose of this paper is to provide valuable empirical insights by building on the attribution theory.,Two vignette-based experimental studies were employed. Data were collected from US respondents who were randomly assigned to scenarios focusing on a hotel’s reception service and restaurant’s waiter service.,Results indicate that respondents make stronger attributions of responsibility for the service performance toward humans than toward robots, especially when a service failure occurs. Customers thus attribute responsibility to the firm rather than the frontline robot. Interestingly, the perceived stability of the performance is greater when the service is conducted by a robot than by an employee. This implies that customers expect employees to shape up after a poor service encounter but expect little improvement in robots’ performance over time.,Robots are perceived to be more representative of a firm than employees. To avoid harmful customer attributions, service providers should clearly communicate to customers that frontline robots pack sophisticated analytical, rather than simple mechanical, artificial intelligence technology that explicitly learns from service failures.,Customer responses to frontline robots have remained largely unexplored. This paper is the first to explore the attributions that customers make when they experience robots in the frontline.

中文翻译:

机器人还是一线员工?探索服务失败或成功后客户对责任和稳定性的归属

服务机器人正在接管组织的一线工作。尽管最近对此主题的研究激增,但现有作品本质上还是概念性的。本文的目的是在归因理论的基础上提供有价值的经验见解。进行了两项基于小插图的实验研究。数据是从美国受访者那里收集的,这些受访者被随机分配到针对酒店接待服务和餐厅服务生的情景中。结果表明,受访者对服务绩效的责任归因于人类而不是机器人,尤其是当服务故障发生时。因此,客户将责任归于公司而不是一线机器人。有趣的是 由机器人进行服务时,感觉到的性能稳定性要比员工来得好。这意味着客户期望员工在遇到糟糕的服务后能够重塑自己,但随着时间的推移,他们期望机器人的性能几乎没有改善。机器人被认为比员工更能代表企业。为避免有害的客户归属,服务提供商应与客户明确沟通,一线机器人采用复杂的分析技术,而不是从服务故障中明确学习的简单的机械,人工智能技术。客户对一线机器人的反应仍未开发。本文是第一个探讨客户在前线体验机器人时所做出的归因的方法。这意味着客户期望员工在遇到糟糕的服务后能够重塑自己,但随着时间的推移,他们期望机器人的性能几乎没有改善。机器人被认为比员工更能代表企业。为避免有害的客户归属,服务提供商应与客户明确沟通,一线机器人采用复杂的分析技术,而不是从服务故障中明确学习的简单的机械,人工智能技术。客户对一线机器人的反应仍未开发。本文是第一个探讨客户在前线体验机器人时所做出的归因的方法。这意味着客户期望员工在遇到糟糕的服务后能够重塑自己,但随着时间的推移,他们期望机器人的性能几乎没有改善。机器人被认为比员工更能代表企业。为避免有害的客户归属,服务提供商应与客户明确沟通,一线机器人采用复杂的分析技术,而不是从服务故障中明确学习的简单的机械,人工智能技术。客户对一线机器人的反应仍未开发。本文是第一个探讨客户在前线体验机器人时所做出的归因的方法。为避免有害的客户归属,服务提供商应与客户明确沟通,一线机器人采用复杂的分析技术,而不是从服务故障中明确学习的简单的机械,人工智能技术。客户对一线机器人的响应仍未开发。本文是第一个探讨客户在前线体验机器人时所做出的归因的方法。为避免有害的客户归属,服务提供商应与客户明确沟通,一线机器人采用复杂的分析技术,而不是从服务故障中明确学习的简单的机械,人工智能技术。客户对一线机器人的反应仍未开发。本文是第一个探讨客户在前线体验机器人时所做出的归因的方法。
更新日期:2020-03-09
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