Purpose

The process of introducing a new robotic technology into a service system is complex, and its impacts on work practices can be challenging. By adopting a system perspective, this study investigates how human–robot collaboration (HRC) transforms work practices (i.e. customer care).

Design/methodology/approach

We conducted a two-year longitudinal analysis of an international company specializing in natural health products, examining changes in customer care practices following the introduction of chatbots. The study leverages expansive learning theory, which emphasizes activity systems and the transformations that occur within them, to trace the integration of robots and their effects on work practices.

Findings

The findings reveal that HRC enhances customer care practices by creating a human–robot activity system organized around shared goals. This system, mediated by tools, rules and the community, evolves through expansive learning dynamics. The process begins by identifying and addressing the contradictions and tensions between current human work practices and robotic capabilities, often revealing challenges and opportunities to improve HRC.

Originality/value

This research offers a novel conceptualization of the systemic and dynamic nature of HRC by placing it within broader frames of activity systems and expansive learning. Collaborations between humans and robots entail an expansive performativity that extends beyond the traditional roles or tasks of either actor or actant. It spans a diverse range of objects, tools, procedures and institutional setups, culminating in transformations of customer care practices.

中文翻译：

---

人机协作的系统和学习视角

 目的

将新的机器人技术引入服务系统的过程很复杂，其对工作实践的影响可能具有挑战性。通过采用系统视角，本研究调查了人机协作 （HRC） 如何改变工作实践（即客户服务）。

设计/方法/方法

我们对一家专门从事天然保健品的国际公司进行了为期两年的纵向分析，研究了引入聊天机器人后客户服务实践的变化。该研究利用广泛的学习理论（强调活动系统及其内部发生的转变）来追踪机器人的整合及其对工作实践的影响。

 发现

研究结果表明，HRC 通过创建围绕共同目标组织的人机活动系统来增强客户服务实践。这个系统由工具、规则和社区介导，通过广泛的学习动态而发展。该过程首先识别和解决当前人类工作实践与机器人能力之间的矛盾和紧张关系，通常会揭示改进 HRC 的挑战和机遇。

 原创性/价值

这项研究通过将 HRC 置于更广泛的活动系统和广泛学习框架中，为 HRC 的系统性和动态性质提供了一种新颖的概念。人类和机器人之间的合作需要一种广泛的表演性，超越了演员或演员的传统角色或任务。它涵盖各种对象、工具、程序和机构设置，最终导致客户服务实践的转变。